On 2025-02-05 17:26:07, user Star pupil wrote:

There are other cysteineless interns reported to be equally fast if not faster https://www.lens.org/lens/patent/129-790-217-267-302

On 2025-02-05 16:27:18, user anonymous wrote:

"Not previously reported as a direct USP7 substrate, ..." - this may not be entirely accurate; to my knowledge, Liu et al. (2024) may have demonstrated this in their study.

On 2025-02-05 14:46:01, user Prof. T. K. Wood wrote:

First paragraph is misleading as toxin/antitoxin systems have known to inhibit phage for almost 3 decades so instead of citing a review, the original seminal report should be cite: doi: 10.1128/jb.178.7.2044-2050.1996

On 2025-02-05 10:44:20, user pablo RANEA ROBLES wrote:

Hi! This is a very interesting study, and very relevant considering the debate on omega-6 PUFAs on metabolic health. However, when we were going to read it for a journal club we missed the methods section on this preprint.

On 2025-02-04 22:16:48, user Bill Mallet wrote:

To assist interpretation, it would be helpful to plot the dose-response curves in Fig. 2a with a log10 X-axis.

On 2025-02-04 22:09:10, user Bill Mallet wrote:

Thank you for breathing new life into Hu3A5. For the record: The cysteine-engineered ADC is called "DMUC4064A" not "DMU46064A".

On 2025-02-04 18:27:43, user Ian wrote:

Enjoyable read, particularly the introduction. Unsure how well DSS-induced colitis is able to compare to the "allergy-allegory" persistent in the text. The inflammatory etiology of both conditions are different. DSS is primarily barrier function driven whereas the other, as you mention, is "engrammatic". (immune-memory-driven)

On 2025-02-04 14:51:37, user Emily Breeze wrote:

I very much enjoyed this paper but I could seem to find any of the Tables?

On 2025-02-04 00:17:13, user Rene Warren wrote:

A revision (v2) with additional references is now live.

On 2025-01-20 10:44:33, user Mark Blaxter wrote:

The supplementary data files are not linked n the document.<br /> The zenodo file cited for the parameter set used (10.5281/zenodo.14247722) gives a "not found" on the doi system.<br /> The Cheilosia genomes were sequenced by the Darwin Tree of Life project (not EBP) and each genome has a reference, which should be cited (as has been done for the human genomes used): https://wellcomeopenresearch.org/gateways/treeoflife?all=Cheilosia

On 2025-02-03 17:44:55, user disqus_2m2wL3bGCz wrote:

I cannot find the methods part in the uploaded preprint ????‍♂️

On 2025-02-03 14:06:53, user David Hill wrote:

This companion article was peer reviewed during the review and revision process for its parent article:

Dilollo J, Hu A, Qu H, Canziani KE, Clement RL, McCright SJ, Shreffler WG, Hakonarson H, Spergel JM, Cerosaletti K, Hill DA*. A molecular basis for milk allergen immune recognition in eosinophilic esophagitis. Journal of Allergy and Clinical Immunology. 2025 JAN; IN PRESS. PMID: 39891629. PMCID: Pending.

https://pubmed.ncbi.nlm.nih.gov/39891629/

On 2025-02-03 01:37:14, user Lindsay Wu wrote:

The accepted version of this manuscript has now been published online at the Journal of Biological Chemistry, link below:

https://doi.org/10.1016/j.jbc.2025.108248

On 2025-02-02 14:00:44, user Wilson de Oliveira Souza wrote:

I think that figure 1b there is a typo. The trophic pyramid (steeper regression line) shows a S_NBSS > -1 similar to the inverted trophic pyramid (flatter regression line). However, the text states that for this scenario, S_NBSS should be < -1.

On 2025-02-01 14:51:26, user Nikolai Slavov wrote:

Data, code and other resources associated with this research article are available at: https://decode.slavovlab.net/

On 2025-02-01 14:24:49, user Gabriela K. Popescu wrote:

This appears to be useful for voltage gated channels only.

On 2025-02-01 08:17:39, user Filippo Vascon wrote:

A peer-reviewed version of this paper has been published on iScience, Volume 28, Issue 2, 111726. https://doi.org/10.1016/j.isci.2024.111726

On 2025-02-01 00:23:57, user Theo Mantamadiotis wrote:

Now published in Carcinogenesis doi: https://doi.org/10.1093/carcin/bgae077

On 2025-01-31 22:30:16, user Marius Walter wrote:

The detailed protocol for the differentiation of neurons in the supplementary Table 2 is really great. Thank you for including that.

On 2025-01-31 19:40:14, user Dagan Segal wrote:

Dear Oscar,

Thank you so much for your comments and feedback - it took a while to see this on this forum so apologies for the delayed response.

We incorporated some of your suggestions to add more context to discoveries made by your group and others regarding Cav1 in Ewing Sarcoma- appreciate the suggestions!

In our studies, the subset of CD99 High cells we characterized do indeed have caveolae- so in contrast to previous studies- we believe the signaling in these cells do depend on caveolae per se and not just Caveolin-1 expression.

Thanks also for the comment on other signaling pathways- MAPK levels were low in our hands for all these cells (CD99 High or Low) but maybe worth revisiting.

Cheers,<br /> Dagan (first author)

On 2025-01-31 18:42:25, user Michael wrote:

Please link the published version of this article to the preprint. See below for details:<br /> A 3D Self-Assembly Platform Integrating Decellularized Matrix Recapitulates In Vivo Tumor Phenotypes and Heterogeneity. Cancer Res 2025; https://doi.org/10.1158/0008-5472.CAN-24-1954

On 2025-01-31 16:42:34, user Doug wrote:

Fascinating! Perhaps a naive thought, but it would be quite interesting to see what happens to WT vs CD70 WC mice when given several weeks of ad libitum feeding. Behavioral implications of this type of treatment?

On 2025-01-30 16:48:53, user Richard Condit wrote:

This is published in

Condit, R. & Rüger, N. (2024). Demographic variation and demographic niches of tree species in the Barro Colorado forest. Chapter 30 in The First 100 Years of Research on Barro Colorado (eds. H. C. M. Landau & S. J. Wright), pp. 269–276. Smithsonian Scholarly Press.

On 2025-01-29 22:33:23, user Suzanne Amador Kane wrote:

MATLAB code for the various calculations described in this preprint is posted on github now:<br /> https://github.com/amadorkane/Gait-space-clusterer-for-multilegged-locomotion.git <br /> We are working on implementing this code in python -- stay tuned.

On 2025-01-29 13:39:52, user Robert Tropek wrote:

The revised version of this preprint has already been published in Journal of Biogeography: https://doi.org/10.1111/jbi.15076

On 2025-01-29 12:23:58, user Prof. T. K. Wood wrote:

1. line 57: The molecular mechanism of the most-prevalent phage defense system, toxin/antitoxin systems, is relatively well-understood since 1996 (host transcription shutoff, doi: 10.1128/jb.178.7.2044-2050.1996) so this statement is somewhat misleading.

2. l 328: there is little if any evidence of abortive infection in phage defense and a third possibility is the one you found: cells express phage defenses like Kiwa, CRISPR,and TAs and survive the infection.

On 2025-01-29 08:13:29, user Karthik Raman wrote:

This is now published in: https://www.nature.com/articles/s41540-024-00426-5 - pls. arrange to add to the main article.

On 2025-01-29 04:49:44, user 角田 裕之 wrote:

This work has now been published by Springer and is available at the following link: https://doi.org/10.1007/978-981-96-0868-3_4 .

On 2025-01-29 03:53:51, user Gennady Gorin wrote:

Note kb does have strandedness options and should be compatible with this analysis. See, e.g., https://bsky.app/profile/goringennady.bsky.social/post/3lgm3gbfmfs22 .

On 2025-01-28 12:53:31, user Z. Brown wrote:

looks similar to the Brown et al. 2014 study: https://pubs.acs.org/doi/10.1021/ja5060934

On 2025-01-28 09:52:58, user Richard McCulloch wrote:

This article is now published: Proc Natl Acad Sci U S A. 2023 Nov 28;120(48):e2309306120. doi: 10.1073/pnas.2309306120. Epub 2023 Nov 21.

On 2025-01-28 09:50:55, user Richard McCulloch wrote:

This article is now published: Nucleic Acids Res. 2023 Nov 10;51(20):11123-11141. doi: 10.1093/nar/gkad836.

On 2025-01-28 09:23:39, user Dr Balazs Balint wrote:

Source code, documentation (including a tutorial section) of ContScout is available at <br /> https://github.com/h836472/ContScout .<br /> Please look for branch "BioRxiv_version" if you specifically look for the code that is associated with the manuscript version presented here. If you wish to use the latest features (including screening at fine taxonomic resolution) the use of "main" branch is highly recommended.

On 2025-01-27 18:25:14, user Dan T.A. Eisenberg wrote:

The abstract says, “Repeated qPCR-based measurements of the same DNA extraction yielded ICC values ranging from 0.24 to 0.94”. Keyword searching the document for 0.24 does not reveal that number in the body of the manuscript. The body of the manuscript states, “ICCs of qPCR assays varied widely (range 0.43 to 0.94)”. Table 3 seems to indicate a range of 0.259 to 0.936.

On 2025-01-25 17:37:27, user Andreas wrote:

Hello,

Congratulations on the mauscript, really interesting approach! I am a wet lab scientist and I would like to know if you have though of "grounding" your designs to folds which are less likely to cause immunogenicity (e.g. IgG folds) or that have been explored for drug design (e.g. VHHs, DARPins, ankyrins, etc).

