On 2025-08-21 07:50:25, user Thibaud Decaens wrote:

Now published in Global Change Biology, 27, 4575–4591. https://doi.org/10.1111/gcb.15752

On 2025-08-21 07:46:54, user Thibaud Decaens wrote:

Now published in Science Advances, 13 Aug 2025, Vol 11, Issue 33. DOI: 10.1126/sciadv.adx4909

On 2025-08-20 15:18:28, user Elin wrote:

Hi,

Nice manuscript! But I can't find the supplementary files that are referred to in the manuscript.

Best,<br /> Elin

On 2025-08-20 14:02:09, user hinata wrote:

no supplementary, no methodology part

On 2025-08-19 19:07:24, user Eric Miller wrote:

The authors present interesting information showing that a KD could enhance glutamine uptake when glucose is reduced through KD thus suggesting that glutamine targeting would be effective for managing pancreatic cancer when employed together with KD therapy. Mukherjee et al. presented a similar therapeutic strategy but with an explanation for the therapeutic effect different from that of the author’s ( https://doi.org/10.1038/s42003-019-0455-x) . It is important for the authors to address the different explanations for the similar findings in their discussion.

Besides an anapleurotic explanation for the role of glutamine in driving tumor growth, the authors should also address a role for mitochondrial substrate level phosphorylation in the glutaminolysis pathway as an additional explanation for the effect ( https://doi.org/10.1080/17590914.2024.2422268) .

The authors assume that ketone bodies and fatty acids are critical fuel sources for pancreatic tumor cells based on their finding of labeled TCA metabolites derived from beta-hydroxybutyrate and caprylic acid. No evidence is presented showing that the pancreatic tumor cells can survive on these fuels in the absence of glucose and glutamine. Caution is needed in considering labeled TCA metabolites as evidence for fuel utilization in the absence of viability studies.

Abnormalities in mitochondria structure and function are found in pancreatic cancer (https://doi. org/ 10. 3109/ 01913 123. 2013. 788306; https:// www. ncbi. nlm. nih. gov/ pubmed/ 6185201; https:// www. ncbi. nlm. nih. gov/ pubmed/ 968802). Such abnormalities would obstruct efficient utilization of fatty acids and ketone bodies for ATP synthesis. The authors must address the question of how ketone bodies and fatty acids can be critical fuel sources in pancreatic cancer showing abnormalities in mitochondria structure and function. Support for the author’s assumption would come from bioenergetic evidence showing that the MIA-PaCa2 cells die in hypoxia and cyanide, which would be expected for cells dependent on fatty acids & ketone bodies for fuel. No credible evidence is presented showing that the MIA-PaCa2 have normal mitochondrial function.

The authors mention (reference 22) as an example of a "push-pulse" strategy, where a ketogenic diet nudges a system towards greater dependency on a specific metabolic program, which in turn exposes new dependencies. This paper is incorrectly cited as there is no mention of a "push-pulse" strategy in the paper. The correct terminology is “Press-Pulse and was first presented in the following paper, which is the correct citation (DOI 10.1186/s12986-017-0178-2).

On 2025-08-19 12:25:54, user Emmanuel Beaurepaire wrote:

Nice work. <br /> A few suggestions for improvements to the optical explanations:<br /> - You suggest that the improvement in imaging depth achieved in THG in your experiments is mainly related to the wavelength used. But 1320 nm probably does not make a significant difference compared to 1150 nm. In fact, your gain compared to the other work you cite is mainly due to the use of 1 MHz OPA excitation.<br /> - You write “In previous work, we showed that the intensity of the THG signal from a slab of lipid surrounded by water increases exponentially with slab thickness” -> it is actually quadratically

On 2025-08-19 01:16:11, user Misha Koksharov wrote:

Will there be an update including Boltz-2 and IntelliFold?

On 2025-08-18 13:24:12, user Thijs J.M. van den Broek wrote:

This manuscript has now been published and can be found here: https://doi.org/10.1093/neuped/wuaf002

On 2025-08-18 08:16:39, user Rishi Raj Singh Rathore wrote:

very much information is provided

On 2025-08-17 18:35:09, user Debal Deb wrote:

Nice photographs. And very nice of the authors to cite Debal Deb's pioneering work with Jugal.

On 2025-08-17 15:51:16, user Gavin McStay wrote:

This is a really interesting and compelling paper indicating the inner mitochondrial membrane protein ATAD3 is an essential component of the mitochondrial permeability transition pore. There is compelling evidence based on the mouse and mitochondria lacking ATAD3 where mitochondrial swelling and calcium handling are impaired and ischaemia and reperfusion injury in the heart is reduced. There is also evidence of pore-forming activity of purified ATAD3. It would be interesting to see how these mice and mitochondria with ATAD3 deleted compare to other mice and mitochondria with other putative component deletions. Also, it would be useful to know more about the ATAD3 protein used in the patch-clamping assays - how was it expressed and purified? There is also the question of the ATAD3 isoforms, how do they differ and do they all act the same.

On 2025-08-16 21:57:06, user Eric Helms wrote:

You report a non-significant p-value of 0.97 in the text for the relationship between 1RM and MVC changes with muscle volume changes, but the figure correctly shows a statistically significant p-value of 0.032. The value in the figure is the correct one based on the reported sample size and r-score. Further, in your subsequent discussion, may aspects are based on this error.

