Reviewer #1 (Public review):

I enjoyed reading this long but compelling account of the new (generalised) version of the Hierarchical Gaussian filter (HGF). Effectively, it describes an extension of the HGF to accommodate the influence of latent states on volatility - and vice versa. This paper describes a generalisation that has been made available to the community via the TAPAS software. This contribution will be of special interest to people in computational psychiatry, where the application of the HGF has been the most prevalent.

I thought the background, motivation, description and illustration of the scheme were excellent. The paper is rather long; however, it serves as a useful technical reference.

There are two issues that I think the authors need to address.

(1) The first is the failure to properly relate the current scheme to standard implementations of Bayesian filtering under hierarchical state-space models.

(2) The second is that whilst the paper is well-written, some of the mathematical notation is cluttered. Furthermore, I think that the authors need to motivate the otherwise overengineered description of the requisite variational message passing and decomposition into update steps.

I think that the authors can address both of these issues by including a technical section in the introduction, relating the HGF to state-of-the-art in the broader field of Bayesian filtering and predictive coding. They can then explain the benefits of the particular generative model - to which the HGF is committed - by drilling down on the update scheme and its implementation in the remainder of the paper.

I was underwhelmed by the account of predictive coding and its relationship to Bayesian filtering. I think that the authors should suppress the references to predictive coding in the recent machine learning literature. Rather, the presented narrative should emphasise the fact that predictive coding and Bayesian filtering are the same thing. The authors could then explain where the hierarchical Gaussian filter fits within Bayesian filtering and why its particular form lends itself to the variational updates they subsequently derive.

The authors could add something like the following to the introduction (accompanying PDF has the equations). There is a summary of what follows in the Wikipedia entry on generalised filtering, in particular, its relationship to predictive coding (https://en.wikipedia.org/wiki/Generalized_filtering).

Relationship to Existing Work

Technically, the hierarchical Gaussian filter is a Bayesian filter under a hierarchical state-space model. The most general form of these models can be expressed as stochastic differential or difference equations as follows, c.f., Equation 9 in (Feldman and Friston, 2010):

This functional form implies a hierarchical decomposition into hierarchical levels (l) that are linked through latent causes (v), with dynamics among latent states (x) at each level. From the perspective of the HGF, the state-dependency of state (z) and observation (e) noise at each level is a key feature. The variance (i.e., inverse precision) of the random fluctuations z is known as volatility, which - in a hierarchical setting - can depend upon latent causes and states at higher levels. The variational inversion of these models - sometimes called variational or generalised filtering - finds a number of important applications: a key example here is dynamic causal modelling, typically in the analysis of imaging timeseries. In this setting, unknown or latent states, parameters and precisions are updated in variational steps by minimising variational free energy (a variational bound on negative log marginal likelihood).

In engineering, the simplest form of generalised filtering is known as a Kalman filter, in which all the equations are linear, and volatility is assumed to be constant. In neurobiology, there is an intimate relationship between generalised filtering and predictive coding: predictive coding was originally introduced for timeseries analysis and compression of sound files (Elias, 1955). Subsequently, the implicit filtering or compression scheme was considered as a description of neuronal processing in the retina (Srinivasan et al., 1982) and then cortical hierarchies (Mumford, 1992; Rao, 1999; Rao and Ballard, 1999). The formal equivalence between predictive coding and Kalman filtering was noted in (Rao, 1999). Kalman filtering itself was then recognised as a special case of generalised filtering that could be read as predictive coding in the brain (Friston and Kiebel, 2009). The estimation of precision in these predictive coding schemes has been associated with endogenous (Feldman and Friston, 2010) and exogenous (Kanai et al., 2015) attention; i.e., with and without state dependency, respectively. Subsequently, precision estimation or uncertainty quantification has become a key focus in computational psychiatry.

In machine learning, there have been recent attempts to implement predictive coding via the minimisation of variational free energy under generative models with the functional form of conventional neural networks: e.g., (Millidge et al., 2022; Salvatori et al., 2022). However, much of this work is nascent and does not deal with dynamics or volatility. There is an interesting exception in machine learning, namely, transformer architectures, where the attention heads can be read as implementing a form of Kalman gain, namely, estimating state-dependent precision, e.g., (Buckley and Singh, 2024).

Within this general setting, the HGF emphasises the importance of precision estimation or uncertainty quantification by committing to a particular functional form for the generative model that can be summarised as follows:

"We will unpack this form below and show how it leads to a remarkably compact and efficient Bayesian belief updating scheme. We will appeal implicitly to variational message passing on factor graphs (Dauwels, 2007; Friston et al., 2017; Winn and Bishop, 2005) to decompose message passing between nodes and, crucially, within-node computations. These computations furnish a scalable and flexible form of generalised Bayesian filtering. In principle, this scheme inherits all the biological plausibility of belief propagation and variational message passing in cortical hierarchies (Friston et al., 2017)."

It might be worth the authors [re-]reading the abstracts of the above papers, for a clearer sense of how those in computational neuroscience and state-space modelling (but not machine learning) think about predictive coding and its relationship to Bayesian filtering. They could then go through the manuscript, nuancing your discussion of the intimate relationship between variational Bayes, generalised filtering, predictive coding and hierarchical Gaussian filtering.

Reviewer #1 (Public review):

Summary:

In the ecological interactions between wild plants and specialized herbivorous insects, structural innovation-based diversification of secondary metabolites often occurs. In this study, Agrawal et al. utilized two milkweed species (Asclepias curassavica and Asclepias incarnata) and the specialist Monarch butterfly (Danaus plexippus) as a model system to investigate the effects of two N,S-cardenolides-formed through structural diversification and innovation in A. curassavica-on the growth, feeding, and chemical sequestration of D. plexippus, compared to other conventional cardenolides. Additionally, the study examined how cardenolide diversification resulting from the formation of N,S-cardenolides influences the growth and sequestration of D. plexippus. On this basis, the research elucidates the ecophysiological impact of toxin diversity in wild plants on the detoxification and transport mechanisms of highly adapted herbivores.

Strengths:

The study is characterized by the use of milkweed plants and the specialist Monarch butterfly, which represent a well-established model in chemical ecology research. On one hand, these two organisms have undergone extensive co-evolutionary interactions; on the other hand, the butterfly has developed a remarkable capacity for toxin sequestration. The authors, building upon their substantial prior research in this field and earlier observations of structural evolutionary innovation in cardenolides in A. curassavica, proposed two novel ecological hypotheses. While experimentally validating these hypotheses, they introduced the intriguing concept of a "non-additive diversity effect" of trace plant secondary metabolites when mixed-contrasting with traditional synergistic perspectives-in their impact on herbivores.

Weaknesses:

The manuscript has two main weaknesses. First, as a study reliant on the control of compound concentrations, the authors did not provide sufficient or persuasive justification for their selection of the natural proportions (and concentrations) of cardenolides. The ratios of these compounds likely vary significantly across different environmental conditions, developmental stages, pre- and post-herbivory, and different plant tissues. The ecological relevance of the "natural proportions" emphasized by the authors remains questionable. Furthermore, the same compound may even exert different effects on herbivorous insects at different concentrations. The authors should address this issue in detail within the Introduction, Methods, or Discussion sections.

Second, the study was conducted using leaf discs in an in vitro setting, which may not accurately reflect the responses of Monarch butterflies on living plants. This limitation undermines the foundation for the novel ecological theory proposed by the authors. If the observed phenomena could be validated using specifically engineered plant lines-such as those created through gene editing, knockdown, or overexpression of key enzymes involved in the synthesis of specific N,S-cardenolides-the findings would be substantially more compelling.

Joint Public review:

Summary

Riva et al. introduce a semi-automatic setup for measuring Drosophila melanogaster oviposition rhythms and use it to map the timekeeping function underlying egg laying rhythms to a subset of clock cells. Using a combination of neurogenetic manipulations and referencing the publicly available female hemi-brain connectome dataset, they narrow the critical circuit down to possibly two of the three CRYPTOCHROME expressing lateral-dorsal neurons (LNds). Their findings suggest that different overlapping sets of clock neurons may control different behavioral rhythms in D. melanogaster.

This work will be of interest to researchers interested in the circadian regulation of oviposition in D. melanogaster (and possibly other insects), a phenomenon which has been left relatively under-explored. The construction of a semi-automated setup which can be made relatively cheaply using available motors and 3D printed molds provides a useful model for obtaining longer records of oviposition activity. The analysis of noisy oviposition timeseries, however, may require revisiting both the methods used for sampling eggs laid per female as well as the analytical tools used to clean up and analyze individual records, because simple averaging can lead to incorrect conclusions regarding the underlying nature of the rhythm.

Strengths

Additional experiments were carried out for this revised version of the manuscript that strengthen their original findings. These include: using a dominant negative form of the circadian clock gene, cycle, to disrupt the circadian clock, which provides additional support for the role of CRY+ LNds in generating the circadian rhythm of oviposition; reassessing the functionality of PDF neurons and showing that they seem to be important for maintaining the circadian period of egg laying; using the per01 mutation to show the role of period locus function in the control of the circadian rhythm of oviposition. The authors also point to some potentially interesting connectome data that suggest hypotheses regarding the neuronal circuit linking daily timekeeping to oviposition, which will require further validation in future studies. The videos and pictures demonstrate the working of the semi-automated egg collection setup, which should help others create similar devices.

Weaknesses:

The major weaknesses of this work result from the noisy nature of the data.

They include:

(1) Problems associated with averaging: The authors intended to focus on the oviposition clock in individual females, however due to the inherent noise in the oviposition rhythm they had to resort to averaging across Lomb-Scargle periodograms generated from individual time-series. They then tested whether the averaged periodogram contains a significant frequency. However, this reduction in noise also reduces the ability to compare differences in power of the rhythm across individuals. Furthermore, this method makes it especially difficult to distinguish the contribution of subsets of the circuit on the proportion of rhythmic flies and the power of the rhythm. In this revised version the authors use two manipulations to disrupt the molecular clock, which could have different success rates based on the type and number of cells targeted. Unfortunately, the type of averaging used prevents the detection of any such effects. It is to be noted that, indeed, individual-level differences in period between the PdfDicer-Gal4 > perRNAi and UAS-perRNAi lines help the authors to establish that there is a significant reduction in period length when the molecular clock is abolished in PDF cells. These individual measurements are now very helpful in discerning the effect of manipulations carried out on different circadian neural subsets, some of which could have been missed if only averages were considered.

(2) Sensitivity to sample size: Averaging reduces the effect of random background noise but noise reduction is dependent upon sample size. Comparing genotypes with different sample sizes in addition to varying signal to noise ratios (which might also change with neural manipulations) makes it difficult to estimate how much of the rhythm structure is contributed by a given neuronal subset; thus, whenever possible comparisons should be made between groups that include similar number of flies. This problem is compounded when the averaged periodogram is composed of both rhythmic and weakly rhythmic individuals. For instance, in the main text the reported value of period length of pdfDicer-Gal4 > perRNAi is 20.74h (see also Fig 2J) but in the Supplementary figure 2S1 this is close to 22h, while the values reported for the control are largely similar (24.35h in Fig 2H versus ~24h in Fig 2S1). A difference of 3.6h between control and experimental flies is much greater than 2h. Which estimate (average versus individual) is more reliable in predicting the behavior of these flies is difficult to determine without further experiments.

(3) Based on the newly provided data for individual fly periodograms the reader can visually evaluate the rhythmicity associated with each genotype. Such visual inspection did not reveal any clear difference between the proportion of rhythmic individuals between experimental and parental GAL4 and/or UAS controls, except for experiments using per01 mutant animals. This is surprising since if these circuits are controlling the oviposition rhythm, perturbing them should affect most individuals in a similar way.

In summary, although the authors have implicated CRY+ LNds in the generation of a circadian rhythm in oviposition it is not clear looking at individual readouts if this manipulation is rendering flies arrhythmic or changing the period of the clock slightly, such that there is increased variation in period length at the individual level which is not being captured by the low signal to noise ratio and in the average gives a flattened output as a result. Thus, while the manipulations done to the clock in these neurons might indeed affect the circadian nature of the oviposition rhythm it is still rather difficult to determine if they are indeed the sole clock cells generating this rhythm especially when nearby PDF+ cells also affect period length. Nevertheless, the connectomic data do show that they are very close to the OviIN neurons, placing them at an important juncture of transmitting circadian time information to the downstream oviposition circuit. Overall, the authors have achieved some of their aims, although the analysis methods leave some of their inferences open to speculation.

Other comments

Disrupting the clock in the 5th sLNv and 3 Cry+ LNds (and weakly in a small subset of DN1) affected egg-laying. Although the work emphasizes the importance of the LNd, the role of the 5th sLNv's role should be discussed.

Reviewer #1 (Public review):

Summary:

In this study, Li et al. used genetically engineered murine intestinal organoids to investigate how the temporal order of oncogenic mutations influences cell state and tumourigenicity of colorectal epithelial cells. By sequentially introducing Apc and Trp53 loss-of-function mutations in alternate orders within a Kras^G12D background, the authors generated isogenic organoid lines for both in vitro and in vivo characterisation. Bulk RNA-seq reveals expected transcriptional changes with relatively modest differences between the two triple-mutant configurations (KAT vs KTA). The key finding emerges from transplantation assays: while KAT and KTA organoids show equivalent tumourigenic potential in immunodeficient mice, only KAT organoids form tumours in immunocompetent hosts (5/10 vs 0/10), suggesting that mutation order shapes susceptibility to immune-mediated clearance. The experiments are well-executed, and the conclusions are generally supported by the data.

Strengths:

The experimental system is well-designed for the question. By combining a Kras^G12D transgenic background with sequential CRISPR-mediated knockout of Apc and Trp53 in alternate orders, the authors generated truly isogenic organoid lines that differ only in mutational sequence. This is technically non-trivial and provides a clean platform for dissecting order effects, a question otherwise difficult to address experimentally.

The authors performed comprehensive baseline characterisation of these organoids, including morphological and histological assessment, quantification of organoid-forming efficiency and proliferation, and bulk RNA-seq profiling. While these analyses revealed no major differences between KAT and KTA organoids, and the observed enhancement of epithelial stemness upon Apc loss and proliferative advantage conferred by Trp53 loss are largely expected, the systematic nature of this characterisation establishes a useful methodological template for future organoid-based studies.

The authors further investigated the functional impact of mutational order using subcutaneous transplantation assays. By comparing tumour formation in immunodeficient versus immunocompetent hosts, the authors uncover a genuinely unexpected finding: KAT and KTA organoids behave equivalently in the absence of adaptive immunity, but diverge dramatically when immune pressure is applied (KAT: 5/10; KTA: 0/10). This observation is arguably the most compelling aspect of the study and opens an interesting line of inquiry.

Weaknesses:

The authors acknowledge that initiating with Kras^G12D does not reflect the typical human sporadic CRC trajectory, where APC loss is usually the first event. While this design choice was pragmatic, it means the observed order effects are contextualised within an artificial starting point. It remains unclear whether the Apc/Trp53 order would matter in a Kras-wild-type background, or whether the Kras-driven cellular state is a prerequisite for these phenotypes to emerge.

Subcutaneous implantation provides a tractable readout of tumourigenicity, but the cutaneous immune microenvironment differs substantially from that of the intestinal mucosa. Given that the central claim concerns immune-mediated selection, orthotopic transplantation would more directly test whether the observed order effects hold in a physiologically relevant context.

The ssGSEA comparison involves only 14 ATK tumours, and the key comparisons (Figure 6E) yield borderline significance (p=0.052). More fundamentally, since mutation order cannot be inferred from the clinical samples, the authors are correlating organoid-derived IFN signatures with tumour immunophenotypes without direct evidence that these patients' tumours followed a KAT-like trajectory. The reasoning becomes circular: KAT organoids define the signature used to identify KAT-like clinical tumours.

Furthermore, the most striking finding of the study, that KTA organoids fail to form tumours in immunocompetent hosts while KAT organoids can, lacks a mechanistic follow-up. The transcriptomic differences between KAT and KTA are modest when cultured as monocultures, yet their in vivo fates diverge dramatically. The authors do not address why these subtle intrinsic differences translate into such divergent immune susceptibility, nor do they characterise the immune response adequately (beyond limited CD4/CD8 IHC at tumour peripheries).

Reviewer #1 (Public review):

This manuscript reports on the behavior of participants playing a game to measure exploration. Specifically, participants completed a task with blocks of exploratory choices (choosing between two 'tables', and within each table, two 'card decks', each of which had a specific probability of showing cards with one color versus another) and test choices, where participants were asked to choose which of the two decks per table had a higher likelihood of one color. Blocks differed on how long (how many trials) the exploration phase lasted. Participants' choices were fit to increasingly complex models of next-trial exploration. Participants' choices were best fit by an intermediate model where the difference in uncertainty between tables influenced the choice. Next, the authors investigated factors affecting whether participants sought out or avoided uncertainty, their choice reaction times, and the relationship of these measures with performance during the test phase of each block. Participants were uncertainty-seeking (exploratory) under most levels of overall uncertainty but became less uncertainty-seeking at high levels of total uncertainty. Participants with a stronger tendency to approach uncertainty at lower levels of total uncertainty were more accurate in the test phase, while the tendency to avoid uncertainty when total uncertainty was high was also weakly positively related to test accuracy. In terms of reaction times, participants whose reaction times were more related to the level of uncertainty, and who deliberated longer, performed better. The individual tendency to repeat choices was related to avoidance of uncertainty under high total uncertainty and better test performance. Lastly, choices made after a longer lag were less affected by these measures.

Reviewer #1 (Public review):

Summary:

Pierre Despas et al. studied the role of Salmonella typhimurium LppB in outer membrane tethering. Using E. coli {delta}lpp mutant the authors showed that Salmonella LppB is covalently attached to PG through K58 and that these crosslinks are formed by the L,D-transpeptidase LdtB, primarily. Additionally, authors demonstrate that LppB forms homodimers via a disulfide bond through C57, but when Lpp is present it can also form heterotrimers with it. Thus, suggesting a regulatory role in Lpp-PG crosslinking.

Strengths:

In my view, this is a nice piece of work that expands our understanding of the role of lpp homologs. The experiments were well-designed and executed, the manuscript is well-written and the figures are well-presented.

Weaknesses:

I have some suggestions to give a clearer message, because I think a few images don't reflect much of what the authors wrote.

It'd be helpful for readers to see the phylogenetic tree of the rest of the organisms that harbor LppB homologs and Lpp.

Increased expression of LppB under low pH is subtle. This result would benefit from quantifying the blots (Fig. S1) and performing statistical analysis.

Similarly, the SDS-EDTA sensitivity result (Fig. S2) is not convincing; the image doesn't seem to show isolated colonies at low pH (Fig. S2B). Please measure CFU/mL and report endpoint growth graphs instead. Statistical analysis should also be presented.

The reduction to PG crosslinking of the C57R mutant is unclear (Fig 4B lane 22). The authors state: "suggesting that additional features of the LppB C-terminal region underlie its reduced efficiency." Does this mean additional amino acids play a role? Did the authors try to substitute Cys with other amino acid residues like Ala or Ser and quantify protein levels to find a mutant with similar expression levels? Do these have less crosslinking too?

Reviewer #1 (Public review):

Foucault and colleagues examine how people's belief updating in a predictive inference task depends on qualitative differences in generative structure, in particular focusing on two generative structures frequently employed in learning and belief updating tasks (changepoints and random walks). While behavior and normative predictions for these structures have been explored many times in different tasks and settings, these exact structures have, to the best of my knowledge, never been explored in the same study and modeling framework for direct comparison. The authors use ideal observer models coupled with a response bias module to make predictions for what structure-appropriate adaptive learning would look like across the two conditions, then they ran an experiment to test behavioral predictions for the two structures under different levels of stochasticity. The authors present evidence that stochasticity changes in learning for two qualitatively different reasons, and that depending on which of these factors dominate, can have different effects on learning. They show that human participants showed qualitative trends consistent with adjusting their structural assumptions of the task to guide learning and adjusting their assessments of stochasticity.

The experiment was well designed and executed, and the paper was well written. The findings from the study are largely consistent with other work in the field, but there are a few advances that go beyond previously established findings, most notably a nuanced examination of how stochasticity affects learning behavior, which has the potential to provide an explanation for a notable discrepancy in the field (Pulco and Browning 2025; Piray and Daw 2024). The paper has notable strengths in its use of computational models to generate qualitative predictions that are evaluated in empirical behavioral data.

The current paper has a few weaknesses. It makes strong claims regarding the impacts of stochasticity on optimal learning that were difficult to evaluate, given a lack of clarity on the exact modeling that was implemented and incompletely supported by the existing analysis. The paper also lacks statistical support for some of its claims and evaluates models only through their ability to reproduce summary measures, rather than through direct model fitting.

Reviewer #1 (Public review):

Summary:

In this study, the authors aim to characterize how moment-to-moment fluctuations in arousal during wakefulness shape large-scale functional brain connectivity. Using pupil diameter as an index of arousal and high-field functional imaging, they seek to determine whether arousal-related modulation of connectivity is uniform across the brain or organized into structured patterns, and whether such patterns show hemispheric asymmetry. The work further aims to assess whether these organizational features generalize across resting-state and naturalistic viewing conditions.

Strengths:

The study addresses an important and timely question regarding how spontaneous variations in arousal influence whole-brain communication during wakefulness. The dataset is rich, combining high-field imaging with concurrent physiological measurements, and the analyses are ambitious in scope. A key strength is the attempt to move beyond region-based effects and to describe arousal-related modulation at the level of large-scale connectivity organization. The comparison across rest and movie viewing provides useful context and suggests a degree of consistency across behavioral states.

Weaknesses

First, a central claim is that arousal modulates functional connectivity in a hemispherically asymmetric and community-specific manner. Although structured asymmetries are demonstrated at the group level, it remains unclear whether these effects reflect a stable neurobiological principle or arise from high-dimensional, connection-wise analyses that are sensitive to sampling variability. Given the interpretive weight placed on hemispheric lateralization, stronger evidence of robustness and individual-level consistency would be necessary to support this conclusion.

Second, all analyses are based on ultra-high-field imaging. The manuscript does not address whether the reported arousal-related patterns, including the community structure and hemispheric asymmetries, are expected to be reproducible at standard field strengths. It therefore remains unclear whether the findings depend critically on the use of high-field data or whether they would generalize to more widely available datasets, limiting the broader applicability of the results.

Third, arousal-connectivity coupling is assessed using zero-lag correlations between pupil diameter and time-resolved connectivity estimates. Physiological and hemodynamic considerations suggest that pupil-linked arousal and blood-based imaging signals may exhibit systematic temporal delays. The absence of analyses examining sensitivity to such delays raises the possibility that the reported coupling patterns depend on a specific temporal alignment assumption.

Fourth, the estimation of time-resolved connectivity relies on a single choice of sliding-window length. The manuscript does not examine whether the reported patterns are stable across different window sizes. Given ongoing concerns about parameter dependence in time-resolved connectivity analyses, sensitivity analyses would be important to establish that the findings are not artifacts of a particular analytical choice.

Finally, the identification of seven connectivity communities is a central result, yet the justification for this choice relies primarily on a single clustering quality measure. In practice, evaluation of clustering solutions typically draws on multiple complementary criteria, including measures of compactness and separation, approaches for selecting the number of clusters, and assessments of stability under resampling. Without such complementary evaluations, it is difficult to determine whether the reported community structure reflects a stable organizational feature or sensitivity to specific methodological decisions.

Reviewer #1 (Public review):

Genetically encoded fluorescent proteins expressed in specific cell types allow recognising them in vivo and, if the protein is a functional indicator, as in the case of genetically encoded calcium indicators (GECIs), to record activity from the same cellular ensemble. Ideally, if proteins (fluorophores) have perfectly distinct spectral properties, signals can be distinguished from as many cell types as the number of employed fluorophores. In practice, fluorescent proteins have non-negligible crosstalk both in absorption and emission bands. In addition, fluorescence contribution of each fluorophore normally varies from cell to cell and therefore spectral properties of cells expressing two or more proteins are different. The work of Phillips et al. addresses this challenge. The authors present an approach defined as "Neuroplex", allowing identification of up to nine cell types from the same number of fluorophores. The fingerprint of each cell is then associated with functional fluorescence from the GECI GCaMP, allowing recording calcium activity from that specific cell. The method is implemented in vivo using head-mounted miniscopes.

The authors used a mouse line expressing GCaMP in cortical pyramidal neurons and developed an experimental pipeline. First, they injected the nine AAV viruses, causing expression of fluorophores in a different brain area. The idea was not to image that area, but a non-infected medial prefrontal cortex (mPFC) section where neurons could be infected by their axons projecting in an injected area, in this way being identified by their targeting region(s). A GRIN lens, allowing spectral analysis, was mounted in the mPFC section, and GCaMP fluorescence was then recorded during behavioural tasks and analysed to identify regions of interest (ROIs) corresponding to neuron somata. After functional imaging, the head of the mouse was fixed, spectral analysis was performed, and after necessary correction for chromatic distortions, the fluorophore contribution was determined for each ROI (neuron) from where GCaMP signals were detected. Notably, the procedures for estimation and correction of chromatic aberration and light transmission (described in Figure 2) were a major challenge in their technical achievements. The selection of the nine fluorophores was another big effort. This was done by combining computer simulations and direct measurement of spectra from individual proteins expressed in HEK293 cells. It is important to say that the authors could simulate arbitrary combinations of two or more different fluorophores and evaluate the ability of their algorithm to detect the correct proteins against wrong estimations of false-negative (absence of an expressed protein) or false-positive (presence of a non-expressed protein). Not surprisingly, this ability decreases with the level of GCaMP expression. The authors underline that most errors were false-negatives, which have a milder impact in terms of result interpretation, but the rate of false positives was, nevertheless, relevant in detecting a second fluorophore from a cell expressing only one protein. The experimental profiles of fluorophores were dependent both on the specific fluorescent protein and on the projecting area, and the distribution of double-labelled did not match anatomical evidence. This result should be taken as the limitation of the present pioneering experiments, presented as proof-of-principle of the approach, but Neuroplex may provide far improved precision under different experimental conditions.

In my view, the work of Phillips et al. represents a significant advance in the state-of-the-art of the field. The rigorous analysis of limitations in the use of Neuroplex must be considered an important guideline for future uses of this approach.

Reviewer #1 (Public review):

This paper presents a reanalysis of a large existing dataset to examine whether serial dependence effects-systematic influences of recent stimulus history on current perceptual judgments-are associated with generalization in perceptual learning. The central hypothesis is that extended, longer-range history effects (beyond the most recent trials) are beneficial for transfer across locations. The authors reanalyze data from a texture discrimination task in which observers discriminated peripheral target orientation against a line background, with performance quantified by stimulus-onset asynchrony thresholds. Three training conditions were compared: a fixed single-location condition, a two-location alternating condition, and a dummy-trial condition with frequent target-absent trials. Transfer was assessed after training at new locations. Serial dependence was quantified using history-sequence analyses and linear mixed-effects models estimating bias weights across stimulus lags, with summary measures distinguishing recent (1-3 trials back) and more distant (4-6 trials back) dependencies.

The authors report extended serial dependence effects, persisting up to 6-10 trials back, with substantial cumulative bias that remains stable across multiple days of training and is not correlated with overall performance thresholds. Recent history effects are stronger for faster responses, suggesting a contribution from decision- or response-related processes, whereas more distant effects decline within sessions, potentially reflecting adaptation dynamics. Critically, longer-range serial dependence is significantly stronger in training conditions that promote generalization than in the single-location condition. Individual differences in the strength and decay profile of distant history effects predict the magnitude of transfer across locations, whereas recent history effects do not. History effects are also correlated across trained locations, suggesting stable individual differences.

The authors interpret longer-range serial dependence as reflecting integrative processes that extract task-relevant structure over time, thereby supporting generalization, while shorter-range effects are attributed to more transient mechanisms such as priming or decision-level bias. The discussion connects these findings to Bayesian accounts of perceptual stability and to concepts of overfitting in machine learning.

The study offers a novel and thoughtful link between short-term serial dependence and long-term generalization in perceptual learning, helping bridge two literatures that are often treated separately. The large dataset enables robust estimation of individual differences, and the use of mixed-effects modeling appropriately accounts for variability across observers. The empirical distinction between recent and more distant history effects is well-supported and adds important nuance to interpretations of serial dependence. Converging evidence from both group-level comparisons and individual-level correlations strengthens the central conclusions.

Several limitations should be addressed. First, the study relies entirely on previously collected data, without experimental manipulations designed to selectively isolate serial dependence mechanisms. Filtering choices, while theoretically motivated, may amplify history effects in ways that are difficult to quantify. Second, sequential dependencies can arise from multiple sources, including gradual updating of internal weight structures, adaptation processes, and history-dependent biases in decision-making. The current analyses do not clearly separate these contributions, limiting mechanistic attribution of long-range effects. Third, the conclusions are based on a single perceptual task, leaving open questions about generality across paradigms. Finally, while the discussion references computational ideas, no explicit modeling is provided to test whether plausible learning rules can jointly account for the observed history profiles and transfer effects.

The findings align with theoretical frameworks that conceptualize perceptual learning as gradual reweighting of stable sensory representations at the decision stage (e.g., Petrov et al., 2005). Trial-by-trial updates in these models naturally give rise to sequential dependencies and sensitivity to training statistics. The observation that longer-range history effects predict generalization is consistent with broader temporal integration supporting more flexible learning, while narrower integration may lead to specificity. The results also indicate that multiple mechanisms - including decision-level biases and adaptation - may coexist with reweighting processes, highlighting the value of hybrid accounts.

In summary, this is a careful and data-rich reanalysis that highlights a potentially important role for serial dependence in enabling generalization during perceptual learning. While the underlying mechanisms remain underspecified, the evidence supporting the reported associations is strong, and the work provides a valuable empirical foundation for further experimental and modeling efforts.

Reviewer #1 (Public review):

Summary:

The authors attempt to use a combination of behavioural and EEG analyses in order to investigate whether expectation of task difficulty influences spatial focus narrowing in the context of a spatially cued task, alongside an expected attention-related amplitude effect. This distinguishes the experiment from previous tasks, which looked at this potential spatial narrowing in the context of more non-cued diffuse attention tasks. The authors present two major findings:

(1) Behaviourally, they analysed the effects of cue validity and difficulty expectation on response accuracy, and found that participants displayed an effect of difficulty expectation in validly cued trials, showing relatively enhanced behaviour to Hard Expectation trials, but no effect of expectation in invalidly cued trials.

(2) Inverted encoding modelling on broadband EEG showed greater pre-target attentional processing in the Hard Expectation blocks. They go on to show that this enhancement comes in the form of greater amplitude of the Channel Tuning Functions (CTFs) approximately 300 to 400ms post-cue, in the absence of any spatial tuning specificity enhancement (as would be evident in a difference in CTF fit width).

Together, these results provide valuable findings for those investigating the separable effects of expectation and attention on target detection in visual search.

Strengths:

(1) This is a very solidly performed experiment and analysis, with different streams of evidence convincingly pointing in the same direction, i.e. a gain effect of Expectation in the absence of a spatial tuning effect.

(2) EEG is competently analysed and interpreted, and the paper is well written and simple in its motivation.

(3) The authors report appropriately on the results in the Discussion, without overreaching.

Weaknesses:

I mainly have a few minor issues for the authors to clarify, which I will leave to Recommendations. However, a few analyses need further work:

(1) The GLMM method used has very large degrees of freedom (pages 6 and 7) of 34542. I assume this is the number of trials minus the number of parameters? This would imply that random slopes were not modelled in the analyses. However, looking at the Methods, it is reported that they were modelled. The authors should clarify exactly what was done here and why, including the LMM model.

(2) Figure 4 shows an "example CTF fit". Why only one? You could put transparent lines in the background for each individual fit, followed by the grand average, or show each fit in the supplementary section?

Reviewer #1 (Public review):

Summary:

This work presents a GUI with SEM images of 8 Utah arrays (8 of which were explanted, and 4 of which were used for creating cortical lesions).

Strengths:

Visual comparison of electrode tips with SEM images, showing that electrolytic lesioning did not appear to cause extra damage to electrodes.

Weaknesses:

Given that the analysis was conducted on explanted arrays, and no functional or behavioural in-vivo data or histological data are provided, any damage to the arrays may have occurred after explantation, making the results limited and inconclusive (firstly, that there was no significant relationship between degree of electrode damage and use of electrolytic lesioning, and secondly, that electrodes closer to the edge of the arrays showed more damge than those in the center).

Overall, these results add new data and reference images to the field, although the insights that can conclusively be drawn are limited due to the low number of electrodes used and lack of in-vivo/ histological/ impedance data.

Reviewer #1 (Public review):

Summary:

Using single-unit recording in 4 regions of non-human primate brains, the authors tested whether these regions encode computational variables related to model-based and model-free reinforcement learning strategies. While some of the variables seem to be encoded by all regions, there is clear evidence for stronger encoding of model-based information in anterior cingulate cortex and caudate.

Strengths:

The analyses are thorough, the writing is clear, the work is well-motivated by prior theory and empirical studies.

Weaknesses:

The authors have adequately addressed my prior comments.

Reviewer #1 (Public review):

Summary:

The authors' goal was to advance the understanding of metabolic flux in the bradyzoite cyst form of the parasite T. gondii, since this is a major form of transmission of this ubiquitous parasite, but very little is understood about cyst metabolism and growth.