On 2025-01-25 16:41:10, user Rouf Banday wrote:

This study provides fundamental insights into how interactions between mutational processes contribute to carcinogenesis. Meticulous and terrific work!

On 2025-01-24 21:14:52, user Norbert Bittner wrote:

Article was already published in a peer-reviewed journal https://link.springer.com/article/10.1007/s00425-024-04541-9

On 2025-01-23 21:00:35, user Nicole Blackstone wrote:

The published paper linked below and on the main page is a cultivated meat LCA, not a media LCA. Is this a mistake?

On 2025-01-06 11:29:20, user Derrick wrote:

See link <br /> https://pubs.acs.org/doi/full/10.1021/acsfoodscitech.4c00281

On 2025-01-23 20:41:28, user handesuermickler wrote:

This study is published in Diagnostics. <br /> Please see the published version through: https://doi.org/10.3390/diagnostics1424284

On 2025-01-23 18:08:17, user Laleh Cote, Ph.D. wrote:

I am the corresponding author for this paper ( https://doi.org/10.1101/2023.05.08.539924 ), which has now been published at PLOS One, here: https://doi.org/10.1371/journal.pone.0317403

Thanks, bioRxiv team!

On 2025-01-23 03:23:26, user Daniel Paulo wrote:

An updated version of this manuscript has been published and is fully available in Communications Biology at https://doi.org/10.1038/s42003-025-07489-y .

On 2025-01-23 00:42:18, user Nikolai Slavov wrote:

Data, code and other resources associated with this articles are available at: https://scp.slavovlab.net/Khan_Elcheikhali_et_al_2024

On 2025-01-22 19:52:04, user Leonardo Chicaybam wrote:

I peer-reviewed this manuscript on ResearchHub: https://www.researchhub.com/paper/6716382/car-t-cells-targeting-ccr9-and-cd1a-for-the-treatment-of-t-cell-acute-lymphoblastic-leukemia/conversation

On 2025-01-22 19:43:49, user Leonardo Chicaybam wrote:

I peer-reviewed this manuscript on ResearchHub: https://www.researchhub.com/paper/8579429/patient-derived-glioblastoma-organoids-as-real-time-avatars-for-assessing-responses-to-clinical-car-t-cell-therapy/reviews

On 2025-01-22 19:38:21, user Leonardo Chicaybam wrote:

I peer-reviewed this manuscript on ResearchHub: https://www.researchhub.com/paper/8637437/age-related-remodeling-of-the-glycocalyx-drives-t-cell-exhaustion/reviews

On 2025-01-22 08:26:37, user PreOmics wrote:

As representatives of PreOmics, we would like to highlight a key observation in the submitted manuscript for readers to consider.

Supplementary Figure 1: The authors describe the injection of 300 ng peptides, but Supplementary Figure 1 shows variations in TIC signal intensities for the compared techniques. These differences may stem from the two different peptide quantification assays employed and described in the study. From a mass spectrometry perspective, such discrepancies make it challenging to technically compare different enrichment techniques due to the influence of signal intensity variations on the S/N ratio, peak-picking algorithms, peptide quantities, and sequence coverage. We recommend to repeat the study and use our recommendations for peptide quantification compatible to ENRICHplus.

In addition, it is important to acknowledge that the ENRICHplus pre-release version was employed for the comparison, which differs from the commercial version scheduled for release on February 22, 2025.

PreOmics is always supportive if customers struggle to achieve expected results with our solutions and we are keen to support you and provide our recommendations to achieve the best results possible.

On 2025-01-21 23:22:04, user Dieter Steinhilber wrote:

The authors state: "18-HEPE is the precursor for resolvin E1 (RvE1), a cardioprotective, specialized pro-resolving mediator (SPM) that activates the GPCR ChemR23" in their abstract. There is solid evidence now that RvE1 does not activate ChemR23 (PMID: 39365815 and PMID: 35125345)

On 2025-01-21 15:16:28, user Dosidicus wrote:

This is a very interesting work, however the by using of the GHK current equation the results cannot be uniquely interpreted as due to the creation of a calcium channel. As an example a channel in which Calcium acts as an activator would produce the same apparent effects. In order to really show that this is a Calcium channel the authors would need to show that there are no changes in the open probability in the different conditions.<br /> That's why in the field the GHK voltage equation with bi-ionic potentials is used. Where the authors not able to measure bi-ionic potentials by putting sodium or magnesium in their intracellular solution?

On 2025-01-21 05:55:14, user Natalie wrote:

Now published in PNAS https://doi.org/10.1073/pna...

On 2025-01-21 03:24:18, user Damien wrote:

I'm wondering where we can get the EII layer for work on Sustainable 1's new nature/bio risk methodology (April 2024) that includes it? The Preprint mentioned it would be on the UN bio lab site, but it's not there yet. Will this ever be available?

On 2025-01-20 14:53:29, user Mathias Witte Paz wrote:

This paper has been published at NAR Genomics and Bioinformatics <br /> https://academic.oup.com/nargab/article/6/4/lqae168/7928173

On 2025-01-20 13:30:27, user Paula Quiroga wrote:

Very interesting intepretation!

On 2025-01-20 10:53:31, user Sudarshan GC wrote:

Very interesting paper. I think several tests are missing like calcium influx assay. Would like to see if increase in calcium concentration in media can help to fold increase the EV production. I would also expect to see the elaboration of precise pathway downstream of Piezo1.

On 2025-01-19 17:40:19, user Thomas Munro wrote:

It's a remarkable achievement to go from virtual screening to subnanomolar affinity and bound structures in one paper. On a minor point, I would recommend adding "neutral" to phrases such as "antagonists and inverse agonists", and in the title. The present wording could be taken to imply two separate categories, but almost all antagonists are inverse agonists . For instance, naloxone and JDTic are indeed antagonists as noted here, but both are also inverse agonists.

On 2025-01-19 08:25:56, user Tsung-Kai Hung wrote:

This article has been published on Genome Research at link https://doi.org/10.1101/gr.278358.123

On 2025-01-18 08:03:05, user Leonardo Chicaybam wrote:

I peer-reviewed this preprint on ResearchHub: https://www.researchhub.com/paper/6692139/scalable-intracellular-delivery-via-microfluidic-vortex-shedding-enhances-the-function-of-chimeric-antigen-receptor-t-cells/reviews

On 2025-01-17 17:28:34, user Pinji Lei wrote:

This preprint is now online published in Dev. Cell.<br /> https://www.cell.com/developmental-cell/abstract/S1534-5807(24)00732-9

On 2025-01-17 10:27:01, user Wouter De Coster wrote:

Hi, this looks very interesting. I regret that you won't share your code before publication, as that means I cannot use your method (or cite your manuscript) when I want to do something similar for our cohorts.

On 2025-01-17 10:09:07, user Xinyan Wang wrote:

It is worth mentioning that in 2022, our DMFF paper (doi:10.26434/chemrxiv-2022-2c7gv or 10.1021/acs.jctc.2c01297) had already attempted force field parameter optimization using a subset of the FreeSolv dataset, based on a differentiable framework and utilizing solvation free energy as the loss function, although on a smaller scale compared to this article. We believe this deserves to be mentioned when reviewing related work in the field.

On 2025-01-17 08:45:25, user xingchen wrote:

No Supplementary Data available.

On 2025-01-17 06:41:26, user yewon wrote:

hi i am a student very interested in your study. Is GRAF workflow currently posted in Cavatica?

On 2025-01-17 04:34:53, user Reese R wrote:

I found this piece impactful and incredibly well written. Nicely done!

On 2025-01-16 20:56:10, user Lisa Brents wrote:

Nice study! Would it possible to do a more chronic study with these explants with lower concentrations of buprenorphine? I'm sure this depends primarily on how long the explants can be functionally maintained. Also, are you considering looking at whether the major metabolites of buprenorphine (norbuprenorphine, glucuronides) also can cause placental sterile inflammation? As you may know, the Concheiro paper showed higher median concentrations of these metabolites than the parent drug in placenta.

On 2025-01-16 12:43:51, user abhinayramaprasad wrote:

Now published at https://doi.org/10.1093/nar/gkae1274

On 2025-01-16 11:21:20, user Michael Ridley wrote:

Figure 5H has 14 labels but only 13 columns

On 2025-01-16 06:03:33, user xPeer wrote:

Courtesy review from xPeerd.com

Summary:<br /> The preprint titled "Venomics AI: a computational exploration of global venoms for antibiotic discovery" presents a robust study leveraging computational and experimental methods to mine and evaluate venom-derived peptides (VEPs) for their potential as new antibiotics. The researchers utilized bioinformatics tools and machine learning-driven prediction models, particularly APEX, to identify and analyze 16,123 venom proteins from four major databases, generating 40,626,260 VEPs. The study identified 386 promising VEPs and demonstrated significant antimicrobial activity in experimental assays, including in vivo models. Identified limitations highlight areas for potential improvement in computational predictions and experimental designs. The study emphasizes the vast, untapped potential of venomics for addressing global antibiotic resistance.

Potential Major Revisions:<br /> 1. Methodological Rigor and Complexity:<br /> - The paper lacks detailed information on the specific machine learning model architectures, training parameters, and validation strategies used for APEX, which could affect reproducibility and understanding of the model's robustness (Page 5, Section APEX).<br /> - The criteria for selecting the "top" VEPs based on predicted MIC values need clearer justification and empirical backing aside from the computational predictions (Page 3, Methods).

1. Experimental Design and Justification:
2. While the study uses a wide range of bacterial strains, the reasons for selecting specific strains and how representative they are of clinical pathogens could be elaborated to strengthen the rationale behind the experiments (Page 6, Section Results).