On 2025-08-15 21:11:01, user Curt F. wrote:

Congratulations on a clear, readable paper and all the solid improvements made to Casanovo v5. I'm a happy user of Casanovo v5.

I'd invite the authors to consider analyzing calibration accuracy (Figure 1a) as a function of peptide length. Consider a 5-mer and a 10-mer peptide, each which has identical residue-level scores of 0.9 at every position. Earlier versions computed overall scores from the arithmetic mean, and this calculation is length-independent, so the version-4-score of both the 5-mer and the 10-mer will be 0.9. But v5, the product of the residue-level scores is used, and this is not length independent. The v5 score will be 0.59 for the 5-mer and 0.35 for the 10-mer.

The behavior of v5 might well be preferred, for many reasons! And if a calibration curve like that in Figure 1a, but only considering short peptides, looks similar to a curve that only considers long peptides -- i.e. both short and long peptides are equally well calibrated, then the authors will have demonstrated one such reason. Alternately, if calibration accuracy is different for short and long peptides, this would be valuable for users to know.

On 2025-08-15 17:01:35, user Rudian Zhang wrote:

The access to the dataset (Figure 2C) requires credentials.

On 2025-08-15 09:06:18, user Alex Zhavoronkov wrote:

Did you see this paper? <br /> Machine Learning on Human Muscle Transcriptomic Data for Biomarker Discovery and Tissue-Specific Drug Target Identification<br /> https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2018.00242/full

On 2025-08-15 02:29:28, user Rahagir Salekeen wrote:

Interesting work - minor error in the text: p21 is a product of the CDKN1A not CDKN2A locus :)

On 2025-08-14 16:00:15, user Shivangi Gupta wrote:

I am not able to find the Supplementary material related to this article. Can I get access to it?

On 2025-08-14 14:56:42, user Olavo Amaral wrote:

Congratulations on the work! This is an impressive achievement, and it's refreshing to see a particular research community conducting a large-scale metaresearch endeavour to reflect upon itself.<br /> That said, based on these results, I’m not sure I’d jump to the conclusion that Drosophila immunity has a replication rate that is higher than in other areas. Some of the studies cited as reproducibility estimates in other fields (Amaral et al. 2025, Errington et al. 2021), as well as large-scale efforts in psychology (e.g. Open Science Collaboration, 2015) and economics (Camerer et al., 2016) that helped spur the “replication crisis” narrative, have relied on performing independent replications of a particular sample of publish findings. This is quite different from reviewing the literature to look for conceptual replications, as the authors do to arrive at the conclusion that most of the findings in the field are verified (i.e. around 84% of those for which a published verification attempt was found).<br /> Interestingly, for the findings which the authors do replicate independently, replicability is much lower (only 16%). Although this large discrepancy may be explained by the fact that the authors focused on unchallenged and suspicious claims (which seems to be their preferred explanation), an alternative hypothesis is that there is a huge amount of confirmation bias in the Drosophila immunity literature, either because attempts to replicate previous findings tend to reach similar results due to researcher bias, or because results that validate previous findings are more likely to be published.<br /> As I think both explanations are plausible (and, not being an expert in the field, I’d have a hard time estimating their relative probability), I think the work would be greatly strengthened if the authors tried to replicate a sample of those findings that were validated in the literature. If they arrive at a similarly high replication rate, this would strongly support the authors’ interpretation of a high replicability of findings in the Drosophila immunity literature. If replicability is much lower in the authors’ independent replications than in the published ones, on the other hand, this would suggest that the high replicability estimate obtained from the literature should be taken with a grain of salt, and could be due to a large confirmation bias problem.<br /> I obviously understand that this would be a lot of work, but I do think it would matter a lot in terms of making skeptics (including myself) agree with the claim on high replicability.

On 2025-08-14 14:35:33, user Chen Chen wrote:

Good job! This study developed a high-resolution CRISPR lineage-tracing platform, eTRACER, which integrates single-cell and spatial multi-omics to reveal dynamic cellular trajectories, while avoiding target loss issues commonly caused by multi-site editing.

On 2025-08-14 14:20:04, user J Sloan wrote:

Published here: https://doi.org/10.1002/pld3.549

On 2025-08-14 09:43:29, user Lakhansing Pardeshi wrote:

Now published in Microbial Genomics. https://doi.org/10.1099/mgen.0.001392

On 2025-08-13 23:32:05, user Jeff Ellis wrote:

“Our findings suggest an experimental framework for predicting evolutionary outcomes of pathogen effector-host target interactions with implications for plant disease resistance breeding.”

This statement at the end of the abstract and end of discussion intrigued me. I asked the question what are these implications and how could these be used in disease resistance breeding? I think the statement begs at least some explanation and discussion. If not supplied I suggest that the statement should be deleted.

On 2025-08-13 19:59:00, user Roland wrote:

Hi Authors, was it an Astral or Exloris 480, as stated in the abstract?

On 2025-08-13 18:16:34, user Robert wrote:

Conveniently missing a citation too https://pubs.rsc.org/en/Content/ArticleLanding/2025/SC/D4SC08402K which already shows hexose formation in water microdroplets from some chemicals used. This work was published long before this work was submitted.

