Dates are correct: she started with neo-adjuvant treatment, then after a year they discovered a bone metastasis but they still decided to do a hygenic mastectomy and axillary clearance

no correction needed

Dates were checked and adapted

Dates were checked and adapted

Learn how to integrate AI into your web application using the MERN stack. This guide covers key concepts, tools, and best practices for building an AI-powered web app with MongoDB, Express, React, and Node.js.

On the erosion of middle class America. Poverty line is around 140k if actual costs taken into account. The 1960s benchmark assumed cost of food to be 1/3 of overall costs. Now it's 7% or so, meaning 1/15 of overall costs. This pushes up the poverty line to 5 times the level used, or some 150k USD pa

Example of a proxy being used as 'measurement' and the assumptions in a proxy never re-evaluated.

would be good to have some answers to the exercises. stuck on number 4

campisme ?

eLife Assessment

This study concerns how macaque visual cortical area MT represents stimuli composed of more than one speed of motion. The study is valuable because little is known about how the visual pathway segments and preserves information about multiple stimuli, and the study involves perceptual reports from both humans and one monkey regarding whether there are one or two speeds in the stimulus. The study presents compelling evidence that (on average) MT neurons shift from faster-speed-takes-all at low speeds to representing the average of the two speeds at higher speeds. Ultimately, this study raises intriguing questions about how exactly the response patterns in visual cortical area MT might preserve information about each speed, since such information could potentially be lost in an average response as described here, depending on assumptions about how MT activity is evaluated by other visual areas.

Reviewer #1 (Public review):

Summary:

Most studies in sensory neuroscience investigate how individual sensory stimuli are represented in the brain (e.g., the motion or color of a single object). This study starts tackling the more difficult question of how the brain represents multiple stimuli simultaneously and how these representations help to segregate objects from cluttered scenes with overlapping objects.

Strengths:

The authors first document the ability of humans to segregate two motion patterns based on differences in speed. Then they show that a monkey's performance is largely similar; thus establishing the monkey as a good model to study the underlying neural representations.

Careful quantification of the neural responses in the middle temporal area during the simultaneous presentation of fast and slow speeds leads to the surprising finding that, at low average speeds, many neurons respond as if the slowest speed is not present, while they show averaged responses at high speeds. This unexpected complexity of the integration of multiple stimuli is key to the model developed in this paper.

One experiment in which attention is drawn away from the receptive field supports the claim that this is not due to the involuntary capture of attention by fast speeds.

A classifier using the neuronal response and trained to distinguish single speed from bi-speed stimuli shows a similar overall performance and dependence on the mean speed as the monkey. This supports the claim that these neurons may indeed underlie the animal's decision process.

The authors expand the well-established divisive normalization model to capture the responses to bi-speed stimuli. The incremental modeling (eq 9 and 10) clarifies which aspects of the tuning curves are captured by the parameters.

Reviewer #3 (Public review):

Summary:

This study concerns how macaque visual cortical area MT represents stimuli composed of more than one speed of motion.

Strengths:

The study is valuable because little is known about how the visual pathway segments and preserves information about multiple stimuli. The study presents compelling evidence that (on average) MT neurons shift from faster-speed-takes-all at low speeds to representing the average of the two speeds at higher speeds. An additional strength of the study is the inclusion of perceptual reports from both humans and one monkey participant performing a task in which they judged whether the stimuli involved one vs two different speeds. Ultimately, this study raises intriguing questions about how exactly the response patterns in visual cortical area MT might preserve information about each speed, since such information is potentially lost in an average response as described here.

Reviewing Editor comment on revised version:

The remaining concern was resolved.

Author response:

The following is the authors’ response to the previous reviews

Reviewer #3 (Recommendations for the authors):

The authors have done an excellent job of addressing most comments, but my concerns about Figure 5 remain. I appreciate the authors' efforts to address the problem involving Rs being part of the computation on both the x and y axes of Figure 5, but addressing this via simulation addresses statistical significance but overlooks effect size. I think the authors may have misunderstood my original suggestion, so I will attempt to explain it better here. Since "Rs" is an average across all trials, the trials could be subdivided in two halves to compute two separate averages - for example, an average of the even numbered trials and an average of the odd numbered trials. Then you would use the "Rs" from the even numbered trials for one axis and the "Rs" from the odd numbered trials for the other. You would then plot R-Rs_even vs Rf-Rs_odd. This would remove the confound from this figure, and allow the text/interpretation to be largely unchanged (assuming the results continue to look as they do).

We have added a description and the result of the new analysis (line #321 to #332), and a supplementary figure (Suppl. Fig. 1) (line #1464 to #1477). 

“We calculated 𝑅_𝑠 in the ordinate and abscissa of Figure 5A-E using responses averaged across different subsets of trials, such that 𝑅_𝑠 was no longer a common term in the ordinate and abscissa. For each neuron, we determined 𝑅_𝑠1 by averaging the firing rates of 𝑅_𝑠 across half of the recorded trials, selected randomly. We also determined 𝑅_𝑠2 by averaging the firing rates of 𝑅_𝑠 across the rest of the trials.  We regressed (𝑅 − 𝑅_𝑠1 )  on (𝑅_𝑓 − 𝑅_𝑠2) , as well as (𝑅_𝑠 - 𝑅_𝑠2)  on (𝑅_𝑓 − 𝑅_𝑠1), and repeated the procedure 50 times. The averaged slopes obtained with 𝑅_𝑠 from the split trials showed the same pattern as those using 𝑅_𝑠 from all trials (Table 1 and Supplementary Fig. 1), although the coefficient of determination was slightly reduced (Table 1). For ×4 speed separation, the slopes were nearly identical to those shown in Figure 5F1. For ×2 speed separation, the slopes were slightly smaller than those in Figure 5F2, but followed the same pattern (Supplementary Fig. 1). Together, these analysis results confirmed the faster-speed bias at the slow stimulus speeds, and the change of the response weights as stimulus speeds increased.”

An additional remaining item concerns the terminology weighted sum, in the context of the constraint that wf and ws must sum to one. My opinion is that it is non-standard to use weighted sum when the computation is a weighted average, but as long as the authors make their meaning clear, the reader will be able to follow. I suggest adding some phrasing to explain to the reader the shift in interpretation from the more general weighted sum to the more constrained weighted average. Specifically, "weighted sum" first appears on line 268, and then the additional constraint of ws + wf =1 is introduced on line 278. Somewhere around line 278, it would be useful to include a sentence stating that this constraint means the weighted sum is constrained to be a weighted average.

Thanks for the suggestion. We have modified the text as follows. Since we made other modifications in the text, the line numbers are slightly different from the last version. 

Line #274 to 275: 

“Since it is not possible to solve for both variables, 𝑤_𝑠 and 𝑤_𝑓, from a single equation (Eq. 5) with three data points, we introduced an additional constraint: 𝑤_𝑠 + 𝑤_𝑓 =1. With this constraint, the weighted sum becomes a weighted average.”

Also on line #309:

“First, at each speed pair and for each of the 100 neurons in the data sample shown in Figure 5, we simulated the response to the bi-speed stimuli (𝑅_𝑒) as a randomly weighted average of 𝑅_𝑓 and 𝑅_𝑠 of the same neuron. 

in which 𝑎 was a randomly generated weight (between 0 and 1) for 𝑅_𝑓, and the weights for 𝑅_𝑓 and 𝑅_𝑠 summed to one.”

The exact method to calculate this is not mentioned anywhere in the text.

A variable is a column, an observation a row and different types of observations are in different tables

Tidy data is made up for values, each value is from an observation and each observation has one or more variables

Gălûñ′lătĭ, secondo la mitologia Cherokee, è un mondo creato prima dell'esistenza della Terra.

[https://www.cherokeepins.org/post/cherokee-stories-and-the-birth-of-a-new-world-the-first-fire]

Ani′-Hyûñ′tĭkwălâ′skĭ è il nome, nella mitologia Cherokee, per "The Thunders," il termine plurale per indicare "coloro che hanno dato il fuoco".

[https://www.cherokeepins.org/post/cherokee-stories-and-the-birth-of-a-new-world-the-first-fire]

recipiente intrecciato

tessere

[https://www.wordreference.com/enit/spun]

Kănăne′skĭ Amai′yĕhĭ, the water spider in the Cherokee myth.

[https://www.cherokeepins.org/post/cherokee-stories-and-the-birth-of-a-new-world-the-first-fire]

"Blacksnake the climber" likely refers to various black-colored snakes, particularly the black rat snake, known for their exceptional climbing abilities due to their specialized belly scales. Gûle′gĭ in the Cherokjee myth.

[https://developmentserver.ravenspacepublishing.org/the-cherokee-natural-world/blacksnake-or-rat-snake]

folata (d'aria)

[https://dictionary.cambridge.org/it/dizionario/inglese-italiano/blast]

Used in athe Cherokee myth to refer to a barn owl, which is also known as a screech owl.

[https://www.cherokeepins.org/post/cherokee-stories-and-the-birth-of-a-new-world-the-first-fire]

gufo

[https://www.wordreference.com/enit/screech%20owl]

si era bruciato

[https://www.wordreference.com/enit/scorched]

corvo maggiore

[https://www.wordreference.com/enit/raven]

platano

[https://www.wordreference.com/enit/sycamore]

ЕБАНАТЫ ПРИЕМ

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)): The authors map the ZFP36L1 protein interactome in human T cells using UltraID proximity labeling combined with quantitative mass spectrometry. They optimize labeling conditions in primary T cells, profile resting and activated cells, and include a time course at 2, 5, and 16 hours. They complement the interactome with co-immunoprecipitation in the presence or absence of RNase to assess RNA dependence. They then test selected candidates using CRISPR knockouts in primary T cells, focusing on UPF1 and GIGYF1/2, and report effects on global translation, stress, activation markers, and ZFP36L1 protein levels. The work argues that ZFP36L1 sits at the center of multiple post-transcriptional pathways in T cells (which in itself is not a novel finding) and that UPF1 supports ZFP36L1 expression at the mRNA and protein level. The main model system is primary human T cells, with some data in Jurkat cells.

The core datasets show thousands of identified proteins in total lysates and enriched biotinylated fractions. Known partners from CCR4-NOT, decapping, stress granules, and P-bodies appear, with additional candidates like GIGYF1/2, PATL1, DDX6, and UPF1. Time-resolved labeling suggests shifts in proximity during early activation. Co-IP with and without RNase suggests both RNA-dependent and RNA-independent contacts. CRISPR loss of UPF1 or GIGYF1/2 increases translation at rest and elevates activation markers, and UPF1 loss reduces ZFP36L1 protein and mRNA while MG132 does not rescue protein levels; UPF1 RIP enriches ZFP36L1 mRNA.

Among patterns worth noting are that the activation state drives the principal variance in both proteome and proximity datasets. Deadenylation, decapping, and granule proteins are consistently near ZFP36L1 across conditions, while some contacts dip at 2 hours and recover by 5 to 16 hours. Mitochondrial ribosomal proteins become more proximal later. UPF1 and GIGYF1 show time-linked behavior and RNase sensitivity that fits roles in mRNA surveillance and translational control. These observations support a dynamic hub model, though they remain proximity-based rather than direct binding maps.

We thank the reviewer for their careful reading and thoughtful summary. Please find our point-to point response below.

Major comments

1) The key conclusions are directionally convincing for a broad and dynamic ZFP36L1 neighborhood in human T cells. The data robustly recover established complexes and add plausible candidates. The time-course and RNase experiments strengthen the claim that interactions shift with activation state and RNA context. The functional tests around UPF1 and GIGYF1/2 point to biological relevance. That said, some statements could be qualified. The statement that ZFP36L1 "coordinates" multiple pathways implies mechanism and directionality that proximity data alone cannot prove. I suggest reframing as "positions ZFP36L1 within" or "supports a model where ZFP36L1 sits within" these networks.

We thank this reviewer for considering our data ‘directionally convincing, and robust, adding new plausible candidates as interactors with ZFP36L1’. We agree that the proposed wording is more appropriate and will change it accordingly.

2) UPF1, as an upstream regulator of ZFP36L1 expression, is a promising lead. The reduction of ZFP36L1 protein and mRNA in UPF1 knockout, the non-rescue by MG132, and the UPF1 RIP on ZFP36L1 mRNA together argue that UPF1 influences ZFP36L1 transcript output or processing. This claim would read stronger with one short rescue or perturbation that pins the mechanism. A compact test would be UPF1 re-expression in UPF1-deficient T cells with wild-type and helicase-dead alleles. This is realistic in primary T cells using mRNA electroporation or virus-based systems. Approximate time 2 to 3 weeks, including guide design check and expansion. Reagents and sequencing about 2 to 4k USD depending on donor numbers. This would help separate viability or stress effects from a direct role in ZFP36L1 mRNA handling.

We agree that a rescue experiment with wild-type and helicase-dead UPF1 in UPF1-deficient primary T cells would be interesting. Unfortunately, however, UPF1 knockout T cells are less viable and divide less (Supp Figure 6B), making further manipulations such as re-expression by viral transduction technically impossible. We will clarify this limitation in the Discussion and will more explicitly indicate that UPF1 promotes ZFP36L1 mRNA and protein expression, while acknowledging that the precise mechanistic contribution of UPF1 (e.g. to transcript processing, export, or surveillance) remain to be fully resolved.

3) The inference that ZFP36L1 proximity to decapping and deadenylation complexes reflects pathway engagement is reasonable and, frankly, expected. Still, where the manuscript moves from proximity to function, the narrative works best when supported by orthogonal validation. Two compact additions would raise confidence without opening new lines of work. First, a small set of reciprocal co-IPs for PATL1 or DDX6 at endogenous levels in activated T cells, run with and without RNase, would tie the RNase-class assignments to biochemistry. Second, a short-pulse proximity experiment using a reduced biotin dose and shorter labeling window in activated cells would address whether long incubations drive non-specific labeling. Both are feasible in 2 to 3 weeks with minimal extra cost for antibodies and MS runs if the facility is in-house.

We fully agree with the reviewer that orthogonal biochemical validation is valuable. Therefore, we already combined time-resolved proximity labeling (between 0-2h, 2-5h, and 5-16 hours) with time-resolved ZFP36L1 co-IPs ± RNase, to address the dynamic behavior and potential temporal broadening of the interactome.

As to running reciprocal co-IPs for PATL1 or DDX6: we had in fact already considered to follow up on PATL1. However, we failed to identified specific antibodies, revealing many unspecific bands (see below). As to DDX6, antibodies suitable for IP have been reported, and we can therefore offer such reciprocal IP as requested.

To further address the raised points, we will (i) clarify how we define and interpret RNase-sensitive versus RNase-resistant classes (ii) emphasize that some key factors (including PATL1) are already detected in shorter labeling conditions (2 h) in activated T cells (Fig 4C); and (iii) better highlight that the our data provide strong candidates and pathway hypotheses that warrant further mechanistic experimentation in follow-up studies, when moving from proximity to function.

As to the suggested lowering dose of biotin: As described in Figure S1, this appeared unsuccessful. We owe it to the reported dependence and use of biotin in primary T cells (Ref’s 31-33 of this manuscript). This also included that we could not culture T cells in biotin-free medium prior to labeling, as most protocols would do in cell lines.

The reviewer also suggested shorter labeling times. Please be advised that the labeling times chosen were based on the reported protein induction and activity on target mRNAs: 1) ZFP36L1 expression peaks at 2h of T cell activation (Zandhuis et al. 2025; 0.1002/eji.202451641, Petkau et al. 2024; 10.1002/eji.202350700), 3) shows the strongest effects on T cell function between 4-5h, and displays a late phase of activity at 5-16h (Popovic et al. Cell Reports 2023; 10.1016/j.celrep.2023.112419). We realize that additional explanation is warranted for this rationale, which we will provide.

4) Reproducibility is helped by donor pooling, repeated T-cell screens, Jurkat confirmation, and detailed methods including MaxQuant, LIMMA, and supervised patterning. Deposition of MS data is listed. The authors should consider adding a brief, stand-alone analysis notebook in SI or on GitHub with exact filtering thresholds and "shape" definitions, since the supervised profiles are central to claims. This would let others reproduce figures from raw tables with the same code and workflows.

We thank the reviewer for his or her suggestion and we have done as suggested. We will include the following link in the manuscript: https://github.com/ajhoogendijk/ZFP36L1_UltraID

5) Replication and statistics are mostly adequate for discovery proteomics. The thresholds are clear, and PCA and correlation frameworks are appropriate. For functional readouts in edited T cells, please make the number of donors and independent experiments explicit in figure legends, and indicate whether statistics are paired by donor. Where viability differs (UPF1), note any gating strategies used to avoid bias in puromycin or activation marker measurements. These clarifications are quick to add.

Please be advised that the current figure legends already contain the requested information at the bottom (which test used, donor number etc). To highlight this better, we will indicate this point more explicitly in the methods section.

Minor comments 6) The UltraID optimization in primary T cells is useful, but the long 16-hour labeling and high biotin should be framed as a compromise rather than a standard. A short statement about potential off-target labeling during extended incubations would set expectations and justify the RNase and time-course controls.

Please be advised that 1) high biotin was required because primary T cells depend on biotin and 2) increase biotin absorption a 2-7-fold upon activation (Ref 31-33 from the paper). For better time resolution, we included a labeling of 2h (from 0-2h of activation), 3h (from 2-5h) and 9h (from 5-16h) of T cell activation. Nevertheless, we agree that we cannot exclude the risk of off-target labeling, which in fact is inherent to any labeling and pulldown method. We will include such statement in the discussion.

7) The overlap across T-cell screens and with HEK293T APEX datasets is discussed, but a compact quantitative reconciliation would help. A table that lists shared versus cell-type-specific interactors with brief notes on known expression patterns would make this point concrete.

We thank the reviewer for this suggestion. We agree and we will include such table.

8) Figures are generally clear. Where proximity and total proteome PCA are shown, consider adding sample-wise annotations for donor pools and activation time to help readers link variance to biology. Ensure all volcano plots and heatmaps display the exact cutoffs used in text.

We agree that sample-wise annotations would be a nice addition. However, when testing this for e.g. FIgure 1D&E, such differentiation into individual donors becomes illegible due to the many different variables already present. We therefore decided against it.

9) Prior work on ZFP36 family roles in decay, deadenylation via CCR4-NOT, granules, and translational control is cited within the manuscript. In a few places, recent proximity and interactome papers could be more explicitly integrated when comparing overlap, especially where conclusions differ by cell type. A concise paragraph in Discussion that lays out what is truly new in primary T cells would help clarify the contribution of this work to the field.

We appreciate this suggestion and will revise the Discussion accordingly. As to what is new in primary T cells, we would also like to mention that adding H2O2 (required for APEX labeling) to T cells results in immediate cell death can therefore not be employed on T cells. This technical limitation further underscores the valuable contribution of the UltraID-based approach we present here.

Reviewer #1 (Significance (Required)):

Nature and type of advance. The study is a technical and contextual advance in mapping ZFP36L1 proximity partners directly in human primary T cells during activation. The combination of time-resolved labeling and RNase-class assignments is informative. The CRIS PR perturbations provide an initial functional bridge from proximity to phenotype, especially for UPF1.

Context in the literature. ZFP36 family proteins have long been linked to ARE-mediated decay, CCR4-NOT recruitment, and granule localization. The present work confirms those cores and extends them to include decapping and GIGYF1/2-4EHP scaffolds in primary T cells with temporal resolution. The UPF1 link to ZFP36L1 expression adds a plausible surveillance angle that merits follow-up. The cell-type specificity analysis versus HEK293T underscores that proximity networks vary with context.

Audience. Readers in RNA biology, T-cell biology, and proteomics will find the dataset valuable. Groups studying post-transcriptional regulation in immunity can use the resource to prioritize candidate nodes for mechanistic work.

Expertise and scope. I work on post-transcriptional regulation, RNA-protein complexes, and T-cell effector biology. I am comfortable evaluating the conceptual claims, experimental design, and statistical treatment. I am not a mass spectrometry specialist, so I rely on the presented parameters and deposited data for MS acquisition specifics.

To conclude, the manuscript delivers a substantive proximity map of ZFP36L1 in human T cells, with useful temporal and RNA-class information. The UPF1 observations are promising and would benefit from a compact rescue to secure causality. A few minor additions for biochemical validation and transparency in replication would further strengthen the paper.

We thank the reviewer for this comprehensive and constructive assessment. We agree that our study primarily provides a substantive and well-annotated proximity map of ZFP36L1 in human T cells, including temporal and RNA-class information, and that the UPF1 observations constitute a promising lead that merits more detailed mechanistic analysis in follow-up studies.

Reviewer #2 (Evidence, reproducibility and clarity (Required)): The manuscript by Wolkers and colleagues describes the protein interactome of the RNA-binding protein ZFP36L1 in primary human T-cells. There is inherent value in the use of primary cells of human origin, but there is also value in that the study is quite complete, as it is performed in a variety of conditions: T-cells that have been activated or not, at different time points after activation, and by two methods (co-IP and proximity labeling). One might imagine that this basically covers all what can be detected for this protein in T-cells. The authors report a large amount of new interactors involved at all steps in post-transcriptional regulation. In addition, the authors show that UPF1, a known interactor of ZFP36L1, actually binds to ZFP36L1 mRNA and enhances its levels. In sum, the work provides a valuable resource of ZFP36L1 interactors. Yet, how the data add to the mechanistic understanding of ZFP36L1 functions and/or regulation of ZFP36L1 remains unclear.

We thank the reviewer for this enthusiasm on our experimental setups, considering the use of primary T cells of inherent value and our study with the variety of conditions complete.

Major comments: 1) Fig 2: It is confusing that the Pearson correlation to define ZFP36L1 interactors is changed depending on figure panel. In panels A-C, a correlation {greater than or equal to} 0.6 is used, while panel D uses a correlation > 0.5, which changes the nº of interactors. Then, this is changed again in Fig 3A for some cell types but not for others. Why has this been done? It would be better to stick to the same thresholds throughout the manuscript.

Please be advised that different correlation thresholds arise from the composition of the individual datasets: they in depth, number of controls, and the overall dynamic range. The initial proximity labeling experiment (Figure 2A–C) had a higher depth and a larger number of suitable control samples, which allowed us to apply a stricter cutoff (r ≥ 0.6). The time-course experiment and some of the cross-cell-type comparisons have fewer controls and somewhat lower depth, which then required a more permissive threshold (e.g. r > 0.5) to retain known core interactors.

We fully agree that this rationale needs to be explicit. In the revised manuscript we (i) clearly state for each dataset which correlation cutoff is used (ii) emphasize that these thresholds are somewhat arbitrary and should not be directly compared across experiments, and (iii) highlight that our key biological conclusions do not depend on the exact boundary chosen but rather on the consistent enrichment of core complexes and pathways across .

2) Fig 3A: It would be nice to have the information of this Figure panel as a Table (protein name, molecular process(es), known or novel, previously detected in which cells) in addition to the figure.

We agree that this would increase the value of our work as a resource to the community, and we will include such table and merge it with the table Reviewer 1 asked about.

3) Fig 6: To what extent are the effects of UPF1 and GIGFYF1 knock-out on translation and T-cell hyper-activation mediated by ZFP36L1? If deletion of ZFP36L1 itself has no effect on these processes, it seems unlikely that it is involved. In this respect, I am not sure that Fig 6 contributes to the understanding of ZFP36L.

We appreciate this conceptual question. In our dataset, ZFP36L1 knockout affects T-cell activation markers, but does not recapitulate the increased global translation observed upon UPF1 or GIGYF1/2 deletion. We will discuss this finding more explicitly in the Results and Discussion. We discuss the possibility that other ZFP36 family members (e.g. ZFP36/TTP, ZFP36L2) may partially compensate for the absence of ZFP36L1 in some readouts1. Moreover, we will emphasize that at this point it is not clear whether ZFP36L1’s contribution to UPF1 and GIGYF1 protein levels is direct or indirect.

We nonetheless consider Fig. 6 an important component of the story, as it demonstrates that proximity partners emerging from the interactome (UPF1, GIGYF1/2) have measurable functional consequences on T cell activation and translational control, thereby illustrating how the resource can guide mechanistic hypotheses. We will now more carefully phrase this as “first indications of mechanism” and avoid implying that these phenotypes are mediated exclusively via ZFP36L1.

4) Fig 7E: Differences in ZFP36L1 mRNA expression are claimed as a consequence of UPF1 deletion, and indeed there is a clear tendency to reduction of ZFP36L1 mRNA levels upon UPF1 KO. Yet the difference is statistically non-significant. Please, repeat this experiment to increase statistical significance. In addition, a clear discussion on how UPF1 -generally associated to mRNA degradation- contributes to increase ZFP36L1 mRNA levels would be appreciated.

We would like to refrain from including repeats for increasing statistical power. We find similar trends with n=3 at 0h as with n=7 at 3h of activation (Fig. 7E). We rather would like to stress that despite the width overall expression levels which most probably stems from using primary human material, the overall levels of ZFP36L1 mRNA are lower in UPF1 KO T cells. We will include a point on how UPF1 possibly may contribute to the decreased ZFP36L1 mRNA levels, as suggested.

5) Fig 6A: The decrease in global translation by GIGFYF1 knock-out upon activation claimed by the authors is not clear in Fig 6A and is non-significant upon quantification. Please, modify narrative accordingly.

Indeed, this was not phrased well. We will correct our description to match the statistical analysis.

6) Page 6: The authors state 'This included the PAN2/3 complex proteins which trim poly(A) tails prior to mRNA degradation through the CCR4/NOT complex'. To the best of my knowledge, the CCR4/NOT complex does not degrade the body of the mRNA. Both PAN2/3 and CCR4/NOT are deadenylases that function independently.

We thank the reviewer for highlighting this inaccuracy. PAN2/3 and CCR4–NOT are indeed both deadenylase complexes that function independently rather than one acting strictly upstream of the other in degrading the mRNA body. We will correct this statement to that PAN2/3 and CCR4–NOT cooperate in poly(A) tail shortening and do not themselves degrade the mRNA body, which is instead handled by the downstream decay machinery.

7) Please, label all Table sheets. Right now one has to guess what is being shown in most of them. Furthermore, it would be convenient to join all Tables related to the same Figure in one unique Excel with several sheets, rather than having many Tables with only one sheet each.

We appreciate this suggestion. In the revised supplementary files all table sheets will be clearly labeled to indicate the corresponding figure and dataset, and combined into a single excel file when multiple tables relate to the same figure. We have already done so.

Minor comments: 8) Fig 1E: Shouldn't there be a better separation by biotinylation in the UltraID IP principal component analysis? In theory, only biotinylated proteins should be immunoprecipitated.

In theory this should indeed be the case. However, in practice, pull down experiments always suffer from background stickiness of proteins to tubes, beads etc. Combined, these known background issues highlight the critical addition of control samples, allowing for unequivocal call of proteins that are above background.

In addition, as we indicated in the manuscript, primary T cells depend on Biotin. This prohibited us to use biotin-free medium, even for a short culture period (it resulted in cell death). Such biotin-free culture steps are included in proximity labeling assays performed in cell lines. Owing to the continuous addition of biotin, some of the ‘background’ biotinylation signal may even be ‘real’. Nevertheless, the higher levels of biotin we added during the labeling results in increased signals, and statistical analysis with these controls identifies which of the proteins are above background, irrespective from the source. We will include a short note on this in the manuscript

9) Fig 3B-E: Is the labeling not swapped, top (always +) is Biotin and bottom (- or +) is aCD3/aCD28?