Nonetheless, this is an important advance in understanding and targeting bradyzoite growth.

Strengths:

The study used a newly developed technique for growing T. gondii cystic parasites in a human muscle-cell myotube format, which enables culturing and analysis of cysts. This enabled screening of a set of anti-parasitic compounds to identify those that inhibit growth in both vegetative (tachyzoite) forms and bradyzoites (cysts). Three of these compounds were used for comparative Metabolomic profiling to demonstrate differences in metabolism between the two cellular forms.

One of the compounds yielded a pattern consistent with targeting the mitochondrial bc1 complex, and suggest a role for this complex in metabolism in the bradyzoite form, an important advance in understanding this life stage.

Weaknesses:

Studies such as these provide important insights into the overall metabolic differences between different life stages, and they also underscore the challenge with interpreting individual patterns caused by metabolic inhibitors due to the systemic level of some of some targets, so that some observed effects are indirect consequences of the inhibitor action. While the authors make a compelling argument for focusing on the role of the bc1 complex, there are some inconsistencies in the some patterns that underscore the complexity of metabolic systems.

Reviewer #1 (Public review):

Summary:

The authors integrated bulk proteomics, single-nucleus RNA sequencing, and cellular communication pipelines to map molecular changes in the mouse lumbar spinal cord following endurance training versus acute exhaustive exercise. This kind of data is currently missing in the literature for the healthy spinal cord; therefore, this work represents a useful resource for the community for the investigation of cellular mechanisms of exercise-induced neuroplasticity. The authors found that endurance training elicited robust plastic transcriptional changes in the glia, in genes involved in synaptic modulation, axon development, and intercellular signaling, with cell-specific differences. Acute exhaustive exercise triggered a more nuanced biphasic temporal response in metabolic and synaptic genes, which was different in trained versus sedentary mice. Although cholinergic neurons did not show robust gene expression changes, they were found to be central hubs for communication with glia, suggesting that their cues may act as upstream regulators of glial plasticity.

Strengths:

Nuclei fixation minimized unwanted RNA degradation and tissue processing-driven expression changes. However, in the text, it needs to be acknowledged that the fixation step was performed only after nuclei isolation, and not at the stage of spinal cord tissue collection. The time course study design allowed for the distinction of different temporal gene expression trajectories.

Weaknesses:

No clear indication of the number of biological replicates is given. No validation of the key findings with alternative methods is presented.

Some aspects of data analysis need to be clarified:

(1) Methods

a) Voluntary exercise: the authors should indicate whether the mice were singly housed, and, if not, clarify that the indicated mean km/day is an average of the mice in the cage.

b) The Authors should indicate more precisely which lumbar level of the spinal cord was used and the number of biological replicates.

c) The Authors should indicate the number of highly variable features and PCs (dims) used for Seurat and provide a QC metric table.

(2) Results and Figures

a) Bulk proteomic analysis: The authors used Pval-and not FDR- to assess differentially abundant proteins. Can the author indicate how many proteins passed a more stringent FDR cutoff? For GO analysis: the authors should indicate what background/reference was used.

b) Figure 1B and Figure S1B-C: the differences in total mass and relative lean mass are very subtle, even if statistically significant. This needs to be acknowledged in the relevant sentences.

c) Figure 2 and Figure S2E panels G and H are inverted.

d) Heatmaps in Figures 1F and 2 Figure 2E-F: some of the proteins and genes listed in the text are not present in the heatmaps (TIM22 and FABP4; Smap25 and Slc4a4). Please check the correspondence of the text with the heatmap, and indicate with an arrow the listed proteins and genes.

e) Page 9 "trained mice displayed a modest increase of oligodendrocytes 24h": from the plot, it looks to me like a decrease rather than an increase.

f) Figure 4 depicts expression changes in selected metabolism and synaptic activity-related genes: it would be useful to add a table as a supplementary file with expression data of all the synaptic and metabolic genes in addition to the ones that were selected.

Reviewer #1 (Public review):

Summary

This study examines how working memory (WM) influences perceptual decisions, with the aim of distinguishing fast attentional capture-like effects from slower, sustained perceptual biases. The authors use a dual-task design in which a perceptual estimation task is embedded within a WM delay, combined with a time-resolved analysis of mouse tracking reports and hierarchical Bayesian modeling. This approach reveals two temporally distinct signatures of WM-perception interactions within single trials, arguing against a unitary account of WM-driven perceptual bias and instead supporting multiple processes that operate over different timescales.

Strengths

A major strength of the study is its innovative use of a time-resolved mouse trajectory analysis to move beyond endpoint measures and reveal the dynamic evolution of decision biases. By decomposing trajectories into components that are and are not explained by the final response, the authors provide compelling evidence for an early transient deviation and a slower, endpoint-consistent drift. The combination of rigorous experimental design, hierarchical Bayesian modeling, and converging analyses yields compelling support for the central claims and offers a valuable framework for studying top-down influences on perception.

Weaknesses/points requiring clarification:

(1) The primary weakness concerns the clarity of the theoretical framing linking the identified trajectory components specifically to attentional capture and representational (or perceptual) shift. While the manuscript reviews prior work on attentional and perceptual biases, the conceptual transition to the proposed distinction between capture and representational shift would benefit from a stronger connection to the existing literature. Clarifying this relationship would strengthen the interpretation of the results.

(2) The use of the term "continuous" to describe the trajectory analyses may be confusing for readers, as it could be interpreted as referring to a continuous task rather than a time-resolved analysis of movements performed to make a discrete response.

(3) Figures 2 and 7 present posterior distributions of hierarchical Bayesian parameter estimates for endpoint responses in Experiments 1 and 2. However, they do not show how these model estimates relate to the raw behavioral data. Including model fits alongside the observed data would help readers assess the quality of the fits and better evaluate how well the modeling captures the underlying behavioral responses. Similarly, it would be helpful to see individual means in Figure 3a, panel 2, as is done in Figure 4.

Reviewer #1 (Public review):

Summary:

Zeng et al. characterized the dynamic brain states that emerged during episodic encoding and the reactivation of these states during the offline rest period in children aged 8-13. In the study, participants encoded scene images during fMRI and later performed a memory recognition test. The authors adopted the BSDS approach and identified four states during encoding, including an "active-encoding" state. The occupancy rate of, and the state transition rates towards, this active-encoding state positively predicted memory accuracy across participants. The authors then decoded the brain states during pre- and post-encoding rests with the model trained on the encoding data to examine state reactivation. They found that the state temporal profile and transition structure shifted from encoding to post-encoding rest. They also showed that the mean lifetime and stability (measured with self-transition probability) of the "default-mode" state during post-encoding rest predict memory performance.

Strengths:

How brain dynamics during encoding and offline rest support long-term memory remains understudied, particularly in children. Thus, this study addresses an important question in the field. The authors implemented an advanced computational framework to identify latent brain states during encoding and carefully characterized their spatiotemporal features. The study also showed evidence for the behavioral relevance of these states, providing valuable insights into the link between state dynamics and successful encoding and consolidation.

Weaknesses:

(1) If applicable, please provide information on the decoding performance of states during pre- and post-encoding rests. The Methods noted that the authors applied a threshold of 0.1 z-scored likelihood, and based on Figure S2, it seems like most TRs were assigned a reinstated state during post-encoding rest. It would be useful to know, for the decodable TRs, how strong the evidence was in favor of one state over others. Further, was decoding performance better during post- vs. pre- encoding rest? This is critical for establishing that these states were indeed "reinstated" during rest. The authors showed individual-specific correlations between encoding and post-encoding state distribution, which is an important validation of the method, but this result alone is not sufficient to suggest that the states during encoding were the ones that occurred during rest. The authors found that the state dynamics vary substantially between encoding and rest, and it would be helpful to clarify whether these differences might be related to decoding performance. I am also curious whether, if the authors apply the BSDS approach to independently identify brain states during rest periods (instead of using the trained model from encoding), they find similar states during rest as those that emerged during encoding?

(2) During post-encoding rest, the intermediate activation state (S1) became the dominant state. Overall, the paper did not focus too much on this state. For example, when examining the relationship between state transitions and memory performance, the authors also did not include this state as a part of the analyses presented in the paper (lines 203-211). Could the author report more information about this state and/or discuss how this state might be relevant to memory formation and consolidation?

(3) Two outcome measures from the BSDS model were the occupancy rate and the mean lifetime. The authors found a significant association with behavior and occupancy rate in some analyses, and mean lifetime in others. The paper would benefit from a stronger theoretical framing explaining how and why these two different measures provide distinct information about the brain dynamics, which will help clarify the interpretation of results when association with behavior was specific to one measure.

(4) For performance on a memory recognition test, d' is a more common metric in the literature as it isolates the memory signal for the old items from response bias. According to Methods (line 451), the authors have computed a different metric as their primary behavioral measure (hits + correction rejections - misses - false alarms). Please provide a rationale for choosing this measure instead. Have the authors considered computing d' as well and examining brain-behavior relationships using d'?

(5) While this study examined brain state dynamics in children, there was no adult sample to compare with. Therefore, it is hard to conclude whether the findings are specific to children (or developing brains). It would be helpful to discuss this point in the paper.

Reviewer #1 (Public review):

This is a high-quality and extensive study that reveals differences in the self-assembly properties of the full set of 109 human death fold domains (DFDs). Distributed amphifluoric FRET (DAmFRET) is a powerful tool that is applied here for a comprehensive examination of the self-assembly behaviour of the DFDs, in non-seeded and seeded contexts, and allows comparison of the nature and extent of self-assembly. The work reveals the nature of the barriers to nucleation in the transition from low to high AmFRET. Alongside analysis of the saturation concentration and protein concentration in the absence of seed, the work demonstrates that the subset of proteins that exhibit discontinuous transitions to higher-order assemblies are expressed more abundantly than DFDs that exhibit continuous transitions. The experiments probing the ~20% of DFDs that exhibit discontinuous transition to polymeric form suggest that they populate a metastable, supersaturated form, in the absence of cognate signal. This is suggestive of a high intrinsic barrier to nucleation.

The differences in self-assembly behaviour are significant and highlight mechanistic differences across this large family of signalling adapter domains, with identification of a small number of key supersaturated adapters, which exhibit higher centrality within networks, and can amplify signals and transduce them to effectors as required. The description of some supersaturated DFD adaptors as long-term, high-energy storage forms or phase change adaptors is attractive and is a framework that addresses many of the requirements for on-demand signaling and amplification in innate immunity. The identification of only a small number of key adaptors and high specificity suggests a mechanism for insulation of pathways from each other and minimisation of aberrant lethal consequences.

An optogenetic approach is applied to initiate self-assembly of CASP1 and CASP9 DFDs, as a model for apoptosome initiation in these two DFDs with differing continuous or discontinuous assembly properties. This comparison reveals clear differences in the stability and reversibility of the assemblies, supporting the authors' hypothesis that supersaturation-mediated DFD assembly underlies signal amplification in at least some of the DFDs. The study also reveals interesting correlations between supersaturation of DFD adapters in short- and long-lived cells, suggestive of a relationship between mechanism of assembly and cellular context. Additionally, the interactions are almost all homomeric or limited to members of the same DFD subfamily or interaction network and examination of bacterial proteins from innate immunity operons suggest that their polymerisation could be driven by similar mechanisms. Future detailed studies that probe the roles and activities of DFDs identified with continuous or discontinuous barriers to nucleation, through mutational analysis, in chimeric proteins and with high resolution studies of the assemblies, can build on this methodology and database.

The Discussion effectively places this work in the context of innate immunity effectors and adapters, explains and provides a justification of the phase change material analogy, and contrasts this mechanism with phase separation. The breadth and depth of the experimental investigations allow a new view of the role of nucleation barriers and supersaturation in DFD assembly and innate immunity pathways.

Reviewer #1 (Public review):

Here, the authors attempted to test whether the function of Mettl5 in sleep regulation was conserved in drosophila, and if so, by which molecular mechanisms. To do so they performed sleep analysis, as well as RNA-seq and ribo-seq in order to identify the downstream targets. They found that the loss of one copy of Mettl5 affects sleep, and that its catalytic activity is important for this function. Transcriptional and proteomic analyses show that multiple pathways were altered, including the clock signaling pathway and the proteasome. Based on these changes the authors propose that Mettl5 modulate sleep through regulation of the clock genes, both at the level of their production and degradation, possibly by altering the usage of Aspartate codon.

Comments on revised version:

The authors satisfactorily addressed my comments, even though the precise mechanism by which Mettl5 regulates translation of clock genes remains to be firmly demonstrated.

Reviewer #1 (Public review):

Summary:

The authors report intracranial EEG findings from 12 epilepsy patients performing an associative recognition memory task under the influence of scopolamine. They show that scopolamine administered before encoding disrupts hippocampal theta phenomena and reduces memory performance, and that scopolamine administered after encoding but before retrieval impairs hippocampal theta phenomena (theta power, theta phase reset) and neural reinstatement but does not impair memory performance. This is an important study with exciting, novel results and translational implications. The manuscript is well written, the analyses are thorough and comprehensive, and the results seem robust.

Strengths:

- Very rare experimental design (intracranial neural recordings in humans coupled with pharmacological intervention);

- Extensive analysis of different theta phenomena;

- Well-established task with different conditions for familarity versus recollection;

- Clear presentation of findings;

- Translational implications for diseases with cholinergic dysfuction (e.g., AD);

- Findings challenge existing memory models and the discussion presents interesting novel ideas.

Reviewer #1 (Public review):

Summary:

An interesting manuscript from the Carrington lab is presented investigating the behavior of single vs double GPI-anchored nutrient receptors in bloodstream form (BSF) T. brucei. These include the transferrin receptor (TfR), the HpHb receptor (HpHbR), and the factor H receptor (FHR). The central question is why these critical proteins are not targeted by host acquired immunity. It has generally been thought that they are sequestered in the flagellar pocket (FP), where they are subject to rapid endocytosis - any Ab:receptor complexes would be rapidly removed from the cell surface. This manuscript challenges that assumption by showing that these receptors can be found all over the outer cell body and flagella surfaces - if one looks in an appropriate manner (rapid direct fixation in culture media).

Strengths and weaknesses:

(1) The presence of a second ESAG6 gene in the BES7 expression site was noted in the previous review. This is now noted and discussed appropriately in the current version.

(2) Surface binding studies: The ability of cells to bind tagged-Tf while in complete media was challenged and it was suggested that classic competition studies be performed to validate saturable ligand binding. This has been done now and the results confirm that this is so. A reasonable discussion of the results is presented.

(3) Variable TfR expression in different BESs: The claim that specific ES environment is the dominant factor controlling TfR expression levels was challenged in that the presented results could be due to technical issues. RNA seq has now been performed confirming that the differences in TfR abundance is indeed directly related to mRNA levels

(4) Surface immuno-localization of receptors: In regard to the novel immunofluorescence (direct fixation) methodology used to demonstrate TfR on the cell surface the authors were asked of they had attempted more traditional methods that involve centrifugation/washing. These data are now provided (Fig S5) and do indicate that centrifugation does reduce signal, likely due to shedding and/or internalization during the procedure. Nevertheless, significant signal is present after centrifugation leaving the issue of why others have never detected significant surface TfR.

These responses address all the major concerns with the original submission and a greatly improved manuscript is now submitted.

Reviewer #1 (Public review):

Summary:

This study examined the functional organization of the mouse posterior parietal cortex (PPC) using meso-scale two-photon calcium imaging during visually-guided and history-guided tasks. The researchers found distinct functional modules within the medial PPC: area A, which integrates somatosensory and choice information, and area AM, which integrates visual and choice information. Area A also showed a robust representation of choice history and posture. The study further revealed distinct patterns of inter-area correlations for A and AM, suggesting different roles in cortical communication. These findings shed light on the functional architecture of the mouse PPC and its involvement in various sensorimotor and cognitive functions.

Strengths:

Overall, I find this manuscript excellent. It is very clearly written and built up logically. The subject is important, and the data supports the conclusions without overstating implications. Where the manuscript shines the most is the exceptionally thorough analysis of the data. The authors set a high bar for identifying the boundaries of the PPC subareas, where they combine both somatosensory and visual intrinsic imaging. There are many things to compliment the authors on, but one thing that should be applauded in particular is the analysis of the body movements of the mice in the tube. Anyone working with head-fixed mice knows that mice don't sit still but that almost invariable remains unanalyzed. Here the authors show that this indeed explained some of the variance in the data.

Comments on revisions:

I only had minor comments on the first version of the manuscript and these concerns were fully addressed after revision.

Reviewer #2 (Public review):

In the manuscript Ruhling et al propose a rapid uptake pathway that is dependent on lysosomal exocytosis, lysosomal Ca2+ and acid sphingomyelinase, and further suggest that the intracellular trafficking and fate of the pathogen is dictated by the mode of entry. Overall, this is manuscript argues for an important mechanism of a 'rapid' cellular entry pathway of S.aureus that is dependent on lysosomal exocytosis and acid sphingomyelinase and links the intracellular fate of bacterium including phagosomal dynamics, cytosolic replication and host cell death to different modes of uptake.

Key strength is the nature of the idea proposed, while continued reliance on inhibitor treatment combined with lack of phenotype / conditional phenotype for genetic knock out is a major weakness.

In the revised version, the authors perform experiments with ASM KO cells to provide genetic evidence of the role for ASM in S. aureus entry through lysosomal modulation. The key additional experiment is the phenotype of reduced bacterial uptake in low serum, but not in high serum conditions. The authors suggest this could be due to the SM from serum itself affecting the entry. While this explanation is plausible, prolonged exposure of cells to low serum is well documented to alter several cellular functions, particularly in the context of this manuscript, lysosomal positioning, exocytosis and Ca2+ signaling. A better control here could be WT cells grown in low serum. If SM in serum can interfere, why do they see such pronounced phenotype on bacterial entry in WT cells upon chemical inhibition?

While the authors argue a role for undetectable nano-scale Cer platforms on the cell surface caused by ASM activity, results do not rule out a SM independent role in the cellular uptake phenotype of ASM inhibitors.

The authors have attempted to address many of the points raised in the previous revision. While the new data presented provide partial evidence, the reliance on chemical inhibitors and lack of clear results directly documenting release of lysosomal Ca2+, or single bacterial tracking, or clear distinction between ASM dependent and independent processes dampen the enthusiasm.

I acknowledge the author's argument of different ASM inhibitors showing similar phenotypes across different assays as pointing to a role for ASM, but the lack of phenotype in ASM KO cells is concerning. The author's argument that altered lipid composition in ASM KO cells could be overcoming the ASM-mediated infection effects by other ASM-independent mechanisms is speculative, as they acknowledge, and moderates the importance of ASM-dependent pathway. The SM accumulation in ASM KO cells does not distinguish between localized alterations within the cells. If this pathway can be compensated, how central is it likely to be ?

The authors allude to lower phagosomal escape rate in ASM KO cells compared to inhibitor treatment, which appears to contradict the notion of uptake and intracellular trafficking phenotype being tightly linked. As they point out, these results might be hard to interpret. Could an inducible KD system recapitulate (some of) the phenotype of inhibitor treatment? If S. aureus does not escape phagosome in macrophages, could it provide a system to potentially decouple the uptake and intracellular trafficking effects by ASM (or its inhibitor treatment) ?

The role of ASM on cell surface remains unclear. The hypothesis proposed by the authors that the localized generation of Cer on the surface by released ASM leads to generation of Cer-enriched platforms could be plausible, but is not backed by data, technical challenges to visualize these platforms notwithstanding. These results do not rule out possible SM independent effects of ASM on the cell surface, if indeed the role of ASM is confirmed by controlled genetic depletion studies.

The reviewer acknowledges technical challenges in directly visualizing lysosomal Ca2+ using the methods outlined. Genetically encoded lysosomal Ca2+ sensor such as Gcamp3-ML1 might provide better ways to directly visualize this during inhibitor treatment, or S. aureus infection.

Reviewer #1 (Public review):

Summary:

The authors report the structure of the human CTF18-RFC complex bound to PCNA. Similar structures (and more) have been reported by the O'Donnell and Li labs. This study should add to our understanding of CTF18-RFC in DNA replication and clamp loaders in general. However, there are numerous major issues that I recommend the authors fix.

Strengths:

The structures reported are strong and useful for comparison with other clamp loader structures that have been reported lately.

Reviewer #1 (Public review):

General assessment of the work

In this manuscript, Mohr and Kelly show that the C1 component of the human VEP is correlated with binary choices in a contrast discrimination task, even when the stimulus is kept constant and confounding variables are considered in the analysis. They interpret this as evidence for the role V1 plays during perceptual decision formation. Choice-related signals in single sensory cells are enlightening because they speak to the spatial (and temporal) scale of the brain computations underlying perceptual decision making. However, similar signals in aggregate measures of neural activity offer a less direct window and thus less insight into these computations. The authors do a good job justifying their focus on the C1 component and illustrating how it may behave under different simulated scenarios. The results are interesting, although it is difficult to specify which reasonable hypothesis is exactly ruled out by these results. One interpretation is that V1 activity directly guides perceptual decisions in this task. Alternatively, higher-level areas may do this, provided that their activity largely reflects their V1-inputs. This certainly seems possible in a simple task like this.

Summary of substantive concerns

I have no substantive concerns about the revised version of the paper.

Reviewer #1 (Public review):

Summary:

The existence of VERT regions is well supported, but the number of regions called as ISCs may be inflated by permissive thresholds (e.g., AEI {greater than or equal to} 0.8 or {less than or equal to} 0.2 in a single clone). This risks conflating transient stochastic differences with stable ISCs. Similarly, the claim of cell-type specificity is not convincingly demonstrated given the small sample size (n=4) and strong batch confounding between lymphoblastoid and cartilage progenitors. While syntenic VERT regions across mouse and human are intriguing, they complicate interpretation of strong clustering by cell type. Sampling depth may also have exaggerated allelic imbalance calls.

The proposed role of ISCs in haploinsufficiency is conceptually interesting but remains speculative; developmental stochasticity and founder population size may play larger roles than replication timing. The claim that autosomal inactivation is mechanistically distinct from XCI, however, is reasonable and supported.

Some conclusions should be more explicitly qualified as preliminary. Cell-type specificity and mitotic stability both require stronger evidence; the latter is inferred indirectly from clonal expansion rather than shown directly, and orthogonal experiments (e.g., allele-specific ChIP-seq, DNA methylation) would be required. Estimated genomic coverage of ISCs should also be re-evaluated, as single-clone observations may inflate counts.

Replication is limited. Hierarchical clustering is confounded by batch and based on presence/absence calls that lack quantitative resolution. More robust approaches would include using magnitude of imbalance, annotating VERTs by genomic location, applying stricter thresholds for replication timing, and benchmarking AEI distributions against the X chromosome. These are realistic re-analyses requiring no new data and could be completed in ~1 month.

Methods are generally well described and reproducible. Figures and text would benefit from improved clarity: axis labels are missing in places (e.g., Fig. 1c, Fig. 2g), legends should explain chromosome arm colors, and cluttered figures such as Fig. 1j could be re-visualized for interpretability. Gene set enrichment analysis should be restricted to avoid inflated significance from overly broad categories. A useful citation for XCI timing (pmid=39420003) could be added to strengthen background.

Significance:

Conceptually, this work introduces ISC-like phenomena in human and mouse progenitor lines, coupling allelic expression imbalance with replication timing. Technically, it combines allele-specific RNA-seq with Repli-seq in genotyped, clonal, single-cell-derived lines. Clinically, it suggests an alternative model for haploinsufficiency, relevant to dosage-sensitive diseases where stochastic transcriptional delays could shape penetrance.

The study builds on prior work in allelic exclusion (e.g., HLA, olfactory receptors) and random monoallelic expression, generalizing these phenomena into ISC/vert frameworks and proposing mitotic stability of allele choice. By extending beyond expression to replication timing, the authors suggest a broader paradigm for epigenetic regulation at autosomal loci.

The paper will be of interest to epigeneticists studying XCI, allelic exclusion, and monoallelic expression; to developmental biologists examining replication timing and differentiation; and to clinicians concerned with dosage-sensitive and haploinsufficient disorders.

Reviewer #1 (Public review):

Summary:

This manuscript by Kolb and Hasseman et al. introduces a significantly improved GABA sensor, building on the pioneering work of the Janelia team. Given GABA's role as the main inhibitory neurotransmitter and the historical lack of effective optical tools for real-time in vivo GABA dynamics, this development is particularly impactful. The new sensor boasts an enhanced signal-to-noise ratio (SNR) and appropriate kinetics for detecting GABA dynamics in both in vitro and in vivo settings. The study is well-presented, with convincing and high-quality data, making this tool a valuable asset for future research into GABAergic signaling.

Strengths:

The core strength of this work lies in its significant advancement of GABA sensing technology. The authors have successfully developed a sensor with higher SNR and suitable kinetics, enabling the detection of GABA dynamics both in vitro and in vivo. This addresses a critical gap in neuroscience research, offering a much-needed optical tool for understanding the most important inhibitory neurotransmitter. The clear representation of the work and the convincing, high-quality data further bolster the manuscript's strengths, indicating the sensor's reliability and potential utility. We anticipate this tool will be invaluable for further investigation of GABAergic signaling.

Weaknesses:

Despite the notable progress, a key limitation is that the current generation of GABA sensors, including the one presented here, still exhibits inferior performance compared to state-of-the-art glutamate sensors. While this work is a substantial leap forward, it highlights that further improvements in GABA sensor would still be highly beneficial for the field to match the capabilities seen with glutamate sensors.

Reviewer #1 (Public review):

Summary:

BK channels are widely distributed and involved in many physiological functions. They have also proven a highly useful tool for studying general allosteric mechanisms for gating and modulation by auxiliary subunits. Tetrameric BK channels are assembled from four separate alpha subunits which would be identical for homozygous alleles and of potentially five different combinations for heterozygous alleles Geng et al . (2023), (https://doi.org/10.1085/jgp.202213302). Construction of BK channels with concatenated subunits in order to strictly control heteromeric subunit composition had not yet been used because the N-terminus in BK channels is extracellular whereas the C-terminus is intracellular. In this new work, Chen, Li, and Yan devise clever methods to construct and assemble BK channels of known subunit composition, as well as to fix the number of γ1 axillary subunits per channel. With their novel molecular approaches, Chen, Li and Yan report that a single γ1 axillary subunit is sufficient to fully modulate a BK channel, that the deep conducting pore mutation L312A exhibited a graded effect on gating with each addition mutated subunit replacing a WT subunit in the channel adding an additional incremental left shift in activation, and that the V288A mutation at the selectivity filter must be present on all four alpha subunits in order to induce channel inactivation. Chen, Li, and Yan have been successful in introducing new molecular tools to generate BK channels of known stoichiometry and subunit composition. They validate their methods and provide three different examples of stoichiometric modulation by LRRC26, the selectivity filter, and the pore.

Strengths:

Powerful new molecular tools for study of channel gating are developed and validated in the study.

Weaknesses:

One example each of auxiliary, deep pore, and selectivity filter allosteric actions are presented, but this is sufficient for the purposes of the paper to establish their methods and present specific examples of applicability.

Reviewer #1 (Public review):

Summary

The manuscript by Ma et al. provides robust and novel evidence that the noctuid moth Spodoptera frugiperda (Fall Armyworm) possesses a complex compass mechanism for seasonal migration that integrates visual horizon cues with Earth's magnetic field (likely its horizontal component). This is an important and timely study: apart from the Bogong moth, no other nocturnal Lepidoptera has yet been shown to rely on such a dual-compass system. The research therefore expands our understanding of magnetic orientation in insects with both theoretical (evolution and sensory biology) and applied (agricultural pest management, a new model of magnetoreception) significance.

The study uses state-of-the-art methods and presents convincing behavioural evidence for a multimodal compass. It also establishes the Fall Armyworm as a tractable new insect model for exploring the sensory mechanisms of magnetoreception, given the experimental challenges of working with migratory birds. Overall, the experiments are well designed, the analyses are appropriate, and the conclusions are generally well supported by the data.

Strengths

• Novelty and significance: First strong demonstration of a magnetic-visual compass in a globally relevant migratory moth species, extending previous findings from the Bogong moth and opening new research avenues in comparative magnetoreception.

• Methodological robustness: Use of validated and sophisticated behavioural paradigms and magnetic manipulations consistent with best practices in the field. The use of 5 min bins to study a dynamic nature of magnetic compass which is anchored to a visual cue but updated with latency of several minutes is an important finding and a new methodological aspect in insect orientation studies.

• Clarity of experimental logic: The cue-conflict and visual cue manipulations are conceptually sound and capable of addressing clear mechanistic questions.

• Ecological and applied relevance: Results have implications for understanding migration in an invasive agricultural pest with expanding global range.

• Potential model system: Provides a new, experimentally accessible species for dissecting the sensory and neural bases of magnetic orientation.

Weaknesses

Overall, this is a strong study, and the authors have completed an excellent major revision that has undoubtedly addressed most major and minor issues. The remaining points below are minor recommendations, and I acknowledge that differences in opinion are always possible:

(1) Structure and Presentation of Results

• I recommend reordering the visual-cue experiments to progress from simpler conditions (no cues) to more complex ones (cue-conflict). This would improve narrative logic and accessibility for non-specialist readers. The authors have chosen not to implement this suggestion, which I respect, but my recommendation stands.

(2) Ecological Interpretation

• The authors should expand their discussion on how the highly simplified, static cue setup translates to natural migratory conditions, where landmarks are dynamic, transient, or absent. Specifically, further consideration is needed on how the compass might function when landmarks shift position, become obscured, or are replaced by celestial cues. Additionally, the discussion would benefit from a more consolidated section with concrete suggestions for future experiments involving transient, multiple, or more naturalistic visual cues.

This point was addressed partially in one paragraph of the Discussion, which reads as follows:

"In nature, they are likely to encounter a range of luminance-gradient visual cues, including relatively stable celestial cues as well as transient or shifting local features encountered en route. Although such natural cues differ from our simplified laboratory stimulus, they may represent intermittently sampled visual inputs that can be optimally integrated with magnetic information, with the congruency between visual and magnetic cues likely playing a key role in maintaining a stable compass response. Whether the cues are static or changing, brief periods without them may still allow the subsequent recovery of a stable long-distance orientation strategy. Determining which types of natural visual cues support the magnetic-visual compass, and how they interact with magnetic information, including how their momentary alignment or angular relationship is integrated and how such visual cue-magnetic field interactions may require time to influence orientation, together with elucidating the genetic and ecological bases of multimodal orientation, will be important objectives for future research."

While this paragraph is informative, the wording remains lengthy, somewhat unclear, and vague. Shorter, clearer statements would improve readability and impact. For example:

• How could moths maintain direction during periods when only the magnetic field is present and visual landmarks are absent?

• Could celestial cues (e.g., stars) compensate, and what happens if these are also obscured?

• What role does saliency play when multiple visual landmarks are present simultaneously?

• How might a complex skyline without salient landmarks affect orientation?

Including simple, concise sentences that pose concrete open questions and suggest experimental designs would strengthen the discussion without creating space issues. In my view, a comprehensive discussion of how the simplified, static cue setup relates to natural migratory conditions-where landmarks are dynamic, transient, or absent-would add significant value to the paper.

(3) Methodological Details and Reproducibility

• The lack of luminance level measurements should be explicitly highlighted.

• The authors chose not to adjust figure legends by replacing "magnetic South" with "magnetic North." While I believe this would be more conventional and preferable, this is ultimately a minor stylistic issue.

(4) Conceptual Framing and Discussion

• Although the authors made a good attempt to explain the limitations of using an artificial visual cue, I believe there is room for a more explicit argument. For example, it could be stated clearly that this species is unlikely to encounter a situation in nature where a single, highly salient landmark coincides with its migratory direction. Therefore, how these findings translate to real migratory contexts remains an open question. A sentence or two making this point directly would strengthen the discussion.

(5) Technical and Open-Science Points

• Sharing the R code openly (e.g., via GitHub) should be seriously considered. The code does not need to be perfectly formatted, but making it available would be highly beneficial from an open-science perspective.

Reviewer #1 (Public review):

Summary:

Laaker et al. investigate the immunological role of the cribriform plate during neuroinflammation using the EAE model. The authors combine immunohistochemistry, flow cytometry, and single-cell RNA sequencing to characterize CD11b+CD11c+ myeloid cells that accumulate at podoplanin (PDPN)-rich meningeal-lymphatic niches surrounding olfactory nerve bundles. They identified distinct populations of migratory dendritic cells (DCs) and macrophages retained at the cribriform plate that exhibit transcriptional signatures consistent with immune tolerance, reduced interferon signaling, and programmed cell death, including Pdcd1 (PD-1) expression. In parallel, CCR2+ monocytes and alternatively activated (M2-like) Arg1+/CHI3L3+ macrophages integrate into this niche, suggesting the establishment of a locally immunosuppressive myeloid network.

Strengths:

(1) Overall, the study postulates a novel model in which the cribriform plate functions as a specialized perineural immune interface that reshapes myeloid phenotypes during neuroinflammation.

(2) Suggests broader relevance for shaping peripheral immunity and therapeutic targeting. If DCs are being "tuned" at this exit site, it could influence what reaches cervical lymph nodes and how peripheral responses are set during CNS autoimmunity; the authors explicitly position this as relevant to CNS autoimmunity and possibly other CNS diseases (while acknowledging the need for human validation).