On 2025-08-13 17:34:25, user Ruslan Dmitriev wrote:

Now published as:<br /> Okkelman, I.A., Zhou, H., Borisov, S.M. et al. Visualizing the internalization and biological impact of nanoplastics in live intestinal organoids by Fluorescence Lifetime Imaging Microscopy (FLIM). Light Sci Appl 14, 272 (2025). https://doi.org/10.1038/s41377-025-01949-0

On 2025-08-13 17:31:55, user Ruslan Dmitriev wrote:

Now published in: <br /> ACS Nano<br /> Cite this: ACS Nano 2024, 18, 19, 12168–12186<br /> https://doi.org/10.1021/acsnano.3c12539 <br /> Published April 30, 2024<br /> https://pubs.acs.org/doi/full/10.1021/acsnano.3c12539

On 2025-08-13 15:58:57, user Piyush Sharma wrote:

This preprint is now published in nature immunology . Please link the published article with the preprint. <br /> Article: https://www.nature.com/articles/s41590-025-02223-6

On 2025-08-13 09:51:08, user Satyendra Mondal wrote:

Interesting manuscript. Figure 4 was uploaded twice (both as Figure 4 and Figure 5), though the correct figure is uploaded in the main PDF. All the best!

On 2025-08-12 18:47:17, user Fran Alvarado Guillen wrote:

This work has been published in Nature Cardiovascular Research:<br /> https://www.nature.com/articles/s44161-025-00693-3

On 2025-08-12 15:24:13, user aleksejzelezniak wrote:

published journal version: https://onlinelibrary.wiley.com/doi/full/10.1002/pro.5239

On 2025-08-12 14:00:19, user Gil Benard wrote:

I really appreciated this work — an in-depth analysis of replicability in science. It presents many important and interesting findings that contribute to the current discussion on reproducibility “crisis” and science integrity. I was particularly impressed by their report of sizable heterogeneity among the results of the replicating labs, despite the fact that (a) they were theoretically under neither publication pressure nor any other pressure from the science environment, (b) protocols and reagents were carefully checked and standardized among the labs, and (c) the experiments were conducted under very controlled conditions.<br /> Could there be intrinsic limitations to replicability in biomedical science?

On 2025-08-12 11:32:26, user Christopher wrote:

The supplementary information is not available. no link to it.

On 2025-08-12 08:12:30, user Florent Morio wrote:

Great work. The fact that Mrr1 also contributes to reduce the susceptibility to 5FC is interesting as it may have a clinical impact. We observed the same phenomenon in Candida parapsilosis after introducing a gain of function mutation in MRR1 (Hartuis et al., AAC 2024 PMID 38624217).

On 2025-08-12 07:47:30, user ME de Jong wrote:

This preprint has now been published in Behavioral Ecology: https://doi.org/10.1093/beheco/araf071

On 2025-08-11 14:10:51, user Noah Lemke wrote:

Please find the published version of the manuscript here:

https://doi.org/10.1163/23524588-bja10275

On 2025-08-11 03:16:21, user Sean Lim wrote:

Below is the link to my review!

https://zenodo.org/records/16790781

On 2025-08-10 14:35:13, user Aparna Watve wrote:

Hallo Prathamesh and Siddharth. Thanks for sharing this pre-print. Congratulations on a detailed study of this endemic species. <br /> I agree with you that a detailed Red List assessment is necessary and this data will certainly help. In this regards, I have a few suggestions for the paper.<br /> 1. Please do not criticize earlier assessment as based on literature survey and lacking field data. Many assessments start like this, as there is often data gap due to lack of local/regional research. It is perfectly valid to conduct an assessment with available data, as the purpose of assessment is to draw attention of conservation world, not to produce a paper. There is always possibility of re-assessment, in fact there are clear rules on how to go for it in Red List system. You can notice that the assessment clearly states "needs updating" on the Red List site. <br /> 2. If you want to conduct this assessment, its best to first take the assessor's training course https://www.conservationtraining.org/course/ which is necessary, if not mandatory. It can clarify many key terms. <br /> 3. If you have used modelling for the assessment work, it is necessary to get it validated as per Red List norms. The guidelines are openly available. <br /> 4. Coming to the assessment, an occurrence point map is needed and you can use GeoCAT app to calculate EOO and AOO.<br /> 5. If the EOO and AOO, are fitting within EN, you need to put a proper argument for (a) or (b)(i,ii,iii,iv,v) . Do you have data to say <br /> a. Species is severely fragmented? (even if you have not collected it, it is possible and accepted to make an informed guess based on species behaviour and biology) <br /> b. If not, then it hinges on the number of locations. Please do not equate this with occurrence points or localities. There is a specific definition of "location" which requires proper understanding of threats. <br /> c. continuous decline in habitat quality/extent etc can be definitely argued (known the habitat well), but that argument has to be detailed and based on hard evidence. <br /> There very specific evidence based reasons as to why EOO, AOO are mapped, calculated in a specific way. So although you may have different or more detailed data or view of it, unless you are able to put it in technical manner accepted by Red List, it would not be accepted. My suggestion is complete the training course, and then start a proper assessment. I will be happy to help you with the basics, but for actually updating the assessment in the online portal, you will have to contact and work with the relevant species specialist group.