We thank the reviewer for catching this mistake- we have corrected it

10) Fig 7A data is from another paper, so I suggest to move this panel to Supplementary materials.

We respectfully disagree. Please be advised that we reanalysed data from published datasets, that resulted in this figure. Re-analysis is a widely accepted method and certainly used for main figure panels. Our re-analysis from Bestenhorn et al 2025; (10.1016/j.molcel.2025.01.001) confirms that ZFP36L1 interacts with UPF1 and GIGYF1/2 in the RAW 264.7 macrophage cell line, which we consider an important consolidation of our findings. To highlight that this table is a re-analysis of published data, we will include this information (including the reference) below the data. As ‘extracted from Bestenhorn et al'

11) Fig S1A: Why is there so much labeling in the UltraID only lane without biotin?

This is a phenomenon also reported by others (Kubitz et al. 2022; 10.1038/s42003-022-03604-5: Figure 5A). UltraID alone is a small protein of (19.7KD), comparable to TurboID or others (Kubitz et al. 2022; 10.1038/s42003-022-03604-5). If not tethered to a specific compartment, these proximity labeling moieties can diffuse through the cytoplasm, biotinylating any protein they ‘bump’ into. Please be advised that we included this control to show this effect, to substantiate why we use GFP-UltraID- as control, to limit such background effects. To highlight this point better, we will better articulate this reasoning in the results section.

12) Fig S1E: Please, explain better. What is WT?

We thank the reviewer for catching this inconsistency. We will explicitly define “WT” as wild-type primary T cells (non-edited, non-transduced) and clarify how this relates to the other conditions.

13) Fig S4B: Please, explain the labels on top of the shapes.

We will update the figure, explaining how the labels above each shape are chosen (e.g. indicating specific clusters, functional categories, or experimental conditions, as appropriate). This should make the reading more intuitive.

14) Page 3: A time-course of incubation with biotin is lacking in Fig S1B, and thereby it is confusing that the authors direct readers to this figure when an increased to 16h incubation is claimed to be better.

Please be advised that short labeling times yielded disappointing results in primary human T cells. Therefore all first analyses were performed with 16h biotinylation, as depicted in Figure S1B). Only after achieving good results (presented in Figure 1B), we performed time course experiments (presented in __Figure 4, __lowering incubation times to 2h, 3h and 9h). We realize that this is confusing and we will rephrase this point in page 3.

Reviewer #2 (Significance (Required)): Strengths: A thorough repository of ZFP36L1 interactors in primary human T-cells. A valuable resource for the community. Weaknesses: There is little mechanistic insight on ZFP36L1 function or regulation.

We would like to highlight that the purpose of our study was to provide a comprehensive interactome of ZFP36L1, and to study the dynamics of these interactions. In addition to known interactors, we identified novel putative interactors of ZFP36L1. We have indeed not followed up on all interactions, which we consider beyond the scope of this manuscript. Rather, we consider our study as a toolbox for the community, that helps in their studies.

Nevertheless, in Fig 6-7, we show first indications of mechanistic insights on ZFP36L1 interactors, exemplifying how the findings of this resource paper can be used by the community.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

The authors have analyzed the interactome of ZFP36L1 in primary human T cells using a biotin-based proximity labeling method. In addition to proteins that are known to interact with ZFP36L1, the authors defined a multitude of novel interactions involved in mRNA decapping, mRNA degradation pathways, translation repressors, stress granule/p-body formation, and other regulatory pathways. Time-lapse proximity labeling revealed that the ZFP36L1 interactome undergoes remodeling during T cell activation. Co-IP for ZFP36L1 executed in the presence/absence of RNA further revealed the interactome and possible regulators of ZFP36L1, including the helicase UPF1. In addition to interacting with ZFP36L1, UPF1 promotes the ZFP36L1 protein expression, seemingly by binding to the ZFP36L1 mRNA transcript, and in some way stabilizing it. This comprehensive interactome map highlights the widespread interactions of ZFP36L1 with proteins of many types, and its potential roles in diverse T cell processes. Although somewhat descriptive, rather than hypothesis-testing, this work represents an important contribution to understanding the potential roles of the ZFP36 family proteins, and sets up many future experiments which could test molecular details.

We thank the reviewer for these thoughtful points, and for recognizing our paper as an important contribution for the field as resource, that should support future experiments.

Major points: 1) Can the authors discuss the specificity of the antibody for ZFP36L1 used in the Co-IP experiments? The antibody listed in Appendix A is abcam catalog number ab42473, although the catalog number for this antibody (unlike the others major ones used) is not listed in the Methods section - please add this to the Methods to make it easier for readers to find this detail. Could this antibody also be immunoprecipitating ZFP36 or ZFP36L2? Other antibodies have had cross-reactivity for the different family members. It is also notable that this antibody has been discontinued by the manufacturer (https://www.abcam.com/en-us/products/unavailable/zfp36l1-antibody-ab42473). Have the authors tried the current abcam anti-ZFP36L1 antibody being sold, catalog number ab230507?

We appreciate the opportunity to clarify this important technical point. We have now added the catalog number (ab42473, Abcam) of the anti-ZFP36L1 antibody used for co-IP to the Methods section, in addition to Appendix A, to facilitate reproducibility. The antibody ab42473 has indeed been discontinued by the manufacturer. We have contacted the manufacturer on multiple occasions with no luck.

We have evaluated multiple alternative anti-ZFP36L1 antibodies, including the currently available Abcam antibody ab230507. In our hands, these alternatives showed weaker or less specific detection of ZFP36L1 compared to the original ZFP36L1 antibody. Only antibody 1A3 recognized ZFP36L1. We therefore used this antibody for the Co-IP. Importantly, even though the signal is lower than the original antibody we used, the migration patterns observed with ab42473 in our co-IP experiments match the expected molecular weight of ZFP36L1 and do not suggest substantial cross-reactivity with ZFP36 or ZFP36L2, which display distinct sizes (we will add the sizes to the WB in figures). We discuss this point briefly in the revised Methods/Results.

2) On this point, the authors report interactions between ZFP36L1 and its related proteins ZFP36 and ZFP36L2 in the Co-IP experiment (Supp 5C). Did these proteins interact in the proximity labeling? Ideally this could be discussed in the Discussion section.

ZFP36 and ZFP36L2 were indeed detected as co-precipitating with ZFP36L1 in the co-IP experiments but were not found as high-confidence interactors in the UltraID proximity labeling datasets. Also in the APEX proximity labeling of Bestehorn et al. In RAW macrophage cells, they did not find ZFP36 or ZFP36L1 to interact with ZFP36L1. * *We now explicitly mention this in the Results and discuss it in the Discussion.

3) Can the authors discuss more fully the limited overlap in identified interactors across the two proximity labeling screens performed in primary T cells (Fig 2C)? Likewise, can the authors comment on the very limited overlap between the screens in T cells and the published ZFP36L1-APEX proximity labelling experiment performed in the HEK293T cell line by Bestehorn et al. (ref 42)? Only 6.8% of proteins found in either T cell screen were found as interactors in this cell line. The authors comment that this may be because "...either expression of certain proteins is cell-type specific, or [because] ZFP36L1 has cell-type specific protein interactions, in addition to its core interactome". While I agree that cell-type specific interactions may be at play, I would think most of the interactors found in the T cell screens are widely expressed proteins necessary for central cell functions.

First, the apparent overlap percentage depends on depth and filtering. As noted above and now detailed in a new Supplementary table, a core set of decapping, deadenylation, and granule-associated factors is consistently recovered across our T-cell screens and the HEK293T APEX dataset. However, beyond this core protein, overlap is reduced, reflecting several factors: (i) differences in expression levels of many interactors between HEK293T cells and primary T cells; (ii) the activation-dependent nature of ZFP36L1 function in T cells, which cannot be fully mimicked in HEK293T; (iii) different proximity labeling enzymes and fusion constructs (APEX vs UltraID, different tags, expression levels); and (iv) distinct experimental designs and control strategies, which influence statistical filtering and the effective “depth” of each interactome.

In the revised Discussion and in the new comparative table, we now emphasize that while many of the ZFP36L1 proximity partners identified in T cells are indeed widely expressed, their effective labeling and enrichment are strongly context dependent. We therefore interpret the relatively limited overlap as highlighting both a robust core interactome and substantial context-specific remodeling, rather than as evidence of artifacts in one or the other dataset.

Minor comments: 4) In Figure 3D, the legend states that black circles indicate significantly enriched proteins in biotin samples, while grey circles indicate non-significant enrichment. However, some genes, including DCP1A, DDX6, YBX1, have black circles in the -biotin group and grey in the +biotin group, which creates confusion in interpretation.

We thank the reviewer for this comment. We have accidentally switched the labeling of biotin and activation as pointed out by reviewer 2. Once this is fixed, this comment will also be fixed.

5) Did the authors find any interactors whose expression is known to be specific to CD4 or CD8 T cells?

In our current dataset we did not identify interactors whose presence was clearly restricted to CD4 or CD8 T-cells. We agree that differential ZFP36L1 interactomes in defined T-cell subsets represent an interesting avenue for future targeted studies and will outline this is the discussion.

Reviewer #3 (Significance (Required)):

The authors present the first comprehensive analysis of the ZFP36L1 interactome in primary T cells. The use of biotin-based proximity labeling enables detection of physiologically relevant interactions in live cells. This approach revealed many novel interactors.

Strengths include the overall richness of the dataset, and the hypothesis-provoking experiments that could follow in the future. Limitations include somewhat limited overlap with a published proximity labeling dataset from performed in a different cell line, suggesting that there may be artifacts in one or both datasets.

The audience for this article would include those interested broadly in RNA binding proteins and those interested in post-transcriptional and translational regulation.

I have immunology expertise on T cell activation and differentiation and expertise on transcriptional and post-transcriptional regulation of gene expression in T cells.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #3

Evidence, reproducibility and clarity

The authors have analyzed the interactome of ZFP36L1 in primary human T cells using a biotin-based proximity labeling method. In addition to proteins that are known to interact with ZFP36L1, the authors defined a multitude of novel interactions involved in mRNA decapping, mRNA degradation pathways, translation repressors, stress granule/p-body formation, and other regulatory pathways. Time-lapse proximity labeling revealed that the ZFP36L1 interactome undergoes remodeling during T cell activation. Co-IP for ZFP36L1 executed in the presence/absence of RNA further revealed the interactome and possible regulators of ZFP36L1, including the helicase UPF1. In addition to interacting with ZFP36L1, UPF1 promotes the ZFP36L1 protein expression, seemingly by binding to the ZFP36L1 mRNA transcript, and in some way stabilizing it. This comprehensive interactome map highlights the widespread interactions of ZFP36L1 with proteins of many types, and its potential roles in diverse T cell processes. Although somewhat descriptive, rather than hypothesis-testing, this work represents an important contribution to understanding the potential roles of the ZFP36 family proteins, and sets up many future experiments which could test molecular details.

Major points:

1) Can the authors discuss the specificity of the antibody for ZFP36L1 used in the Co-IP experiments? The antibody listed in Appendix A is abcam catalog number ab42473, although the catalog number for this antibody (unlike the others major ones used) is not listed in the Methods section - please add this to the Methods to make it easier for readers to find this detail. Could this antibody also be immunoprecipitating ZFP36 or ZFP36L2? Other antibodies have had cross-reactivity for the different family members. It is also notable that this antibody has been discontinued by the manufacturer (https://www.abcam.com/en-us/products/unavailable/zfp36l1-antibody-ab42473). Have the authors tried the current abcam anti-ZFP36L1 antibody being sold, catalog number ab230507?

2) On this point, the authors report interactions between ZFP36L1 and its related proteins ZFP36 and ZFP36L2 in the Co-IP experiment (Supp 5C). Did these proteins interact in the proximity labeling? Ideally this could be discussed in the Discussion section.

3) Can the authors discuss more fully the limited overlap in identified interactors across the two proximity labeling screens performed in primary T cells (Fig 2C)? Likewise, can the authors comment on the very limited overlap between the screens in T cells and the published ZFP36L1-APEX proximity labelling experiment performed in the HEK293T cell line by Bestehorn et al. (ref 42)? Only 6.8% of proteins found in either T cell screen were found as interactors in this cell line. The authors comment that this may be because "...either expression of certain proteins is cell-type specific, or [because] ZFP36L1 has cell-type specific protein interactions, in addition to its core interactome". While I agree that cell-type specific interactions may be at play, I would think most of the interactors found in the T cell screens are widely expressed proteins necessary for central cell functions.

Minor comments:

4) In Figure 3D, the legend states that black circles indicate significantly enriched proteins in biotin samples, while grey circles indicate non-significant enrichment. However, some genes, including DCP1A, DDX6, YBX1, have black circles in the -biotin group and grey in the +biotin group, which creates confusion in interpretation.

5) Did the authors find any interactors whose expression is known to be specific to CD4 or CD8 T cells?

Significance

The authors present the first comprehensive analysis of the ZFP36L1 interactome in primary T cells. The use of biotin-based proximity labeling enables detection of physiologically relevant interactions in live cells. This approach revealed many novel interactors.

Strengths include the overall richness of the dataset, and the hypothesis-provoking experiments that could follow in the future. Limitations include somewhat limited overlap with a published proximity labeling dataset from performed in a different cell line, suggesting that there may be artifacts in one or both datasets.

The audience for this article would include those interested broadly in RNA binding proteins and those interested in post-transcriptional and translational regulation.

I have immunology expertise on T cell activation and differentiation and expertise on transcriptional and post-transcriptional regulation of gene expression in T cells.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

The manuscript by Wolkers and colleagues describes the protein interactome of the RNA-binding protein ZFP36L1 in primary human T-cells. There is inherent value in the use of primary cells of human origin, but there is also value in that the study is quite complete, as it is performed in a variety of conditions: T-cells that have been activated or not, at different time points after activation, and by two methods (co-IP and proximity labeling). One might imagine that this basically covers all what can be detected for this protein in T-cells. The authors report a large amount of new interactors involved at all steps in post-transcriptional regulation. In addition, the authors show that UPF1, a known interactor of ZFP36L1, actually binds to ZFP36L1 mRNA and enhances its levels. In sum, the work provides a valuable resource of ZFP36L1 interactors. Yet, how the data add to the mechanistic understanding of ZFP36L1 functions and/or regulation of ZFP36L1 remains unclear.

Major comments:

1) Fig 2: It is confusing that the Pearson correlation to define ZFP36L1 interactors is changed depending on figure panel. In panels A-C, a correlation {greater than or equal to} 0.6 is used, while panel D uses a correlation > 0.5, which changes the nº of interactors. Then, this is changed again in Fig 3A for some cell types but not for others. Why has this been done? It would be better to stick to the same thresholds throughout the manuscript.

2) Fig 3A: It would be nice to have the information of this Figure panel as a Table (protein name, molecular process(es), known or novel, previously detected in which cells) in addition to the figure.

3) Fig 6: To what extent are the effects of UPF1 and GIGFYF1 knock-out on translation and T-cell hyper-activation mediated by ZFP36L1? If deletion of ZFP36L1 itself has no effect on these processes, it seems unlikely that it is involved. In this respect, I am not sure that Fig 6 contributes to the understanding of ZFP36L.

4) Fig 7E: Differences in ZFP36L1 mRNA expression are claimed as a consequence of UPF1 deletion, and indeed there is a clear tendency to reduction of ZFP36L1 mRNA levels upon UPF1 KO. Yet the difference is statistically non-significant. Please, repeat this experiment to increase statistical significance. In addition, a clear discussion on how UPF1 -generally associated to mRNA degradation- contributes to increase ZFP36L1 mRNA levels would be appreciated.

5) Fig 6A: The decrease in global translation by GIGFYF1 knock-out upon activation claimed by the authors is not clear in Fig 6A and is non-significant upon quantification. Please, modify narrative accordingly.

6) Page 6: The authors state 'This included the PAN2/3 complex proteins which trim poly(A) tails prior to mRNA degradation through the CCR4/NOT complex'. To the best of my knowledge, the CCR4/NOT complex does not degrade the body of the mRNA. Both PAN2/3 and CCR4/NOT are deadenylases that function independently.

7) Please, label all Table sheets. Right now one has to guess what is being shown in most of them. Furthermore, it would be convenient to join all Tables related to the same Figure in one unique Excel with several sheets, rather than having many Tables with only one sheet each.

Minor comments:

8) Fig 1E: Shouldn't there be a better separation by biotinylation in the UltraID IP principal component analysis? In theory, only biotinylated proteins should be immunoprecipitated.

9) Fig 3B-E: Is the labeling not swapped, top (always +) is Biotin and bottom (- or +) is aCD3/aCD28?

10) Fig 7A data is from another paper, so I suggest to move this panel to Supplementary materials.

11) Fig S1A: Why is there so much labeling in the UltraID only lane without biotin?

12) Fig S1E: Please, explain better. What is WT?

13) Fig S4B: Please, explain the labels on top of the shapes.

14) Page 3: A time-course of incubation with biotin is lacking in Fig S1B, and thereby it is confusing that the authors direct readers to this figure when an increased to 16h incubation is claimed to be better.

Significance

Strengths: A thorough repository of ZFP36L1 interactors in primary human T-cells. A valuable resource for the community.

Weaknesses: There is little mechanistic insight on ZFP36L1 function or regulation.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

The authors map the ZFP36L1 protein interactome in human T cells using UltraID proximity labeling combined with quantitative mass spectrometry. They optimize labeling conditions in primary T cells, profile resting and activated cells, and include a time course at 2, 5, and 16 hours. They complement the interactome with co-immunoprecipitation in the presence or absence of RNase to assess RNA dependence. They then test selected candidates using CRISPR knockouts in primary T cells, focusing on UPF1 and GIGYF1/2, and report effects on global translation, stress, activation markers, and ZFP36L1 protein levels. The work argues that ZFP36L1 sits at the center of multiple post-transcriptional pathways in T cells (which in itself is not a novel finding) and that UPF1 supports ZFP36L1 expression at the mRNA and protein level. The main model system is primary human T cells, with some data in Jurkat cells.

The core datasets show thousands of identified proteins in total lysates and enriched biotinylated fractions. Known partners from CCR4-NOT, decapping, stress granules, and P-bodies appear, with additional candidates like GIGYF1/2, PATL1, DDX6, and UPF1. Time-resolved labeling suggests shifts in proximity during early activation. Co-IP with and without RNase suggests both RNA-dependent and RNA-independent contacts. CRISPR loss of UPF1 or GIGYF1/2 increases translation at rest and elevates activation markers, and UPF1 loss reduces ZFP36L1 protein and mRNA while MG132 does not rescue protein levels; UPF1 RIP enriches ZFP36L1 mRNA.

Among patterns worth noting are that the activation state drives the principal variance in both proteome and proximity datasets. Deadenylation, decapping, and granule proteins are consistently near ZFP36L1 across conditions, while some contacts dip at 2 hours and recover by 5 to 16 hours. Mitochondrial ribosomal proteins become more proximal later. UPF1 and GIGYF1 show time-linked behavior and RNase sensitivity that fits roles in mRNA surveillance and translational control. These observations support a dynamic hub model, though they remain proximity-based rather than direct binding maps.

Major comments

The key conclusions are directionally convincing for a broad and dynamic ZFP36L1 neighborhood in human T cells. The data robustly recover established complexes and add plausible candidates. The time-course and RNase experiments strengthen the claim that interactions shift with activation state and RNA context. The functional tests around UPF1 and GIGYF1/2 point to biological relevance. That said, some statements could be qualified. The statement that ZFP36L1 "coordinates" multiple pathways implies mechanism and directionality that proximity data alone cannot prove. I suggest reframing as "positions ZFP36L1 within" or "supports a model where ZFP36L1 sits within" these networks.

UPF1, as an upstream regulator of ZFP36L1 expression, is a promising lead. The reduction of ZFP36L1 protein and mRNA in UPF1 knockout, the non-rescue by MG132, and the UPF1 RIP on ZFP36L1 mRNA together argue that UPF1 influences ZFP36L1 transcript output or processing. This claim would read stronger with one short rescue or perturbation that pins the mechanism. A compact test would be UPF1 re-expression in UPF1-deficient T cells with wild-type and helicase-dead alleles. This is realistic in primary T cells using mRNA electroporation or virus-based systems. Approximate time 2 to 3 weeks, including guide design check and expansion. Reagents and sequencing about 2 to 4k USD depending on donor numbers. This would help separate viability or stress effects from a direct role in ZFP36L1 mRNA handling.

The inference that ZFP36L1 proximity to decapping and deadenylation complexes reflects pathway engagement is reasonable and, frankly, expected. Still, where the manuscript moves from proximity to function, the narrative works best when supported by orthogonal validation. Two compact additions would raise confidence without opening new lines of work. First, a small set of reciprocal co-IPs for PATL1 or DDX6 at endogenous levels in activated T cells, run with and without RNase, would tie the RNase-class assignments to biochemistry. Second, a short-pulse proximity experiment using a reduced biotin dose and shorter labeling window in activated cells would address whether long incubations drive non-specific labeling. Both are feasible in 2 to 3 weeks with minimal extra cost for antibodies and MS runs if the facility is in-house.

Reproducibility is helped by donor pooling, repeated T-cell screens, Jurkat confirmation, and detailed methods including MaxQuant, LIMMA, and supervised patterning. Deposition of MS data is listed. The authors should consider adding a brief, stand-alone analysis notebook in SI or on GitHub with exact filtering thresholds and "shape" definitions, since the supervised profiles are central to claims. This would let others reproduce figures from raw tables with the same code and workflows.

Replication and statistics are mostly adequate for discovery proteomics. The thresholds are clear, and PCA and correlation frameworks are appropriate. For functional readouts in edited T cells, please make the number of donors and independent experiments explicit in figure legends, and indicate whether statistics are paired by donor. Where viability differs (UPF1), note any gating strategies used to avoid bias in puromycin or activation marker measurements. These clarifications are quick to add.

Minor comments

The UltraID optimization in primary T cells is useful, but the long 16-hour labeling and high biotin should be framed as a compromise rather than a standard. A short statement about potential off-target labeling during extended incubations would set expectations and justify the RNase and time-course controls.

The overlap across T-cell screens and with HEK293T APEX datasets is discussed, but a compact quantitative reconciliation would help. A table that lists shared versus cell-type-specific interactors with brief notes on known expression patterns would make this point concrete.

Figures are generally clear. Where proximity and total proteome PCA are shown, consider adding sample-wise annotations for donor pools and activation time to help readers link variance to biology. Ensure all volcano plots and heatmaps display the exact cutoffs used in text.

Prior work on ZFP36 family roles in decay, deadenylation via CCR4-NOT, granules, and translational control is cited within the manuscript. In a few places, recent proximity and interactome papers could be more explicitly integrated when comparing overlap, especially where conclusions differ by cell type. A concise paragraph in Discussion that lays out what is truly new in primary T cells would help clarify the contribution of this work to the field.

Significance

Nature and type of advance. The study is a technical and contextual advance in mapping ZFP36L1 proximity partners directly in human primary T cells during activation. The combination of time-resolved labeling and RNase-class assignments is informative. The CRISPR perturbations provide an initial functional bridge from proximity to phenotype, especially for UPF1.

Context in the literature. ZFP36 family proteins have long been linked to ARE-mediated decay, CCR4-NOT recruitment, and granule localization. The present work confirms those cores and extends them to include decapping and GIGYF1/2-4EHP scaffolds in primary T cells with temporal resolution. The UPF1 link to ZFP36L1 expression adds a plausible surveillance angle that merits follow-up. The cell-type specificity analysis versus HEK293T underscores that proximity networks vary with context.

Audience. Readers in RNA biology, T-cell biology, and proteomics will find the dataset valuable. Groups studying post-transcriptional regulation in immunity can use the resource to prioritize candidate nodes for mechanistic work.

Expertise and scope. I work on post-transcriptional regulation, RNA-protein complexes, and T-cell effector biology. I am comfortable evaluating the conceptual claims, experimental design, and statistical treatment. I am not a mass spectrometry specialist, so I rely on the presented parameters and deposited data for MS acquisition specifics.

To conclude, the manuscript delivers a substantive proximity map of ZFP36L1 in human T cells, with useful temporal and RNA-class information. The UPF1 observations are promising and would benefit from a compact rescue to secure causality. A few minor additions for biochemical validation and transparency in replication would further strengthen the paper.

激動

阻礙

梗阻 干擾

廣泛

經歷 experience, go through, undergo 遭受 miss, mucker, receive

重大的 富裕的 podded, substantial, well-fixed 堅實 solid, substantial 實惠 solid, substantial 物質的 material, substantial 殷 flourishing, substantial, thriving 殷實 substantial, well-off 優厚 beneficial, bountiful, charitable 優渥

This page lifts quite a bit out of my descriptions of networked agency, a term I coined 2016, without attribution. It reads like a generated text. Unclear too what the point of the site is at all.

Document d'Information : Le Traitement Médiatique des Violences Faites aux Femmes

Résumé Exécutif

Ce document d'information synthétise les discussions d'une table ronde sur le traitement médiatique des violences faites aux femmes, réunissant une journaliste d'investigation, une vulgarisatrice et une militante féministe.

Il ressort que si la médiatisation de ce sujet sociétal est croissante, elle est entachée de biais significatifs et de pratiques problématiques. Les points essentiels sont les suivants :

• Le Rôle Ambivalent des Médias : Les médias jouent un rôle crucial en rendant publiques des violences souvent cantonnées à la sphère privée, ce qui permet de faire évoluer les mentalités et de reconnaître le caractère systémique du problème.

Chaque avancée sociétale sur le sujet est liée à la médiatisation d'une affaire emblématique (Mazneff, Depardieu, etc.).

• Critiques Principales du Traitement Médiatique : La couverture médiatique est critiquée pour sa tendance à racialiser les agresseurs, servant un agenda politique raciste en surreprésentant les agresseurs étrangers ou racisés contre des victimes blanches.

On observe également une différence de traitement majeure entre la presse nationale, qui aborde parfois le sujet sous un angle systémique, et la presse locale (PQR), qui le confine souvent au sensationnalisme du "fait divers".

• Éthique Journalistique et Protection des Victimes : Le traitement rigoureux d'une affaire de violence sexiste et sexuelle (VSS) repose sur des principes déontologiques stricts.

La priorité est de croire et de protéger la victime, notamment par l'anonymat, et de respecter son choix de parler ou non.

L'enquête doit être irréprochable pour éviter les risques de diffamation et garantir la crédibilité du récit, ce qui inclut la vérification des faits et la procédure du "contradictoire" (contacter l'agresseur présumé).

• Les Angles Morts de la Médiatisation : De nombreuses formes de violences demeurent largement invisibles.

C'est le cas des violences psychologiques (contrôle, harcèlement numérique via traceurs) et surtout des violences visant les populations les plus marginalisées : les enfants, les travailleuses du sexe et les femmes trans, dont les agressions sont souvent ignorées, voire justifiées par un traitement médiatique transphobe et déshumanisant.

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1. Introduction et Définitions Clés

La discussion établit un cadre conceptuel pour analyser le traitement médiatique des violences faites aux femmes, un sujet de plus en plus présent dans le débat public, souvent à travers le prisme d'affaires très médiatisées impliquant des personnalités publiques (PPDA, Gérard Depardieu, Léo Grasset).

Définition du Patriarcat et de la Notion de "Femme"

Pour analyser les violences, les intervenantes adoptent une approche matérialiste et sociologique.

• Femme : Dans ce contexte, une "femme" n'est pas définie par sa biologie ou son identité de genre, mais comme une personne subissant des conditions sociales spécifiques, notamment le sexisme, les violences et l'exploitation par le système patriarcal.