(3) Technical sound and highly original work. Convergent multi-method support: the central narrative is backed by immunohistochemistry + flow cytometry + scRNA-seq, rather than a single assay. The headline conclusion (tolerogenic/suppressive skew at the cribriform plate during EAE) is explicitly built from these combined modalities.

Weaknesses:

(1) In Figure 1, the manuscript would be strengthened by quantification of CSF1R-GFP+ and CD11c-eYFP+ cells in PDPN+LYVE1- versus PDPN+LYVE1+ regions in both control and EAE mice. This would demonstrate selective accumulation or retention of myeloid cells at the cribiform plate niche.

(2) While the PostContact-seq strategy is innovative (Figure 3), additional justification is needed to demonstrate that tissue dissociation did not artificially disrupt PDPN-myeloid contacts. The relatively small proportion of live PDPN-rich doublets (~2.5% total aggregates and ~18% PDPN+ within total aggregates) raises questions about representativeness compared with in situ observations. The authors should also more explicitly elaborate on why PostContact-seq was favored over alternative approaches such as PIC-seq.

(3) The authors stated that results regarding cell-cell interactions were integrated across four intercellular communication methodologies (Figure 4B), but this integration is not clearly described in either the Results or Method sections. This needs clarification. Moreover, the interaction analysis in Figure 4B seems to rely on TALKIEN, which does not incorporate prior ligand-receptor knowledge. Given the availability of widely used tools, such as CellChat and NicheNet, the authors may consider cross-referencing their findings.

(4) Given the increase in CCR2+ cells in PDPN+ regions (Figure S4), a pseudotime trajectory analysis may be valuable to test whether CCR2+ monocytes preferentially differentiate into CHI3L3+ immunosuppressive macrophages, PD-1+ DCs, or other myeloid subsets in post-contact versus no contact.

(5) Validation of immunosuppressive signatures in macrophages (Fig. 4G-H) using the same FACS-based post-contact versus no-contact sorting strategy (as in Figure 3A) would strengthen the conclusions.

(6) The identity of CD45IV+ cells in contact with PDPN+ cells is unclear (Figure 6B-C). The authors should provide a gating strategy demonstrating that these cells are CD11b+CD11c+ DCs within the PDPN+ doublet population, and ideally show whether these dying cells are PD-1+. Furthermore, co-labeling in tissue sections for PD-1, cleaved caspase-3, and CD11c-eYP would provide important spatial validation of flow cytometry findings (Figure 6E).

(7) In Figures 1F-H, the authors should comment on the morphological differences of CD11c+ cells in the olfactory bulb versus those infiltrating the cribriform plate.

Reviewer #1 (Public review):

Summary:

This is an important study that employs high-throughput single-cell imaging to directly investigate the relationship between topologically associating domain (TAD) boundaries and gene regulation. The authors rigorously test the prevailing model that TAD boundaries functionally regulate gene activity by modulating chromatin interactions. Their core finding is that, under their specific experimental conditions, the physical distance between TAD boundaries shows no consistent correlation with the transcriptional bursting activity of a gene within the TAD. However, the authors' leap from this specific observation to the broad conclusion that "TAD boundary architecture and gene activity are uncoupled" risks conceptual overgeneralization and may lead to misinterpretation, as it seemingly contradicts substantial prior evidence supporting the regulatory role of TAD structures.

Strengths:

The major strength of this work lies in its innovative high-throughput, multi-colour imaging platform, which enables the simultaneous detection of spatial distances between specific DNA elements (TAD boundaries) and transcriptional activity at the same genomic locus in single cells and single alleles. The high-throughput nature makes the results convincing. A second key strength is the incorporation of perturbations, including global transcriptional inhibition, cell-type comparison, and degradation of key architectural proteins (CTCF, cohesin). This provides a comprehensive methodological framework to examine the relationship between boundary proximity and gene activity from multiple angles under defined conditions.

Weaknesses:

(1) Conceptual framing and interpretation:

The central conclusion may require more precise framing to avoid potential overreach. The authors' interpretation equating "physical distance between TAD boundaries" with overall "TAD boundary architecture," and "transcriptional bursting events" with broader "gene activity," could benefit from clarification. This framing may not fully capture the temporal dynamics of transcription or the regulatory complexity within TADs. Furthermore, the broad conclusion of an uncoupled relationship appears to challenge extensive prior evidence from perturbation studies showing that disrupting TAD boundaries can alter gene expression. The authors' own observation of reduced gene activity upon RAD21 degradation suggests that global TAD disruption can affect transcription. A more precise and limited conclusion, acknowledging that their data demonstrate a lack of detectable correlation between boundary distance and bursting activity in their system, would be more accurate and help reconcile these findings with the existing literature.

(2) Technical methods and data presentation:

(2.1) Accuracy and dimensionality of distance measurements: The manuscript does not clearly state whether distances are measured in 2D or 3D, nor does it sufficiently address precision limits. The stated Z-step size (1 µm) may be inadequate for accurately measuring sub-micron chromatin distances in 3D.

(2.2) Probe design and systematic error: The genomic coverage size of the BAC probes used for DNA FISH is not explicitly stated. Large probe coverage could inherently blur the precise spatial location of adjacent DNA loci. The reported average distance (~300 nm) may be influenced by the physical size of the probes, as well as systematic expansion or distortion introduced by sample fixation and FISH processing. Although such technical limitations are currently unavoidable, the authors should clarify how these factors might affect their ability to detect subtle distance changes.

(2.3) Data Visualization: The manuscript would benefit from including representative, zoomed-in regions of interest from the raw imaging data. This would allow readers to visually assess measured distance differences against background noise.

(2.4) Potential impact of resolution limits: In Figure 5, the micro-C data reveal a clear difference in interaction patterns inside versus outside the VARS2 locus TAD, yet the imaging data show no corresponding distance difference. This strongly suggests that the current imaging system, limited by optical resolution, probe size, and localisation accuracy, may be unable to resolve finer-scale spatial reorganizations associated with specific chromatin conformations (e.g., enhancer-promoter loops). The authors should explicitly discuss that their conclusion of "no coupling observed" may be constrained by the resolution and sensitivity of their method and does not preclude the possibility of detecting such associations with higher-precision measurements or in live-cell dynamics.

In summary, this study provides a valuable single-cell perspective. However, the authors should more cautiously define the scope of their findings in the manuscript and provide a more balanced discussion situating their work within the broader field.

Reviewer #1 (Public review):

Summary:

The ubiquitin kinase PINK1 accumulates on damaged mitochondria to signal the initiation of mitophagy. While we know what PINK1 looks like when it is stabilised on damaged mitochondria, not much is known about how it gets there. In this study, Okatsu et al. solve a cryoEM structure of partially folded PINK1 in complex with its chaperones HSP90 and CDC37 to a resolution of 3.08 Å. This structure captures PINK1 in a state whereby the C-lobe of its kinase domain is folded, while the N-lobe remains unfolded and stabilised by an HSP90 dimer. According to the authors' model, their structure represents cytosolic PINK1 on its way to the mitochondria. This structure also demonstrates how PINK1 is folded in a step-wise mechanism and proposes a role for residues that are mutated in Parkinson's disease.

Strengths:

PINK1 is known to be a client of the HSP90 chaperone system. Here, Okatsu et al. present a solid structural dataset showing how PINK1 interacts with HSP90 and CDC37, and they describe key residues and motifs predicted to facilitate the interactions between PINK1 and the chaperones. Notably, two key residues within interacting regions on PINK1 are also mutated in Parkinson's disease. The structure by Okatsu et al. is in line with another recently published structure of the same complex (Tian et al. Nat Comms, 2025), which appears very similar, further supporting the findings. Together, these two studies represent the first observations of cytosolic PINK1 in a semi-folded state, which provides a novel insight into PINK1 at an earlier stage within the signalling cascade.

Weaknesses:

This paper is not the first to describe the structure of the PINK1-HPS90-CDC37 complex. A study by Tian et al. was published in early December 2025 in Nature Communications, reporting a 2.84 Å structure of PINK1-HSP90-CDC37, as well as a structure of PINK1 with HSP90 and another HSP90 co-chaperone, FKBP51. It would be important to acknowledge this comparable study and to discuss how the structure in this study compares with the Tian et al. structures and whether it reveals any additional information.

Although they make claims about the functional relevance of PINK1-interacting residues, the study by Okatsu et al. does not include any biochemical or functional validation of the structure. To support their claims, the authors should test the PINK1-HSP90-CDC37 interaction using their recombinant proteins for mutants of the conserved hydrophobic PINK1 residues in the PINK1 c-lobe, H352, L353, H360, I382, D384, as well as the PINK1 HPNI motif, especially the PD mutation H271Q. The PINK1 PD mutation L347P, which interacts with the CDC37 HPNI moti,f is also worth testing.

A major question that arises from this work is whether the PINK1-HSP90-CDC37 complex is newly translated PINK1 on its way to mitochondria (as suggested by the authors) or PINK1 that has already entered mitochondria, been cleaved and then retrotranslocated. This latter scenario is the favoured model proposed by Tian et al. (Nat Comms) based on their biochemical experiments. The discrepancies between the two models should at least be discussed, and the authors should also attempt to demonstrate experimentally whether their model is correct. This question is important to address because it would allow this structural information to be placed in the greater context of PINK1 signalling.

It is also unclear what the consequences are of disrupted PINK1-HSP90-CDC37 interactions on the PINK1 signalling process more broadly - does PINK1 accumulate in the cytosol? Is there less of it? Can it still be degraded via the N-end rule? What happens during mitophagy? Perhaps some of these questions can be answered with cell-based studies using a selection of the PINK1 mutants mentioned above that disrupt the PINK1-HSP90-CDC37 complex formation.

Reviewer #1 (Public review):

Summary:

This manuscript by Ghosh and colleagues investigates the transcriptional changes within the oligodendrocyte lineage that contribute to age-related declines in oligodendrocyte differentiation and myelination. Combining bulk RNA-Seq on acutely purified oligodendrocyte lineage cells with bioinformatic approaches, the authors identify groups of genes that show different patterns of dynamic regulation during differentiation (which they term "switch" genes, or "switches"). A subset of these switch genes is differentially regulated with age. The authors identify two transcription factors, Bcl11a and Foxm1, that are downregulated during differentiation, have predicted binding site enrichment at other switch genes, and are downregulated in aged OPCs. Functionally testing Bcl11a, the authors show that Bcl11a knockdown inhibits the differentiation of young OPCs in culture, whereas overexpression promotes the differentiation of aged OPCs. Viral expression of Bcl11a in Sox10-expressing cells accelerates the formation of Plp1+ oligodendrocytes in aged rodents following lysolecithin induced demyelination.

Strengths:

The work is clearly presented and addresses an important biological problem. The bioinformatic approaches used in the manuscript are powerful, and the identification of Bcl11a as a modulator of oligodendrocyte differentiation is a novel finding. The combined in vitro and in vivo approaches to assess the function of Bcl11a in oligodendrocyte differentiation are a substantial strength of the work.

Weaknesses:

Although the PCA plots show distinct and reproducible global gene expression differences between the different isolated cell populations, the authors do not present a figure showing expression levels of typical stage-specific markers (e.g., Pdgfra, Pcdh15, C1ql1 for OPCs, Bcas1, Enpp6, Gpr17 for preOLs, Mobp, Mog, etc. for OLs) or confirm the absence of markers of other lineages (astrocytes, neurons, microglia, etc.). This makes it difficult to evaluate the success of their cell isolation strategy at different ages without reanalyzing the raw data. In addition, other publicly available datasets (e.g., the Barres lab bulk RNA-Seq datasets from PMID 25186741 or the Castelo-Branco lab single cell datasets from PMID 27284195) do not show downregulation of Bcl11a during OL differentiation as is described here - this apparent discrepancy is not discussed.

Reviewer #2 (Public review):

Summary:

This paper formulates an individual-based model to understand the evolution of division of labor in vertebrates. The model considers a population subdivided in groups, each group has a single asexually-reproducing breeder, other group members (subordinates) can perform two types of tasks called "work" or "defense", individuals have different ages, individuals can disperse between groups, each individual has a dominance rank that increases with age, and upon death of the breeder a new breeder is chosen among group members depending on their dominance. "Workers" pay a reproduction cost by having their dominance decreased, and "defenders" pay a survival cost. Every group member receives a survival benefit with increasing group size. There are 6 genetic traits, each controlled by a single locus, that control propensities to help and disperse, and how task choice and dispersal relate to dominance. To study the effect of group augmentation without kin selection, the authors cross-foster individuals to eliminate relatedness. The paper allows for the evolution of the 6 genetic traits under some different parameter values to study the conditions under which division of labour evolves, defined as the occurrence of different subordinates performing "work" and "defense" tasks. The authors envision the model as one of vertebrate division of labor.

The main conclusion of the paper is that group augmentation is the primary factor causing the evolution of vertebrate division of labor, rather than kin selection. This conclusion is drawn because, for the parameter values considered, when the benefit of group augmentation is set to zero, no division of labor evolves and all subordinates perform "work" tasks but no "defense" tasks.

Strengths:

The model incorporates various biologically realistic details, including the possibility to evolve age polytheism where individuals switch from "work" to "defence" tasks as they age or vice versa, as well as the possibility of comparing the action of group augmentation alone with that of kin selection alone.

Weaknesses from the previous round of review::

The model and its analysis are limited, which in my view makes the results insufficient to reach the main conclusion that group augmentation and not kin selection is the primary cause of the evolution of vertebrate division of labour. There are several reasons.

First, although the main claim that group augmentation drives the evolution of division of labour in vertebrates, the model is rather conceptual in that it doesn't use quantitative empirical data that applies to all/most vertebrates and vertebrates only. So, I think the approach has a conceptual reach rather than being able to achieve such conclusion about a real taxon.

Second, I think that the model strongly restricts the possibility that kin selection is relevant. The two tasks considered essentially differ only by whether they are costly for reproduction or survival. "Work" tasks are those costly for reproduction and "defense" tasks are those costly for survival. The two tasks provide the same benefits for reproduction (eqs. 4, 5) and survival (through group augmentation, eq. 3.1). So, whether one, the other, or both helper types evolve presumably only depends on which task is less costly, not really on which benefits it provides. As the two tasks give the same benefits, there is no possibility that the two tasks act synergistically, where performing one task increases a benefit (e.g., increasing someone's survival) that is going to be compounded by someone else performing the other task (e.g., increasing that someone's reproduction). So, there is very little scope for kin selection to cause the evolution of labour in this model. Note synergy between tasks is not something unusual in division of labour models, but is in fact a basic element in them, so excluding it from the start in the model and then making general claims about division of labour is unwarranted. In their reply, the authors point out that they only consider fertility benefits as this, according to them, is what happens in cooperative breeders with alloparental care; however, alloparental care entails that workers can increase other's survival *without group augmentation*, such as via workers feeding young or defenders reducing predator-caused mortality, as a mentioned in my previous review but these potentially kin-selected benefits are not allowed here.

Third, the parameter space is understandably little explored. This is necessarily an issue when trying to make general claims from an individual-based model where only a very narrow parameter region of a necessarily particular model can be feasibly explored. As in this model the two tasks ultimately only differ by their costs, the parameter values specifying their costs should be varied to determine their effects. In the main results, the model sets a very low survival cost for work (yh=0.1) and a very high survival cost for defense (xh=3), the latter of which can be compensated by the benefit of group augmentation (xn=3). Some limited variation of xh and xn is explored, always for very high values, effectively making defense unevolvable except if there is group augmentation. In this revision, additional runs have been included varying yh and keeping xh and xn constant (Fig. S6), so without addressing my comment as xn remains very high. Consequently, the main conclusion that "division of labor" needs group augmentation seems essentially enforced by the limited parameter exploration, in addition to the second reason above.

Fourth, my view is that what is called "division of labor" here is an overinterpretation. When the two helper types evolve, what exists in the model is some individuals that do reproduction-costly tasks (so-called "work") and survival-costly tasks (so-called "defense"). However, there are really no two tasks that are being completed, in the sense that completing both tasks (e.g., work and defense) is not necessary to achieve a goal (e.g., reproduction). In this model there is only one task (reproduction, equation 4,5) to which both helper types contribute equally and so one task doesn't need to be completed if completing the other task compensates for it; instead, it seems more fitting to say that there are two types of helpers, one that pays a fertility cost and another one a survival cost, for doing the same task. So, this model does not actually consider division of labor but the evolution of different helper types where both helper types are just as good at doing the single task but perhaps do it differently and so pay different types of costs. In this revision, the authors introduced a modified model where "work" and "defense" must be performed to a similar extent. Although I appreciate their effort, this model modification is rather unnatural and forces the evolution of different helper types if any help is to evolve.

I should end by saying that these comments don't aim to discourage the authors, who have worked hard to put together a worthwhile model and have patiently attended to my reviews. My hope is that these comments can be helpful to build upon what has been done to address the question posed.

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

Reviewer #1 (Public review):

Summary:

The authors aimed to characterize neurocomputational signals underlying interpersonal guilt and responsibility. Across two studies, one behavioral and one fMRI, participants made risky economic decisions for themselves or for themselves and a partner; they also experienced a condition in which the partners made decisions for themselves and the participant. The authors also assessed momentary happiness intermittently between choices in the task. Briefly, the results demonstrated that participants' self-reported happiness decreased after disadvantageous outcomes for themselves and when both they and their partner were affected; and this effect was exacerbated when participants were responsible for their partner's low outcome, rather than the opposite, reflecting experienced guilt. Consistent with previous work, BOLD signals in the insula correlated with experienced guilt and insula-right IFG connectivity was enhanced when participants made risky choices for themselves and safe choices for themselves and a partner.

Strengths:

This study implements an interesting approach to investigating guilt and responsibility; the paradigm in particular is well-suited to approach this question, offering participants the chance to make risky vs. safe choices that affect both themselves and others. I appreciate the assessment of happiness as a metric for assessing guilt across the different task/outcome conditions, as well as the implementation of both computational models and fMRI.

Weaknesses:

In spite of the overall strengths of the study, I think there are a few areas in which the paper fell a bit short and could be improved.

Comment on the revised submission:

I appreciate the authors' attention to all of my comments and questions regarding the initial version of the paper. However, I still do not believe that the point about the small volume correction in the insula has been adequately addressed. The authors claim that because the SVC was done using an anatomically defined ROI, that it is valid and not double dipping. I understand where the authors are coming from. However, there are a few issues here. First, any use of ROIs is best done via pre-registration (Gentili et al., 2021, European Journal of Neuroscience). Second, the whole set of analyses in this section leading up to the SVC seems somewhat circular. The first step was a whole brain contrast of lottery vs. safe outcomes, which revealed activation in many areas including the insula. Then, it appears that the parameter estimates from the insula were extracted and submitted offline to linear mixed models probing for effects of outcome magnitude, social condition and time, which revealed that the insula activation demonstrated the 'sought after' effect. Next, the manuscript states that the authors attempted to confirm these results with a univariate analysis for the so-called guilt effect within regions showing a stronger response to outcomes of risky relative to safe outcomes, which again showed activation in the insula (not surprisingly), and then a small volume correction was applied to these insula voxels. While an anatomical ROI from a different study was used for the correction, the issue is that multiple analyses already revealed that the insula was involved in the effect of interest. It is unclear why this is even necessary given that the LMM analysis demonstrated the expected result.

Reviewer #1 (Public review):

Summary:

The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.

Strengths:

The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.

Weaknesses:

While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, several aspects of the experimental design and data analysis require further clarification and strengthening.

Major Comments:

(1) In Figure 1A, the author showed "stronger binding affinity" based on shifts at lower peptide concentrations, but no quantitative binding parameters (e.g., apparent Kd, fraction bound, or densitometric analysis) are presented. This claim would be better supported by including: (i) A binding curve with quantification of free vs bound RNA band intensities (ii) Replicates and error estimates (mean {plus minus} SD).

(2) The authors report droplet formation at low RNA (50 ng/µL) but protein aggregation at high RNA (400 ng/µL) through fluorescence microscopy. However, no intermediate RNA concentrations (e.g., 100-300 ng/µL) are tested or discussed, leaving a critical gap in understanding the full phase diagram and transition mechanisms. Additionally, the behaviour of PSMα3 in the absence of RNA under LLPS conditions is not shown. Without protein-only data, it is difficult to assess if droplets are RNA-induced or if protein has a weak baseline LLPS that RNA tunes. The saturation concentration (csat) for PSMα3 phase separation, either in the absence or presence of RNA, should be reported.

(3) For a convincing LLPS claim, it is important to show: Quantitative FRAP curves (mobile fraction and half-time of recovery) rather than only microscopy images and qualitative statements.

(4) The manuscript highly relies on fluorescence microscopy to show colocalization. However, the colocalization is presented in a qualitative manner only. The manuscript would benefit from the inclusion of quantitative metrics (e.g., Pearson's correlation coefficient, Manders' overlap coefficients, or intensity correlation analysis).

(5) In Figures 3 B and 3C, the contrast between "no AT630 at 30 min, strong at 2 h" (50 ng/μL) and "strong at 30 min" (400 ng/μL) is compelling, but a simple quantification (e.g., mean fluorescence intensity per area) would greatly increase rigor.

(6) In Figure S3 ssCD data, if possible, indicate whether the α-helical signal increases with RNA concentration or shows a non-linear dependence, which might link to the LLPS vs solid aggregate regimes.

(7) In Figure 5B, FRAP recovery in dying cells may reflect artifactual mobility rather than biological relevance. Additionally, the absence of quantification data limits interpretation; providing recovery curves would clarify relevance.

(8) The narrative conflates cytotoxicity endpoints (membrane damage, PI staining, aggregates) with localization data (nucleolar foci), creating ambiguity about whether nucleolar targeting drives toxicity or is a consequence of cell death. Separating toxicity assessment from localization analysis, or clearly demonstrating that nucleolar accumulation precedes cytotoxicity, would resolve this ambiguity.

(9) In Figure 8, to strengthen the LLPS assignment for LL-37, additional evidence, such as FRAP analysis or observation of droplet fusion events, would be valuable. This is particularly relevant given that the heat shock conditions (65{degree sign}C for 15 minutes) could potentially induce partial denaturation or nonspecific coacervation.

Reviewer #1 (Public review):

Domínguez-Rodrigo and colleagues make a moderately convincing case for habitual elephant butchery by Early Pleistocene hominins at Olduvai Gorge (Tanzania), ca. 1.8-1.7 million years ago. They present this at the site scale (the EAK locality, which they excavated), as well as across the penecontemporaneous landscape, analyzing a series of findspots that contain stone tools and large-mammal bones. The latter are primarily elephants, but giraffids and bovids were also butchered in a few localities. The authors claim that this is the earliest well-documented evidence for elephant butchery; doing so requires debunking other purported cases of elephant butchery in the literature, or in one case, reinterpreting elephant bone manipulation as being nutritional (fracturing to obtain marrow) rather than technological (to make bone tools). The authors' critical discussion of these cases may not be consensual, but it surely advances the scientific discourse. The authors conclude by suggesting that an evolutionary threshold was achieved at ca. 1.8 ma, whereby regular elephant consumption rich in fats and perhaps food surplus, more advanced extractive technology (the Acheulian toolkit), and larger human group size had coincided.

The fieldwork and spatial statistics methods are presented in detail and are solid and helpful, especially the excellent description (all too rare in zooarchaeology papers) of bone conservation and preservation procedures. However, the methods of the zooarchaeological and taphonomic analysis - the core of the study - are peculiarly missing. Some of these are explained along the manuscript, but not in a standard Methods paragraph with suitable references and an explicit account of how the authors recorded bone-surface modifications and the mode of bone fragmentation. This seems more of a technical omission that can be easily fixed than a true shortcoming of the study. The results are detailed and clearly presented.

By and large, the authors achieved their aims, showcasing recurring elephant butchery in 1.8-1.7 million-year-old archaeological contexts. Nevertheless, some ambiguity surrounds the evolutionary significance part. The authors emphasize the temporal and spatial correlation of (1) elephant butchery, (2) Acheulian toolkits, and (3) larger sites, but do not actually discuss how these elements may be causally related. Is it not possible that larger group size or the adoption of Acheulian technology have nothing to do with megafaunal exploitation? Alternative hypotheses exist, and at least, the authors should try to defend the causation, not just put forward the correlation. The only exception is briefly mentioning food surplus as a "significant advantage", but how exactly, in the absence of food-preservation technologies? Moreover, in a landscape full of aggressive scavengers, such excess carcass parts may become a death trap for hominins, not an advantage. I do think that demonstrating habitual butchery bears very significant implications for human evolution, but more effort should be invested in explaining how this might have worked.

Overall, this is an interesting manuscript of broad interest that presents original data and interpretations from the Early Pleistocene archaeology of Olduvai Gorge. These observations and the authors' critical review of previously published evidence are an important contribution that will form the basis for building models of Early Pleistocene hominin adaptation.

Reviewer #1 (Public review):

Summary:

The authors investigate how UVC induced DNA damage alters the interaction between the mitochondrial transcription factor TFAM and mtDNA. Using live-cell imaging, qPCR, atomic force microscopy (AFM), fluorescence anisotropy, and high-throughput DNA-chip assays, they show that UVC irradiation reduces TFAM sequence specificity and increases mtDNA compaction without protecting mtDNA from lesion formation. From these findings the authors suggest that TFAM acts as a "sensor" of damage rather than a protective or repair-promoting factor.

Strengths:

(1) The focus on UVC damage offers a clean system to study mtDNA damage sensing independently of more commonly studied repair pathways, such as oxidative DNA damage. The impact of UVC damage is not well understood in the mitochondria and this study fills that gap in knowledge.

(2) In particular, the custom mitochondrial genome DNA chip provides high resolution mapping of TFAM binding and reveals a global loss of sequence specificity following UVC exposure.

(3) The combination of in vitro TFAM DNA biophysical approaches combined with cellular responses (gene expression, mtDNA turnover) provides a coherent multi-scale view.

(4) The authors demonstrate that TFAM induced compaction does not protect mtDNA from UVC lesions, an important contribution given assumptions about TFAM providing protection.

Weaknesses:

(1) The authors show a decrease in mtDNA levels and increased lysosomal colocalization but do not define the pathway responsible for degradation. Distinguishing between replication dilution, mitophagy, or targeted degradation would strengthen the interpretation and justifies future experiments.

(2) The manuscript briefly notes enrichment of TFAM at certain regions of the mitochondrial genome but provides little interpretation of why these regions are favored. Discussion of whether high-occupancy sites correspond to regulatory or structural elements would add valuable context.

(3) The authors provide a discrepancy between the anisotropy and binding array results. The reason for this is not clear and one wonders if an orthogonal approach for the binding experiments would elucidate this difference (minor point).

Assessment of conclusions:

The manuscript successfully meets its primary goal of testing whether TFAM protects mtDNA from UVC damage and the impact this has on the mtDNA. While their data points to an intriguing model that TFAM acts as a sensor of damaged mtDNA, the validation of this model requires further investigation to make the model more convincing. This is likely warranted for a followup study. Also the biological impact of this compaction, such as altering transcription levels is not clear in this study.

Impact and utility of the methods:

This work advances our understanding of how mitochondria manage UVC genome damage and proposes a structural mechanism for damage "sensing" independent of canonical repair. The methodology, including the custom TFAM DNA chip, will be broadly useful to the scientific community.

Context: The study supports a model in which mitochondrial genome integrity is maintained not only by repair factors, but also by selective sequestration or removal of damaged genomes. The demonstration that TFAM compaction correlates with damage rather than protection reframes an interesting role in mtDNA quality control.

Comments on revised version:

The authors addressed all concerns during the revision.

Reviewer #1 (Public review):

Summary:

This fundamental study identifies a new mechanism that involves a mycobacterial nucleomodulin manipulation of the host histone methyltransferase COMPASS complex to promote infection. Although other intracellular pathogens are known to manipulate histone methylation, this is the first report demonstrating specific targeting the COMPASS complex by a pathogen. The rigorous experimental design using of state-of-the art bioinformatic analysis, protein modeling, molecular and cellular interaction and functional approaches, culminating with in vivo infection modeling provide convincing, unequivocal evidence that supports the authors claims. This work will be of particular interest to cellular microbiologist working on microbial virulence mechanisms and effectors, specifically nucleomodulins, and cell/cancer biologists that examine COMPASS dysfunction in cancer biology.

Strengths:

(1) The strengths of this study include the rigorous and comprehensive experimental design that involved numerous state-of-the-art approaches to identify potential nucleomodulins, define molecular nucleomodulin-host interactions, cellular nucleomodulin localization, intracellular survival, and inflammatory gene transcriptional responses, and confirmation of the inflammatory and infection phenotype in a small animal model.

(2) The use of bioinformatic, cellular and in vivo modeling that are consistent and support the overall conclusions is a strengthen of the study. In addition, the rigorous experimental design and data analysis including the supplemental data provided, further strengthens the evidence supporting the conclusions.

Comments on revisions:

The authors have previously addressed the weaknesses that were identified by this reviewer by providing rational explanation and specific references that support the findings and conclusions.

Reviewer #1 (Public review):

Summary:

This work by Beaudet and colleagues aims at exploring the effect of phosphorylation on the formation of tau envelopes and consequently on axonal transport, both in vitro on reconstituted microtubules and in human excitatory neurons derived from IPSCs.

The authors found that a relatively widely used construct in which 14 serine or threonine residues, often hyperphosphorylated in Alzheimer's disease, are mutated to alanines (phosphodeficient), increases the density of tau envelopes compared to wildtype tau, whereas a phosphomimetic (same residues mutated to glutamic acid) reduces envelope density both in vitro and in human excitatory neurons derived from IPSCs.

By analysing the trafficking of different kinesins (KIF1a and KIF5C), they observed different effects of tau phosphorylation status on the movement of these two motors.

They then analyse transport of lysosomes by employing live imaging of lysotracker in human excitatory neurons derived from IPSCs transfected with wildtype, phosphodeficient or phosphomimetic tau, observing that phosphodeficient tau seems to reduce transport of lysosomes while phosphomimetic increases transport compared to wildtype tau.

Strengths:

(1) The work aims to study a novel and underexplored topic in the tau field, tau envelopes, and investigate their relevance to Alzheimer's disease pathology.

(2) Experiments are well conducted and of high quality.

Weaknesses:

Relying only on in vitro reconstituted microtubules and human neurons derived from IPSCs leaves some doubts about the relevance of these results for Alzheimer's disease, considering the embryonic state of IPSCs-derived neurons.

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 a 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 of 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. However, this study does not really extend our knowledge related to binding determinants essential for LIR motifs in LC3B binding. They basically verify known characteristics, including the importance of varied types of electrostatic interactions supporting the docking of the core LIR into the LDS of LC3B.

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 manages 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.

Reviewer #1 (Public review):

Summary:

The study provides insightful characterization of the mycobacterial secreted effector protein MmpE which translocates to the host nucleus and exhibits phosphatase activity. The study characterizes the nuclear localization signal sequences and residues critical for the phosphatase activity, both of which are required for intracellular survival

Strengths:

(1) The study addresses the role of nucleomodulins, an understudied aspect in mycobacterial infections.

(2) The authors employ a combination of biochemical and computational analyses along with in vitro and in vivo validations to characterize the role of MmpE.

Weaknesses:

(1) While the study establishes that the phosphatase activity of MmpE operates independently of its NLS, there is a clear gap in understanding how this phosphatase activity supports mycobacterial infection. The investigation lacks experimental data on specific substrates of MmpE or pathways influenced by this virulence factor.

(2) The study does not explore whether the phosphatase activity of MmpE is dependent on the NLS within macrophages, which would provide critical insights into its biological relevance in host cells. Conducting experiments with double knockout/mutant strains and comparing their intracellular survival with single mutants could elucidate these dependencies and further validate the significance of MmpE's dual functions.

(3) The study does not provide direct experimental validation of the MmpE deletion on lysosomal trafficking of the bacteria.

(4) The role of MmpE as a mycobacterial effector would be more relevant using virulent mycobacterial strains such as H37Rv.

Comments on revisions:

I appreciate the work the authors have done to address reviewers comments. The revised manuscript looks significantly improved. My major concern in the revised version is the microscopy data where the BCG staining using the DiD fluorescent stain does not bring out the rod-shaped bacilli structure. I suggest the authors either use a GFP reporter or some other fluorescent stain to address this issue.

Reviewer #1 (Public review):

Summary:

Metabolic dysfunction-associated steatotic liver disease (MASLD) ranges from simple steatosis, steatohepatitis, fibrosis/cirrhosis, and hepatocellular carcinoma. In the current study, the authors aimed to determine the early molecular signatures differentiating patients with MASLD associated fibrosis from those patients with early MASLD but no symptoms. The authors recruited 109 obese individuals before bariatric surgery. They separated the cohorts as no MASLD (without histological abnormalities) and MASLD. The liver samples were then subjected to transcriptomic and metabolomic analysis. The serum samples were subjected to metabolomic analysis. The authors identified dysregulated lipid metabolism, including glyceride lipids, in the liver samples of MASLD patients compared to the no MASLD ones. Circulating metabolomic changes in lipid profiles slightly correlated with MASLD, possibly due to the no MASLD samples derived from obese patients. Several genes involved in lipid droplet formation were also found elevated in MASLD patients. Besides, elevated levels of amino acids, which are possibly related to collagen synthesis, were observed in MASLD patients. Several antioxidant metabolites were increased in MASLD patients. Furthermore, dysregulated genes involved in mitochondrial function and autophagy were identified in MASLD patients, likely linking oxidative stress to MASLD progression. The authors then determined the representative gene signatures in the development of fibrosis by comparing this cohort with the other two published cohorts. Top enriched pathways in fibrotic patients included GTPas signaling and innate immune responses, suggesting the involvement of GTPas in MASLD progression to fibrosis. The authors then challenged human patient derived 3D spheroid system with a dual PPARa/d agonist and found that this treatment restored the expression levels of GTPase-related genes in MASLD 3D spheroids. In conclusion, the authors suggested the involvement of upregulated GTPase-related genes during fibrosis initiation.