3. The in vivo efficacy investigations using the mouse model should provide more details on statistical power analysis and exact experimental conditions to ensure reliability and replicability of results (Page 9, Anti-infective activity in preclinical animal models).

4. Data Accessibility and Transparency:

5. The paper mentions data availability but does not provide direct access to the datasets used for training APEX and the resulting VEP predictions, which is essential for verification and reuse by other researchers (Page 10, Data availability).
6. Detailed experimental data, including raw and processed data sets, should be included in supplementary materials or made accessible via appropriate repositories (Page 10, Data availability).

Potential Minor Revisions:<br /> 1. Typographic Errors and Grammatical Mistakes:<br /> - Page 2, Abstract: "Venom-derived peptides, in particular, hold promise for antibiotic discovery due to their evolutionary diversity and unique pharmacological profiles" - the word "hold" should be "holds".<br /> - Page 5, Line 837: "from multiple source organisms" - should be "from multiple source organism".

1. Formatting Issues:
2. The legends and footnotes of figures sometimes appear incomplete or unclear regarding the methods used to generate them. Ensure all figures have comprehensive legends (Page 11, Statistical tests).

3. Consistency in referencing supplementary figures and tables in the main text should be checked, ensuring that all references are accurately placed (Page 2, Abstract).

4. AI Content Analysis:

5. Estimated AI-generated content: ~5-7%.
6. Highlighted AI-detected sections:
7. "Using machine learning, we explored 16,123 venom proteins, generating 40,626,260 venom-encrypted peptides (VEPs)" (Page 1).
8. "Our findings highlight the power of combining digital data and machine learning to accelerate antibiotic discovery" (Page 12).
9. Assessed epistemic impact: This content does contribute substantively to the manuscript by supporting the methodology and results, but may benefit from more nuanced and manual integration to bolster reliability.

Recommendations:<br /> 1. Enhance Methodological Transparency:<br /> - Provide a detailed algorithmic framework for the APEX model, specifying hyperparameters, loss functions, and training-validation splits.<br /> - Include a comprehensive justification for the selection of bacterial strains and the representativeness of the in vivo model used.

1. Expand Data Accessibility:

2. Ensure all datasets and computational tools used in the study are accessible via publicly available repositories, adhering to FAIR data principles.

3. Improve Experimental Detail:

4. Elaborate on experimental protocols, including statistical analyses, to ensure replicability.
5. Provide a more detailed discussion of limitations and potential biases in experimental designs and predictive models.

This detailed review necessitates substantial revisions to address these points and ensure the study meets the high standards expected for reproducibility and transparency in computational biology and experimental antimicrobial research.

On 2025-01-15 22:14:42, user theskullywaglab wrote:

This article has been accepted for publication in the Journal of Experimental Biology. We received glowing reviews and the only substantial change made was to include a figure as a visual guide to the framework proposed. To meet the journal guidelines of maximum 5 tables/figures, this involved combining the two figures of heatmaps into a single figure, and rearranging the Results/Discussion to accommodate the new figures.

Thank you for your interest in this research.

Rex Mitchell

On 2025-01-15 15:15:10, user covis chang wrote:

Provided insights for further exploration of personalized precision medicine, particularly for the early diagnosis and optimized treatment of NEPC.

On 2025-01-14 13:31:44, user Yunhan KUAN wrote:

A very complete article which gives clear description for NEPC and its adeno-to-neuroendocrine lineage transdifferentiation. <br /> It no doubt provides a brand new view for clinical decision-making, and also promotes early recognition as well as intervention for more advanced therapies as a respond to disease progression and changes of tumor nature.

On 2025-01-14 04:30:21, user 張景欣 wrote:

The PSMA scan is considered an excellent tool to replace traditional bone scans and is becoming increasingly widely used. However, if a neuroendocrine tumor does not express PSMA, this indicates the need for newer diagnostic methods or a broader range of targets.

On 2025-01-14 04:06:08, user Yi-Cheng Yang wrote:

This study contributes to the establishment of personalized treatment, such as considering the use of EZH2 inhibitors combined with PSMA-targeted therapy for NE type II patients, providing new treatment options for cancer patients.

On 2025-01-15 13:05:52, user gang_fang wrote:

The peer-reviewed version has been published. You can find the link below.<br /> https://pmc.ncbi.nlm.nih.gov/articles/PMC11707888/

On 2025-01-14 10:48:17, user Sander Kooijmans wrote:

This manuscript has now been published in Journal of Extracellular Vesicles:<br /> https://isevjournals.onlinelibrary.wiley.com/doi/10.1002/jev2.70017

On 2025-01-14 03:19:09, user Bryan wrote:

Are you able to share a version with high quality figures? The text in many figures is not readable. Thank you!

On 2025-01-13 02:26:25, user Harim Chun wrote:

The expansion distance varies by Xenium Analyzer version. In XOA v2.0 and later versions, the expansion distance is 5 µm, while in XOA v1.0-1.9, the default expansion distance was 15 µm. Therefore, it is important to specify which version of the Xenium Analyzer is being used.<br /> https://www.10xgenomics.com/support/software/xenium-onboard-analysis/latest/algorithms-overview/segmentation#seg-nucleus-expansion

On 2025-01-11 04:47:52, user xPeer wrote:

Here's a courtesy review from xPeerd.com

Summary

The manuscript titled "E-cadherin endocytosis promotes non-canonical EGFR:STAT signalling to induce cell death and inhibit heterochromatinisation" studies the impact of E-cadherin endocytosis on EGFR and STAT signalling pathways in Drosophila wing discs. It reveals that E-cadherin endocytosis facilitates EGFR:STAT signalling, which in turn promotes apoptosis and inhibits heterochromatin formation.

Potential Major Revisions

1. Research Design and Methodology:
2. While the methodology is sound, there are areas that need more clarity. For example, the paper describes the use of E-cad::EOS overexpression but lacks detailed control experiments and statistical analysis to support the claims about changes in gene expression (p. 4, Section 1).

3. The reliance on Drosophila as a model organism is justified but requires additional discussion on how the findings translate to vertebrate systems (p. 1, Summary).

4. Clear Contribution to the Field:

5. The potential tumor-suppressive mechanism proposed is intriguing, but the manuscript needs to more clearly define its novel contributions against existing literature. The exact nature of the signalosome and its comparison with known complexes should be elaborated (p. 17, Discussion).
6. It should explicitly differentiate findings from previous studies that linked E-cadherin and EGFR signalling (p. 11).

Potential Minor Revisions

1. Typographic and Grammatical Errors:
2. Typographic errors, such as “the transcriptional reporter” should be “transcriptional reporter” (p. 14, Line 20).

3. Ensure consistent use of “EGFR:STAT signalling” throughout the document (p. 12, Line 1).

4. Formatting Issues:

5. Ensure all figure legends and references are consistently formatted (Figures on pages 12-16).

6. Verify all statistical analysis descriptions, as some sections mention methods without complete context (p. 16-17).

7. AI Content Analysis:

8. The document appears to be human-authored, as the writing style and the depth of content are consistent with academic rigor. There are no substantial indicators of AI-generated content.

Recommendations

1. Enhanced Clarity:
2. Enhance clarity by adding detailed flow diagrams for the signalling pathways discussed, particularly the role of endocytic trafficking of E-cadherin and its intersection with EGFR and STAT signalling pathways.

3. Include a summary table for gene expression changes associated with E-cadherin overexpression, illustrating the overlap with STAT92EY704F and HP1 knockdown (p. 4).

4. Control Experiments:

5. Additional control experiments are essential, particularly targeting the specificity of STAT92E interactions with Heterochromatin Protein 1 (HP1) and EGFR (p. 3-4).

6. Linking to Human Context:

7. Increase the discussion of how these findings might translate to human epithelial cancers, supporting the relevance of these mechanisms with references to similar studies in mammalian cells (p. 11-12).

Conclusion

The manuscript offers valuable insights into the non-canonical roles of STAT and EGFR signalling regulated by E-cadherin endocytosis. Addressing the suggested major and minor revisions will significantly strengthen the manuscript, ensuring clarity and robustness in its scientific contributions.

On 2025-01-09 19:54:36, user J. P. Gerdt wrote:

Revised version published: https://www.nature.com/articles/s41564-024-01910-8

On 2025-01-09 09:22:25, user Dominique Sebastian Stolle wrote:

Dear community, this article was published under the title“STIC2 selectively binds ribosome-nascent chain complexes in the cotranslational sorting of Arabidopsis thylakoid proteins” ( https://doi.org/10.1038/s44318-024-00211-4) in The EMBO Journal in August 2024.

Best regards<br /> Dominique Stolle

On 2025-01-09 06:09:05, user Chun Wai Wong wrote:

This has been published in Nature Communications ( https://www.nature.com/articles/s41467-023-41737-1#citeas )

On 2025-01-08 09:30:44, user Robert King wrote:

github repos are not accessible?

On 2025-01-07 19:02:17, user Thomas Munro wrote:

This is an ingenious idea. The name azo-morphine will likely cause confusion, however, given that the scaffold used is naltrexamine. The name is already in use for azo-substituted morphine derivatives. A full semi-systematic name would be unwieldy, but could be used to derive a distinctive acronym like IBNtxA, which would make literature searches much easier.

On 2025-01-07 14:01:13, user Ryan S. Soledade wrote:

A pleasant and quick read. The inference of Lagoa Santa's environmental conditions based on the presence of a frugivorous fauna is notorious. However, it wasn't clear to me what specific features link the new specimen to the genus Artibeus. A figure on the Discussion section comparing the specimens cited would help to visualize the morphological similarities between them. In addition, a simple phylogenetic analysis would provide a quantitative basis for the assignment to Artibeus and strengthen it.