• Patriarcat : Il est défini comme un système social qui hiérarchise les groupes sociaux "hommes" et "femmes".

Ce système organise l'exploitation (notamment économique via le travail domestique) et l'oppression des femmes, et sanctionne toute personne déviant des normes qu'il impose (ex: hétéronormativité, sanctionnée par l'homophobie).

2. Les Formes de Violence et le Rôle des Médias

Typologie des Violences Sexistes et Sexuelles (VSS)

Les VSS englobent une large gamme de violences, souvent sous-représentées dans leur diversité.

• Violences les plus médiatisées : Le viol et les agressions sexuelles sont les plus visibles médiatiquement, car perçus comme les plus graves.

Les violences conjugales physiques sont également mentionnées, mais les violences psychologiques restent largement ignorées.

• Statistiques et Binarité : Les statistiques disponibles sur les VSS sont majoritairement binaires (hommes/femmes), ce qui invisibilise les victimes non-binaires.

Pauline Bouty souligne que si la plupart des victimes sont des femmes et la plupart des auteurs des hommes, il est crucial de rappeler que des personnes de tous genres peuvent être victimes.

Il est rappelé que près de 90 % des victimes connaissent leur agresseur, qui est souvent un membre de la famille ou le conjoint, contredisant le mythe de l'agresseur inconnu dans une ruelle sombre.

L'Importance Cruciale du Rôle des Médias

Le traitement médiatique des VSS est considéré comme un enjeu public majeur et non une affaire privée.

• Le "5ème Pouvoir" : Jade Bourgerie, journaliste, qualifie les médias de "5ème pouvoir" dont le rôle est de refléter les maux de la société.

Traiter une affaire de VSS relève de l'intérêt public, car ces violences sont le symptôme d'une "société malade".

• Visibilité et Existence : Selon Pauline Bouty, "ce qu'on ne voit pas n'existe pas".

La médiatisation permet au public de prendre conscience de l'existence et de l'ampleur de ces violences.

Chaque progression dans la compréhension de ce phénomène est directement liée à la couverture médiatique d'une affaire symbolique.

• Déconstruire les Stéréotypes : La médiatisation aide à humaniser les victimes et les agresseurs, brisant l'image du "monstre".

Elle montre que l'agresseur peut être "votre voisin, votre frère, votre oncle", une personne perçue comme sympathique en société.

3. Pratiques et Éthique Journalistiques dans le Traitement des VSS

La journaliste Jade Bourgerie détaille les règles déontologiques qu'elle s'impose pour traiter ces sujets sensibles, en l'absence de règles formelles universelles dans la profession.

Les Règles Déontologiques et la Rigueur de l'Enquête

1. Respecter et Croire la Victime : Le point de départ est de croire la parole de la victime et de respecter ses volontés.

2. Rigueur de l'Enquête : L'article doit être "parfait" et "solide".

Cela implique de vérifier méticuleusement chaque élément fourni par la victime pour construire un dossier inattaquable et se prémunir contre les accusations de diffamation.

Exemple donné : retrouver une gynécologue consultée par une victime dans les années 90 pour corroborer une partie de son récit.

3. Le Contradictoire : Une étape essentielle consiste à contacter la personne mise en cause (l'agresseur présumé) pour lui exposer les faits recueillis et lui donner la possibilité de se défendre.

Le Rôle de l'Anonymat pour la Protection des Victimes

L'anonymat est un outil de protection essentiel pour les victimes, en particulier dans les milieux professionnels restreints (ex: musique classique) où tout le monde se connaît. Il permet à la victime d'éviter :

• D'être durablement étiquetée comme "victime de viol".

• De subir des représailles professionnelles ou sociales dans une société encore peu avancée sur ces questions.

4. Critiques Majeures du Traitement Médiatique Actuel

Plusieurs problèmes récurrents dans la couverture des VSS sont identifiés par les intervenantes.

La Racialisation des Récits

Lou Girard dénonce un biais racial majeur : les médias, en particulier ceux détenus par des groupes de droite et d'extrême-droite (citant les "empires Bolloré et Drahi"), tendent à surreprésenter les affaires où des femmes blanches sont agressées par des hommes racisés ou migrants.

Ce traitement sert un "narratif raciste" qui présente "la femme blanche, pure, la Française" comme étant attaquée par "le migrant, l'étranger".

Cela occulte la réalité statistique : la grande majorité des violences sont intra-communautaires et intrafamiliales.

Disparités entre Presse Nationale et Presse Quotidienne Régionale (PQR)

Un clivage important existe entre les types de médias.

Critère

Presse Nationale (ex: Le Monde, Libération)

Presse Quotidienne Régionale (PQR) (ex: La Dépêche)

Traitement

Tendance à traiter les affaires sous un angle plus systémique, souvent liées à des personnalités connues ou à des faits de grande ampleur.

Traitement majoritairement sous le prisme du fait divers et du sensationnalisme.

Biais Racial

Le narratif racialisant est "assez absent" des grands médias nationaux.

Le schéma "femme blanche victime d'un agresseur racisé" est beaucoup plus fréquent.

Causes

Journalistes plus jeunes, formés aux enjeux actuels des VSS dans les écoles de journalisme.

Journalistes souvent en poste depuis des décennies, moins formés à ces problématiques spécifiques.

L'Évolution du Vocabulaire : Du "Crime Passionnel" au "Féminicide"

Le langage utilisé a évolué, mais des termes problématiques persistent.

• Progrès : Le terme "féminicide" a émergé et s'est démocratisé après le mouvement #MeToo. Son usage est politique : il souligne que la victime a été tuée parce qu'elle est une femme, et non dans le cadre d'un simple homicide.

• Persistance : Des termes euphémisants ou inappropriés comme "crime passionnel" ou la description de viols comme des "relations sexuelles imposées" sont encore utilisés, minimisant la notion de violence et de domination.

5. Les Violences Invisibilisées et les Critères de Médiatisation

Violences Psychologiques et Violences contre les Populations Marginalisées

Certaines violences sont systématiquement absentes de la couverture médiatique.

• Violences Psychologiques : Le contrôle insidieux, qui ne "laisse pas de bleu", est très peu représenté. Pauline Bouty cite le documentaire Traquée de Marine Périn sur les hommes installant des traceurs sur les téléphones de leurs compagnes.

Ce contrôle peut aussi être financier ou social.

• Violences contre les enfants : Les enfants sont particulièrement vulnérables car dépendants des adultes qui sont souvent leurs agresseurs.

• Violences contre les femmes trans : Lou Girard souligne leur vulnérabilité extrême. "En tant que femme on a peur d'être violé, en tant que femme trans on a peur d'être violé puis tué."

Le traitement médiatique, quand il existe, est souvent abominable, utilisant des termes transphobes ("homme travesti") et présentant l'agression comme un fait divers "presque marrant".

Les victimes sont mégenrées, même après leur mort.

• Violences contre les travailleuses du sexe : Leurs agressions sont souvent invisibilisées ou justifiées par leur profession, niant la notion de consentement.

Les Critères de Médiatisation d'une Affaire

Pour qu'une affaire soit traitée médiatiquement de manière solide, plusieurs critères sont souvent nécessaires du point de vue journalistique :

• Avoir plusieurs victimes : Cela permet d'éviter la situation de "parole contre parole".

• Au moins une victime acceptant de parler à visage découvert : Cela renforce la crédibilité du récit.

• Des faits documentables avec des preuves : Une affaire reposant uniquement sur un témoignage sans plainte ni preuve est quasiment impossible à traiter pour un journaliste.

• Le consentement de la victime : Le respect de la parole de la victime est primordial. De nombreuses affaires ne sortent pas car les victimes ne souhaitent pas parler, un choix qui doit être absolument respecté.

6. L'Impact sur les Victimes et la Question du Langage

Le Manque de Couverture sur les Conséquences pour les Victimes

Les médias se concentrent sur les faits et les agresseurs, mais très rarement sur l'impact à long terme des violences sur la vie des victimes (psychologique, social, professionnel).

• Analyse Politique : Lou Girard analyse ce manque comme un choix politique.

S'intéresser à la "carrière brisée" de l'agresseur est commun, mais parler des "conséquences terribles du viol" sur la vie des femmes serait un acte "hautement féministe" que beaucoup de médias évitent.

• Le Rôle des Livres : Pauline Bouty nuance en affirmant que ce n'est peut-être pas le rôle des journalistes de parler à la place des victimes de leur ressenti.

Elle défend l'importance des espaces où les victimes peuvent s'exprimer avec leur propre voix, comme les livres (citant Florence Porcel) ou les films (Les Chatouilles).

L'Importance de la Précision Terminologique

L'usage de termes précis est un enjeu politique.

• Pédocriminalité vs. Pédophilie : Il est crucial de différencier la pédophilie (une paraphilie, un attrait) de la pédocriminalité (le passage à l'acte).

La plupart des personnes ayant des attirances pédophiles ne passent pas à l'acte et se font suivre. Un pédocriminel cherche avant tout à exercer une emprise et n'est pas nécessairement "pédophile".

• La Voix Active : Il est recommandé d'utiliser la voix active pour nommer l'agresseur et sa responsabilité : "un homme a violé une femme" plutôt que "une femme s'est fait violer".

Présenter les faits est un choix politique : soit on le fait avec des euphémismes, soit on nomme la violence telle qu'elle est.

eLife Assessment

This paper presents the fundamental discovery that lipid metabolic imbalance induced by Snail, an EMT-related transcription factor, contributes to the acquisition of chemoresistance in cancer cells. The evidence, supported by a wide range of methods and adequate quantification, provides a convincing mechanistic explanation of how Snail drives ectopic expression of the cholesterol- and drug-efflux transporter ABCA1. This work, which introduces a novel therapeutic concept targeting invasive cancer, will be of broad interest to researchers in cancer biology, lipid metabolism, and cell biology.

Reviewer #1 (Public review):

The authors focus on the molecular mechanisms by which EMT cells confer resistance to cancer cells. The authors use a wide range of methods to reveal that overexpression of Snail in EMT cells induces cholesterol/sphingomyelin imbalance via transcriptional repression of biosynthetic enzymes involved in sphingomyelin synthesis. The study also revealed that ABCA1 is important for cholesterol efflux and thus for counterbalancing the excess of intracellular free cholesterol in these snail-EMT cells. Inhibition of ACAT, an enzyme catalyzing cholesterol esterification, also seems essential to inhibit the growth of snail-expressing cancer cells.

Overall, the provided data are convincing and enhance our knowledge on cancer biology.

Reviewer #2 (Public review):

Summary:

This revised study provides a clearer and more mechanistically grounded explanation of how lipid metabolic imbalance contributes to EMT-associated chemoresistance in renal cancer. In this study, the authors discovered that chemoresistance in RCC cell lines correlates with the expression levels of ABCA1 and the EMT-related transcription factor Snail. They demonstrate that Snail induces ABCA1 expression and chemoresistance, and that inhibition of ABCA1-associated pathways can counteract this resistance. The study also suggests that Snail disrupts the cholesterol-sphingomyelin balance by repressing enzymes involved in VLCFA-sphingomyelin synthesis, leading to excess free cholesterol and activation of the LXR-ABCA1 axis. Importantly, inhibiting cholesterol esterification, which renders free cholesterol inert, selectively suppresses growth of a xenograft model of Snail-positive kidney cancer. These findings provide potential lipid metabolism-targeting strategies for cancer therapy. The revised version includes additional quantitative analyses and new experiments addressing lipid balance and ABCA1 localization, further strengthening the overall mechanistic model.

Strengths:

This revised manuscript provides a more comprehensive and convincing mechanistic explanation for how Snail-driven EMT induces chemoresistance through altered lipid homeostasis. The study presents a novel concept in which the Chol/SM balance, rather than individual lipid levels, shapes therapeutic vulnerability. The potential for targeting cholesterol detoxification pathways in Snail-positive cancer cells remains a significant therapeutic implication. In the revised version, the authors provide additional quantitative analyses and complementary experiments - including ABCA1 localization, restoration of VLCFA-SM levels by supplementation with C22:0 ceramide, and membrane-order assays - which further strengthen the mechanistic interpretation and address key concerns raised in earlier reviews.

Weaknesses:

The revised version includes new experiments showing that restoring sphingomyelin levels suppresses ABCA1 expression, thereby strengthening the causal link between altered lipid balance and ABCA1 induction. However, the evidence that ABCA1 is directly required for chemoresistance remains somewhat limited, as the phenotype was not reproduced by ABCA1 knockout or knockdown, and CsA may affect additional targets beyond ABCA1.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review):

The authors focus on the molecular mechanisms by which EMT cells confer resistance to cancer cells. The authors use a wide range of methods to reveal that overexpression of Snail in EMT cells induces cholesterol/sphingomyelin imbalance via transcriptional repression of biosynthetic enzymes involved in sphingomyelin synthesis. The study also revealed that ABCA1 is important for cholesterol efflux and thus for counterbalancing the excess of intracellular free cholesterol in these snail-EMT cells. Inhibition of ACAT, an enzyme catalyzing cholesterol esterification, also seems essential to inhibit the growth of snail-expressing cancer cells.

However, It seems important to analyze the localization of ABCA1, as it is possible that in the event of cholesterol/sphingomyelin imbalance, for example, the intracellular trafficking of the pump may be altered.

The authors should also analyze ACAT levels and/or activity in snail-EMT cells that should be increased. Overall, the provided data are important to better understand cancer biology.

We thank the reviewer for recognizing the significance of our study. Consistent with the hypothesis that ABCA1 contributes to chemoresistance in hybrid E/M cells, we agree that demonstrating the localization of ABCA1 at the plasma membrane is important, and we have included additional experiments to address this point.

We also examined the expression of the major ACAT isoform in the kidney, SOAT1, across RCC cell lines. However, its expression did not correlate with that of Snail (Figure 4B), suggesting that SOAT1 is constitutively expressed at a certain level regardless of Snail expression. The details of these additional experiments are provided in the point-by-point responses below.

Reviewer #2 (Public review):

Summary:

In this study, the authors discovered that the chemoresistance in RCC cell lines correlates with the expression levels of the drug transporter ABCA1 and the EMT-related transcription factor Snail. They demonstrate that Snail induces ABCA1 expression and chemoresistance, and that ABCA1 inhibitors can counteract this resistance. The study also suggests that Snail disrupts the cholesterol-sphingomyelin (Chol/SM) balance by repressing the expression of enzymes involved in very long-chain fatty acid-sphingomyelin synthesis, leading to excess free cholesterol. This imbalance activates the cholesterol-LXR pathway, inducing ABCA1 expression. Moreover, inhibiting cholesterol esterification suppresses Snail-positive cancer cell growth, providing potential lipid-targeting strategies for invasive cancer therapy.

Strengths:

This research presents a novel mechanism by which the EMT-related transcription factor Snail confers drug resistance by altering the Chol/SM balance, introducing a previously unrecognized role of lipid metabolism in the chemoresistance of cancer cells. The focus on lipid balance, rather than individual lipid levels, is a particularly insightful approach. The potential for targeting cholesterol detoxification pathways in Snail-positive cancer cells is also a significant therapeutic implication.

Weaknesses:

The study's claim that Snail-induced ABCA1 is crucial for chemoresistance relies only on pharmacological inhibition of ABCA1, lacking additional validation. The causal relationship between the disrupted Chol/SM balance and ABCA1 expression or chemoresistance is not directly supported by data. Some data lack quantitative analysis.

We thank the reviewer for his/her insightful and constructive comments. In response, we have performed additional experiments using complementary approaches to further substantiate the contribution of Snail-induced ABCA1 expression to chemoresistance. Furthermore, to clarify the causal relationship between reduced sphingomyelin biosynthesis and ABCA1 expression, we conducted new experiments showing that supplementation with sphingolipids attenuates ABCA1 upregulation (Figure 3H). The details of these additional experiments are described in the point-by-point responses below.

Reviewer #1 (Recommendations for the authors):

In this paper, the authors reveal that snail expression in EMT-cells leads to an imbalance between cholesterol and sphingomyelin via a transcriptional repression of enzymes involved in the biosynthesis of sphingomyelin.

This paper is interesting and highlights how the imbalance of lipids would impact chemotherapy resistance. However, I have a few comments.

In Figure 2 in Eph4 cells, while filipin staining appears exclusively at the plasma membrane in the case of EpH4-snail cells filipin staining is also intracellular. It seems plausible that all filipin-positive intracellular staining is not exclusively in LDs, authors should therefore try to colocalize filipin with other intracellular markers. To this aim, authors might want to use topfluocholesterol-probe for instance.

We examined the distribution of TopFluor-cholesterol in hybrid E/M cells (Figure 2H) and found that TopFluor-cholesterol colocalizes with lipid droplets. In addition, we analyzed the colocalization between intracellular filipin signals and organelle-specific proteins, ADRP (lipid droplets) and LAMP1 (lysosomes) (Figure 2I). Since filipin binds exclusively to unesterified cholesterol, filipin signals did not colocalize with ADRP. Instead, we observed colocalization of filipin with LAMP1, suggesting that cholesterol accumulates in hybrid E/M cells in both esterified and unesterified forms.

In Figure 3, the authors reveal that the exogenous expression of the snail alters the ratio of cholesterol to sphingomyelin. The authors should reveal where is found the intracellular cholesterol and intracellular sphingomyelin within these cells Eph4-snail.

To investigate the lipid composition of the plasma membrane, we utilized lipid-binding protein probes, D4 (for cholesterol) and lysenin (for sphingomyelin) (Figures 2L and 2M). We found that the plasma membrane cholesterol content was not affected by EMT, whereas sphingomyelin levels were markedly decreased. In addition, intracellular cholesterol was visualized (Comment 1-1; Figures 2E–2K). On the other hand, because visualization of intracellular sphingomyelin is technically challenging, we were unable to include this analysis in the present study. We consider this an important direction for future investigation.

Regarding the model described in panel K of Figure 3. I would expect that the changes in lipid-membrane organization depicted in panel K should affect the pattern of GM1 toxin for instance or the motility of raft-associated proteins for instance. The authors could perform these experiments in order to sustain the change of lipid plasma membrane organization.

We attempted staining with FITC–cholera toxin to visualize GM1, but both EpH4 and EpH4–Snail cells exhibited very low levels of GM1, resulting in minimal or no detectable staining (data not shown). Instead, to assess the impact of decreased sphingomyelin on the overall biophysical properties of the plasma membrane, we used a plasma membrane–specific lipid-order probe, FπCM–SO₃ (Figures 2N–2P and Figure 2—figure supplement 3). We found that the plasma membrane of EpH4–Snail cells was more disordered (fluidized), suggesting that the overall properties of the plasma membrane are altered by ectopic expression of Snail.

Another issue is the intracellular localization of ABCA1 in Eph4-Snail cells. Knowing that a change in the cholesterol/sphingomyelin ratio can also modify intracellular protein trafficking, it seems important to analyze the intracellular localization of ABCA1 in EPh4-Snail cells.

We performed immunofluorescence microscopy for ABCA1 and found that ABCA1 was mainly localized at the plasma membrane in EpH4–Snail cells (Figure 1M).

As for the data on ACAT inhibition, we expect an increase in ACAT activity and protein levels in EMT cells overexpressing Snail. The authors should also investigate this point.

As noted in our response to the public review, we examined the expression of the major ACAT isoform in the kidney, SOAT1, across RCC cell lines. However, its expression did not correlate with Snail (Figure 4B), suggesting that SOAT1 is expressed at sufficient levels even in cells with low Snail expression. We agree that measuring ACAT activity would be important, as ACATs are regulated at multiple levels. However, we consider this to be beyond the scope of the present study and plan to address it in future work.

Minor comments

I do not understand why in the text, Figure S1 appears after Figure S2. The authors might want to change the numbering of these two figures.

We thank the reviewer for pointing this out. We have corrected the numbering of the supplementary figures so that Figure S1 now appears before Figure S2 in both the text and the revised figure legends.

Page 5, lane 20 Figure 1I instead of 1H.

Page 6, lane 2, Figure 1J instead of 1I, and lane 9 Figure 1H instead of 1I.

We thank the reviewer for carefully checking the figure references. We have corrected the figure numbering errors in the text as suggested.

Reviewer #2 (Recommendations for the authors):

For Figures 1B, 1H, 1J, 2B, 2C, 3G, S3A, and S3B, to enhance data reliability, it is necessary to conduct a quantitative analysis of the Western blot data. The average values from at least three biological replicates should be calculated, with statistical significance assessed.

We have conducted quantitative analyses of the Western blot data for Figures 1B, 1H, 1J, 2B, 2C, 3G, S3A, and S3B. Band intensities from at least three independent biological replicates were quantified, and the mean values with statistical significance are now presented in the revised figures.

For Figures 1D, 2A, 2D, and S2, the images of cells or tissues should not rely solely on selected fields. Quantitative analysis is required, and the mean values from at least three biological replicates should be provided with statistical significance testing.

We have performed quantitative analyses for Figures 1D, 2A, 2D, and S2. The quantification was based on data from at least three independent biological replicates, and the mean values with statistical significance are now included in the revised figures.

For Figures 1A, 1G, 4, and S5, evaluating ABCA1's involvement in drug resistance based solely on CsA treatment is insufficient. Demonstrating the loss of drug resistance through ABCA1 knockdown or knockout is necessary.

We generated ABCA1 knockout EpH4–Snail cells and examined their resistance to nitidine chloride. However, knockout of ABCA1 alone did not affect resistance to the compound (Figure 2 - figure supplement 2). This may be due to secondary metabolic alterations induced by ABCA1 loss or compensatory upregulation of other LXR-induced cholesterol efflux transporters. Instead, we demonstrated that treatment with the LXR inhibitor GSK2033 reduced the nitidine chloride resistance of EpH4–Snail cells (Figure 2C), supporting the idea that enhanced efflux of antitumor agents through the LXR–ABCA1–mediated cholesterol efflux pathway contributes to nitidine chloride resistance.

For Figure 3, to establish a causal relationship between changes in the Chol/SM balance and ABCA1 expression, it is important to test whether modifying cholesterol and SM levels to disrupt this balance affects ABCA1 expression.

Regarding causality, as shown in Figure 2, we have already demonstrated that reducing cholesterol levels in EpH4–Snail cells decreases ABCA1 expression. To further explore this relationship, we examined whether increasing sphingomyelin levels by adding ceramide to the culture medium—thereby restoring the sphingomyelin-to-cholesterol ratio—would reduce ABCA1 expression (Figure 3H). Indeed, supplementation with C22:0 ceramide decreased ABCA1 expression, suggesting that downregulation of the VLCFA-sphingomyelin biosynthetic pathway triggers ABCA1 upregulation. Collectively, these findings support a causal relationship between the Chol/SM balance and ABCA1 expression.

In Figure 3, if there is any information on differences in cholesterol affinity between LCFA-SM and VLCFA-SM, it would be beneficial to include it in the manuscript.

Differences in cholesterol affinity between LCFA-SM and VLCFA-SM in cellular membranes remain controversial and have yet to be fully elucidated. The decrease in cell surface sphingomyelin content, evaluated by lysenin staining (Figure 2L), was more pronounced than that of total sphingomyelin (Figure 3A). Given that VLCFA-SMs have been suggested to undergo distinct trafficking during recycling from endosomes to the plasma membrane (Koivusalo et al. Mol Biol Cell 2007), their reduction may lead to decreased plasma membrane sphingomyelin content by altering its intracellular distribution. We have added this discussion to the revised manuscript.

In Figure 3F, it is recommended to assess housekeeping gene expression as a control. Quantitative real-time PCR should be performed, and the average values from at least three biological replicates should be presented.

We have performed quantitative RT-PCR analysis. The average values from at least three independent biological replicates are presented in Figure 3G.

For Figure 3F, to show whether the reduction of CERS3 or ELOVL7 affects the Chol/SM balance and ABCA1 expression, it is necessary to investigate the phenotypes following the knockdown or knockout of these enzymes.

We fully agree that phenotypic analyses of epithelial cells lacking CerS3 or ELOVL7 would provide valuable insights. However, we consider such investigations to be beyond the scope of the present study and plan to pursue them in future work.

Clarifying whether similar phenotypes are induced by other EMT-related transcription factors, or if they are specific to Snail, would be beneficial.

We agree that examining whether similar phenotypes are induced by other EMT-related transcription factors would be highly valuable for understanding the broader EMT network. However, as the focus of the present study is on lipid metabolic alterations associated with EMT—particularly the imbalance between sphingomyelin and cholesterol—we consider this investigation to be beyond the scope of the current work and plan to address it in future studies.

There are errors in figure citations within the text that need correction:

p.9 l.18 Fig. 3D → Fig. 3G

p.9 l.22 Fig. 3I → Fig. 3H

p.9 l.23 Fig. S2 → Fig. S4

p.10 l.6 Fig. 3J → Fig. 1J

p.10 l.8 Fig. 3J → Fig. 1J

p.10 l.9 Fig. 3K → Fig. 3I

p.10 l.12 Fig. 3H → Fig. 3J

p.10 l.14 Fig. 2D and Fig. S4 → Fig. 2G and Fig. S4D

We thank the reviewer for carefully pointing out these citation errors. We have corrected all figure references in the text as suggested.

Datum van upload

Alles wat in HTML moet staan Momenteel nog wachten tot de docent het zegt.

Alles wat in HTML moet staan

andarsene via

[https://www.wordreference.com/enit/go%20off]

barcollare

[https://www.wordreference.com/enit/totter]

valle

[https://www.wordreference.com/enit/glen]

collinetta

[https://www.wordreference.com/enit/knoll]

simple past tense di "swim", in senso letterale "gli occhi gli nuotavano nella testa", in senso letterato "così stordito, così confuso da avere la vista appannata"

[https://dictionary.cambridge.org/it/dizionario/inglese-italiano/swim]

Playing "at ninepins" refers to playing a version of the game of bowling that uses nine pins instead of ten.

[https://en.wikipedia.org/wiki/Nine-pin_bowling]

vedere, notare

[https://dictionary.cambridge.org/dictionary/english/behold]

dicesi di una bevanda alla spina

[https://www.wordreference.com/enit/draught]

fiasco, caraffa (di vino o altra bevanda)

[https://www.wordreference.com/enit/flagon]

chiamare qualcuno, "hey!"

[https://www.wordreference.com/enit/halloo]

dall'aspetto strambo

[https://www.wordreference.com/enit/odd-looking]

arrancare

[https://www.wordreference.com/enit/toil]

spiccare (il volo)

[https://www.wordreference.com/enit/wing]

corvo

[https://dictionary.cambridge.org/dictionary/english-italian/crow]

passeggiata in campagna

[https://dictionary.cambridge.org/it/dizionario/inglese-italiano/ramble]

succube

[https://dictionary.cambridge.org/dictionary/english/henpecked]

buono, di buon carattere

[https://dictionary.cambridge.org/dictionary/english-italian/good-natured]

The "village worthy" is a person who is popular and respected in their community but lacks true moral character.

[https://ntu-sp.primo.exlibrisgroup.com/discovery/fulldisplay/alma991016713204505146/65NTU_INST:65NTU_INST]

The Catskill Mountains, or the Catskills, are a group of mountains in southeastern New York and are part of the larger Appalachian Mountain range.

[https://en.wikipedia.org/wiki/Catskill_Mountains]

"to stand in the shade of sth" means to position oneself in the area of darkness created by a large object, like a tree.