Significance:

Overall, the current study might provide some new resources regarding transcriptomic and metabolomic data derived from obese patients with and without MASLD. The MASLD research community will be interested in the resource data.

Comments on revised version:

I have no further comments. Thank you.

Reviewer #1 (Public review):

Summary:

The hippocampus, especially the ventral subregion, has been related to emotional processing. However, the specific circuitry involved deserves further investigation. By using a bidirectional optogenetic modulation, Kambali et al. have investigated the role of different inputs to vCA1 (i.e., from vCA3 and entorhinal cortex) in anxiety- and fear-related responses. The major findings of this work suggested that both inputs to vCA1 control fear-related responses, whereas only the projection between vCA3 and vCA1 controls anxiety-related behavior. Overall, the authors used an advanced methodological approach, which allows them to modulate specific brain circuits, to study specific hippocampal projections, providing some new information regarding the hippocampal function in anxiety and fear.

Strengths:

(1) The manuscript is well written, clear and has a detailed and specific discussion.

(2) Results from each optogenetic manipulation are clear in different anxiety- and fear-related tasks, demonstrating the robustness of the findings.

(3) The overall conclusions are very interesting and might be relevant for the field of mental health disorders accompanied by anxiety- and fear-related alterations.

Weaknesses:

(1) The major differences in basal behavioral performance in the different paradigms between the two optogenetic modulations prevent the achievement of strong conclusive results.

(2) Data presentation and representative figures need a major revision.

(3) No analysis has been performed to analyze potential sex differences in behavioral domains where sex is important.

Reviewer #1 (Public review):

The main significance of this work is characterizing the function of a new gene Lmod1 in muscle stem cell biology. The study suggests an intriguing regulatory mechanism by which Sirt1 sequesters Lmod1 in a specific temporal window during myogenesis.

Comments on revisions:

The authors have satisfactorily addressed my inquires. Thank you.

Reviewer #1 (Public review):

In this study, the noncanonical amino acid acridon-2-ylalanine (Acd) was inserted at various positions within the human Hv1 protein using a genetic code expansion approach. The purified mutants with incorporated fluorophore were shown to be functional using a proton flux assay in proteoliposomes. FRET between native tryptophan and tyrosine residues and Acd were quantified using spectral FRET analysis. Predicted FRET efficiencies calculated from an AlphaFold model of the Hv1 dimer were compared to the corresponding experimental values. Spectral FRET analysis was also used to test whether structural rearrangements caused by Zn2+, a well-known Hv1 inhibitor, could be detected. The experimental data provide a good validation of the approach, but further expansion of the analysis will be necessary to differentiate between intra- and intersubunit structural features.

Interestingly, the observed rearrangements induced by Zn2+ were not limited to the protein region proximal to the extracellular binding site but extended to the intracellular side of the channel. This finding agrees with previous studies showing that some extracellular Hv1 inhibitors, such as Zn2+ or AGAP/W38F, can cause long-range structural changes propagating to the intracellular vestibule of the channel (De La Rosa et al. J. Gen. Physiol. 2018, and Tang et al. Brit J. Pharm 2020). The authors should consider adding these references.

Since one of the main goals of this work was to validate Acd incorporation and the spectral FRET analysis approach to detect conformational changes in hHv1 in preparation for future studies, the authors should consider removing one subunit from their dimer model, recalculating FRET efficiencies for the monomer, and comparing the predicted values to the experimental FRET data. This comparison could support the idea that the reported FRET measurements can inform not only on intrasubunit structural features but also on subunit organization.

Reviewer #1 (Public review):

Summary:

This revised manuscript describes critical intermediate reaction steps of a HA synthase at the molecular level; specifically, they examine the 2nd step, polymerization, adding GlcA to GlcNAc to form the initial disaccharide of the repeating HA structure. Unlike the vast majority of known glycosyltransferases, the viral HAS (a convenient proxy extrapolated to resemble the vertebrate forms) uses a single pocket to catalyze both monosaccharide transfer steps. The authors work illustrates the interactions needed to bind & proof-read the UDP-GlcA using direct and '2nd layer' amino acid residues. This step also allows the HAS to distinguish the two UDP-sugars; this is very important as the enzymes are not known or observed to make homopolymers of only GlcA or GlcNAc, but only make the HA disaccharide repeats GlcNAc-GlcA.

Strengths:

Techniques & analysis; overview of HA synthase mechanisms

Weaknesses:

None

Comments on revisions:

Previous clarity issues in the original submission were all resolved. Again, this is a very well done body of work!!

Reviewer #1 (Public review):

This work analyzes innate resistance to drugs in mycobacteria by comparing minimum inhibitory concentrations (MICs) across a diverse panel of mycobacterial species. The results show that MICs are poorly correlated with growth rate while phylogeny associated with horizontal gene transfer underlies the observed differences in MIC, an important demonstration. A further investigation into the driver for the vast differences in susceptibility profiles shows that for three drugs the MIC is not correlated with intrabacterial drug concentrations where intrabacterial drug concentration is comprised of cytosolic and cell wall associated drug. This is a striking observation. The authors delve into the mechanisms that drive resistance to rifamycins and confirm that resistance is driven by ADP-ribosyltransferases of which two variant groups exist, one of which is kinetically faster and apparently is superior at modifying more hydrophobic rifamycins. The relative role of the two ADP-ribosyltransferases in conferring resistance especially in the species with both orthologs is not fully understood since the modified drug can possibly be further modified and transcriptional downregulation experiments performed in this work do not provide genetic evidence of perturbation of mRNA levels of the respective open reading frames.

Comments on revisions:

Demonstration of the level of transcriptional downregulation of the two Arr orthologs would have been a nice demonstration of (1) the utility of CRISPRi in other mycobacteria, (2) that the difference in rifabutin susceptibility during knockdown of Arr-1 vs Arr-X can fully be ascribed to the role of Arr-X in modifying the drug.

Reviewer #1 (Public review):

Summary:

In this manuscript, the role of the insulin receptor and the insulin growth factor receptor was investigated in podocytes. Mice, where both receptors were deleted, developed glomerular dysfunction and developed proteinuria and glomerulrosclerosis over several months. Because of concerns about incomplete KO, the authors generated and studied podocyte cell lines where both receptors were deleted. Loss of both receptors was highly deleterious with greater than 50% cell death. To elucidate the mechanism of cell death, the authors performed global proteomics and found that spliceosome proteins were downregulated. They confirmed this directly by using long-read sequencing. These results suggest a novel role for insulin and IGF1R signaling in RNA splicing in podocytes.

This is primarily a descriptive study and no technical concerns are raised. The mechanism of how insulin and IGF1 signaling regulates splicing is not directly addressed but implicates potentially the phosphorylation downstream of these receptors. In the revised manuscript, it is shown that the mouse KO is incomplete potentially explaining the slow onset of renal insufficiency. Direct measurement of GFR and serial serum creatinines might also enhance our understanding of progression of disease, proteinuria is a strong sign of renal injury. An attempt to rescue the phenotype by overexpression of SF3B4 would also be useful but may be masked by defects in other spliceosome genes. As insulin and IGF are regulators of metabolism, some assessment of metabolic parameters would be an optional add-on.

Significance:

With the GLP1 agonists providing renal protection, there is great interest in understanding the role of insulin and other incretins in kidney cell biology. It is already known that Insulin and IGFR signaling play important roles in other cells of the kidney. So, there is great interest in understanding these pathways in podocytes. The major advance is that these two pathways appear to have a role in RNA metabolism.

Comments on revised version:

I'm satisfied with the revised manuscript and the responses to my previous concerns.

Reviewer #1 (Public review):

Summary:

The authors show that genetic deletion of the orphan tumor necrosis factor receptor DR6 in mice does not protect peripheral axons against degeneration after axotomy. Similarly, Schwann cells in DR6 mutant mice react to axotomy similarly to wild type controls. These negative results are important because previous work has indicated that loss or inhibition of DR6 is protective in disease models and also against Wallerian degeneration of axons following injury. This carefully executed counterexample is important for the field to consider.

Strengths:

A strength of the paper is the use of two independent mouse strains that knockout DR6 in slightly different ways. The authors confirm that DR6 mRNA is absent in these models (western blots for DR6 protein are less convincingly null, but given the absence of mRNA, this is likely an issue of antibody specificity). One of the DR6 knockout strains used is the same strain used in a previous paper examining the effects of DR6 on Wallerian degeneration.

The authors use a series of established assays to evaluate axon degeneration, including light and electron microscopy on nerve histological samples and cultured dorsal root ganglion neurons in which axons are mechanically severed and degeneration is scored in time lapse microscopy. These assays consistently show a lack of effect of loss of DR6 on Wallerian degeneration in both mouse strains examined.

Additional strengths are that the authors examine both the axonal response and the Schwann cell response to axotomy and use both in vivo and in vitro assays.

Therefore, these experiments, the author's data support their conclusion that loss of DR6 does not protect against Wallerian degeneration.

Weaknesses:

A weakness of this paper is that no effort is made to determine why the results presented here may differ from previous studies. A notable possibility is that the original mouse strain that showed 5 of 13 mice being protected from Wallerian degeneration was studies on a segregating C57BL/6.129S background.

Finally, it is important to note that previously reported effects of DR6 inhibition, such as protection of cultured cortical neurons from beta-amyloid toxicity, are not necessarily the same as Wallerian degeneration of axons distal to an injury studied here. The negative results presented here showing that loss of DR6 is not protective against Wallerian degeneration induced by injury are important given the interest in DR6 as a therapeutic target. However, care should be taken in attempting to extrapolate these results to other disease contexts such as ALS or Alzheimer's disease.

Reviewer #1 (Public review):

Summary:

In this study, the authors investigate the physiological role of the Type VI secretion system (T6SS) in a naturally evolved gut microbiome derived from wild mice (the WildR microbiome). Focusing on Bacteroides acidifaciens, the authors use newly developed genetic tools and strain-replacement strategies to test how T6SS-mediated antagonism influences colonization, persistence, and fitness within a complex gut community. They further show that the T6SS resides on an integrative and conjugative element (ICE), is distributed among select community members, and can be horizontally transferred, with context-dependent effects on colonization and persistence. The authors conclude that the T6SS stabilizes strain presence in the gut microbiome while imposing ecological and physiological constraints that shape its value across contexts.

This study is likely to have a significant impact on the microbiome field by moving experimental tests of T6SS function out of simplified systems and into a naturally co-evolved gut community. The WildR system, together with the strain replacement strategy, ICE-seq approach, and genetic toolkit, represents a powerful and reusable platform for future mechanistic studies of microbial antagonism and mobile genetic elements in vivo.

The datasets, including isolate genomes, metagenomes, and ICE distribution maps, will be a valuable community resource, particularly for researchers interested in strain-resolved dynamics, horizontal gene transfer, and ecological context dependence. Even where mechanistic resolution is incomplete, the work provides a strong experimental foundation upon which such questions can be directly addressed.

Overall, this study occupies a space between system building and mechanistic dissection. The authors demonstrate that the T6SS influences persistence and community structure in vivo, but the physiological basis of these effects remains unresolved. Interpreting the results as evidence of fitness costs or selective advantage, therefore, requires caution, as multiple ecological and host-mediated processes could produce similar abundance trajectories.

Placing the findings within the broader literature on microbial antagonism, particularly work emphasizing measurable costs, benefits, and tradeoffs, would help readers better contextualize what is directly demonstrated here versus what remains an open question. Viewed in this light, the principal contribution of the study is to show that such questions can now be addressed experimentally in a realistic gut ecosystem.

Strengths:

A major strength of this study is that it directly interrogates the physiological role of the T6SS in a naturally evolved gut microbiome, rather than relying on simplified pairwise or in vitro systems. By working within the WildR community, the authors advance beyond descriptive surveys of T6SS prevalence and address function in an ecologically relevant context.

The authors provide clear genetic evidence that Bacteroides acidifaciens uses a T6SS to antagonize co-resident Bacteroidales, and that loss of T6SS function specifically compromises long-term persistence without affecting initial colonization. This temporal separation is well designed and supports the conclusion that the T6SS contributes to maintenance rather than establishment within the community.

Another strength is the identification of the T6SS on an integrative and conjugative element (ICE) and the demonstration that this element is distributed among, and exchanged between, community members. The use of ICE-seq to track distribution and transfer provides strong support for horizontal mobility and adds mechanistic depth to the study.

Finally, the transfer of the T6SS-ICE into Phocaeicola vulgatus and the observation of context-dependent colonization benefits followed by decline is a compelling result that moves the study beyond simple "T6SS is beneficial" narratives and highlights ecological contingency.

Weaknesses:

Despite these strengths, there is a mismatch between the precision of the claims and the precision of the measurements, particularly regarding fitness costs, physiological burden, and the mechanistic role of the T6SS.

First, while the authors conclude that the T6SS "stabilizes strain presence" and that its value is constrained by fitness costs, these costs are not directly measured. Persistence, abundance trajectories, and eventual loss are informative outcomes, but they do not uniquely identify fitness tradeoffs. Decline could arise from multiple non-exclusive mechanisms, including community restructuring, host-mediated effects, incompatibilities of the ICE in new hosts, or ecological retaliation, none of which are disentangled here.

Second, the manuscript frames the T6SS as having a defined physiological role, yet the data do not resolve which physiological processes are under selection. The experiments demonstrate that T6SS activity affects persistence, but they do not distinguish whether this occurs via direct killing, resource release, niche modification, or higher-order community effects. As a result, "physiological role" remains underspecified and risks being conflated with ecological outcome.

Third, although the authors emphasize context dependence, the study offers limited quantitative insight into what aspects of context matter. Differences between native and recipient hosts, or between early and late colonization phases, are described but not mechanistically interrogated, making it difficult to generalize beyond the specific cases examined.

Fourth is the lack of engagement with recent experimental literature demonstrating functional roles of the T6SS beyond simple interference competition. While the authors focus on persistence and competitive outcomes, they do not adequately situate their findings within recent work demonstrating that T6SS-mediated antagonism can serve additional physiological functions, including resource acquisition and DNA uptake, thereby linking killing to measurable benefits and tradeoffs. The absence of this literature makes it difficult to place the authors' conclusions about physiological role and fitness cost within the current conceptual framework of the field. Without this context, the physiological interpretation of the results remains incomplete, and alternative functional explanations for the observed dynamics are underexplored.

A further limitation concerns the taxonomic scope of the functional analysis. The authors state that the role of the T6SS in the murine environment is functionally investigated using genetically tractable Bacteroides species, citing the lack of genetic tools for Mucispirillum schaedleri. While this is a reasonable, practical choice, it means that a substantial fraction of T6SS-encoding species in the WildR community are not experimentally interrogated. Consequently, conclusions about the role of the T6SS in the murine gut necessarily reflect the subset of taxa that are genetically accessible and may not fully capture community-level or niche-specific functions of T6SS activity. Given that M. schaedleri is represented as a metagenome-assembled genome, its isolation and genetic manipulation would be technically challenging. Nonetheless, explicitly acknowledging this limitation and slightly tempering claims of generality would strengthen the manuscript.

Finally, several interpretations would benefit from more cautious language. In particular, claims invoking fitness costs, selective advantage, or physiological burden should be explicitly framed as inferences from persistence dynamics, rather than as direct measurements, unless supported by additional quantitative fitness or growth assays.

Reviewer #1 (Public review):

Summary:

The authors aim to determine whether TENT5A, a post-transcriptional regulator previously implicated in bone formation, also plays a role in enamel development. Using a mouse model lacking TENT5A, they report hypomineralized enamel with structural defects, accompanied by reduced expression, altered poly(A) tail length, and impaired secretion of enamel matrix proteins, particularly amelogenin. By combining ultrastructural imaging, transcriptomics, direct RNA sequencing, and protein localization analyses, the study proposes that TENT5A promotes cytoplasmic polyadenylation and translation of a subset of extracellular matrix transcripts required for enamel biomineralization.

Strengths:

A major strength of this work is its conceptual novelty. To my knowledge, this is the first study to demonstrate that a non-canonical poly(A) polymerase plays a direct role in enamel development, extending post-transcriptional regulation by cytoplasmic polyadenylation from bone to enamel, a biologically distinct and non-regenerative mineralized tissue. The identification of amelogenin as a dominant, tissue-specific target provides a new perspective on how enamel matrix production is regulated beyond transcriptional control.

In addition, the study is supported by a comprehensive and complementary set of approaches linking molecular changes to tissue-level phenotypes. The use of direct RNA sequencing provides strong evidence for selective regulation of poly(A) tail length in specific transcripts rather than global effects on mRNA metabolism, and the phenotypic analyses convincingly connect altered post-transcriptional regulation to defects in enamel structure and mineralization.

Weaknesses:

Although the data support a role for TENT5A in stabilizing and promoting translation of amelogenin and related transcripts, the mechanism underlying substrate specificity remains unresolved. Poly(A) tail length alone does not explain why certain transcripts are regulated while others are not, and the proposed involvement of protein partners or RNA processing steps remains speculative. This limitation should be more clearly framed as an open question rather than an emerging mechanism.

A further limitation is the lack of direct human genetic or clinical evidence linking TENT5A to enamel defects. In humans, loss-of-function variants in TENT5A are known to cause a recessive form of osteogenesis imperfecta, but TENT5A has not been associated with amelogenesis imperfecta or other enamel phenotypes. This limits immediate translational interpretation of the mouse enamel phenotype and highlights the need for future human genetic or clinical studies.

Finally, the manuscript does not address whether other members of the TENT5 family are expressed in ameloblasts or could compensate for the loss of TENT5A, leaving open questions about redundancy and specificity within this family.

DOI: 10.1016/j.celrep.2026.116971

Resource: None

Curator: @areedewitt04

SciCrunch record: RRID:ZFIN_ZDB-ALT-110411-1

What is this?

Reviewer #1 (Public review):

Summary:

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 a 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 a mismatch. The timecourse of pupillary responses during match decisions was 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.

Weaknesses:

The technical proficiency and complexity of the study and analysis also present a clear limitation and challenge for interpretation. As a reader, even those who are quite knowledgeable about the methods, constructs, and questions being addressed will often struggle (as this reviewer did) to keep the large set of findings in mind and gain an understanding of how they all fit together.

Indeed, it seems like there are many threads running together in the paper, which makes it challenging to find the through-line of the key findings, or to understand how they might relate to some pre-existing hypotheses, rather than merely interesting patterns detected in the data. In the Introduction and Discussion, it seems as if the key question is to understand the pathways by which MPEs impact cognition, but this is a rather broad topic, so it is not clear exactly what the authors are aiming at with this question and study design.

As an example, authors operationalize frontal theta power as an index of cognitive control demand, and one of the pathways by which MPEs impact cognition. But this point becomes somewhat circular, since it is not clear how or why the Mismatch x Strength interaction in frontal theta reflects that demand. It would have been better to set this pattern up in the Introduction as a theoretically driven hypothesis, since it currently appears more like a post-hoc interpretation. This is mirrored by how the issue is first brought up in the Introduction, where it states somewhat vaguely: "whether MPEs are followed by an increase in frontal theta... warrants closer examination". Later in the results, there are findings relating frontal theta to pupil dilation, posterior alpha suppression and then subsequent memory. It was hard to understand how all the findings might be linked together functionally or conceptually. Are the authors potentially postulating a mediating or mechanistic pathway, in which the MPE leads to increased cognitive control (frontal theta), which then leads to enhanced subsequent memory of those events? If this is the case, then maybe a formal path analysis would be the best way to test or state this hypothesis. It would also be useful to specify more clearly how the pupil components and alpha suppression factor into this mediating path, since it was not clear.

Relatedly, the authors suggest that internal attention and arousal also play relevant roles in this pathway, but these are also not clear. In some cases, it is stated as if this is a distinct pathway from the cognitive control one, since there is a focus in the results on the independence of frontal theta and posterior alpha, but elsewhere they seem to be treated as two aspects, or distinct steps, within a single pathway. Again, these different threads of the findings were quite challenging for the reader to follow. Pathway analyses, such as with multiple mediation or moderated mediation, could be a useful way to address this question. For example, it seems as if readiness-to-remember is another behavioral outcome (like subsequent memory) that could be used in the search for mediators.

At the minimum, it would be quite helpful to have diagrammatic figures that specify the hypothesized and observed relationships between independent variables (Strength, Mismatch), physiological indices (pupil dilation components, frontal theta, posterior alpha) and key outcome measures (accuracy, RT, next-trial retrieval success, subsequent memory), so that the reader can refer back to them as each component of the analyses is conducted.

Minor Points:

Many figures had x-axes showing a pupil component or EEG power metric broken down by quartile or quintile. Yet nowhere is it ever explained why this graphical (or analytic?) approach is used and what it reflects, or how it is decided which break down to use (quartile/quintile). If the data are analyzed as a correlation, why is a scatterplot not shown instead?

It was surprising that, unlike readiness-to-remember, which was analyzed via logistic regression and odds-ratio, subsequent memory was not analyzed in the same fashion (i.e., as a binary outcome variable predicted by frontal theta), rather than in a reverse chronological one (subsequent memory predicting frontal theta). Historically, it was the case that subsequent memory was analyzed in this manner, but that was before the era in which trial-level linear mixed-effect models were in wide usage, as they are implemented in this study. Thus, the choice seems like a wasted opportunity or a step backwards analytically.

Reviewer #1 (Public review):

Summary:

This computational modelling study addresses the important question of how neurons can learn non-linear functions using biologically realistic plasticity mechanisms. The study extends the previous related work on metaplasticity by Khodadadi et al. (2025), using the same detailed biophysical model and basic study design, while significantly simplifying the synaptic plasticity rule by removing non-linearities, reducing the number of free parameters, and limiting plasticity to only excitatory synapses. The rule itself is supervised by the presence or absence of a binary dopamine reward signal, and gated by separate calcium-sensitive thresholds for potentiation and depression. The author shows that, when paired with a strong form of dendritic non-linearity called a "plateau potential" and appropriate pre-existing dendritic clustering of features, this simpler learning mechanism can solve a non-linear classification task similar to the classic XOR logic operator, with equal or better performance than the previous publication. The primary claims of this publication are that metaplasticity is required for learning non-linear feature classification, and that simultaneous dynamics in two separate thresholds (for potentiation and depression) are critical in this process. By systematically studying the properties of a biophysically plausible supervised learning rule, this paper adds interesting insights into the mechanics of learning complex computations in single neurons.

Strengths:

The simplified form of the learning rule makes it easier to understand and study than previous metaplasticity rules, and makes the conclusions more generalizable, while preserving biological realism. Since similar biophysical mechanisms and dynamics exist in many different cell types across the whole brain, the proposed rule could easily be integrated into a wide range of computational models specializing in brain regions beyond the striatum (which is the focus of this study), making it of broad interest to computational neuroscientists. The general approach of systematically fixing or modifying each variable while observing the effects and interactions with other variables is sound and brings great clarity to understanding the dynamic properties and mechanics of the proposed learning rule.

Weaknesses:

General notes

(1) The credibility of the main claims is mainly limited by the very narrow range of model parameters that was explored, including several seemingly arbitrary choices that were not adequately justified or explored.

(2) The choice to use a morphologically detailed biophysical model, rather than a simpler multi-compartment model, adds a great deal of complexity that further increases uncertainty as to whether the conclusions can generalize beyond the specific choices of model and morphology studied in this paper.

(3) The requirement for pre-existing synaptic clustering, while not implausible, greatly limits the flexibility of this rule to solve non-linear problems more generally.

(4) In order to claim that two thresholds are truly necessary, the author would have to show that other well-known rules with a single threshold (e.g., BCM) cannot solve this problem. No such direct head-to-head comparisons are made, raising the question of whether the same task could be achieved without having two separate plasticity thresholds.

Specific notes

(1) Regarding the limited hyperparameter search:

(a) On page 5, the author introduces the upper LTP threshold Theta_LTP. It is not clear why this upper threshold is necessary when the weights are already bounded by w_max. Since w_max is just another hyperparameter, why not set it to a lower value if the goal is to avoid excessively strong synapses? The values of w_max and Theta_LTP appear to have been chosen arbitrarily, but this question could be resolved by doing a proper hyperparameter search over w_max in the absence of an upper Theta_LTP.

(b) The author does not explore the effect of having separate learning rates for theta_LTP and theta_LTD, which could also improve learning performance in the NFBP. A more comprehensive exploration of these parameters would make the inclusion of theta_max (and the specific value chosen) a lot less arbitrary.

(c) Figure 4 Supplements 3-4: The author shows results for a hyperparameter search of the learning rule parameters, which is important to see. However, the parameter search is very limited: only 3 parameter values were tried, and there is no explanation or rationale for choosing these specific parameters. In particular, the metaplasticity learning rates do not even span one order of magnitude. If the author wants to claim that the learning rule is insensitive to this parameter, it should be explored over a much broader range of values (e.g., something like the range [0.1-10]).

(2) Regarding the similarity to BCM, the author would ideally directly implement the BCM learning rule in their model, but at the least the author could have shown whether a slight variant of their rule presented here can be effective: for example having a single (plastic, not fixed) Ca-dependent threshold that applies to both LTP and LTD, with a single learning rate parameter.

(3) This paper is extremely similar (and essentially an extension) to the work of Khodadadi et al. (2025). Yet this paper is not mentioned at all in the introduction, and the relation between these papers is not made clear until the discussion, leaving me initially puzzled as to what problems this paper addresses that have not already been extensively solved. The introduction could be reworked to make this connection clearer while pointing out the main differences in approach (e.g., the important distinction between "boosting" nonlinearities and plateau potentials).

(4) The introduction is missing some citations of other recent work that has addressed single-neuron non-linear computation and learning, such as Gidon et al (2020); Jones & Kording (2021).

(5) Figure 1: The figure prominently features mGluR next to the CaV channel, but there is no mention of mGluR in the introduction. The introduction should be updated to include this.

(6) Could the author explain why there is a non-monotonic increase/decrease in the [Ca]_L in Figure 2B_4? Perhaps my confusion comes from not understanding what a single line represents. Does each line represent the [Ca] in a single spine (and if so, which spine), or is each line an average of all the spines in a given stim condition?

(7) Row 124 (page 4): L-type Ca microdomains (in which ions don't diffuse and therefore don't interact with Ca_NMDA) is a critical assumption of this model. The references for this appear only in the discussion, so when reading this paper, I found myself a bit confused about why the same ion is treated as two completely independent variables with separate dynamics. Highlighting the assumption (with citations) a bit more clearly in the results section when describing the rule would help with understanding.

(8) Row 149 (page 5): The current formulation of the update rule is not actually multiplicative. The fact that the update is weight-dependent alone does not make it a multiplicative rule, and judging by equation (1) it appears to simply be an additive rule with a weight regularization term that guarantees weight bounds. For example, a similar weight-dependent update is also a core component of BTSP (Milstein et al. 2021; Galloni et al. 2025), which is another well-known *additive* rule. An actual multiplicative rule implies that the update itself is applied via a multiplication, i.e. w_new = w_old * delta_w

For an example of a genuinely multiplicative rule, see: Cornford et al. 2024, "Brain-like learning with exponentiated gradients"). Multiplicative rules have very different properties to additive rules, since larger weights tend to grow quickly while small weights shrink towards 0.

(9) Equation 1 (page 5): Shouldn't the depression term be written as: (w_min - w)? This term would be negative if w is larger than w_min, leading to LTD. As it is written now, a large w and small w_min would just cause further potentiation instead of depression.

(10) In the introduction, the teaching signal is described in binary terms (DA peak, or DA pause), but in Equation 1, it actually appears to take on 3 different values. Could the author clarify what the difference is between a "DA pause" and the "no DA" condition? The way I read it, pause = absence of DA = no DA

(11) Figure 3: In these experimental simulations, DA feedback comes in 400ms after the stimulus. The author could motivate this choice a bit better and explain the significance of this delay. Clearly, the equations have a delta_t term, but as far as the learning algorithm is concerned, it seems like learning would be more effective at delta_t=0. Is the choice of 400ms mainly motivated by experimental observations? On a related note, is it meaningful that the 200ms delta_t before the next stimulus is shorter than the 400ms pause from the first stimulus? Wouldn't the DA that arrives shortly before a stimulus also have an effect on the learning rule?

(12) Figure 4C: How is it possible that the theta_LTP value goes higher than the upper threshold (dashed line)? Equation 3 implies that it should always be lower.

(13) Row 429 (page 11): The statement that "without metaplasticity the NFBP cannot be solved" is overly general and not supported by the evidence presented. There exist many papers in which people solve similar non-linear feature learning problems with Hebbian or other bio-plausible rules that don't have metaplasticity. A more accurate statement that can be made here is that the specific rule presented in this paper requires metaplasticity.

(14) The methods section does not make any mention of publicly available code or a GitHub repository. The author should add a link to the code and put some effort into improving the documentation so that others can more easily assess the code and reproduce the simulations.

Reviewer #1 (Public review):

The manuscript entitled "Blocking SHP2 1 benefits FGFR2 inhibitor and overcomes its resistance in 2 FGFR2-amplified gastric cancer" by Zhang, et al., reports that FGFR2 was amplification in 6.2% (10/161) of gastric cancer samples and that dual blocking SHP2 and FGFR2 enhanced the effects of FGFR2 inhibitor (FGFR2i) in FGFR2-amplified GC both in vitro and in vivo via suppressing RAS/ERK and PI3K/AKT pathways. Furthermore, the authors also showed that SHP2 blockade suppressed PD-1 expression and promoted IFN-γ secretion of CD8+ 46 T cells, enhancing the cytotoxic functions of T cells. Thus, the authors concluded that dual blocking SHP2 and FGFR2 is a compelling strategy for treatment of FGFR2-amplified gastric cancer. Although the finding is interesting, the finding that FGFR2 is amplified in gastric cancer and that FGFR inhibitors have some effect on treating gastric cancer is not novel. The data quality is not high, the effects of double inhibitions are not significant. It appears that the conclusions are largely overstated, the supporting data is weak and not compelling.

The data in Figure 1 is not novel; similar data have been reported elsewhere.

It is unclear why the two panels in fig 2a and 2b can not be integrated into one panel, which will make it easier to compare the activities.

The synergetic effects of azd4547 and shp099 are not significant in Fig 2e and 2f, as well as in Fig. 3g and Fig. 4f

Data in Fig. 5 is weak and can be removed. It is unclear why FGFR inhibitor has some activities toward t cells since t cells do not express FGFR.

Reviewer #1 (Public review):

Summary:

This paper investigates the thermal and mechanical unfolding pathways of the doubly knotted protein TrmD-Tm1570 using molecular simulations, optical tweezers experiments, and other methods. In particular, the detailed analysis of the four major unfolding pathways using a well-established simulation method is an interesting and convincing result.

Strengths:

A key finding that lends credibility to the simulation results is that the molecular simulations at least qualitatively reproduce the characteristic force-extension distance profiles obtained from optical tweezers experiments during mechanical unfolding. Furthermore, a major strength is that the authors have consistently studied the folding and unfolding processes of knotted proteins, and this paper represents a careful advancement building upon that foundation.

Weaknesses:

While optical tweezers experiments offer valuable insights, the knowledge gained from them is limited, as the experiments are restricted to this single technique.

The paper mentions that the high aggregation propensity of the TrmD-Tm1570 protein appears to hinder other types of experiments. This is likely the reason why a key aspect, such as whether a ribosome or molecular chaperones are essential for the folding of TrmD-Tm1570, has not been experimentally clarified, even though it should be possible in principle.

Comments on revisions:

According to reviewers' comments, the authors revised the manuscript appropriately.

Reviewer #1 (Public review):

Summary:

Since dimerization is essential for SARS-CoV-2 Mpro enzymatic activity, the authors investigated how different classes of inhibitors, including peptidomimetic inhibitors (PF-07321332, PF-00835231, GC376, boceprevir), non-peptidomimetic inhibitors (carmofur, ebselen, and its analog MR6-31-2), and allosteric inhibitors (AT7519 and pelitinib), influence the Mpro monomer-dimer equilibrium using native mass spectrometry. Further analyses with isotope labeling, HDX-MS, and MD simulations examined subunit exchange and conformational dynamics. Distinct inhibitory mechanisms were identified: peptidomimetic inhibitors stabilized dimerization and suppressed subunit exchange and structural flexibility, whereas ebselen covalently bound to a newly identified site at C300, disrupting dimerization and increasing conformational dynamics. This study provides detailed mechanistic evidence of how Mpro inhibitors modulate dimerization and structural dynamics. The newly identified covalently binding site C300 represents novelty as a druggable allosteric hotspot.