On 2025-08-09 18:48:13, user curiousresearcher1908 wrote:

The authors should cite DOI: 10.1038/s41594-025-01610-9, which formally proves the existence and structure of the metazoan RAVE complex, composed of DMXL1/2, WDR7, and ROGDI. This study also elucidates mRAVE's function and mechanism of action.

On 2025-08-09 08:35:22, user Matthew Bowler wrote:

Now published in J Biol Chem https://www.jbc.org/article/S0021-9258(25)02429-9/fulltext

On 2025-08-09 00:08:45, user Andreas Baumler wrote:

Dogma Check:

A Salmonella T3SS-2 mutant grows fine in spleen macrophages, contradicting tissue culture dogma (PMID: 23236281). This observation was largely ignored, but here Garcia-Rodrigues et al. show that adding certain carbon sources rescues growth in cultured macrophages, hinting that T3SS-2 may be doing something entirely different in vivo.

On 2025-08-08 17:10:33, user Reviewer 6 wrote:

A major flaw with this work, which none of 3 eLife reviewers point out, is that they only show results until the F2 generation and claim that this independently validates "transgenerational inheritance". However, in the original assay the learning is carried out on adult worms with F1 embryos (and germ cells) in utero which are exposed along with the parent (P0) to the pathogen. For maternal inheritance, effects at F2 are generally still considered intergenerational (ie maternal) effects - not "transgenerational" epigenetic inheritance. The effect would have to be shown at F3 (and also F4 as the original Murphy study showed) for them to really claim validation of the study.

I refer the authors to the following review (PMID: 24679529), cited >2000 times, on transgenerational epigenetic inheritance which clarifies this point: "In the case of an exposed female... the fetus can be affected in utero (F1), as can the germ line of the fetus (the future F2). These are considered to be parental effects, leading to intergenerational epigenetic inheritance. Only F3 individuals can be considered as true **trans-generational ** inheritance (see Box 1), in the absence of exposure."

Given the F2 effect in this eLife study is already quite small, its imperative that the authors show F3 and F4 data to actually test the original Murphy claim. Moreover, in some of the Murphy experiments, effects at F3 and F4 are even stronger than they are at F1. So, this should not be a problem if the authors have actually replicated the Murphy results.

On 2025-08-07 22:33:07, user Evan Perkowski wrote:

Please note that this manuscript is now published in Journal of Experimental Botany: https://doi.org/10.1093/jxb/eraf118

On 2025-08-07 14:13:30, user michael peters wrote:

We developed a fragment discovery algorithm some time ago for the de novo design of intrinsically disordered proteins/peptides. As an example we targeted to HIV GP41. (Current Enzyme Inhibition, 2017, 13, 1-7; PMCID: PMC5411995 PMID: 28503119)

On 2025-08-06 17:18:29, user Swathy Babu wrote:

@bioRxiv<br /> This manuscript is now published. https://www.nature.com/articles/s41467-025-61937-1 <br /> Please add a link to the published version.

On 2025-08-06 14:42:59, user Bill Martin wrote:

This is an interesting paper.

On 2025-08-06 08:18:07, user AngelPerezDiz wrote:

This paper has now been published in the journal CRYOBIOLOGY. https://doi.org/10.1016/j.cryobiol.2025.105288

On 2025-08-06 03:48:07, user Guei-Sheung Liu wrote:

The manuscript has been published as follows:<br /> Platelet-derived extracellular vesicle drug delivery system loaded with kaempferol for treating corneal neovascularization.<br /> Liu GS, Chen HA, Chang CY, Chen YJ, Wu YY, Widhibrata A, Yang YH, Hsieh EH, Delila L, Lin IC, Burnouf T, Tseng CL.<br /> Biomaterials. 2025 Aug;319:123205. doi: 10.1016/j.biomaterials.2025.123205. Epub 2025 Feb 24.<br /> PMID: 40023929

On 2025-08-05 19:16:26, user Jacob S wrote:

wow super informative ???? fantastic

On 2025-08-05 13:29:54, user Prof. T. K. Wood wrote:

Please see two other 'rare' prophage-driven 'complex and fundamental' effects of phage on metabolism:

1. doi:10.1111/1462-2920.15816 for prophage control of host resuscitation from the persister state

and

1. doi: 10.1128/spectrum.03471-23 for a prophage protein increasing survival in bile.

On 2025-08-04 18:32:32, user Leslie Biesecker wrote:

Wonderful work. I wonder if you should replace most, if not all, occurrences of the word "conserved" with a form of the word "identical". "Conserved" (in the protein context) can mean identity or similarity, the latter being a more elastic term, that can depend on which matrix you choose and then your definition of the degree of similarity that you determine to meet your definitional threshold. Reading this preprint, I have the feeling you mean identical amino acids when you say conserved amino acids. Or maybe "conserved" means similar and "fully conserved" means identical? Would be great to clarify this. <br /> Note that we use likelihood ratios to calibrate evidence for clinical variant classification, not sensitivity and precision. In your first pass you had 4,328 & 26,006 for the P/LP variants and 245 & 16479 for the B/LB. That yields LR+ of 1.55:1 and 1/LR- of 7.25:1. That would not meet the supporting criterion (+1 Bayes conditional probability points) for pathogenic evidence. It would meet moderate evidence (-2 Bayes points) for benign evidence. When you increased stringency, you got 3,884 & 26,450 for P/LP and 102 & 16,622 for B/LB. That again does not meet the supporting threshold for pathogenic evidence (1.6:1) but it does strengthen the benign evidence with 1/LR- or 15:1 (between moderate and strong, -3 points). Not sure I am doing the math correctly from your data - feel free to correct me if I am wrong about this.

