On 2025-03-11 16:46:46, user Nikhil Thomas wrote:
This manuscript has been published in PLoS Genetics at the following link:<br /> https://doi.org/10.1371/journal.pgen.1011370
On 2025-03-11 16:46:46, user Nikhil Thomas wrote:
This manuscript has been published in PLoS Genetics at the following link:<br /> https://doi.org/10.1371/journal.pgen.1011370
On 2025-03-11 05:53:34, user John Golz wrote:
This manuscript has now been published and a link to the publication could now be included.
https://doi.org/10.1186/s12896-024-00864-3
Thanks
On 2025-03-10 04:21:18, user Young Cho wrote:
Dear Authors,<br /> Thank you for sharing your insightful work, "In Silico Engineering of Stable siRNA Lipid Nanoparticles: Exploring the Impact of Ionizable Lipid Concentrations for Enhanced Formulation Stability." Your study makes an important contribution to the field of lipid nanoparticle (LNP) research by highlighting the role of ionizable lipid concentrations in siRNA encapsulation and stability. The use of coarse-grained molecular dynamics (MD) simulations and steered molecular dynamics (SMD) provides a detailed molecular-level understanding of LNP formation, which is particularly valuable for optimizing RNA-based drug delivery systems.<br /> Summary<br /> This study examines how neutral and positive ionizable lipids influence LNP stability and siRNA encapsulation efficiency. The findings indicate that LNPs with positive ionizable lipids encapsulate siRNA more effectively than those with neutral lipids, likely due to their integration with phospholipids and the prevention of siRNA escape. Interestingly, low and medium concentrations of both neutral and positive DLKC2 showed better compartment formation and encapsulation efficiency compared to high concentrations. Additionally, neutral lipids exhibited greater aggregation, which could impact LNP stability.<br /> Introduction<br /> Your introduction effectively establishes the relevance of this study by situating it within the broader context of LNP research. The discussion of existing challenges in siRNA delivery and the role of lipid composition is well-articulated. However, further elaboration on how your study builds upon previous experimental findings could help connect computational insights with practical applications.<br /> Results<br /> The figures and data presentation generally support your conclusions. Figure 4, which illustrates LNP compartment formation at different lipid concentrations, is particularly valuable in showing how high concentrations lead to instability. We do think that some quantitative metrics such as bilayer thickness, lipid density, or compartment size would enhance the strength of these findings. Additionally, since water is omitted from the visualizations for clarity, we think it would be beneficial to include a figure that shows water so we can visualize the hydration effects and lipid-water interactions.<br /> Discussion<br /> Your discussion effectively compares findings with prior studies, reinforcing that positive ionizable lipids enhance siRNA encapsulation and that lipid aggregation in neutral systems may reduce stability. While you mention previous molecular dynamics studies (e.g., Paloncýová et al. and Trollmann & Böckmann), we feel a more direct comparison of numerical data and trends from these works would further contextualize your results. Additionally, discussing potential experimental validation techniques (e.g., cryogenic electron microscopy or encapsulation efficiency assays) could provide future directions for integrating simulations with laboratory-based studies. However, that is just our opinion as we do understand that this study takes on a more computational approach and is still very impactful.<br /> Suggestions for Improvement<br /> 1. Expand quantitative analysis in Figure 4 by including measurements of bilayer thickness, lipid density, and compartment size to provide a more rigorous validation of LNP stability.<br /> 2. Clarify the role of hydration in lipid-water interactions since water was omitted in visualizations.<br /> 3. Strengthen comparisons with previous molecular dynamics and experimental studies by integrating direct numerical contrasts.<br /> 4. Discuss potential experimental validation approaches that could complement your computational findings and enhance their real-world applicability.<br /> Final Thoughts<br /> Overall, this paper presents a well-structured and valuable contribution to siRNA delivery research. With minor refinements in quantitative analysis, literature comparisons, and discussion of experimental validation, the study could be even more impactful. Thank you for your efforts in advancing the field of LNP-based RNA therapeutics!<br /> Best regards,<br /> UHM MBBE 602 Graduate Students
On 2025-03-10 04:17:10, user Young Cho wrote:
Summary:<br /> This study provides a comprehensive analysis of miRNA profiles in Culex tarsalis, identifying 86 known miRNAs and 20 novel miRNAs, is a significant contribution to the field of insect molecular biology and vector research. This works sets the foundation for future studies on gene regulation and host-pathogen interactions in Cx. tarsalis, a major vector of West Nile Virus (WNV). While the methodology is robust and the findings are compelling, the paper would benefit from some minor revisions to strengthen data presentation, clarify experimental choices, and align its conclusions more closely with the results. <br /> Introduction: <br /> The introduction frames the importance of miRNA research in Cx. tarsalis well, particularly in the context of understanding its role as a vector for WNV. However, the title of the paper may be misleading since the findings do not directly link the identified miRNAs to WNV vectoring. Reframing the title and introduction to focus on the broader importance of miRNA characterization in Cx. tarsal without overemphasizing the WNV connection would improve clarity and prevent misalignment between the study’s scope and its claims. <br /> Results: <br /> The results section presents a comprehensive dataset of miRNAs identified through computational comparison with other mosquito species and validated using RT-qPCR. The discovery of novel miRNAs and the observed isomiR variations are particularly noteworthy, with the predominance of 3’ end insertions being a finding of potential significance in gene regulation. That said, clearer justification for the selection of the 10 miRNAs validated by qPCR would strengthen the interpretability of the results. <br /> Discussion: <br /> The discussion effectively places the study’s findings within the broader context of existing research on mosquito miRNAs and draws meaningful comparisons with other species like Aedes albopictus and Cx. quinquefasciatus. The evolutionary conservation of miR-184 and the identification of unique miRNAs in Cx. tarsalis offer valuable insights. However, the paper would benefit from further discussion on the functional implications of these miRNAs, particularly their potential roles in development, immunity, and host-pathogen interactions. Additionally, the observed differences in miRNA expression between cell lines and whole organisms raise important questions that warrant more exploration. <br /> Suggestions: <br /> 1. Revise the title to better reflect the study’s current findings and avoid overemphasizing WNV. <br /> 2. Clarify the rationale behind the selection of the 10 miRNAs for qPCR validation. <br /> 3. Expand the discussion on the functional roles of the identified miRNAs and their potential involvement in host-pathogen interactions. <br /> 4. Address the limitations more explicitly, such as the reliance on a single genome assembly, the lack of data from different mosquito life stages and tissues, and the absence of additional validation methods like Northern blot. <br /> 5. Consider including a statistical analysis to highlight differences in miRNA expression between cell lines and whole organisms. <br /> 6. Discuss the potential influence of feeding behavior on gene expression and its relevance to vector competence.
On 2025-03-07 18:39:57, user Randall Eck wrote:
Exciting article! Given the role of 3' UTR alternative polyadenylation (APA) in RNA localization and stability (PMC9261900) and the role of TDP-43 in regulating 3' UTR APA (PMC10849503), is there a relationship between TDP-43 regulation of RNA localization and 3' UTR APA in your data?
On 2025-03-07 12:28:58, user Marc RobinsonRechavi wrote:
Under Data Accessibility, the authors write:
Data and R code sufficient to replicate all analyses will be made publicly available upon acceptance of this manuscript for publication.
This is a publication, i.e. it is made public as part of the scientific record and is citable, thus I strongly invite the authors to make the corresponding data and code available without delay.
On 2025-03-07 07:27:12, user Marc RobinsonRechavi wrote:
Under Code Sharing Plan, the authors write:
All the code used for the generation of datasets and subsequent analysis will be made publicly available in<br /> a GitHub repository upon publication
This is a publication, i.e. it is made public as part of the scientific record and is citable, thus I strongly invite the authors to make the corresponding code available without delay.
On 2025-03-06 09:47:18, user Alexei Korennykh wrote:
As a corresponding author, Alexei Korennykh hereby documents the timeline of our discovery of Nocturnin NADP(H) phosphatase activity.
[2018, December 17]<br /> Our Manuscript "The Metabolites NADP+ and NADPH are the Targets of Circadian Protein Nocturnin (Curled)" was submitted to a high-quality journal (per BioRxiv policy journal name cannot be mentioned here) (under id ....2018-12-17736A)
[2018, December 19]<br /> The editor sends the work to referees.
[2018, December 21]<br /> We submit our Nocturnin-NADP co-crystal structure to the PDB database and obtain PDB ID 6NF0.
https://www.rcsb.org/structure/6NF0 has the following permanent record:
Deposited: 2018-12-18 <br /> Released: 2019-05-01 <br /> Deposition Author(s): Estrella, M.A., Du, J., Korennykh, A.
[2019, January 15]<br /> Journal rejects the manuscript, based substantially on negative remarks of Ref#3, who is “an expert on Nocturnin”:
Referee expertise:
Although we responded that all concerns can be addressed directly and without experiments, the journal is not willing to re-consider our work.
[2019, January 30]<br /> We posted our manuscript here, to BioRxiv and it became available to the public.
[2019, March 28] <br /> We submitted the paper to the final publishing journal (see top of the page, "Now published in ") and the paper was received and sent for review.
[2019, April 18] <br /> The paper was accepted (see top of the page, "Now published in ").
[2019, May 30] <br /> The paper was published (see top of the page, "Now published in ").
[2019, June 5] <br /> Alexei Korennykh wrote to change Uniprot annotation of Nocturnin
Wed Jun 05 05:20:37 2019, akorenny@princeton.edu wrote:
Major changes in NOCT (CCRN4L) gene function and description. <br /> Source:<br /> https://www.nature.com/articles/s41467-019-10125-z <br /> Suggested revisions:
"Circadian deadenylase"<br /> changes to<br /> "Circadian NADP(H) phosphatase"
"Catalytic activity: Exonucleolytic cleavage of poly(A) to 5'-AMP. EC:3.1.13.4"<br /> changes to:<br /> "Catalytic activity: 2'-Phosphate removal from NADP+ and NADPH. EC:to be created"
[2019, June 7] <br /> UniProt Begins re-annotation<br /> Dear Alexei,
Thank you for having submitted a request for the update of a UniProtKB entry.
Your request has already been sent to an annotator and will be handled with<br /> high priority.
We will send you an e-mail when the update is completed.
Best regards
SP
[2019, July 1] <br /> UniProt changes Deadenylase to Phosphatase for Nocturnin:
Dear Alexei,
Thank you for passing on the details of your recent paper. The nocturnin <br /> entry has been updated and will be available as part of UniProt release <br /> 2019_08 on 18th September. In the meantime, I have included the entry <br /> below in text format. Please feel free to get back in touch if you have <br /> any comments about the content.
Kind regards,<br /> MM
ID NOCT_HUMAN Reviewed; 431 AA.<br /> AC Q9UK39; D3DNY5; Q14D51; Q9HD93; Q9HD94; Q9HD95;<br /> DT 02-NOV-2001, integrated into UniProtKB/Swiss-Prot.<br /> DT 04-NOV-2008, sequence version 2.<br /> DT 31-JUL-2019, entry version 148.<br /> ……<br /> CC NAD(+) and of NADPH to NADH (PubMed:31147539). Shows a small<br /> CC preference for NADPH over NADP(+) (PubMed:31147539). Represses<br /> CC translation and promotes degradation of target mRNA molecules<br /> CC (PubMed:29860338
…
[2019, July 1]
Up to this date (i.e. 5 months since our BioArxive paper became publically available) no work by others, which described Nocturnin as NADP(H) phosphatase was published or submitted to any journal, to the best of our knowledge.
On 2025-03-06 02:33:06, user Charles Warden wrote:
Thank you very much for posting this preprint!
The "Code availability" section indicates "We provide supplementary files containing an R script with functions to run our CRF-based correction procedure as well as a tutorial notebook illustrating how to run it.".
However, I think I see anything uploaded as supplemental files. Am I overlooking anything, or does the supplemental code need to be added in a revision?
Thank you very much!
Sincerely,<br /> Charles
On 2025-03-06 00:00:06, user Laura Lackner wrote:
An updated version of this preprint has been published in MBoC - https://doi.org/10.1091/mbc.E23-05-0168 . The revised and accepted version has a slight modification to the title.
On 2025-03-05 19:55:42, user Enrico Radaelli wrote:
In this viral video on YouTube<br /> https://www.youtube.com/watch?v=WNuzopVDFQs <br /> The company claims that "There were no unintended consequences except adorability".<br /> However, the mice are clearly pruritic and they exhibit crusty/flaky skin in glabrous areas (especially paws and eyelids).<br /> I wonder if this is part of the phenotype or if the mice contracted infections that might have caused these lesions (mites, C. bovis, etc.).
On 2025-03-04 21:05:38, user Simone Picelli wrote:
Hi, I think there is a mistake in the name of the company used to make the modified TSO. It's not Biosyn Corporation ( http://biosyncorp.com ), as you wrote, but rather Bio-Synthesis ( http://biosyn.com ). <br /> Moreover, in the TSO sequence: "/5Biosg/" is the acronym used by IDT for a 5' biotin. The "g" has nothing to do with deoxyguanosine (G), but you write in the paper "5BiosG/" and this can be confusing. The standard 10x TSO sequence is, in fact: 5’-AAGCAGTGGTATCAACGCAGAGTACATrGrGrG-3’<br /> so no G at the 5' (like there was never a G at the 5' of the SMART-seq oligo, from which 10x took their sequence).<br /> The code for biotin at Biosyn is [Btn] (standard C6 spacer, which I assume is the one you mean here).
On 2025-03-04 02:21:17, user Nelly Olova wrote:
This work has now been published in the Methods in Molecular Biology book series, volume 2866 (Springer Nature)
On 2025-03-03 17:25:34, user Johannes Daniel Scharwies wrote:
This is the author's version of the work. It is posted here by AAAS for personal use, not for redistribution. The definitive version was published in Science on 6 Feb 2025, DOI: 10.1126/science.ads5999.
On 2025-03-03 16:11:50, user hansdb wrote:
One Corded Ware (CGG107476) and two Bell Beaker individuals (CGG106805 and CGG106737) from your interesting study belong to Y-DNA haplogroup I2-L38 (aka I2a1b2a).<br /> As decribed in my citizen scientist paper ( https://www.academia.edu/115363574/RECONSTRUCTING_THE_JOURNEY_OF_Y_DNA_HAPLOGROUP_I2_S2555_TO_I2_L38_Tracing_Genetic_Footprints_Across_Time_and_Space ) this haplogroup was also related to:<br /> * an EBA Unetice sample from Germany (I0114)<br /> * an EBA Unetice sample from Bohemia (I7959)<br /> * an IA Hallstatt sample from Germany (MBG008)<br /> * an IA La Tène sample from Bohemia (I17327)<br /> * an IA La Tène sample from France: GLN32
Most interestly this haplogroup also occured among the Urnfield epoch Lichtenstein clan from Osterode-am-Harz. Since it is mentioned (paragrapghs 194 to 196) that very few genomes from the Urnfield Culture exist (as a result of the cremation practice) it would be interesting if the well-preserved samples of the Lichtenstein cave could be integrated in your study.
On 2025-03-03 14:46:23, user Elisa Rosati wrote:
A couple of questions:<br /> 1) How can you be sure that the MAIT cells you observed are not bystander activated during the T cell stimulation and thus not really Myelin-specific? I would perhaps perform the experiments with two additional setups:<br /> a) MHC-blockage (If MAIT cells are really specific they should appear here) <br /> b) MR1-blockage (if MAIT cells are specific and activated via TCR they should not appear here)
2) Have you tried to perform the analyses separately for HLA-DRB1*15:01 positive and negative individuals separately? It was shown by a study from Adaptive Biotechnology that a limited number of TCR clusters enriched in MS exist and that these clusters are mostly CD4 and very different in DRB1*15:01 positive and negative individuals.