On 2025-01-07 11:09:38, user Hossein Shirali wrote:

This preprint has been peer-reviewed and published in Invertebrate Systematics. Please see the final version here: 10.1071/IS24011.

On 2025-01-06 16:53:47, user Mark Gasser wrote:

Now published at Microbiology Resource Announcements (ASM Journals) https://doi.org/10.1128/mra.00484-24

On 2025-01-06 16:51:54, user Micha Wijesingha Ahchige wrote:

The paper is now published in the Computational and Structural Biotechnology Journal:

https://doi.org/10.1016/j.csbj.2024.10.028

On 2025-01-06 16:49:33, user Mark Gasser wrote:

Now published at Journal of Microbial Biotechnology (Wiley) https://doi.org/10.1111/1751-7915.70064

On 2025-01-06 11:36:49, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> The preprint "A Bioinformatics-Driven ceRNA Network in Stomach Adenocarcinoma" presents a study that identifies and examines novel prognostic biomarkers and ceRNA regulatory networks in stomach adenocarcinoma using a sophisticated bioinformatics approach. The study integrates mRNA, miRNA, and lncRNA interactions, unveiling key pathways and contributing insights into potential biomarkers like KCNQ1OT1 linked to cancer progression. The findings are promising for advancing diagnosis and treatment, though they require experimental validation to confirm their biological relevance.

Potential Major Revisions<br /> 1. Experimental Validation:<br /> - Issue: The study is heavily reliant on computational predictions without in vitro or in vivo experimental validation.<br /> - Recommendation: Initiate experimental validation of key ceRNA interactions, particularly the KCNQ1OT1-miR-29a-3p-ELAVL3 axis, to substantiate the bioinformatics findings. Validation can be executed through techniques such as qRT-PCR, Western blotting, and functional assays in cell lines.

1. Statistical Analysis Transparency:
2. Issue: While databases like GEPIA, UALCAN, and miRNet are utilized, statistical methods are not consistently detailed.

3. Recommendation: Provide a comprehensive description of the statistical analyses, particularly regarding corrections for multiple testing (e.g., false discovery rate). This will improve the clarity and reproducibility of the results.

4. Data Accessibility:

5. Issue: Accessibility to the raw and processed data used in the analysis is not adequately ensured.
6. Recommendation: Publish direct links to the datasets and any supplementary materials. Ensure all data used in analysis such as TCGA, GTEx, and specific results like those from GEPIA, are readily accessible to ensure reproducibility.

Potential Minor Revisions<br /> 1. Typographical Errors:<br /> - Page 4: "preprintthis" should be spaced to "preprint this".<br /> - Page 17: "has-miR-29a-3p" should correctly read "hsa-miR-29a-3p".

1. Grammatical Mistakes:
2. Abstract: The phrase "The elevated expression was associated with unfavorable prognosis" would be clearer as "Its elevated expression was associated with an unfavorable prognosis."

3. Discussion: Change "This findings support" to "These findings support" to correct the grammar.

4. Formatting Issues:

5. Ensure uniformity in figure captions and references like "Figure S5" instead of mixed styles "Figure S5" and "figure S5."

6. Improve the readability of complex diagrams with annotations or legends for clarity.

7. AI Content Analysis:

8. Estimated AI-generated content: ~5%.
9. Sections such as "Introduction," "Methodology," and "Discussion" show structured and repetitive phrasing, a potential indicator of AI assistance in writing. This doesn’t compromise the substance but may affect the readability and originality.

Recommendations<br /> 1. Enhance Experimental Validation:<br /> - Conduct in vitro and in vivo experiments to validate the interactions and pathways predicted by the bioinformatics analysis. Validate key findings such as the KCNQ1OT1-miR-29a-3p-ELAVL3 axis to establish causality in stomach adenocarcinoma progression.

1. Strengthen Statistical Rigor:

2. Clarify and detail statistical analyses across the manuscript. Detail corrections applied for multiple hypotheses testing and ensure consistent methodology. This will enhance the credibility of the bioinformatics results and encourage wider acceptance.

3. Improve Data Presentation:

4. Ensure data transparency by providing direct access to databases, completing figure legends, and providing detailed methodology. Clear visual aids and methodological descriptions will improve comprehension of complex bioinformatics data.

5. Refine Writing and Formatting:

6. Address typographical and grammatical errors to enhance clarity and professionalism. Consistent formatting in figures and tables is essential for maintaining a professional presentation of the research.

Conclusion<br /> The manuscript contributes substantial and promising bioinformatics research on ceRNA networks in stomach adenocarcinoma. By implementing the suggested revisions, the authors will substantiate their claims, improve clarity, and make valuable scholarly contributions to the field.

On 2025-01-06 11:26:52, user Derrick wrote:

https://pubs.acs.org/doi/full/10.1021/acsfoodscitech.4c00281

On 2025-01-06 11:23:42, user xPeer wrote:

Courtesy review from xPeerd.com

Summary

The study analyzes bubble net feeding behaviors in the Kitimat Fjord System (KFS) in northern British Columbia using 20 years of data. Employing network-based diffusion analysis (NBDA), the authors establish strong evidence for social learning in humpback whales, highlighting rapid diffusion of both cooperative and solo bubble net feeding behaviors. The study underscores the significant role of social networks in the propagation of these behaviors and their conservation implications.

Potential Major Revisions

1. Clarification and Consistency of Hypotheses:

2. While the study makes a compelling case for both social and individual learning, the presentation of hypotheses regarding their respective contributions needs clarity. This can be achieved by clearly delineating between the influences of individual and social learning on behavior acquisition (pp. 1-3, Abstract and Introduction).

3. Enhanced Methodological Detail:

4. The methods section, although comprehensive, could benefit from more explicit descriptions of the parameters used in NBDA models. Including model validation techniques and discussing potential biases in data collection and analysis would strengthen the reproducibility of the findings. Providing additional information on model configurations, as well as the rationale behind specific methodological choices, could be helpful (pp. 8-10, Methods).

5. Integration of Homophily and Social Learning Models:

6. The current analysis acknowledges homophily but requires a more thorough exploration of its limitations and overlap with social learning models. Detailed statistical comparisons and interpretations of their interactions would improve understanding and robustness, considering the strong inherent sociality of bubble net feeding (pp. 12-13, Results).

Potential Minor Revisions

1. Typographical and Terminological Corrections:
2. Correct minor typographical errors, such as replacing "homophilic" with "homophily" (p. 11).

3. Correct terms like "Cequence" to "sequence" (p. 11).

4. Formatting Consistency:

5. Ensure that figures and tables are consistently formatted and well-integrated into the text. Adding detailed legends to explain all depicted variables would enhance clarity (e.g., Figure 2, pp. 14-15).

6. Verify consistent alignment and formatting of section headers and sub-headers according to standardized guidelines (entire document review recommended).

7. AI Content Analysis:

8. Analysis suggests a low estimated likelihood of AI-generated content, given the depth of analysis and domain-specific context. To ensure authenticity, documenting all analytical steps and contextual background in detail is recommended (general observation across document).

Recommendations

1. Ecological Implications Discussion:

2. Expand on the broader ecological implications of rapid diffusion in bubble net feeding. Discuss potential impacts on prey availability and ecosystem dynamics within the KFS. Comparative analysis with other regions and species showing similar behaviors would add significant value (pp. 15-17, Discussion).

3. Methodological Transparency Enhancement:

4. Create a supplementary section detailing the specific NBDA algorithms, models, and preprocessing steps used. Full model configurations and validation techniques should be added to facilitate replication and independent validation (pp. 8-10, Methods).

5. In-Depth Social Network Analysis:

6. Providing more detailed visualization of the social network analysis, including social network diagrams and statistical validation, would help readers understand interactions between individual whales and the spread of behaviors (pp. 10-12, Results).

7. Conservation Strategies Integration:

8. Formulate concrete recommendations for incorporating findings into long-term conservation planning. Understanding social transmission of behaviors can guide management decisions aimed at protecting humpback whale populations in the North Pacific (pp. 15-17, Discussion).

On 2025-01-06 00:23:27, user Carole LaBonne wrote:

This work should cite work from Marianne Bronner from 2002 showing that the effects of ethanol were due to programed cell death of neural crest cells <br /> https://pubmed.ncbi.nlm.nih.gov/12140368/

On 2025-01-05 16:16:24, user Joshua Flack wrote:

This article has been peer-reviewed and is now published online here: https://www.nature.com/articles/s42003-024-07201-6 .

On 2025-01-04 07:42:26, user uneventhompson wrote:

Is the raw data available for these samples? A bunch of us living R--U106 and R-Z19 men are interested in digging through the Y SNP reads to help with identifying any possible sub-clades that may exist.

On 2025-01-03 18:39:13, user Ryan wrote:

I believe this manuscript is now published in Nature Methods:<br /> https://www.nature.com/articles/s41592-023-01779-1

On 2025-01-03 13:16:34, user ASC wrote:

This manuscript is now published: https://www.tandfonline.com/doi/epdf/10.2989/10220119.2024.2428295

On 2025-01-03 10:03:03, user Andreia Wendt wrote:

The final peer-reviewed version of this article is open-accessible here: https://www.nature.com/articles/s41467-024-55538-7

On 2025-01-03 07:27:48, user Sam Danziger wrote:

This is an enormously interesting dataset.

Are you willing to also share some of the cell-type annotations for the data deposited in GEO?

Thank you,<br /> -Sam

On 2025-01-02 16:17:39, user David Pollock wrote:

Nice study. So much food for thought on a very complex system.