Strengths:

This manuscript investigates how different classes of inhibitors modulate SARS-CoV-2 main protease dimerization and structural dynamics, and identifies a newly observed covalent binding site for ebselen.

Weaknesses:

The major concern is the absence of mutagenesis data to support the proposed inhibitory mechanisms, particularly regarding the role of the inhibitor binding site.

Reviewer #1 (Public review):

Summary:

Despite accumulating prior studies on the expressions of AVP and AVPR1a in the brain, a detailed, gender-specific mapping of AVP/AVPR1a neuronal nodes has been lacking. Using RNAscope, a cutting-edge technology that detects single RNA transcripts, the authors created a comprehensive neuroanatomical atlas of Avp and Avpr1a in male and female brains.

Strengths:

This well-executed study provides valuable new insights into gender differences in the distribution of Avp and Avpr1a. The atlas is an important resource for the neuroscience community.

The authors have previously adequately addressed all of my concerns. I have no further questions or concerns.

Reviewer #1 (Public review):

Summary:

RNA modification has emerged as an important modulator of protein synthesis. Recent studies found that mRNA can be acetylated (ac4c), which can alter mRNA stability and translation efficiency. The role of ac4c mRNA in the brain has not been studied. In this paper, the authors convincingly show that ac4c occurs selectively on mRNAs localized at synapses, but not cell wide. The ac4c "writer" NAT10 is highly expressed in hippocampal excitatory neurons. Using NAT10 conditional KO mice, decreasing levels of NAT10 resulted in decreases in ac4c of mRNAs and also showed deficits in LTP and spatial memory. These results reveal a potential role for ac4c mRNA in memory consolidation.

This is a new type of mRNA regulation that seems to act specifically at synapses, which may help elucidate the mechanisms of local protein synthesis in memory consolidation. Overall, the studies are well carried out and presented. The precise mRNAs that require ac4c to carry out memory consolidation is not clear, but is an important focus of future work. The specificity of changes occurring only at the end of training, rather than after each day of training is interesting and also warrants further investigation. This timeframe is puzzling because the authors show that ac4c can dynamically increase within 1hr after cLTP.

Strengths:

(1) The studies show that mRNA acetylation (ac4c) occurs selectively at mRNAs localized to synaptic compartments (using synaptoneurosome preps).

(2) The authors identify a few key mRNAs acetylated involved in plasticity and memory - eg Arc.

(3) The authors show that Ac4c is induced by learning and neuronal activity (cLTP).

(4) The studies show that the ac4c "writer" NAT10 is expressed in hippocampal excitatory neurons and may relocated to synapses after cLTP/learning induction.

(5) The authors used floxed NAT10 mice injected with AAV-Cre in the hippocampus (NAT10 cKO) to show that NAT10 may play a role in LTP maintenance and memory consolidation (using the Morris Water Maze).

Weaknesses:

(1) The NAT10 cKO mice are useful to test the causal role of NAT10 in ac4a and plasticity/memory but all the experiments used AAV-CRE injections in the dorsal hippocampus that showed somewhat modest decreases in total NAT10 protein levels. For these experiments, it would be better to cross the NAT10 floxed animals to CRE lines where better knock down of NAT10 can be achieved postnatally in specific neurons, with less variability.

(2) Because knock down is only modest (~50%), it is not clear if the remaining ac4c on mRNAs is due to remaining NAT10 protein or due to alternative writer (as the authors pose).

Reviewer #1 (Public review):

Summary:

This study uncovers a protective role of the ubiquitin-conjugating enzyme variant Uev1A in mitigating cell death caused by over-expressed oncogenic Ras in polyploid Drosophila nurse cells and by RasK12 in diploid human tumor cell lines. The authors previously showed that over-expression of oncogenic Ras induces death in nurse cells, and now they perform a deficiency- screen for modifiers. They identified Uev1A as a suppressor of this Ras-induced cell death. Using genetics and biochemistry, the authors found that Uev1A collaborates with the APC/C E3 ubiquitin ligase complex to promote proteasomal degradation of Cyclin A. This function of Uev1A appears to extend to diploid cells, where its human homologs UBE2V1 and UBE2V2 suppress oncogenic Ras-dependent phenotypes in human colorectal cancer cells in vitro and in xenografts in mice.

Strengths:

(1) Most of the data is supported by sufficient sample size and appropriate statistics.

(2) Good mix of genetics and biochemistry.

(3) Generation of new transgenes and Drosophila alleles that will be beneficial for the community.

Comments on revisions:

The authors have greatly improved the manuscript and satisfactorily addressed all of my concerns.

Reviewer #1 (Public review):

Summary:

The authors used an in vitro microfluidic system where HUVECs are exposed to high, low or physiologic (normal) shear stress to demonstrate that both high and low shear stress for 24 hours resulted in decreased KLF6 expression, decreased lipid peroxidation and increased cell death which was reversible upon treatment with Fer-1, the ferroptosis inhibitor. RNA sequencing (LSS vs normal SS) revealed decreased steroid synthesis and UPR signaling in low shear stress conditions, which they confirmed by showing reduced expression of proteins that mitigate ER stress under both LSS and HSS. Decreased KLF6 expression after exposure to HSS/LSS was associated with decreased expression of regulators of ER stress (PERK, BiP, MVD) which was restored with KLF6 overexpression. Overexpression of KLF6 also restored SLC7A11 expression, Coq10 and reduced c11 bodipy oxidation state- all markers of lipid peroxidation and ferroptosis. The authors then used vascular smooth muscle cells (atherosclerotic model) with HUVECs and monocytes to show that KLF6 overexpression reduces the adhesion of monocytes and lipid accumulation in conditions of low shear stress.

Strengths:

(1) The use of a microfluidic device used to simulate shear stress while keeping the pressure constant when varying shear stress applied is improved and more physiologic compared to traditional cone and shearing devices. Similarly, the utilization of both low and high shear stress in most experiments is a strength.

(2) This study provides a link between disturbed shear stress and ferroptosis, which is novel, and fits nicely with existing knowledge that endothelial cell ferroptosis promote atherosclerosis. This concept was also recently reported Sept 2025 when a publication also demonstrated that LSS trigger ferroptosis in vascular endothelial cells (PMID: 40939914), which partly validates these findings.

Weaknesses:

(1) While HUVECs are commonly used in endothelial in vitro studies, it would be preferable to confirm the findings using an arterial cell line such as human coronary artery cells when studying mechanisms of early atherosclerosis. Furthermore, physiologic arterial shear stress is higher than venous shear stress, and different vascular beds have varying responses to altered shear stress and as such, the up and downregulated pathways in HUVECs should be confirmed in an arterial system.

(2) The authors provide convincing evidence of disturbances in shear stress inducing endothelial ferroptosis with assays for impaired lipid peroxidation and increased cell death that was reversed with a ferroptosis inhibitor. However more detailed characterization of ferroptosis with iron accumulation assays, as well as evaluating GPX4 activity as a consequence of the impaired mevalonate pathway, and testing for concomitant apoptosis in addition to ferroptosis would add to the data.

(3) The authors state that KLF2 and KLF4 are not amongst the differentially expressed genes downregulated by reduced shear stress, which is contrary to previous data, where both KLF2 and KLF4 are well studied to be upregulated by physiologic laminar shear stress. While this might be due to the added pressure in their microfluidic system, it also might be due to changes in gene expression over time. In this case, a time course experiment would be needed. It is possible that KLF2, KLF4 and KLF6 are all reduced in low (and high) shear stress and cooperatively regulate the endothelial cell phenotype. Both KLF2 and KLF4 have been shown to be protective against atherosclerosis.

Comments on revisions:

The authors have failed to respond to all the preceding critiques with supporting experimental data. Recommend a reassessment of the initial critiques.

Reviewer #1 (Public review):

The study provides a robust bioinformatic characterization of the evolution of pT181. My main criticism of the work is the lack of experimental validation for the hypotheses proposed by the authors.

Comments on the study:

(1) One potential reason for the decline in pT181 copy number over time may be a high cost associated with the multicopy state. In this sense, it would be interesting if the authors could use (or construct) isogenic strains differing only in the state of the plasmid (multicopy/integrated). With this system, the authors could measure the fitness of the strains in the presence and absence of tetracycline, and they could be able to understand the benefit associated with the plasmid transition. The authors discuss these ideas, but it would be nice to test them.

(2) It would be interesting to know the transfer frequencies of the multicopy mobilizable pT181 plasmid, compared to the transfer frequency of the plasmid integrated into the SSCmec element (which can be co-transferred, integrated in conjugative plasmids, or by transduction).

(3) One important limitation of the study that should be mentioned is that inferring pT181 PCN from whole genome data can be problematic. For example, some DNA extraction methods may underestimate the copy number of small plasmids because the small, circular plasmids are preferentially depleted during the process (see, for example, https://www.nature.com/articles/srep28063).

Reviewer #1 (Public review):

Summary:

PSD95 has long been studied in detail to understand molecular mechanisms of synaptic plasticity as related to specific cell types (excitatory), circuits (visual cortex) and circuit development and function (ocular dominance plasticity ). While much was known about the molecular and cellular details of its function, it remained unclear whether and how it might contribute to the development of specific aspects of visual perception. While overall vision is preserved in PSD95 KO (Knockout) mice, studying natural, visually-guided prey capture behavior revealed robust, yet specific, perturbations to binocular processing during the behavior.

Strengths:

A major strength of the paper is being able to quantify precise measures of the visual aspects versus the motor aspects of prey pursuit. Comparing changes in behavior due to monocular occlusion was particularly revealing that mice indeed employ binocular summation to extract visual cues useful for prey pursuit. This result further suggested that in cases with poor binocular vision, monocular input can improve perceptual and behavioral processes as it does in human subjects with comparable challenges.

The study not only provided a useful finding regarding the function of PSD95, but also outlined a useful general approach toward identifying and quantifying specific deficits in binocular summation. This is likely to broadly impact studies of visual system development, behavior, and neural circuit function. The careful attention to details, observations, and openness about subject variance will also be helpful to those studying specific visual pursuit and natural prey capture behavior in the mouse.

Weaknesses:

Lack of eye movement monitoring and detailed head movement analysis preclude total certainty for the interpretation of observed behaviors.

Reviewer #2 (Public review):

The revised manuscript does a good job of using less definitive language, particularly by adding "possible" qualifiers to several interpretations. This addresses the concern about overstatement.

The main issue raised in the original review, however, remains unresolved. Only two elephant bone specimens at EAK show green-bone breakage interpreted as anthropogenic, and the diagnostic basis for that interpretation is not demonstrated clearly on the EAK material itself. The manuscript discusses a suite of fracture attributes described as diagnostic of dynamic percussive breakage, but these attributes are not explicitly documented on the EAK specimens. Instead, the diagnostic traits are illustrated using material from other Olduvai contexts, and that behavior is then extrapolated to make similar claims at EAK. For a paper making a potentially important behavioral argument, the key diagnostic evidence is not clearly demonstrated at the focal assemblage.

This problem is evident in the presentation of the EAK specimens. In their response, the authors state that one EAK specimen shows "overlapping scars" and constitutes a "long bone flake"; however, these features are not clearly identifiable in the figures or captions as currently presented. The authors state that Figures S21-S23 clearly indicate human agency, including a long bone flake with overlapping scars and a view of the medullary surface, but it is unclear which specimens or surfaces these descriptions refer to. Figure S21 does appear to show green fracture and is described only as an "elephant-sized flat bone fragment with green-bone curvilinear break." Figure S22 shows the same bone and cortical surface in a different orientation, providing no additional information. In Figure S23, I cannot clearly identify a medullary surface or evidence of green-bone fracture from this image. None of these images clearly demonstrates overlapping scars, and the figures would be substantially improved by explicitly identifying the features described in the text. Even if both EAK specimens are accepted as green-broken, they do not demonstrate the co-occurrence of multiple diagnostic fracture traits such as multiple green breaks, large step fractures, hackle marks, and overlapping scars that the authors state is required to attribute dynamic percussive activity to hominins and address equifinality.

I appreciate that the authors are careful to state that spatial association between stone tools and fossils alone does not demonstrate hominin behavior, and that they treat the spatial analyses as supportive rather than decisive. While the association is intriguing, the problem is downstream: spatial association is used to strengthen an interpretation of butchery at EAK that still depends on fracture evidence that is not clearly documented at the assemblage level.

The critique concerning Nyayanga is not addressed in the revision. The manuscript proposes alternative explanations for the Nyayanga material but does not demonstrate why these are more plausible than the interpretation advanced by Plummer et al. (2023). I am not arguing that the Nyayanga material should be accepted as butchery; rather, showing that trampling is possible does not establish it as more probable than cut marks. In contrast, the EAK material is treated as evidence of butchery on the basis of evidence that, in my opinion, is more limited and less clearly demonstrated. Even if this is not the authors' intention, the uneven treatment removes an earlier megafaunal case from the comparison and strengthens the case for interpreting EAK as marking a behavioral shift toward megafaunal butchery by excluding other early cases.

While I remain concerned about how the EAK evidence is documented and interpreted, I think the manuscript is appropriate for publication and will generate useful discussion. Readers can then assess for themselves whether the available evidence supports the strength of the behavioral claims.

Reviewer #1 (Public review):

Summary:

This manuscript follows up previous work from this group using a conditional TCF4 mouse where Cre-expression turns "on" expression of TCF4 to investigate whether postnatal re-expression of TCF4 is effective to correct phenotypes related to Pitt-Hopkins Syndrome (PTHS) in humans. Results may inform gene therapy human PTHS gene therapy efforts on effective developmental windows for gene therapy. The authors demonstrate that re-expression of TCF4, induced by retro-orbital (RO) AAV-PHP.eB-Cre, during 2-4th postnatal week, does not rescue brain or body weight, anxiety-like or nest-building behaviors, but rescues an object location memory task, a measure of cognition. These results are novel and interesting in that they reveal distinct developmental roles for TCF4 in distinct behaviors and suggest that TCF4 plays a role in the mature brain in hippocampal and memory-related plasticity. Results may inform gene therapy design in PTHS.

Strengths:

The results are rigorous and high quality. Multiple methods are used to assess AAV-mediated re-expression of Cre, reactivation of TCF4, and the developmental time course of expression. Multiple behavioral phenotypes and molecular rescue are assessed. Most behavioral phenotypes are reproducible and robust, and it is clear whether a rescue was observed.

Weaknesses:

(1) Although the authors demonstrate the time course and spatial extent of Cre and a Cre-reporter (TdTom) in the brain with the AAV-Cre, it is unclear how many cells are transduced. Similarly, the authors do not measure TCF4 levels with immunohistochemistry or western blot. So the level of protein reactivation is unknown. A possible reason the rescue is incomplete is that the TCF4 protein is not induced in a large % of neurons in specific brain regions that mediate specific behaviors, such as the hippocampus vs. the striatum.

(2) The authors perform bulk qPCR to demonstrate a 20% increase in TCF4 RNA with Cre-mediated activation. It is unclear why the full gene reactivation is not observed. An alternative interpretation of the incomplete rescue of the phenotypes is that full TCF4 expression is required at later developmental time points.

Reviewer #1 (Public review):

Summary:

The authors aimed to develop a translational framework for predicting vaccine reactogenicity by training a penalized ordinal regression model on mouse muscle transcriptomics and applying it across tissues and species to rank human vaccines by their inflammatory potential.

Strengths:

The study addresses an important gap in preclinical vaccine safety assessment. The identification of IL6/JAK/STAT3 signaling as a key pathway implicated in reactogenicity is biologically plausible, and the observation of coordinated changes between muscle and blood compartments supports the biological relevance of the signature. The model achieves near-perfect classification in mouse muscle tissue and successfully identifies Fluad (MF59-adjuvanted) as the most reactogenic among licensed human vaccines, consistent with clinical safety data.

Weaknesses:

The methodological foundation has several concerns. The reactogenicity class definitions rely on PC1 scores with modest variance explained, yet no sensitivity analyses demonstrate robustness to different normalization strategies, feature selection approaches, or dimensionality reduction methods. I suggest performing sensitivity analyses demonstrating that reactogenicity class definitions are robust to alternative normalization methods, feature selection criteria, and dimensionality reduction approaches.

The combined mouse analysis reveals that tissue effects dominate over vaccine-induced variation, and no explicit batch or compartment correction was reported. The authors can apply batch/compartment correction (e.g., SVA) when analyzing combined mouse muscle and blood data, then recompute PCA and downstream analyses.

The central claim regarding cross-species ranking capability is not fully supported. In human blood, the model largely distinguishes Fluad from other vaccines but shows limited separation among non-Fluad formulations, with many pairwise comparisons yielding non-significant adjusted p-values. This pattern suggests the model may be tuned to detect large inflammatory magnitudes-likely a consequence of training on extreme stimuli such as LPS and whole-cell pertussis-rather than capturing the finer gradations relevant for distinguishing licensed vaccines with moderate reactogenicity profiles. I highly suggest retraining the model, excluding extreme stimuli (LPS, Pentavac), to evaluate whether mid-range separations among licensed vaccines can be recovered.

Impact:

While the conceptual framework is promising, the current evidence does not convincingly demonstrate that the model can rank vaccines beyond identifying highly inflammatory outliers. The utility for preclinical assessment of novel vaccine candidates with moderate reactogenicity profiles remains uncertain.

Reviewer #1 (Public review):

This manuscript by Toczyski and colleagues explores the role of ubiquitin-dependent degradation in the co-regulation between pro- and anti-apoptotic proteins. The binding of the pro-apoptotic sensor Bim to BCL2 anti-apoptotic proteins sequesters it into inactive complexes, inhibiting BCL2 members but also preventing Bim from activating the apoptotic executors BAX and BAK. The authors now suggest that the E3 ubiquitin ligase Cul5-Wsb2 targets Bim turnover while in complex with BLC2 members. The authors reveal the importance of WSB2 in apoptosis of neuroblastoma cell lines, highlighting the importance of Wsb2 as a cancer biomarker. In sum, this study identifies Bim as a novel Wsb2 target and suggests a novel co-receptor mechanism using BCL-2 members as bridging factors, thus adding a novel mechanistic layer to the apoptosis repressor role of Wsb2. Their experimental approach is sound, and in most cases, the conclusions are justified. However, whether Cul5-Wsb2 targets Bim via BLC2 anti-apoptotic members would require further analysis.

Major comments:

(1) They find that Wsb2 or Cul5 downregulation increases the levels of Puma and Bim isoforms, and that Wsb2 strongly interacts with all Bim isoforms. Moreover, Wsb2 regulates Bim turnover, especially visible for Bim-EL, and controls Bim-L ubiquitylation. Finally, Figure 2E suggests that Wsb2-Bim interaction is bridged by Bcl-xL, and they identify the domain in Bcl-xL/Wsb2 responsible for their binding in Figure 4A-E. However, Figure 4F shows only a mild decrease between Bim-EL and HA-Wsb2EEE, which is inconsistent with their model. This important gap should be backed up by further experimental evidence. For example, by performing (a) coIP studies between Bim and Wsb2 in the presence of Bcl-xlAAA and (b) Bim stability and ubiquitylation analysis in the presence of either Bcl-xlAAA or Wsb2EEE.

(2) The manuscript lacks quantifications and statistical analysis in most figures, which are particularly important for Figure 1D - especially regarding the upregulation of Puma and Bim isoforms upon downregulation of Cul5 and Wsb2, for Fig 3A - also including statistical analyses of Bim1 stability in presence or absence of proteasomal inhibitors, and for Figure 4D, F, especially regarding the interaction of Bim-EL- with WT and mutant Bcl-xL in 4D and with WT and mutant Wsb2 in 4F.

(3) The localization of BCL2 family members at the mitochondrial outer membrane is a crucial step in the implementation of apoptosis, and BCL2 members recruit Bim to the OM. Despite their finding suggesting that Bim insertion into the OM might be dispensable for interaction with Bim, the interaction was abolished by BH3-mimetics that disrupt Bcl-xL interaction with BIM. This suggests that Wsb2 interacts with Bim at the mitochondrial surface. Therefore, it would be interesting to investigate the sub-cellular localization Bim and WSB2 with and without ABT-263.

(4) Wsb2 mildly interacts with Bcl-xL and with Mcl1, but does not interact with Bcl-w or Bcl2. However, they show that Wsb2 recognizes Bcl-xl through a motif conserved between Bcl-xl, Bcl-w and Bcl2. Therefore, it would be helpful to precipitate Bcl-w or Bcl2 and check interaction with Wsb2.

Reviewer #1 (Public review):

Kotzadimitriou et al. investigate how synaptotagmin-7 (syt7) contributes to short-term plasticity at cortical glutamatergic synapses. Using quantal-level iGluSnFR imaging and failure-based analyses at single boutons, the authors distinguish between synchronous and asynchronous glutamate release across boutons with differing baseline efficacy. They show that knocking out syt7 abolishes facilitation of synchronous release while leaving asynchronous facilitation largely intact, although reduced in magnitude. Furthermore, they argue that synchronous and asynchronous events arise from functionally distinct vesicle pools. The manuscript concludes that syt7 is essential for the facilitation of synchronous release, while other calcium sensors govern asynchronous release.

Strengths:

(1) The use of iGluSnFR provides a robust readout of single-synapse activity. Unlike traditional ephys methods that average the activity of thousands of synapses (which may mask the facilitation of low Pr synapses), the authors employ quantal imaging to analyze thousands of individual boutons and stratify them by efficacy. The representative images and traces in Figure 1 are of high quality, and the quantal analysis demonstrating multiple quantal peaks aligns well with previously published work (Mendonca et al., 2022; Wang et al., 2022).

(2) The failure-based analysis is thoughtfully implemented. By isolating trials in which no release occurred, the authors effectively separate facilitation from depletion, strengthening their central argument that syt7 is required for facilitation independent of vesicle depletion.

(3) The proposed model (depicted in Figure 7) is interesting and may reconcile the contradictory roles attributed to syt7, as described by others in the field. Specifically, the authors provide data to address syt7's potential function in facilitation, asynchronous release, and replenishment. However, to further support their model, which argues that "multiple Ca2+ sensors have both unique and overlapping roles in regulating synaptic plasticity," additional experiments are needed (see point 2 below).

Weaknesses:

(1) While the authors use cultures from syt7 knockout mice (and wild-type controls), there are no acute rescue experiments (e.g., syt7 viral transduction in KO cultures) or checks for compensatory changes in other proteins. Previous studies (Bacaj et al., 2013; Jackman et al., 2016) have utilized viral rescues to confirm specificity. Without such experiments, it remains theoretically possible that the chronic loss of syt7 leads to downregulation of another protein essential for facilitation. At a minimum, the authors should perform rescue experiments for at least some of their findings. Additionally, western blots for syt1 and syt7 should be conducted to confirm that their knockout is specific to syt7.

(2) The manuscript acknowledges the possible roles of Doc2a and syt3 but fails to address them experimentally. Recent work (Wu et al., 2024; Weingarten et al., 2024) has identified Doc2a as the primary sensor for asynchronous release. Even if its expression in cortical cultures remains unconfirmed (as claimed by the authors), they should, at the very least, perform Western blots for Doc2a and syt3 in both wild-type (to determine basal expression levels) and syt7 knockout cultures. Without analyzing the levels of these proteins, the mechanism/model behind the "remaining" asynchronous release remains speculative. Is it possible that these other calcium sensors are upregulated in their syt7 KO cultures and could instead explain their results?

Test

Reviewer #1 (Public review):

Summary:

This preprint investigates the molecular mechanism by which warm temperature induces female-to-male sex reversal in the ricefield eel (Monopterus albus), a protogynous hermaphroditic fish of significant aquacultural value in China. The study identifies Trpv4 - a temperature-sensitive Ca²⁺ channel - as a putative thermosensor linking environmental temperature to sex determination. The authors propose that Trpv4 causes Ca²⁺ influx, leading to activation of Stat3 (pStat3). pStat3 then transcriptionally upregulates the histone demethylase Kdm6b (aka Jmjd3), leading to increased dmrt1 gene expression and ovo-testes development. This work aims to bridge ecological cues with molecular and epigenetic regulators of sex change and has potential implications for sex control in aquaculture.

Strengths:

(1) This study proposes the first mechanistic pathway linking thermal cues to natural sex reversal in adult ricefield eel, extending the temperature-dependent sex determination paradigm beyond embryonic reptiles and saltwater fish

(2) The findings could have applications for aquaculture, where skewed sex ratios apparently limit breeding efficiency

Weaknesses:

Although the revised manuscript represents an improvement over the original version, substantial weaknesses remain.

Scientific Concerns

(1) Western blot normalization and exposure: The loading controls (GAPDH) in Fig. S3C appear overexposed, as do several Foxl2 blots. Because these signals are likely outside the linear range, I am not convinced that normalization is reliable. This raises concerns about the validity of the quantified results.

(2) Antibody validation and referencing (Line 776): The authors need to refer explicitly to figures demonstrating antibody validation. At present, these data are provided only as a supplementary file that is not cited in the manuscript. In addition, the Sox9a antibody appears to yield indistinguishable signals in control and RNAi conditions, suggesting that it may not recognize eel Sox9a. This issue is not addressed by the authors. Furthermore, antibody validation Western blots should be quantified.

(3) Unclear sample sizes (N values): Sample sizes remain unclear for several figures:

(a) Fig. 3F - No N value is provided. Each graph shows three data points; does this indicate that only three samples were quantified? If ten samples were collected, why were all not quantified?

(b) Fig. 4 - No N values are reported.

(c) Fig. 5A - Again, only three data points are shown per group, despite the apparent availability of twelve samples. The rationale for this discrepancy is not explained.

(4) qRT-PCR normalization: The manuscript does not specify the reference gene(s) used for qRT-PCR normalization. Although expression levels are reported as "relative," neither the identity of the reference gene(s) nor the justification for their selection is provided.

(5) Specificity of key antibodies: While the authors have made some effort to validate anti-Amh, anti-Sox9, and anti-Dmrt antibodies, the results remain incomplete. The Amh and Dmrt antibodies detect reduced protein levels following knockdown of their respective targets, which is encouraging. However, the Sox9a antibody shows no difference between control and RNAi conditions, suggesting it does not recognize eel Sox9. This is not acknowledged in the manuscript. In addition, no validation data are presented for Foxl2. Antibody validation data must be clearly referenced in the main text and presented in an interpretable and quantitative manner.

(6) Immunofluorescence data quality: The immunofluorescence images remain difficult to interpret. I strongly encourage the authors to enlarge the image panels and to present monochrome images (white signal on black background). The current presentation severely limits interpretability.

(7) Unreferenced supplementary figure: Fig. S4 is included in the submission but is not referenced anywhere in the manuscript text.

(8) Fig. 5B image resolution: The micrographs in Fig. 5B are too small to allow meaningful evaluation of the data.

(9) Unexplained data inclusion (Fig. 5E): Fig. 5E includes a pERK blot that is not mentioned in the Results section. The rationale for including these data is unclear.

(10) Poor blot quality (Fig. S3C): The blots in Fig. S3C exhibit high background and overexposure. I am concerned about the reliability of the quantification shown in panel D.

(11) Poor blot quality (Fig. S5G): The Stat3 blots in Fig. S5G contain numerous white artifacts, raising concerns about their suitability for normalization in panel H.

(12) Missing controls (Fig. 6E): Fig. 6E lacks controls for HO-3867 and Colivelin treatments alone. Without these controls, it is not possible to determine whether the reported effects are meaningful.

(13) Graphical presentation: The use of a light blue-to-pink gradient in bar graphs throughout the manuscript does not aid interpretation. I recommend using more distinct colors (e.g., red, orange, green, blue, purple, gray, black) to improve clarity. In summary, the interpretation of the study remains limited by persistent issues related to data presentation, image quality, and reagent specificity.

Reviewer #1 (Public review):

Summary:

Abdelmageed et al. investigate age-related changes in the subcellular localization of DNA polymerase kappa (POLK) in the brains of mice. POLK has been actively investigated for its role in translesion DNA synthesis and involvement in other DNA repair pathways in proliferating cells, very little is known about POLK in a tissue-specific context or let alone in post-mitotic cells. The authors investigated POLK subcellular distribution in the brains of young, middle-aged, and old mice via immunoblotting of fractioned tissue extracts and immunofluorescence (IF). Immunoblotting revealed a progressive decrease in the abundance of nuclear POLK, while cytoplasmic POLK levels concomitantly increased. Similar findings were present when IF was performed on brain sections. Further IF studies of cingulate cortex (Cg1), motor cortex (M1, M2), and somatosensory (S1) cortical regions all showed an age-related decline in nuclear POLK. Nuclear speckles of POLK decrease in each region, meanwhile the number of cytoplasmic POLK granules decreases in all four regions, but granule size is increasing. The authors report similar findings for REV1, another Y-family DNA polymerase.

The authors then investigate the colocalization of POLK with other DNA damage response (DDR) proteins in either pyramidal neurons or inhibitory interneurons. At 18 months of age, DNA damage marker gH2AX demonstrated colocalization with nuclear POLK, while strong colocalization of POLK and 8-oxo-dG was present in geriatric mice. The authors find that cytoplasmic POLK granules colocalize with stress granule marker G3BP1, suggesting that the accumulated POLK ends up in the lysosome.

Brain regions were further stained to identify POLK patterns in NeuN+ neurons, GABAergic neurons, and other non-neuronal cell types present in the cortex. Microglia associated with pyramidal neurons or inhibitory interneurons were found to have higher abundance of cytoplasmic POLK. The authors also report that POLK localization can be regulated by neuronal activity induced by Kainic acid treatment. Lastly, the authors suggest that POLK could serve as an aging clock for brain tissue, but POLK deserves further characterization and correlation to functional changes before being considered for a biomarker.

Strengths:

Investigation of TLS polymerases in specific tissues and in post-mitotic cells is largely understudied. The potential changes in sub cellular localization of POLK and potentially other TLS polymerases opens up many questions about DNA repair and damage tolerance in the brain and how it can change with age.

Weaknesses:

The work is quite novel and interesting, and the authors do suggest some potentially interesting roles for POLK in the brain, but these are in of themselves a bit speculative. The majority of the findings of this paper draw upon findings from POLK antibody and its presumed specificity for POLK. However, this antibody has not been fully validated and would benefit from further validation of the different band sizes. More mechanistic investigation is needed before POLK could be considered as a brain aging clock but does not preclude the potential for using POLK as a biological "dating" system for the brain.

Comments on revisions:

The revised manuscript is suitably improved and addresses reviewer comments.

Reviewer #1 (Public review):

Summary:

GID/CTLH-type RING ligases are huge multi-protein complexes that play an important role in protein ubiquitylation. The subunits of its core complex are distinct and form a defined structural arrangement, but there can be variations in subunit composition, such as exchange of RanBP9 and RanBP10. In this study, van gen Hassend and Schindelin provide new crystal structures of (parts of) key subunits and use those structures to elucidate the molecular details of the pairwise binding between those subunits. They identify key residues that mediate binding partner specificity. Using in vitro binding assays with purified protein, they show that altering those residues can switch specificity to a different binding partner.

Strengths:

This is a technically demanding study that sheds light on an interesting structural biology problem in residue-level detail. The combination of crystallization, structural modeling, and binding assays with purified mutant proteins is elegant and, in my eyes, convincing.

Weaknesses:

I mainly have some suggestions for further clarification, especially for a broad audience beyond the structural biology community.

(1) The authors establish what they call an 'engineering toolkit' for the controlled assembly of alternative compositions of the GID complex. The mutagenesis results are great for the specific questions asked in this manuscript. It would be great if they could elaborate on the more general significance of this 'toolkit' - is there anything from a technical point of view that can be generalized? Is there a biological interest in altering the ring composition for functional studies?

(2) Along the same lines, the mutagenesis required to rewire Twa1 binding was very complex (8 mutations). While this is impressive work, the 'big picture conclusion' from this part is not as clear as for the simpler RanBP9/10. It would be great if the authors could provide more context as to what this is useful for (e.g., potential for in vivo or in vitro functional studies, maybe even with clinical significance?)

(3) For many new crystal structures, the authors used truncated, fused, or otherwise modified versions of the proteins for technical reasons. It would be helpful if the authors could provide reasoning why those modifications are unlikely to change the conclusions of those experiments compared to the full-length proteins (which are challenging to work with for technical reasons). For instance, could the authors use folding prediction (AlphaFold) that incorporates information of their resolved structures and predicts the impact of the omitted parts of the proteins? The authors used AlphaFold for some aspects of the study, which could be expanded.

Reviewer #1 (Public review):

Summary:

This study investigates the molecular mechanisms allowing the KSM mite to infest tea plants, a host that is toxic to the closely related TSSM mite due to high concentrations of phenolic catechins. The authors utilize a comparative approach involving tea-adapted KSM, non-adapted KSM, and TSSM to assess behavioral avoidance and physiological tolerance to catechins. The main finding is that tea-adapted KSM possesses a specific detoxification mechanism mediated by an enzyme, TkDOG15, which was acquired via horizontal gene transfer. The study demonstrates that adaptation is a two-step process: (1) structural refinement of the TkDOG15 enzyme through amino acid substitutions that enhance enzymatic efficiency against catechins, and (2) significant transcriptional upregulation of this gene in response to tea feeding. This enzymatic adaptation allows the mites to cleave and detoxify tea catechins, enabling survival on a toxic host plant.