On 2025-03-01 00:59:54, user Tim wrote:
While groundbreaking, I wish this paper expanded up author N.R.B.’s de novo inclusion of huel in the fine tuning of the RFDiffusion network compared to the characterization of fermented yeast to acetaldehyde formation chain on massive (1 million samples or more) scales.
On 2025-02-28 12:53:50, user Prof. T. K. Wood wrote:
l 339: Paris is a toxin/antitoxin system and TAs are the most-prevalent phage inhibition system; this should be noted.
l 365: The seminal identification of of TAs and phage inhibition (1996) should cited:<br /> doi: 10.1128/jb.178.7.2044-2050.1996
On 2025-02-28 10:05:42, user Giampaolo Minetti wrote:
This preprint has now been published as a peer reviewed, open access article in Cell Death Discovery:<br /> Minetti G, Dorn I, Köfeler H, Perotti C, Kaestner L. Insights from lipidomics into the terminal maturation of circulating human reticulocytes. Cell Death Discov. 11, 79 (2025). doi: /10.1038/s41420-025-02318-x<br /> Stable, shortened URL:<br /> https://rdcu.be/ebvgH
On 2025-02-28 08:34:44, user Bjarke Jensen wrote:
Dear authors,
Congratulations with this interesting study.
In my view it would be helpful if you further develop the descriptions of the state of trabeculation. For example, did you make measurements (counting, thicknesses, proportions) of the trabecular and compact layer, what were the values and how do they relate to diagnostic criteria associated with trabeculation? It would also be helpful if you support this part of your Results with clinical imaging (echocardiography and CMR) onto which is shown the measurements (or overt phenotype) that led to the interpretation of 'hypertrabeculation'. I for one would not mind a full text figure dedicated to this part. <br /> Part of the reason for giving these suggestions is of course that your title states 'hypertrabeculation' while the associated phenotyping is proportionally very small and accordingly a bit unclear.
Best wishes and good luck with the publication.
Bjarke
On 2025-02-27 02:16:06, user Le Zhen wrote:
Now this manuscript has been accepted for publication in the journal Biomaterials, with a new title: Synthetic Vascular Graft That Heals and Regenerates (doi: https://doi.org/10.1016/j.biomaterials.2025.123206) .
On 2025-02-26 17:21:48, user Leonardo Di Bari wrote:
Thanks for the analysis, the study is promising. I am, Leonardo Di Bari, a PhD student in the SPQB ( https://sites.google.com/view/spqb ) group of Martin Weigt and Francesco Zamponi: we have utilized the entropy that you present in the following three articles.<br /> https://arxiv.org/pdf/2412.01969 <br /> https://www.pnas.org/doi/abs/10.1073/pnas.2406807121 <br /> https://www.nature.com/articles/s41467-022-31643-3 <br /> I think it would be interesting to maybe compare the two formulations. <br /> Best regards,<br /> Leonardo Di Bari
On 2025-02-26 10:03:48, user Young Cho wrote:
This is a comment from a Journal Club of MBBE 602 in Univ of Hawaii.
Summary<br /> This paper explores the capabilities of twin prime editing (twinPE) for large DNA sequence modifications, including deletions, replacements, integrations, and inversions. The authors demonstrate the efficiency of twinPE in human cells (HEK293T & Huh7) and its potential for therapeutic applications when combined with the Bxb1 integrase. Key findings include precise and flexible editing with fewer indels, high knock-in efficiency, and the ability to bypass certain DNA repair pathways. However, the study lacks long-term data on genomic stability and scalability for human applications, and some experimental details and comparisons with other gene-editing techniques are insufficiently explored.
Introduction<br /> The introduction provides a solid foundation for the study but could benefit from more background information on the therapeutic applications explored, as well as the mechanism that resulted in limitations relating to the pegRNA pairs, or the low Bxb1 efficiency.
Results<br /> Figure 2:<br /> The figure demonstrates twinPE’s efficiency in large DNA sequence insertion and replacement. However, the formatting is poor, the figure legend is separate from the figure and labels are a bit confusing. The authors should revise the figure to improve readability.<br /> The large error bar in Fig. 2F (deletion size 589) suggests variability in the editing strategy. The authors should address this in the text, discussing potential outliers or variability in the system.
Figure 3:<br /> This figure effectively shows the mechanism and efficiency of twinPE combined with Bxb1 integrase. However, the authors should clarify why certain pegRNA pairs performed better than others and why some loci (e.g., CCR5, AAVS1) were more successful.<br /> The discussion should also address the limitations of single transfection compared to sequential transfection to allow researchers to build off of this work.
Figure 4:<br /> The figure explores therapeutic applications of twinPE, particularly in correcting inversions at recombination hotspots. The authors should expand on the implications of these findings for gene therapy and discuss potential challenges in scaling up for human applications.
Discussion<br /> The discussion is well-written but could be strengthened by addressing the following:<br /> Limitations of twinPE: The authors should discuss why lower frequencies occurred in single transfection compared to sequential transfection and why some pegRNA pairs performed better than others. Additionally, they should explore the potential limitations of using Bxb1 integrase and whether other integrases could be more effective.<br /> Comparison with other gene-editing techniques: The authors briefly mention the advantages of twinPE over CRISPR but do not provide a direct comparison. Including experimental data or a discussion comparing twinPE to CRISPR or other editing methods would strengthen the paper.<br /> Long-term implications: The study lacks long-term data on genomic stability after large DNA modifications. The authors should discuss potential risks, such as off-target effects or genomic instability, and suggest future studies to address these concerns.
Suggestions<br /> Improve Figure Quality: Revise figures to ensure they are clear, readable, and properly formatted. Include detailed legends and consider adding summary panels to highlight key findings.<br /> Expand on Limitations: Discuss the limitations of twinPE in more detail, including variability in editing efficiency, challenges in scaling up for human applications, and potential long-term effects on genomic stability.<br /> Compare with Other Techniques: Include a direct comparison of twinPE with CRISPR or other gene-editing methods to highlight its advantages and disadvantages.<br /> Explore Additional Integrases: Investigate the use of other integrases in combination with twinPE to determine if they offer improved efficiency or precision.<br /> Provide Long-Term Data: Conduct follow-up studies to assess the long-term effects of large DNA modifications on genomic stability and cell viability.<br /> Enhance the Introduction: Add more background information on the limitations of existing gene-editing technologies and how twinPE addresses these challenges.<br /> Address Variability in Results: Discuss potential outliers or variability in the data, particularly in Fig. 2F, and suggest ways to improve consistency in future experiments.
Editorial Decision<br /> The paper presents significant advancements in gene-editing technology and demonstrates the potential of twinPE for precise and efficient large DNA sequence modifications. However, the study would benefit from addressing the limitations and expanding on the comparisons with other gene-editing techniques. This publication could be strengthened with revisions to improve figure quality, clarify data interpretation, and exploring long-term stability the genetic edits. Overall, the paper was dense with information so the limitations are understandable, as only so much can be presented in one publication.
On 2025-02-25 21:24:18, user Xiaotong Yao wrote:
The measurements for the "realistic"-ness of the simulated genomes seems inadequate. For examples, what are the VAFs of mutations in the LOH or homozygously deleted or amplified regions?
On 2025-02-25 21:16:36, user Xiaotong Yao wrote:
No. You simply cannot "simulate" structural variants as if they are just rows in a BEDPE file.
Doing it in the way of this paper won't even guarantee your CNV boundaries are matched correctly with the junction breakends! Let alone consistent junction copy numbers or realistic complex SV events. This approach of treating each "variant" as an individual event only works for short variants, and CNVs to some extent.
To truly forward simulate a cancer genome that is accumulating structural variants/CNVs requires virtual cell cycles and keeping tabs on the junction balance constraints and linear/circular DNA structures, e.g., losing a telomere, di-centric chromsomes. We tried this before, but it is very very hard as the genomes coming out of the simulations are not anything remotely survivable for a cell and nothing like the real cancer genomes. So this is a fascinating and challenging open question.
On 2025-02-25 20:42:31, user Victor Gonzalez Perdomo wrote:
This study seems biased, there is very little data from the Paleolithic, you have data mostly around Neolithic. Also it seems that you have very little ancient data around the southeast Europe. You neither aproach the fact most light pigmentation features appeared close to the atlantic coast then seems to spred to the interior.
On 2025-02-25 05:38:33, user Roberto Nava wrote:
The reporter system is genius! Any chance the authors would be willing to share the supplemental tables? They don't appear in the PDF.
On 2025-02-25 01:58:05, user Maria Rebolleda Gomez wrote:
Really interesting paper showing that variation across strains in the relationship between growth rate and antibiotic-induced lysis as well as interactions can shape the outcomes of community re-structuring after antibiotic treatment. The authors are able to use data from individual E. coli strains to predict the overall enrichment in the community after antibiotics. However, the last step of the derivation in the methods was not clear to me why is it G_m,i + C - It is not clear what that constant is. Also in the main body of the paper it states that this is an approximation, but in the derivation is stated as an identity relationship.
On 2025-02-25 00:16:29, user Meet Zandawala wrote:
This study investigates the dynamics of neuropeptide release and activity following blood feeding in female Aedes aegypti mosquitoes. Sajadi et al. provide valuable insights into the temporal signaling dynamics of diuretic and anti-diuretic hormones, significantly enhancing our understanding of excretory physiology in mosquitoes. The authors employ heterologous expression of receptors to quantify circulating peptide levels, a robust methodological approach that strengthens receptor-ligand interaction validation and hormone quantification. Notably, the study demonstrates a synergistic interaction between DH31 and kinin-like peptides on Malpighian tubules, contributing novel findings to the existing literature on neuropeptide-mediated excretory regulation in mosquitoes. Overall, the study presents an innovative and well-executed investigation with high methodological rigor.
The authors have presented their findings in a clear and well-structured manner. We only have a few questions and comments/suggestions that could help improve the clarity of the manuscript:<br /> 1. Can the authors clarify the exact number of female mosquitoes used in each condition (blood-fed vs. non-blood-fed) at each time point, specifically in methodology section 3.2 for the haemolymph collection?<br /> 2. Were there any biological replicates across different mosquito cohorts? Did the authors observe variability between different mosquito batches? Sample sizes have been provided in the figure captions but what does n signify? <br /> 3. The study utilizes specific time points for haemolymph collection post-blood feeding. Can the authors provide justification for selecting these intervals? Were preliminary studies conducted to determine these as the most informative time-points, or were they based on prior literature?<br /> 4. The authors acknowledge the roles of serotonin (5HT) and DH44 in regulating fluid secretion but focus their experimental analysis on DH31, kinin, and CAPA peptides. Could they clarify why 5HT and DH44 were not included in their haemolymph quantification assays? Were there methodological limitations, or were these hormones not expected to show significant post-bloodmeal changes, or is this something they plan to address in the future?<br /> 5. The study quantifies neuropeptide levels over time but does not discuss the mechanisms responsible for their clearance from haemolymph. Can the authors speculate on whether DH31, kinin, and CAPA peptides are degraded enzymatically, removed through receptor-mediated internalization, or cleared by the Malpighian tubules? Can they use in silico approaches to predict the half-life of these peptides based on their sequence composition? Alternatively, can they extract hemolymph when the peptide has peak activity and test this extract after different times to see how much bioactivity they retain over time? Addressing this would enhance our understanding of neuropeptide turnover and regulation.<br /> 6. Including the individual data points in the bar graphs can provide more information on the spread of the data.
Comments prepared by Bilal Amir (on behalf of Zandawala lab)
On 2025-02-24 03:43:01, user ryhisner wrote:
I am unable to copy and paste anything into the reference window in the variability tab. It only allows me to type, not copy and paste. This means I would have to type in the entire nucleotide sequence by hand, which I'd rather not do.
On 2025-02-24 01:16:55, user Alex Monell wrote:
Hi bioRxiv staff,
The published version of this manuscript is out at https://www.nature.com/articles/s41586-024-08466-x
Thanks!
On 2025-02-23 02:33:22, user Cecil Saunders wrote:
I believe there is a typo in the abstract citation; Charles, 2019 should be Darwin, 2019.
On 2025-02-21 20:37:42, user Krzysztof Kozak wrote:
Multiple technological choices resulted in fatal flaws that make the conclusions of this manuscript unjustifiable:<br /> 1. Inadequate chain of custody of the samples, likely leading to massive contamination.<br /> 2. Application of insufficient sequencing methods and inappropriate data processing tools, potentially resulting in various technical artefacts.<br /> 3. Lack of replication, further exacerbated by deliberate mixing of the isolates.<br /> 4. A simplistic and biased interpretation of the observed patterns of change in the molecular sequences.
I posted a full review of the paper on ResearchHub: https://www.researchhub.com/paper/9161412/discovery-of-single-stranded-dna-in-meteorite-derived-cultures-evidence-of-novel-genetic-elements/reviews
On 2025-02-21 15:30:18, user Yuan Fu wrote:
The paper was published in JIPB on February 21, 2025. The DOI link is: https://doi.org/10.1111/jipb.13867 . Please cite it.
On 2025-02-21 14:20:17, user JJ wrote:
In figure 2, part D, the figure legend says - "The median UMI/gene count is shown as a number above a dataset and as a bold line". Does the numbers say UMI/gene or is it just the Median Number of Genes for each dataset?
On 2025-02-21 11:30:52, user mcsu wrote:
Hi, <br /> Care must be taken when using old data tables for example in table S1 the uniprot_IDs given for the following U. maydis proteins no longer map:-<br /> PRA1_USTMA <br /> PRA2_USTMD <br /> UM03423
but are <br /> P31302<br /> P31303<br /> A0A0D1E0T5
In addition, given these errors how confident are you that the Literature-sourced GPCRs are classified correctly?<br /> Many of the Pfam domains claimed to be "consistent with their associated GPCR class (Table 1)" are not found in the exemplar sequences of each class in table S1.<br /> For example, the Git3 Pfam PF11710 suggested as associated with CPCR class 3 is only found in GPR1_YEAST and not the other 4 proteins suggested as Class 3 GPCRs in table S1; see A0A1U8QVN2_EMENI, A0A1U8QIJ6_EMENI, A0A1U8QJM4_EMENI or Q7SAB9_NEUCR
On 2025-02-21 09:14:43, user Wenjun wrote:
Great work! In addition to enhancing light collection efficiency, the proposed method also effectively reduces the number of optical components in the remote imaging system.
On 2025-02-21 01:11:53, user Charles Warden wrote:
Thank you very much for posting this preprint for the Giotto Suite!
You have a couple different citations for STalign.
I believe this is the correct citation (Reference 34):
34.↵Clifton, K. et al. Alignment of spatial transcriptomics data using diffeomorphic metric mapping. BioRxiv Prepr. Serv. Biol. 2023.04.11.534630 (2023) doi:10.1101/2023.04.11.534630.Abstract/FREE Full TextGoogle Scholar
However, I think the following reference (to Hildebrandt et al. 2021) may not be correct?
"Image registration was performed using STalign [Reference 2]"
Best Wishes,<br /> Charles
On 2025-02-21 00:46:47, user Hurrian Fan wrote:
Congratulations to the team on some amazing work! The steppe component visible in East_steppe_Sets in Chalcolithic and Bronze Age western Anatolia is modeled with Yamnaya, CWC, and Bell Beaker, which are chronologically and geographically somewhat improbable for the early samples. <br /> Have the authors considered checking potentially more proximal sources of potential steppe ancestry, such as the Kartal A & B clusters from Penske et al 2023?
The subclades of y-hg I-L699 found in the Kulluoba and Kalehoyuk samples are not only shared with Serednii Stih individuals, but also Cernavoda (KTL001 & KTL006) and Thracian EBA individuals (Bul4 & I2165), which might lend some plausibility to this source.