One aspect that is somewhat confusing to me in the paper. There are striking differences in functional effects of global KO of Bmal1 in rats versus mice. There are some places in the paper that state results are based on mice, but actually refer to rat data, and vice versa.

The SNGFR findings are somewhat puzzling. One expects the GFR to be higher during the active period when food and water consumption are the highest. This results in a greater filtered load on the nephron and so there must be a greater proportion of Na being reabsorbed at this time. This would explain why Na conserving mechanisms such as aldosterone are higher during the time of day when Na intake is highest. This would seem paradoxical, but the increased filtered load means that more absolute Na is reabsorbed while more Na is also excreted.

Of course, the balance of the various regulators of these transporters will need to be considered in the model at some point. This includes things like aldo, sympathetic nerve activity, endothelin, etc., etc. Most of these mechanisms also function in a circadian pattern.

David

On 2025-01-02 14:38:54, user Parijat Biswas wrote:

Link to the published version of this article: https://doi.org/10.7554/eLife.92719

On 2025-01-02 10:54:24, user Christian wrote:

A revised from of this manuscript was published in PNAS: https://www.pnas.org/doi/10.1073/pnas.2404738121

On 2025-01-01 19:28:27, user William DeGroat wrote:

This manuscript has been published in Genome Biology: https://doi.org/10.1186/s13059-024-03365-w

On 2024-12-31 19:17:23, user Kate Keller wrote:

This paper has now been accepted for publication:<br /> https://pubmed.ncbi.nlm.nih.gov/38809543/

On 2024-12-30 14:06:29, user Ali Reza Manzoori wrote:

Accepted version available at https://doi.org/10.1017/wtc.2024.11

On 2024-12-28 12:04:43, user WILLIAM NEWMAN wrote:

Very interesting and elegantly conducted study - note that ectopic expression of ARHGAP36 is associated with Bazex Dupre Christol syndrome in humans DOI: 10.1111/bjd.21842

On 2024-12-27 20:52:01, user 张昊天 wrote:

If your work was inspired by previous research such as ECloudGen (published in June), we respectfully request that you cite it. We have noticed potential overlap in references, particularly those discussing electron clouds as a reflection of fundamental physics. For example, both works cite:

Sebens, C. T. Electron charge density: A clue from quantum chemistry for quantum foundations. Foundations of Physics 51, 75 (2021).<br /> Leckband, D. & Israelachvili, J. Intermolecular forces in biology. Q Rev Biophys 34, 105–267, doi:10.1017/s0033583501003687 (2001).

Such overlaps suggest the influence of prior work, and it would be appropriate to acknowledge it with a citation.

On 2024-12-27 18:54:27, user ML Gaynor wrote:

This preprint was 'Just Accepted' (12/17/2024) and will be available here: <br /> https://doi.org/10.1086/734411

On 2024-12-27 03:11:02, user samuel Yi wrote:

Thank you very much for this remarkable work. While reading the article, I noticed a detail that warrants further discussion. The authors used Codex staining results from adjacent sections as the gold standard to evaluate the performance of different spatial omics technologies. However, Codex exhibited relatively strong edge staining effects in certain channels, such as CD20, which led to an abnormal accumulation of B cells at the periphery of the sections. This observation is inconsistent with the results obtained from hematoxylin and eosin (H&E) staining. Therefore, a more meticulous examination of the Codex data analysis may be necessary to address these discrepancies.

On 2024-12-26 20:12:49, user Huy Le wrote:

Now has been published in Advanced Science: https://onlinelibrary.wiley.com/share/GRXAEZQFHDVMNTTIKBN8?target=10.1002/advs.202406751

On 2024-12-26 11:37:01, user Francisco Rodriguez-Valera wrote:

Did you include in the sample the microbiome of microscopic animals (e.g. nematodes)?

On 2024-12-25 08:04:03, user phillip kyriakakis wrote:

One thing I often wonder about when people report transformation efficiencies, or do not have a very detailed protocol, is about the growth phase of the cells that are harvested to make competent cells. I often see something like "cells are grown overnight". I suspect harvesting cells in log phase would be most ideal for high transformation, but then a higher volume of cells would be needed and the time incubated in TEL+DTT buffer would likely need to be lowered/optimized. Does the age of the colony used to start the culture matter?

If authors spent time optimizing this, it would be a great resource/reference if some of these details were shared.

On 2024-12-01 12:54:07, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> The preprint titled "Ultra-Efficient Integration of Gene Libraries onto Yeast Cytosolic Plasmids" describes a novel method utilizing integrases for high-efficiency integration of gene libraries onto the yeast OrthoRep plasmid. This method facilitates continuous in vivo gene diversification and evolution, improving transformation efficiency and enabling the generation of large, diverse gene libraries. The study demonstrates this approach with mock nanobody libraries and shows promising potential for broader applications in protein engineering and yeast genetics.

Major Revisions<br /> 1. Claim Confidence and Validation:<br /> - Doubts arise around the degree to which the claimed efficiency improvements can be generalized beyond the specific experimental parameters used. While TP901 integrase is shown to be highly effective, the generalizability to other integrases and diverse organism contexts needs further empirical validation. Citations within the document should more thoroughly delineate the extent and limitations observed in different experimental setups, ensuring that readers understand both the strengths and potential constraints of the approach.<br /> - The manuscript briefly mentions (in the introduction and results sections) comparative transformation efficiencies but lacks detailed statistical analysis and discussion on potential variances across different yeast strains or growth conditions.

1. Methodological Transparency:
2. The preprint should provide more detailed step-by-step protocols, especially for the transformation and sorting processes, to improve reproducibility. Information such as specific buffer compositions, incubation times, and electroporation settings would greatly benefit other researchers attempting to replicate the findings.

3. The current data representation (e.g., Fig. S1, S2) should go beyond simple efficiency comparisons and instead include discussions on potential confounding factors or biases that could have influenced observed results.

4. Data Integration and Interpretation:

5. The interpretation of multiple integrations per cell should include discussions around the biological implications of such events and how they might influence long-term genome stability and gene expression profiles in yeast cells.
6. Consideration of any unintended off-target effects or genomic instabilities caused by high-frequency integrase activity should be examined more comprehensively.

Minor Revisions<br /> 1. Typos and Formatting Issues:<br /> - Correct minor typographical errors such as "chromitinization" which should be "chromatinization".<br /> - Maintain consistency in the citation format and ensure that all figures and tables are accurately referenced within the text.

1. AI Content Analysis:
2. It is estimated that approximately 10-15% of the text could have been influenced by AI-generated content, specifically in highly repetitive methodological details and generalized scientific language. These sections might benefit from further scrutiny to ensure precision and contextual specificity.

Recommendations<br /> 1. Empirical Validation: Conduct additional empirical studies across various yeast strains and potentially other model organisms to validate and extend the utility of the TP901 integrase-mediated integration strategy.<br /> 2. Protocol Detail Enhancement: Provide more comprehensive methodological details and standard operating procedures (SOPs) to assist in replication and application.<br /> 3. In-depth Statistical Analysis: Include detailed statistical analyses for transformation efficiency data and other quantitative results.<br /> 4. Extended Discussions: Broaden discussions on possible biological implications, off-target effects, and the broader impact on genomic stability to anticipate and address potential challenges in practical applications.<br /> 5. Enhanced Figures and Tables: Ensure that all supplemental figures and tables are adequately referenced and described in the main text to aid in data transparency and comprehension.

By addressing these recommendations, the manuscript can improve both its scientific robustness and practical utility, greatly enhancing its value to the research community interested in gene library integration and continuous evolution methodologies.

On 2024-12-25 00:21:30, user Don Gilbert wrote:

This paper has several useful points, e.g. use of plant standards in cytometry of plants, and a need to update such standards. It has a major flaw in regarding as complete the recent gapless, telomere-to-telomere (T2T) assemblies of plants, for use as genome size standards. Such assemblies are still "pseudo-molecules", that is, improving but still uncertain representations of genome contents. T2T assembly quality metrics concentrate on base-level accuracy, including those discussed, along with measures of gene completeness and others are focused on unique portions of genomes.

Measurement of genomes from whole genome shotgun DNA has different requirements from assembly of these. One requirement is unbiased, random coverage of a genome. This is a problem for assembly of duplicated spans. Duplicated genome contents are filtered and averaged to obtain gap-free T2T assemblies. These duplicated portions are measurable, from raw shotgun DNA reads, and correspond roughly to the discrepancy between assembled pseudo-molecule sizes and cytometric measures.

An important value of flow cytometry is its direct measurement of real, whole genomes. An alternate to assemblies that complements cytometry is measurement of raw DNA reads, as in my recent work [1]. This generally supports genome sizes closer to cytometric measures than to smaller assemblies, as this Table indicates.

Table G. Genome Size Estimates of long-read assemblies (Asmbl), flow cytometry (FCkew), and long-read DNA, as median megabase values of "haploid" genome content. <br /> Genome Asmbl FCkew DNA<br /> ----------------------------- arath 136 162 150 rice 392 431 406 sorghum 757 818 804 cotton 2305 2450 2492 pea 3796 4312 4141<br /> FCkew and DNA are not statistically different, while assembly values are significantly lower than both. Asmbl are those found at NCBI Genomes dated from 2020; FCkew are from http://cvalues.science.kew.org ; long-read Oxford Nanopore DNA, of these assemblies and other public data, is measured by Gnodes [1]. Species strains are those of this paper but with some ambiguity of strains.

Comparing fluorescence ratios, primary data of this paper's Table 1, for arath/rice, sorghum/r, cotton/s, and pea/cotton, to the ratios of these 3 genome estimates finds no statistical difference. The rank order of average difference has DNA (0.007) as most similar, then Asmbl (0.009), then FCkew (0.012). The DNA measured size for sorghum and arath are very close to values expected from fluorescence ratios of this paper, using an updated rice size of 406 Mb, certainly within an 18% standard error for rice genome sizes.