Strengths:

A multiomics approach (transcriptomics and proteomics) provided a compelling cross-validation of its findings. Functional bioassays, such as RNAi and recombinant enzyme assays, demonstrated that the adapted mite has higher activity against catechins via TkDOG15. Other methodologies, like feeding assay using a parafilm-covered leaf disc, were effective in avoiding contact chemosensation.

Weaknesses:

Although TkDOG15 is assumed to "detoxify" catechins by ring cleavage, the study doesn't identify or characterize the breakdown metabolic products. If the metabolites are indeed non-toxic compared to the parent catechins, that would strengthen the detoxification hypothesis. Also, the transcriptomic and proteomic analyses identified other potential detoxification enzymes, such as CCEs, UGTs, and ABC (Supplementary Tables 3-1 & 3-2), which were also upregulated. The manuscript focuses almost exclusively on TkDOG15, potentially overlooking a multigenic adaptation mechanism, where these other enzymes might play synergistic roles, although it was mentioned in the discussion section.

Reviewer #1 (Public review):

Summary:

This manuscript presents high-resolution cryoEM structures of VPS34-complex II bound to Rab5A at 3.2A resolution. The Williams group previously reported the structure of VPS34 complex II bound to Rab5A on liposomes using tomography, and therefore, the previous structure, although very informative, was at lower resolution.

The first new structure they present is of the 'REIE>AAAA' mutant complex bound to RAB5A. The structure resembles the previously determined one, except that an additional molecule of RAB5A was observed bound to the complex in a new position, interacting with the solenoid of VPS15.

Although this second binding site exhibited reduced occupancy of RAB5A in the structure, the authors determined an additional structure in which the primary binding site was mutated to prevent RAB5A binding ('REIE>ERIR'). In this structure, there is no RAB5A bound to the primary binding site on VPS34, but the RAB5A bound to VPS15 now has strong density. The authors note that the way in which RAB5A interacts with each site is distinct, though both interfaces involve the switch regions. The authors confirm the location of this additional binding site using HDX-MS.

The authors then determine multiple structures of the wild-type complex bound to RAB5A from a single sample, as they use 3D classifications to separate out versions of the complex bound to 0, 1, or 2 copies of RAB5A. Overall, the structure of VPS34-Complex II does not change between the different states, and the data indicate that both RAB5A binding sites can be occupied at the same time.

The authors then design a new mutant form of the complex (SHMIT>DDMIE) that is expected to disrupt the interaction at the secondary site between VPS15 and RAB5A. This mutation had a minor impact on the Kd for RAB5A binding, but when combined with the REIE>ERIR mutation of the primary binding site, RAB5A binding to the complex was abolished.

Comparison of sequences across species indicated that the RAB5A binding site on VPS15 was conserved in yeast, while the RAB5A binding site on VPS34 is not.

The authors tested the impact of a corresponding yeast Vps15 mutation (SHLITY>DDLIEY) predicted to disrupt interaction with yeast Rab5/Vps21, and found that this mutant Vps15 protein was mislocalized and caused defective CPY processing.

The authors then compare these structures of the RAB5A-class II complex to recently published structures from the Hurley group of the RAB1A-class I complex, and find that in both complexes the Rab protein is bound to the VPS34 binding site in a somewhat similar manner. However, a key difference is that the position of VPS34 is slightly different in the two complexes because of the unique ATL14L and UVRAG subunits in the class I and class II complexes, respectively. This difference creates a different RAB binding pocket that explains the difference in RAB specificity between the two complexes.

Finally, the higher resolution structures enable the authors to now model portions of BECLIN1 and UVRAG that were not previously modeled in the cryoET structure.

Strengths:

Overall, I found this to be an interesting and comprehensive study of the structural basis for the interaction of RAB5A with VPS34-complex II. The authors have performed experiments to validate their structural interpretations, and they present a clear and thorough comparative analysis of the Rab binding sites in the two different VPS34 complexes. The result is a much better understanding of how two different Rab GTPases specifically recruit two different, but highly similar complexes to the membrane surface.

Weaknesses:

No significant weaknesses were noted.

Joint Public review:

Summary

This interesting work by Shuhao Li and colleagues suggests that developmental sleep and feeding behavior in larval flies is genetically programmed to prepare the animal for adult contingencies, such as in the case of flies living in harsh ecological environments, such as deserts. Thus, the work proposes that desert-dwelling flies such as Drosophila mojavensis sleep less and feed more than D. melanogaster as larvae, which allows them to feed less and sleep more as adults in the harsh desert conditions where they live. The authors argue that this is evidence for developmental sleep reallocation, which helps the adult flies survive in the desert. In general, their results support this compelling hypothesis, so this work provides a new perspective on how sleep might be differentially programmed across developmental stages according to the requirements of an ecological niche. This work is particularly innovative for several reasons. First, it extends the Drosophila sleep field beyond D. melanogaster and directly addresses questions about the evolution of sleep that remain largely unexplored. Second, it investigates the possibility that changes in sleep across development may be adaptive, rather than sleep being a static trait. Overall, this work opens new avenues of research, effectively bridges the fields of sleep biology and evolutionary ecology, and should be of broad interest to a general readership. The manuscript is scientifically sound and clearly written for a generalist audience.

There are, however, two important weaknesses that should be addressed. The first is the implicit assumption that all observed behavioral differences are adaptive; this would benefit from a more cautious framing. Second, the manuscript would be strengthened by a more detailed discussion, and potentially additional data, regarding the ecological differences experienced by D. mojavensis and D. melanogaster at distinct life-cycle stages.

Strengths:

(1) The study astutely uses desert Drosophila species as models to understand how sleep is optimized in a challenging environment. The manuscript is rigorous, experiments are well controlled, the work is very clearly presented, and the results support the main conclusions, which are quite exciting.

(2) The manuscript examines previously unexplored sleep differences in a non-melanogaster species.

(3) The study provides evidence that selective pressure can be restricted to specific developmental stages.

(4) This work offers evolutionary insights into the trade-offs between sleep and feeding across development.

Weaknesses

(1) The authors should soften interpretations so that it is not assumed that any observed difference between mojavensis and melanogaster is necessarily adaptive, or evolved due to food availability or temperature stress.

(2) The study relies on comparisons and correlations. While it seems likely that the observed differences in sleep explain the increased food consumption and energy storage in the larvae of desert flies, demonstrating this through sleep manipulation would strengthen the authors' conclusions.

(3) The question arises regarding whether transiently quiescent larvae are always really sleeping, and whether it is appropriate to treat sleep as a stochastic population-level phenomenon rather than as an individual trait.

(4) The manuscript would benefit from comparative analysis beyond mojavensis and melanogaster.

(5) A deeper discussion of the ecological differences between the 2 Drosophila species would place the results in a broader context.

(6) The feeding parameters used in adults and larvae measure different aspects of feeding, confounding comparisons.

Reviewer #1 (Public review):

Summary:

Despite accumulating prior studies on the expressions of AVP and AVPR1a in the brain, a detailed, gender-specific mapping of AVP/AVPR1a neuronal nodes has been lacking. Using RNAscope, a cutting-edge technology that detects single RNA transcripts, the authors created a comprehensive neuroanatomical atlas of Avp and Avpr1a in male and female brains.

Strengths:

This well-executed study provides valuable new insights into gender differences in the distribution of Avp and Avpr1a. The atlas is an important resource for the neuroscience community.

The authors have adequately addressed all of my concerns. I have no further questions or concerns.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors describe the generation of a Drosophila model of RVCL-S by disrupting the fly TREX1 ortholog cg3165 and by expressing human TREX1 transgenes (WT and the RVCL-S-associated V235Gfs variant). They evaluate organismal phenotypes using OCT-based cardiac imaging, climbing assays, and lifespan analysis. The authors show that loss of cg3165 compromises heart performance and locomotion, and that expression of human TREX1 partially rescues these phenotypes. They further report modest differences between WT and mutant hTREX1 under overexpression conditions. The study aims to establish Drosophila as an in vivo model for RVCL-S biology and future therapeutic testing.

Strengths:

(1) The manuscript addresses an understudied monogenic vascular disease where animal models are scarce.

(2) The use of OCT imaging to quantify fly cardiac performance is technically strong and may be useful for broader applications.

(3) The authors generated both cg3165 null mutants and humanized transgenes at a defined genomic landing site.

(4) The study provided initial in vivo evidence that human TREX1 truncation variants can induce functional impairments in flies.

Weaknesses:

(1) Limited mechanistic insight.

RVCL-S pathogenesis is strongly linked to mislocalization of truncated TREX1, DNA damage accumulation, and endothelial/podocyte cellular senescence. The current manuscript does not examine any cellular, molecular, or mechanistic readouts - e.g. DNA damage markers, TREX1 subcellular localization in fly tissues, oxidative stress, apoptosis, or senescence-related pathways. As a result, the model remains largely phenotypic and descriptive.

To strengthen the impact, the authors should provide at least one mechanistic assay demonstrating that the humanized TREX1 variants induce expected molecular consequences in vivo.

(2) The distinction between WT and RVCL-S TREX1 variants is modest.

In the cg3165 rescue experiments, the authors do not observe differences between hTREX1 and the V235Gfs variant (e.g., Figure 3A-B). Phenotypic differences only emerge under ubiquitous overexpression, raising two issues:

(i) It is unclear whether these differences reflect disease-relevant biology or artifacts of strong Act5C-driven expression.

(ii) The authors conclude that the model captures RVCL-S pathogenicity, yet the data do not robustly separate WT from mutant TREX1 under physiological expression levels.

The authors should clarify these limitations and consider additional data or explanations to support the claim that the model distinguishes WT vs RVCL-S variants.

(3) Heart phenotypes are presented as vascular defects without sufficient justification.

RVCL-S is a small-vessel vasculopathy, but the Drosophila heart is a contractile tube without an endothelial lining. The authors refer to "vascular integrity restoration," but the Drosophila heart lacks vasculature.

The manuscript would benefit from careful wording and from a discussion of how the fly heart phenotypes relate to RVCL-S microvascular pathology.

(4) General absence of tissue-level or cellular imaging.

No images of fly hearts, brains, eyes, or other tissues are shown. TREX1 nuclear mislocalization is a hallmark of RVCL-S, yet no localization studies are included in this manuscript.

Adding one or two imaging experiments demonstrating TREX1 localization or tissue pathology would greatly enhance confidence in the model.

Reviewer #1 (Public review):

Summary:

The manuscript titled, "Sleep-Wake Transitions Are Impaired in the AppNL-G-F Mouse Model of Early Onset Alzheimer's Disease", is about a study of sleep/wake phenomena in a knockin mouse strain carrying "three mutations in the human App gene associated with elevated risk for early onset AD". Traditional, in-depth characterization of sleep/wake states, EEG parameters, and response to sleep loss are employed to provide evidence, "supporting the use of this strain as a model to investigate interventions that mitigate AD burden during early disease stages". The sleep/wake findings of earlier studies (especially Maezono et al., 2020, as noted by the authors) were extended by several important, genotype-related observations, including age-related hyperactivity onset that is typically associated with increased arousal, a normal response to loss of sleep and to multiple sleep latency testing, and a stronger AD-like phenotype in females. The authors conclude that the AppNL-G-F mice demonstrate many of the human AD prodromal symptoms and suggest that this strain may serve as a model for prodromal AD in humans, confirming the earlier results and conclusions of Maezono et al. Finally, based on state bout frequency and duration analyses, it is suggested that the AppNL-G-F mice may develop disruptions in mechanism(s) involved in state transition.

Strengths:

The study appears to have been, technically, rigorously conducted with high quality, in-depth traditional assessment of both state and EEG characteristics, with the concordant addition of activity and temperature. The major strengths of this study derive from observations that the AppNL-G-F mice: (1) are more hyperactive in association with decreased transitions between states; (2) maintain a normal response to sleep deprivation and have normal MSLT results; and (3) display a sex specific, "stronger" insomnia-like effect of the knockin in females.

Weaknesses:

The weaknesses stem from the study's impact being limited due to its being largely confirmatory of the Maezono et al. study, with advances of importance to a potentially more focused field. Further, the authors conclude that AppNL-G-F mice have disrupted mechanism(s) responsible for state transition; however, these were not directly examined. The rationale for this conclusion is stated by the authors as based on the observations that bouts of both W and NREM tend to be longer in duration and decreased in frequency in AppNL-G-F mice. Although altered mechanism(s) of state transition (it is not clear what mechanisms are referenced here) cannot be ruled out, other explanations might be considered. For example, increased arousal in association with hyperactivity would be expected to result in increased duration of W bouts during the active phase. This would also predictably result in greater sleep pressure that is typically associated with more consolidated NREM bouts, consistent with the observations of bout duration and frequency.

Reviewer #1 (Public review):

While the revised manuscript includes additional methodological details and a supplementary comparison with conventional NMF, it would be great if the authors could add the point below as limitations in the manuscript or change the title and abstract accordingly, since core issues remain:

(1) The study claims to evaluate rehabilitation outcomes without demonstrating that patients actually improved functionally

(2) The comparison with existing methods lacks the quantitative rigor needed to establish superiority

(3) The added value of this complex framework over much simpler alternatives has not been demonstrated

The strength of evidence supporting the main claims remains incomplete. I would encourage the authors to consider discussing these points

(1) including or adding a limitation section about functional outcome measures that go beyond clinical scale scores, (2) providing/discussing quantitative benchmarks showing their method outperforms alternatives on specific, predefined metrics, and (3) clarifying the clinical pathway by which these biomarkers would inform treatment decisions.

There are specific, relatively minor points, that require attention

The authors write: "we did not focus on such complementary evidence in this study." This is a weakness for a paper claiming to provide "biomarkers of therapeutic responsiveness." The FMA-UE threshold defines responders, but there's no independent validation that patients actually functioned better in daily life. Can you please clarify?

Maybe I missed the exact point about this, but with the added NMF plot, the authors list 'lower dimensionality' among their framework's advantages, but the basis for this claim is not clear because given that 12 network components were extracted compared to 11 "conventional" synergies. Can you please clarify, as it is not clear. You claim 'lower dimensionality' as an advantage of the proposed framework (in the Supplementary Materials), yet you extracted 12 components (5 redundant + 7 synergistic networks) compared to 11 synergies from the conventional NMF approach, which does not support a clinical / outcome advantage of this method. Please clarify.

Reviewer #1 (Public review):

Summary:

The study by Wu et al. uses endogenous bruchpilot expression in a cell-type-specific manner to assess synaptic heterogeneity in adult Drosophila melanogaster mushroom body output neurons. The authors performed genomic on locus tagging of the presynaptic scaffold protein bruchpilot (brp) with one part of splitGFP (GFP11) using the CRISPR/Cas9 methodology and co-expressed the other part of splitGFP (GFP1-10) using the GAL4/UAS system. Upon expression of both parts of splitGFP, fluorescent GFP is assembled at the C-terminus of brp, exactly where brp is endogenously expressed in active zones. For manageable analysis, a high-throughput pipeline was developed. This analysis evaluated parameters like location of brp clusters, volume of clusters, and cluster intensity as a direct measure of the relative amount of brp expression levels on site using publicly available 3D analysis tools that are integrated in Fiji. Analysis was conducted for different mushroom body cell types in different mushroom body lobes using various specific GAL4 drivers. Further validation was provided by extending analysis to R8 photoreceptors that reside in the fly medulla. To test this new method of synapse assessment, Wu et al. performed an associative learning experiment in which an odor was paired with an aversive stimulus and found that in a specific time frame after conditioning, the new analysis solidly revealed changes in brp levels at specific synapses that are associated with aversive learning. Additionally, brp levels were assessed in R8 photoreceptor terminals upon extended exposure to light.

Strengths:

Expression of splitGFP bound to brp enables intensity analysis of brp expression levels as exactly one GFP molecule is expressed per brp. This is a great tool for synapse assessment. This tool can be widely used for any synapse as long as driver lines are available to co-express the other part of splitGFP in a cell-type-specific manner. As neuropils and thus brp label can be extremely dense, the analysis pipeline developed here is very useful and important. The authors have chosen an exceptionally dense neuropil - the mushroom bodies - for their analysis and compellingly show that brp assessment can be achieved even with such densely packed active zones. The result that brp levels change upon associative learning in an experiment with odor presentation paired with punishment is likewise compelling and strongly suggests that the tool and pipeline developed here can be used in an in vivo context. Thus, the tool and its uses have the potential to fundamentally advance protein analysis not only at the synapse but especially there.

Weaknesses:

The weaknesses I perceived originally were satisfactorily explained and refuted.

Reviewer #1 (Public review):

Summary:

This study focuses on characterizing the EEG correlates of item-specific proportion congruency effects. Two types of learned associations are characterized, one being associations between stimulus features and control states (SC), and the other being stimulus features and responses (SR). Decoding methods are used to identify time-resolved SC and SR correlates, which are used to test properties of their dynamics.

The conclusion is reached that SC and SR associations can independently and simultaneously guide behavior. This conclusion is based on results showing SC and SR correlates are: (1) not entirely overlapping in cross-decoding; (2) simultaneously observed on average over trials in overlapping time bins; (3) independently correlate with RT; and (4) have a positive within-trial correlation.

Strengths:

Fearless, creative use of EEG decoding to test tricky hypotheses regarding latent associations.

Nice idea to orthogonalize ISPC condition (MC/MI) from stimulus features.

Weaknesses:

I still have my concern from the first round that the decoders are overfit to temporally structured noise. As I wrote before, the SC and SR classes are highly confounded with phase (chunk of session). I do not see how the control analyses conducted in the revision adequately deal with this issue.

In the figures, there are several hints that these decoders are biased. Unfortunately, the figures are also constructed in such a way that hides or diminishes the salience of the clues of bias. This bias and lack of transparency discourage trust in the methods and results.

I have two main suggestions:

(1) Run a new experiment with a design that properly supports this question.

I don't make this suggestion lightly, and I understand that it may not be feasible to implement given constraints; but I feel that this suggestion is warranted. The desired inferences rely on successful identification of SC and SR representations. Solidly identifying SC and SR representations necessitates an experimental design wherein these variables are sufficiently orthogonalized, within-subject, from temporally structured noise. The experimental design reported in this paper unfortunately does not meet this bar, in my opinion (and the opinion of a colleague I solicited).

An adequate design would have enough phases to properly support "cross-phase" cross-validation. Deconfounding temporal noise is a basic requirement for decoding analyses of EEG and fMRI data (see e.g., leave-one-run-out CV that is effectively necessary in fMRI; in my experience, EEG is not much different, when the decoded classes are blocked in time, as here). In a journal with a typical acceptance-based review process, this would be grounds for rejection.

Please note that this issue of decoder bias would seem to weaken the rest of the downstream analyses that are based on the decoded values. For instance, if the decoders are biased, in the within-trial correlation analysis, how can we be sure that co-fluctuations along certain dimensions within their projected values are driven by signal or noise? A similar issue clouds the LMM decoding-RT correlations.

(2) Increase transparency in the reporting of results throughout main text.

Please do not truncate stimulus-aligned timecourses at time=0. Displaying the baseline period is very useful to identify bias, that is, to verify that stimulus-dependent conditions cannot be decoded pre-stimulus. Bias is most expected to be revealed in the baseline interval when the data are NOT baseline-corrected, which is why I previously asked to see the results omitting baseline correction. (But also note that if the decoders are biased, baseline-correcting would not remove this bias; instead, it would spread it across the rest of the epoch, while the baseline interval would, on average, be centered at zero.)

Please use a more standard p-value correction threshold, rather than Bonferroni-corrected p<0.001. This threshold is unusually conservative for this type of study. And yet, despite this conservativeness, stimulus-evoked information can be decoded from nearly every time bin, including at t=0. This does not encourage trust in the accuracy of these p-values. Instead, I suggest using permutation-based cluster correction, with corrected p<0.05. This is much more standard and would therefore allow for better comparison to many other studies.

I don't think these things should be done as control analyses, tucked away in the supplemental materials, but instead should be done as a part of the figures in the main text -- including decoding, RSA, cross-trial correlations, and RT correlations.

Other issues:

Regarding the analysis of the within-trial correlation of RSA betas, and "Cai 2019" bias:

The correction that authors perform in the revision -- estimating the correlation within the baseline time interval and subtracting this estimate from subsequent timepoints -- assumes that the "Cai 2019" bias is stationary. This is a fairly strong assumption, however, as this bias depends not only on the design matrix, but also on the structure of the noise (see the Cai paper), which can be non-stationary. No data were provided in support of stationarity. It seems safer and potentially more realistic to assume non-stationarity.

This analysis was included in the supplemental material. However, given that the correlation analysis presented in the Results is subject to the "Cai 2019" bias, it would seem to be more appropriate to replace that analysis, rather than supplement it.

Regardless, this seems to be a moot issue, given that the underlying decoders seem to be overfit to temporally structured noise (see point above regarding weakening of downstream analyses based on decoder bias).

Outliers and t-values:

More outliers with beta coefficients could be because the original SD estimates from the t-values are influenced more by extreme values. When you use a threshold on the median absolute deviation instead of mean +/-SD, do you still get more outliers with beta coefficients vs t-values?

Random slopes:

Were random slopes (by subject) for all within-subject variables included in the LMMs? If not, please include them, and report this in the Methods.

Reviewer #1 (Public review):

Summary:

Using high-precision eyetracking, the authors measure foveolar sensitivity modulations before, during, and after instructed microsaccades to a centrally cued orientation stimulus.

Strengths:

The article is clearly written, and the stimulus presentation method is sophisticated and well-established. The data provide interesting insights that will be useful for comparisons between trans-saccadic and trans-microsaccadic sensitivity modulations.

Weaknesses:

Nonetheless, I have major concerns regarding the interpretation of the measured time courses (in particular, inconsistencies in distinguishing enhancement from suppression), the attempt to disentangle these effects from endogenous attention shifts, and the overstatement of the findings' novelty.

(1) Overstatement of novelty

The authors motivate their study by stating that "the temporal dynamics of these pre-microsaccadic modulations remain unknown" (l. 55-56). However, Shelchkova & Poletti (2020) already report a microsaccade-aligned sensitivity time course. I understand that the present study uses shorter target durations and thus provides a more resolved estimate. Nonetheless, a fairer characterization of the study's novelty would be that observers' discrimination performance is continuously measured across the pre-, intra-, and post-movement interval, within the same observers and experimental design. Relatedly, the authors state that it is unclear whether pre-microsaccadic sensitivity modulations reflect "suppression at the non-foveated location, enhancement at the microsaccade target, or both" (l. 70). Guzhang et al. (2024) examined the spatial spread of pre-microsaccadic sensitivity modulations by measuring performance at the PRL, the movement target, and several other equidistant locations. They report that "whereas fine spatial vision is enhanced at the microsaccade goal location, it drops at the very center of gaze". The current authors' reasoning seems to be that performances at locations that are neither the target nor the PRL may behave differently. Why would that be the case? If my understanding is correct, I would recommend incorporating these clarifications into the motivation paragraph, so that readers less familiar with the literature do not overestimate the novelty of the findings. Moreover, and related to point 3, I am unsure if the current analyses provide decisive evidence to distinguish enhancement from suppression, as claimed by the authors.

(2) Distinction from endogenous attention

To "rule out the possible influence of covert attention" (l. 232), the authors compute a cue-aligned in addition to the movement-aligned performance time course. A difference in alignment cannot rule out the influence of a certain mechanism; it can only dilute it. Just like endogenous attention may contribute to the movement-aligned time course, movement preparation will necessarily contribute to the cue-aligned time course, since these timelines are intrinsically correlated: as the trial progresses, observers will be in later and later stages of saccade preparation. For this and several additional reasons, an effect in the cue-aligned time course is in fact expected-and, in my view, clearly present (see below). As the authors themselves note, endogenous attention has been shown to operate within the foveola and should therefore be engaged in the present experiment in addition to movement-related attentional shifts (unless the authors believe that specific design features, e.g., stimulus timing, preclude its involvement?). Regardless of the theoretical considerations, the empirical data show a pronounced, near-linear increase in performance at the target location, with d′ doubling from approximately 1 to 2. Although the interaction between condition and time does not reach significance (p = 0.09), this result should not be taken as conclusive evidence against a plausible and perhaps expected contribution of endogenous attention. I suggest an additional analysis that could more directly address these issues. In previous work (Rolfs & Carrasco, 2012; Kroell & Rolfs, 2025; see Figure 3), the relative contributions of cue-alinged influences and pre-saccadic attention were disentangled by reweighting each data point according to its position on both the cue-locked and saccade-locked timelines. Applied to the present study, the authors could compute, for each cue-to-target offset bin, its proportional contribution to each pre-movement time bin. Microsaccade-locked sensitivities could then be reweighted based on these proportions. As a result, each movement-locked time bin would contain equal contributions from all cue-locked time bins, effectively isolating the effect of microsaccade preparation.

(3) Interpretation and analysis of the time course

(3.1) Discrimination before microsaccade onset<br /> In lines 151-153, the author state "While the enhancement at the target location did not reach significance relative to baseline, the impairment at the non-target location did", suggesting that pre-movement sensitivity advantages for information presented at the target location are due to a decrease in performance at the non-target location and not an enhancement at the target location per se. After analyzing the difference between the two locations, the authors state, "These results show that approximately 100 milliseconds before microsaccade onset, discrimination rapidly improved at the intended target location while decreasing at the non-target location." (l. 159-161). How is the statement that discrimination performance rapidly improved (which is repeated throughout the manuscript) justified by the results?

More generally, the authors may benefit from applying bootstrapping or permutation-based analyses to their data. Such approaches would, for example, allow direct comparisons between congruent and incongruent conditions at every individual time point in Figure 3B and may be more sensitive to temporally confined sensitivity variations while requiring fewer assumptions than analyses based on manually segregated temporal bins and aggregate measures. If enhancement at the target location does not reach significance even in these analyses, all corresponding statements should be removed throughout the manuscript. The term "enhancement" should then be rephrased as "detection advantage" or "relative performance benefit" to emphasize the contrast to enhancement effects classically associated with pre-saccadic attention shifts.

Relatedly, the authors state that pre-microsaccadic enhancement peaks around 70 ms before microsaccade onset, which is earlier than sensitivity enhancements preceding large-scale saccades that often increase monotonically up until movement onset. The authors suggest potential reasons for this in the Discussion, yet an additional one seems conceivable based on Figure 3B. Performances at both the cue-congruent and incongruent location decrease leading up to the movement, reaching values even below their early baselines around 100 ms and 25 ms before movement onset for the incongruent and congruent location, respectively. A spatially non-specific decline that drives sensitivities toward a common absolute minimum may thus dictate the time course of detection advantages. In other words, a spatially widespread decrease in foveolar sensitivity likely contributes to both "suppression" at the non-target location and the decrease in "enhancement" at the target location. If this general decrease is due to saccadic suppression, as the authors suggest, it appears to exert a much more pronounced influence on sensitivity modulations than it does before large-scale saccades (which is interesting). Are there other findings suggesting an increased magnitude of micro-saccadic (as compared to saccadic) suppression? Another potentially related phenomenon is the decrease in pre-saccadic foveal detection performances reported twice before (Hanning & Deubel, 2022; Kroell & Rolfs, 2022). It is possible that whatever mechanism triggers this decrease is engaged by the preparation of microsaccadic and saccadic motor programs alike. In any case, I would ask the authors to acknowledge this general decrease early on to clarify that any currently significant advantage for the target location relies on varied degrees of suppression, and not on true enhancement similar to pre-saccadic attention shifts.

Moreover, in Figure 3C, the final 25 ms before microsaccade onset are excluded from the aggregate measure, presumably since including this interval substantially reduces the effect size. Since the last 25 ms before movement onset is the interval most commonly associated with saccadic suppression, I think that this choice can be justified. Nonetheless, it should be mentioned explicitly in the main text. On a minor note, the authors state that "Performance (evaluated as percent of correct responses) was averaged within a 50 millisecond sliding window, advancing in 1 ms steps (with 24 ms overlap)". Why is the overlap not 49 ms?

(3.2) Discrimination during the microsaccade:<br /> The authors state that "in the "during" trials the target must be presented during the peak speed of the microsaccade." Since the target was presented for 50 ms and the average microsaccade duration was around 60 ms, this implies that the intra-microsaccadic condition includes many trials in which the target overlapped with the pre- or post-movement fixation interval. Were there not enough trials to isolate purely intra-microsaccadic presentations? Are the results descriptively comparable?

(4) Additional analyses

Several additional analyses could strengthen the authors' conclusions. If there are enough trials in which observers erroneously saccaded to the uncued (i.e., wrong) location, these trials could experimentally isolate the influence of pre-microsaccadic attention, assuming that endogenous attention went to the cued location. In addition, the authors speculate whether differences in saccadic and microsaccadic movement latencies may underlie the differences in perceptual time courses. The latency distributions provided in the manuscript look sufficiently broad, such that intra-individual variation could be harnessed to explore this question. Do sensitivity time courses differ before microsaccades with shorter vs. longer latencies?

(5) Clarifications regarding the design

At 50 ms, the duration of the to-be discriminated stimulus, although shorter than in previous investigations, is still rather long. What is the reason for this? I would encourage the authors to state in the main text that the duration of the analyzed/plotted time bins is often shorter than the stimulus duration (i.e., there is some overlap between bins that likely introduces smoothing). In Figure 3A, it would be helpful to plot raw data points computed from non-overlapping bins on top of the moving-window estimates, to allow readers to assess the degree of smoothing and potential temporal delays introduced by this analysis. Moreover, I wonder whether the abrupt onset of the target unmasked by flickering noise masks might induce saccadic inhibition, which would manifest as a transient dip in saccade execution probability. The distributions shown in Figure 2B appear too smoothed or fitted to clearly reveal such a dip. How exactly are all distributions in the manuscript computed (e.g., binning, smoothing, fitting procedures)? Finally, on a minor note, explicitly stating on line 105 that two different orientations can be presented at the cued and non-cued location would help avoid potential confusion.

Reviewer #1 (Public review):

Review of the revised submission:

I thank the authors for their detailed consideration of my comments and for the additional data, analyses, and clarifications they have incorporated. The new behavioral experiments, quantification of targeted manipulations, and expanded methodological details strengthen the manuscript and address many of my initial concerns. While some questions remain for future work, the authors' careful responses and the additional evidence provided help resolve the main issues I raised, and I am generally satisfied with the revisions.

Review of original submission:

Summary

In this article, Kawanabe-Kobayashi et al., aim to examine the mechanisms by which stress can modulate pain in mice. They focus on the contribution of noradrenergic neurons (NA) of the locus coeruleus (LC). The authors use acute restraint stress as a stress paradigm and found that following one hour of restraint stress mice display mechanical hypersensitivity. They show that restraint stress causes the activation of LC NA neurons and the release of NA in the spinal cord dorsal horn (SDH). They then examine the spinal mechanisms by which LC→SDH NA produces mechanical hypersensitivity. The authors provide evidence that NA can act on alphaA1Rs expressed by a class of astrocytes defined by the expression of Hes (Hes+). Furthermore, they found that NA, presumably through astrocytic release of ATP following NA action on alphaA1Rs Hes+ astrocytes, can cause an adenosine-mediated inhibition of SDH inhibitory interneurons. They propose that this disinhibition mechanism could explain how restraint stress can cause the mechanical hypersensitivity they measured in their behavioral experiments.

Strengths:

(1) Significance. Stress profoundly influences pain perception; resolving the mechanisms by which stress alters nociception in rodents may explain the well-known phenomenon of stress-induced analgesia and/or facilitate the development of therapies to mitigate the negative consequences of chronic stress on chronic pain.

(2) Novelty. The authors' findings reveal a crucial contribution of Hes+ spinal astrocytes in the modulation of pain thresholds during stress.

(3) Techniques. This study combines multiple approaches to dissect circuit, cellular, and molecular mechanisms including optical recordings of neural and astrocytic Ca2+ activity in behaving mice, intersectional genetic strategies, cell ablation, optogenetics, chemogenetics, CRISPR-based gene knockdown, slice electrophysiology, and behavior.

Weaknesses:

(1) Mouse model of stress. Although chronic stress can increase sensitivity to somatosensory stimuli and contribute to hyperalgesia and anhedonia, particularly in the context of chronic pain states, acute stress is well known to produce analgesia in humans and rodents. The experimental design used by the authors consists of a single one-hour session of restraint stress followed by 30 min to one hour of habituation and measurement of cutaneous mechanical sensitivity with von Frey filaments. This acute stress behavioral paradigm corresponds to the conditions in which the clinical phenomenon of stress-induced analgesia is observed in humans, as well as in animal models. Surprisingly, however, the authors measured that this acute stressor produced hypersensitivity rather than antinociception. This discrepancy is significant and requires further investigation.

(2) Specifically, is the hypersensitivity to mechanical stimulation also observed in response to heat or cold on a hotplate or coldplate?

(3) Using other stress models, such as a forced swim, do the authors also observe acute stress-induced hypersensitivity instead of stress-induced antinociception?

(4) Measurement of stress hormones in blood would provide an objective measure of the stress of the animals.

(5) Results:

(a) Optical recordings of Ca2+ activity in behaving rodents are particularly useful to investigate the relationship between Ca2+ dynamics and the behaviors displayed by rodents.