On 2024-12-09 17:25:57, user Hannah Moots wrote:
Exciting research!! Just wanted to point you towards some additional research on the appearance of steppe-related ancestries in Italy. You mentioned that previous studies had identified the earliest appearance of these ancestries to be about 3,600 BP in central Italy. We published 4 ancient genomes from the Bronze Age site of Pian Sultano in central Italy and all of these individuals carried steppe-related ancestries, the oldest of which dates back to 3872 - 3719 calBP. https://doi.org/10.1038/s41559-023-02143-4 . Figure S4 has a timeline and admixture plots to visualize this as well.
On 2025-02-20 20:30:48, user Jesse Conklin wrote:
This should be linked to the final publication:
Conklin, J. R., Verkuil, Y. I., Lefebvre, M. J. M., Battley, P. F., Bom, R. A., Gill, R. E. Jr, Hassell, C. J., ten Horn, J., Ruthrauff, D. R., Tibbitts, T. L., Tomkovich, P. S., Warnock, N., Piersma, T., & Fontaine, M. C. (2024). High dispersal ability versus migratory traditions: Fine-scale population structure and post-glacial colonisation in bar-tailed godwits. Molecular Ecology, 33, e17452. https://doi.org/10.1111/mec.17452
On 2025-02-20 19:02:49, user Raoul wrote:
There is a previous report that has targeted a disease resistance gene to generate plants with enhance resistance. Similar to what is said in this pre-print ("SNC1 is an attractive target for proof-of-principle modulation of disease resistance by epigenome engineering").<br /> Reference: CRISPRa-mediated transcriptional activation of the SlPR-1 gene in edited tomato plants<br /> Plant Sci, 329 (2023), Article 111617, 10.1016/j.plantsci.2023.111617<br /> Recently a review article has mentioned that: "One notable example of enhancing disease resistance in crops involved the CRISPR activation (CRISPRa) system to activate the defense gene PATHOGENESIS-RELATED GENE 1 gene (SlPR-1) conferring enhanced resistance to Clavibacter michiganensis subsp. michiganensis infection in tomatoes" (taken from: https://doi.org/10.1016/j.pbi.2024.102669 ).<br /> Consequently, the concept has shown to be scientifically and technically feasible, as shown previously in 10.1016/j.plantsci.2023.111617.<br /> Thus, what is stated in this preprint is not really new, for plants: "The results demonstrate that epigenome-engineering of a single defense gene, SNC1, is sufficient to generate plants with improved disease resistance phenotypes."
On 2025-02-20 14:08:04, user Prashant Kaushik wrote:
Could the author kindly comment on how human plasma was processed post collection? Were there sequential centrifugation steps involved and were they consistent among different MS based tech? <br /> Thank you for sharing your fantastic Work
On 2025-02-20 12:15:37, user kei wrote:
Thank you for your interesting paper.
I am curious about the behavior when only the non-natural amino acids in cyclic peptides are not tokenized at the atomic level, and all cyclic peptides are represented using SMILES. I am thinking of investigating this.
That said, I have one question:<br /> What is the input format when inferring complexes of cyclic peptides containing non-natural amino acids and proteins?<br /> (In other words, how are non-natural amino acids formatted in the input?)
If possible, I would appreciate it if you could share an example of the YAML file or other input data used for Boltz1.
Thank you in advance.
On 2025-02-18 17:40:04, user Dongyao Li wrote:
Great work, thank you! I have one comment regarding comparison of cell segmentation. The paper states:
Overall, the CosMx 6K segmentation tool produced cells with larger sizes, higher solidity, and better circularity, indicative of more regular and convex cell shapes compared to other platforms
I would argue "larger", "more circular", and "convex" do not necessarily mean better segmentation. For example, "more circular" and "convex" could be the bias of the particular segmentation model. If more circular is better, then "nucleus segmentation + large expansion" (basically the first version of Xenium segmentation prior to multi modal cell segmentation stain) is the better segmentation since it's large, circular, and convex.
The paper later states:
Among the ST platforms, Xenium 5K showed better separation of marker gene pairs after segmentation
We further visualized marker gene expression across the annotated cell types. Xenium 5K exhibited the most distinct expression patterns (Supplementary Fig. 8d), facilitating more accurate cell type annotations.
and concludes:
Despite exhibiting more irregular segmentation shapes, Xenium 5K effectively distinguished different cell types and minimized transcript mixing between adjacent cells
"Better separation of marker gene pairs", "distinguish different cell types" and "minimize transcript mixing" are indeed the more principled and biologically meaningful metrics to evaluate cell segmentation. The word "despite" in the conclusion suggests circularity means better segmentation, which I don't necessarily agree.
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 2025-02-18 15:37:48, user Andrew Kennard wrote:
This preprint has since been peer-reviewed, revised, and published in a journal:
Kennard AS et al. (2025). Tubulin sequence divergence is associated with the use of distinct microtubule regulators. Current Biology 35(2): p233-248.e8. doi: https://doi.org/10.1016/j.cub.2024.11.022
On 2025-02-17 18:48:35, user Michael Young wrote:
We just discussed this paper in our lab - nice work! One minor comment and one general one. Figure 2f - use same x-axis for both plots. More importantly, the paper is trying to do a lot. Not sure whether we would suggest splitting into two papers, relegating some elements to supplementary materials, or keeping as is with details relegated to supplementary.
On 2025-02-17 08:16:49, user Jeziel Dener Damasceno wrote:
Please, could this preprint be linked to the final publication, please: https://www.nature.com/articles/s41467-025-56785-y
On 2025-02-16 01:30:11, user Nikolai Slavov wrote:
Code and data for reproducing the analysis are available at: <br /> https://github.com/SlavovLab/Protein-Clearance
On 2025-02-15 03:06:45, user Jayson Zhao wrote:
how about the nearest neighbor search algorithm behind that strongly affect the loss function of non-linear dimension reduction and dataset dimension, in which we will have hubs. See some discussion here: https://academic.oup.com/nargab/article/6/4/lqae172/7928174
On 2025-02-15 02:39:09, user sa pa wrote:
I read this paper with great interest.
Is there a name given to the single-cell RNA-seq using the “Solution-phase indexing by kinetic confinement” technique that you are proposing?
It would be easier to cite it as a single-cell RNA-seq method if it had a name like “xxx-seq”, but what should we call it officially?
In the text, it says “Single cell RNAseq using Kinetic Confinement”, is this correct?
On 2025-02-14 04:28:23, user Felix wrote:
I have only skimmed the paper, but I wonder if the link given for the fungal catalogue ( https://entrepot.recherche.data.gouv.fr/dataset.xhtml?persistentId=doi:10.15454/WQ4UTV ) is the correct one. It redirects to human oral microbiota gene and species catalogue rather than fungal-specific catalogue.
On a somewhat related topic, have the authors considered expanding the fungal catalogue with the recent cultivated human gut fungi resource ( https://doi.org/10.1016/j.cell.2024.04.043 )?
On 2025-02-13 22:20:55, user Amer Alam wrote:
The peer reviewed version of this manuscript has been published in the EMBO journal:
Structural insights into binding-site access and ligand recognition by human ABCB1
PMID: 39806099 DOI: 10.1038/s44318-025-00361-z
On 2025-02-13 19:40:38, user Pick Up Litter wrote:
This paper will help move science away from studying "cute" species and to be objective. Perhaps the most severe example is the housecat-- still portrayed as cute in media, but in the feral form a worldwide destroyer of birds. One critique concerning the Ivory-billed Woodpecker-- the number quoted by Troy et al, 20 million dollars spent for studies, is misleading. Most of the efforts are university and private, not governmental, and if the bird is proven to be extant, will have conservation benefits since it is a wide-ranging and keystone species. I help with research for the Ivory-billed Woodpecker. The growing body of evidence that this species exists is more rational than the critique-- see other BioRxiv papers and the work of Mike Collins for example. John D Williams
On 2025-02-13 17:59:30, user Mikaela Gray wrote:
This preprint has now been published in ACS Omega. Here is the link: https://pubs.acs.org/doi/10.1021/acsomega.4c07666
On 2025-02-12 14:36:44, user Sergio Angel wrote:
Very interesting. Our anti-TgATM antibody also labeled the cytosol, with phleomycin in cytosol and some foci in nucleus.
On 2025-02-12 10:42:04, user Claudio Vasapollo wrote:
This manuscript has been published with a different title wanted by the journal. You can find the published version on the PeerJ website at the link:<br /> https://peerj.com/articles/18765/
Thank you.<br /> Claudio Vasapollo
On 2025-02-12 06:12:29, user Prof. Sergio Manni Vanzini wrote:
The paper presents a novel perspective on the application of oxygen-ozone therapy in spine disorders, introducing the concept of adaptive chaos as a key mechanism in biological resilience and healing. A significant strength lies in its interdisciplinary approach, integrating mathematical modeling, bioinformatics, and clinical insights to establish a framework for understanding the therapeutic effects of ozone therapy. The use of Lyapunov exponents, Shannon entropy, and fractal dimensions to quantify biological complexity is particularly innovative, providing a structured means of evaluating systemic responses to treatment. Additionally, the study’s emphasis on precision dosing—highlighting the differential effects of low versus high ozone concentrations—adds valuable insight into the hormetic nature of the therapy, reinforcing the need for controlled perturbations in medical interventions. The thorough review of existing literature, including randomized controlled trials, strengthens the credibility of the findings and underscores the translational potential of the proposed model.<br /> However, certain limitations must be acknowledged. The reliance on mathematical simulations, while insightful, may not fully capture the variability of real-world biological responses, as complex physiological interactions are difficult to model with absolute accuracy. Additionally, while the study references clinical data, it does not provide direct experimental validation, making it difficult to assess the immediate applicability of the findings in clinical practice. The concept of adaptive chaos, though compelling, remains somewhat abstract, and further empirical studies are needed to establish its clinical relevance definitively. Lastly, some of the statistical approaches, particularly the unusually high values of Lyapunov exponents, may require re-evaluation to ensure their biological plausibility and proper contextualization within established dynamical system theory. Despite these challenges, the study provides a groundbreaking theoretical framework with promising implications for regenerative medicine and personalized therapy.
On 2025-02-10 12:29:07, user Alberto Farleschi wrote:
I came through these data, which represents a novelty for me, endeavoured in the field of bioinformatics. The study by Chirumbolo et al. presents a compelling and innovative perspective on adaptive chaos and its role in modulating oxygen-ozone therapy for spine disorders. By integrating mathematical modeling, bioinformatics, and clinical insights, the authors provide a rigorous framework to understand how mild chaotic perturbations can enhance systemic complexity and biological resilience.<br /> A particular strength of this work lies in its multidimensional approach, incorporating Shannon entropy, Lyapunov exponents, and fractal dimensions to quantify the therapeutic impact of oxygen-ozone therapy. Therefire, in my opinion, the authors successfully demonstrate that low-dose ozone (20–40 µg/ml O3) fosters adaptive chaos, leading to reduced inflammation, enhanced repair, and improved systemic stability. In contrast, higher doses (>60 µg/ml O3) appear to push the system into pathological chaos, emphasizing the importance of precision dosing in regenerative medicine. Really interesting outcomes!<br /> The translational significance of this study cannot be overstated. It not only advances our understanding of chaos-driven medical interventions but also sets a precedent for personalized medicine strategies that leverage nonlinear dynamics to optimize therapeutic outcomes. Future research could expand on these findings by incorporating real-world clinical datasets and patient-specific modeling, further solidifying the role of adaptive chaos in medical practice.<br /> I trust this study is a landmark contribution to the fields of biophysics, complexity science, and regenerative medicine, offering novel insights into the interplay between biological chaos and therapeutic control.<br /> Great results!!
On 2025-02-12 01:34:43, user Ddeadpanscience wrote:
I think normally rfdiffusion will require that you test at least 48 or 96 designs. The success rate is not that high
On 2025-02-10 16:30:17, user Pierre L wrote:
last references are not present in the article.
On 2025-02-10 16:19:15, user David Lähnemann wrote:
At the time of writing, the GitHub repository simply gives a 404 This is not the web page you are looking for at:<br />
https://github.com/wbvguo/BSReadSim.git <br />
Did you forget to make the repo public? Or is there a typo in there somewhere?
On 2025-02-10 11:32:39, user malandrin wrote:
The prepint is now published in Ticks and Tick Borne Diseases DOI10.1016/j.ttbdis.2024.102434.
On 2025-02-10 11:10:36, user Siobhán McClean wrote:
This article is now published in Microbiology Open. The citation is as follows:
Dennehy, R., Duggan, N., Dignam, S., McCormack, S., Dillon, E., Molony, J., ... & McClean, S. (2022). Protein with negative surface charge distribution, Bnr1, shows characteristics of a DNA‐mimic protein and may be involved in the adaptation of Burkholderia cenocepacia. MicrobiologyOpen, 11(1), e1264.
On 2025-02-09 11:10:57, user Zheng Gong wrote:
The authors should note that in line 549, the promoter that drives gRNA expression is the U6 snoRNA promoter and not a "Ubiquitin 6" promoter. Otherwise, a very interesting read!
Thank you!
On 2025-02-07 23:35:18, user Prof. T. K. Wood wrote:
On 2025-02-07 21:55:49, user Patricia Legler wrote:
We made FRET substrates for CHIKV PMID: 30742841. They are in the Suppl. Info.
On 2025-02-06 12:27:20, user Prof. T. K. Wood wrote:
page 51: CRISPR-Cas type IE is NOT inactive as found by at least two groups. It has been shown to control the cryptic prophages ( https://www.mdpi.com/1422-0067/23/24/16195 ).
On 2025-02-06 02:55:28, user Tom Liang wrote:
Excellent contribution to understanding the microscopic mechanisms of anion transport across Band 3! I would like to draw the author’s attention to a highly relevant recent publication in Langmuir: https://doi.org/10.1021/acs.langmuir.4c00216
On 2025-02-05 23:24:58, user Emry Gutierrez wrote:
Great paper! I was curious on the procedures regarding preparing the 48 well plates, as we've been trying to implement these methods into our experiments. Who can I reach out to for more information?
On 2025-02-05 17:50:10, user Emry Gutierrez wrote:
Great paper! Would any of the authors be able to share their procedures for preparing the 48 well plates? We've been trying to implement this methodology and this has been causing us some difficulties!
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 2025-02-03 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.
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:
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 2025-01-31 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 2025-01-30 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:
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.
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 2025-01-28 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 09:23:39, 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 2025-01-23 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 2025-01-23 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 2025-01-22 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 19:38:21, 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 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 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 2025-01-20 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 2025-01-19 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 2025-01-18 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 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 2025-01-16 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 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).
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).
Data Accessibility and Transparency:
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".
Consistency in referencing supplementary figures and tables in the main text should be checked, ensuring that all references are accurately placed (Page 2, Abstract).
AI Content Analysis:
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.
Ensure all datasets and computational tools used in the study are accessible via publicly available repositories, adhering to FAIR data principles.
Improve Experimental Detail:
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 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 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
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).
Clear Contribution to the Field:
Potential Minor Revisions
Ensure consistent use of “EGFR:STAT signalling” throughout the document (p. 12, Line 1).
Formatting Issues:
Verify all statistical analysis descriptions, as some sections mention methods without complete context (p. 16-17).
AI Content Analysis:
Recommendations
Include a summary table for gene expression changes associated with E-cadherin overexpression, illustrating the overlap with STAT92EY704F and HP1 knockdown (p. 4).
Control Experiments:
Additional control experiments are essential, particularly targeting the specificity of STAT92E interactions with Heterochromatin Protein 1 (HP1) and EGFR (p. 3-4).
Linking to Human Context:
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 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 2025-01-07 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 16:51:54, user Micha Wijesingha Ahchige wrote:
The paper is now published in the Computational and Structural Biotechnology Journal:
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.
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.
Data Accessibility:
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".