Discrepancies between assembly and raw DNA are often in high-identity repeat spans such as nucleolar organizing regions of many plants, and extensive transposons as for maize genomes [1]. DNA measures more in such spans than is assembled, but is in agreement with carefully measured cytometric sizes (157 Mb for A.t. model plant [2], 2600Mb to 3000Mb for maize isolines [4]). Some 7% of Arabidopsis model genome is contained in NOR spans, which need special methods to assemble [3], and are under-represented in recent assemblies. In maize, DNA measures 4,000 copies of rRNA genes but its assembly has only 400 copies, similar to human assembly [1]. These authors caution against using human and animal standards for plant flow cytometry; a similar caution exists for T2T assembly methods developed on human genomes. My experience with the Verkko assembler, an outcome of human genomics, is that it fails to fully assemble appropriate DNA of A.t. and maize plants.

My suggestion to the authors: moderate this suggested reliance on genome assemblies as new standards for cytometric sizes; add measures of DNA reads for sizes and assembly completeness. Suggest also a statistical range, or standard error, of reference sizes be applied. There is a common range of 70 Mb, or 18%, for rice genome sizes measured by cytometry, assemblies, and DNA reads.

To obtain more accurate genome size measures and assemblies, scientists should again work together to produce DNA and cytometry measures of the same bio-samples. One such example, a recent paper on many A.t. ecotype lines [6], shows genome size variation from DNA, but lacks cytomety that could validate DNA and/or assembly results. Maize isolines show close agreement of DNA and cytometry, with deficits in assemblies, but could be extended. Rice strains may be useful, as japonica and indica differ in size by DNA and FC measures.

Refs:<br /> 1. Gilbert, D.G. (2024). Measuring DNA contents of animal and plant genomes with Gnodes, the long and short of it. bioRxiv, doi: 10.1101/2024.10.06.616888

1. Bennett, MD, IJ Leitch, HJ Price and JS Johnston (2003) Comparisons with Caenorhabditis (100Mb) and Drosophila (175Mb) using flow cytometry show genome size in Arabidopsis to be 157Mb and thus 25% larger than the Arabidopsis genome initiative estimate of 125Mb. Ann. Botany, 91, 547-557 doi: 10.1093/aob/mcg057

2. Fultz, D., McKinlay A, Enganti R, Pikaard CS (2023). Sequence and epigenetic landscapes of active and silent nucleolus organizer regions in Arabidopsis. Sci. Adv. 9, eadj4509; doi: 10.1126/sciadv.adj4509

3. Bilinski P, Albert PS, Berg JJ, Birchler JA, Grote MN, Lorant A, et al. (2018) Parallel altitudinal clines reveal trends in adaptive evolution of genome size in Zea mays. PLoS Genet 14: e1007162. doi: 10.1371/journal.pgen.1007162

4. Lian, Q et al (2024). A pan-genome of 69 Arabidopsis thaliana accessions reveals a conserved genome structure throughout the global species range. Nat. Genet. 56: 982-991; doi: 10.1038/s41588-024-01715-9

On 2024-12-23 17:46:28, user Ivan wrote:

I thought you would be interested in checking out this article on flow cytometry in Galleria mellonella hemocytes (see below).

https://pubmed.ncbi.nlm.nih.gov/38357909/

On 2024-12-23 07:13:37, user James Hane wrote:

This preprint was published here: https://www.nature.com/articles/s42003-024-07327-7

On 2024-12-23 03:50:53, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> This manuscript investigates the genomic signals of local adaptation in Eleginops maclovinus from North Patagonia using an extensive seascape genomics approach. The study employed RAD-seq to genotype 11,961 SNPs from 246 individuals across 10 locations. Using population genetic differentiation (PGD) and genotype-environment association (GEA) methods, it identified 2,164 putative adaptive loci, highlighting polygenic selection driven by environmental gradients such as temperature, salinity, and oxygen.

Potential Major Revisions<br /> 1. Reproducibility Concerns: The manuscript lacks detailed information about the reproducibility of certain methods and data sets. For instance, the environmental marine database used should have its accessibility and validation methodology more explicitly discussed to ensure that other researchers can access and validate these findings.<br /> 2. Combination of Methods: While the combination of PGD and GEA is justified as reducing false positives, a statistical analysis comparing the results of each method individually with their combined results should be included. This could enhance the rigor of the claimed synergy (page 5).<br /> 3. Interpretation of Genetic Differentiation: The interpretation of high and low FST values could be further backed by more concrete demographic and ecological data examples. The current explanation could be expanded to provide clearer mechanistic insights into how these genetic differences may translate into phenotypic adaptation (page 9).

Potential Minor Revisions<br /> 1. Formatting and Typographical Errors:<br /> - "protandrous hermaphrodite" (page 4, section 1): Ensure the term and its context align correctly. The term might need a brief explanation for broader accessibility to multi-disciplinary audiences.<br /> - Typing inconsistency in "adoptive vs adaptative loci" across the manuscript needs strict unification, particularly on page 7.<br /> - Missing or misplaced punctuations: e.g., "concerntration" should be "concentration" (page 4, section 2).

1. AI Content Evaluation: The estimated likelihood of AI-generated content in this manuscript is approximately 12% based on identified patterns of wording and stylistic consistency. This is relatively low and does not currently impact the authenticity and validity of contributions. Specific checks can be made in future to ensure the methodology descriptions are manually documented comprehensively.

Recommendations<br /> 1. Additional Clarity on Adaptive Loci: More comprehensive discussion on how specific adaptive loci contribute to the organism’s traits can strengthen the manuscript. Emphasize direct links between environmental variables and physiological traits that the adaptive loci influence (section 4).<br /> 2. Data Accessibility: Provide a supplementary section with complete data sharing and code accessibility to promote transparency and reproducibility (page 4, section 3).<br /> 3. Expanded Discussion on Conservation Implications: Given the analysis’s relevance to management policies, a more detailed section dedicated to conservation recommendations based on findings is encouraged (section 4).

On 2024-12-22 21:26:23, user Michiel Pegtel wrote:

In the introduction it reads ‘ For instance, microRNAs (miRNAs) delivered by EVs can suppress the expression of target genes by binding to complementary mRNA sequences, leading to gene silencing (Valadi et al., 2007; Ong et al., j2014; Ding et al., 2015; Viñas et al., 2016).’

For accuracy, 2007 Valadi et al, a paradigm shifting paper, dit not show functional transfer of miRNAs, but association of miRNAs in their EV preps. They did show evidence for functional mRNA transfer.

On 2024-12-21 20:11:11, user Prof. T. K. Wood wrote:

1. Line 44: most notable pre-2018 anti-phage system would be the most prevalent one, toxin-antitoxin systems, discovered in 1996 to inhibit T4 phage ( https://doi.org/10.1128/jb.178.7.2044-2050.1996 ) and corroborated by many independent groups. Please cite the appropriate literature by adding this ref.

2. Line 249: there is no credible evidence for 'abortive infection'.

On 2024-12-20 19:25:26, user Misha Koksharov wrote:

I was thinking some time ago on how to grow flies better on synthetic media (with bioluminescent reporters in mind) and what could be missing: http://dx.doi.org/10.13140/RG.2.2.14541.36327/2 .

It's quite intriguing that flies grow less well on ergosterol, their major natural sterol from yeast (and often the only sterol - on sucrose/yeast food). I wonder if it could be due to different solubilities/bioavailabilities of sterols as precipitate suspensions. Maybe, this can be alleviated by using their complexes with methylated cyclodestrins or by using phosphatidylcholine/sterol (e.g. POPC/ergosterol) liposomes as a food component.

It's unclear what reagents were used (no clear Materials section with product numbers and purity). Regarding ergosterol, Thermo Fisher sells one with close to 100% purity (cat # B2384006 & AC117810050), pretty inexpesively: http://www.thermofisher.com/TFS-Assets/CCG/Alfa-Aesar/certificate/Certificate-of-Analysis/B23840-A0461475.pdf (Certificate of Analysis).

On 2024-12-19 19:19:33, user Helen Üce wrote:

This study elegantly uncovers how TRAIP and TTF2 coordinate to resolve stalled replisomes during mitosis, highlighting the intricate mechanisms cells employ to maintain genome stability. The discovery of the TRAIP-TTF2-Pol ε bridge is particularly fascinating, as it showcases the precision required to disassemble replication machinery and restore chromosome structure. Insights like these not only deepen our understanding of mitotic DNA repair but also hold significant potential for tackling genome instability-related diseases. Congrats!

On 2024-12-19 09:10:29, user Daniel Wüstner wrote:

Comment to Doktorova et al. ’Cell membranes sustain phospholipid imbalance via cholesterol asymmetry’<br /> bioRxiv doi: 10.1101/2023.07.30.551.1157

by Prof. Daniel Wüstner (University of Southern Denmark) and Prof. Fred Maxfield (Weill Medical College of Cornell University, USA).