On 2025-08-04 17:29:56, user Jon Fisher wrote:

Does anyone know if this paper was ever submitted for peer review and published?

On 2025-08-04 16:03:22, user Julian C wrote:

(Note from the corresponding author) To appear in J Prot Res.

On 2025-08-04 09:35:07, user Ivan Martin wrote:

The manuscript offers a paradigm example on how to address the controversially discussed use of MSC for treatmnent of OA. The authors pave the way to define scientifically grounded criteria enabling to predict clinical outcomes, connecting the spaces of cell quality and patient characteristics. The study has been carried out with a limited sample size, but should be prospectively extended with more data generated by multiple groups. This will be pivotal to develop international clinical guidelines and to dissect more indepth the mechanism of action of such treatments.

On 2025-07-28 14:12:54, user Daniel J. Weiss MD PhD wrote:

This is a timely and important analysis broadly assessing both physiologic/pathophysiologic, molecular, and clinical factors influencing outcome of MSC administration for knee arthritis. This field has had mixed success so far and identifying critical attributes that not just better predict success but offer more advanced consideration of MSC and patient critical quality attributes is an important evolutionary step. This is all the more important considering the range of unproven therapies offered for orthopedic issues by a number of clinics not just in Canada and the US but worldwide. National and global orthopedic societies should strongly consider guidelines based on the analyses in this article.

On 2025-08-04 08:59:45, user Julian Downward wrote:

This paper has now been published in Cancer Research https://doi.org/10.1158/0008-5472.CAN-23-2814

On 2025-08-03 18:34:18, user gary stormo wrote:

This paper is now published in NAR https://doi.org/10.1093/nar/gkaf739

On 2025-08-03 16:43:34, user Милан Рајевац wrote:

There were two Rurikids named Sviatoslav III. The one that was paternal ancestor of Duke Bela of Macso belonged to the Olgovichi branch, and was the son of Vsevolod II, the Grand Prince of Kiev. The one mentioned in this preprint was the son of Vsevolod III, the Grand Prince of Vladimir. This is also confirmed by genetics, as Bela of Macso is VL11-, while Dmitry Alexandrovich is VL11+.

On 2025-08-02 21:52:44, user Dr. Monique Simair wrote:

As a PhD scientist in this field, I've performed a basic peer review of this paper. This platform doesn't allow users to post under the peer reviews section, so I'm posting in the comments as others have. I couldn't paste my review here with links included properly, so here is a link to the full thing. https://www.moniquesimair.ca/insights/selenium-coal-mining-spin-vs-science

On 2025-07-03 00:51:23, user GUY GILRON wrote:

Critical Review: “Fish remain high in selenium long after mountaintop coal mines close” (Cooke et al, 2025)1