Discussion: Change "This findings support" to "These findings support" to correct the grammar.
Formatting Issues:
Improve the readability of complex diagrams with annotations or legends for clarity.
AI Content Analysis:
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.
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.
Improve Data Presentation:
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.
Refine Writing and Formatting:
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 11:23:42, 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
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).
Enhanced Methodological Detail:
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).
Integration of Homophily and Social Learning Models:
Potential Minor Revisions
Correct terms like "Cequence" to "sequence" (p. 11).
Formatting Consistency:
Verify consistent alignment and formatting of section headers and sub-headers according to standardized guidelines (entire document review recommended).
AI Content Analysis:
Recommendations
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).
Methodological Transparency Enhancement:
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).
In-Depth Social Network Analysis:
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).
Conservation Strategies Integration:
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 2025-01-04 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 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 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 2024-12-26 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.
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.
Data Integration and Interpretation:
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.
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
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
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
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
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 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).
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:
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.
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:
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 2024-12-17 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 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
On 2024-12-17 10:07:24, user Preprint Journal Club at MPIPZ wrote:
We recently reviewed this preprint in the PhD preprint journal club in the Department of Plant Microbe Interactions at the MPI for Plant Breeding Research. You can find the PREreview here: https://prereview.org/reviews/14505813
On 2024-12-16 22:03:01, user Alexander Scheffold wrote:
The specificity of the so called AIM assay is a highly relevant topic since it is now used by many labs. And the manuscript nicely addresses the signals leading to marker upregulation and identifies bystander stimulation to be a major confounding factor after 20 hours of stimulation.<br /> However, I wonder why the authors do not compare with the initial protocol using CD154 upregulation after only 7 hours. There it is convincingly shown that CD154 after 7 hours is absolutely specific for TCR activated T cells (e.g. Frentsch et al Nat Med 2005 PMID: 16186818).<br /> A simple but very reliable confirmation is also AIM combined with single cell sorting, cloning and restimulation. Again for CD154+ T cells after 7 hours for several antigens at least 80-90% specificity has been demonstrated (Bacher et al JI 2013 PMID: 23479226). We have confirmed that for many different antigens since then.<br /> Best<br /> Alex Scheffold
On 2024-12-16 11:16:14, user Monika Opałek wrote:
The published peer-reviewed verison of this article describing R package and shiny-based aplication is avaliable: https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.14269
On 2024-12-15 19:46:44, user Leonardo Sepúlveda Durán wrote:
Very useful research. The resolution of some figures is very low, makes them hard to read. Could you update the preprint with higher resolution images?
On 2024-12-14 15:21:00, user Stephanie Wankowicz wrote:
This publication aims to develop a platform of methods to identify small molecule ligand and RNA substrate interactions. Using a library of coumarin derivatives, they discovered a small molecule, C30, with high affinity binding to RNA single G bulges over other bulges (A, U, and C). The authors used Gaussian accelerated Molecular Dynamics (GaMD) simulations to study interactions, NMR to confirm the binding site location, and lasso regression to identify molecular descriptors for structure-activity relationships. The other narrative in this paper argues that this methodology could be used to develop better RNA-small molecule ligands for therapeutic purposes. <br /> Major Revisions:<br /> To strengthen the novel aspects of the authors' methodology, it would be beneficial to add context on why this method is more advantageous than previous workflow paths. <br /> Additionally, to drive this home in the conclusion, it would be beneficial to summarize the novel nature of this workflow and how it was used to discover these new ligands.<br /> We suggest clarifying and justifying the type of RNA substrate used in each assay (ssRNA, dsRNA, etc.). For example, we suggest clarifying if the modeled version of “SL5RNA” used in the Fig 2 in vitro assay is the same as the additional FP simulations. <br /> For Fig. 3, in these FP simulations, please clarify if this “DNA version” of the RNA5 and RNA1 substrains is dsDNA or ssDNA. If it is a helical dsDNA version of the substrate, a justification as to why this was used to probe a minor groove binding mechanism for a seemingly bulged ssRNA substrate would be beneficial.<br /> We would suggest integrating some of the supplementary figures, like Supplementary Figure 6, into the main text. This could enhance the reader's understanding of the electrostatic interactions in RNA-ligand binding and the significance of Ring A's positive charge in identifying binding pockets. <br /> Additionally, we suggest exploring alternative feature selection methods such as SHAP or Markov trees. These could potentially capture more nuanced, nonlinear interactions that might be missed by a linear selection method like LASSO.<br /> Minor Revisions:<br /> In the introduction, we suggest that the authors clarify the importance of preventing deep hydrophobic binding pockets in a pharmaceutical context, including a more streamlined discussion of coumarin derivatives and their therapeutic potential for SARS-CoV-2.<br /> We suggest in Fig. 2D that the graphs’ y-axes should be scaled the same and these curves should be labeled “GA-rich” and “G” for clarity. <br /> For Fig. 3A, we suggest the legend be enhanced and a scale bar added for clarity. <br /> For Fig 3D, it is difficult to identify the yellow, grey, and orange dashed lines. Please make this more obvious to highlight.
On 2024-12-13 12:34:06, user Alexis Verger wrote:
It's a very interesting paper that I really enjoyed. Below are a few comments:
I don't understand figure S1A. The TAD for VP16 is shown as 304-382. I assume this is a mistake as it is 410-490.
For the Med7-HA-SNAP549 construction, I assume controls have been made such as the ability to be correctly integrated into the Mediator complex. It would be nice to show this.
All the experiments were carried out using nuclear extracts and therefore potentially ‘contaminants’ (such as transcription factors interacting with the Mediator and competing with Gal4-VP16) which could interfere with recruitment. Did the authors attempt to directly purify the Mediator and/or Pol II in their system?
The multiple bridging model at the end is interesting. But if I've understood correctly, it can only work if 2 or more activator molecules interact simultaneously with the same Mediator complex. This model is possible if the activator targets different Mediator subunits. This is the case for VP16 in yeast (Med15 and Med17). But how does the model apply to an activator that targets a single subunit? Did the authors try another activator? A Gal4DBD-Gcn4 TAD for example?
-VP16 is also known to interact with TBP, TFIIB and p62 TFIIH. How can this be reconciled with the authors' model which suggests that the Mediator is recruited first and then the PIC?
On 2024-12-12 18:59:34, user Adrien Jolly wrote:
Dear authors,
Thank you very much for this great study. Many smart ideas, much food for thought.<br /> I have a specific concern regarding figure 6. If I understand correctly, you make the assumption that the frequency of Ki67 positive cells directly correlates with proliferation speed. I find this assumption problematic, Ki67 protein accumulates in S-G2M and is degraded in G0/G1 (see for instance PMID: 30067968). One can find that, at steady growth, a shortening of SG2M will actually reduce the proportion of Ki67+ cells, (a shortening of G1 will however increase it), depending on these parameters, the growth rate of the population could be significantly larger for big clones with no change to the proportion of Ki67+ cells. With the Fucci markers combined with ki67 you might be able to resolve this question, but I can imagine it would be very difficult to also identify different clones in this case.
Cheers,
Adrien
On 2024-12-12 11:47:04, user FKA Arebolas wrote:
Interesting work, that allows of all us to understand a little bit more about 'project-based science'. I do hope that a substantially revised version of this paper would eventually be published—in an internationally renowned journal. The authors have done a great job and deserve such a form of recognition.
Still, the paper also suffers from several shortcomings that have less to do with its 'pre-print' status than with its theoretical and methodological foundations. The following is a brief exposition of its weaknesses, as I see them.
The paper is beset with inconsistencies. To begin with, the contrast between 'ERC science' and 'Consortia science' is a non-starter. Not only do some ERC grants require grantees to set up international consortia (i.e., Synergy Grants), but, also, 'Consortia science' in this context aims to group together types of EU-awarded grants that are internally diverse, including Research and Innovation Actions (that make provision for fundamental research) and Innovation Actions (that do not). 'Consortia science', put it simply, do not exist—not even as an analytical category.
Along these lines, at some point in the 'Introduction' section, the paper hints at an important aspect of grant funding: the constant need to look for new funding, or 'strategic anticipation'. This has to do neither with 'consortia science' nor with 'ERC science', because, in both cases, recipients are expected and must search for funding once the project is finished. Unfortunately, this rather important aspect of grant funding (or project-based funding) is nowhere considered in the presentation and discussion of results. Pursuing this line of research further would be rather illuminating and would help us disclose the real problems connected to grant funding (a topic that Merimans is concerned with in another paper, already published).
Also critical, by this commentator's point of view, is the assimilation of 'international collaboration' to 'knowledge co-creation' and 'knowledge co-production'. This usage is clearly confusing and misguiding. 'Co-production' has a very specific meaning in Science and Technology Studies, and it has nothing whatsoever to do with getting industry involved in the project. Furthermore, the reality of RIAs and IAs do not stand to the implied meaning of such moniker. Most of the time, such involvement truly amounts to a division of labour, according to which the companies in question act as 'demonstration cases' that implement and test (or demonstrate) the technology being proposed. Nowhere can one find an instance of 'co-production'.
I am pretty sure that the authors know a great deal about grant funding, and about EC's Framework Programmes in particular. Yet, the previous critical remarks are a glaring illustration that additional research is needed to get fully acquainted with the subtleties of such funding scheme—knowledge necessary to fully understand what is at stake in the interviews.
To conclude with this informal review, two methodological remarks: 1) it is by no means clear which the selection of participants have been. I believe that only a minority of them have experience in ERC grants (either applying for them or, crucially, gaining them), so that framing the whole paper in terms of 'how well ERC grants are' might be, once again, distorting and misleading; 2) nowhere are details about the coding process being offered. As the research work, despite the pre-print format of the paper, seems to have concluded, this is not an absence that can be attributed to the preliminary stage at which the results have been published.
Hoping that these indications help the authors improve the manuscript.
With kind regards,
L.
On 2024-12-12 11:32:12, user eggersii wrote:
I would like to suggest a few experiments / changes in information that will increase the value of the manuscript:
Going off the information given in Section 4.3: ‘Hemoglobin is passively encapsulated by combining the desired concentration of hemoglobin with silk solution prior to combining with PVA.’ Does that mean 250 µg/mL Hb was added into a 5% w/v silk solution (0.25 mg/mL / 50 mg/mL = 0.005 = 0.5 %). With Silk:PVA = 1:4, thus a 4x dilution (=1.25%). Thus, the Hb content is either 1.25% (for 250 Hb formulations) or 0.625% (for 125 Hb formulations)?
Whatever the Hb content is, it will give valuable information in their potential, and worth reporting in the manuscript.<br /> - UV-Vis Spectroscopy. The authors determine the mHb% using the cyanmethemoglobin method, which is based on the UV-Vis spectra of Hb. Would it be possible to add the full UV-Vis spectra of the tested formulation in the SI? Often, NPs create an absorbance signal itself, so it would be nice to see how this affects the measurements, if at all.<br /> - In vitro studies. Section 4.10: ‘The wells stimulated with silk nanoparticles received 250 μl of M0 media supplemented with 50 μg of silk particles.’ How did this concentration come about? Would it be possible to add a prior cell viability assay that determined the optimal particle concentration to use, or even show a IC50?
On 2024-12-11 14:59:37, user mohit panghal wrote:
We are pleased to share that the NPBD code ( associated with this study ) is available on GitHub for public access and use. You can find it at the following link - https://github.com/cbl-nabi/NPBDetect/
On 2024-12-11 13:13:52, user Kostas Konstantinidis wrote:
Dear Cameron<br /> Thank you for bringing these papers to our attention. We are familiar with most of them and indeed, some of the results reported in these papers are consistent with some of the results of our study. I would like to point out, however, a key point: these papers are not relevant for the main topic of our study because they do not link recombination to the ANI units (clusters) and/or have not shown that recombination is random (unbiased) across the genome (as opposed to selection-driven, and thus spatially and functionally biased) and frequent enough to serve as cohesive force for the unit.<br /> kostas
On 2024-12-11 12:53:46, user Sam wrote:
Hi, thank you for this interesting paper. Just a small question for clarification: The 50 kbp or longer uncorrected ONT reads that were used for hifiasm UL input are supplied a second time as hifiasm normal input (but in this case after correction and chopping to 10-30kb), correct?<br /> Thanks!
On 2024-12-10 02:10:47, user Dovini wrote:
The preprint titled "GxE PRS: Genotype-environment interaction in polygenic risk score models for quantitative and binary traits" is published as "Mitigating type 1 error inflation and power loss in GxE PRS: Genotype–environment interaction in polygenic risk score models".
Full text link: https://onlinelibrary.wiley.com/doi/full/10.1002/gepi.22546
On 2024-12-09 01:41:58, user avtrader wrote:
Science Discussion
The multiple modern, peer reviewed papers on the field status of Ivory-billed Woodpecker (IBWO) are dominated by visual media depicting putative or actual Ivory-billed Woodpeckers. The most important and impactful data sets determining that the species is extant is the collection of thousands of video and picture frames taken by discreet researchers with various cameras.
Since there is only one other large woodpecker in the USA, which is not a congeneric, using visual evidence is effective as the two species are quite different in plumage, movements, and behavior. Visual evidence of putative or actual IBWOs shows that the subjects are clearly not Pileateds when plumage, movements and behavior are examined.
Elevating the veracity of acoustical evidence firmly indicating IBWO presence, as this paper concludes, is problematic since there are several known and hypothetical avian and other vertebrate sources of kent calls.
A major, glaring omission is that the putative IBWO kent data set is only compared to one Blue Jay kent when it is well known that several species of vertebrates, including birds, amphibians and mammals, are accepted as producing Ivory-billed-like kent sounds. Even if the author establishes or approaches establishing that the putative IBWO kents are not blue jays, which is not accomplished, he has not addressed any other competing species.
Note that the 2024 peer reviewed paper "Echo of extinction: The Ivory-billed Woodpecker's tragic legacy and its impact on scientific integrity", P. Michalak employs a much more sophisticated spectrogram analysis than the prepaper and found the putative IBWO kents from LA did not match with known IBWO kents. (Bio Science, Volume 74, Issue 11, November 2024, Pages 740–746, https://doi.org/10.1093/biosci/biae072
Compounding the impediments to a firm acoustical ID, the only widely accepted kents of IBWOs recorded were of agitated birds (n =2), 90 years ago from the Singer Tract, LA. Alerted or stressed individual birds can have frequencies different than nominal productions of the same song or call type. This prepaper fails to even acknowledge these major and other issues yet somehow has very strong conclusions that are therefore unsupported, metaphysical and proselytizing in nature rather than scientifically anchored.
One well known competing source of IBWO-like kents is the Blue Jay (BLJA). For decades it has been understood that some spectrograms of Blue Jay kents have shown differences with Singer Tract, LA, Ivory-billed kents.
At a minimum any research paper that attempts to address and dispositively conclude this issue will need careful spectrogram analysis of many examples of these Blue Jay kents and then compare them to IBWO kents or putative IBWO kents. The biological context of the putative jay kents must be detailed; not ignored. Many would concur with the prepaper author including Choctawhatchee River, FL kents in the set of putative Ivory-billed kents since these were spatiotemporal to hundreds of other IBWO supporting data points in key data sets such as---suggestive videos, IB sightings some by 2 observers, recorded and heard Campephilus-like double knocks near the kents, IB-like roosts holes. etc.
I have line surveyed the Choctawhatchee River over 120 hours and found Blue Jays to be non-existent to rare since this river bottom corridor has few oaks. Unfortunately the author's standards for most of the non-Choctawhatchee, FL, alleged IBWO kents in his set is minimal and nebulous.
The prepaper has so many biases, omissions, and basic scientific flaws that a rewrite is needed. A terse comment here however would not help the conservation of the few Ivory-bills likely left.
The following observations and recommendations are offered.