In this manuscript, the authors reassess lipid asymmetry in model and cell membranes and focus in particular on the role of sterol asymmetry between the two membrane leaflets. For this, various tools are used including quenching of the intrinsically fluorescent sterol, dehydroergosterol (DHE), which has been applied in several previous studies for this purpose. The authors use Förster resonance energy transfer (FRET) between DHE and the lipophilic probe di-4-ANEPPDHQ added to liposomes or cells as a measure of DHE distribution between membrane leaflets. In erythrocytes, they find that 64% of the fluorescence of DHE can be quenched, which they interpret as most sterol probe residing in the outer leaflet of the plasma membrane (PM; Fig. 3). Given that these findings are in contradiction to earlier results using DHE quenching with collisional quenchers in other cell systems, they reassess potential DHE self-quenching as phenomenon giving rise to the deviating conclusions from earlier studies. For that, the titrate DHE in liposomes of varying composition and conclude from the observed non-linearity of fluorescence versus sterol concentration, that DHE self-quenches in membranes above ca. 15 mol% (Fig. S8). The authors claim that such self-quenching might have been missed in previous studies. <br /> There are the following problems with the data and the author’s conclusions in our view:

1. In the cited study on sterol asymmetry in yeast (Solanko et al. Traffic, 2018, suppl. references, 9), yeast have been loaded with varying mixtures of DHE and ergosterol, and a linear relationship between DHE concentration and fluorescence was determined. This should be correctly referred to, and claims, that potential self-quenching of DHE could complicate the interpretation of these previous studies, should be removed. In fact, Solanko et al. did assess this aspect in intact yeast, where the entire sterol pool can be replaced with ergosterol/DHE at various rations, and no evidence for self-quenching was found.
2. The claimed ‘strong self-quenching of DHE’ is not apparent in the manuscript, nor is it evident from the cited study, Schroeder et al. 1987, ref. 17 in supplementals. While the authors report some deviation from linearity in Fig. S8A, the observed effect is far from being strong self-quenching. Also, Schroeder et al. report only a slight reduction in fluorescence quantum yield (QY) of DHE above 5 mol%, while they find surprisingly a large drop in DHE’s fluorescence above ca. 30 mol% (Fig. 2A). Other studies (Loura and Prieto, Biophys. J. 1997, Garvik et al. Chem. Phys. Lipids 2009, Pourmousa et al. J. Phys. Chem 2014) could not reconcile this and did not find evidence of significant self-quenching of DHE’s fluorescence intensity in membranes.
3. Combined spectroscopic and computational studies of DHE’s self-aggregation in aqueous solution revealed that DHE in micelles/aggregates shows only weak excitonic coupling resulting in slight fluorescence reduction in dimers oriented in parallel(Reinholdt et al. J. Phys. Chem. 2021). Fluorescence of DHE in aggregates was lower than the intensity in the corresponding number of monomers but aggregates were still very bright, which is in line with earlier studies by Loura and Prieto. Thus, even in aggregates, DHE’s fluorescence is not strongly quenched.
4. TNBS can be used to chemically modify molecules, but also as side-specific collisional quenchers when employed as sodium salt. This was shown among others in Solanko et al., and the work should be properly cited in that context. Assessment of side specific quenching in the PM of mammalian cells was done from both sides, i.e., also by injecting the quencher into cells in the study by Mondal and Maxfield. This control should have been added in the current study as well.
5. The claim, that quenching by FRET allows for assessing transbilayer sterol distribution should be substantiated by measuring the Förster radius between both fluorophores. If that radius is larger than 2.5 nm, it is likely that also DHE in the inner leaflet gets lowered in its intensity. In that case, the assumption of side-specificity would not be valid. Also, in contrast to contact quenching by collisions, FRET depends on the mutual orientations of the transition dipoles. Thus, more thorough characterization of the potential FRET system is essential for supporting the claims of the study. An important experiment would also be to inject the FRET acceptor lipid probe into the cells and validate the lower quenching on the inner PM leaflet. Such experiments have been done with TNBS by Mondal and Maxfield (see ref.8 in the Supplementals).

On 2024-12-18 18:47:29, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> The manuscript introduces “semantic mining,” leveraging a 7-billion parameter genomic language model (Evo 1.5) to generate de novo functional proteins guided by genomic context. Applications include toxin-antitoxin systems and anti-CRISPR proteins, with experimental validation demonstrating significant activity. The introduction of SynGenome, an AI-generated database of 120 billion synthetic DNA base pairs, expands accessibility to sequence exploration. While the methodology is innovative, the work requires greater clarity in data validation, reproducibility, and assessment of model biases.

Major Revisions<br /> Validation of Novelty and Utility:

Page 3–6: While Evo-generated proteins are novel, the manuscript lacks detailed benchmarking against state-of-the-art generative tools like ESMFold or AlphaFold for function-guided design. Comparing success rates and biological plausibility of sequences generated by Evo vs. other models would validate its unique contributions.<br /> Recommendation: Include a comparative analysis using publicly available benchmarks or direct competition against contemporary tools.<br /> Model Limitations and Bias:

Page 10–11: The manuscript notes the autoregressive sampling approach's propensity for repetitive or non-functional sequences but does not quantify failure rates. A robust statistical analysis of failures versus successes would strengthen confidence in Evo's predictions.<br /> Recommendation: Provide an error rate analysis for generated sequences, specifying how often Evo outputs unusable or irrelevant results.<br /> Experimental Validation Scope:

Pages 7–8: While experimental validations (e.g., toxin-antitoxin assays) are presented, the sample size of 10–15 per class may not generalize to broader applications.<br /> Recommendation: Increase experimental validations, particularly for diverse protein classes, or clarify why the existing sample size is statistically sufficient.<br /> Ethical Considerations of AI in Genomics:

Page 12–13: The paper touches on the novelty of AI-designed proteins but does not address the ethical implications of releasing 120 billion synthetic sequences, especially regarding misuse.<br /> Recommendation: Include a section discussing potential misuse (e.g., biosecurity risks) and measures to mitigate ethical concerns.<br /> Scalability and Practical Deployment:

Pages 8–10: SynGenome’s database is comprehensive but lacks a discussion on computational resources required for its generation and queries.<br /> Recommendation: Add a performance benchmarking section detailing the hardware and time required for large-scale queries and data generation.<br /> Minor Revisions<br /> Formatting and Presentation:

Figures 3D–G (Page 8): Improve resolution and annotation clarity. Figures lack consistent labeling for protein sequence lengths and functional annotations.<br /> Headings (Throughout): Ensure consistent capitalization for section titles.<br /> AI Content Evaluation:

Estimated AI Contribution: 20–25%.<br /> Identified Sections: Abstract, Methods (Page 13–15), and descriptive portions of Results show repetitive phrasing indicative of AI generation.<br /> Impact: Low epistemic risk as AI-assisted text remains aligned with scientific integrity but lacks nuanced argumentation.<br /> Recommendation: Revise abstract and descriptive content to improve readability and originality.<br /> Methods Reproducibility:

Pages 14–16: The methods section requires clearer step-by-step reproducibility guidelines for Evo training and sampling, including parameter settings and failure case management.<br /> Recommendation: Add a concise reproducibility checklist summarizing critical steps and dependencies.<br /> Recommendations<br /> Enhance comparative benchmarking to validate Evo’s claims of novelty and efficiency.<br /> Provide expanded experimental validation, ensuring sufficient generalizability across diverse protein functions.<br /> Address ethical concerns about AI-generated sequences to preempt potential misuse and establish guidelines for responsible use.<br /> Refine text clarity in AI-generated sections and enhance the formatting of figures for better readability.<br /> Strengthen reproducibility guidelines, particularly for model training and sequence generation, to facilitate adoption by other researchers.

On 2024-12-18 18:17:32, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> The manuscript presents a novel method for producing bioactive peptides (BAPs) in E. coli by encapsulating them within bacteriophage P22 virus-like particles (VLPs). This approach addresses challenges such as host toxicity and proteolytic degradation, enabling biosynthetic production of BAPs that are typically difficult to express. Using this system, the authors successfully produced peptides from three structurally distinct classes and established a downstream processing pipeline for purification. While the study demonstrates a significant advance, it would benefit from more comprehensive validation of scalability and broader applicability.

Major Revisions<br /> Validation of Therapeutic Applications:

The manuscript effectively highlights the potential of the P22 VLP system for producing BAPs, but it lacks robust in vivo or functional validation of these peptides' therapeutic efficacy. For instance, demonstrating antimicrobial or anticancer activities of purified BAPs would strengthen the findings (e.g., Sections 5–7).<br /> Scalability Considerations:

The scalability of the encapsulation and purification process is not adequately addressed. The downstream processing pipeline, while efficient for lab-scale production, may face challenges at industrial scales. Providing pilot data on larger-scale production would be valuable (e.g., Section 8).<br /> Charge Dependency Discussion:

The strong correlation between peptide charge and encapsulation efficiency is noted but not fully explored in the context of broader peptide libraries. A discussion of whether these findings are generalizable to other cationic peptides or specific to the tested classes is needed (e.g., Section 12).<br /> Impact of Toxicity on Host Viability:

While the study mentions host protection through encapsulation, more data on host cell viability under varying peptide expression levels would provide clearer insights into system robustness (e.g., Figures 3–4).<br /> Reproducibility and Transparency:

Include more details on the variability of yields across replicates. For example, reporting standard deviations or confidence intervals for the recombinant yield of encapsulated peptides would enhance data robustness (e.g., Section 13).<br /> Minor Revisions<br /> Formatting and Clarity:

Fix formatting inconsistencies, such as overlapping figure captions and tables, particularly in Figures 2 and 5.<br /> Ensure uniformity in the use of units (e.g., mg/L consistently across text and figures).<br /> Figures and Data Presentation:

Improve the resolution and annotation of figures. For example, the TEM images lack clear scale bar descriptions, and data on cargo loading could benefit from a graphical summary.<br /> AI Content Estimate:

Estimated AI-generated content: ~10-15%, identified mainly in repetitive or formulaic phrasing in sections like the introduction and methods.<br /> Highlighted sections include: Abstract, Sections 2–3, and Methods.<br /> Impact: Low epistemic risk but would benefit from manual stylistic revisions for improved readability.<br /> Referencing and Citations:

Ensure all references are formatted consistently, particularly in-text citations that occasionally deviate from standard formats.<br /> Recommendations<br /> Add experimental data on the bioactivity of purified peptides to strengthen claims of therapeutic potential.<br /> Provide a comparative analysis of yield and cost-efficiency relative to chemical synthesis to highlight economic and environmental benefits.<br /> Expand the discussion on scalability and potential integration into industrial workflows.<br /> Conduct additional studies on encapsulation efficiency with a broader range of peptides to confirm system generalizability.<br /> Enhance figure annotations and standardize formatting for improved readability.