Voor info over project

Synthèse du Webinaire : Aménagements d'Examens pour les Élèves à Besoins Éducatifs Particuliers

Résumé Exécutif

Ce document de synthèse résume les points clés du webinaire organisé par la FCPE nationale le 20 novembre 2025, animé par Guillaume Laffitte, conseiller technique académique pour l'École inclusive, et Laurence Noël, chef de la division des examens et concours (DEC) de l'académie de Montpellier.

L'objectif central était de clarifier les droits, les procédures et les délais concernant les aménagements d'examens.

Les aménagements ne sont pas des faveurs, mais un droit fondamental pour garantir l'égalité des chances et permettre une évaluation juste et adaptée aux besoins de chaque élève.

Le concept central est la cohérence du "parcours de l'élève" : les aménagements aux examens doivent être l'aboutissement logique des aides pédagogiques mises en place durant toute la scolarité.

Deux acteurs principaux collaborent : le Pôle École Inclusive, qui se concentre sur l'accompagnement pédagogique en amont, et la Division des Examens et Concours (DEC), qui gère le cadre réglementaire et logistique des épreuves.

La procédure de demande se divise en deux voies : une procédure simplifiée pour les élèves bénéficiant déjà d'un PAP, PAI ou PPS, et une procédure complète pour les autres cas ou les demandes nouvelles.

L'anticipation est cruciale : les démarches doivent être entamées dès la classe de quatrième pour le brevet et en seconde pour le baccalauréat.

Enfin, des outils pédagogiques innovants comme les "matrices pédagogiques" sont encouragés pour renforcer l'autonomie des élèves, illustrant une évolution vers une "école pour tous" où les adaptations bénéfiques pour certains le sont pour l'ensemble des élèves.

--------------------------------------------------------------------------------

1. Principes Fondamentaux et Philosophie

Le webinaire établit d'emblée que les démarches d'aménagement d'examen sont essentielles pour garantir l'égalité des chances. Elles constituent un parcours souvent lourd et mal compris pour les familles.

• Un Droit, Pas une Faveur : Il est rappelé que les aménagements sont un "droit indispensable pour que chaque élève soit évalué dans des conditions le plus juste et adaptée à leurs besoins".

• De l'École Inclusive à l'École pour Tous : Guillaume Laffitte propose de dépasser le terme "école inclusive" pour viser une "école pour tous", qui répond aux besoins de chacun sans étiqueter les élèves. La diversité est présentée comme normale et bénéfique.

• Le Parcours de l'Élève : L'idée centrale est que l'examen n'est pas une simple étape, mais l'aboutissement de toute la scolarité.

Il doit exister une cohérence systématique entre les aménagements pédagogiques fournis en classe tout au long du parcours et ceux accordés lors des épreuves. Cette continuité renforce l'autonomie de l'élève.

"Il faut vraiment qu'on puisse corréler systématiquement [...] le parcours de l'élève jusqu'aux épreuves pour le candidat, parce qu'il faut une cohérence et c'est comme ça qu'on peut renforcer finalement les élèves face à leur autonomie en situation d'apprentissage." - Guillaume Laffitte

2. Les Acteurs Clés et Leurs Rôles

La gestion des aménagements repose sur la collaboration de deux services principaux au sein du rectorat, ici illustrés par l'Académie de Montpellier.

Le Pôle Académique École Inclusive

Dirigé par Guillaume Laffitte, ce pôle se concentre sur l'accompagnement pédagogique de l'élève tout au long de sa scolarité.

• Coordination : Il pilote l'organisation de l'école inclusive au niveau académique, en s'appuyant sur les orientations nationales.

• Collaboration : Il travaille en lien étroit avec tous les services de l'académie, notamment la Division des Examens et Concours (DEC).

• Création de Ressources : Il produit des guides pour les familles et les équipes, comme le "guide académique pour les aménagements des examens, mais du parcours de l'élève jusqu'aux aménagements des examens".

• Priorités Académiques : L'une des priorités est l'utilisation des matrices pédagogiques comme réponse pédagogique cohérente.

La Division des Examens et Concours (DEC)

Dirigée par Laurence Noël, la DEC est le service administratif et logistique qui organise l'ensemble des épreuves et gère l'application réglementaire des aménagements.

Chaque rectorat possède une DEC (à Paris, il s'agit du SIEC).

Missions principales :

• Organisation Globale : Organisation de tous les examens (DNB, CAP, Baccalauréats, BTS, etc.) et des concours de recrutement de l'Éducation Nationale.

• Volet Sujets : Élaboration et adaptation des sujets d'examen (ex: dictée aménagée, sujets agrandis, sujets en braille).

• Volet Organisationnel : Gestion des inscriptions, élaboration des calendriers (en tenant compte des tiers temps qui allongent la durée des épreuves), répartition des candidats dans les centres, et communication des aménagements aux chefs de centre.

• Volet Logistique : Fourniture de matériel spécifique comme les copies spéciales (mais pas les ordinateurs ou le mobilier ergonomique).

• Volet Administratif :

◦ Notification : C'est la DEC qui envoie la décision officielle d'aménagement (la "notification") aux familles via l'application Cyclades.  

◦ Recours : Elle traite les recours des familles en cas de désaccord avec une décision.   

◦ Fraudes : Elle gère les commissions de discipline, y compris celles liées à un mauvais usage des aménagements (ex: aide humaine qui donne les réponses, ordinateur non vidé de son contenu).

3. Le Cadre des Aménagements d'Examens

Types d'Aménagements Possibles

Les aménagements peuvent porter sur divers aspects de l'épreuve pour répondre aux besoins spécifiques du candidat.

Catégorie

Exemples d'aménagements

Temps

- Temps majoré (ex: tiers temps) pour les épreuves écrites, orales ou pratiques.<br>- Temps compensatoire pour permettre des soins ou des pauses.<br>- Temps pour se lever et faire quelques pas.

Espace

- Composition en rez-de-chaussée.<br>- Placement spécifique dans la salle (près d'une fenêtre).<br>- Composition dans une salle isolée.

Aides Techniques

- Utilisation d'un ordinateur (personnel ou fourni par le centre).<br>- Matériel spécifique (tables ou chaises ergonomiques, non fournies par la DEC).<br>- Sujets adaptés : en braille, agrandis, sur support numérique.

Aides Humaines

- Secrétaire : Tâches d'exécution pure (lecteur, scripteur sous la dictée).<br>- Assistant : Marge d'autonomie (reformulation ou séquençage des consignes, recentrage de l'attention).<br>- AESH : Missions précises définies dans le cadre d'un PPS.

Adaptations & Dispenses

- Adaptation de l'épreuve : Dictée aménagée pour le DNB.<br>\

• Dispense d'épreuve : Très réglementée et spécifique à chaque examen (ex: dispense de langue vivante, non applicable à tous les diplômes).<br>\

• Étalement : Possibilité de passer les épreuves sur plusieurs sessions consécutives.<br>\

• Conservation des notes : Les notes obtenues peuvent être conservées durant cinq ans.

Correction

- Anonymat respecté : Le correcteur n'a pas connaissance du handicap.<br>\

• Non-pénalisation de l'orthographe : Si validé, un sigle sur la copie anonyme l'indique au correcteur.

Les "Matrices Pédagogiques" : Un Outil d'Avenir

Fortement mises en avant par Guillaume Laffitte, les matrices sont des outils méthodologiques qui aident l'élève à séquencer une tâche et à organiser sa pensée.

• Principe : Elles ne sont pas une antisèche, mais une fiche qui guide l'élève dans les étapes d'une tâche (ex: comment utiliser son brouillon, construire un fil conducteur, organiser son temps).

• Cohérence : Elles permettent à l'élève d'utiliser le jour de l'examen un outil qu'il maîtrise déjà pour l'avoir utilisé en classe.

• Autonomie : Elles visent à rendre l'élève plus autonome et à renforcer son estime de soi.

• Statut : L'utilisation de matrices est un aménagement réglementaire autorisé pour les examens.

_"Ce qui réussit à l'élève qui a le plus de besoins, il n'y a pas de raison que ce ne soit pas utile à tous.

C'est ce qu'on appelle la conception universelle des apprentissages."_ - Guillaume Laffitte

Distinction Cruciale : Dispense d'Enseignement et Aménagement d'Examen

Il est essentiel de ne pas confondre ces deux notions :

• Dispense d'enseignement : Décision très rare, prise uniquement par le recteur à la demande des parents, pour un élève en situation de handicap.

Elle a un impact majeur sur le parcours et l'orientation future de l'élève et doit être évaluée en cohérence avec les examens à venir.

• Dispense d'épreuve d'examen : Fait partie des aménagements possibles mais est strictement encadrée par la réglementation de chaque diplôme.

La DEC ne peut valider une dispense que si le règlement de l'examen le permet.

4. Procédures de Demande d'Aménagement

La procédure a été simplifiée en 2020 pour garantir la continuité entre le parcours scolaire et les examens. Elle s'articule en deux voies principales.

Pour Qui ?

Tout candidat présentant un handicap (reconnu par la MDPH), un trouble de santé invalidant (dans le cadre d'un PAP ou PAI) ou une limitation temporaire d'activité (ex: bras cassé avant l'épreuve) peut demander un aménagement, quel que soit son statut (scolarisé, candidat individuel, etc.).

Procédure Simplifiée

• Conditions : Réservée aux élèves scolarisés en établissement public ou privé sous contrat, disposant d'un PAP, PAI ou PPS valide, et dont les aménagements demandés pour l'examen sont identiques à ceux déjà mis en place durant leur scolarité.

• Processus : La demande ne nécessite pas l'avis d'un médecin. Le chef d'établissement signe le formulaire, qui est ensuite transmis à la DEC.

Procédure Complète

• Conditions : S'applique à tous les autres candidats (individuels, hors contrat), à ceux qui n'ont pas de plan formalisé (PAP, PAI, PPS), ou à ceux qui demandent des aménagements différents ou nouveaux par rapport à leur scolarité.

Elle est également requise en cas d'aggravation de l'état de santé ou pour une majoration de temps au-delà du tiers temps (mi-temps).

• Processus : Le dossier est examiné par l'équipe pédagogique et doit obligatoirement recevoir l'avis d'un médecin de l'Éducation Nationale avant d'être transmis à la DEC.

Calendrier et Délais Clés

L'anticipation est le maître-mot. L'interlocuteur principal pour les familles est le chef d'établissement.

Examen

Moment pour Entamer la Procédure

DNB / CFG

En classe de quatrième

Baccalauréats (général, techno, pro)

Fin du second trimestre de la classe de seconde

Autres examens (CAP, BTS, etc.)

Au cours de l'année de l'examen

La demande formelle et la transmission des pièces se font généralement au moment de l'inscription à l'examen. Le respect des délais est impératif pour permettre à la DEC d'organiser la logistique (ex: la production d'un sujet en braille demande un mois).

Le Processus de Traitement et de Notification

1. Instruction : Les services de la DEC étudient le dossier et vérifient sa conformité réglementaire.

2. Décision : Le recteur prend la décision finale.

3. Notification : La DEC informe officiellement la famille de la décision via l'application Cyclades. Les notifications sont envoyées entre février et mai.

4. Conservation : La notification est à conserver précieusement, à présenter à chaque épreuve avec la convocation, et peut servir de pièce justificative pour de futures demandes.

5. Données Chiffrées et Tendances (Académie de Montpellier)

Les statistiques de l'Académie de Montpellier illustrent une forte augmentation des demandes d'aménagement.

Indicateur

Données 2020

Données 2025 (prévisionnel)

% de candidats avec aménagement

10 %

13,51 %

Nombre total de dossiers

~10 000

14 000

Nombre total de mesures d'aménagement

15 000

76 000

Moyenne de mesures par candidat

~1,5

~5,5

Taux de notifications positives

N/A

99,67 %

Mesures les plus courantes :

• Tiers temps

• Dictée aménagée (DNB)

• Autorisation de la calculatrice

• Aide humaine pour le séquençage ou la reformulation des consignes

6. Points de Vigilance et Conseils Pratiques

• Confiance et Autonomie : Les deux intervenants insistent sur la nécessité de faire confiance aux capacités des enfants, de viser leur autonomie et de s'assurer que les aménagements demandés correspondent réellement à leurs besoins et à leurs habitudes de travail.

• Utilisation de l'ordinateur : Si un ordinateur personnel est autorisé, il doit être entièrement vide de tout dossier et présenté au chef de centre pour vérification avant chaque épreuve.

Il faut bien distinguer la demande de "sujet sur support numérique" de la "composition sur ordinateur".

• Enregistrement régulier : En cas de composition sur ordinateur, il est vital d'enregistrer le travail très régulièrement sur le disque dur ET sur une clé USB pour éviter toute perte en cas de problème technique.

• Contacter le Centre d'Examen : Pour des aménagements lourds ou spécifiques (notamment liés à l'espace, comme un fauteuil roulant), il est conseillé de prendre contact en amont avec le chef du centre d'examen.

• Recours : Si un aménagement accordé n'est pas respecté le jour de l'épreuve, la famille doit adresser un recours écrit au recteur.

La DEC mènera alors une enquête.

Balngrijk om deze weg te laten

Belangrijk om dit te doen, om zo de breedte van apparaat bekijken.

Je kan specifiek kiezen hoe de style eruit ziet bij elk specifiek apparaat

Voor classen te maken

voor ID te maken

Het belangrijkste

Voor Iets appart te houden en dan te stylen

Om dingen te groeperen en samen aan te passen

CTRL + ALT + J Voor een template te gebruiken dan moet je geen sluiting zelf typen

Hoe je de CSS aan de html file linkt.

eLife Assessment

This study reports the important development and characterization of next-generation analogs of the molecule AA263, which was previously identified for its ability to promote adaptive ER proteostasis remodeling. The evidence supporting the conclusions is convincing, with rigorous assays used to benchmark the changes in potency and efficacy of the AA263 analogs as well as AA263 targets. The ability of AA263 analogs to restore the loss of function associated with disease-associated proteins prone to misfolding will be of interest to pharmacologists, chemical biologists, and cell biologists, as well as those working on protein misfolding disorders.

Reviewer #1 (Public review):

Summary:

This study builds off prior work that focused on the molecule AA147 and its role as an activator of the ATF6 arm of the unfolded protein response. In prior manuscripts, AA147 was shown to enter the ER, covalently modify a subset of protein disulfide isomerases (PDIs), and improve ER quality control for the disease-associated mutants of AAT and GABAA. Unsuccessful attempts to improve the potency of AA147 have led the authors to characterize a second hit from the screen in this study: the phenylhydrazone compound AA263. The focus of this study on enhancing biological activity of the AA147 molecule is compelling, and overcomes a hurdle of the prior AA147 drug that proved difficult to modify. The study successfully identifies PDIs as a shared cellular target of AA263 and its analogs. The authors infer, based on the similar target hits previously characterized for AA147, that PDI modification likely accounts for a mechanism of action for AA263.

Strengths:

The work establishes the ability to modify the AA263 molecule to create analogs with more potency and efficacy for ATF6 activation. The "next generation" analogs are able to enhance the levels of functional AAT and GABAA receptors in cellular models expressing the Z-variant of AAT or an epilepsy-associated variant of the GABAA receptor, outlining the therapeutic potential for this molecule and laying the foundation for future organism-based studies.

The authors are able to establish that like AA147, AA263 covalently targets ER PDIs. While it is a likely mechanism that AA263 works through the PDIs, the authors are careful to discuss that this is a potential mechanism that remains to be explicitly proven. The study provides the foundation for future work to further define a role for the PDIs in the actions of AA263.

Reviewer #2 (Public review):

Modulating the UPR by pharmacological targeting of its sensors (or regulators) provides mostly uncharted opportunities in diseases associated with protein misfolding in the secretory pathway. Spearheaded by the Kelly and Wiseman labs, ATF6 modulators were developed in previous years that act on ER PDIs as regulators of ATF6. However, hurdles in their medicinal chemistry have hampered further developments. In this study, the authors provide evidence that the small molecule AA263 also targets and covalently modifies ER PDIs with the effect of activating ATF6. Importantly, AA263 turned out to be amenable to chemical optimization while maintaining its desired activity. Building on this, the authors show that AA263 derivatives can improve aggregation, trafficking and function of two disease-associated mutants of secretory pathway proteins. Together, this study provides compelling evidence for AA263 (and its derivatives) being interesting modulators of ER proteostasis. Mechanistic details of its mode of action will need more attention in future studies that can now build on this.

In detail, the authors provide strong evidence that AA263 covalently binds to ER PDIs, which will inhibit the protein disulfide isomerase activity. ER PDIs regulate ATF6, and thus their finding provides a mechanistic interpretation of AA263 activating the UPR. It should be noted, however, that AA263 shows broad protein labeling (Fig. 1G) which may suggest additional targets, beyond the ones defined as MS hits in this study. Also, a further direct analysis of the IRE1 and PERK pathways (activated or not by AA263) may be an interesting future directions, as e.g. PDIA1, a target of AA263, directly regulates IRE1 (Yu et al., EMBOJ, 2020) and other PDIs also act on PERK and IRE1. The authors interpret modest activation of IRE1/PERK target genes (Fig. 2C) as an effect on target gene overlap, indeed the most likely explanation based on their selective analyses on IRE1 (ERdj4) and PERK (CHOP) downstream genes, but direct activation due to the targeting of their PDI regulators is also a possible explanation. Further key findings of this paper are the observed improvement of AAT behavior and GABAA trafficking and function. Further strength to the mechanistic conclusion that ATF6 activation causes this could be obtained by using ATF6 inhibitors/knockouts in the presence of AA263 (as the target PDIs may directly modulate behavior of AAT and/or GABAA). Along the same line, it also warrants further investigation in future studies why the different compounds, even if all were used at concentrations above their EC50, had different rescuing capacities on the clients.

Together, the study now provides a strong basis for such in-depth mechanistic analyses.

Reviewer #3 (Public review):

Summary:

This study aims to develop and characterize phenylhydrazone-based small molecules that selectively activate the ATF6 arm of the unfolded protein response by covalently modifying a subset of ER-resident PDIs. The authors identify AA263 as a lead scaffold and optimize its structure to generate analogs with improved potency and ATF6 selectivity, notably AA263-20. These compounds are shown to restore proteostasis and functional expression of disease-associated misfolded proteins in cellular models involving both secretory (AAT-Z) and membrane (GABAA receptor) proteins. The findings provide valuable chemical tools for modulating ER proteostasis and may serve as promising leads for therapeutic development targeting protein misfolding diseases.

Strengths:

The study presents a well-defined chemical biology framework integrating proteomics, transcriptomics, and disease-relevant functional assays.

Identification and optimization of a new electrophilic scaffold (AA263) that selectively activates ATF6 represents a valuable advance in UPR-targeted pharmacology.

SAR studies are comprehensive and logically drive the development of more potent and selective analogs such as AA263-20.

Functional rescue is demonstrated in two mechanistically distinct disease models of protein misfolding-one involving a secretory protein and the other a membrane protein-underscoring the translational relevance of the approach.

Weaknesses:

ATF6 activation is primarily inferred from reporter assays and transcriptional profiling; direct biochemical evidence of ATF6 cleavage or nuclear translocation remains missing. However, the authors have added supporting data showing that co-treatment with the ATF6 inhibitor CP7 suppresses target gene induction, which partially strengthens the evidence for ATF6-dependent activity.

Although the proposed mechanism involving PDI modification and ATF6 activation is plausible, it is still not experimentally demonstrated and remains incompletely characterized.

In vivo validation is absent, and thus the pharmacological feasibility, selectivity, and bioavailability of these compounds in physiological systems remain untested.

Comments on revisions:

The authors have generally addressed my comments.

Author response:

The following is the authors’ response to the previous reviews.

Reviewer #1 (Public review):

Summary: 

This study builds off prior work that focused on the molecule AA147 and its role as an activator of the ATF6 arm of the unfolded protein response. In prior manuscripts, AA147 was shown to enter the ER, covalently modify a subset of protein disulfide isomerases (PDIs), and improve ER quality control for the disease-associated mutants of AAT and GABAA. Unsuccessful attempts to improve the potency of AA147 have led the authors to characterize a second hit from the screen in this study: the phenylhydrazone compound AA263. The focus of this study on enhancing the biological activity of the AA147 molecule is compelling, and overcomes a hurdle of the prior AA147 drug that proved difficult to modify. The study successfully identifies PDIs as a shared cellular target of AA263 and its analogs. The authors infer, based on the similar target hits previously characterized for AA147, that PDI modification accounts for a mechanism of action for AA263. 

Strengths: 

The authors are able to establish that, like AA147, AA263 covalently targets ER PDIs. The work establishes the ability to modify the AA263 molecule to create analogs with more potency and efficacy for ATF6 activation. The "next generation" analogs are able to enhance the levels of functional AAT and GABAA receptors in cellular models expressing the Z-variant of AAT or an epilepsy-associated variant of the GABAA receptor, outlining the therapeutic potential for this molecule and laying the foundation for future organism-based studies. 

We thank the reviewer for the positive comments on our manuscript. We address the reviewers remaining comments on our work, as described below.

Weaknesses: 

Arguably, the work does not fully support the statement provided in the abstract that the study "reveals a molecular mechanism for the activation of ATF6". The identification of targets of AA263 and its analogs is clear. However, it is a presumption that the overlap in PDIs as targets of both AA263 and AA147 means that AA263 works through the PDIs. While a likely mechanism, this conclusion would be bolstered by establishing that knockdown of the PDIs lessens drug impact with respect to ATF6 activation. 

We thank the reviewer for this comment. We previously showed that genetic depletion of different PDIs modestly impacts ATF6 activation afforded by ATF6 activating compound such as AA147 (see Paxman et al (2018) ELIFE). However, as discussed in this manuscript, the ability for AA147 and AA263 to activate ATF6 signaling is mediated through polypharmacologic targeting of multiple different PDIs involved in regulating the redox state of ATF6. Thus, individual knockdowns are predicted to only minimally impact the ability for AA263 and its analogs to activate ATF6 signaling. 

To address this comment, we have tempered our language regarding the mechanism of AA263-dependent ATF6 activation through PDI targeting described herein to better reflect the fact that we have not explicitly proven that PDI targeting is responsible for this activity, as highlighted below:

“Page 7, Line 158: “Intriguingly, 12 proteins were shared between these two conditions, including 7 different ER-localized PDIs (Fig. 1H). This includes PDIs previously shown to regulate ATF6 activation including TXNDC12/ERP18.[45,46] These results are similar to those observed when comparing proteins modified by the selective ATF6 activating compound AA147^yne and AA132^yne.[38] Further, we found that the extent of labeling for PDIs including PDIA1, PDIA4, PDIA6, and TMX1, but not TXNDC12, showed greater modification by AA132^yne, as compared to AA263^yne (Fig. 1I). Similar results were observed for AA147^yne.[38] This suggests that, like AA147, the selective activation of ATF6 afforded by AA263 is likely attributed to the modifications of a subset of multiple different ER-localized PDIs by this compound.”

Alternatively, it has previously been suggested that the cell-type dependent activity of AA263 may be traced to the presence of cell-type specific P450s that allow for the metabolic activation of AA263 or cell-type specific PDIs (Plate et al 2016; Paxman et al 2018). If the PDI target profile is distinct in different cell types, and these target difference correlates with ATF6-induced activity by AA263, that would also bolster the authors' conclusion. 

As highlighted by the reviewer, different ER oxidases (e.g., P450s) could differentially influence activation of compounds such as AA263 to promote PDI modification and subsequent ATF6 activation. The specific ER oxidases responsible for AA263 activation are currently unknown; however, we anticipate that multiple different enzymes can promote this activity making it difficult to discern the specific contributions of any one oxidase. We have made this point clearer in the revised submission, as below:

Page 7, Line 169: “This specificity for ER proteins instead suggests the localized generation of AA263 quinone methides at the ER membrane, likely through metabolic activation by different ER localized oxidases, which has been previously been shown to contribute to the selective modification of ER proteins afforded by other compounds such as AA147 [49]”   

Reviewer #2 (Public review):

Modulating the UPR by pharmacological targeting of its sensors (or regulators) provides mostly uncharted opportunities in diseases associated with protein misfolding in the secretory pathway. Spearheaded by the Kelly and Wiseman labs, ATF6 modulators were developed in previous years that act on ER PDIs as regulators of ATF6. However, hurdles in their medicinal chemistry have hampered further development. In this study, the authors provide evidence that the small molecule AA263 also targets and covalently modifies ER PDIs, with the effect of activating ATF6. Importantly, AA263 turned out to be amenable to chemical optimization while maintaining its desired activity. Building on this, the authors show that AA263 derivatives can improve the aggregation, trafficking, and function of two disease-associated mutants of secretory pathway proteins. Together, this study provides compelling evidence for AA263 (and its derivatives) being interesting modulators of ER proteostasis. Mechanistic details of its mode of action will need more attention in future studies that can now build on this.

We thank the reviewer for their positive comments on our manuscript. We address the reviewer’s specific queries on our work, as outlined below. 

In detail, the authors provide strong evidence that AA263 covalently binds to ER PDIs, which will inhibit the protein disulfide isomerase activity. ER PDIs regulate ATF6, and thus their finding provides a mechanistic interpretation of AA263 activating the UPR. It should be noted, however, that AA263 shows broad protein labeling (Figure 1G), which may suggest additional targets, beyond the ones defined as MS hits in this study. 

This is true. We do show broad proteome-wide labeling with AA263^yne, which are largely reflected in the hits identified by MS beyond PDI family members. It is possible that other observed engaged targets, in addition to PDIs, may contribute to the activation of ATF6 signaling. Regardless, our MS analysis clearly shows that the compounds modified by AA263 are enriched for PDIs, further supporting our model whereby AA263-dependent PDI modification is likely responsible for ATF6 activation. 

Also, a further direct analysis of the IRE1 and PERK pathways (activated or not by AA263) would have been a benefit, as e.g., PDIA1, a target of AA263, directly regulates IRE1 (Yu et al., EMBOJ, 2020), and other PDIs also act on PERK and IRE1. The authors interpret modest activation of IRE1/PERK target genes (Figure 2C) as an effect on target gene overlap, indeed the most likely explanation based on their selective analyses on IRE1 (ERdj4) and PERK (CHOP) downstream genes, but direct activation due to the targeting of their PDI regulators is also a possible explanation. 

While we do observe mild increases in IRE1/XBP1s target genes, we do not observe significant increases in PERK/ISR target genes in cells treated with optimized AA263 analogs (see Fig. 2C). We previously showed that genetic ATF6 activation leads to a modest increase in IRE1/XBP1s target genes, reflecting the overlap in target genes of the IRE1/XBP1s and ATF6 pathways (see Shoulders et al (2013) Cell Reports). However, with our data, we cannot explicitly rule out the possibility that the mild increase in IRE1/XBP1s target genes reflects direct IRE1/XBP1s activation, as suggested by the reviewer. To address this, we have adapted the text to highlight this point, now specifically referring to preferential ATF6 activation afforded by these compounds, as below:

Page 5, Line 100: “In addition to finding AA147, our original high-throughput screen also identified the phenylhydrazone compound AA263 as a compound that preferentially activates the ATF6 arm of the UPR [26]”  

Further key findings of this paper are the observed improvement of AAT behavior and GABAA trafficking and function. Further strength to the mechanistic conclusion that ATF6 activation causes this could be obtained by using ATF6 inhibitors/knockouts in the presence of AA263 (as the target PDIs may directly modulate the behavior of AAT and/or GABAA). 