The data in this prepaper includes only one Blue Jay kent call spectrogram which was recorded and commented on by many over the decades. The author then inserts an unprecedented, unfounded and unsound comparative method, not found in the ornithological literature. The data includes ~ 136 Blue Jay calls, of which none are kent calls, to claim the establishment of an unabridged frequency capability for all types of Blue Jay calls. The author erroneously takes his incomplete set, in regards to the species extensive repertoire of Blue Jay and any hypothetical spectrograms and concludes that this eliminates all possible frequencies, tonality or partials/harmonics that may be produced when a Blue Jay kents.
The author takes the actually abridged set of Hz and illogically and awkwardly states in the Abstract "Differences are seen such that these two species cannot be mistaken for each other". In the Conclusion sections he supports the hyperbole by stating that interspecific physiological differences make it impossible for a BLJA to produce the Hzs he found in the putative IBWO set of kents he examined. "Because of different morphology and functional anatomy, Blue Jays and Ivory-billed Woodpeckers are going to make different quality sounds."
He continues that all Blue Jay kents cannot be IBWO kents and the reverse but the scientific premise he employs is unprecedented in ornithological research. The text or bibliography does not include one reference that uses body length as a driver or predictor of avian Hz range capabilities. During an on-line comment exchange with the author pivotal parts of his concept are formed by the idea that a larger bird cannot possibly be matched by smaller birds as far as Hz convergence. In this case the birds are of relatively similar size of 20 inches and 12 inches. There is no Ostrich to Hummingbird length disparity involved here. The author may have no field experience with any members of the genus genus Procnias (bellbirds) with a 125 decibel level with a body length of 11 inches. Volume or Hz range may have little to no correlation with body size. I have searched the literature unsuccessful to discover what the author is possibly using as a prerequisite to his sweeping Bergmann's rule-like conclusions that correlate acoustical Hz and moderate changes in avian body size. This is an example of common sense bias that a 20 inch bird cannot produce at least some of the same Hz as a 12 inch bird. These biases and assertions seem unsupported and unlikely hypotheses let alone conclusions by the author.
The author is responsible for doing a literature search, not readers, before prepapers are posted; the text and bibliography portray minimal research was done to support the presented hyperbolic declarations.
Most publication submittals are rejected because the literature search was poor. This prepaper's bibliography verifies that not even one adequate reference let alone comprehensive work on Blue jay ecology, mimicry, relative high intelligence, syrinx, physiology, vocalizations, point surveys for Blue Jays in the alleged IBWO kent areas, etc. was read or done .
Blue Jay' hypothetical acoustical capabilities have as a pretext a species possessing a syrinx with broad capabilities, high avian intelligence, wide repertoire, strong memory and substantial mimicry ability. Years ago I checked the literature on the subject species and at these rather mid value frequencies and harmonics there is no physiologically based reason that IBWO kents and Blue Jay kents must always be at different Hzs. In addition the literature does generalize that there is often sexual intraspecific differences in a species Hz for the same general call, such as a kent. Extrapolating from known ornithological literature, no one knows how a male blue jay would mimic a modern female IBWO it ambiently heard kenting; how a female blue jay would imitate a male IBWO, etc. It is not known how a blue jay would mimic a nuthatches kent vs an IBWO it heard kenting.
A major, glaring omission is that the putative IBWO kent data set is only compared to one Blue Jay kent when it is well known that several species of vertebrates, including birds, amphibians and mammals, are known to produce IBWO-like kent sounds.
Brief info on Hz
Within a single bird species, different calls can have varying frequencies. This variation can depend on several factors:
Type of Call: Different calls serve different purposes (e.g., alarm calls, mating calls, contact calls) and can have distinct frequency ranges.
Individual Variation: Just like humans have unique voices, individual birds may produce calls with slightly different frequencies due to physiological differences.
Context and Situation: The context in which a call is made can influence its frequency. For example, a bird may alter its call if it's trying to signal alarm in a crowded area versus calling to a mate.
Environmental Factors: The surrounding environment can affect how calls are produced and perceived. For instance, birds may adjust their calls in dense forests versus open areas.
The Abstract is ambiguous and misleading; also inconsistent with the rest of the paper. The Abstract does not mention many of the strong conclusions and constructs that accumulate as the paper proceeds. The constructs and conclusions, if true, would be quite compelling, with scientific value; the issue of distinguishing recorded Ivory-billed Woodpecker kent calls from other species kent calls is a complex issue. Unfortunately this paper ineffectively addresses the issue with a short, terse incomplete Abstract that is subsequently followed by unsubstantiated and unsupported conclusions and erroneous, sweeping ornithological assertions.
Ambiguity---the paper’s central theme is initially thought to be that IBWO kents can be distinguished from Blue Jay kents. The short Abstract mentions ~ 136 Blue Jay calls have been examined; after quite a bit of reading one finds out that only one of the ~136 Blue Jays calls examined is a jay kent call ( Blue jay calls, n = 137, Blue jay kent call n = 1). At this point some readers will realize the omission in the Abstract is an intended pathway to one of the papers eventual conclusions that Blue Jays are physiologically incapable of producing the Hz found in the putative IBWO putative kent call spectrograms.
Misleading---the Title and Abstract concentrate on Blue Jay kents; the latter highlighting n’s of 136 and n = 200, but these numbers are for data sets that do not include any Blue Jay kents. Actual Blue Jay kents spectrograms examined closely by this paper is n = 1.
Inconsistent --- The Abstract is overstated yet some of the subsequent constructs and conclusions are bold and somewhat hyperbolic. Conclusions presented are unsupported and are more correctly described as hypothesizes or unsupported hypothesizes.
The paper has n = > 200 for putative IBWO kent calls but fails to call them putative. This omission leads to concerns of circular logic. The paper provides no supporting evidence that some of these putative IBWO kent calls were derived from birds that were field IDed as IBWOs or for some reason likely IBWOs. Acceptable reasons could be that the subject kent call were associated with a tempospatially IBWO sighting or double knocks. Field details are needed for all kents that were not from Choctawhatchee River, FL. Kents in that study were spatiotemporal to hundreds of others IBWO supporting data points in data sets.
It is possible that a hypothesis that all IBWO and BLJA kents can be differentiated by spectrograms is correct. I propose it as a hypothesis. However jumping to premature conclusions with so much missing is not the way to proceed. We have delayed the erroneous extinction proposal with solid field techniques that had little if anything to do with Blue Jays and exaggerations but did truthfully present the videos, game cams, sighting notes, etc.
IBWO conservation will not be prodded by examining characteristics such as acoustical Hz with flawed methods. Some will rightfully suspect that these odd assertions are designed to proselytize rather than establish the truth.
On 2024-11-30 19:30:43, user avtrader wrote:
BioRxiv Violation
The author claims no competing interests, yet he and others have said he is the Science Director for Mission Ivorybill. Mission Ivorybill's stated goal--is to save the Ivory-billed Woodpecker. Mission Ivorybill or the related, The Louisiana Wilds do not seem to be federal non-profits via a 501-c3 data base search.
Mission Ivorybill raises money via various channels and seems to be a commercial entity; this violates BioRxiv's publication rules for authors in addition to being a non-disclosed conflict by the author. Mission Ivorybill also has Go Fund Me efforts, publications, etc. and the organization is IBWO-centric. The author participates vigorously in marketing Mission Ivorybill. He controls and/or participates in Mission Ivorybill's media and marketing efforts such as their Facebook page and Zoom public presentations. The author reviews evidence gathered by Mission Ivorybill yet fails to disclose the relationship tainting this prepaper's Abstract and Conclusions.
Mission Ivorybill is mentioned in the subject paper. The author is well known to exaggerate claims of Ivory-bills recently proselytizing a video of a Tufted Titmouse was an Ivory-billed Woodpecker is association with a Mission Ivorybill presentation and on social media. The founder of Mission Ivorybill quickly distanced himself from the false Ivory-billed claims by the author.
The author receives organizational support, professional and informal introductions, recognition, publicity and public face-time from Mission Ivorybill/The Louisiana Wilds perhaps in return for his often aggressive marketing efforts for Mission Ivorybill. His efforts have even included researching and contacting employers, to disparge and econimically damage people who disagree with him on the Ivory-bill's status.
The author may have purposely not disclosed this unambiguous conflict and his association with a possible commercial entity whose only product is the Ivory-billed Woodpecker. Related the subject BioRxiv prepaper has some hyperbolic, marketing-like claims that are not based in science.
On 2024-12-06 17:54:14, user Malte Elson wrote:
The remarks below are a summary of the points discussed during the Cake Club of the Psychology of Digitalisation lab at University of Bern ( https://www.dig.psy.unibe.ch/studies/cake_club_/index_eng.html ). They do not reflect the opinions of each individual journal club participant. Any responses to these points should be addressed to Malte Elson.
In their preprint, Spiess et al. (2024) illustrate the impact of influential data points on statistical significance in linear regression analyses. The authors reanalyzed data from three high-impact journals by searching for the term "linear regression” and digitizing graphs of the included papers (due to the absence of raw data). Their findings revealed that excluding influential data points often rendered previously significant results non-significant. The simulations included in the study largely confirmed expected outcomes, supporting the overall argument for incorporating leave-one-out analyses in data analyses practices. The authors ultimately advocate for broader adoption of such methods to enhance the robustness of statistical conclusions.
We found the paper to be interesting and an illustrative contribution to statistical education, both in terms of the potential fragility of published claims and as an illustration of an intuitive but underused outlier detection method. We identified points that might allow the authors to strengthen future versions of the manuscript, including some critical points about potential weaknesses or absences in the current version of the manuscript.
1) TERMINOLOGY CONFUSION AND REPORTING ISSUES<br /> * Graphs vs. Papers: There is some confusion regarding the unit of analyses, and probably some reporting errors: On p. 4, l. 115, the paper states that the sample was 24 + 30 + 46 = 100 graphs, whereas on p. 6, l. 170 the authors state they examined 100 publications (going by Table 1, this is a simple clerical error, and should say graphs).
* Similarly, the description of the columns in Table 1 (p. 11) is confusing, and we think has at least one reporting error:
* It is unclear what “Hits” represent: Are these unique papers, or do the search engines of Science/Nature/PNAS return the same paper multiple times for each instance of the search term (“linear regression”)?
* What does "number of graphs that were not shown" mean? We think these are instances of linear regressions that simply were not reported with a corresponding graph in the original publication, but they could also be graphs missing, inaccessible, or excluded <br /> * The “Articles” column is described as “number of Articles in which the analyzable graphs were found” (p. 11, l. 314), but we think these are the 21 articles in which the 29 “influential variables” were found. The number of articles with analyzable graphs is not reported. It thus remains unclear how many papers were included, and how many graphs were analyzed from each paper.
* On p. 6, the authors report having identified 29 graphs in 21 papers in which the removal of one datapoint changes the result of a linear regression (see also Figure 1). On p. 6, l. 179 the “incidence” (should be prevalence instead) of changes in papers is reported as ~20%. However, this puts papers (21) in the numerator and graphs in the denominator (100), which underestimates the prevalence. On the graph-level, it should be 29/100 = 29%. The paper-level prevalence cannot be calculated because the authors do not report the number of papers with analyzable graphs (see above).
* We strongly recommend reporting a Prisma flowchart to clarify the inclusion/exclusion of graphs and papers. In the same vein, the paper lacks basic information about the included studies, such as sample sizes or the distribution of p-values. Other information would also help emphasizing the importance of the present study, e.g. citation metrics.
* The authors refer to “Supplementary Data 1” (p. 4, l. 121) but provide no link.
2) SAMPLING STRATEGY <br /> * The study focuses on digitizable graphs without overlapping data points, inherently excluding studies with (1) larger samples and (2) homogeneous effects, where overlapping data points should be more frequent. This selection skews the included papers towards studies with smaller samples and p-values near 0.05 (due to lower power and publication bias / p-hacking), which are more susceptible to the illustrated effects. This is not a problem per se, but means the findings (including the prevalence rate) are about a narrower population of studies. Either way, the selection effects should be discussed in the paper.
* It is not fully clear how it was decided which graphs are analyzable and which are not. Moreover, on p. 4, l. 127-130 the authors state that the obtained regression parameters match those reported in the paper closely, but they do not further explain what exactly this means, or what happened when they did not match
3) ANALYSES AND CONCLUSIONS <br /> * The analysis does not account for dependencies when multiple graphs from the same paper, which will likely be based on the same data (which are then susceptible to the exclusion effects), are included.
* In a way, the susceptibility of findings to the removal of a single data point is a restatement of issues related to small samples. Small samples are inherently more fragile, and larger sample sizes are more robust to the influence of removing (or adding) single data points and render p-values (and other estimates) more stable. This is not to say that the findings reported are not interesting; however, we were wondering whether a table of all included studies sorted by observed p-value and sample size would have flagged the same fragile papers. This is also not to say that dfstat is redundant, and we absolutely see the pedagogical value in being able to point at individual data points that “cause” a finding to be significant. Rather, we would be interested to what extent dfstat converges with common heuristics.
* Relatedly, the authors decry that influence measures such as dfstat are largely ignored, even by statisticians (p. 4, l. 139). This may well be, but of course, statisticians (and non-statisticians) are obviously aware of issues related to low power and small samples, and one of these issues is the problem of spurious findings (e.g. due to few, extreme data points).
* The authors largely blame frequentist statistics, particularly on p. 10, where e.g. they state that “[a]s long as stating significance or not is still based on the ubiquitous α = 0.05 threshold, these statements can be sensitive to the presence of a single data point.” (l. 282-284). However, it is unclear how this follows from their findings. Any inference (not just α = 0.05) could be susceptible to the influence of single data points when the estimate is close to the criterion. Moreover, particularly when the sample size is low, any metric’s value (e.g. point estimates) will vary as a function of the removal of individual data points, regardless of whether the inference is threshold-based or not. This is simply a property of statistical models fit to a limited amount of data. So again, the issue seems to be with small sample sizes.
4) RECOMMENDATIONS AND FUTURE DIRECTIONS<br /> Things we would have liked to see:
* Additional analyses, such as leave-two-out or leave-k-out methods. The leave-one-out analyses are providing a good intuition of how fragile some small-sample study results are. Additional leave-k-out analyses would provide further information about the fragility of the entire sample.
* So far, the authors are concerned with the fragility of results as an outcome of removing data points. An additional study exploring the reverse scenario would be valuable. Specifically, it could investigate how extreme an additional data point would need to be to alter results, and how adding non-extreme data points could mitigate the relative weight of extreme data points.
* Discussing dfstat as a robustness metric (“How many individual data points would have to be removed/added to render a significant result nonsignificant or vice versa”)
* A discussion of how dfstat could be used for p-hacking by showing researchers which data points they would have to remove to turn a nonsignificant study result into a significant one.
* The authors graciously and immediately shared data and code with one of us who requested it, and we thank them for this. We would like to see this data and code provided in a public repository and linked to in a future version of the manuscript.
* We note that the authors chose to anonymise their data so that the reader cannot tell which original study’s results are robust or not. Personally, we think that meta-scientific interests are best served by making this information public; that is, we would like this data to not merely be used to illustrate the method but also inform the reader about the fragility or robustness of those publications’ results. Of course, not everyone agrees with this practice - perhaps the authors could comment on their perspective on this issue in a future version of the manuscript.
On 2024-12-06 16:47:49, user Nick wrote:
Incredible work! I was looking through the supplemental data and it appears that the A549_Compartment tab in Table S2 is duplicated from the HeLa_HPLM_Compartment tab rather than containing the 2,320 compartment hits for this cell line.
On 2024-12-06 16:11:31, user Sanjay Magavi wrote:
Huang et al have developed impressive ELOVL1 inhibitors for the treatment of ALD. Their lead compound effectively reduces the putative pathological substance, VLCFAs, in the CNS. There are a few points to address in this paper that could significantly improve an otherwise strong piece of work.