On 2024-12-18 17:12:24, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> This manuscript investigates oxaliplatin resistance in colorectal cancer (CRC), identifying the SERPINE1-based RESIST-M gene signature as a predictive marker for pro-metastatic CMS4/iCMS3-fibrotic CRC subtypes. Employing transcriptomics, in vitro/in vivo experiments, and bioinformatics, the study proposes therapeutic strategies targeting cholesterol biogenesis and SERPINE1 to re-sensitize CRC cells to oxaliplatin. The work is well-structured but needs refinement in statistical models, transparency, and clarity.

Major Revisions<br /> 1. Statistical Models and Reproducibility<br /> Page 6, Lines 95–120: Statistical details for in vivo studies (e.g., metastatic score calculation) are insufficient. Include effect sizes, confidence intervals, and corrections for multiple comparisons.<br /> Recommendation: Present Kaplan-Meier survival curves with hazard ratios (HR) and p-values for different gene signatures (e.g., RESIST-M) in relevant datasets (PETACC-3, TCGA).<br /> Page 11, Line 210: The statistical pipeline for GSEA and pseudotime analyses lacks critical thresholds. Specify adjusted p-values (e.g., FDR-corrected) for hallmark pathways.<br /> 2. Validation of the RESIST-M Signature<br /> Page 14, Lines 275–285: The study compares RESIST-M to other gene signatures but lacks comprehensive head-to-head validation using robust statistical tests.<br /> Recommendation: Provide ROC-AUC scores to quantify predictive accuracy across datasets. Supplement with external validation using independent clinical cohorts.<br /> 3. Mechanistic Insights<br /> Page 8, Lines 150–170: The link between cholesterol biosynthesis, lipid raft dynamics, and TGF-β signaling is compelling but speculative.<br /> Recommendation: Enhance mechanistic validation by including experiments showing cholesterol restoration effects on TGFBRII localization and signaling attenuation.<br /> Page 13, Line 245: Include co-immunoprecipitation or fluorescence resonance energy transfer (FRET) assays to demonstrate direct interactions between SERPINE1, SMAD2/3, and lipid raft components.<br /> 4. Ethical Concerns in In Vivo Studies<br /> Page 23, Lines 495–525: Randomization protocols and blinding measures are not adequately detailed.<br /> Recommendation: Ensure transparency by specifying whether investigators were blinded to treatment arms during tumor and metastasis scoring.<br /> 5. Clinical Utility of SERPINE1 Inhibition<br /> Page 10, Lines 180–200: The therapeutic viability of tiplaxtinin and simvastatin is discussed but lacks detailed pharmacokinetic or toxicity evaluations.<br /> Recommendation: Include dose-response curves and combinatorial therapy data to support clinical translation.<br /> Minor Revisions<br /> 1. Language and Formatting<br /> Page 3, Abstract: Simplify dense phrasing like "RESIST-M signature derived from our models showed that the models can mimic CMS-4/iCMS-fibrotic-like metastatic CRC patients."<br /> Ensure consistent nomenclature for gene/protein names (e.g., "SERPINE1" vs. "PAI-1").<br /> Improve figure legends with more descriptive captions (e.g., axes labels in Figures 4 and 5).<br /> 2. Figure Clarity<br /> Figures 1–6: Use consistent color schemes to distinguish CMS subtypes across datasets. Add error bars to all bar plots and specify statistical tests in figure legends.<br /> 3. Data Accessibility<br /> Page 27, Lines 595–605: Make raw and processed data from in-house RNA-seq experiments publicly available. Provide repository links and accession codes.<br /> AI-Generated Content Analysis<br /> Indicators:

Stylistic Repetition: Frequent repetition of phrases like "RESIST-M signature predicts poor prognosis" and "CMS4/iCMS3-fibrotic subtypes" suggests templated assembly.<br /> Simplistic Explanations: Complex mechanisms (e.g., lipid raft dynamics) are summarized without technical depth, consistent with AI-generated sections.<br /> Sentence Structure: Overuse of passive voice in mechanistic descriptions.<br /> Estimate: 10–15% AI-generated content, primarily in introductory and discussion sections.

Impact:

Minimal: Core scientific claims are data-driven and original.<br /> Recommendations:

Reassess and refine introductory sections to ensure technical accuracy and eliminate redundancy.<br /> Provide nuanced discussions of limitations in the final paragraphs.<br /> Recommendations<br /> Statistical Rigor: Refine statistical models, especially for pathway enrichment and survival analyses.<br /> Mechanistic Validation: Conduct additional experiments to confirm hypothesized pathways.<br /> Data Transparency: Enhance reproducibility by releasing data/code under FAIR principles.<br /> Therapeutic Context: Expand discussion on potential side effects and combinatorial strategies for proposed therapies.

On 2024-12-18 17:08:51, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> The manuscript explores functional connectivity (FC) changes associated with rapid remission from treatment-resistant major depressive disorder (MDD) using Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT). It presents compelling evidence of FC reductions between key brain regions involved in emotion regulation and correlates these changes with clinical improvement. While the results are promising, the manuscript requires revisions for enhanced clarity, rigor, and generalizability.

Major Revisions<br /> Clinical Trial Design and Transparency:

Page 13, Lines 4-18: The open-label design raises concerns about placebo effects and biases. Incorporate a discussion on these limitations and emphasize the ongoing sham-controlled trials as critical next steps.<br /> Recommendation: Clearly articulate (a) participant inclusion criteria (e.g., baseline severity threshold) and (b) statistical rationale for the sample size. Include a CONSORT-style flow diagram for improved transparency.<br /> Interpretation of Functional Connectivity Results:

Page 10, Lines 12-20: The claim that DMN hyper-connectivity underpins MDD remission warrants caution. Highlight alternative interpretations (e.g., compensatory mechanisms) and the variability in individual FC changes.<br /> Recommendation: Contextualize findings with respect to the heterogeneity of depression subtypes and potential outliers in FC changes. Include additional statistical metrics (e.g., effect size for FC changes across participants).<br /> Mechanistic Insights:

Page 8, Lines 7-15: The manuscript lacks direct mechanistic evidence linking SAINT-induced FC changes to emotion regulation improvements. For example, the role of sgACC-DMN decoupling remains speculative.<br /> Recommendation: Discuss whether other circuits, such as hippocampus-related networks, might play a role. Acknowledge gaps in mechanistic understanding due to limited resolution of imaging data.<br /> Ethics and Intellectual Property Disclosure:

Page 2, Footnote: The intellectual property disclosures (methodology patents) should be expanded. Clarify how this might influence interpretation or replication of findings.<br /> Recommendation: Include a conflict-of-interest statement aligned with journal ethics.<br /> Minor Revisions<br /> Language Precision:

Page 3, Abstract: Avoid overgeneralized claims such as "provides a significantly clearer picture." Rephrase to reflect study-specific findings.<br /> Throughout: Replace speculative terms (e.g., "may reflect") with precise qualifiers ("likely reflects based on X evidence").<br /> Figures and Tables:

Figures 1-3: Enhance figure legends to explain axes and statistical thresholds. Add asterisks or annotations to highlight significant FC changes.<br /> Page 6, Line 30: Provide a visual representation of clinical score improvements (e.g., histogram or boxplot for MADRS reductions).<br /> Data Accessibility:

Page 12, Data Analysis: Include a link to de-identified datasets and code used for FC analysis to support reproducibility. Explicitly state if there are restrictions.<br /> Formatting and Style:

Standardize abbreviation usage (e.g., "lDLPFC" inconsistently capitalized).<br /> Ensure all references conform to journal guidelines (e.g., consistent DOI inclusion).<br /> Recommendations<br /> Expand Clinical Impact: Discuss how SAINT might complement existing treatments, particularly in comparison to electroconvulsive therapy and ketamine-based interventions.<br /> Address Generalizability: Highlight limitations in applying SAINT to diverse populations, given the small and homogeneous sample.<br /> Provide Supplementary Details: Include a supplementary table summarizing prior studies on FC changes in MDD for comparative context.

On 2024-12-18 00:44:40, user Lydia Bilinsky wrote:

I’d love to get feedback on whether SFq(D) is invariant with regard to conditions in irradiated cell culture.

On 2024-12-17 23:21:22, user Pedro Ballester wrote:

This issue is not new. It has been studied before in terms of protein sequence similarity:<br /> https://pubs.acs.org/doi/10.1021/ci100264e <br /> https://pubs.acs.org/doi/10.1021/ci200057e

And more recently in terms of protein structure and ligand structure similarity as well:<br /> https://www.mdpi.com/2218-273X/8/1/12

GEMS seems interesting though, thanks for releasing the code, we will try it.

On 2024-12-17 14:36:39, user Susanne Lachmuth wrote:

A peer-reviewed version of this article has now been published here: https://doi.org/10.1002/ecm.1593

On 2024-12-17 12:10:33, user Luc Bussiere wrote:

Note this is now published, and needs a link to the published article: https://academic.oup.com/evolut/article/74/8/1741/6850800