Guy Gilron, Borealis Environmental Consulting Inc., North Vancouver, BC CANADA

This above article presents new selenium (Se) data in muscle tissue from three fish species in Crowsnest Lake (i.e., brown trout, lake trout, and mountain whitefish) and concludes that these data represent an environmental concern, based on the fact that the tissue Se concentrations exceed fish tissue guidelines. However, the article’s interpretation, contextual framing, and supporting evidence for these claims raise several scientific and methodological concerns.<br /> The authors posit an apparent paradox, specifically, that low aqueous Se concentrations and elevated fish muscle Se concentrations. This is presented as an alarming ecological signal, and supports the thesis that the Se in these fish has accumulated over many years despite low aqueous concentrations. The assumption here is that Se has potentially cycled within the food web; however, a more fulsome historical understanding of this system is required to make this link. Specifically, were aqueous Se concentrations historically higher, and then declined more recently? If this were the case, comparing current water Se concentrations to current fish tissue concentrations is an “apples vs oranges” scenario. While elevated tissue Se in fish certainly warrants further investigation (i.e., are populations and/or fish health being impacted?), this ‘paradox’ is actually not inherently unusual. Selenium bioaccumulates, particularly in food webs involving algae, invertebrates and fish/birds, and tissue concentrations can remain elevated for years after aqueous exposures have declined, particularly in lentic waters with longer residence times. Without time-resolved aqueous and tissue Se data, it is at best speculative to interpret these findings as alarming, or even ecologically significant. The article does not present any data or evidence of historical Se concentrations in water or biota to support its claims of historical or ongoing accumulation.<br /> The article presents new Se fish tissue data, but fails to reference any previous monitoring efforts in Crowsnest Lake or nearby waterbodies. Consequently, one cannot assess trends in Se (i.e., whether concentrations are increasing, stable, or anomalous). This is significant, since it would need to be demonstrated that high concentrations had been sustained in order for Se to bioaccumulate in aquatic biota tissues. Moreover, there is no attempt to address the mobility patterns of the fish species sampled, which is a significant omission, given the authors’ assertion that the Se in the system originated from the two decommissioned mines2. For example, species like brown trout and mountain whitefish may use tributaries for spawning or feeding, potentially exposing them to elevated Se concentrations outside the lake. If this is the case, then the lake itself may not have been the primary source of Se accumulation. Without tools like radiotelemetry, tagging, or isotopic forensics, the source attribution to Crowsnest Lake or Tent Mountain is speculative.<br /> The authors themselves acknowledge that the fish populations reported on in the paper (i.e., brown trout, lake trout, and mountain whitefish) in Crowsnest Lake are “self-sustaining”; they then suggest that current tissue Se concentrations may lead to a “population collapse” or “reproductive failure”. This contradiction is neither reconciled nor supported with data on recruitment, deformities, or reproductive metrics. The reference to such a collapse is not only unsupported, but actually conflicts with their own admission of population persistence. The article further suggests that Whirling Disease and Se toxicity could have overlapping symptoms, possibly confounding diagnoses. This suggestion is completely speculative and unsubstantiated. No peer-reviewed evidence to-date links Se-induced pathologies in fish to the clinical signs of Myxobolus cerebralis infection (the cause of Whirling Disease). <br /> A central assumption of the paper is that Se is leaching into the lake from historical waste rock from the closed Tent Mountain mine. However, the authors provide no chemical fingerprinting, hydrological modeling, or sediment Se profiles to demonstrate a link. As such, the attribution again remains speculative and circumstantial. Phrases such as “devastating consequences,” “complete reproductive failure,” and “acute threat” are used throughout the paper without any corresponding ecological data. These statements are alarmist and do not reflect the chronic, sub-lethal, nature of Se toxicity in aquatic ecosystems; it is well known that Se is not acutely toxic at environmental concentrations and does not cause sudden population collapses in the absence of sustained exposure and bioaccumulation.<br /> Figure 2 compares Se concentrations across fish species and regions, but does not control for species-specific bioaccumulation potential, life stage, or habitat use. Comparing lake trout to other fish in other regions is both inappropriate and misleading. Species-specific comparisons are more relevant, and a consideration of whether the fish inhabit lentic vs lotic systems would make the comparison more valid and informative. Furthermore, no effort is made to explain the geological and ecological differences among the geographically-diverse reference sites in comparison to Crowsnest Lake.<br /> While the authors report Se concentrations in fish tissue, key details on analytical methods, quality control, and lab accreditation are not provided in the article. Without such information, confidence in the analytical results is difficult to evaluate fully. This is especially important in the case of Se, due to its low environmental concentrations and the complexity of accurately measuring low concentrations. As suggested, and given the significant implications of these data, independent verification or confirmation through expert review is highly recommended.<br /> It should be noted that the article comprises a couple of important inaccuracies, specifically:<br /> • the article refers to a CCME sediment Se guideline of 2 µg/g, which does not exist; Canada has not adopted sediment guidelines for Se. Additionally, the cited whole-body fish tissue guideline of 6.7 µg/g appears to be based on the ECCC Federal Environmental Quality Guideline (FEQG), and is not a CCME guideline. The FEQG applies specifically to egg/ovary Se (14.7 µg/g) and muscle Se only as a screening value. Mis-stating the origin and intent of these values is a significant error that undermines the scientific rigor of the article; and,<br /> • the article cites the 93% decline in Westslope Cutthroat Trout in the Fording River, but fail to cite the detailed, peer-reviewed Investigation of Cause (IOC) study, which attributed the decline to climatic conditions and not selenium toxicity. <br /> • the article incorrectly implies that a $60 million fine was due to this decline. That fine, in fact, stemmed from broader non-compliance issues from 2012 – long before that decline occurred - and not a direct attribution to the population drop. <br /> <br /> Summary<br /> While it is understandable that elevated Se in fish tissue relative to low water concentrations raises a concern, the information provided in this paper fails to establish causality, provide historical or trophic context, or rigorously support its conclusions. The speculative connections to Tent Mountain, Whirling Disease, and catastrophic ecological effects are not supported by specific and relevant evidence. Misuse of terminology, misattribution of guideline values, and emotionally-charged language further erodes its credibility.<br /> A study of this type initially requires the clear identification and articulation of key research hypotheses (e.g., “is the elevated Se in fish tissue mine-related?”; “how is Se cycled in Crowsnest Lake”), and then determine what data/information are required to address those hypotheses. A multi-disciplinary, scientifically-defensible approach integrating fish movement, food web monitoring, sediment and water Se speciation, and reproductive success metrics, is essential to developing and reporting on scientifically-defensible conclusions.

On 2025-08-02 20:12:14, user Alex Crits-Christoph wrote:

1. This is an interesting work, but it really should have benchmarked a comparison to gLM2 / gLM. These are very similar models - the idea of using gene synteny in a protein language model was really already previously described in gLM/gLM2 papers:<br /> https://www.nature.com/articles/s41467-024-46947-9 <br /> https://www.biorxiv.org/content/10.1101/2024.08.14.607850v2

Unfortunately it seems like gLM(2) is not even cited in this work... I think this is a critical issue to fix.