In figure 2 Huang et al report C26:0/C22:0 levels. These probably slightly underestimate the potency of their compound, as ELOVL1 inhibition reduces not only C26:0, but also C22:0, the denominator. Through most of the paper, they report absolute concentrations, so this is a minor concern.
Huang et al incorrectly report that our studies (Come et al, 2021) "measured only Lysophosphotidylcholine C26:0 levels", and were thus less complete. We report reductions in C26:0 LPCs, acyl carnitines and total VLCFAs in the CNS in our paper.
Huang et al report that "treatment with the ELOVL1 inhibitor unexpectedly led to profound transcriptional changes beyond correction of pathways altered by the loss of ABCD1." Almost all small molecule drugs have off target activities and clinically apparent side effects that are accompanied by transcriptional changes. The most parsimonious explanation for the "off target" transcriptional changes is "off target" activity of the compound. If they were to test multiple structurally distinct ELOVL1 inhibitors and find a shared pattern across scaffolds, that could support the argument that this is somehow a general property of small molecule ELOVL1 inhibition. The conclusion to their abstract that "ELOVL1 inhibition may have broader consequences . . . than the correction of lipid homeostasis" goes beyond the data they have in hand.
In the face of a disease that is fatal in one third of boys who carry mutations, such changes in transcriptional profiles, without any associated findings in traditional in vivo toxicology studies, should not be a reason to discontinue development. Indeed, an absence of "off-target" or unexpected transcriptional changes is a barrier that even most currently prescribed safe and effective drugs could not meet.
This paper presents an impressive chemistry campaign and biological characterization of novel ELOVL1 inhibitors.
On 2024-12-06 15:02:38, user Alex Crits-Christoph wrote:
In examining a few of the top hits from this work, it becomes apparent that most of them are due to contamination during sequencing.
Here are two examples:<br /> https://www.ncbi.nlm.nih.gov/nuccore/NZ_BMOE01000030.1?report=fasta <br /> https://www.ncbi.nlm.nih.gov/nuccore/NZ_WWEN01000019.1?report=fasta
Both of these are small contigs, and therefore may not actually be part of a contiguous bacteria genome. When we BLAST them with BLASTN, they match very closely known synthetic vectors for working with HIV.
Therefore, in these two cases (and all others I've spot checked, although I have not been comprehensive), there is no evidence that these genes are present in the bacterial genome. Rather, these are evidently cases where someone was sequencing an HIV-related sample on the same lane as a bacterial genome, and cross-contamination occurred (either index hopping or well to well). The HIV-vector sequence was then assembled as part of the bacterial genome, and missed in contamination screening (both by the authors and by NCBI!).
Thus I was not able to identify any cases of genomic evidence for the claims of the authors, although I did not look at every hit because the pattern above quickly emerged.
If the authors of this work want to provide sufficient evidence for the claim that there are close homologs of HIV related proteins in bacterial genomes, I would suggest taking a close manual inspection of all hits in their table. They should be able to show that these hits are integrated into bacterial chromosomes, and not always on separate contigs. They should show the raw reads then support those integrations. If the claim is that "some bacteria can acquire HIV-1 genetic material", they should then also do a comparison at the nucleotide level, not at the translated amino acid level. Finally, if that claim was tree, they should construct a phylogenetic tree to identify the nearest HIV relative and estimate time since divergence.
However, it is simply dubious that this is biologically true, because it would be an extraordinary claim if true, with no evidence yet emerged. It is essential to always closely inspect genomic results. Genomic results are not a black box, and manual inspection can quickly shed light on them.
On 2024-12-06 01:19:33, user xPeer wrote:
Courtesy review from xPeerd.com
Summary
The preprint "Cell based dATP delivery as a therapy for chronic heart failure" proposes using genetically modified human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) to deliver deoxy-ATP (dATP) to improve contractility in chronic heart failure. This strategy involves overexpressing ribonucleotide reductase in hPSC-CMs, enhancing their dATP production. Key outcomes include increased left ventricular function, greater exercise capacity, improved cardiac metabolism, and reduced symptoms of heart failure in animal models. The approach combines remuscularization with enhanced contractility, offering a novel therapeutic direction for chronic heart failure.
Major Revisions
Example: "Our goal was to improve regenerative strategies by genome-editing hPSC to make dATP-donor cells… Our results indicate that dATP donor CMs can… persistently improve the function of the chronically injured heart".
Mechanisms of dATP Delivery:
Example: "In vivo, dATP-producing CMs formed new myocardium that transferred dATP to host cardiomyocytes via gap junctions, increasing their dATP levels".
Long-Term Safety and Efficacy:
Minor Revisions
There are a few minor typographical errors and ambiguities in phrasing that can be corrected for better readability.
Figures and Diagrams Consistency:
The figures and diagrams should uniformly represent the data and should be referenced consistently within the text (e.g., Fig 6 referenced properly with aligned legends and labels).
Formatting and Style:
Recommendations
Conduct larger and more diverse animal studies to establish translational efficacy and safety across different species. This would bridge the existing gap between rodent models and potential human applications.
Detailed Mechanistic Studies:
Expand mechanistic studies on the biophysics of dATP transfer and integration into host cells, detailing the kinetics of dATP movement and concentration gradients across different heart zones.
Extended Safety Profiles:
Investigate long-term safety profiles of dATP elevation in vivo, focusing on electrical stability of myocardial tissues and potential non-target effects on other tissues/organs跨链接。
Human Trials:
Initiate phase I clinical trials after thorough preclinical validations to evaluate safety, dosage, efficacy, and delivery mechanisms in human heart failure patients.
Data Sharing and Reproducibility:
In conclusion, the preprint presents a promising approach to treating chronic heart failure using genetically engineered hPSC-CMs. Nonetheless, further work on validation, safety, and translational studies is essential to move toward clinical applications.
On 2024-12-05 23:03:05, user Dina Sarsam wrote:
There is increasing evidence suggesting an interplay between DNA damage response (DDR) and cellular metabolism pathways, specifically regarding the regulatory role of the DDR kinase Ataxia Telangiectasia and Rad3-related protein (ATR) and the metabolic regulator mechanistic Target of Rapamycin Complex 1 (mTORC1) in p16-low cancer cells. However, the mechanism by which ATR regulates mTORC1 activity remains poorly understood. To address these knowledge gaps, the authors of the Tangudu et al. manuscript investigated the role of ATR in activating mTORC1 in both unperturbed and p16 knockdown cell models. The findings of this study unveiled several key novelties including the role of ATR in modulating mTORC1 activity via de novo cholesterol synthesis under both low p16 expression and basal conditions. Additionally, lanosterol synthase (LSS), an enzyme that regulates the biosynthesis of cholesterol, is regulated by ATR, and ATR's regulation of mTORC1 is independent of the Checkpoint Kinase 1 (CHK1) and Tuberous Sclerosis Complex (TSC) pathways. Several innovative experimental techniques were employed within the course of the study, including the simultaneous proteomic and transcriptomic profiling used to identify transcriptional and post-translational changes in ATR signaling and the use of phospho-specific antibodies to monitor the effects of ATR modulation on mTORC1 activation at specific time points.
However, we have identified one major concern that we believe should be addressed prior to the publication of the paper.
The major concern that was found in the paper was that the mechanism of action for the ATR-mTORC1 pathway was not fully represented in all the broad ranges of cells in the data shown in the figures. The issue is that while in Figure 1 the expression of ATR and mTORC1 was shown through a broad range of cell lines, the latter portion of the paper focused primarily on SKMEL28 cells, a melanoma cell line, which does not fully represent the broad spectrum of the cellular model that the ATR-mTORC1 pathway has a role in general cell metabolism and proliferation. An experiment that could be done to address this major issue of underrepresentation of the ATR-mTORC1 expression in unperturbed cells, as well as diseased cells, is to repeat the experiments done from Figure 2 to Figure 4 in all cells that were used in Figure 1 (HeLa, HEK293, MEFs).
There are also some minor concerns we identified with the manuscript. One small issue is the lack of quantification or statistical analysis included in Figure 1. This would allow for a better understanding of the content of the figure. Another minor concern is the coloration of the fluorescence images in Figure 4. The chosen colors make it difficult to make out the overlaps in the merged images, especially in Figure 4B. This could be fixed by changing the colors to ones that are more distinct when merged. The final minor concern identified is the absence of GTPase Rheb in the working model. GTPase Rheb is included in the introduction as it plays a role in the activation of mTORC1 after localization to the lysosome. While the paper is focused on the localization of mTORC1, its activation by GTPase Rheb may also be affected by this mechanism.
On 2024-12-05 22:37:23, user Cecylia Olivo wrote:
The DNA Damage Repair (DDR) pathway, including ATR/ATM, have previously been linked to metabolism and mTORC1 regulation, however the key players and mechanisms, especially in unperturbed cells, in this downstream signaling pathway are currently unknown. This manuscript, authored by Aird et al., demonstrates that in both p16 knockdown cells and unperturbed cells, ATR increases lanosterol synthesis through de novo cholesterol synthesis, which promotes mTORC1 activity by lysosomal localization. They determined that this pathway consists of ATR, not ATM, and is independent of the CHK2 and TSC2 processes.
The paper contains several major concerns, detailed below, that must be addressed before the data can be properly evaluated. Until these concerns are resolved the findings within the paper are unable to be thoroughly assessed, delaying our understanding of how ATR influences mTORC1 during DDR.
The first major concern identified within the paper is the lack of orthogonal validation, specifically for Figure 4 A & B. This is a concern because, in order to validate the findings, different methods should be applied to confirm reliability, reproducibility and robustness. In Figure 4 A & B we are specifically relying on the visual trends to make a conclusion, which could be misinterpreted. The authors should perform Radiolabeled Cholesterol Uptake Assays which measure cell cholesterol absorbance by labeling cholesterol compounds with radioactive isotopes which would contribute to their orthogonal validation and help support their results. The second major concern is that phosphorylation of S6K is not limited to mTORC1. This is a major concern because S6K is a direct substrate for other kinases, such as JNK1 and PKC. Multiple validations are required to show that mTORC1 activity leads to the decrease in phosphorylation of S6K. One validation that can be conducted is to overexpress ATR to observe if phosphorylation of S6K increases, which would further support the direct link between mTORC1 activity and S6K phosphorylation. An additional validation is to conduct an in vitro kinase assay with mTORC1 and S6K to eliminate the possibility of confounding variables. The third major concern is that p16 expression can vary significantly between cell types. This is a major concern because HeLa cells have high levels of p16 expression, HEK293 cells have low levels of p16 expression unless under stress and MEFs have significantly higher levels of p16 as cells approach senescence. Quantifying the basal levels of p16 in each type of cell line is crucial since the focus is on ATR’s effect under basal conditions. This can be done by quantifying the levels of p16 through western blotting and testing if ATR affects mTORC1 similarly across varying expression levels.
The first minor concern is that the quantification of the western blots is needed throughout the paper in order to substantially improve the clarity of the figures. The second minor concern would be to provide justification about the selection of the specific cell lines which would provide clarity on the major concerns related to varying p16 expression. The third minor concern is that the verbiage of mTORC1 should be consistent throughout the whole paper to increase readability and reduce confusion. The final minor concern is that Figure 3’s title is unclear; replacing “decreases” with “knockdown” would be more effective.
On 2024-12-05 12:22:35, user xPeer wrote:
Courtesy review from xPeerd.com
Summary<br /> The study explores the development of human heart assembloids integrated with autologous tissue-resident macrophages to replicate physiological immuno-cardiac interactions. The research emphasizes the importance of this model for understanding heart development and disease. The authors provide a detailed methodology for generating the assembloids, coupled with multi-omic analyses and functional assays, demonstrating the model's capacity to emulate key cardiac and immune processes. However, while the study presents comprehensive data and a novel approach, certain areas require further clarification and detailed statistical analysis to strengthen the findings.
Major Revisions<br /> 1. Statistical Analysis: The study lacks detailed statistical information to support the presented data. Including p-values, confidence intervals, and statistical tests used for each dataset is crucial for validating the results (e.g., Figures and gene set enrichment plots).
Reproducibility of Methods: While the methods section is comprehensive, it would benefit from additional clarity on specific protocols to ensure reproducibility. Including precise details about reagents, equipment, and any variations in experimental conditions can aid reproducibility (e.g., generation of heart assembloids).
Integration of Findings: The discussion should integrate the findings more thoroughly with existing literature. Highlighting how the study advances the field and addressing possible discrepancies with previous studies will provide a stronger context for the research.
Limitations and Future Work: The discussion needs a more critical examination of the study's limitations, potential biases, and confounding factors. Proposals for future research directions should be specified to guide subsequent investigations.
Minor Revisions<br /> 1. Typographical and Formatting Errors:<br /> - Page 15, Figure 2 legend: The phrase "∆ë ëë ë ëëë" is a clear formatting error that needs correction.<br /> - Verify consistent formatting of subheadings and figure legends throughout the manuscript.
Definition of Terms: Ensure all technical terms, abbreviations, and acronyms are defined upon their first appearance. This will enhance readability for a broader audience.
Reference Formatting: Ensure all references are correctly formatted according to the journal's guidelines. Cross-check for the latest updates in cited references.
AI Content Analysis: Based on language consistency and technical depth, the estimated percentage of AI-generated content seems minimal. No sections explicitly exhibit characteristics typical of AI-generated text.
Recommendations<br /> 1. Enhancing Data Presentation: Incorporate more statistical data into figures and tables, such as error bars and exact p-values, to reinforce the reliability of the results.
Detailed Protocols: Append a supplementary section with detailed step-by-step protocols for key procedures to facilitate reproducibility by other researchers.
Expanded Abstract: Enrich the abstract with specific quantitative results to provide a clearer snapshot of the study's impact and conclusions.
Broader Impact Discussion: Expand the discussion on the broader implications of the model for disease modeling, drug testing, and therapeutic applications, tying it back to the study's findings.
This autonomous review aims to provide a comprehensive evaluation of the study, pinpointing critical areas for improvement while acknowledging its scientific contributions.
On 2024-12-05 03:18:42, user Arianna wrote:
The mechanism driving miRNA load and 3’UTR lengthening and its subsequent effect on mRNA half life, and the significance of mRNA stability mechanisms shaping gene expression and 3’UTR usage during human neurodevelopment are well documented. The manuscript by Ellis et al. investigates an alternative approach to systematically quantify transcription rate and mRNA stability using RATE-seq and SLAM-seq to further validate the relevance of miRNA loads among induced pluripotent stem cells (iPSCs), neural progenitors (NPC), and neurons (Neu). This approach expands on the role of mRNA stability in shaping transcriptional buffering and driving 3’UTR lengthening via miRNA load. <br /> The paper suggests a comprehensive approach towards understanding the regulation of mRNA stability and transcription rates during human neurodevelopment. The use of RATE-seq as a technique for measuring half-life and transcription rates was a powerful and novel approach to dive deeper into the current understanding of this field, and could be applicable to future studies. The authors also explore the idea of a mechanistic link between miRNA regulation and transcriptome changes. The reproducibility of results between cell types was reinforced that accumulation of miRNAs during neurodevelopment potentially leads to preferential degradation of short 3' UTR-containing mRNAs in neurons.
The manuscript outlined the following findings about neuronal differentiating cells: i) mRNA stability and transcription rate play an equal role in establishing steady-state levels of the transcriptome, ii) buffering genes controlled by pluripotency transcription factors are regulated by mRNA stability, iii) increased miRNA load corresponds to mRNA degradation of most genes in neurons, and iv) preferential degradation of neuronal short 3’ UTR-containing mRNAs resulting in decreased RNA stability. These are not novel findings to the scientific community but the reproduction of previous research is not without merit. Reproducibility is a hallmark of quality scientific discovery. However the novelty of this research is demonstrated in the unique sequencing protocols and statistical techniques utilized. Despite this achievement the paper doesn’t sufficiently expand the literature in such a way that qualifies it for publication. Given the issues outlined below, the manuscript must address the following concerns prior to acceptance for publication.