(b) The authors report an increase in Ca2+ events in LC NA neurons during restraint stress: Did mice display specific behaviors at the time these Ca2+ events were observed such as movements to escape or orofacial behaviors including head movements or whisking?

(c) Additionally, are similar increases in Ca2+ events in LC NA neurons observed during other stressful behavioral paradigms versus non-stressful paradigms?

(d) Neuronal ablation to reveal the function of a cell population.

(e) The proportion of LC NA neurons and LC→SDH NA neurons expressing DTR-GFP and ablated should be quantified (Figures 1G and J) to validate the methods and permit interpretation of the behavioral data (Figures 1H and K). Importantly, the nocifensive responses and behavior of these mice in other pain assays in the absence of stress (e.g., hotplate) and a few standard assays (open field, rotarod, elevated plus maze) would help determine the consequences of cell ablation on processing of nociceptive information and general behavior.

(f) Confirmation of LC NA neuron function with other methods that alter neuronal excitability or neurotransmission instead of destroying the circuit investigated, such as chemogenetics or chemogenetics, would greatly strengthen the findings. Optogenetics is used in Figure 1M, N but excitation of LC→SDH NA neuron terminals is tested instead of inhibition (to mimic ablation), and in naïve mice instead of stressed mice.

(g) Alpha1Ars. The authors noted that "Adra1a mRNA is also expressed in INs in the SDH".

(h) The authors should comprehensively indicate what other cell types present in the spinal cord and neurons projecting to the spinal cord express alpha1Ars and what is the relative expression level of alpha1Ars in these different cell types.

(i) The conditional KO of alpha1Ars specifically in Hes5+ astrocytes and not in other cell types expressing alpha1Ars should be quantified and validated (Figure 2H).

(j) Depolarization of SDH inhibitory interneurons by NA (Figure 3). The authors' bath applied NA, which presumably activates all NA receptors present in the preparation.

k) The authors' model (Figure 4H) implies that NA released by LC→SDH NA neurons leads to the inhibition of SDH inhibitory interneurons by NA. In other experiments (Figure 1L, Figure 2A), the authors used optogenetics to promote the release of endogenous NA in SDH by LC→SDH NA neurons. This approach would investigate the function of NA endogenously released by LC NA neurons at presynaptic terminals in the SDH and at physiological concentrations and would test the model more convincingly compared to the bath application of NA.

(l) As for other experiments, the proportion of Hes+ astrocytes that express hM3Dq, and the absence of expression in other cells, should be quantified and validated to interpret behavioral data.

(m) Showing that the effect of CNO is dose-dependent would strengthen the authors' findings.

(n) The proportion of SG neurons for which CNO bath application resulted in a reduction in recorded sIPSCs is not clear.

(o) A1Rs. The specific expression of Cas9 and guide RNAs, and the specific KD of A1Rs, in inhibitory interneurons but not in other cell types expressing A1Rs should be quantified and validated.

(6) Methods:

It is unclear how fiber photometry is performed using "optic cannula" during restraint stress while mice are in a 50ml falcon tube (as shown in Figure 1A).

Reviewer #1 (Public review):

Summary:

In this study, Lamberti et al. investigate how translation initiation and elongation are coordinated at the single-mRNA level in mammalian cells. The authors aim to uncover whether and how cells dynamically adjust initiation rates in response to elongation dynamics, with the overarching goal of understanding how translational homeostasis is maintained. To this end, the study combines single-molecule live-cell imaging using the SunTag system with a kinetic modeling framework grounded in the Totally Asymmetric Simple Exclusion Process (TASEP). By applying this approach to custom reporter constructs with different coding sequences, and under perturbations of the initiation/elongation factor eIF5A, the authors infer initiation and elongation rates from individual mRNAs and examine how these rates covary.

The central finding is that initiation and elongation rates are strongly correlated across a range of coding sequences, resulting in consistently low ribosome density ({less than or equal to}12% of the coding sequence occupied). This coupling is preserved under partial pharmacological inhibition of eIF5A, which slows elongation but is matched by a proportional decrease in initiation, thereby maintaining ribosome density. However, a complete genetic knockout of eIF5A disrupts this coordination, leading to reduced ribosome density, potentially due to changes in ribosome stalling resolution or degradation.

Strengths:

A key strength of this work is its methodological innovation. The authors develop and validate a TASEP-based Hidden Markov Model (HMM) to infer translation kinetics at single-mRNA resolution. This approach provides a substantial advance over previous population-level or averaged models and enables dynamic reconstruction of ribosome behavior from experimental traces. The model is carefully benchmarked against simulated data and appropriately applied. The experimental design is also strong. The authors construct matched SunTag reporters differing only in codon composition in a defined region of the coding sequence, allowing them to isolate the effects of elongation-related features while controlling for other regulatory elements. The use of both pharmacological and genetic perturbations of eIF5A adds robustness and depth to the biological conclusions. The results are compelling: across all constructs and conditions, ribosome density remains low, and initiation and elongation appear tightly coordinated, suggesting an intrinsic feedback mechanism in translational regulation. These findings challenge the classical view of translation initiation as the sole rate-limiting step and provide new insights into how cells may dynamically maintain translation efficiency and avoid ribosome collisions.

Assessment of Goals and Conclusions:

The authors successfully achieve their stated aims: they quantify translation initiation and elongation at the single-mRNA level and show that these processes are dynamically coupled to maintain low ribosome density. The modeling framework is well suited to this task, and the conclusions are supported by multiple lines of evidence, including inferred kinetic parameters, independent ribosome counts, and consistent behavior under perturbation.

Impact and Utility:

This work makes a significant conceptual and technical contribution to the field of translation biology. The modeling framework developed here opens the door to more detailed and quantitative studies of ribosome dynamics on single mRNAs and could be adapted to other imaging systems or perturbations. The discovery of initiation-elongation coupling as a general feature of translation in mammalian cells will likely influence how researchers think about translational regulation under homeostatic and stress conditions.

The data, models, and tools developed in this study will be of broad utility to the community, particularly for researchers studying translation dynamics, ribosome behavior, or the effects of codon usage and mRNA structure on protein synthesis.

Context and Interpretation:

This study contributes to a growing body of evidence that translation is not merely controlled at initiation but involves feedback between elongation and initiation. It supports the emerging view that ribosome collisions, stalling, and quality control pathways play active roles in regulating initiation rates in cis. The findings are consistent with recent studies in yeast and metazoans showing translation initiation repression following stalling events. However, the mechanistic details of this feedback remain incompletely understood and merit further investigation, particularly in physiological or stress contexts.

In summary, this is a thoughtfully executed and timely study that provides valuable insights into the dynamic regulation of translation and introduces a modeling framework with broad applicability. It will be of interest to a wide audience in molecular biology, systems biology, and quantitative imaging.

Reviewer #1 (Public review):

Summary:

Drosophila larval type II neuroblasts generate diverse types of neurons by sequentially expressing different temporal identity genes during development. Previous studies have shown that transition from early temporal identity genes (such as Chinmo and Imp) to late temporal identity genes (such as Syp and Broad) depends on the activation of the expression of EcR by Seven-up (Svp) and progression through the G1/S transition of the cell cycle. In this study, Chaya and Syed examined if the expression of Syp and EcR is regulated by cell cycle and cytokinesis by knocking down CDK1 or Pav, respectively, throughout development or at specific developmental stages. They find that knocking down CDK1 or Pav either in all type II neuroblasts throughout the development or in single type neuroblast clones after larval hatching consistently leads to failure to activate late temporal identity genes Syp and EcR. To determine whether the failure of the activation of Syp and EcR is due to impaired Svp expression, they also examined Svp expression using a Svp-lacZ reporter line. They find that Svp is expressed normally in CDK1 RNAi neuroblasts. Further, knocking down CDK1 or Pav after Svp activation still leads to loss of Syp and EcR expression. Finally, they also extended their analysis to type I neuroblasts. They find that knocking down CDK1 or Pav, either at 0 hours or at 42 hours after larval hatching, also results in loss of Syp and EcR expression in type I neuroblasts. Based on these findings, the authors conclude that cycle and cytokinesis are required for the transition from early to late late temporal identity genes in both types of neuroblasts. These findings add mechanistic details to our understanding of the temporal patterning of Drosophila larval neuroblasts.

Strengths:

The data presented in the paper are solid and largely support their conclusion. Images are of high quality. The manuscript is well-written and clear.

Weaknesses:

The authors have addressed all the weaknesses in this revision.

Reviewer #1 (Public review):

Summary:

Here, the authors aim to investigate the potential improvements of ANNs when used to explain brain data using top-down feedback connections found in the neocortex. To do so, they use a retinotopic and tonotopic organization to model each subregion of the ventral visual (V1, V2, V4, and IT) and ventral auditory (A1, Belt, A4) regions using Convolutional Gated Recurrent Units. The top-down feedback connections are inspired by the apical tree of pyramidal neurons, modeled either with a multiplicative effect (change of gain of the activation function) or a composite effect (change of gain and threshold of the activation function).

To assess the functional impact of the top-down connections, the authors compare three architectures: a brain-like architecture derived directly from brain data analysis, a reversed architecture where all feedforward connections become feedback connections and vice versa, and a random connectivity architecture. More specifically, in the brain-like model the visual regions provide feedforward input to all auditory areas, whereas auditory areas provide feedback to visual regions.

First, the authors found that top-down feedback influences audiovisual processing and that the brain-like model exhibits a visual bias in multimodal visual and auditory tasks. Second, they discovered that in the brain-like model, the composite integration of top-down feedback, similar to that found in the neocortex, leads to an inductive bias toward visual stimuli, which is not observed in the feedforward-only model. Furthermore, the authors found that the brain-like model learns to utilize relevant stimuli more quickly while ignoring distractors. Finally, by analyzing the activations of all hidden layers (brain regions), they found that the feedforward and feedback connectivity of a region could determine its functional specializations during the given tasks.

Strengths:

The study introduces a novel methodology for designing connectivity between regions in deep learning models. The authors also employ several tasks based on audiovisual stimuli to support their conclusions. Additionally, the model utilizes backpropagation of error as a learning algorithm, making it applicable across a range of tasks, from various supervised learning scenarios to reinforcement learning agents. Conversely, the presented framework offers a valuable tool for studying top-down feedback connections in cortical models. Thus, it is a very nice study that can also give inspiration to other fields (machine learning) to start exploring new architectures.

Reviewer #1 (Public review):

Summary:

Jeay-Bizot and colleagues investigate the neural correlates of the preparation of, and commitment to, a self-initiated motor action. In their introduction, they differentiate between theoretical proposals relating to the timing of such neural correlates relative to the time of a recorded motor action (e.g., a keypress). These are categorised into 'early' and 'late' timing accounts. The authors advocate for 'late' accounts based on several arguments that align well with contemporary models of decision-making in other domains (for example, evidence accumulation models applied to perceptual decisions). They also clearly describe prevalent methodological issues related to the measurement of event-related potentials (ERPs) and time-frequency power to gauge the timing of the commitment to making a motor action. These methodological insights are communicated clearly and denote potentially important limitations on the inferences that can be drawn from a large body of existing work.

To attempt to account for such methodological concerns, the authors devise an innovative experiment that includes an experimental condition whereby participants make a motor action (a right-hand keypress) to make an image disappear. They also include a condition whereby the stimulus presentation program automatically proceeds at a set time that is matched to the response timing in a previous trial. In this latter condition, no motor action is required by the participant. The authors then attempt to determine the times at which they can differentiate between these two conditions (motor action vs no motor action) based on EEG and MEG data, using event-related potential analyses, time-frequency analyses, and multivariate classifiers. They also apply analysis techniques based on comparing M/EEG amplitudes at different time windows (as used in previous work) to compare these results to those of their key analyses.

When using multivariate classifiers to discriminate between conditions, they observed very high classification performance at around -100ms from the time of the motor response or computer-initiated image transition, but lower classification performance and a lack of statistically significant effects across analyses for earlier time points. Based on this, they make the key claim that measured M/EEG responses at the earlier time points (i.e., earlier than around -100ms from the motor action) do not reliably correlate with the execution of a motor action (as opposed to no such action being prepared or made). This is argued to favour 'late' accounts of motor action commitment, aligning with the well-made theoretical arguments in favour of these accounts in the introduction. Although the exact time window related to 'late' accounts is not concretely specified, an effect that occurs around -100ms from response onset is assumed here to fall within that window.

Importantly, this claim relies on accepting the null hypothesis of zero effect for the time points preceding around -100ms based on a somewhat small sample of n=15 and some additional analyses of individual participant datasets. Although the authors argue that their classifiers are sensitive to detecting relevant effects, and the study appears well-powered to detect the (likely to be large magnitude) M/EEG signal differences occurring around the time of the response or computer-initiated image transition, there is no guarantee that the study is adequately sensitive to detect earlier differences in M/EEG signals. These earlier effects are likely to be more subtle and exhibit lower signal-to-noise ratios, but would still be relevant to the 'early' vs 'late' debate framed in the manuscript. This, along with some observed patterns in the data, may substantially reduce the confidence one may have in the key claim about the onset timing of M/EEG signal differences.

Notably, there is some indication of above-chance (above 0.5 AUC) classification performance at time points earlier than -100ms from the response, as visible in Figure 3A for the task-based EEG analyses (EEG OC dataset, blue line). While this was not statistically significantly above chance for their n=15 sample, these results do not appear to be clear evidence in favour of a zero-effect null-hypothesis. In Figures 2A-B, there are also visible differences in the ERPs across conditions, from around the time that motor action-related components have been previously observed (around -500ms from the response). The plotted standard errors in the data are large enough to indicate that the study may not have been adequately powered to differentiate between the conditions.

Although the authors acknowledge this limitation in the discussion section of their manuscript, their counter-argument is that the classifiers could reliably differentiate between conditions at time points very close to the motor response, and in the time-based analyses where substantive confounds are likely to be present, as demonstrated in a set of analyses. Based on this data, the authors imply that the study is sufficiently powered to detect effects across the range of time points used in the analyses. While it's commendable that these extra analyses were run, they do not provide convincing evidence that the study is necessarily sensitive to detecting more subtle effects that may occur at earlier time points. In other words, the ability of classifiers (or other analysis methods) to detect what are likely to be very prominent, large effects around the time of the motor response does not guarantee that such analyses will detect smaller magnitude effects at other time points.

In summary, the authors develop some very important lines of argument for why existing work may have misestimated the timing of neural signals that precede motor actions. This in itself is an important contribution to the field. However, their attempt to better estimate the timing of such signals is limited by a reliance on accepting the null hypothesis based on non-statistically significant results, and arguably a limited degree of sensitivity to detect subtle but meaningful effects.

Strengths:

This manuscript provides compelling reasons why existing studies may have misestimated the timing of the neural correlates of motor action preparation and execution. They provide additional analyses as evidence of the relevant confounds and provide simulations to back up their claims. This will be important to consider for many in the field. They also endeavoured to collect large numbers of trials per participant to also examine effects in individuals, which is commendable and arguably better aligned with contemporary theory (which pertains to how individuals make decisions to act, rather than groups of people).

The innovative control condition in their experiment may also be very useful for providing complementary evidence that can better characterise the neural correlates of motor action preparation and commitment. The method for matching image durations across active and passive conditions is particularly well thought-out and provides a nice control for a range of potential confounding factors.

Weaknesses:

There is a mismatch between the stated theoretical phenomenon of interest (commitment to making a motor action) and what is actually tested in the study (differences in neural responses when an action is prepared and made compared to when no action is required). The assumed link between these concepts could be made more explicit for readers, particularly because it is argued in the manuscript that neural correlates of motor action preparation are not necessarily correlates of motor action commitment.

As mentioned in the summary, the main issue is the strong reliance on accepting the null hypothesis of no differences between motor action and computer initiation conditions based on a lack of statistically significant results from the modest (n=15) sample. Although a larger sample will increase measurement precision at the group level, there are some EEG data processing changes that could increase the signal-to-noise ratio of the analysed data and produce more precise estimates of effects, which may improve the ability to detect more subtle effects, or at least provide more confidence in the claims of null effects.

First, it is stated in the EEG acquisition and preprocessing section that the 64-channel Biosemi EEG data were recorded with a common average reference applied. Unless some non-standard acquisition software was used (of which we are not aware exists), Biosemi systems do not actually apply this reference at recording (it is for display purposes only, but often mistaken to be the actual reference applied). As stated in the Biosemi online documentation, a reference should be subsequently applied offline; otherwise, there is a substantial decrease in the signal-to-noise ratio of the EEG data, and a large portion of ambient alternating current noise is retained in the recordings. This can be easily fixed by applying a referencing scheme (e.g., the common average reference) offline as one of the first steps of data processing. If this was, in fact, done offline, it should be clearly communicated in the manuscript.

In addition, the data is downsampled using a non-integer divisor of the original sampling rate (a 2,048 Hz dataset is downsampled to 500 Hz rather than 512 Hz). Downsampling using a non-integer divisor is not recommended and can lead to substantial artefacts in raw data as a result, as personally observed by this Reviewer in Biosemi data. Finally, although a 30 Hz low-pass filter is applied for visualisation purposes of ERPs, no such filter is applied prior to analyses, and no method is used to account for alternating current noise that is likely to be in the data. As noted above, much of the alternating current noise will be retained when an offline reference is not applied, and this is likely to further degrade the quality of the data and reduce one's ability to identify subtle patterns in EEG signals. Changes in data processing to address these issues would likely lead to more precise estimates of EEG signals (and by extension differences across conditions).

With regard to possible effects extending hundreds of milliseconds before the response, it would be helpful for the authors to more precisely clarify the time windows associated with 'early' and 'late' theories in this case. The EEG data that would be required to support 'early' theories is also not made sufficiently clear. For example, even quite early neural correlates of motor actions in this task (e.g., around -500ms from the response, or earlier) could still be taken as evidence for the 'late' theories if these correlates simply reflect the accumulation of evidence toward making a decision and associated motor action, as implied by the Leaky Stochastic Accumulator model described by the authors. In other words, even observations of neural correlates of motor action preparation that occur much earlier than the response would not constitute clear evidence against the 'late' account if this neural activity represents an antecedent to a decision and action (rather than commitment to the action), as the authors point out in the introduction.

In addition, there is some discrepancy regarding the data that is used by the classifiers to differentiate between the conditions in the EEG data and the claims about the timing of neural responses that differentiate between conditions. Unless we reviewers are mistaken, the Sliding Window section of the methods states that the AUC scores in Figure 3 are based on windows of EEG data that extend from the plotted time point until 0.5 seconds into the past. In other words, an AUC value at -100ms from the response is based on classifiers applied to data ranging from -600 to -100 milliseconds relative to the response. In this case, the range of data used by the classifiers extends much earlier than the time points indicated by Figure 3, and it is difficult to know whether the data at these earlier time points may have contributed (even in subtle ways) to the success of the classifiers. This may undermine the claim that neural responses only become differentiable from around -100ms from response onset. The spans of these windows used for classification could be made more explicit in Figure 3, and classification windows that are narrower could be included in a subset of analyses to ensure that classifiers only using data in a narrow window around the response show the high degree of classification performance in the dataset. If we are mistaken, then perhaps these details could be clarified in the method and results sections.

Reviewer #1 (Public review):

Summary:

This study reports the effects of psilocin on iPSC-derived human cortical neurons.

Strengths:

The characterization was comprehensive, involving immunohistochemistry of various markers, 5-HT2A receptors, BDNF, and TrkB, transcriptomics analyses, morphological determination, electrophysiology, and finally synaptic protein measurements. The results are in close agreement with prior work (PMID 29898390) on rat cultured cortical neurons. Nevertheless, there is value in confirming those earlier findings and furthermore to demonstrate the effects in human neurons, which are important for translation. The genetic, proteomics, and cell structure analyses used in this paper are its major strength. The study supports the value of using iPSC-derived human cortical neurons for drug development involving psychedelics-related compounds.

Weaknesses:

(1) Line 140: 5-HT2A receptor expression was found via immunocytochemistry to reside in the somatodendritic and axonal compartments. However, prior work from ex vivo tissue using electron microscopy has found predominantly 5-HT2A receptor expression in the somatodendritic compartment (PMID: 12535944). Was this antibody validated to be 5-HT2A receptor-specific? Can the authors reason why the discrepancy may arise, and if the axonal expression is specific to the cultured neurons?

(2) Line 143: It would be helpful to specify the dose of psilocin tested, and describe how this dose was chosen.

(3) Figure 1: The interpretation is that the differential internalization in the axonal and somatodendritic compartments is time-dependent. However, given that only one dose is tested, it is also possible that this reflects dose dependence, with the longer time exposure leading to higher dose exposure, so these variables are related. That is, if a higher dose is given, internalization may also be observed after 10 minutes in the dendritic compartment.

(4) Figure 3 & 4: What is the 'control' here? A more appropriate control for the 24 hours after psilocin application would be 24 hours after vehicle application. Here the authors are looking at before and after, but the factor of time elapsed and perturbation via application is not controlled for.

(5) The sample size was not clearly described. In the figure legend, N = the number of neurites is provided, but it is unclear how many cells have been analyzed, and then how many of those cells belong to the same culture. These are important sample size information that should be provided. Relatedly, statistical analyses should consider that the neurites from the same cells are not independent. If the neurites indeed come from the same cells, then the sample size is much smaller and a statistical analysis considering the nested nature of the data should be used.

Comments on revisions:

The authors performed substantial experiments to check validity of the HTR2A antibody for the revision. Briefly, they found that western blot shows a single band, abolished by a blocking peptide, in neural progenitors and iPSC-derived neurons, suggesting positive results. However, they also detected immunofluorescence signals in HEK293 and HeLa cells, which do not express 5-HT2A receptors as scRNAseq analysis of these cells show complete absence of the transcript. Therefore the antibody has epitope-selective binding but also has some non-specific binding, precluding its use. The authors rightfully removed the data related to the antibody in the revised manuscript. The account is repeated here to highlight to anyone who may find the information helpful. Overall, the additional results added rigor to the study.

Reviewer #1 (Public review):

Summary:

This manuscript presents findings on the adaptation mechanisms of Saccharomyces cerevisiae under extreme stress conditions. The authors try to generalize this to adaptation to stress tolerance. A major finding is that S. cerevisiae evolves a quiescence-like state with high trehalose to adapt to freeze-thaw tolerance independent of their genetic background. The manuscript is comprehensive, and each of the conclusions is well supported by careful experiments.

Strengths:

This is excellent interdisciplinary work.

I have commented on the response of the authors, in-line, below. This is to maintain the conversation thread with the authors.

Comment 1:

Earlier papers have shown that loss of ribosomal proteins, that slow growth, leads to better stress tolerance in S. cerevisiae. Given this, isn't it expected that any adaptation that slows down growth would, overall, increase stress tolerance? Even for other systems, it has been shown that slowing down growth (by spore formation in yeast or bacteria/or dauer formation in C. elegans) is an effective strategy to combat stress and hence is a likely route to adaptation. The authors stress this as one of the primary findings. I would like the authors to explain their position, detailing how their findings are unexpected in the context of the literature.

Response:

We agree that the link between slower growth and higher stress tolerance has been well stud-ied. What is distinctive here is that repeated, near-lethal freeze-thaw selected not only for a tolerant/quiescent-like state but also for a shorter lag on re-entry. In this regime of freeze-thaw-regrowth, cells that are tolerant but slow to restart would be outcompeted by naive fast growers. Our quiescence-based selection simulations reproduce exactly this constraint. We have added this explanation to the Results to make clear that the novelty is the co-evolution of a tolerant, trehalose-rich state together with rapid regrowth under an alternating regime.

Comment to Response: I get the point. I believe that the outcome is highly dependent on how selection pressure is administered. So, generalizing this over all stresses (as done in the abstract) may not be accurate.

Comment 2:

Convergent evolution of traits: I find the results unsurprising. When selecting for a trait, if there is a major mode to adapt to that stress, most of the strains would adapt to that mode, independent of the route. According to me, finding out this major route was the objective of many of the previous reports on adaptive evolution. The surprising part in the previous papers (on adaptive evolution of bacteria or yeast) was the resampling of genes that acquired mutations in multiple replicates of an evolution experiments, providing a handle to understand the major genetic route or the molecular mechanism that guides the adaptation (for example in this case it would be - what guides the over-accumulation of trehalose). I fail to understand why the authors find the results surprising, and I would be happy to understand that from the authors. I may have missed something important.

Response:

Our surprise was precisely that we did not see the classical pattern of "phenotypic convergence + repeated mutations in the same locus/module." All independently evolved lines converged on a trehalose-rich, mechanically reinforced, quiescence-like phenotype, but population sequencing across lines did not reveal a single repeatedly hit gene or small shared pathway, even when we increased selection stringency (1-3 freeze-thaw cycles per round). We have now stated in the manuscript that this decoupling (strong phenotypic convergence, non-overlapping genetic routes) is the central inference: selection is acting on a physiologically defined state that multiple genotypes can reach.

Comment to Response: You indeed saw a case of phenotypic convergence. Converging towards trehalose-rich, mechanically reinforced, quiescent like - are phenotypes that have converged. This is what prevented lysis. The same locus need not be mutated over and over again, if the trehalose pathway is controlled by many processes (it is, and many are still unknown as I point in the next comment), many different mutations on different loci can result in the same regulation! I do not see the decoupling between phenotypic convergence and decoupling of genetic mutations as surprising or novel; molecular and cellular biology is replete with such examples where deletion(mutation) of hundreds of different genes can have the same phenotypic outcome (yeast deletion library screening, indirect effects etc). If this was a specific question unsolved in evolutionary biology, then the matter is different.

A minor point: Here I would also like to point out that the three phenotypes you measure may be linked to each other, so their independent evolution may just be a cause-effect relationship. For example Trehalose accumulation may drive the other two. This has not been deconvoluted in this manuscript.

Comment 3:

Adaptive evolution would work on phenotype, as all of selective evolution is supposed to. So, given that one of the phenotypes well-known in literature to allow free-tolerance is trehalose accumulation, I think it is not surprising that this trait is selected. For me, this is not a case of "non-genetic" adaptation as the authors point out: it is likely because perturbation of many genes can individually result in the same outcome - up-regulation of trehalose accumulation. Thereby, although the adaptation is genetic, it is not homogeneous across the evolving lines - the end result is. Do the authors check that the trait is actually a non-genetic adaptation, i.e., if they regrow the cells for a few generations without the stress, the cells fall back to being similarly only partially fit to freeze-thaw cycles? Additionally, the inability to identify a network that is conserved in the sequencing does not mean that there is no regulatory pathway. A large number of cryptic pathways may exist to alter cellular metabolic states.<br /> This is a point in continuation of point #2, and I would like to understand what I have missed.

Response:

We agree, and we have removed the wording "non-genetic adaptation." The evolved populations retain high survival even after regrowth for {greater than or equal to}25 generations without freeze-thaw, so the adaptation is clearly genetically maintained. What our data show is that there is no single genetic route to the shared phenotype; different mutations can all drive cells into the same trehalose-rich, quiescence-like, mechanochemically reinforced state. We now describe this as "genetic diversification with phenotypic convergence."

Comment to Response: While the last term does explain what is going on, isn't it an outcome that is routine in cell biology (as pointed out in my previous comment to your response)? I apologize for not understanding the punchline that is provided in the last few sentences of the abstract.

Comment 4:

To propose the convergent nature, it would be important to check for independently evolved lines and most probably more than 2 lines. It is not clear from their results section if they have multiple lines that have evolved independently.

Response:

We indeed evolved four independent lines and maintained two independent controls. We have added this information at the start of the Results so that the level of replication is immediately clear.

Comment to Response: Previous large scale studies have done hundreds of sequencing to oversample the pathway and figure out reproducible loci. With pooled sequencing (as mentioned below) and only 4 sample evolution, I am not sure that you would have the power in your study to conclude in the loci are sampled or not! If there were 10 gene LOFs that control Trehalose levels (which you can find from the published deletion screening experiment), then four of the experiments are likely to go through one of these routes; what is the likely event that you would identify the same route in two pools? It is unlikely, and therefore, sequencing of 4 pools cannot tell you if the mutation path is repeatedly sampled or not.

Comment 5:

For the genomic studies, it is not clear if the authors sequenced a pool or a single colony from the evolved strains. This is an important point, since an average sequence will miss out on many mutations and only focus on the mutations inherited from a common ancestral cell. It is also not clear from the section.

Response:

We sequenced population samples from the evolved lines. Our specific question was whether independently evolved lines would show the same high-frequency genetic solution, as is often seen in parallel evolution. Pool sequencing may under-sample rare/private variants, but it is appropriate for detecting such shared, high-frequency routes - and we do not find any. We have clarified this rationale in the Methods/Results.

Comment to Response: Please provide the average sequencing depth of each sequencing run. It is essential to understand the power of this study in identifying mutations. What coverage was used in Xgenome size?

Reviewer #1 (Public review):

In their manuscript, Papadopoli et al explore the role of ETFDH in transformation. They note that ETFDH protein levels are decreased in cancer, and that deletion of ETFDH in cancer cell lines results in increased tumorigenesis, elevated OXPHOS and glycolysis, and a reduction in lipid and amino acid oxidation. The authors attribute these effects to increased amino acid levels stimulating mTORC1 signaling and driving alterations in BCL6 and EIF4EBP1. They conclude that ETFDH1 is epigenetically silenced in a proportion of neoplasms, suggesting a tumor-suppressive function. Overall, the authors logically present clear data and perform appropriate experiments to support their hypotheses.

Reviewer #1 (Public review):

Schafer et al. tested whether the hippocampus tracks social interactions as sequences of neural states within an abstract social space defined by the dimensions of affiliation and power, using a narrative-based task in which participants engaged in dynamic social interactions. The study showed that individual social relationships were represented as distinct trajectories of hippocampal activity patterns. These neural trajectories systematically reflected trial-by-trial changes in affiliation and power between the participant and each character, suggesting that the hippocampus encodes sequences of socially relevant events and their relational structure, extending its well-established role beyond spatial representations.

A major strength of this study is the use of a richly structured, narrative-based task that allows social relationships to evolve dynamically over time. The use of representational similarity analysis provides a principled framework for linking behavioral trajectories in social space to neural pattern dynamics.

One potential limitation concerns temporal autocorrelation in the neural data, as nearby trials are inherently related both behaviorally and temporally within a continuous narrative. Although the authors carefully attempted to control for temporal distance and related confounds, fully disentangling representational similarity driven by social structure from similarity driven by temporal proximity remains challenging within a single-session task design.

While the findings of a two-dimensional representational structure is an important contribution, it remains an open question whether such a representation reflects an inherent property of how the human brain encodes social relationships, or whether it is partly driven by task constraints in which social interactions were limited to changes along two (affiliation and power) dimensions. Future studies that allow social relationships to vary along richer or higher-dimensional feature spaces will be necessary to determine the generality of low dimensional representations.

Reviewer #1 (Public review):

Summary:

The manuscript by Mengxing et al., reports an assessment of three first-order thalamic nuclei (auditory, visual, somatosensory) in a 3 x 2 factorial design to test for specificity of responses in first-order thalamic nuclei to linguistic processing particularly in the left hemisphere. The conditions are reading, speech production, and speech comprehension and their respective control conditions. The authors report the following results:

(1) BOLD-response analyses: left MGB linguistic vs non-linguistic significant; left LGN linguistic vs non-linguistic significant. There is no hemisphere x stimulus interaction.

(2) MVPA: left MGB linguistic vs. non-linguistic significant; bilateral VLN linguistic vs. non-linguistic significant; significant lateralisation in MGB (left MGB responses better classified linguistic vs. non-linguistic in contrast to right).

(3) Functional connectivity: there is, in general, connectivity between the thalamic ROIs and the respective primary cortices independent of linguistics.

Strengths:

The study has a clear and comprehensive design and addresses a timely topic. First-order thalamic nuclei and their interaction with the respective cerebral cortex area are likely key to understanding how perception works in a world where one has to compute highly dynamic stimuli often in an instant. Speech is a prime example of an ecologically important, extremely dynamic, and complex stimulus. The field of the contribution of cerebral cortex-thalamic loops is wide open, and the study presents a solid approach to address their role in different speech modalities (i.e., reading, comprehension, production).

Weaknesses:

I see two major overall weaknesses in the manuscript in its current form:

(1) Statistics:

Unfortunately, I have doubts about the solidity of the statistics. In the analyses of the BOLD responses, the authors do not find significant hemisphere x stimulus interactions. In my view, such results would pre-empt doing a post-hoc t-test. Nevertheless, the authors motivate their post-hoc t-test by 'trends' in the interaction and prior hypotheses. I see two difficulties with that. First, the origin of the prior hypotheses is somewhat unclear (see also the comment below on hypotheses), and the post-hoc t-test is not corrected for multiple comparisons. I find that it is a pity that the authors did not derive more specific hypotheses grounded in the literature to guide the statistical testing, as I think these would have been available, and the response properties of the MGB and LGN also make sense in light of them. In addition, I was wondering whether the MVPA results would also need to be corrected for the three tests, i.e., the three ROIs.