AA263 and related compounds could influence ER proteostasis of destabilized proteins through multiple mechanisms including ATF6 activation or direct modification of a subset of PDIs. We previously showed that AA263-dependent enhancement of A1AT-Z secretion and activity can be largely attributed to ATF6 activation (see Sun et al (2023) Cell Chem Biol). In the revised submission, we now show that increased levels of g2(R177G) afforded by treatment with AA263^yne are partially blocked by co-treatment with the ATF6 inhibitor Ceapin-A7 (CP7), highlighting the contributions of ATF6 activation for this phenotype (Fig. S5B,C). Intriguingly, this result also demonstrates the benefit for targeting ER proteostasis using compounds such as our optimized AA263 analogs, as this approach allows us to enhance ER proteostasis of destabilized proteins through multiple mechanisms. We further expand on this specific point in the revised manuscript as below:

Page 14, Line 375: “AA263 and its related analogs can influence ER proteostasis in these models through different mechanisms including ATF6-dependent remodeling of ER proteostasis and direct alterations to the activity of specific PDIs.(*) Consistent with this, we show that pharmacologic inhibition of ATF6 only partially blocks increases of g2(R177G) afforded by treatment with AA263^yne, highlighting the benefit for targeting multiple aspects of ER proteostasis to enhance ER proteostasis of this diseaserelevant GABA_A variant. While additional studies are required to further deconvolute the relative contributions of these two mechanisms on the protection afforded by our optimized compounds, our results demonstrate the potential for these compounds to enhance ER proteostasis in the context of different protein misfolding diseases.”  

Along the same line, it also warrants further investigation why the different compounds, even if all were used at concentrations above their EC50, had different rescuing capacities on the clients.

This is an interesting question that we are continuing to study. While in general, we observe fairly good correlation between ATF6 activation and correction of diseases of ER proteostasis linked to proteins such as A1AT-Z or GABA_A receptors, as the reviewer points out, we do find some compounds are more efficient at correcting proteostasis than others activate ATF6 to similar levels. We attribute this to differences in either labeling efficiency of PDIs or differential regulation of various ER proteostasis factors, although that remains to be further defined. As we continue working with these (and other) compounds, we will focus on defining a more molecular basis for these findings. 

Together, the study now provides a strong basis for such in-depth mechanistic analyses.

We agree and we are continuing to pursue the mechanistic basis of ER proteostasis remodeling afforded by these and related compounds. 

Reviewer #3 (Public review):

Summary: 

This study aims to develop and characterize phenylhydrazone-based small molecules that selectively activate the ATF6 arm of the unfolded protein response by covalently modifying a subset of ER-resident PDIs. The authors identify AA263 as a lead scaffold and optimize its structure to generate analogs with improved potency and ATF6 selectivity, notably AA263-20. These compounds are shown to restore proteostasis and functional expression of disease-associated misfolded proteins in cellular models involving both secretory (AAT-Z) and membrane (GABAA receptor) proteins. The findings provide valuable chemical tools for modulating ER proteostasis and may serve as promising leads for therapeutic development targeting protein misfolding diseases.

Strengths: 

(1) The study presents a well-defined chemical biology framework integrating proteomics, transcriptomics, and disease-relevant functional assays. 

(2) Identification and optimization of a new electrophilic scaffold (AA263) that selectively activates ATF6 represents a valuable advance in UPR-targeted pharmacology.

(3) SAR studies are comprehensive and logically drive the development of more potent and selective analogs such as AA263-20.

(4) Functional rescue is demonstrated in two mechanistically distinct disease models of protein misfolding-one involving a secretory protein and the other a membrane protein-underscoring the translational relevance of the approach. 

We thank the reviewer for their positive comments related to our work. We address specific weaknesses highlighted by the reviewer, as outlined below. 

Weaknesses: 

(1) ATF6 activation is primarily inferred from reporter assays and transcriptional profiling; however, direct evidence of ATF6 cleavage is lacking.

While ATF6 trafficking and processing can be visualized in cell culture models following severe ER insults (e.g., Tg, Tm), we showed previously that the more modest activation afforded by pharmacologic activators such as AA147 and AA263 cannot be easily visualized by monitoring ATF6 processing (see Plate et al (2016) ELIFE). As we have shown in numerous other manuscripts, we have established a transcriptional profiling approach that accurately defines ATF6 activation. We use that approach to confirm preferential ATF6 activation in this manuscript. We feel that this is sufficient for confirming ATF6 activation. However, we also now include data showing that co-treatment with ATF6 inhibitors (e.g., CP7) blocks increased expression of ATF6 target genes induced by our prioritized compound AA263^yne (Fig. S1B). This further supports our assertion that this compound activates ATF6 signaling.  

(2) While the mechanism involving PDI modification and ATF6 activation is plausible, it remains incompletely characterized. 

We thank the reviewer for this comment. We previously showed that genetic depletion of different PDIs modestly impacts ATF6 activation afforded by ATF6 activating compound such as AA147. However, as discussed in this manuscript, the ability for AA147 and AA263 to activate ATF6 signaling is mediated through polypharmacologic targeting of multiple different PDIs involved in regulating ATF6 redox. Thus, individual knockdowns are predicted to only minimally impact the ability for AA263 and its analogs to activate ATF6 signaling. 

To address this comment, we have tempered out language regarding the mechanism of AA263-dependent ATF6 activation through PDI targeting described herein to better reflect the fact that we have not explicitly proven that PDI targeting is responsible for this activity, as highlighted below:

Page 7, Line 158: “Intriguingly, 12 proteins were shared between these two conditions, including 7 different ER-localized PDIs (Fig. 1H). This includes PDIs previously shown to regulate ATF6 activation including TXNDC12/ERP18.[45,46] These results are similar to those observed when comparing proteins modified by the selective ATF6 activating compound AA147^yne and AA132^yne.[38] Further, we found that the extent of labeling for PDIs including PDIA1, PDIA4, PDIA6, and TMX1, but not TXNDC12, showed greater modification by AA132^yne, as compared to AA263^yne (Fig. 1I). Similar results were observed for AA147^yne[38] This suggests that, like AA147, the selective activation of ATF6 afforded by AA263 is likely attributed to the modifications of a subset of multiple different ER-localized PDIs by this compound.”

(3) No in vivo data are provided, leaving the pharmacological feasibility and bioavailability of these compounds in physiological systems unaddressed.

We are continuing to test the in vivo activity of these compounds in work outside the scope of this initial study. 

Reviewer #1 (Recommendations for the authors): 

(1) First page of the discussion, last sentence. "We previously showed the relatively labeling of PDI modification directly impacts..." should be reworded.

Thank you. We have corrected this in the revised manuscript. 

(2) What is the rationale for measuring ERSE-Fluc activity at 18 h but RNAseq at 6 h? What is known about the timing of action for AA263?

Compound-dependent activation of luciferase reporters requires the translation and accumulation of the luciferase protein for sufficient signal, while qPCR does not. We normally use longer incubations for reporter assays to ensure that we have sufficient quantity of reporter protein to accurately monitor activation. We have found that AA263 can rapidly increase ATF6 activity, with gene expression increases being observed after only a few hours of treatment. This is consistent with the proposed mechanism of ATF6 activation discussed herein involving metabolic activation and subsequent PDI modification.   

(3) Figure 1 panel E and Figure S2 panel B. Are these the same data for AA263 and AA263yne, with the AA2635 added to the plot for Figure S2? If so, it would be nice to note that panel B represents data from 3 of the replicates that are shown in Figure 1 (n=6).

Yes. The AA263 and AA263^yne data shown in Fig. 1E and Fig. S2B are the same data, as these experiments were performed at the same time. We apologize for this oversight, which has now been corrected in the revised version. Note that there were n=3 replicates for the dose response shown in Fig. 1E, which we corrected in the figure legend as below:

Fig. S2B Figure Legend: “B. Activation of the ERSE-FLuc ATF6 reporter in HEK293T cells treated for 18 h with the indicated concentration of AA263, AA263^yne, or AA263-5. Error bars show SEM for n= 3 replicates. The data for AA263 and AA263^yne is the same as that shown in Fig. 1E and are shown for comparison.” 

(4) Figure S3. The legend notes 5 µM AA263-yne and 20 µM analog, whereas the figure itself outlines the same ratio but different concentrations: 10 µM and 40 µM.

We apologize for this mistake in the legend, which has been corrected. The information in the figure is correct. 

Reviewer #2 (Recommendations for the authors): 

(1) The activation mechanism of ATF6 is still debated (really trafficking as a monomer?); the authors may want to word more carefully here. 

We agree. We have corrected this in the revised manuscript to indicate that increased populations of reduced ATF6 traffic for proteolytic processing. 

(2) In Figure 1B, below the figure, mM is written for BME, but micromolar is meant.

Thank you. This has been corrected in the revised manuscript. 

(3) The authors may want to make clearer, why BME does not completely inhibit AA263 and does not cause ER stress itself under the conditions tested.

The addition of BME in our experiments is designed to shift the redox potential of the cell to increase intracellular thiol reagents, such as glutathione, that can quench ‘activated’ AA263 and its analogs. However, BME is actively being oxidized upon addition and the intracellular redox environment can rapidly equilibrate following BME addition. Thus, we do not expect that AA263 or other metabolically activated compounds will be fully quenched using this approach, as is observed. This is consistent with other experiments where we show that the use of these types of reducing agents do not fully suppress the activity of reactive molecules, instead shifting their dosedependent activation of specific pathways.  

(4) The data in Figure 4C seems to disagree with the other data on the tested compounds; this should be clarified. 

It is unclear to what the reviewer is referring. The data in 4C shows that treatment with our optimized AA263 analogs improved elastase inhibition afforded by secreted A1AT, as would be predicted. 

(5) PDIs that have been shown to regulate ATF6 should be discussed in more detail in the light of the presented data/interactome (e.g., ERp18).

Thank you for the suggestion. We now explicitly note that AA263^yne covalent modifies TXNDC12/ERP18 in our proteomic dataset. However, we also note that there is no difference in labeling of this specific PDI between AA263^yne and AA132^yne. This may indicate that the targeting of this protein is responsible for the larger levels of ATF6 activation afforded by both these compounds relative to AA147, with the activation of other UPR pathways afforded by AA132 resulting from increased labeling of other PDIs. We are now exploring this possibility in work outside the scope of this current manuscript. 

Page 7 Line 158: “Intriguingly, 12 proteins were shared between these two conditions, including 7 different ER-localized PDIs (Fig. 1H). This includes PDIs previously shown to regulate ATF6 activation including TXNDC12/ERP18.[45,46] These results are similar to those observed when comparing proteins modified by the selective ATF6 activating compound AA147^yne and AA132^yne.[38] Further, we found that the extent of labeling for PDIs including PDIA1, PDIA4, PDIA6, and TMX1, but not TXNDC12, showed greater modification by AA132^yne, as compared to AA263^yne (Fig. 1I). Similar results were observed for AA147^yne [38] This suggests that, like AA147, the selective activation of ATF6 afforded by AA263 is likely attributed to the modifications of a subset of multiple different ER-localized PDIs by this compound.”

Reviewer #3 (Recommendations for the authors):

(1) Please consider adding detection of ATF6 cleavage by Western blot as direct evidence of AA263-induced ATF6 activation, to substantiate the central mechanistic claim.

While ATF6 trafficking and processing can be visualized in cell culture models following severe ER insults (e.g., Tg, Tm), we showed previously that the more modest activation afforded by pharmacologic activators such as AA147 and AA263 cannot be easily visualized through monitoring ATF6 proteolytic processing by western blotting (see Plate et al (2016) ELIFE). As we have shown in numerous other manuscripts, we have established a transcriptional profiling approach that accurately defines ATF6 activation. We use that approach to confirm preferential ATF6 activation in this manuscript. We feel that this is sufficient for confirming ATF6 activation. However, we also now include qPCR data showing that co-treatment with ATF6 inhibitors (e.g., CP7) blocks increased expression of ATF6 target genes induced by our prioritized compounds. 

(2) To strengthen causal inference, loss-of-function experiments such as PDI knockdown, cysteine mutant inactivation, or reconstitution studies may be informative.

We thank the reviewer for this comment. We previously showed that genetic depletion of different PDIs modestly impacts ATF6 activation afforded by ATF6 activating compound such as AA147. However, as discussed in this manuscript, the ability for AA147 and AA263 to activate ATF6 signaling is mediated through polypharmacologic targeting of multiple different PDIs involved in regulating ATF6 redox state rather than a single PDI family member. Thus, individual knockdowns are predicted to only minimally impact the ability for AA263 and its analogs to activate ATF6 signaling. 

To address this comment, we have tempered out language regarding the mechanism of AA263-dependent ATF6 activation through PDI targeting described herein to better reflect the fact that we have not explicitly proven that PDI targeting is responsible for this activity.

(3) Since β-mercaptoethanol inhibits ATF6 activation, it would be helpful to examine whether DTT also suppresses the activity of AA263 or its analogs, to clarify the redox sensitivity of the mechanism.

The use of reducing agents stronger than BME, such as DTT, globally activates the UPR, including the ATF6 arm of the UPR. Thus, we are unable to perform the requested experiments. We specifically use BME because it is a sufficiently mild reducing agent that can quench reactive metabolites (e.g., activated AA263 analogs) through alterations in cellular glutathione levels without globally activating the UPR.  

(4) Given the electrophilic nature of AA263, which may allow it to react with endogenous thiols (e.g., glutathione or cysteine), a brief discussion or experimental validation of this potential liability would enhance the interpretation of in vivo applicability.

Metabolically activated AA263, like AA147, can be quenched by endogenous thiols such as glutathione. However, treatment with our metabolically activatable electrophiles AA147 and AA263 , either in vitro or in vivo, does not seem to induce activation of the NRF2-regulated oxidative stress response (OSR) in the cell lines used in this manuscript (e.g., Fig. S2C). This suggests that treatment with these compounds does not globally disrupt the intracellular redox state, at least in the tested cell lines. While AA147 has been shown to activate NRF2 in specifical neuronal cell lines and in primary neurons, AA147 does not activate NRF2 signaling in other nonneuronal cell lines or other tissues (see Rosarda et al (2021) ACS Chem Bio). We are currently testing the potential for AA263 to similarly activate adaptive NRF2 signaling in neuronal cells. Regardless, AA147, which functions through a similar mechanism to that proposed for AA263, has been shown to be beneficial in multiple models of disease both in vitro and in vivo. This indicates that this mechanism of action is suitable for continued translational development to mitigate pathologic ER proteostasis disruption observed in diverse types of human disease.  

(5) Evaluation of in vivo activity, such as BiP induction in the liver following intraperitoneal administration of AA263-20 or related analogs, could substantially increase the translational impact of the work.

We are continuing to probe the activity of our optimized AA263 analogs in vivo in work outside the scope of this current manuscript. We thank the reviewer for this suggestion. 

(6) The degree of BiP induction may also be contextualized by comparison with known ER stress inducers such as thapsigargin or tunicamycin, ideally by providing relative dose-equivalent responses.

We are not sure to what the reviewer is referring. We show comparative activation of ATF6 in cells treated with the ER stressor Tg and our compounds by both reporter assay (e.g., Fig. 2B) and qPCR of the ATF6 target gene BiP (HSPA5) (Fig. S2A). We feel that this provides context for the more physiologic levels of ATF6 activation afforded by these compounds.

This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giaf141), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

Reviewer 2: Nicolas Gaggion

The manuscript "pyRootHair: Machine Learning Accelerated Software for High-Throughput Phenotyping of Plant Root Hair Traits" presents a valuable tool for plant phenotyping in microscopy images. As it stands, my recommendation is to accept after minor revisions.

I found the GitHub repository provides detailed instructions and was straightforward to install and run. The whole process took only a few minutes to execute, which speaks well to the software's accessibility.

To further enhance the clarity, precision, and accessibility of the manuscript, I have several comments.

On the random forest classifier training process, the manuscript states "For this comparison, the RFC was trained on a single input image, and used to perform inference on all subsequent images." However, the repository documentation indicates: "To train a random forest model, you will need to train the model on a single representative example of an image, and a corresponding binary mask of the image." The repository further notes that "You will need to ensure that all the images are relatively consistent in terms of lighting, appearance, root hair morphology, and have the same input dimensions. Should your images vary for these traits, you will need to train separate random forest models for different batches of images."

The manuscript needs clarification on this training process. Please specify whether users are expected to manually segment one of their own images, use the nnUNet model to generate binary segmentation and refine it using annotation tools (such as ilastik), or select one of the images from ones provided by the authors of the manuscript that best matches their new data.

Regarding nnUNet performance, I support the decision not to compare with other models, as nnUNet represents state-of-the-art performance and enables easy training for non-expert users. However, I have several questions: Do you plan to release the training dataset so users can retrain the model by incorporating new manually annotated data? The manuscript would benefit from quantifying segmentation performance by crop type. Measuring performance solely by computing time is insufficient, and quantitative metrics such as Dice scores on test holdout sets or cross-validation results (as performed by the nnUNet model) should be reported.

The current abstract describes pyRootHair as an "AI-powered software application to automate root hair trait extraction from images of plant roots grown on agar plates." This description needs to clarify that images were obtained via microscopy. Do you have insights on how the trained model performs across different microscope systems?

The manuscript requires additional clarification on the root straightening process using piecewise transformation, as this represents an important step in the measurement procedure. Please specify how this is performed and whether a specific algorithm or function from a library is used for the piecewise affine transformation. For readers who are not computer vision specialists, a figure illustrating the measurement steps (segmentation → skeletonization → straightening → measurement) would be valuable.

Really minor comments: It would be helpful if the demo generated all plots by default, and Random Forest Classifier (RFC) is not included in the abbreviation list.

Overall, this represents solid work that addresses an important need in plant phenotyping research. The suggested clarifications will enhance both the scientific rigor and practical utility of the contribution.

This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giaf141), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

Reviewer 1: Wanneng Yang

This paper introduces an artificial intelligence-driven software named pyRootHair, which enables high-throughput automated extraction of root hair traits from plant root images, thereby facilitating rapid analysis of root hair morphological variations in various plants, including wheat. However, the following issues remain: 1）Compared to previously published work, the contributions and innovations of this study are not sufficiently highlighted. For instance, the work by Lu, Wei, Xiaochan Wang, and Wei Jia, titled "Root hair image processing based on deep learning and prior knowledge" (Comput. Electron. Agric. 202, 2022: 107397), should be explicitly referenced to clarify the advancements presented here. 2） Although the study demonstrates that pyRootHair can be applied to multiple plant species, including Arabidopsis, Brachypodium, rice, and tomato, the primary validation and analysis are conducted on wheat. For other species, only segmentation results and trait extraction figures are presented, lacking detailed comparative validation with manual measurements as thoroughly as for wheat. 3）The process of "straightening" curved roots is implemented, but the potential introduction of new errors by this procedure is not discussed. 4） In the trait validation section, the correlation analysis between automated and manual measurements shows strong agreement for root hair length and root length, but weaker correlation for elongation zone length. The study should provide a more in-depth discussion on the possible reasons for this lower correlation. 5）The details of the core algorithms (CNN architecture, random forest classifier) are insufficiently described. Key aspects such as parameter selection, optimization, training procedures, and the division ratios of the training/validation/test sets are not clearly specified. Additionally, the specific strategies for data augmentation are not mentioned. 6） No quantitative comparisons with similar tools (e.g., in terms of speed and accuracy) are provided.

This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giaf133), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

Reviewer 2: Yang Yang

The manuscript describes RNA-SeqEZPZ, an automated RNA-Seq analysis pipeline with a user-friendly point-and-click interface. It aims to make comprehensive transcriptomics analyses more accessible to researchers who lack extensive bioinformatics skills by addressing common issues with standardization and usability that arise from using in-house scripts. The pipeline's main features are the use of a Singularity container to simplify software installation and a Nextflow version to support scalability across different computing environments like clouds and clusters. However, I'm not sure if this manuscript fits the journal's scope in its current form. It seems to be just an integration of existing tools without offering new methods or findings.

Major comments:

1. The manuscript mentions several existing RNA-Seq pipelines, such as ENCODE, nf-core, ROGUE, Shiny-Seq, bulkAnalyseR, Partek™ flow, RaNA-Seq, and RASflow. A more detailed comparison of RNA-SeqEZPZ with these tools is needed, especially regarding specific features, performance metrics, and ease of use. For example, it would be helpful to compare the computational resources required by each pipeline or the statistical methods used for differential expression analysis.

2. The manuscript emphasizes reproducibility through Singularity containers and Nextflow. However, it would be stronger if it included a more rigorous demonstration of reproducibility. This could involve running the pipeline on multiple datasets and comparing the results, or providing a detailed protocol for other researchers to reproduce the findings.

3. The manuscript highlights the scalability and portability of RNA-SeqEZPZ due to its Nextflow version. It would be useful to include specific examples of how the pipeline has been used in different computing environments (e.g., cloud, cluster) and to provide performance data to demonstrate its scalability.

4. The point-and-click interface is a key feature, but the manuscript could benefit from a more detailed description of the interface and its functionalities. Including screenshots or a video demonstration would be valuable for potential users.

5. The manuscript shows the effects of batch adjustment using a public dataset. It would be beneficial to expand this section with a discussion of the limitations of batch adjustment methods and to provide guidance on when and how to apply them.

This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giaf133), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

Reviewer 1: Unitsa Sangket

This research presents a well-designed and powerful program for comprehensive transcriptomics analysis with interactive visualizations. The tool is conceptually strong and user-friendly, requiring only raw reads in FASTQ format to initiate the analysis, with no need for manual quality checks. However, a limitation is that the software must be installed manually, which typically requires access to a high-performance computing (HPC) system and support from a system administrator for installation and server maintenance. As such, non-technical users may find it difficult to install and operate the program independently.

With appropriate revisions based on the comments below, the manuscript has the potential to be significantly improved.

• Page 8, line 158-160 "DESeq2 was selected based on findings by Rapaport et al. (2013)40, which demonstrated its superior specificity and sensitivity as well as good control of false positive errors." The findings in the paper titled "bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data" (https://peerj.com/articles/14344) show that DESeq2 achieves higher sensitivity than other tools when applied to newer human RNA-Seq datasets. This finding should be included in the manuscript. For example, DESeq2 was selected based on findings by Rapaport et al. (2013)⁴⁰, which demonstrated its superior specificity and sensitivity as well as good control of false positive errors. Additionally, recent findings from the bestDEG study (cite bestDEG) further support the higher sensitivity of DESeq2 than other tools when applied to newer human RNA-Seq datasets.

• Page 6, line 124-125 "Raw reads quality control are then performed using 125 FASTQC18 and QC reports are compiled using MultiQC19." The quality of the trimmed reads can be assessed using FastQC, as demonstrated and summarized in the paper titled "VOE: automated analysis of variant epitopes of SARS-CoV-2 for the development of diagnostic tests or vaccines for COVID-19." (https://peerj.com/articles/17504/) (Page 4, in last paragraph ""(1) Per base sequence quality (median value of each base greater than 25), (2) per sequence quality (median quality greater than 27), (3) perbase N content (N base less than 5% at each read position) and (4) adapter content (adapter sequences at each position less than 5% of all reads)". This point should be mentioned in the manuscript, including the cutoff values for each FastQC metrics used in RNA-SeqEZPZ, as these thresholds may vary. For example, the quality of the trimmed FASTQ reads was assessed based on the four FastQC metrics, as summarized by Lee et al. (2024). The cutoffs for RNA-SeqEZPZ were set as follows: the median value of each base must be greater than [x], the median quality score must be above [y], the percentage of N bases at each read position must be less than [z]%, and the proportion of adapter sequences at each position must be below [xx]% of all reads.

• The programs used for counts table creation and alignment process should be mentioned in the manuscript.

• The default cutoffs for FDR and log₂ fold change, as well as instructions on how to modify these thresholds, should be clearly stated in the manuscript.

Getting it Right for Every Child

eLife Assessment

This useful study develops an individual-based model to investigate the evolution of division of labor in vertebrates, comparing the contributions of group augmentation and kin selection. The model incorporates several biologically relevant features, including age-dependent task switching and separate manipulation of relatedness and group-size benefits. However, the evidence remains incomplete to support the authors' central claim that group augmentation is the primary driver of vertebrate division of labor. Key modelling assumptions, such as limited opportunities for task synergy, the structure of helper and floater dynamics, and the relatively narrow parameter space explored, continue to restrict the potential for kin selection to produce division of labor, thereby limiting the generality of the conclusions.

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:

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 a 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.

Author response:

The following is the authors’ response to the previous reviews

Reviewer #1 (Public review):

This paper presents a computational model of the evolution of two different kinds of helping ("work," presumably denoting provisioning, and defense tasks) in a model inspired by cooperatively breeding vertebrates. The helpers in this model are a mix of previous offspring of the breeder and floaters that might have joined the group, and can either transition between the tasks as they age or not. The two types of help have differential costs: "work" reduces "dominance value," (DV), a measure of competitiveness for breeding spots, which otherwise goes up linearly with age, but defense reduces survival probability. Both eventually might preclude the helper from becoming a breeder and reproducing. How much the helpers help, and which tasks (and whether they transition or not), as well as their propensity to disperse, are all evolving quantities. The authors consider three main scenarios: one where relatedness emerges from the model, but there is no benefit to living in groups, one where there is no relatedness, but living in larger groups gives a survival benefit (group augmentation, GA), and one where both effects operate. The main claim is that evolving defensive help or division of labor requires the group augmentation; it doesn't evolve through kin selection alone in the authors' simulations.

This is an interesting model, and there is much to like about the complexity that is built in. Individual-based simulations like this can be a valuable tool to explore the complex interaction of life history and social traits. Yet, models like this also have to take care of both being very clear on their construction and exploring how some of the ancillary but potentially consequential assumptions affect the results, including robust exploration of the parameter space. I think the current manuscript falls short in these areas, and therefore, I am not yet convinced of the results. In this round, the authors provided some clarity, but some questions still remain, and I remain unconvinced by a main assumption that was not addressed.

Based on the authors' response, if I understand the life history correctly, dispersers either immediately join another group (with 1-the probability of dispersing), or remain floaters until they successfully compete for a breeder spot or die? Is that correct? I honestly cannot decide because this seems implicit in the first response but the response to my second point raises the possibility of not working while floating but can work if they later join a group as a subordinate. If it is the case that floaters can have multiple opportunities to join groups as subordinates (not as breeders; I assume that this is the case for breeding competition), this should be stated, and more details about how. So there is still some clarification to be done, and more to the point, the clarification that happened only happened in the response. The authors should add these details to the main text. Currently, the main text only says vaguely that joining a group after dispersing " is also controlled by the same genetic dispersal predisposition" without saying how.

In each breeding cycle, individuals have the opportunity to become a breeder, a helper, or a floater. Social role is really just a state, and that state can change in each breeding cycle (see Figure 1). Therefore, floaters may join a group as subordinates at any point in time depending on their dispersal propensity, and subordinates may also disperse from their natal group any given time. In the “Dominance-dependent dispersal propensities” section in the SI, this dispersal or philopatric tendency varies with dominance rank.

We have added: “In each breeding cycle” (L415) to clarify this further.

In response to my query about the reasonableness of the assumption that floaters are in better condition (in the KS treatment) because they don't do any work, the authors have done some additional modeling but I fail to see how that addresses my point. The additional simulations do not touch the feature I was commenting on, and arguably make it stronger (since assuming a positive beta_r -which btw is listed as 0 in Table 1- would make floaters on average be even more stronger than subordinates). It also again confuses me with regard to the previous point, since it implies that now dispersal is also potentially a lifetime event. Is that true?