One of the most pressing major concerns is the lack of a discernable attempt to close the gap in knowledge regarding the relationship between mRNA stability and transcriptional regulation during neurodevelopment. Specifically, the manuscript demonstrates the shifts in mRNA stability and 3’UTR lengthening. These results have already been documented in previous literature thus leaving unclear how this research advances the field and our understanding beyond known mechanisms. The question of whether miRNA load is sufficient or necessary to drive 3’UTR lengthening should be addressed in any future iterations of this paper. The authors could address this concern by designing an experiment to validate the causal relationship between increasing miRNA load and 3’ UTR lengthening. This can be achieved experimentally by overexpressing miRNA in human cell lines and tracking subsequent increases or decreases in 3’UTR lengthening.
A second major concern that should ideally be remedied by the authors is the use of a single experimental cell line. To strengthen the quality of the research performed in this manuscript experiments should be orthogonally validated in other human cell lines. Justification of each cell line used should be explicitly mentioned in the manuscript. Additional tissue types can also be explored experimentally to strengthen the mechanistic link.
The minor concern that needs to be addressed by the authors of Ellis et al. is the addition of a justification of the time points used during data collection. This context will allow readers more insight into the overall logic of the experiment. It is generally understood that the chosen time points are typical when working with neural cells but this logic may not be clear to an individual not actively involved in the field.
On 2024-12-04 17:12:09, user Qingrong Huang wrote:
is the supplement table data available somewhere?
On 2024-12-04 13:08:38, user Xibing Xu wrote:
This preprint is now published in Nature communications, please check the online article, DOI: 10.1038/s41467-024-53931-w
On 2024-12-04 07:54:19, user MRR wrote:
Under Data availability, the authors write:<br /> "The authors declare that the data, materials and code supporting the findings reported in this study are available from the authors upon reasonable request."
This preprint is a publication, and data, materials and code should be made available in a open databases.
On 2024-12-03 20:57:12, user xPeer wrote:
Courtesy review from xPeerd.com
Summary<br /> This preprint introduces the novel concept of "oncoembryology" to analyze the shared molecular mechanisms of embryonic colon development and colorectal cancer (CRC). SoxC transcription factors (Sox4, Sox11, Sox12) are identified as critical regulators of embryonic programs reactivated in CRC, driving tumor progression and poor patient survival. Using murine and organoid models, the authors elucidate SoxC-driven pathways influencing chromatin remodeling, proliferation, and metastasis. Despite robust experimental frameworks, translational gaps and underexplored mechanistic details need addressing.
Major Revisions<br /> Mechanistic Elucidation
Insufficient Detail on SoxC-Driven Programs: The role of SoxC in chromatin remodeling and gene regulation is well-documented. However, indirect targets (e.g., Mdk) require deeper exploration. Linking protein networks (e.g., Figure 3A) to specific cellular processes in tumor microenvironments would enhance clarity (Section: Results, p.7).<br /> Immune Modulation Underexplored: SoxC’s regulation of immune-related genes (e.g., Mif, Il19) is introduced but lacks functional validation. Including immune cell profiling from tumor environments or patient samples could substantiate claims (Section: Results, p.8).<br /> Clinical Relevance
Translational Gaps: The manuscript emphasizes SoxC’s therapeutic potential but lacks direct discussion on pharmacological inhibitors. For example, the clinical applicability of targeting Tead2 or Mdk in CRC contexts remains speculative (Section: Discussion, p.10).<br /> Prognostic Model Validation: The SoxC-oncoembryonic signature is promising, but additional validation in independent, larger patient cohorts is essential to ensure reproducibility and clinical utility (Section: Results, p.9).<br /> Experimental Controls
Baseline Comparisons for SoxC Inhibition: While SoxC-KO models demonstrate tumor suppression, parallel experiments using standard chemotherapies or combination treatments would provide comparative benchmarks (Section: Results, p.8).<br /> Hindgut Model Robustness: The embryonic hindgut model is compelling but differs significantly from adult tumor environments. Supplementary experiments incorporating human organoids or ex vivo models could address potential translational limitations (Section: Methods, p.11).<br /> Data Presentation and Statistical Rigor
Incomplete Statistical Details: Kaplan-Meier analyses (e.g., Figure 3C) require hazard ratios and confidence intervals. Clarifying thresholds for “high” and “low” gene expression groups would strengthen interpretability.<br /> Underrepresented Raw Data: Additional raw data (e.g., ATAC-seq peaks, ChIP-seq binding sites) should be included to validate the claims of direct SoxC target regulation (Section: Results, p.6).<br /> Minor Revisions<br /> Typos and Formatting
Figures: Figure legends occasionally omit critical methodological details (e.g., staining conditions in Figure 5A).<br /> Grammar: Line 154, "which may be similarly drive CRC progression," should read "which may similarly drive CRC progression."<br /> AI Content Analysis
Estimated AI-Generated Content: ~10-15%.<br /> Implications: Stylistically consistent but occasionally repetitive phrases (e.g., "regulates both embryonic and cancerous programs") suggest AI-assisted drafting. This does not detract from the scientific rigor but indicates potential areas for manual refinement.<br /> Terminology Consistency
Key terms such as "oncoembryonic genes" and "progenitor maintenance" are inconsistently applied across sections. Standardizing definitions would aid clarity (e.g., Section: Introduction, p.2).<br /> Ethical and Methodological Transparency
The manuscript references ethical approvals but omits details about humane endpoints for animal studies (Section: Methods, p.11). Expanding on regulatory compliance would ensure adherence to ethical standards.<br /> Citations
References to foundational studies (e.g., Weinberg, 1996; Hanahan, 2022) should be balanced with more recent CRC-specific literature.<br /> Recommendations<br /> Mechanistic Depth:
Incorporate RNA-seq or proteomic analyses to map SoxC interactions with immune pathways and chromatin regulators.<br /> Validate indirect target regulation (e.g., Mdk, Tead2) using perturbation assays.<br /> Clinical Insights:
Expand discussion of SoxC inhibitors and therapeutic strategies, including potential combination therapies targeting chromatin remodeling.<br /> Data Enhancements:
Provide supplementary raw datasets for reproducibility, including ATAC-seq peaks and Kaplan-Meier survival data.<br /> Broaden Validation:
Validate findings in independent patient cohorts and alternative models, including humanized CRC organoids.<br /> Formatting and Precision:
Improve figure clarity, add comprehensive legends, and standardize terminology across sections.
On 2024-12-03 20:49:57, user xPeer wrote:
Courtesy review from xPeerd.com
Summary<br /> This manuscript investigates a novel locoregional therapy, MBC-005, targeting p21 induction via intratumoral percutaneous administration in BALB/c mice bearing breast cancer liver metastases. The work demonstrates a 3.9-fold increase in survival and tumor volume reduction through a hydrogel delivery system designed to mitigate hydrophobicity and enzymatic degradation of the active compound. While the study makes a strong case for MBC-005’s preclinical efficacy, there are gaps in experimental design, mechanistic exploration, and translational relevance.
Major Revisions<br /> 1. Mechanistic Clarity<br /> The manuscript attributes MBC-005’s effects to p21 induction but does not sufficiently explain how this mechanism influences overall tumor microenvironment dynamics, such as angiogenesis or immune modulation. Including downstream effects of p21 upregulation (e.g., cell cycle arrest versus immune response interplay) would improve the study’s depth (Section: Results, p.8).<br /> Further exploration of how N-allyl noroxymorphone interacts with the opioid growth factor receptor, specifically in liver-specific metastases, is required to justify its locoregional application (Section: Discussion, p.11).<br /> 2. Experimental Controls<br /> Absence of Baseline Control for Locoregional Therapies: Comparative efficacy with locoregional standards like radiofrequency ablation (RFA) or transcatheter arterial chemoembolization (TACE) is missing. This would contextualize MBC-005’s potential advantages (Section: Results, p.7).<br /> Dose-Response Study Gaps: Although the study evaluates a range of MBC-005 doses, a detailed dose-response curve for survival benefit is absent. Highlighting toxicity thresholds across doses would strengthen the rationale for the selected therapeutic window (Section: Results, p.9).<br /> 3. Translation and Scalability<br /> Translational relevance remains underdeveloped. For example, the manuscript does not discuss challenges related to scaling hydrogel administration for clinical imaging systems or variability in tumor sizes (Section: Discussion, p.12).<br /> Specific limitations of murine liver tumor models compared to human liver metastases (e.g., perfusion, immune differences) should be acknowledged.<br /> 4. Reproducibility and Statistical Rigor<br /> The manuscript does not provide raw data or error ranges in figures showing critical in vivo findings (e.g., Figures 3, 10). The absence of confidence intervals or standard error bars undermines the reliability of these results.<br /> Statistical comparisons (e.g., Figure 9 survival curves) are inconsistently reported. Inclusion of hazard ratios and Kaplan-Meier plots with confidence intervals is needed.<br /> 5. Safety and Toxicity<br /> While the manuscript claims MBC-005 induces no off-target toxicity, details on off-target organ effects are insufficient. Clinical chemistry and histopathology for other critical organs (e.g., kidneys, spleen, heart) would provide a more comprehensive toxicity profile (Section: Results, p.10).<br /> 6. Ethical and Methodological Transparency<br /> Ethical approval processes are ambiguously described, particularly regarding animal welfare protocols. Details about analgesia and endpoint criteria for euthanasia in murine models are essential (Section: Methods, p.4).<br /> Specific imaging protocols for tumor measurement (e.g., ultrasound or bioluminescence imaging) lack clarity regarding resolution and reproducibility parameters.<br /> Minor Revisions<br /> 1. AI Content Analysis<br /> Estimated AI-Generated Content: ~20-25%.<br /> Detected Issues: Over-reliance on templated phrases, particularly in introductory and summary sections (e.g., "poor prognosis; and, when treated with the standard of care systemic therapy they have a median survival of <9-months").<br /> Impact: While these sections are stylistically consistent, they weaken the originality of argumentation. Rewriting these areas to reflect a more critical and nuanced understanding of literature would improve epistemic integrity.<br /> 2. Figures and Tables<br /> Some figures, such as Figure 10 (Kaplan-Meier survival curves), lack clarity and appropriate legends to describe their analytical methodology.<br /> Tables presenting survival metrics (e.g., Table III) should incorporate statistical significance indicators.<br /> 3. Terminology Consistency<br /> Terms like "locoregional therapies" and "p21 induction" are inconsistently defined across sections, leading to potential reader confusion.<br /> 4. Citations<br /> Certain key statements lack direct citation support (e.g., "Locoregional therapies are appealing due to their minimally invasive nature"). Verify these with authoritative sources to enhance credibility (Section: Introduction, p.3).<br /> 5. Formatting and Typos<br /> Line 256: Repeated phrase "was also shown to be significantly decreased."<br /> Ensure uniform formatting of references (e.g., adherence to journal-specific citation styles).<br /> Recommendations<br /> Enhance Mechanistic Insights:
Integrate RNA-seq or proteomic analyses to identify downstream signaling pathways influenced by p21 induction.<br /> Evaluate immune cell infiltration or cytokine profiling in treated tumors to investigate secondary effects.<br /> Address Limitations:
Explicitly discuss how murine models differ from human metastases and any anticipated challenges in clinical translation.<br /> Improve Data Presentation:
Add confidence intervals, raw data, and Kaplan-Meier analyses for survival metrics.<br /> Ensure all figures include clear legends, error bars, and scale descriptions.<br /> Augment Comparisons with Existing Therapies:
Introduce comparative benchmarks with locoregional standards (e.g., RFA, PEI) to establish MBC-005’s potential superiority.<br /> Refine Ethical Transparency:
Provide detailed procedural descriptions for animal welfare compliance, imaging techniques, and dose administration.
On 2024-12-03 13:54:03, user Flor wrote:
Hi readers! This manuscript has been published now at The Plant Journal! On behalf of all the authors, I invite you to read it there! https://onlinelibrary.wiley.com/doi/10.1111/tpj.17159
On 2024-12-03 01:56:44, user Rishav Mitra wrote:
Review by Ziyue Zou, Rishav Mitra, and James Fraser
This manuscript provides a baseline comparison between current physics-based computational methods with machine-learning (ML) methods in predicting key thermodynamics properties in drug discovery – binding energy in presence of inhibitor (ΔΔG). Here three non-ML algorithms are studied against one existing ML model — Random Forest (RF), which was directly trained to predict this physical property in a previous study. The results suggest physics-based simulations in general provide better estimates compared to the ML/structural-based methods when benchmarking to experimental measures, especially against distal mutations. Overall the manuscript is well-written and provides a sufficient amount of detail in each methodology used.
Here are our comments:
The generalizability of the trained ML model is not immediately clear to us. It would be helpful if the author can include some data analyses on this model with the train/validation/test datasets in this manuscript to show the audience the performance of the model. How was the dataset different from Aldeghi et al. ACS central science 5, no. 8 (2019): 1468-1474? Will RF model predict better if it is trained on the Platinum database? Will a combination of Platinum database to data used in this manuscript improve the predicting ability of the model?
Following the previous comment, similar to neural nets, deep tree-based methods can be easily overfitted to the training data, is this also expected here?The NanoBRET vs. measurements in Hauser el al (2018) scatter plot and NanoBRET vs. RF plot look very similar to each other. Could that be evidence of overfitting to the dataset? Again it would be beneficial to present some results on model training.
As the authors summarized in the end, the physics-based simulation methods outperform structural/ ML-based methods. Does this mean by introducing structural descriptors to machine learning models, the predictions can be largely improved. This could be easily validated by retraining a RF model with additional (distal) features, which can be a valuable ML-based benchmark for future study.
While the authors provide a detailed investigation of the effects of forcefield selection in non-equilibrium perturbation (NEQ), the free energy calculations (FEP+) method does not seem well studied under various forcefield parameters. Is there a reason why OPLS was chosen for FEP+ and GAFF/CGenFF were selected for NEQ? If so, please elucidate.
The authors may want to comment on the utility of the training dataset from Hauser et al. (2018) given the importance of measuring the ΔΔG values for each TKI from a single measurement as demonstrated and alluded to in this paper.
Can the authors comment on the structural basis for the impact of distal mutations (Supp. Fig. 5, 6) which have a significant impact on inhibitor binding? It might also be useful to make a separate list for the identity of the mutated residue, their ΔΔG values, distance from the active site, RMSE and correlation values for these interesting mutations.
The RF model has been trained with mostly nearly-neutral point mutations. Is it expected to perform well for large-effect resistant or sensitive mutations for which experimental ΔΔG values are not within the 土1 kcal/mol range?
The authors assign a mutation as resistant if both the NanoBRET and computational approach predict an increase in ΔΔG by ΔΔG > +1 kcal/mol . What about the performance of the models on mutations for which the predicted -1 < ΔΔG < +1 kcal/mol, i.e., nearly neutral, but the clinically observed phenotype is cancer resistance or sensitive?
It is unclear if there are H-bond interactions between the water molecules within 0.4 nm from T315 and other chemical groups in the vicinity, such as backbone amides or a ligand atom. Are there features in the electron density map for the crystal structure of Abl kinase that indicate other water- mediated contacts in this site that might be disrupted by the T315A mutation?
Minor points:
Term “singular point” in PRAUC plots is only mentioned in the caption of Figure 5, it would be good to have it mentioned and defined in the main text, followed by a discussion on its significance.
What is the shaded region around the diagonal line in Fig. 2B?
What is the provenance of the “sensitizing” mutation L298F, it is unclear if this is patient derived or engineered?