1. It should really be more properly emphasized in the work that the PPI predictions are entirely dependent upon operonic context (Figure S7, C). PPI prediction based on operonic context is an entirely separate problem from PPI prediction of non-operonic proteins, and it is not clear if BacFormer performs well on that second problem. In all benchmarks I recommend splitting the two out (the authors do so currently in some cases but not all)

On 2025-07-24 10:47:37, user Bruno Gabriel Andrade wrote:

Great use of Large Language models for Biology particularly in decoding the functional syntax of bacterial evolution. Also the ability to predict protein-protein interactions, operon structures, and phenotypic traits and to build synthetic genomes was fascinating and the use cases are endless.<br /> Bacformer gave me lots of ideas and I thank you for that. Hats off.

On 2025-08-01 21:06:44, user Jesus Colino wrote:

I think the statement "To the best of our knowledge, no capsule-specific nAbs have been explicitly documented.", is incomplete or false. There are plenty of examples of nAbs with a well documented specificity for specific capsular polysaccharides.

On 2025-08-01 20:29:38, user Roel Nusse wrote:

Rebuttal to Claims Regarding Reproducibility of Our WntD and Edin Studies<br /> Michael D. Gordon1, Janelle S. Ayres2, David S Schneider3 and Roel Nusse3<br /> 1. University of British Columbia<br /> 2. The Salk Institute<br /> 3. Stanford University

We write in response to the preprint by Lemaitre and colleagues that challenges the reproducibility of our published findings on wntD (Nature, 2006) and Edin (PLOS Pathogens, 2008). While we welcome efforts to independently validate and extend prior findings, we believe that the conclusions drawn by the authors are not supported by rigorous replication and, in several key respects, reflect significant experimental and interpretive flaws.

Mischaracterization of the wntD Mutant Allele

The preprint by Lemaitre and colleagues centers on the observation that our original wntD allele reproduces the published phenotypes, but a second allele does not. The authors infer, based on quantitative PCR in early embryos, that our stock must have lost the mutation and that the observed effects are due to background variation. However:

• The qPCR assay used by Lemaitre and colleagues is technically invalid for assessing the integrity of our allele. As clearly described in our original work, our wntD mutant was generated by insertion of a w⁺ cassette into the wntD coding region—leaving the 5′ portion of the gene intact. The primers used by the authors target this unaffected region and are therefore expected to detect RNA transcripts, even though the resulting mRNA is non-functional. This is a fundamental flaw that undermines their central argument.<br /> • The authors did not attempt genomic PCR or sequencing to verify the presence or structure of the mutant allele in our stock—an essential step before invoking reversion or mislabeling.<br /> • The phenotypes associated with the original wntD allele were in fact replicated in their hands, contradicting their own assertion of irreproducibility. The failure of a second allele, generated in a different background and evaluated under different conditions, does not constitute a failure to reproduce but rather a failure to validate by independent means—a distinction that matters.

Strain Background and Controls

Lemaitre and colleagues raise concerns about genetic background effects while applying inconsistent standards in their own work. Our original wntD experiments were conducted in a y-w- background, and controls were matched accordingly. Their second allele appears to be in a wild-type background, yet their comparison is made to both y-w- and w1118 lines. It is well established that immune phenotypes in Drosophila can be highly sensitive to background variation. As such, a difference in phenotypes between two alleles in different backgrounds is neither surprising nor indicative of poor reproducibility.

Misinterpretation of wntD Expression Patterns<br /> The preprint by Lemaitre and colleagues suggests that wntD is only expressed at embryonic stages, questioning its relevance to immunity. However, the Fly Cell Atlas reveals specific clusters of cells expressing wntD in the whole body, gut, and Malpighian tubule samples. Moreover, additional studies have demonstrated that wntD is in fact inducible in adult flies upon infection with either L. monocytogenes or S. pneumoniae, supporting its role in immune modulation (Chambers et al., 2012, https://doi.org/10.1371/journal.ppat.1002970 ). The claim by Lemaitre and colleagues that the field has not followed up is inaccurate.

Edin: Distinction Between RNAi Knockdown and Knockout

In the case of Edin, Lemaitre and colleagues observe that a knockout mutant lacks the infection sensitivity we previously reported using fat-body-specific RNAi. They suggest off-target effects as a possible explanation. However:<br /> • We demonstrated the phenotype using two independent RNAi lines, reducing the likelihood of off-target artifacts.<br /> • The tissue specificity and temporal dynamics of RNAi versus germline knockout are fundamentally different. Loss of a gene during development may engage compensatory pathways that are not triggered in an acute knockdown context.<br /> • The conditions of microbial challenge differ between studies and were not standardized, further complicating direct comparison.

Edin Overexpression: Dose Matters

Lemaitre and colleagues report that Edin overexpression is not deleterious in their system, but this is entirely consistent with our findings. In our original study, mild overexpression had no phenotype; only very strong overexpression (>600-fold) triggered a measurable deleterious effect. The line used in their study achieves ~50-fold overexpression and would not be expected to phenocopy our results.