We are not quite sure where the reviewer gets this idea because we have never assumed a competitive advantage of floaters versus helpers. As stated in the previous revision, floaters can potentially outcompete subordinates of the same age if they attempt to breed without first queuing as a subordinate (step 5 in Figure 1) if subordinates are engaged in work tasks. However, floaters also have higher mortality rates than group members, which makes them have lower age averages. In addition, helpers have the advantage of always competing for an open breeding position in the group, while floaters do not have this preferential access (in Figure S2 we reduce even further the likelihood of a floater to try to compete for a breeding position).

Moreover, in the previous revision (section: “Dominance-dependent dispersal propensities” in the SI) we specifically addressed this concern by adding the possibility that individuals, either floaters or subordinate group members, react to their rank or dominance value to decide whether to disperse (if subordinate) or join a group (if floater). Hence, individuals may choose to disperse when low ranked and then remain on the territory they dispersed to as helpers, OR they may remain as helpers in their natal territory as low ranked individuals and then disperse later when they attain a higher dominance value. The new implementation, therefore, allows individuals to choose when to become floaters or helpers depending on their dominance value. This change to the model affects the relative competitiveness between floaters and helpers, which avoids the assumption that either low- or high-quality individuals are the dispersing phenotype and, instead, allows rank-based dispersal as an emergent trait. As shown in Figure S5, this change had no qualitative impact on the results.

To make this all clearer, we have now added to all of the relevant SI tables a new row with the relative rank of helpers vs floaters. As shown, floaters do not consistently outrank helpers. Rather, which role is most dominant depends on the environment and fitness trade-offs that shape their dispersing and helping decisions.

Some further clarifications: beta_r is a gene that may evolve either positive or negative values, 0 (no reaction norm of dispersal to dominance rank) is the initial value in the simulations before evolution takes place. Therefore, this value may evolve to positive or negative values depending on evolutionary trade-offs. Also, and as clarified in the previous comment, the decision to disperse or not occurs at each breeding cycle, so becoming a floater, for example, is not a lifetime event unless they evolve a fixed strategy (dispersal = 0 or 1). 

Meanwhile, the simplest and most convincing robustness check, which I had suggested last round, is not done: simply reduce the increase in the R of the floater by age relative to subordinates. I suspect this will actually change the results. It seems fairly transparent to me that an average floater in the KS scenario will have R about 15-20% higher than the subordinates (given no defense evolves, y_h=0.1 and H_work evolves to be around 5, and the average lifespan for both floaters and subordinates are in the range of 3.7-2.5 roughly, depending on m). That could be a substantial advantage in competition for breeding spots, depending on how that scramble competition actually works. I asked about this function in the last round (how non-linear is it?) but the authors seem to have neglected to answer.

As we mentioned in the previous comment above, we have now added the relative rank between helpers and floaters to all the relevant SI tables, to provide a better idea of the relative competitiveness of residents versus dispersers for each parameter combination. As seen in Table S1, the competitive advantage of floaters is only marginally in the favor for floaters in the “Only kin selection” implementation. This advantage only becomes more pronounced when individuals can choose whether to disperse or remain philopatric depending on their rank. In this case, the difference in rank between helpers and floaters is driven by the high levels of dispersal, with only a few newborns (low rank) remaining briefly in the natal territory (Table S6). Instead, the high dispersal rates observed under the “Only kin selection” scenario appear to result from the low incentives to remain in the group when direct fitness benefits are absent, unless indirect fitness benefits are substantially increased. This effect is reinforced by the need for task partitioning to occur in an all-or-nothing manner (see the new implementation added to the “Kin selection and the evolution of division of labor” in the Supplementary materials; more details in following comments).

In addition, we specifically chose not to impose this constraint of forcing floaters to be lower rank than helpers because doing so would require strong assumptions on how the floaters rank is determined. These assumptions are unlikely to be universally valid across natural populations (and probably not commonly met in most species) and could vary considerably among species. Therefore, it would add complexity to the model while reducing generalizability.

As stated in the previous revision, no scramble competition takes place, this was an implementation not included in the final version of the manuscript in which age did not have an influence in dominance. Results were equivalent and we decided to remove it for simplicity prior to the original submission, as the model is already very complex in the current stage; we simply forgot to remove it from Table 1, something we explained in the previous round of revisions.

More generally, I find that the assumption (and it is an assumption) floaters are better off than subordinates in a territory to be still questionable. There is no attempt to justify this with any data, and any data I can find points the other way (though typically they compare breeders and floaters, e.g.: https://bioone.org/journals/ardeola/volume-63/issue-1/arla.63.1.2016.rp3/The-Unknown-Life-of-Floaters--The-Hidden-Face-of/10.13157/arla.63.1.2016.rp3.full concludes "the current preliminary consensus is that floaters are 'making the best of a bad job'."). I think if the authors really want to assume that floaters have higher dominance than subordinates, they should justify it. This is driving at least one and possibly most of the key results, since it affects the reproductive value of subordinates (and therefore the costs of helping).

We explicitly addressed this in the previous revision in a long response about resource holding potential (RHP). Once again, we do NOT assume that dispersers are at a competitive advantage to anyone else. Floaters lack access to a territory unless they either disperse into an established group or colonize an unoccupied territory. Therefore, floaters endure higher mortalities due to the lack of access to territories and group living benefits in the model, and are not always able to try to compete for a breeding position.

The literature reports mixed evidence regarding the quality of dispersing individuals, with some studies identifying them as low-quality and others as high-quality, attributing this to them experiencing fewer constraints when dispersing that their counterparts (e.g. Stiver et al. 2007 Molecular Ecology; Torrents‐Ticó, et al. 2018 Journal of Zoology). Additionally, dispersal can provide end-of-queue individuals in their natal group an opportunity to join a queue elsewhere that offers better prospects, outcompeting current group members (Nelson‐Flower et al. 2018 Journal of Animal Ecology). Moreover, in our model floaters do not consistently have lower dominance values or ranks than helpers, and dominance value is often only marginally different.

In short, we previously addressed the concern regarding the relative competitiveness of floaters compared to subordinate group members. To further clarify this point here, we have now included additional data on relative rank in all of the relevant SI tables. We hope that these additions will help alleviate any remaining concerns on this matter.

Regarding division of labor, I think I was not clear so will try again. The authors assume that the group reproduction is 1+H_total/(1+H_total), where H_total is the sum of all the defense and work help, but with the proviso that if one of the totals is higher than "H_max", the average of the two totals (plus k_m, but that's set to a low value, so we can ignore it), it is replaced by that. That means, for example, if total "work" help is 10 and "defense" help is 0, total help is given by 5 (well, 5.1 but will ignore k_m). That's what I meant by "marginal benefit of help is only reduced by a half" last round, since in this scenario, adding 1 to work help would make total help go to 5.5 vs. adding 1 to defense help which would make it go to 6. That is a pretty weak form of modeling "both types of tasks are necessary to successfully produce offspring" as the newly added passage says (which I agree with), since if you were getting no defense by a lot of food, adding more food should plausibly have no effect on your production whatsoever (not just half of adding a little defense). This probably explains why often the "division of labor" condition isn't that different than the no DoL condition.

The model incorporates division of labor as the optimal strategy for maximizing breeder productivity, while penalizing helping efforts that are limited to either work or defense alone. Because the model does not intend to force the evolution of help as an obligatory trait (breeders may still reproduce in the absence of help; k₀ ≠ 0), we assume that the performance of both types of task by the helpers is a non-obligatory trait that complements parental care.

That said, we recognize the reviewer’s concern that the selective forces modeled for division of labor might not be sufficient in the current simulations. To address this, we have now introduced a new implementation, as discussed in the “Kin selection and the evolution of division of labor” section in the SI. In this implementation, division of labor becomes obligatory for breeders to gain a productivity boost from the help of subordinate group members. The new implementation tests whether division of labor can arise solely from kin selection benefits. Under these premises, philopatry and division of labor do emerge through kin selection, but only when there is a tenfold increase in productivity per unit of help compared to the default implementation. Thus, even if such increases are biologically plausible, they are more likely to reflect the magnitudes characteristic of eusocial insects rather than of cooperatively breeding vertebrates (the primary focus of this model). Such extreme requirements for productivity gains and need for coordination further suggest that group augmentation, and not kin selection, is probably the primary driving force particularly in harsh environments. This is now discussed in L210-213.

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:

The model and its analysis is limited, which 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 labor. There are several reasons.

First, 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 tasks 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. I made this same point in my first review, although phrased differently, but it was left unaddressed.

The scope of this paper was to study division of labor in cooperatively breeding species with fertile workers, in which help is exclusively directed towards breeders to enhance offspring production (i.e., alloparental care), as we stated in the previous review. Therefore, in this context, helpers may only obtain fitness benefits directly or indirectly by increasing the productivity of the breeders. This benefit is maximized when division of labor occurs between group members as there is a higher return for the least amount of effort per capita. Our focus is in line with previous work in most other social animals, including eusocial insects and humans, which emphasizes how division of labor maximizes group productivity. This is not to suggest that the model does not favor synergy, as engaging in two distinct tasks enhances the breeders' productivity more than if group members were to perform only one type of alloparental care task. We have expanded on the need for division of labor by making the performance of each type of task a requirement to boost the breeders productivity, see more details in a following comment.

Second, the parameter space is very little explored. This is generally an issue when trying to make general claims from an individual-based model where only a very narrow parameter region has been explored of a necessarily particular model. However, in this paper, the issue is more evident. 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. Instead, 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 very limited variation of xh and xn is explored, always for very high values, effectively making defense unevolvable except if there is group augmentation. Hence, as I stated in my previous review, a more extensive parameter exploration addressing this should be included, but this has not been done. Consequently, the main conclusion that "division of labor" needs group augmentation is essentially enforced by the limited parameter exploration, in addition to the first reason above.

We systematically explored the parameter landscape and report in the body of the paper only those ranges that lead to changes in the reaction norms of interest (other ranges are explored in the SI). When looking into the relative magnitude of cost of work and defense tasks, it is important to note that cost values are not directly comparable because they affect different traits. However, the ranges of values capture changes in the reaction norms that lead to rank-depending task specialization.

To illustrate this more clearly, we have added a new section in the SI (Variation in the cost of work tasks instead of defense tasks section) showing variation in y_h, which highlights how individuals trade off the relative costs of different tasks. As shown, the results remain consistent with everything we showed previously: a higher cost of work (high y_h) shifts investment toward defense tasks, while a higher cost of defense (high x_h) shifts investment toward work tasks.

Importantly, additional parameter values were already included in the SI of the previous revision, specifically to favor the evolution of division of labor under only kin selection. Basically, division of labor under only kin selection does happen, but only under conditions that are very restrictive, as discussed in the “Kin selection and the evolution of division of labor” section in the SI. We have tried to make this point clearer now (see comments to previous reviewer above, and to this reviewer right below).

Third, what is called "division of labor" here is an overinterpretation. When the two tasks 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 "tasks" contribute equally and so one task doesn't need to be completed if the other task compensates for it. So, this model does not actually consider division of labor.

Although it is true that we did not make the evolution of help obligatory and, therefore, did not impose division of labor by definition, the assumptions of the model nonetheless create conditions that favor the emergence of division of labor. This is evident when comparing the equilibria between scenarios where division of labor was favored versus not favored (Figure 2 triangles vs circles).

That said, we acknowledge the reviewer’s concern that the selective forces modeled in our simulations may not, on their own, be sufficient to drive the evolution of division of labor under only kin selection. Therefore, we have now added a section where we restrict the evolution of help to instances in which division of labor is necessary to have an impact on the dominant breeder productivity. Under this scenario, we do find division of labor (as well as philopatry) evolving under only kin selection. However, this behavior only evolves when help highly increases the breeders’ productivity (by a factor of 10 what is needed for the evolution of division of labor under group augmentation). Therefore, group augmentation still appears to be the primary driver of division of labor, while kin selection facilitates it and may, under certain restrictive circumstances, also promote division of labor independently (discussed in L210-213).

Reviewer #1 (Recommendations for the authors):

I really think you should do the simulations where floaters do not come out ahead by floating. That will likely change the result, but if it doesn't, you will have a more robust finding. If it does, then you will have understood the problem better.

As we outlined in the previous round of revisions, implementing this change would be challenging without substantially increasing model complexity and reducing its general applicability, as it would require strong assumptions that could heavily influence dispersal decisions. For instance, by how much should helpers outcompete floaters? Would a floater be less competitive than a helper regardless of age, or only if age is equal? If competitiveness depends on equal age, what is the impact of performing work tasks given that workers always outcompete immigrants? Conversely, if floaters are less competitive regardless of age, is it realistic that a young individual would outcompete all immigrants? If a disperser finds a group immediately after dispersal versus floating for a while, is the dominance value reduced less (as would happen to individuals doing prospections before dispersal)? 

Clearly it is not as simple as the referee suggests because there are many scenarios that would need to be considered and many assumptions made in doing this. As we explained to the points above, we think our treatment of floaters is consistent with the definition of floaters in the literature, and our model takes a general approach without making too many assumptions.

Reviewer #2 (Recommendations for the authors):

The paper's presentation is still unclear. A few instances include the following. It is unclear what is plotted in the vertical axes of Figure 2, which is T but T is a function of age t, so this T is presumably being plotted at a specific t but which one it is not said.

The values graphed are the averages of the phenotypically expressed tasks, not the reaction norms per se. We have now rewritten the the axis to “Expressed task allocation T (0 = work, 1 = defense)” to increase clarity across the manuscript.

The section titled "The need for division of labor" in the methods is still very unclear.

We have rephased this whole section to improve clarity.

eLife Assessment

The authors identify the Bearded-type small protein E(spl)m4 as a physical and genetic interactor of TRAF4 in the Drosophila wing disc. These valuable findings with potential biomedical relevance are, however, supported by incomplete evidence based largely on overexpression studies that lack quantification, limited molecular support for their model, and issues with Bearded family protein specificity. The work could be of interest to researchers in the fields of cell signaling and developmental biology.

Reviewer #1 (Public review):

Summary:

The authors investigate how the Drosophila TNF receptor-associated factor Traf4 - a multifunctional adaptor protein with potential E3 ubiquitin ligase activity - regulates JNK signaling and adherens junctions (AJs) in wing disc epithelium. When they overexpress Traf4 in the posterior compartment of the wing disc, many posterior cells express the JNK target gene puckered (puc), apoptose, and are basally extruded from the epithelium. The authors term this process "delamination", but I think that this is an inaccurate description, especially since they can suppress the "delamination" by blocking programmed cell death (by concomitantly overexpressing p35). Through Y2H assays using Traf4 as a bait, they identified the Bearded family proteins E(spl)m4 (and to a lesser extent E(spl)m2), as Traf4 interactors. They use Alphafold to model computationally the interaction between Traf4 and E(spl)m4. They show that co-overexpression of Traf4 with E(spl)m4 in the posterior domain of the wing disc reduces death of posterior cells. They generate a new, weaker hypomorphic allele of Traf4 that is viable (as opposed to the homozygous lethality of null Traf4 alleles). There is some effect of these mutations on wing margin bristles; fewer wing margin bristle defects are seen when E(spl)m4 is overexpressed, suggesting opposite effects of Traf4 and E(spl)m4. Finally, they use the Minute model of cell competition to show that Rp/+ loser clones have greater clone area (indicating increased survival) when they are depleted for Traf4 or when they overexpress E(spl)m4. Only the cell competition results are quantified. Because most of the data in the preprint are not quantified, it is impossible to know how penetrant the phenotypes are. The authors conclude that E(spl)m4 binds the Traf4 MATH/TRAF domain, disrupts Traf4 trimerization, and selectively suppresses Traf4-mediated JNK and caspase activation without affecting its role in AJ destabilization. However, I believe that this is an overstatement. First, there is no biochemical evidence showing that Traf4 binds E(spl)m4 and that E(spl)m4 disrupts Traf4 trimerization. Second, the data on AJs is weak and not quantified; additionally, cells that are being basally extruded lose contact with neighboring cells, hence changes in adhesion proteins. Related to this, the authors, in my opinion, inaccurately describe basal extrusion of dying cells from the wing disc epithelium as delamination.

Strengths:

(1) The authors use multiple approaches to test the model that overexpressed E(spl)m4 inhibits Traf4, including genetics, cell biological imaging, yeast two-hybrid assays, and molecular modeling.

(2) The authors generate a new Traf4 hypomorphic mutant and use this mutant in cell competition studies, which supports the concept that E(spl)m4 (when overexpressed) can antagonize Traf4.

Weaknesses:

(1) Conflation of "delamination" with "basal extrusion of apoptotic cells": Over-expression of Traf4 causes apoptosis in wing disc cells, and this is a distinct process from delamination of viable cells from an epithelium. However, the two processes are conflated by the authors, and this weakens the premise of the paper.

(2) Dependence on overexpression: The conclusions rely heavily on ectopic expression of Traf4 and E(spl)m4. Thus, the physiological relevance of the interaction remains inferred rather than demonstrated.

(3) Lack of quantitative rigor: Except for the cell competition studies, phenotypic descriptions (e.g., number of apoptotic cells, puc-LacZ intensity) are qualitative; additional quantification, inclusion of sample size, and statistical testing would strengthen the conclusions.

(4) Limited biochemical validation: The Traf4-E(spl)m4 binding is inferred from Y2H and in silico models, but no co-immunoprecipitation or in vitro binding assays confirm direct interaction or the predicted disruption of trimerization.

(5) Specificity within the Bearded family: While E(spl)m2 shows partial binding and Tom shows none, the mechanistic basis for this selectivity is not deeply explored experimentally, leaving questions about motif-context contributions unresolved.

Reviewer #2 (Public review):

Summary:

This manuscript analyzes the contribution of Traf4 to the fate of epithelial cells in the developing wing imaginal disc tissue. The manuscript is direct and concise and suggests an interesting and valuable hypothesis with dual functions of Traf4 in JNK pathway activation and cell delamination. However, the text is partially speculative, and the evidence is incomplete as the main claims are only partially supported. Some results require validation to support the conclusions.

Strengths:

(1) The manuscript is direct and concise, with a well-written and precise introduction.

(2) It presents an interesting and valuable hypothesis regarding the dual role of Traf4 in JNK pathway activation and cell delamination.

(3) The study addresses a relevant biological question in epithelial tissue development using a genetically tractable model.

(4) The use of newly generated Traf4 mutants adds novelty to the experimental approach.

(5) The manuscript includes multiple experimental strategies, such as genetic manipulation and imaging, to explore Traf4 function.

Weaknesses:

(1) The evidence supporting key claims is incomplete, and some conclusions are speculative.

(2) The use of GFP-tagged Traf4 lacks validation regarding its functional integrity.

(3) Orthogonal views and additional imaging data are needed to confirm changes in apicobasal localization and cell delamination.

(4) Experimental conditions and additional methods should be further detailed.

(5) The interaction between Traf4 and E(spl)m4 remains speculative in Drosophila.

(6) New mutants require deeper analysis and validation.

(7) The elimination of Traf4 mutant clones may be due to cell competition, which requires further experimental clarification.

(8) The role of Traf4 in cell competition is contradictory and needs to be resolved.

Reviewer #3 (Public review):

Summary:

This is an important and well-conceived study that identifies the Bearded-type small protein E(spl)m4 as a physical and genetic interactor of TRAF4 in Drosophila. By combining classical genetics, yeast two-hybrid assays, and AlphaFold in silico modeling, the authors convincingly demonstrate that E(spl)m4 acts as an inhibitor of TRAF4-mediated induction of JNK-driven apoptosis in developing larval imaginal wing discs, while not affecting TRAF4's role in adherence junction remodeling.

Based primarily on modeling, the authors propose that the specificity of E(spl)m4 towards TRAF4-mediated signaling arises from its interference with TRAF4 trimerization, which is likely required for the activation of the JNK signaling arm but not for the maintenance of adherence junctions and stability of E-cadherin/β-catenin complex.

Overall, this study is of broad interest to cell and developmental biologists. It also holds potential biomedical relevance, particularly for strategies aimed at modulating TRAF protein activities to dissect and modulate canonical versus non-canonical signaling functions.

Strengths:

(1) The work identifies the Bearded-type small protein E(spl)m4 as a physical and genetic interactor of TRAF4 in Drosophila, extending the understanding of E(spl)m4 beyond its established functions in Notch signaling.

(2) The study is experimentally solid, well-executed, and written, combining classical genetics with protein-protein interaction assays and modeling to reveal E(spl)m4 as a new regulator of TRAF4 signaling.

(3) The genetic and biochemical data convincingly show the ability of E(spl)m4 overexpression to inhibit TRAF4-induced JNK-dependent apoptosis, while leaving the TRAF4 role in adherens junction remodeling unaffected.

(4) The findings have important implications for the regulation of cell signaling and apoptosis and may guide pharmacological targeting of TRAF proteins.

Weaknesses:

The study is overall strong; however, several aspects could be clarified or expanded to strengthen the proposed mechanism and data presentation:

(1) The proposed mechanism that E(spl)m4 inhibits TRAF4 activation of JNK signaling by affecting TRAF4 trimerization relies mainly on modeling. Experimental evidence would strengthen this claim. For example, a native or non-denaturing SDS-PAGE could be used to assess TRAF4 oligomerization states in the absence or presence of E(spl)m4 overexpression, testing whether E(spl)m4 interferes with high-molecular-weight TRAF4 assemblies.

(2) The study depends largely on E(spl)m4 overexpression, which may not reflect physiological conditions. It would be valuable to test, or at least discuss, whether loss-of-function or knockdown of E(spl)m4 modulates the strength or duration of JNK-mediated signaling, potentially accelerating apoptosis. Such data would reinforce the model that E(spl)m4 acts as a physiological modulator of TRAF4-JNK signaling in vivo.

(3) The authors initially identify both E(spl)m4 and E(spl)m2 as TRAF4 interactions, but subsequently focus on E(spl)m4. It would be helpful to clarify or discuss the rationale for prioritizing E(spl)m4 for detailed functional analysis.

(4) E(spl)m4 overexpression appears to protect RpS3 loser clones (Figure 6H-K), yet caspase-3-positive cells are still visible in mosaic wing discs. Please comment on the nature of these Caspase 3-positive cells, whether they are cell-autonomous to the clone or non-autonomous (Figure 6K)?

(5) This is a clear, well-executed, and conceptually strong study that significantly advances understanding of TRAF4 signaling specificity and its modulation by the Bearded-type protein E(spl)m4.

eLife Assessment

This important study applies an innovative multi-model strategy to implicate the ribosomal protein (RP) encoding genes as candidates causing Hypoplastic Left Heart Syndrome. The evidence from the screen in stem cell-derived cardiomyocytes and whole genome sequencing of human patients, followed by functional analyses of RP genes in fly and fish models, is convincing and supports the authors' claims. This work and methodology applied would be of broad interest to medical biologists working on congenital heart diseases.

Reviewer #1 (Public review):

Nielsen et al have identified a new disease mechanism underlying hypoplastic left heart syndrome due to variants in ribosomal protein genes that lead to impaired cardiomyocyte proliferation. This detailed study starts with an elegant screen in stem cell derived cardiomyocytes and whole genome sequencing of human patients and extends to careful functional analysis of RP gene variants in fly and fish models. Striking phenotypic rescue is seen by modulating known regulators of proliferation including the p53 and Hippo pathways. Additional experiments suggest that cell type specificity of the variants in these ubiquitously expressed genes may result from genetic interactions with cardiac transcription factors. This work positions RPs as important regulators of cardiomyocyte proliferation and differentiation involved in the etiology of HLHS, and point to potential downstream mechanisms.

The revised manuscript has been extended, facilitating interpretation and reinforcing the authors' conclusions.

Reviewer #2 (Public review):

Tanja Nielsen et al. presents a novel strategy for identification of candidate genes in Congenital Heart Disease (CHD). Their methodology, which is based on comprehensive experiments across cell models, drosophila and zebrafish models, represents an innovative, refreshing and very useful set of tools for identification of disease genes, in a field which are struggling with exactly this problem.

The authors have applied their methodology to investigate the pathomechanisms of Hypoplastic Left Heart Syndrome (HLHS) - a severe and rare subphenotype in the large spectrum of CHD malformations. Their data convincingly implicates ribosomal proteins (RPs) in growth and proliferation defects of cardiomyocytes, a mechanism which is suspected to be associated with HLHS.

By whole genome sequencing analysis of a small cohort of trios (25 HLHS patients and their parents) the authors investigated a possible association between RP encoding genes and HLHS.

Although the possible association between defective RPs and HLHS needs to be verified, the results suggest a novel disease mechanism in HLHS, which is a potentially substantial advance in our understanding of HLHS and CHD. The conclusions of the paper are based on solid experimental evidence from appropriate high- to medium-throughput models, while additional genetic results from an independent patient cohort is needed to verify an association between RP encoding genes and HLHS in patients.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review):

Nielsen et al have identified a new disease mechanism underlying hypoplastic left heart syndrome due to variants in ribosomal protein genes that lead to impaired cardiomyocyte proliferation. This detailed study starts with an elegant screen in stemcell-derived cardiomyocytes and whole genome sequencing of human patients and extends to careful functional analysis of RP gene variants in fly and fish models. Striking phenotypic rescue is seen by modulating known regulators of proliferation, including the p53 and Hippo pathways. Additional experiments suggest that the cell type specificity of the variants in these ubiquitously expressed genes may result from genetic interactions with cardiac transcription factors. This work positions RPs as important regulators of cardiomyocyte proliferation and differentiation involved in the etiology of HLHS, although the downstream mechanisms are unclear.

We thank Reviewer 1 for the thoughtful assessment of our manuscript. Our point-bypoint responses to the recommendations are provided (Reviewer 1, “Recommendations for the authors”).

Reviewer #2 (Public review):

Tanja Nielsen et al. present a novel strategy for the identification of candidate genes in Congenital Heart Disease (CHD). Their methodology, which is based on comprehensive experiments across cell models, Drosophila and zebrafish models, represents an innovative, refreshing and very useful set of tools for the identification of disease genes, in a field which are struggling with exactly this problem. The authors have applied their methodology to investigate the pathomechanisms of Hypoplastic Left Heart Syndrome (HLHS) - a severe and rare subphenotype in the large spectrum of CHD malformations. Their data convincingly implicates ribosomal proteins (RPs) in growth and proliferation defects of cardiomyocytes, a mechanism which is suspected to be associated with HLHS.

By whole genome sequencing analysis of a small cohort of trios (25 HLHS patients and their parents), the authors investigated a possible association between RP encoding genes and HLHS. Although the possible association between defective RPs and HLHS needs to be verified, the results suggest a novel disease mechanism in HLHS, which is a potentially substantial advance in our understanding of HLHS and CHD. The conclusions of the paper are based on solid experimental evidence from appropriate high- to medium-throughput models, while additional genetic results from an independent patient cohort are needed to verify an association between RP encoding genes and HLHS in patients.

We thank Reviewer 2 for the thoughtful assessment of our manuscript. Our point-by-point responses to the recommendations are provided (Reviewer 2, “Recommendations for the authors”).

Reviewer #1 (Recommendations for the authors): 

(1) Despite an interesting surveillance model, the disease-causing mechanisms directly downstream of the RP variants remain unclear. Can the authors provide any evidence for abnormal ribosomes or defects in translation in cells harboring such variants? The possibility that reduced translation of cardiac transcription factors such as TBX5 and NKX2-5 may contribute to the functional interactions observed should be considered. How do the authors consider that the RP variants are affecting transcript levels as observed in the study?