On 2024-12-02 10:45:47, user Robert E White wrote:
Nice study. One question on the EBV transcripts: have you tried separating the reads into latency genes (EBNAs, EBERs, BARTs, LMPS) vs Immediate Early/Early vs Late? This might be quite informative as to the type of EBV biology you are observing (esp in PBMC). For instance I might expect Early and late reads in the nasal and airway samples (EBV lytic replication) whereas in the blood this could be either expansion of latency III blasts, or productive reactivation as they differentiate into plasma cells, or even an abortive replication [IE and E but no late transcripts] as they migrate to peripheral mucosal sites for transmission.
On 2024-12-02 00:02:22, user Iain Cheeseman wrote:
I really enjoyed this paper. The data that you curated looks very helpful. Would it be possible to include a supplemental table with the peptides that you identified in each of the categories?
On 2024-12-01 22:50:37, user Oki O'Connor wrote:
Very nice study. Are the authors looking at lifespan? They started with such old animals it shouldn't take much longer.
On 2024-12-01 16:53:12, user Clement Kent wrote:
Interesting work which advances the field. <br /> Just recording a few typos here. <br /> Line 103 refers to Allan(19) but no such item in the references.<br /> Line 8,16,18 - author Erclik listed with 2 identical affiliations.<br /> Line 188- put in the reference number. <br /> Lines 214 and 257 - tup is the Flybase standard name for this gene. I don't see why you insist on Islet. At any rate, italicize tup in 214.<br /> Line 393: optogenetically instead of optogenetic.<br /> Line 447: "for each of 32 hemilineages"<br /> Line 628 " obtained from"<br /> Lines 833,894,967 - update references
On 2024-11-30 22:24:18, user xPeerd wrote:
Peer review report from http://xpeerd.com
Summary<br /> The preprint presents a novel strategy termed Transient Overexpression of P-glycoprotein (P-gp) for Cardiac reprogramming (TopCare) aimed at mitigating doxorubicin (Dox)-induced cardiotoxicity in cancer chemotherapy. The approach employs lipid nanoparticles (LNPs)-based mRNA therapeutics to transiently overexpress P-gp in cardiomyocytes, reducing intracellular Dox levels and associated cytotoxic effects, both in vitro and in vivo. The study demonstrates promising results, including enhanced survival rates and improved cardiac function in treated mice and pigs. However, detailed analysis and validation in clinical settings are needed.
Major Revisions<br /> 1. Ethics and Concerns on mRNA Technology:<br /> The preprint does not provide comprehensive information on the long-term safety and potential mutagenic effects of repeated mRNA administration. Although the authors claim no potential insertion mutagenesis, a detailed toxicological assessment must be included.<br /> - Example: The long-term impact on genomic stability has been vaguely mentioned (Section: Results, Page 6) but needs further elaboration.
Example: The pig model data is summarized, but detailed statistical analysis and larger sample size validation are crucial (Discussion, Page 7).
Broader Relevance and Risk Mitigation:<br /> The potential immunogenicity of LNPs and mRNA therapeutics should be discussed to address the broader clinical relevance and possible adverse immune responses.
Recommendations<br /> 1. Enhance Toxicology and Safety Data:<br /> Include detailed data on the longitudinal impact of mRNA administration, focusing on potential genomic stability issues and systemic safety profiles. Consider supplementary studies evaluating mutagenic and oncogenic risks.<br /> 2. Comprehensive Animal Model Studies:<br /> Expand the large animal model studies to include a broader sample size and various cardiovascular conditions, supplemented with detailed histopathological analyses.<br /> 3. Immune Response Mitigation:<br /> Address potential immunogenicity by conducting comprehensive immunological assessments on treated animals and documenting any adverse reactions. Present a risk mitigation strategy for the clinical setting.<br /> 4. Expanded Clinical Relevance Exploration:<br /> Provide a more robust discussion on how to adapt the TopCare strategy to different cancer treatments, varying dosages, and combined therapies to ensure broader applicability.
Minor Revisions<br /> 1. Textual and Formatting Errors:<br /> - Correct minor typographical errors and ensure consistent formatting across sections. Specific errors to address:<br /> - Page 2, Title capitalization inconsistency ("Cardiac Reprogramm...").<br /> - Figure labels and axis titles should follow uniform font size and style (Section: Results).<br /> 2. AI Content Analysis:<br /> - Estimated AI Content: Approximately 10-15%.<br /> - Highlighted AI-Detected Sections: Repetitive and templated language indicating likely AI aid in introduction and discussion.<br /> - Epistemic Impact Assessment: The AI-generated segments maintain consistency but could benefit from nuanced, domain-specific language refinements to underline originality and expertise..
Overall, the preprint provides an innovative and promising approach to tackling cardiotoxicity in chemotherapy but requires crucial improvements and detailed validations before realistic clinical applications.
On 2024-11-30 10:38:30, user Balázs Vedelek wrote:
We recently read with great interest your paper titled “Adaptive protein coevolution preserves telomere integrity” and found your findings on the evolution of Drosophila telomere capping to be quite engaging. The topic of the current manuscript is essentially the same that we addressed earlier by biochemical and informatical means ( https://doi.org/10.1371/journal.pone.0142771 , https://doi.org/10.1098/rsob.210261) . Upon reading your work, we noticed that our earlier research in this area appears to have not been acknowledged. <br /> Given that, while the experimental approaches differ, both of our studies address essentially the same phenomena and build on the same underlying principles, we believe that proper acknowledgment of our studies would be a beneficial addition to your manuscript. <br /> We truly appreciate your contributions to the field and look forward to seeing how your research continues to evolve.<br /> Thank you for your attention to this matter.
On 2024-11-29 09:51:01, user Simon Gascoin wrote:
Dear authors<br /> I also revisited Roland et al. results in the light of our recent study on biases in Landsat greening trends by Bayle et al. (2024) https://www.cesbio.cnrs.fr/multitemp/is-antarctica-greening/
Bayle, A., Gascoin, S., Berner, L. T., & Choler, P. (2024). Landsat-based greening trends in alpine ecosystems are inflated by multidecadal increases in summer observations. In Ecography. https://doi.org/10.1111/ecog.07394
On 2024-11-28 11:08:54, user Marco Barreca wrote:
Dear all, the peer-reviewed version was out on 24 October, you can find it at this link: https://www.nature.com/articles/s41698-024-00730-7 <br /> The DOI is: https://doi.org/10.1038/s41698-024-00730-7
On 2024-11-27 23:21:01, user Monica Berger wrote:
Great preprint and I agree about the two basic types of hoaxes.
I keenly followed the Conceptual Penis hoax (Boghossian and Lindsay) as it unfolded in real time as I was writing my book on predatory publishing. Although it initially correctly stated that the Conceptual Penis hoax as exposing gender studies, he later says they published in a predatory journal. This is incorrect. There were peer review problems but no predatory publishing.
They submitted the article to a prestigious gender studies journal, NORMA: International Journal for Masculinity Studies, from Taylor and Francis. The journal rejected the article and transferred the article down to another T & F lower-tier open access journal, Cogent Social Sciences. This editorial process is called “cascading.” The less prestigious journal peer-reviewed it and, when it was accepted, requested an APC. After publication, the authors revealed the hoax, and the article was retracted; the journal explained that the peer reviewers for the lower tier publication lacked experience. See: https://www.skeptic.com/reading_room/conceptual-penis-social-contruct-sokal-style-hoax-on-gender-studies/
On 2024-11-27 10:42:17, user S. Bachellier-Bassi wrote:
Why is Candida albicans grown in a medium designed for bacteria ? Does it influence the efficiency of hyphal development ?
On 2024-11-27 03:40:20, user rdshrestha wrote:
Interesting work, but the assertion that 'CNTN2 known to plays a role in murine retina development but not in human' is not accurate. In recent study, utilizing human telencephalon-eye organoids, we demonstrated the expression of CNTN2 in human retinal development. We highlighted its differential expression in early RGCs of human fetal retinas, suggesting its potential as a marker for RGC isolation and underscoring a conserved role in retinal development across species. Reference: https://doi.org/10.7554/elife.87306
On 2024-11-26 19:42:30, user Shelley wrote:
Well cocaine and heroin isn't the same thing at all one is more targeted than the other...
On 2024-11-26 15:54:10, user Prof. T. K. Wood wrote:
Congratulations on your discovery of a novel hibernation factor.<br /> 1. p. 11 middle paragraph has some unintended text.<br /> 2. p. 3: why not include the mechanism of ppGpp to 100S via RMF/Hpf for persister cell formation and 100S undimerized with HflX to resuscitation (low ppGpp) since it is related and mechanistic for the physiological relevance of hibernating ribosomes ( https://doi.org/10.1016/j.bioflm.2019.100018 )?
On 2024-11-25 14:04:59, user Chie Kodera wrote:
Hello,<br /> This article is already published here.<br /> https://www.degruyter.com/document/doi/10.1515/mim-2024-0002/html <br /> Can I ask you to put the link?<br /> Thank you.
On 2024-11-25 14:02:29, user Chie Kodera wrote:
Hello,<br /> This article is already published here.<br /> https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-021-07503-7 <br /> Can I ask you to put the link?<br /> Thank you.
On 2024-11-25 11:52:43, user Ronan O'Cualain wrote:
Please consider referencing the work done by Herrera et al ( https://pubmed.ncbi.nlm.nih.gov/32565759/ ) which includes AFA ultrasonication, S-trap sample processing, and DDA of FFPE micro-dissected sections.
On 2024-11-25 11:32:41, user Sebastien Leclercq wrote:
That is a nice study, well done, although not bringing breakthrough ideas : it is not a great surprise that conjugative plasmids PTUs are more prone to spread AMR genes than non mobile ones, and are also more prone to recombine because they meet more unrelated DNA. At least it is now demonstrated.
I however have some doubt about the host range analysis, because the methods applied are not very clear. It is written that the host range was assigned with COPLA (l.159). But I guess that the host range inferred by COPLA includes all plasmids in their database for each PTU, including some containing AMR genes. So in the last (and most important) section of the manuscript, removing the ARG-carrying plasmids from the AMR+ PTUs will not change the host range classification given by COPLA. <br /> This bring an inconsistency between the given host range and the actual plasmids in the 118 ARG-free PTUs investigated.<br /> My feeling is that the rare grade V+VI PTUs are actually caused by ARG carriage, bringing a great fitness advantage in very distant bacterial hosts in which plasmids should otherwise struggle to maintain because of maladaptation.<br /> It will be necessary I think to calculate the host range only with the data investigated in the study, simply by looking at the plasmid's host taxonomy and not rely on COPLA results. Like this it can be calculated independently for the various sets of PTUs (with/without pAMR).
Other samll comment : in figure 2 355 PTUs containing 13,048 plasmids are given in top panl but less than 8000 plasmids and 50 PTUs are given in bottom panel, and it is not indicated what was the display threshold in bottom panel. Please provide the threshold.
On 2024-11-23 00:09:48, user Lee Bardwell wrote:
Nice work! Are the supplementary tables available?
On 2024-11-22 19:56:01, user Giovanni Bussi wrote:
Authors of the review
Giovanni Bussi, Ivan Gilardoni
This report was written after a journal club given by GB in the bussilab group meeting. All the members of the group, including external guests, are acknowledged for participating in the discussion and providing feedback that was useful to prepare this report. The corresponding author of the original manuscript was consulted before posting this report.
Summary
The authors introduce a method to perform maximum entropy reweighting of molecular dynamics (MD) trajectories, specifically addressing the choice of regularization parameters. Interestingly, an automatic procedure to determine the relative strength of the regularization terms acting on different experimental datapoints is proposed. The method is then applied to extensive MD simulations of 5 intrinsically disordered proteins (IDPs) using 3 different force fields. For 3 of the tested IDPs, different simulations converge to the similar ensembles after reweighting. For the other 2, the ensemble overlap is too limited, and the reweighted ensemble is significantly force-field dependent.
We are mostly interested in the methodological part of the paper. Technical innovations are:
* The idea of including the statistical error of the MD, as computed with block analysis, in the regularization term.<br /> * The idea of performing preliminary regularization scans for individual sets of experiments to tune the relative uncertainty, and ultimately end up with a single parameter (prefactor) to be tuned.<br /> * The idea of tuning the parameters monitoring the Kish sample size.
To our knowledge, the comparative results for the 5 IDPs and 3 force fields are also new and very relevant.
Comments
* Could there be some speculation by the authors on the relative role of the water model and of the protein force field? The way results are presented, it is not clear if the reason for the discrepancies is in the protein force field or in the water model. Maybe it is not possible to disentangle them.<br /> * The authors evaluate the errors of the employed forward models by applying the Flyvbjerg block analysis method, which only estimates statistical errors, without keeping into account possible systematic errors in the forward models themselves. We would suggest to clarify it in the text.<br /> * In many sentences of the main text, the authors use the word "weight" to refer both to the statistical weight of each frame in the trajectory and to the strength of the experimental restraints. To avoid undesired misunderstandings, we suggest to use words like "strength" or "confidence" of the experimental data/restraints etc.<br /> * Figure 2B is unexpected. The authors used the derivation from Cesari et al JCTC (2016) to introduce uncertainty in the experimental observation. This is formally equivalent to BioEn (Koefinger and Hummer, 2015) if the theta hyperparameter is set to 1. If we understood correctly how the global scaling was applied, its scan would correspond to a scan over theta in the BioEn formalism. When doing so, it can be proven analytically that the chi^2 should be a monotonic function of the regularization hyperparameter. Hence, when the authors decrease sigma_global, the average RMSE should decrease monotonically. However, in the figure all the reported RMSEs seem to be increasing for sigma → 0, so their average will increase. This seems inconsistent. Is this related to some issues with the minimization process (e.g., minimizations with a very low sigma are not converging)? Or is there something we misunderstood in the explanation?<br /> * The perfect match of the SAXS data for PaaA2 for the AMBER force field (before reweighting) is striking. Was perhaps the force field optimized using this system as a reference? If so, we would suggest to mention this in the text.<br /> * “An IDP ensemble containing ten consecutive residues [...] neighboring residues”. This is super interesting. Could the author explicitly compute this and show it? We believe it is a very interesting example of what can be observed in an MD simulation and not in a bulk experiment, and so it would be relevant to know if the answer is force field dependent or not. For instance, one could plot a 2D map with DDG associated to the helical content.<br /> * The authors quantify the similarity of two ensembles by computing the normalized overlap integral of the kernel densities in the ELViM latent space. This quantity is, by construction, sensitive to this particular choice of the ensemble representation, based on the C\alpha carbon atoms, which is in effect a dimensionality reduction. We agree that it is in practice unfeasible to evaluate the similarity between ensembles sampled in different MD simulations using quantities that do not rely on dimensionality reduction. However, when comparing reweighted with unbiased ensembles, we expect the Kish sample size to be relatively low (around 0.1), whereas the shown density overlap S is high (>0.66 for all the examined IDPs - values along the diagonal in Fig. 8B). Does this happen because the employed dimensionality reduction (based on C\alpha carbon atoms) focuses more on some robust part of the structural ensembles, preserved by the reweighting? Or is it because two different (possibly uncomparable) metrics are used?<br /> * The authors comment that leave-one-out cross validation should not be used with correlated data, and claim that this is the reason for the unexpected good performance of cross validation in Figure 2C. This is very interesting as, to our knowledge, has not been seen before. Adding more points in the low-Kish-size region might be interesting.<br /> * At some point the authors write "We note a conceptual similarity of the reweighting procedure proposed here with the concept of gentle ensemble refinement in the recently published work of Kofinger and Hummer.32 " We believe the authors meant to cite Ref. 33 rather than Ref. 32.
On 2024-11-21 18:12:02, user Diane Codding wrote:
Please update to the published article: https://doi.org/10.3998/tia.5109