Hypotheses:

In my view, it is relatively unclear where the hypotheses precisely come from. For example, the paragraph on the hypotheses in the introduction (p. 6-7) is devoid of references. I also have the impression that the hypotheses are partly not taking into account previous reports on first-order thalamic nuclei involvement in linguistic vs. non-linguistic processing. For example, the authors test for lateralisation of linguistic vs. non-linguistic responses in all nuclei. However, from previous literature, one could derive the hypothesis that the lateralisation in MGB for speech might be there - previous work shows, for example, that speech recognition abilities consistently correlate with left MGB only (von Kriegstein et al., 2008 Curr Biol; Mihai et al., 2019 eLife). In addition, the involvement of the MGB in speech in noise processing is present in the left MGB (Mihai et al., 2021, J Neuroscience). Developmental dyslexia, which is supposed to be based on imprecise phonological processing (Ramus et al., 2004 TiCS), has alterations in left MGB (Diaz et al., 2012 PNAS; Galaburda et al., 1994 PNAS) and left MGB connections to planum temporale (Tschentscher et al., 2019 J Neurosci) as well as altered lateralisation (Müller-Axt et al., 2025 Brain). Conversely, in the LGN, I'm not aware of any studies showing lateralisation for speech. See, for example, Diaz et al., 2018, Neuroimage, where there are correlations of LGN task-dependent modulation with visual speech recognition behaviour in both LGNs. Thus, based on this literature, one could have predicted the result pattern displayed, for example, in Figure 3A at least for MGB and LGN.

In summary, the motivation for the different hypotheses needs to be carved out more and couched into previous literature that is directly relevant to the topic. The above paragraph is, of course, my view on the topic, but currently, the paper lacks different literature as references to fully understand where the hypotheses are derived from.

Reviewer #1 (Public review):

Summary:

Thach et al. report on the structure and function of trimethylamine N-oxide demethylase (TDM). They identify a novel complex assembly composed of multiple TDM monomers and obtain high-resolution structural information for the catalytic site, including an analysis of its metal composition, which leads them to propose a mechanism for the catalytic reaction.

In addition, the authors describe a novel substrate channel within the TDM complex that connects the N-terminal Zn²-dependent TMAO demethylation domain with the C-terminal tetrahydrofolate (THF)-binding domain. This continuous intramolecular tunnel appears highly optimized for shuttling formaldehyde (HCHO), based on its negative electrostatic properties and restricted width. The authors propose that this channel facilitates the safe transfer of HCHO, enabling its efficient conversion to methylenetetrahydrofolate (MTHF) at the C-terminal domain as a microbial detoxification strategy.

Strengths:

The authors provide convincing high-resolution cryo-EM structural evidence (up to 2 Å) revealing an intriguing complex composed of two full monomers and two half-domains. They further present evidence for the metal ion bound at the active site and articulate a plausible hypothesis for the catalytic cycle. Substantial effort is devoted to optimizing and characterizing enzyme activity, including detailed kinetic analyses across a range of pH values, temperatures, and substrate concentrations. Furthermore, the authors validate their structural insights through functional analysis of active-site point mutants.

In addition, the authors identify a continuous channel for formaldehyde (HCHO) passage within the structure and support this interpretation through molecular dynamics simulations. These analyses suggest an exciting mechanism of specific, dynamic, and gated channeling of HCHO. This finding is particularly appealing, as it implies the existence of a unique, completely enclosed conduit that may be of broad interest, including potential applications in bioengineering.

Weaknesses:

Although the idea of an enclosed channel for HCHO is compelling, the experimental evidence supporting enzymatic assistance in the reaction of HCHO with THF is less convincing. The linear regression analysis shown in Figure 1C demonstrates a THF concentration-dependent decrease in HCHO, but the concentrations used for THF greatly exceed its reported KD (enzyme concentration used in this assay is not reported). It has previously been shown that HCHO and THF can couple spontaneously in a non-enzymatic manner, raising the possibility that the observed effect does not require enzymatic channeling. An additional control that can rule out this possibility would help to strengthen the evidence. For example, mutating the THF binding site to prevent THF binding to the protein complex could clarify whether the observed decrease in HCHO depends on enzyme-mediated proximity effects. A mutation which would specifically disable channeling could be even more convincing (maybe at the narrowest bottleneck).

Another concern is that the observed decrease in HCHO could alternatively arise from a reduced production of HCHO due to a negative allosteric effect of THF binding on the active site. From this perspective, the interpretation would be more convincing if a clear coupled effect could be demonstrated, specifically, that removal of the product (HCHO) from the reaction equilibrium leads to an increase in the catalytic efficiency of the demethylation reaction.

While the enzyme kinetics appear to have been performed thoroughly, the description of the kinetic assays in the Methods section is very brief. Important details such as reaction buffer composition, cofactor identity and concentration (Zn²⁺), enzyme concentration, defined temperature, and precise pH are not clearly stated. Moreover, a detailed methodological description could not be found in the cited reference (6), if I am not mistaken.

The composition of the complex is intriguing but raises some questions. Based on SDS-PAGE analysis, the purified protein appears to be predominantly full-length TDM, and size-exclusion chromatography suggests an apparent molecular weight below 100 kDa. However, the cryo-EM structure reveals a substantially larger complex composed of two full-length monomers and two half-domains.

Given the lack of clear evidence for proteolytic fragments on the SDS-PAGE gel, it is unclear how the observed stoichiometry arises. This raises the possibility of higher-order assemblies or alternative oligomeric states. Did the authors attempt to pick or analyze larger particles during cryo-EM processing? Additional biophysical characterization of particle size distribution - for example, using interferometric scattering microscopy (iSCAT)-could help clarify the oligomeric state of the complex in solution.

The authors mention strict symmetry in the complex, yet C2 symmetry was enforced during refinement. While this is reasonable as an initial approach, it would strengthen the structural interpretation to relax the symmetry to C1 using the C2-refined map as a reference. This could reveal subtle asymmetries or domain-specific differences without sacrificing the overall quality of the reconstruction.

In this context, the proposed catalytic role of Zn²⁺ raises additional questions. Why is a 2:1 enzyme-to-metal stoichiometry observed, and how does this reconcile with previous reports? This point warrants discussion. Does this imply asymmetric catalysis within the complex? Would the stoichiometry change under Zn²⁺-saturating conditions, as no Zn²⁺ appears to be added to the buffers? It would be helpful to clarify whether Zn²⁺ occupancy is equivalent in both active sites when symmetry is not imposed, or whether partial occupancy is observed.

The divalent ion Zn2+ is suggested to activate water for the catalytic reaction. I am not sure if there is a need for a water molecule to explain this catalytic mechanism. Can you please elaborate on this more? As one aspect, it might be helpful to explain in more detail how Zn-OH and D220 are recovered in the last step before a new water molecule comes in.

Overall, the authors were successful in advancing our structural and functional understanding of the TDM complex. They suggest an interesting oligomeric complex composition which should be investigated with additional biophysical techniques.

Additionally, they provide an intriguing hypothesis for a new type of substrate channeling. Additional kinetic experiments focusing on HCHO and THF turnover by enzymatic proximity effects would strengthen this potentially fundamental finding. If this channeling mechanism can be supported by stronger experimental evidence, it would substantially advance our understanding and knowledge of biologic conduits and enable future efforts in the design of artificial cascade catalysis systems with high conversion rate and efficiency, as well as detoxification pathways.

Reviewer #1 (Public review):

This study by Radziun and colleagues investigates the effects of using a hand-augmentation device on mental body representations. The authors use a proprioceptive localisation task to measure metric representations of finger length before and after participants wear the device, and then before and after they learn to use the device, which extends the lengths of the fingers by 10 cm. The authors find changes between different time points, which they interpret as evidence for three distinct forms of plasticity: one related to simply wearing the device, one related to learning to use it, and an aftereffect after taking the device off. A control experiment with a similar device, which does not lengthen the fingers, showed the first and third of these forms of plasticity, but not the second.

This study takes an interesting approach to a timely and theoretically significant issue. The study appears to be appropriately designed and conducted. There are, however, some points which require clarification.

(1) The nature of the localization task is unclear. On its face, the task appears to involve localization of each landmark within the 2-dimensional surface of the touchscreen. However, the regression analysis presupposes that localization is made in a 1-dimensional space. Figure S2 shows that three lines are presented on the screen above the index, middle, and ring fingers, which I imagine the participant is meant to use as a guide. But it is at least conceivable that the perceived location or orientation of the finger might not correspond exactly to these lines. While the method can deal gracefully with proximal-distal translations of the fingers (i.e., with the intercept parameter of the regression), it isn't clear how the participant is supposed to respond if their proprioceptive perception of finger location is translated left-right or rotated relative to the lines on the screen. I also worry that presenting a long, thin line to represent each finger on the screen may not be a neutral method and may prime participants to represent the finger as long and thin.

(2) The task used here fits within a wider family of tasks in the literature using localization judgments of multiple landmarks to map body representations. I feel that some discussion of this broader set of tasks and their use to measure body representation and plasticity is notably absent from the paper. It is also striking to me that some of the present authors have themselves recently criticized the use of landmark localization methods as a measure of represented body size and shape (Peviani et al, 2024, Current Biology). It is therefore surprising to see them use this task here as a measure of represented finger length without commenting on this issue.

(3) 18 participants strikes me as a relatively small sample size for this type of study. It weakens the manuscript that the authors do not provide any justification, or even comment on, the sample size. This is especially true as participants are excluded from the entire sample, and from specific analyses, on rather post-hoc grounds.

(4) I have some concerns about the interpretation of contraction in stage 2. The authors claim that wearing the finger extended produces "a contraction",i.e., an "under-representation" (page 12). But in both experiments, regression slopes in stage 2 were not significantly different from 1 (i.e., 0.98 [SE: 0.07] in Exp 1a and 1.04 [SE: 0.09] in Experiment 1b). So how can that be interpreted as "under-representation"?

(5) I also have concerns about the interpretation of the stretch that is claimed to occur following training. In Exp 1a, regression slopes in stage 3 are on average 1.15. That is LESS than in the pretest at stage 1 (mean: 1.16). The idea of stretch only comes about because of the lower slopes in stage 2, which the authors have interpreted as reflecting contraction. So what the authors call stretch and a 2nd form of plasticity could just be the contraction from stage 2 wearing off or dissipating, since perceived finger length in stage 3 just appears to return to the baseline level seen in stage 1. While the authors describe their results in terms of three distinct forms of plasticity, these are not in fact statistically independent. The dip in regression slopes in stage 2 is interpreted as evidence for two distinct plasticity effects, which I do not find convincing.

(6) The distinction between plasticity at stage 3 (which appears specific to augmentation) and plasticity at stage 4 (which does not appear specific, as it also occurs in Experiment 1b) feels strained. This feels like a very subtle distinction, and the theoretical significance of it is not convincingly developed.

(7) The reporting of statistics is not always consistent. For example, 95%CIs are presented for regression slopes in stages 1, 3, and 4, but not for stage 2. Statistics are performed on regression slopes, except for one t-test on page 7 comparing lengths in cm. Estimates of effect size would be nice additions to statistical tests.

(8) Minor point: On page 4, the authors write, "These included sorting colored blocks, stacking a Jenga tower, and sorting pegs into holes; the latter task required fine-grained manipulation and was used as our outcome measure of motor learning." This suggests that peg sorting was the outcome measure, but in Figure 1D, Jenga is presented as the outcome measure.

Reviewer #1 (Public review):

Summary:

Ewing sarcoma is an aggressive pediatric cancer driven by the EWS-FLI oncogene. Ewing sarcoma cells are addicted to this chimeric transcription factor, which represents a strong therapeutic vulnerability. Unfortunately, targeting EWS-FLI has proven to be very difficult and better understanding how this chimeric transcription factor works is critical to achieving this goal. Towards this perspective, the group had previously identified a DBD-𝛼4 helix (DBD) in FLI that appears to be necessary to mediate EWS-FLI transcriptomic activity. Here, the authors used multi-omic approaches, including CUT&tag, RNAseq, and MicroC to investigate the impact of this DBD domain. Importantly, these experiments were performed in the A673 Ewing sarcoma model where endogenous EWS-FLI was silenced, and EWS-FLI-DBD proficient or deficient isoforms were re-expressed (isogenic context). They found that the DBD domain is key to mediate EWS-FLI cis activity (at msat) and to generate the formation of specific TADs. Furthermore, cells expressing DBD deficient EWS-FLI display very poor colony forming capacity, highlighting that targeting this domain may lead to therapeutic perspectives.

Strengths:

The group has strong expertise in Ewing sarcoma genetics and epigenetics and also in using and analyzing this model (Theisen et al., 2019; Boone et al., 2021; Showpnil et al., 2022).

They aim at better understanding how EWS-FLI mediated its oncogenic activity, which is critical to eventually identifying novel therapies against this aggressive cancer.

They use the most recent state-of-the-art omics methods to investigate transcriptome, epigenetics, and genome conformation methods. In particular, Micro-C enables achieving up to 1kb resolved 3D chromatin structures, making it possible to investigate a large number of TADs and sub-TADs structures where EWS-FLI1 mediates its oncogenic activity.

They performed all their experiments in an Ewing sarcoma genetic background (A673 cells) which circumvents bias from previously reported approaches when working in non-orthologous cell models using similar approaches.

Weaknesses:

The main weakness stems from the poor reproducibility of the Micro-C data. Indeed, the distances and clustering observed between replicates appear to be similar to, or even greater than, those observed between biological conditions. For instance, in Figure 1B, we do not observe any clear clustering among DBD1, DBD2, DBD+1, and DBD+2. Although no further experiments were performed, the authors tempered their claims by rephrasing aspects related to this issue and the reviewer also acknowledged that the transcriptomic data are convincing and support their findings.

Regarding DBD stability and the cycloheximide experiments requested to rule out any half-life bias of DBD (as higher stability of the re-expressed DBD+ could also partially explain the results independently of a 3D conformational change), the reviewer acknowledged that the WB, RNA-seq data and agar assays presented by the authors appear reproducible across experiments.

Reviewer #1 (Public review):

Summary:

This study by Howe and colleagues investigates the role of the posterolateral cortical amygdala (plCoA) in mediating innate responses to odors, specifically attraction and aversion. By combining optogenetic stimulation, single-cell RNA sequencing, and spatial analysis, the authors identify a topographically organized circuit within plCoA that governs these behaviors. They show that specific glutamatergic neurons in the anterior and posterior regions of plCoA are responsible for driving attraction and avoidance, respectively, and that these neurons project to distinct downstream regions, including the medial amygdala and nucleus accumbens, to control these responses.

Strengths:

The major strength of the study is the thoroughness of the experimental approach, which combines advanced techniques in neural manipulation and mapping with high-resolution molecular profiling. The identification of a topographically organized circuit in plCoA and the connection between molecularly defined populations and distinct behaviors is a notable contribution to understanding the neural basis of innate motivational responses. Additionally, the use of fucntional manipulations adds depth to the findings, offering valuable insights into the functionality of specific neuronal populations.

Weaknesses:

Previously described weaknesses in the study's methods and interpretation were fully addressed during revision. Locomotor behavior of the mice during head-fixed imaging experiments was added and analysis of the correlation of locomotion with neural activity was also added.

This work provides significant insights into the neural circuits underlying innate behaviors and opens new avenues for further research. The findings are particularly relevant for understanding the neural basis of motivational behaviors in response to sensory stimuli, and the methods used could be valuable for researchers studying similar circuits in other brain regions. If the authors address the methodological issues raised, this work could have a substantial impact on the field, contributing to both basic neuroscience and translational research on the neural control of behavior.

Reviewer #1 (Public review):

Summary:

This study set out to investigate potential pharmacological drug-drug interactions between the two most common antimalarial classes, the artemisinins and quinolines. There is strong rationale for this aim, because drugs from these classes are already widely-used in Artemisinin Combination Therapies (ACTs) in the clinic, and drug combinations are an important consideration in the development of new medicines. Furthermore, whilst there is ample literature proposing many diverse mechanisms of action and resistance for the artemisinins and quinolines, it is generally accepted that the mechanisms for both classes involve heme metabolism in the parasite, and that artemisinin activity is dependent on activation by reduced heme. The study was designed to measure drug-drug interactions associated with a short pulse exposure (4 h) that is reminiscent of the short duration of artemisinin exposure obtained after in vivo dosing. Clear antagonism was observed between dihydroartemisinin (DHA) and chloroquine, which became even more extensive in chloroquine-resistant parasites. Antagonism was also observed in this assay for the more clinically-relevant ACT partner drugs piperaquine and amodiaquine, but not for other ACT partners mefloquine and lumefantrine, which don't share the 4-aminoquinoline structure or mode of action. Interestingly, chloroquine induced an artemisinin resistance phenotype in the standard in vitro Ring-stage Survival Assay, whereas this effect was not as extensive for piperaquine.

The authors also utilised a heme-reactive probe to demonstrate that the 4-aminoquinolines can inhibit heme-mediated activation of the probe within parasites, which suggests that the mechanism of antagonism involves the inactivation of heme, rendering it unable to activate the artemisinins. Measurement of protein ubiquitination showed reduced DHA-induced protein damage in the presence of chloroquine, which is also consistent with decreased heme-mediated activation, and/or with decreased DHA activity more generally.

Overall, the study clearly demonstrates a mechanistic antagonism between DHA and 4-aminoquinoline antimalarials in vitro. It is interesting that this combination is successfully used to treat millions of malaria cases every year, which may raise questions about the clinical relevance of this finding. However, the conclusions in this paper are supported by multiple lines of evidence and the data is clearly and transparently presented, leaving no doubt that DHA activity is compromised by the presence of chloroquine in vitro. It is perhaps fortunate the that the clinical dosing regimens of 4-aminoquinoline-based ACTs have been sufficient to maintain clinical efficacy despite the non-optimal combination. Nevertheless, optimisation of antimalarial combinations and dosing regimens is becoming more important in the current era of increasing resistance to artemisinins and 4-aminoquinolines. Therefore, these findings should be considered when proposing new treatment regimens (including Triple-ACTs) and the assays described in this study should be performed on new drug combinations that are proposed for new or existing antimalarial medicines.

Strengths:

This manuscript is clearly written and the data presented is clear and complete. The key conclusions are supported by multiple lines of evidence, and most findings are replicated with multiple drugs within a class, and across multiple parasite strains, thus providing more confidence in the generalisability of these findings across the 4-aminoquinoline and peroxide drug classes.

A key strength of this study was the focus on short pulse exposures to DHA (4 h in trophs and 3 h in rings), which is relevant to the in vivo exposure of artemisinins. Artemisinin resistance has had a significant impact on treatment outcomes in South-East Asia, and is now emerging in Africa, but is not detected using a 'standard' 48 or 72 h in vitro growth inhibition assay. It is only in the RSA (a short pulse of 3-6 h treatment of early ring stage parasites) that the resistance phenotype can be detected in vitro. Therefore, assays based on this short pulse exposure provide the most relevant approach to determine whether drug-drug interactions are likely to have a clinically-relevant impact on DHA activity. These assays clearly showed antagonism between DHA and 4-aminoquinolines (chloroquine, piperaquine, amodiaquine and ferroquine) in trophozoite stages. Interestingly, whilst chloroquine clearly induced an artemisinin-resistant phenotype in the RSA, piperaquine only had a minor impact on the early ring stage activity of DHA, which may be fortunate considering that piperaquine is a currently recommended DHA partner drug in ACTs, whereas chloroquine is not.

The evaluation of additional drug combinations at the end of this paper is a valuable addition, which increases the potential impact of this work. The finding of antagonism between piperaquine and OZ439 in trophozoites is consistent with the general interactions observed between peroxides and 4-aminoquinolines, and it may be interesting to see whether piperaquine impacts the ring-stage activity of OZ439.

The evaluation of reactive heme in parasites using a fluorescent sensor, combined with the measurement of K48-linked ubiquitin, further support the findings of this study, providing independent read-outs for the chloroquine-induced antagonism.<br /> The in-depth discussion of the interpretation and implications of the results are an additional strength of this manuscript. Whilst the discussion section is rather lengthy, there are important caveats to the interpretation of some of these results, and clear relevance to the future management of malaria that require these detailed explanations.

Overall, this is a high quality manuscript describing an important study that has implications for the selection of antimalarial combinations for new and existing malaria medicines.

Weaknesses:

This study is an in vitro study of parasite cultures, and therefore caution should be taken when applying these findings to decisions about clinical combinations. The drug concentrations and exposure durations in these assays are intended to represent clinically relevant exposures, although it is recognised that the in vitro system is somewhat simplified and there may be additional factors that influence in vivo activity. This limitation is reasonably well acknowledged in the manuscript.

It is also important to recognise that the majority of the key findings regarding antagonism are based on trophozoite-stage parasites, and one must show caution when generalising these findings to other stages or scenarios. For example, piperaquine showed clear antagonism in trophozoite stages, but minimal impact in ring stages under these assay conditions.

A key limitation is the interpretation of the mechanistic studies that implicate heme-mediated artemisinin activation as the mechanism underpinning antagonism by chloroquine. This study did not directly measure the activation of artemisinins. The data obtained from the activation of the fluorescent probe are generally supportive of chloroquine suppressing the heme-mediated activation of artemisinins, and I think this is the most likely explanation, but there are significant caveats to consider. Primarily, the inconsistency between the fluorescence profile in the chemical reactions and the cell-based assay raise questions about the accuracy of this readout. In the chemical reaction, mefloquine and chloroquine showed identical inhibition of fluorescence, whereas piperaquine had minimal impact. On the contrary, in the cell, chloroquine and piperaquine had similar impacts on fluorescence, but mefloquine had minimal impact. This inconsistency indicates that the cellular fluorescence based on this sensor does not give a simple direct readout of the reactivity of ferrous heme, and therefore, these results should be interpreted with caution. Indeed, the correlation between fluorescence and antagonism for the tested drugs is a correlation, not causation. There could be several reasons for the disconnect between the chemical and biological results, either via additional mechanisms that quench fluorescence, or the presence of biomolecules that alter the oxidation state or coordination chemistry of heme or other potential catalysts of this sensor. It is possible that another factor that influences the H-FluNox fluorescence in cells also influences the DHA activity in cells, leading to the correlation with activity. It should be noted that H-FluNox is not a chemical analogue of artemisinins. It's activation relies on Fenton-like chemistry, but with a N-O rather that O-O bond, and it possesses very different steric and electronic substituents around the reactive centre, which are known to alter reactivity to different iron sources. Despite these limitations, the authors have provided reasonable justification for the use of this probe to directly visualise heme reactivity in cells, and the results are still informative.

Another interesting finding that was not elaborated by the authors is the impact of chloroquine in the DHA dose-response curves from the ring stage assays. Detection of artemisinin resistance in the RSA generally focuses on the % survival at high DHA concentrations (700 nM) as there is minimal shift in the IC50 (see Fig 2), however, chloroquine clearly induces a shift in the IC50 (~5-fold), where the whole curve is shifted to the right, whereas the increase in % survival is relatively small. This different profile suggests that the mechanism of chloroquine-induced antagonism may be different to the mechanism of artemisinin resistance. Current evidence regarding the mechanism of artemisinin resistance generally points towards decreased heme-mediated drug activation due to a decrease in hemoglobin uptake, which should be analogous to the decrease in heme-mediated drug activation caused by chloroquine. However, these different dose response curves suggest different mechanisms are primarily responsible. Additional mechanisms have been proposed for artemisinin resistance, involving redox or heat stress responses, proteostatic responses, mitochondrial function, dormancy and PI3K signalling among others. Whilst the H-FluNox probe generally supports the idea that chloroquine suppresses heme-mediated DHA activation, it remains plausible that chloroquine could induce these, or other, cellular responses that suppress DHA activity.

Impact:

This study has important implications for the selection of drugs to form combinations for the treatment of malaria. The overall findings of antagonism between peroxide antimalarials and 4-aminoquinolines in the trophozoite stage are robust, and the this carries across to the ring stage for chloroquine.

The manuscript also provides a plausible mechanism to explain the antagonism, although future work will be required to further explore the details of this mechanism and to rule out alternative factors that may contribute.

Overall, this is an important contribution to the field and provides a clear justification for the evaluation of potential drug combinations in relevant in vitro assays before clinical testing.

Reviewer #1 (Public review):

Summary:

Mitochondria encode a small set of proteins that are made inside the organelle by specialized ribosomes. When this mitochondrial translation system fails, oxidative phosphorylation is impaired, an outcome that is particularly harmful to energy-demanding tissues such as the heart. In this manuscript, the authors use a targeted CRISPR/Cas9 screen in cultured cells grown on galactose (a condition that forces reliance on oxidative phosphorylation) to identify genes required for mitochondrial activity. They highlight EOLA1, previously studied mainly in inflammatory contexts, as a top candidate.

Strengths:

The authors present data suggesting that EOLA1 is imported into mitochondria via an N-terminal targeting sequence and resides in the mitochondrial matrix. Loss of EOLA1 reduces oxygen consumption and is associated with altered mitochondrial ultrastructure. Mechanistically, affinity purification suggests interaction with mitochondrial elongation factors TUFM (mtEF-Tu), and RNA immunoprecipitation experiments enrich 12S mt-rRNA, consistent with a relationship to the small ribosomal subunit. Multiple assays, including sucrose-gradient profiling, reduced abundance of selected mtDNA-encoded proteins, and a click-chemistry labeling approach, support the conclusion that mitochondrial protein synthesis is decreased in EOLA1-deficient cells. Finally, whole-body Eola1 knockout mice show echocardiographic findings consistent with dilated cardiomyopathy and reduced levels of representative mitochondrially encoded proteins in cardiac tissue.

How to interpret the work:

The data support a role for EOLA1 in maintaining mitochondrial gene expression and oxidative phosphorylation capacity, and they plausibly implicate mitochondrial translation.

Weaknesses:

The main caveat is that the study does not yet establish how EOLA1 acts, whether it directly modulates translation elongation through TUFM, whether it is primarily required for mitoribosome biogenesis/rRNA stability, or whether it influences translation indirectly through mitochondrial stress pathways. The in vivo phenotype is intriguing, but without tissue-specific deletion/rescue and deeper cardiac pathology/mitochondrial functional measurements, it remains uncertain how directly the heart phenotype reflects a cardiomyocyte-autonomous defect in mitochondrial translation.

Reviewer #1 (Public review):

Summary:

Du, Daniel X. et al studied the interaction of the ultrashort electron and laser pulses inside a scanning electron microscopy (SEM), aiming to build a foundation for pulsed laser phase plate electron microscopy, in which the contrast of cryo samples can be significantly increased. The author modified a commercial SEM to accommodate optics to introduce a laser beam inside the instrument to overlap with the electron beam and performed multiple experiments aimed to characterize the electron-light interaction, particularly reaching an extremely high phase shift of >400 rad. Moreover, the authors built a theoretical model for this interaction and estimated the laser beam parameters needed to reach 90 degrees phase shift in transmission electron microscopy (TEM).

Strengths:

The conclusion on the interaction of the electron pulses and laser pulses is well described and supported by the experiment.

The presented instrument can serve as a great tool for studying fundamental interactions of electrons with extremely intense light pulses.

Weaknesses:

The authors motivate the project by using the pulsed electron beam with a phase shift for improving the contrast in cryo-EM, and while they indicate the low current in UEM, they do not discuss the limitations of the laser beam properties.

Such, even for 1 ps electron pulses with the repetition rate of 100 GHz (duty cycle of 10%), they will need to use 100 GHz laser pulses with pulse energies of at least ~1 uJ a second (the lowest pulse energy reported in the simulations in Figure 4), which would mean that ~10 kW of optical power needs to enter the electron microscope and be dumped somewhere after leaving the instrument. This significantly complicates the system and, in my view, makes it harder to use a pulsed laser phase plate in cryo-EM due to either low acquisition rate at lower repetition rates or extreme difficulties to operate multi kW ultrafast laser system.

I would also expect the unscattered electron beam diameter to be <1 micron, which would significantly change the plot in 4b for the 300 keV electron beam.

Adding experimental parameters for a typical cryo-EM experiment with the pulsed phase plate, including the repetition rate, electron pulse duration, number of electrons per pulse, electron beam size, and the parameters of the laser beam (wavelength, laser pulse duration, pulse energy), will help readers better understand technical requirements for the proposed cryo-EM experiments.

Reviewer #2 (Public review):

Zhang et al. have developed an advanced three-dimensional culture system of human endometrial cells, termed a receptive endometrial assembloid, that models the uterine lining during the crucial window of implantation (WOI). During this mid-secretory phase of the menstrual cycle, the endometrium becomes receptive to an embryo, undergoing distinctive changes. In this work, endometrial cells (epithelial glands, stromal cells, and immune cells from patient samples) were grown into spheroid assembloids and treated with a sequence of hormones to mimic the natural cycle. Notably, the authors added pregnancy-related factors (such as hCG and placental lactogen) on top of estrogen and progesterone, pushing the tissue construct into a highly differentiated, receptive state. The resulting WOI assembloid closely resembles a natural receptive endometrium in both structure and function. The cultures form characteristic surface structures like pinopodes and exhibit abundant motile cilia on the epithelial cells, both known hallmarks of the mid-secretory phase. The assembloids also show signs of stromal cell decidualization and an epithelial mesenchymal transition, like process at the implantation interface, reflecting how real endometrial cells prepare for possible embryo invasion.

Although the WOI assembloid represents an important step forward, it still has limitations: the supportive stromal and immune cell populations decrease over time in culture, so only early-passage assembloids retain full complexity. Additionally, the differences between the WOI assembloid and a conventional secretory-phase organoid are more quantitative than absolute; both respond to hormones and develop secretory features, but the WOI assembloid achieves a higher degree of differentiation due to the addition of "pregnancy" signals. Overall, while it's a reinforced model (not an exact replica of the natural endometrium), it provides a valuable in vitro system for implantation studies and testing potential interventions, with opportunities to improve its long-term stability and biological fidelity in the future.

[Editors' note: the authors have responded to the previous round of recommendations.]

Reviewer #1 (Public review):

Summary:

This paper presents maRQup a Python pipeline for automating the quantitative analysis of preclinical cancer immunotherapy experiments using bioluminescent imaging in mice. maRQup processes images to quantify tumor burden over time and across anatomical regions, enabling large-scale analysis of over 1,000 mice. The study uses this tool to compare different CAR-T cell constructs and doses, identifying differences in initial tumor control and relapse rates, particularly noting that CD19.CD28 CAR-T cells show faster initial killing but higher relapse compared to CD19.4-1BB CAR-T cells. Furthermore, maRQup facilitates the spatiotemporal analysis of tumor dynamics, revealing differences in growth patterns based on anatomical location, such as the snout exhibiting more resistance to treatment than bone marrow.

Strengths:

(1) The maRQup pipeline enables the automatic processing of a large dataset of over 1,000 mice, providing investigators with a rapid and efficient method for analyzing extensive bioluminescent tumor image data.

(2) Through image processing steps like tail removal and vertical scaling, maRQup normalizes mouse dimensions to facilitate the alignment of anatomical regions across images. This process enables the reliable demarcation of nine distinct anatomical regions within each mouse image, serving as a basis for spatiotemporal analysis of tumor burden within these consistent regions by quantifying average radiance per pixel.

Weaknesses:

(1) While the pipeline aims to standardize images for regional assessment, the reliance on scaling primarily along the vertical axis after tail removal may introduce limitations to the quantitative robustness of the anatomically defined regions. This approach does not account for potential non-linear growth across dimensions in animals of different ages or sizes, which could result in relative stretching or shrinking of subjects compared to an average reference.

(2) Furthermore, despite excluding severely slanted images, the pipeline does not fully normalize for variations in animal pose during image acquisition (e.g., tucked body, leaning). This pose variability not only impacts the precise relative positioning of internal anatomical regions, potentially making their definition based on relative image coordinates more qualitative than truly quantitative for precise regional analysis, but it also means that the bioluminescent light signal from the tumor will not propagate equally to the camera as photons will travel differentially through the tissue. This differing light path through tissues due to variable positioning can introduce large variability in the measured radiance that was not accounted for in the analysis algorithm. Achieving more robust anatomical and quantitative normalization might require methods that control animal posture using a rigid structure during imaging.

Comments on revisions:

(1) Clarification of 2D Analysis. We strongly recommend that the authors explicitly define maRQup as a 2D spatiotemporal analysis technique. Since optical imaging quantification is inherently dependent on tissue type and signal depth, characterizing this as a 3D or volumetric method without tomographic correction is inaccurate. Please precede "spatiotemporal" with "2D" throughout the text to ensure precision regarding the method's capabilities.

(2) Data Validation and Scaling in Supplemental Figure g currently lacks the units necessary to support the assertion.

Non-Uniform Growth: The authors' method implies that mouse growth is linear and uniform in all directions (isotropic). However, murine growth is not akin to the inflation of a balloon; animals elongate and widen at different rates. The current scaling does not account for these physiological non-linearities.

Pose Variability: The scaling approach appears to neglect significant variability in animal positioning. Even under anesthesia, animal pose is rarely identical across subjects or time points.

Requirement for Evidence: Without quantitative data, there appears to be significant differences between the individual images and the merged image. If the authors assert that this is a "classical setting" where mouse positioning is 100% consistent and growth curves are identical in multiple dimensions, please provide specific references that validate these assumptions. Otherwise, the scaling must be corrected to account for anisotropic growth and pose differences or stated that scaling was only based on one dimension.

(3) Methodology of Spatial Regions The manuscript does not currently indicate how the nine distinct spatial regions were determined. Please expand the methods section to include the specific segmentation algorithms or anatomical criteria used to define these regions, as this is critical for reproducibility.