Our model implies that cell cycle arrest does not require abnormal ribosomes or translational defects but instead relies on the sensing of RP levels or mutations as a fitness-sensing mechanism that activates TP53/CDKN1A-dependent arrest. Supporting this framework, we observed no significant changes in TBX5 or NKX2-5 expression (data not shown), but rather an upregulation of CDKN1A levels upon RP KD.

(2) The authors suggest that a nucleolar stress program is activated in cells harboring RP gene variants. Can they provide additional evidence for this beyond p53 activation? 

We added additional data to support nucleolar stress (Suppl. Fig. 6) and text (lines 52635):

To determine whether cardiac KD of RpS15Aa causes nucleolar stress in the Drosophila heart, we stained larval hearts for Fibrillarin, a marker for nucleoli and nucleolar integrity.  We found that RpS15Aa KD causes expansion of nucleolar Fibrillarin staining in cardiomyocyte, which is a hallmark of nucleolar stress (Suppl. Fig. 6A-C). As a control, we also performed cardiac KD of Nopp140, which is known to cause nucleolar stress upon loss-of-function. We found a similar expansion of Fibrillarin staining in larval cardiomyocyte nuclei (Suppl. Fig. 6C,D). This suggests that RpS15Aa KD indeed causes nucleolar stress in the Drosophila heart, that likely contributes to the dramatic heart loss in adults.

Other recommendations: 

(3) Concerning the cell type specificity, in the proliferation screen, were similar effects seen on the actinin negative as actinin positive EdU+ cells? It would be helpful to refer to the fibroblast result shown in Supplementary Figure 1C in the results section. 

As suggested by reviewer #1, we have added a reference to Supplementary Fig. 1C, D and noted that RP knockdown exerts a non–CM-specific effect on proliferation.

(4) The authors refer to HLHS patients with atrial septal defects and reduced right ventricular ejection fraction. Please clarify the specificity of the new findings to HLHS versus other forms of CHD, as implied in several places in the manuscript, including the abstract.

This study focused on a cohort of 25 HLHS proband-parent trios selected for poor clinical outcome, including restrictive atrial septal defect and reduced right ventricular ejection fraction.  We have revised the following sentence  in response to the Reviewer’s comment (lines 567-571): “While our study highlights the potential of this approach for gene prioritization, additional research is needed to directly demonstrate the functional consequence of the identified genetic variants, verify an association between RP encoding genes and HLHS in other patient cohorts with and without poor outcome, and determine if RP variants have a broader role in CHD susceptibility.

(5) The multi-model approach taken by the authors is clearly a good system for characterizing disease-causing variants. Did the authors score for cardiomyocyte proliferation or the time of phenotypic onset in the zebrafish model? 

We used an antibody against phosphohistone 3 to identify proliferating cells and DAPI to identify all cardiac cells in control injected, rps15a morphants, and rps15a crispants. We found that  cell numbers and proliferating cells were significantly reduced at 24 and 48 hpf. By 72 hpf cardiac cell proliferation is greatly diminished even in controls, where proliferation typically declines. 

Reduced ventricular cardiomyocyte numbers could potentially result from impaired addition of LTPB3-expressing progenitors. In experiments where altered cardiac rhythm is observed, please comment on the possible links to proliferation.

Heart function data showed that heart period (R-R interval) was unaffected in morphants and crispants at 72 hpf where we also observed significant reductions in cell numbers. This suggests that the bradycardia observed in the rps15a + nkx2.5 or tbx5a double KD (Sup. Fig. 5D & E) was not due to the reduction in cell numbers alone. 

Author response image 1.

Finally, the use of the mouse to model HLHS in potential follow-up studies should be discussed. 

We have added a mouse model comment to the discussion (lines 571-74): “In conclusion, we propose that the approach outlined in this study provides a novel framework for rapidly prioritizing candidate genes and systematically testing them, individually or in combination, using a CRISPR/Cas9 genome-editing strategy in mouse embryos (PMID: 28794185)”.

(6) When the authors scored proliferation in cells from the proband in family 75H, did they validate that RPS15A expression is reduced, consistent with a regulatory region defect? 

Good point. We examined RPS15A expression in these cells and found no significant reduction in gene expression in day 25 cardiomyocytes (data not shown). One possible explanation is that this variant may regulate RPS15A expression in a stage-specific manner during differentiation or under additional stress conditions.

(7) Minor point. Typo on line 494: comma should be placed after KD, not before.

Thank you, this has now been corrected (new line 490)

Reviewer #2 (Recommendations for the authors):  

(1) The authors are invited to revise the part of the manuscript that describes the genetic analysis and provide a more balanced discussion of the WGS data, with a conclusion that aligns with the strength of the human genetic data. 

We disagree with reviewer #2’s assessment. The goal of our study is not to apply a classical genetic approach to establish variant pathogenicity, but rather to employ a multidisciplinary framework to prioritize candidate genes and variants and to examine their roles in heart development using model systems. In this context, genetic analysis serves primarily as a filtering tool rather than as a means of definitively establishing causality.

(2) The genetic analysis of patients does not appear to provide strong evidence for an association between RP gene variants and HLHS. More information regarding methodology and the identified variants is needed. 

HLHS is widely recognized as an oligogenic and heterogeneous genetic disease in which traditional genetic analyses have consistently failed to prioritize any specific gene class as reviewer#2 is pointing out. Therefore, relying solely on genetic analysis is unlikely to yield strong evidence for association with a given gene class. This limitation provides the rationale for our multidisciplinary gene prioritization strategy, which leverages model systems to interrogate candidate gene function. Ultimately, definitive validation of this approach will require studies in relevant in vivo models to establish causality within the context of a four-chambered heart (see also Discussion).

In Table S2, it would be appropriate to provide information on sequence, MAF, and CADD. Please note the source of MAF% (GnomAD version?, which population?).  

As summarized in Figure 2A, the 292 genes from the families with the 25 proband with poor outcome displayed in Supplemental Table 2 fulfilled a comprehensive candidate gene prioritization algorithm based on the variant, gene, inheritance, and enrichment, which required all of the following: 1) variants identified by whole genome sequencing with minor allele frequency <1%; 2) missense, loss-of-function, canonical splice, or promoter variants; 3) upper quartile fetal heart expression; and 4)De novo or recessive inheritance. Unbiased network analysis of these 292 genes, which are displayed in Supplemental Table 2 for completeness, identified statistically significant enrichment of ribosomal proteins. The details about MAF, CADD score, and sequence highlighted by the Reviewer are provided for the RP genes in Table 1, which are central to the focus and findings of the manuscript.    

It would also be helpful for the reader if genome coordinates (e.g., 16-11851493-G-A for RSL1D1 p.A7V) were provided for each variant in both Table 1 and S2.

Genome coordinates have been added to Table 1.

(3) The dataset from the hPSC-CM screen could be of high value for the community. It would be appropriate if the complete dataset were made available in a usable format. 

The dataset from the hPSC-CM screen has been added to the manuscript as Supp Table 1

(4) The "rare predicted-damaging promoter variant in RPS15A" (c.-95G>A) does not appear so rare. Considering the MAF of 0,00662, the frequency of heterozygous carriers of this variant is 1 out of 76 individuals in the general population. Thus, considering the frequency of HLHS in the population (2-3 out of 10,000) and the small size of family 75H, the data do not appear to indicate any association between this particular variant and HLHS. The variants in Table 1 also appear to have relatively mild effects on the gene product, judging from the MAF and CADD scores. The authors are invited to discuss why they find these variants disease-causing in HLHS. 

Our study design is based on the widely held premise that HLHS is an oligogenic disorder. Our multi-model systems platform centered on comprehensive filtering of coding and regulatory variants identified by whole genome sequencing of HLHS probands to identify candidate genes associated with susceptibility to this rare developmental phenotype. 75H proved to be a high-value family for generating a relatively short list of candidate genes for left-sided CHD. Given the rarity of both left-sided CHD and the RPS15A variant identified in the HLHS proband and his 5th degree relative, with a frequency consistent with a risk allele for an oligogenic disorder, we made the reasonable assumption that this was a bona fide genotype-phenotype association rather than a chance occurrence. Moreover, incomplete penetrance and variable expression is consistent with a genetically complex basis of disease whereby the shared variant is risk-conferring and acts in conjunction with additional genetic, epigenetic, and/or environmental factors that lead to a left-sided CHD phenotype. In sum, we do not claim these variants are definitively disease causing, but rather potentially contributing risk factors.

(5) Information is lacking on how clustering of RP genes was demonstrated using STRING (with P-values that support the conclusions). What is meant by "when the highest stringency filter was applied"? Does this refer to the STRING interaction score or something else? The authors could also explain which genes were used to search STRING (e.g., all 292 candidate genes) and provide information on the STRING interaction score used in the analysis, the number of nodes and edges in the network.

To determine whether certain gene networks were over-represented, two online bioinformatics tools were used. First, genes were inputted into STRING (Author response table 2 below) to investigate experimental and predicted protein-protein and genetic interactions. Clustering of ribosomal protein genes was demonstrated when applying the highest stringency filter. Next, genes were analyzed for potential enrichment of genes by ontology classification using PANTHER .Applying Fisher’s exact test and false discovery rate corrections, ribosomal proteins were the most enriched class when compared to the reference proteome, including data annotated by molecular function (4.84-fold, p=0.02), protein class (6.45-fold, p=0.00001), and cellular component (9.50fold, p=0.001). A majority of the identified RP candidate genes harbored variants that fit a recessive inheritance disease model.

Author response image 2.

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Synthèse du Débat : Le Genre Précède-t-il le Sexe ?

Résumé Exécutif

Ce document de synthèse analyse le débat contradictoire portant sur l'affirmation « Le genre précède le sexe », opposant Lou Girard (position affirmative) et Franck Ramus (position négative).

Le débat met en lumière une divergence fondamentale entre deux cadres d'analyse :

• l'un, issu des études de genre et de la sociologie, postule que les structures sociales (le genre) façonnent la conceptualisation scientifique de la biologie (le sexe) ;

• l'autre, ancré dans la biologie évolutionniste, soutient que les réalités biologiques (le sexe) constituent le substrat sur lequel se développent les constructions culturelles (le genre).

Lou Girard, s'appuyant sur les travaux de Christine Delphy et Thomas Laqueur, argue que la notion de sexe binaire est une construction scientifique récente (XVIIIe siècle), historiquement contingente et influencée par le système patriarcal qu'elle visait à justifier.

Pour Girard, le genre, en tant que système social hiérarchique, est donc premier.

Franck Ramus contre-argumente sur trois niveaux : ontologique (le phénomène biologique du sexe existe depuis un milliard d'années), développemental (un individu est sexué dès la conception, bien avant l'influence du genre) et évolutionniste (les différences de stratégies reproductives entre mâles et femelles expliquent l'émergence de rôles de genre récurrents dans les sociétés humaines).

La divergence principale ne réside pas seulement dans la conclusion, mais dans l'épistémologie :

quel poids accorder aux preuves issues de la sociologie historique par rapport à celles de la biologie évolutionniste ?

Le débat révèle que même lorsque les deux intervenants partagent des sources communes, leurs cadres interprétatifs radicalement différents les mènent à des conclusions opposées, notamment sur la nature binaire du sexe et la validité des reconstructions historiques des concepts scientifiques.

--------------------------------------------------------------------------------

1. Contexte et Cadre du Débat

Le débat a été organisé dans un format de "débat constructif" visant à clarifier les points d'accord et de désaccord plutôt qu'à déterminer un vainqueur.

Les deux intervenants ont été invités à défendre des positions opposées sur la proposition "Le genre précède le sexe".

• Position Affirmative ("Oui") : Défendue par Lou Girard.

• Position Négative ("Non") : Défendue par Franck Ramus.

Le format incluait des phases distinctes :

• une prise de position initiale, une session de clarification pour assurer la compréhension mutuelle,

• une phase de "personne de fer" où chaque intervenant reformulait la position de l'autre de manière charitable,

• et des discussions sur les racines des convictions, les limites des approches respectives,

• et enfin les points de convergence et de divergence.

2. Position Affirmative (Lou Girard) : Le Genre comme Principe Organisateur

La position de Lou Girard s'ancre dans le champ pluridisciplinaire des études sur le genre (sociologie, philosophie, études féministes).

Son argument central est que notre compréhension du "sexe" biologique est une construction sociale façonnée par le système de genre préexistant.

Origine et Définitions Clés

• Source de l'affirmation : La sociologue Christine Delphy.

• Définition du Genre : Un "système bicatégorisé (hommes/femmes) et hiérarchisé" où les femmes sont subordonnées aux hommes, notamment par l'exploitation de leur travail domestique et reproductif (patriarcat).

• Définition du Sexe : Il ne s'agit pas des organes génitaux, mais du concept de sexe tel qu'utilisé en biologie, c'est-à-dire la "distinction antagoniste entre les mâles et les femelles".

L'Argument Principal : Une Construction Sociale du Sexe Biologique

L'affirmation "Le genre précède le sexe" signifie que le concept scientifique du sexe biologique a été construit épistémologiquement sur les bases du patriarcat.

Il s'agit d'une "justification scientifique d'un système social".

La science n'a pas découvert le sexe binaire dans un vide neutre ; elle a formalisé une catégorie qui servait à rationaliser une organisation sociale déjà en place.

Preuves Historiques (Thomas Laqueur)

Girard s'appuie fortement sur les travaux de l'historien Thomas Laqueur (La fabrique du sexe) pour démontrer que la conception binaire du sexe est une idée récente.

• Avant le XVIIIe siècle : Le sexe n'était pas conçu comme deux catégories distinctes.

◦ Antiquité : Un modèle à "sexe unique" prévalait, où les organes féminins étaient vus comme une version invertie des organes masculins.  

◦ Moyen Âge : Le sexe était perçu comme un continuum basé sur la "chaleur vitale", les hommes représentant le plus haut degré de cette chaleur.

• À partir du XVIIIe siècle : Le modèle binaire s'impose, coïncidant avec une volonté de naturaliser les rôles sociaux.

Implications et Continuité du Biais Patriarcal

Le modèle binaire, une fois établi, a eu des conséquences concrètes, servant d'outil de normalisation sociale.

• Personnes intersexes : Plutôt que de remettre en question le modèle binaire face à des cas qui ne s'y conforment pas, la médecine a historiquement "mutilé" les personnes intersexes pour les faire correspondre à l'une des deux catégories.

• Homosexuels et personnes trans : Leur existence contrevenant au modèle biomédical, ils ont été psychiatrisés et internés.

• Biais actuel : Ce biais patriarcal continue, selon Girard, d'influencer la recherche scientifique, qui tend à justifier inconsciemment les normes patriarcales plutôt qu'à décrire les faits de manière neutre.

3. Position Négative (Franck Ramus) : Le Sexe comme Prérequis Biologique

La position de Franck Ramus repose sur une distinction claire entre le phénomène biologique du sexe et le concept humain de sexe.

Il soutient que le sexe, en tant que réalité biologique fondamentale, précède et influence l'émergence des constructions sociales comme le genre.

Définition Fondamentale du Sexe

• Le Sexe comme Stratégie Reproductive : Ramus définit le sexe à son niveau le plus fondamental, stabilisé en biologie, comme la distinction entre deux types sexuels dans la reproduction sexuée anisogame :

◦ Femelles : Porteurs de gros gamètes (ovocytes).    ◦ Mâles : Porteurs de petits gamètes (spermatozoïdes).

• Cette définition est primordiale, et les autres aspects (génétiques, hormonaux) en découlent.

L'Argument Principal : Trois Niveaux d'Analyse

Ramus défend que le sexe précède le genre à trois échelles distinctes :

1. Niveau Ontologique : Le phénomène du sexe existe dans la nature depuis environ un milliard d'années, bien avant l'apparition de l'humanité, du patriarcat ou de la conceptualisation humaine du sexe.

2. Niveau Développemental (Individuel) : Un individu possède un sexe dès la conception (chromosomes sexuels).

L'influence du genre et des représentations sociales n'intervient qu'après la naissance. Pour le fœtus, le sexe précède donc clairement le genre.

3. Niveau Évolutionniste (Espèce) : Le genre, en tant que phénomène social, n'émerge pas de rien.

Il se développe sur la base de prédispositions biologiques issues de l'évolution.

Le Modèle Évolutionniste : De l'Anisogamie à la Domination Masculine

Ramus propose une explication évolutionniste à l'origine des rôles de genre.

• Investissement Parental Différentiel : L'anisogamie (différence de taille des gamètes) entraîne un investissement reproductif initial plus élevé pour les femelles.

Cela les incite à investir davantage dans la survie de la progéniture (gestation, allaitement, élevage).

L'investissement des mâles peut rester minimal.

• Conséquences Comportementales :

◦ Les mâles sont en compétition pour l'accès aux femelles, ce qui sélectionne des traits comme l'agressivité, la taille et la force.  

◦ Les femelles, ayant plus à perdre, sont plus sélectives dans le choix de leurs partenaires.

• Origine de la Domination Masculine : La sélection pour une plus grande taille et force chez les mâles (pour la compétition inter-mâles) a pour "effet secondaire" de les rendre physiquement plus forts que les femelles, rendant ainsi la domination masculine possible.

• Division du Travail : Les contraintes reproductives (grossesse, allaitement) rendent les femelles plus sédentaires, tandis que les mâles sont plus mobiles.

Cela favorise une "répartition relativement naturelle des rôles et des tâches", que l'on retrouve dans de multiples cultures.

Ramus précise que ce n'est pas une justification morale, mais une explication causale.

4. Points de Divergence Fondamentaux

Le débat a cristallisé plusieurs points de désaccord profonds, qui sont moins factuels qu'épistémologiques.

Primauté de la Nature vs. la Culture

C'est l'opposition centrale du débat.

• Pour Girard : La culture précède la nature. Les systèmes sociaux (genre) déterminent la manière dont nous conceptualisons et même percevons la réalité biologique (sexe).

• Pour Ramus : La nature précède la culture. Les prédispositions biologiques humaines constituent le socle sur lequel les cultures se développent.

La Binarité du Sexe : Concept vs. Réalité Biologique

• Pour Ramus : Le sexe, défini par la stratégie reproductive (production de deux types de gamètes), est fondamentalement binaire.

• Pour Girard : Le sexe biologique n'est pas binaire. Cette vision est le produit d'un modèle social imposé à une réalité plus complexe (comme en témoignent les personnes intersexes).

L'Interprétation des Preuves Historiques et Scientifiques

Le cas de Thomas Laqueur est emblématique de cette divergence.

• Girard accepte les conclusions de Laqueur comme une preuve historique valide que la conception binaire du sexe est une construction récente.

• Ramus exprime son "incrédulité" face à cette affirmation, la trouvant contre-intuitive.

Il a du mal à imaginer qu'avant le XVIIIe siècle, les humains n'avaient pas conscience de l'existence de deux sexes.

Pour lui, le critère d'arbitrage serait le consensus scientifique parmi les historiens, pas la thèse d'un seul auteur.

Poids Épistémologique des Disciplines et des Données

Initialement présentée comme une opposition entre sociologie (Girard) et biologie (Ramus), la divergence est plus subtile.

• Girard accorde une grande valeur aux analyses des études de genre pour déconstruire les biais inhérents à la production du savoir scientifique.

• Ramus ne rejette pas les sciences humaines et sociales, mais se dit "non convaincu" par certains arguments et données spécifiques issus des études de genre, qu'il confronte à des données issues de la biologie ou de la psychologie.

Le débat a montré que même en lisant les mêmes auteurs (ex: Anne Fausto-Sterling), ils en tirent des conclusions radicalement opposées, révélant des cadres d'analyse irréconciliables.

5. Racines des Positions et Limites Reconnues

Parcours et Motivations Personnelles

• Franck Ramus : Son intérêt pour le sujet provient de ses recherches en sciences cognitives, où il a observé de manière répétée et non sollicitée des différences entre sexes (prévalence de l'autisme, dyslexie, développement du langage, neuroanatomie), le poussant à en chercher les origines.

• Lou Girard : Sa position est façonnée par son expérience de femme transgenre.

La confrontation au sexisme et à la transphobie l'a conduite à s'intéresser au féminisme, puis aux études de genre, dont elle a adopté le cadre d'analyse matérialiste comme étant le plus pertinent pour comprendre la société.

Limites et Incertitudes Avouées

• Franck Ramus : Admet que l'approche évolutionniste est une "inférence à la meilleure explication" et qu'il ne peut apporter de "preuves irréfutables" pour chaque détail de ce récit historique.

Sa force réside dans sa cohérence et son pouvoir explicatif global.

• Lou Girard : Reconnaît ses limites personnelles en tant que non-experte diplômée, ce qui pourrait limiter sa compréhension des théories qu'elle expose.

Elle admet également la possibilité de faiblesses épistémologiques dans l'approche des études de genre elle-même, ainsi que l'existence de limites qu'elle ne perçoit pas.

6. Points de Convergence Identifiés

Malgré les divergences profondes, quelques points d'accord ont été établis :

• L'existence du patriarcat en tant que système social qui désavantage les femmes.

• La préexistence de phénomènes biologiques ("nature") avant l'émergence de la culture humaine.

• Le fait que les individus sont biologiquement sexués avant d'être socialisés.

• Un désaccord commun sur la validité du premier modèle des "cinq sexes" d'Anne Fausto-Sterling, bien que leur analyse de l'évolution de son travail diverge par la suite.

eLife Assessment

This valuable work substantially advances our understanding of prognostic value of total gfDNA in gastric cancer. The evidence supporting the conclusions is solid, supported by a large, well-classified patient cohort and controlled clinical variables. The work will be of broad interest to scientists and clinical pathologist working in the field of gastric cancer.

Reviewer #1 (Public review):

The study analyzes the gastric fluid DNA content identified as a potential biomarker for human gastric cancer. However, the study lacks overall logicality, and several key issues require improvement and clarification. In the opinion of this reviewer, some major revisions are needed:

(1) This manuscript lacks a comparison of gastric cancer patients' stages with PN and N+PD patients, especially T0-T2 patients.

(2) The comparison between gastric cancer stages seems only to reveal the difference between T3 patients and early-stage gastric cancer patients, which raises doubts about the authenticity of the previous differences between gastric cancer patients and normal patients, whether it is only due to the higher number of T3 patients.

(3) The prognosis evaluation is too simplistic, only considering staging factors, without taking into account other factors such as tumor pathology and the time from onset to tumor detection.

(4) The comparison between gfDNA and conventional pathological examination methods should be mentioned, reflecting advantages such as accuracy and patient comfort.

(5) There are many questions in the figures and tables. Please match the Title, Figure legends, Footnote, Alphabetic order, etc.

(6) The overall logicality of the manuscript is not rigorous enough, with few discussion factors, and cannot represent the conclusions drawn.

Comments on revisions:

The authors have addressed all concerns in the revision.

Reviewer #2 (Public review):

Summary

The authors aimed to evaluate whether total DNA concentration in gastric fluid (gfDNA) collected during routine endoscopy could serve as a diagnostic and prognostic biomarker for gastric cancer. Using a large cohort (n=941), they reported elevated gfDNA in gastric cancer patients, an unexpected association with improved survival, and a positive correlation with immune cell infiltration.

Strengths

The study benefits from a substantial sample size, clear patient stratification, and control of key clinical confounders. The method is simple and clinically feasible, with preliminary evidence linking gfDNA to immune infiltration.

Weaknesses

(1) While the study identifies gfDNA as a potential prognostic tool, the evidence remains preliminary. Unexplained survival associations and methodological gaps weaken support for the conclusions.

(2) The paradoxical association between high gfDNA and better survival lacks mechanistic validation. The authors acknowledge but do not experimentally distinguish tumor vs. immune-derived DNA, leaving the biological basis speculative.

(3) Pre-analytical variables were noted but not systematically analyzed for their impact on gfDNA stability.

Comments on revisions:

To enhance the completeness and credibility of this research, it is essential to clarify the biological origin of gastric fluid DNA and validate these preliminary findings through a prospective, longitudinal study design.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review): 

“The study analyzes the gastric fluid DNA content identified as a potential biomarker for human gastric cancer. However, the study lacks overall logicality, and several key issues require improvement and clarification. In the opinion of this reviewer, some major revisions are needed:” 

(1) “This manuscript lacks a comparison of gastric cancer patients' stages with PN and N+PD patients, especially T0-T2 patients.”

We are grateful for this astute remark. A comparison of gfDNA concentration among the diagnostic groups indicates a trend of increasing values as the diagnosis progresses toward malignancy. The observed values for the diagnostic groups are as follows:

Author response table 1.

The chart below presents the statistical analyses of the same diagnostic/tumor-stage groups (One-Way ANOVA followed by Tukey’s multiple comparison tests). It shows that gastric fluid gfDNA concentrations gradually increase with malignant progression. We observed that the initial tumor stages (T0 to T2) exhibit intermediate gfDNA levels, which in this group is significantly lower than in advanced disease (p = 0.0036), but not statistically different from non-neoplastic disease (p = 0.74).

Author response image 1.

(2) “The comparison between gastric cancer stages seems only to reveal the difference between T3 patients and early-stage gastric cancer patients, which raises doubts about the authenticity of the previous differences between gastric cancer patients and normal patients, whether it is only due to the higher number of T3 patients.”

We appreciate the attention to detail regarding the numbers analyzed in the manuscript. Importantly, the results are meaningful because the number of subjects in each group is comparable (T0-T2, N = 65; T3, N = 91; T4, N = 63). The mean gastric fluid gfDNA values (ng/µL) increase with disease stage (T0-T2: 15.12; T3-T4: 30.75), and both are higher than the mean gfDNA values observed in non-neoplastic disease (10.81 ng/µL for N+PD and 10.10 ng/µL for PN). These subject numbers in each diagnostic group accurately reflect real-world data from a tertiary cancer center.

(3) “The prognosis evaluation is too simplistic, only considering staging factors, without taking into account other factors such as tumor pathology and the time from onset to tumor detection.”

Histopathological analyses were performed throughout the study not only for the initial diagnosis of tissue biopsies, but also for the classification of Lauren’s subtypes, tumor staging, and the assessment of the presence and extent of immune cell infiltrates. Regarding the time of disease onset, this variable is inherently unknown--by definition--at the time of a diagnostic EGD. While the prognosis definition is indeed straightforward, we believe that a simple, cost-effective, and practical approach is advantageous for patients across diverse clinical settings and is more likely to be effectively integrated into routine EGD practice.

(4) “The comparison between gfDNA and conventional pathological examination methods should be mentioned, reflecting advantages such as accuracy and patient comfort. “

We wish to reinforce that EGD, along with conventional histopathology, remains the gold standard for gastric cancer evaluation. EGD under sedation is routinely performed for diagnosis, and the collection of gastric fluids for gfDNA evaluation does not affect patient comfort. Thus, while gfDNA analysis was evidently not intended as a diagnostic EGD and biopsy replacement, it may provide added prognostic value to this exam.

(5) “There are many questions in the figures and tables. Please match the Title, Figure legends, Footnote, Alphabetic order, etc. “

We are grateful for these comments and apologize for the clerical oversight. All figures, tables, titles and figure legends have now been double-checked.

(6) “The overall logicality of the manuscript is not rigorous enough, with few discussion factors, and cannot represent the conclusions drawn. “

We assume that the unusual wording remark regarding “overall logicality” pertains to the rationale and/or reasoning of this investigational study. Our working hypothesis was that during neoplastic disease progression, tumor cells continuously proliferate and, depending on various factors, attract immune cell infiltrates. Consequently, both tumor cells and immune cells (as well as tumor-derived DNA) are released into the fluids surrounding the tumor at its various locations, including blood, urine, saliva, gastric fluids, and others. Thus, increases in DNA levels within some of these fluids have been documented and are clinically meaningful. The concurrent observation of elevated gastric fluid gfDNA levels and immune cell infiltration supports the hypothesis that increased gfDNA—which may originate not only from tumor cells but also from immune cells—could be associated with better prognosis, as suggested by this study of a large real-world patient cohort.

In summary, we thank Reviewer #1 for his time and effort in a constructive critique of our work.

Reviewer #2 (Public review):

Summary: 

“The authors investigated whether the total DNA concentration in gastric fluid (gfDNA), collected via routine esophagogastroduodenoscopy (EGD), could serve as a diagnostic and prognostic biomarker for gastric cancer. In a large patient cohort (initial n=1,056; analyzed n=941), they found that gfDNA levels were significantly higher in gastric cancer patients compared to non-cancer, gastritis, and precancerous lesion groups. Unexpectedly, higher gfDNA concentrations were also significantly associated with better survival prognosis and positively correlated with immune cell infiltration. The authors proposed that gfDNA may reflect both tumor burden and immune activity, potentially serving as a cost-effective and convenient liquid biopsy tool to assist in gastric cancer diagnosis, staging, and follow-up.”

Strengths: 

“This study is supported by a robust sample size (n=941) with clear patient classification, enabling reliable statistical analysis. It employs a simple, low-threshold method for measuring total gfDNA, making it suitable for large-scale clinical use. Clinical confounders, including age, sex, BMI, gastric fluid pH, and PPI use, were systematically controlled. The findings demonstrate both diagnostic and prognostic value of gfDNA, as its concentration can help distinguish gastric cancer patients and correlates with tumor progression and survival. Additionally, preliminary mechanistic data reveal a significant association between elevated gfDNA levels and increased immune cell infiltration in tumors (p=0.001).”

Reviewer #2 has conceptually grasped the overall rationale of the study quite well, and we are grateful for their assessment and comprehensive summary of our findings.

Weaknesses: 

(1) “The study has several notable weaknesses. The association between high gfDNA levels and better survival contradicts conventional expectations and raises concerns about the biological interpretation of the findings.“

We agree that this would be the case if the gfDNA was derived solely from tumor cells. However, the findings presented here suggest that a fraction of this DNA would be indeed derived from infiltrating immune cells. The precise determination of the origin of this increased gfDNA remains to be achieved in future follow-up studies, and these are planned to be evaluated soon, by applying DNA- and RNA-sequencing methodologies and deconvolution analyses.

(2) “The diagnostic performance of gfDNA alone was only moderate, and the study did not explore potential improvements through combination with established biomarkers. Methodological limitations include a lack of control for pre-analytical variables, the absence of longitudinal data, and imbalanced group sizes, which may affect the robustness and generalizability of the results.“

Reviewer #2 is correct that this investigational study was not designed to assess the diagnostic potential of gfDNA. Instead, its primary contribution is to provide useful prognostic information. In this regard, we have not yet explored combining gfDNA with other clinically well-established diagnostic biomarkers. We do acknowledge this current limitation as a logical follow-up that must be investigated in the near future.

Moreover, we collected a substantial number of pre-analytical variables within the limitations of a study involving over 1,000 subjects. Longitudinal samples and data were not analyzed here, as our aim was to evaluate prognostic value at diagnosis. Although the groups are imbalanced, this accurately reflects the real-world population of a large endoscopy center within a dedicated cancer facility. Subjects were invited to participate and enter the study before sedation for the diagnostic EGD procedure; thus, samples were collected prospectively from all consenting individuals.

Finally, to maintain a large, unbiased cohort, we did not attempt to balance the groups, allowing analysis of samples and data from all patients with compatible diagnoses (please see Results: Patient groups and diagnoses).

(3) “Additionally, key methodological details were insufficiently reported, and the ROC analysis lacked comprehensive performance metrics, limiting the study's clinical applicability.“

We are grateful for this useful suggestion. In the current version, each ROC curve (Supplementary Figures 1A and 1B) now includes the top 10 gfDNA thresholds, along with their corresponding sensitivity and specificity values (please see Suppl. Table 1). The thresholds are ordered from-best-to-worst based on the classic Youden’s J statistic, as follows:

Youden Index = specificity + sensitivity – 1 [Youden WJ. Index for rating diagnostic tests. Cancer 3:32-35, 1950. PMID: 15405679]. We have made an effort to provide all the key methodological details requested, but we would be glad to add further information upon specific request.

Reviewer #1 (Recommendations for the authors):

The authors should pay attention to ensuring uniformity in the format of all cited references, such as the number of authors for each reference, the journal names, publication years, volume numbers, and page number formats, to the best extent possible. 

Thank you for pointing this inconsistency. All cited references have now been revisited and adjusted properly. We apologize for this clerical oversight.

Reviewer #2 (Recommendations for the authors):

(1) “High gfDNA levels were surprisingly linked to better survival, which conflicts with the conventional understanding of cfDNA as a tumor burden marker. Was any qualitative analysis performed to distinguish DNA derived from immune cells versus tumor cells?“

Tumor-derived DNA is certainly present in gfDNA, as our group has unequivocally demonstrated in a previous publication [Pizzi M. P., et al. (2019) Identification of DNA mutations in gastric washes from gastric adenocarcinoma patients: Possible implications for liquid biopsies and patient follow-up Int J Cancer 145:1090–1097. DOI: 10.1002/ijc.32114]. However, in the present manuscript, our data suggest that gfDNA may also contain DNA derived from infiltrating immune cells. This may also be the case for other malignancies, and qualitative deconvolution studies could provide more informative information. To achieve this, DNA sequencing and RNA-Seq analyses may offer relevant evidence. Our study should be viewed as an original and preliminary analysis that may encourage such quantitative and qualitative studies in biofluids from cancer patients. Currently, this is a simple approach (which might be its essential beauty), but we hope to investigate this aspect further in future studies.

(2) “The ROC curve AUC was 0.66, indicating only moderate discrimination ability. Did the authors consider combining gfDNA with markers such as CEA or CA19-9 to improve diagnostic accuracy?“

This is indeed a logical idea, which shall certainly be explored in planned follow-up studies.

(3) “DNA concentration could be influenced by non-biological factors, including gastric fluid pH, sampling location, time delay, or freeze-thaw cycles. Were these operational variables assessed for their effect on data stability?“

We appreciate the rigor of the evaluation. Yes, information regarding gastric fluid pH was collected. All samples were collected from the stomach during EGD procedure. Samples were divided in aliquots and were thawed only once. This information is now provided in the updated manuscript text.

(4) “This cross-sectional study lacks data on gfDNA changes over time, limiting conclusions on its utility for monitoring treatment response or predicting recurrence.“

Again, temporal evaluation is another excellent point, and it will be the subject of future analyses. In this exploratory study, samples were collected at diagnosis, at a single point. We have not obtained serial samples, as participants received appropriate therapy soon following diagnosis.

(5) The normal endoscopy group included only 10 patients, the precancerous lesion group 99 patients, while the gastritis group had 596 patients. Such uneven sample sizes may affect statistical reliability and generalizability. Has weighted analysis or optimized sampling been considered for future studies?“

Yes, in future studies this analysis will be considered, probably by employing stratified random sampling with relevant patient attributes recorded.

(6) “The SciScore was only 2 points, indicating that key methodological details such as inclusion/exclusion criteria, randomization, sex variables, and power calculation were not clearly described. It is recommended that these basic research elements be supplemented in the Methods section. “

This was an exploratory research, the first of its kind, to evaluate prognostic potential of gfDNA in the context of gastric cancer. Patients were not included if they did not sign the informed consent or excluded if they withdrew after consenting. Other exclusion criteria included diagnoses of conditions such as previous gastrectomy or esophagectomy, or the presence of non-gastric malignancies. Randomization and power analyses were not applicable, as no prior data were available regarding gfDNA concentration values or its diagnostic/prognostic potential. All subjects, regardless of sex, were invited to participate without discrimination or selection.

(7) “Although a ROC curve was provided in the supplementary materials (Supplementary Figure 1), only the curve and AUC value were shown without sensitivity, specificity, predictive values, or cutoff thresholds. The authors are advised to provide a full ROC performance assessment to strengthen the study's clinical relevance.

These data are now given alongside the ROC curves in the Supplementary Information section, specifically in Supplementary Figure 1 and in the newly added Supplementary Table 1.

We thank Reviewer #2 for an insightful and positive overall assessment of our work.

L'Idéologie et l'Esprit Critique : Synthèse du Débat

Résumé Exécutif

Ce document synthétise les arguments et les conclusions du débat sur la compatibilité entre l'idéologie et l'esprit critique, opposant Gwen Pallarès (position positive) et Pascal Wagner-Egger (position négative).

Gwen Pallarès soutient que l'idéologie est non seulement compatible mais souvent un prérequis et un moteur pour l'esprit critique, arguant que tout individu possède une idéologie qui structure sa pensée et motive sa curiosité.

Pascal Wagner-Egger défend la position selon laquelle l'idéologie est fondamentalement un obstacle à la pensée critique et à la démarche scientifique, un ensemble de préconceptions qu'il faut activement chercher à minimiser en s'appuyant sur des données empiriques.

Malgré leurs positions de départ opposées, un consensus significatif a émergé sur plusieurs points.

Les deux intervenants s'accordent sur l'existence d'un "point de bascule" ou d'un "saut qualitatif" où l'idéologie devient incompatible avec l'esprit critique, notamment dans les cas de fanatisme, de radicalisation ou lorsque les croyances fondamentales liées à l'identité sont menacées.

Ils reconnaissent également que l'idéologie peut agir comme une puissante "motivation épistémique", incitant à la recherche et à l'analyse.

La divergence principale réside dans la nature de cette relation.

Pour Pascal, la motivation induite par l'idéologie est une arme à double tranchant qui exige une vigilance épistémique accrue pour contrer les biais.

Pour Gwen, cette motivation est un moteur fondamental, et la volonté de se placer dans une position "centriste" pour éviter les biais est elle-même une position idéologique.

Cette différence de perspective trouve sa source dans des divergences épistémologiques plus profondes sur la nature des sciences, la construction des données et la porosité entre les domaines scientifique et politique.

1. Introduction au Débat

Le débat, animé par Peter Barret, a pour objectif d'explorer la question "L’idéologie est-elle compatible avec l’esprit critique ?" dans un format visant à être constructif et à clarifier les positions plutôt qu'à encourager la contre-argumentation.

Les deux intervenants sont :

• Gwen Pallarès : Maîtresse de conférence en didactique des sciences à l'Université de Reims Champagne-Ardenne, défendant la position positive.

• Pascal Wagner-Egger : Psychologue social à l'Université de Fribourg, défendant la position négative.

2. Définitions Clés

Les intervenants se sont accordés sur les définitions suivantes pour encadrer le débat.

Terme

Définition de Gwen Pallarès (Psychologie Sociale)

Définition de Pascal Wagner-Egger (Larousse)

Idéologie

Un système d'attitudes, de croyances et de stéréotypes qui coordonne les actions des institutions et des individus.

Ce système vise notamment à justifier ou à critiquer les hiérarchies sociales existantes (ex: féminisme vs. masculinisme).

Un système d'idées générales constituant un corps de doctrine philosophique et politique à la base d'un comportement individuel ou collectif (ex: idéologie marxiste, nationaliste).

Esprit Critique : Défini par Gwen Pallarès comme un ensemble de compétences (analyse, évaluation d'arguments et d'informations) et de dispositions (humilité intellectuelle, curiosité, réflexivité).

Cet ensemble est orienté vers la prise de décision raisonnée ("Qu'est-ce qu'il convient de croire ou de faire ?") et s'opérationnalise souvent par une argumentation de bonne qualité.

3. Positions Initiales

3.1. Position de Gwen Pallarès (Positive) : L'Idéologie comme Prérequis Compatible

L'argument central de Gwen Pallarès repose sur l'universalité de l'idéologie :

• Tout le monde a une idéologie : La pensée de chaque individu est structurée par des systèmes de croyances, d'attitudes et de stéréotypes.

Refuser cela serait nier une réalité fondamentale du fonctionnement humain.

• L'incompatibilité rendrait l'esprit critique impossible : Si l'idéologie était incompatible avec l'esprit critique, et puisque tout le monde a une idéologie, alors personne ne pourrait avoir d'esprit critique.

• L'esprit critique est un spectre : Tout le monde possède des compétences minimales d'analyse et d'argumentation, même si leur application peut être biaisée (ex: biais de confirmation où l'on critique plus durement les informations qui contredisent nos croyances).

• Limite de la compatibilité : Elle concède que les formes extrêmes d'idéologie (radicalisation, emprise sectaire, fanatisme) sont, elles, incompatibles avec l'esprit critique car elles poussent à une acceptation acritique des informations.

3.2. Position de Pascal Wagner-Egger (Négative) : L'Idéologie comme Obstacle à la Science

Pascal Wagner-Egger ancre sa position dans l'histoire des sciences et la psychologie sociale :

• La science s'est construite contre l'idéologie : Il cite l'exemple de la science luttant contre l'idéologie religieuse, qu'il qualifie de "régime totalitaire".

• La "méthode idéologique" : Elle postule que la vérité est contenue dans un texte fondateur (la Bible, Le Capital) et que toute observation doit s'y conformer. C'est l'inverse de la méthode scientifique.

• L'ennemi intérieur et extérieur : L'idéologie est un obstacle institutionnel (externe) mais aussi un obstacle interne aux chercheurs eux-mêmes.

Il cite Gaston Bachelard et ses "obstacles épistémologiques" (opinion, connaissance générale) comme précurseurs de la notion de biais cognitifs.

• Le rôle des données empiriques : La méthode scientifique est le principal outil pour limiter les effets de nos idéologies et tester nos préconceptions contre la réalité.

Il cite des études montrant plus de dogmatisme et de complotisme aux extrêmes politiques.

4. Racine des Convictions : Les Parcours Académiques

Les positions des deux débatteurs sont fortement influencées par leurs expériences personnelles et académiques.

• Pascal Wagner-Egger : Son parcours l'a mené des sciences "dures" vers les sciences sociales.

Il a été frappé par ce qu'il a perçu comme des positions idéologiques dogmatiques chez certains collègues, notamment le rejet des méthodes quantitatives qualifiées d'"impérialisme anglo-saxon".

Cette expérience a forgé sa conviction que l'idéologie peut nuire à la recherche de la vérité scientifique et qu'il faut s'en prémunir.

• Gwen Pallarès : Son parcours est inverse, des mathématiques vers la didactique des sciences.

L'étude approfondie des controverses socio-scientifiques (IA, genre, écologie) pour sa thèse l'a progressivement politisée.

Son engagement politique est devenu un moteur pour produire une recherche scientifique plus rigoureuse et utile socialement, notamment pour l'éducation.

Pour elle, l'idéologie n'est pas un obstacle à la rigueur, mais ce qui la motive.

5. Analyse de la Convergence et de la Divergence

Le débat a révélé un terrain d'entente plus large qu'attendu, tout en précisant la nature des désaccords.

5.1. Points de Convergence Fondamentaux

1. Le "Point de Bascule" : Les deux intervenants s'accordent sur le fait qu'il existe un seuil où l'idéologie devient incompatible avec l'esprit critique.

Ce seuil est atteint dans les cas de fanatisme, de radicalisation, ou lorsque des croyances fondamentales liées à l'identité de la personne sont menacées, rendant le dialogue et la remise en question impossibles.

2. La Motivation Épistémique : Il est admis par les deux parties que l'idéologie est un puissant moteur.

Un engagement idéologique (ex: écologiste, féministe) peut stimuler la curiosité intellectuelle, la recherche d'informations et la volonté d'analyser des arguments, qui sont des dispositions centrales de l'esprit critique.

3. L'Universalité de l'Idéologie : Les deux débatteurs partagent le postulat que chaque individu, y compris les scientifiques, possède une ou plusieurs idéologies qui structurent sa vision du monde.

5.2. Points de Divergence Clés

La principale divergence ne porte pas tant sur la compatibilité en soi, mais sur la nature de la relation entre idéologie et esprit critique.

Point de Divergence

Position de Pascal Wagner-Egger

Position de Gwen Pallarès

Nature du lien

Une arme à double tranchant : L'idéologie motive, mais elle biaise simultanément.

Il est donc crucial d'exercer une vigilance épistémique accrue et de chercher à minimiser l'influence de ses propres idéologies, notamment en les confrontant aux données empiriques.

Un moteur fondamental : L'idéologie est le moteur principal de la recherche et de l'engagement critique. Tenter de l'annuler est illusoire.

La posture qui consiste à se vouloir "au centre" pour être moins biaisé est elle-même une idéologie ("biais du juste milieu").

Épistémologie sous-jacente

Plus proche de l'empirisme et du rationalisme critique (citant Popper et se revendiquant de Lakatos).

Les données, bien que partiellement construites, permettent par triangulation de s'approcher d'une réalité indépendante de la méthode.

Plus proche du constructivisme et du pragmatisme. Les données sont fondamentalement construites par la méthodologie, qui est elle-même issue de cadres théoriques.

La distinction entre science et politique est plus poreuse.

Rapport Science / Politique

Vise à maintenir une distinction claire. Dans le domaine scientifique, les données doivent primer sur les préconceptions. Dans le domaine politique, l'idéologie et le militantisme sont utiles et nécessaires.

La distinction est moins nette. Le travail scientifique est intrinsèquement lié à des enjeux de société et peut être motivé par un engagement politique, cet engagement pouvant être un gage de rigueur pour rendre la science utile.

Hoe can z-eef decrease as going down?

Hunter, Estelle Belle. 1923. Modern Filing Manual. Rochester, NY: Yawman and Erbe Manufacturing Company. https://www.google.com/books/edition/Modern_Filing_Manual/F-lNAQAAMAAJ?hl=en.

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The entry \(2\) should here be \(1\).

OBSERVATION: Poinsett explains that despite the amicable relations between the US and the Latin American nations, there was no obligation on the part of the US to interfere in Latin American skirmishes such as the attempted invasion of Cuba by France.

INTERPRETATION: Poinsett is relaying clarifications on the part of the administration at the time, who were not keen on having demands made by other countries whom they had no intention of involving themselves officially with.

CONNECTION: The tertiary source notes that although the Monroe Doctrine made a strong declaration that invasion of any of the Americas by European nations will not be tolerated by the US, the people behind it (particularly Henry Clay) quickly changed their stance on US interference with other nations' affairs, choosing to take a more neutral stance and deny any obligation to help anybody beyond their borders.

CHANGE OVER TIME: The US went from boldly positioning themselves as a guiding figure for other nations and a powerful force against European invasion to recoiling and attempting to distance themselves from foreign affairs.

OBSERVATION: Upon having his authority questioned, Poinsett strongly affirms to Clay that his declaration of the US not to permit Europe to interfere with any Latin American governmental affairs was entirely in reference to declarations made by President Monroe in the Monroe Doctrine.

INTERPRETATION: Only three years after the doctrine was issued, miscommunication occurred between the Monroe administration and personnel such as Poinsett, with Poinsett being chastised simply for informing Mexican diplomats of official statements made by the President.

CONNECTION: The tertiary source stated that the authors behind the Monroe Doctrine began to have cold feet not too long after publishing it due to the unintended implication that Spanish-American territories would receive military aid as a part of efforts to keep Europe out of their hair, and that by 1824 Clay's position was that the US would not concern itself with affairs outside of its own borders. It seems that a side effect of this was a discrepancy in understanding between different levels of authority.

CHANGE OVER TIME: The Monroe administration published the Monroe Doctrine as a bold, authoritative stance on international affairs, reflective of the attitude of the War Hawks who were coming into power at the time, but by 1826, they were beginning to backpedal on their assertions due to a fear of misconception on the part of their neighbors down South.

OBSERVATION: Poinsett explains that the government of Mexico entirely understands the nature of the Monroe Doctrine, which is merely a statement made by the Executive branch and not binding in any way.

INTERPRETATION: The US administration saw Poinsett's statements to the government of Mexico as an affirmation of actions which they weren't intent on performing. As such, Poinsett felt the need to not only clarify that he had zero intent to do so, but also that Mexico was fully cognizant of the unbinding nature of the doctrine.

CONNECTION: The implication that Mexico fully understood the true implications of the Monroe Doctrine seems to contradict the tertiary sources, which state that many South American nations thought they would be receiving aid from the US in order to fend off European invasion, hence why Clay needed to clarify that South American nations would be expected to defend themselves entirely.

COMPLEXITY: This suggests that although much of South America misunderstood the implications of the Monroe Doctrine, some nations such as Mexico fully understood the non-committal nature of what was expressed. It could also suggest CHANGE OVER TIME, as perhaps these countries only came to understand this by the time Poinsett had made his statements to the Mexican plenipotentiaries.

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bonjour, j'ai une preoccupation et elle est la suivante : je suis aller dans cette section de code pen j'ai constaté que les valeurs attribuées à l'attribu class ne sont declarées de la meme maniére dans le css. et j'aimerai comprendre pourquoi s'il vous plait.

aussi j'aimerai comprendre si Box apres l'espace dans le HTML lors de l'affectation des valeurs à l'attribut veut tout simplement dire que l'on aura des valeurs geometriques comme par exemple un carré et donc c'est la raison pour laquelle il ne figure pas dans le CSS. merci d'avance pour votre orientation

Editors Assessment:

Coded and written up as part of the African Society for Bioinformatics and Computational Biology (ASBCB) Omicscodeathons, EMImR is a novel Shiny application for transcriptomic and epigenomic change identification and correlation wrapped up using a combination of Bioconductor and CRAN packages. Case studies are on publicly available GEO data corresponding to sequencing data of human blood cell samples of multiple sclerosis patients to demonstrate how the tool works. And a documentation and videos are provided. Peer review and the study highlighting the usefulness of the developed tool for analyzing transcriptomic and epigenomic data.

This evaluation refers to version 1 of the preprint

This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.168), and has published the reviews under the same license.

Reviewer 1. Haikuo Li

Is there a clear statement of need explaining what problems the software is designed to solve and who the target audience is? No. Should be made more clear.

Comments: The authors developed EMImR as an R toolkit and open-sourced software for analysis of bulk RNA-seq as well as epigenomic sequencing data including DNA methylation seq and non-coding RNA profiling. This work is very interesting and should be of interest to people interested in transcriptomic and epigenomic data analysis but without computational background. I have two major comments: 1. Results presented in this manuscript were only from microarray datasets and are kind of “old” data. Although these data types and sequencing platforms are still very valuable, I don’t think they are widely used as of today, and therefore, it may be less compelling to the audience. It is suggested to validate EMImR using additional more recently published datasets. 2. The authors studied bulk transcriptomic and epigenomic sequencing data. In fact, single-cell and spatially resolved profiling of these modalities are becoming the mainstream of biomedical research since those methods offer much better resolution and biological insights. The authors are encouraged to discuss some key references of this field (for example, PMIDs: 34062119 and 38513647 for single-cell multiomics; PMID: 40119005 for spatial multiomics sequencing), potentially as the future direction of package development. Re-review: The authors have answered my questions and added new content in the Discussion section as suggested.

Reviewer 2. Weiming He

Dear Editor-in-Chief, The EMImR developed by the author is a Shiny application designed for the identification of transcriptomic and epigenomic changes and data association. This program is mainly targeted at Windows UI users who do not possess extensive computational skills. Its core function is to identify the intersections between genetic and epigenetic modifications

Review Recommendation I recommend that after making appropriate revisions to the current “Minor Revision”, the article can be accepted. However, the author needs to address the following issues.

Major Issue The article does not provide specific information on the resource consumption (memory and time) of the program. This is crucial for new users. Although we assume that the resource consumption is minimal, users need to know the machine configuration required to run the program. Therefore, I suggest adding two columns for “Time” and “Memory” in Table 1.

Minor Issues 1. GitHub Page The Table of Contents on the GitHub page provides a Demonstration Video. However, due to restricted access to YouTube in some regions, it is recommended to also upload a manual in PDF format named “EMImR_manual.pdf” on GitHub. In step 4 of the Installation Guide, it states that “All dependencies will be installed automaticly”. It is advisable to add a step: if the installation fails, prompt the user about the specific error location and guide the user to install the dependent packages manually first to ensure successful installation. Currently, the command “source(‘Dependencies_emimr.R’)” does not return any error messages, which is extremely inconvenient for novice users. The author can provide the maintainer's email address so that users can seek timely solutions when encountering problems

1. R Version The author recommends using R - 4.2.1 (2022), which was released three years ago. The current latest version is R 4.5.1. It is suggested that the author test the program with the latest version to ensure its adaptability to future developments.

2. Flowchart Suggestion It is recommended to add a flowchart to illustrate the sequential relationships among packages such as DESeq2 for differential analysis, clusterProfiler for clustering, enrichplot for plotting, and miRNA - related packages (this is optional).

4.Function Addition Currently, the program seems to lack a button for saving PDFs, as well as functions for batch uploading, saving sessions, and one - click exporting of PDF/PNG files. It is recommended to add the “shinysaver” and “downloadHandler” functions to fulfill these requirements.

1. Personalized Features and Upgrade Plan To attract more users, more personalized features should be added. The author can mention the future upgrade plan in the discussion section. For example, currently, DESeq2 is used for differential analysis, and in future upgrades, more methods such as PossionDis, NOIseq, and EBseq could be provided for users to choose from.

2. Text Polishing Suggestions 6.1 Unify the usage of “down - regulated” and “downregulated”, preferably using the latter. 6.2 “R - studio version” ---》 “RStudio” 6.3 Lumian, ---》 Lumian 6.4 no login wall ---》 does not require user registration 6.5 Rewrite “genes were simultaneously differentially expressed and methylated” as “genes that were both differentially expressed and differentially methylated”. 6.6 Ensure that Latin names of species are in italics 6.7 make corresponding modifications to other sentences to improve the accuracy and professionalism of the language in the article.

The above are my detailed review comments on this article. I hope they can provide a reference for your decision - making.

今後主流になるかは

くらいでいいのでは

以下は冗長なので省略でよさそう

これだと短すぎるので、なんかのリポジトリをまるっと型チェックとかする方がいいかなと思いました

このリンクがわかりにくいので、説明を書いて欲しいかな。

サンドボックスでexample.pyを◯◯した結果

みたいな

nits: 比較する、でいいかなと

VS Codeと書くのが正しいはず https://code.visualstudio.com/

nits: 体言止めと~~するがまざっているのでどっちかに統一がいかな

高速に動作 付ける機能

でよさそう

あとで比較対象にもなっているので、「型チェッカーにはmypy、pyrightなどがありますが、Pyrefryには◯◯な特徴があります」みたいな感じの文章があるといいなと思いました

nits: 名はなくてもよさそうです。（あるいは文章のほうに名をつけるか）

from

/hyperpost/🌐/🧊/0/

Origo Folder - hyperpost web directory on IPFS

https://k51qzi5uqu5div1auuxm59ygav4p7gdg9z4e9iggtu6m43rmc3xw75mczx2b7x.ipns.dweb.link/📝/?isPathWritable=true&path=/♖/hyperpost/🌐/🧊/0/index.html

cut the middle bit out and have access to the document to read and share

📝/?isPathWritable=true&path=

via dweb link

root of the ipfs indy web

Origo Folder - hyperpost web directory on IPFS

哪些年份的

It's raw Mastery

Important steps for a solid introduction