Conclusion<br /> While we support efforts to critically assess past findings, we reject the characterization of our studies as “non-reproducible” based on the experiments presented by Lemaitre and colleagues. The authors did not repeat our experiments as described, used different alleles, different controls, and in some cases, flawed assays. Differences in outcome under these circumstances are part of the normal course of scientific investigation and should not be conflated with a failure of reproducibility.<br /> We encourage future studies that further explore wntD and Edin biology, using rigorously matched conditions and appropriate validation techniques. Scientific progress depends on careful experimentation, not just reanalysis.

Sincerely,

Michael D. Gordon, email: mikedgordon@gmail.com<br /> Janelle S. Ayres, email: jayres@salk.edu<br /> David S Schneider, email: dschneid@stanford.edu<br /> Roel Nusse, email: rnusse@stanford.edu

On 2025-08-01 15:43:59, user Gil Yardeni wrote:

A revised version of this work was published in July 2025, https://doi.org/10.1093/sysbio/syaf039

On 2025-08-01 07:22:22, user YMIZUT58@YAHOO.CO.JP wrote:

This preprint has now been published in a journal.<br /> https://doi.org/10.1002/cm.70003

On 2025-07-30 16:15:07, user Alexander wrote:

Dear Authors,

Thank you for your valuable research on "A copper-dependent, redox-based hydrogen peroxide perception in plants". I noticed that the methods section appears to be missing from your preprint. Would it be possible for you to upload it? <br /> Best regards,<br /> Alexander

On 2025-07-30 14:30:40, user Lara Salah1 wrote:

Very interesting

On 2025-07-30 11:21:16, user GKI wrote:

Our analyses indicate little or no IBD connection between the EMMs and proto-Ob-Ugric groups in Western Siberia, despite their close geographical proximity for 1500–2000 years after their split estimated by linguistic models and chronology.<br /> Please clarify what this means!

On 2025-07-29 17:20:59, user Kristin G wrote:

???? AI ∩ Bio: Testing the Physics Beneath the Predictions<br /> Beyond RMSD: What AlphaFold3 Really Understands

Dan Herschlag was my postdoc advisor. Dan taught me how to think mechanistically, how to test assumptions, and how to pursue scientific clarity with unflinching rigor.

That legacy is all over this paper. And is incredibly needed in this era of AI hype where data volume often sidelines careful model-driven science.

Herschlag et al. show that while AlphaFold3 predicts protein structures with backbone-level structural precision, it struggles to capture the physical rules that govern biological function.

But this paper isn’t a takedown: it’s a roadmap for how to go further.

What They Did<br /> Rather than rely on RMSD alone, the team evaluated AlphaFold2 and AlphaFold3 against:<br /> →Energetic rules: bond torsions, hydrogen bonds, and van der Waals contacts<br /> →Experimental ensembles: from multi-temperature crystallography<br /> →Model confidence: comparing pLDDT to physical plausibility

What They Found:

~30% of side-chain interactions deviated from experimental observations, often with incorrect partners or implausible geometries<br /> High-confidence predictions (>90 pLDDT) still showed strained or physically invalid conformations<br /> Energetically-favorable conformations could increase RMSD and be penalized by the model<br /> AlphaFold3 missed ~85% of conformational variability seen in real experimental ensembles

Key Insight: Physics ≠ Proximity<br /> AlphaFold can recapitulate Ramachandran and Lennard-Jones-like patterns. But that doesn’t mean it understands physical constraints.<br /> To improve these tools, we need evaluation metrics grounded in molecular energetics, not just geometry.

???? Takeaway for Scientists<br /> This paper is a reminder that progress requires more than prettier predictions. It demands models that reflect the physics that drive biology.

On 2025-07-29 15:47:03, user Leah Gulyas wrote:

This work has been subdivided; a submission featuring data from this preprint with additional new data is available on bioRxiv as:<br /> "Cleavage of the RNA polymerase II general transcription factor TFIIB tunes transcription during stress" (doi: https://doi.org/10.1101/2025.07.28.667251 )

On 2025-07-29 15:40:39, user Leah Gulyas wrote:

This work has been derived in part from data previously posted in an earlier bioRxiv submission: "The general transcription factor TFIIB is a target for transcriptome control during cellular stress and viral infection" (doi: https://doi.org/10.1101/2024.01.16.575933 ).

On 2025-07-29 08:39:05, user Martin Gill wrote:

Now published as "Olaparib synergy screen reveals Exemestane induces replication stress in triple-negative breast cancer" in Molecular Oncology as early view article: https://febs.onlinelibrary.wiley.com/doi/full/10.1002/1878-0261.70093

On 2025-07-29 00:11:28, user Brian Coullahan wrote:

Thank you for posting on BioRxiv, I appreciate the opportunity to read about the work that you and your team are working on. At Element Biosciences, we're particularly excited to see our AVITI platform used to help enable your discoveries. I did notice that our platform was referenced as the Illumina AVITI instead of the Element Biosciences AVITI and are hoping that you would be open to correct. Thank you again.

On 2025-07-28 13:55:38, user Huihong Li wrote:

Great Work!

On 2025-07-28 09:38:48, user Chris wrote:

This study has been published in November 2024: https://doi.org/10.1093/ismeco/ycae147

On 2025-07-27 22:27:49, user Paul Macklin wrote:

Article is now published in Cell as:

Johnson et al., Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories. Cell (2025). DOI: 10.1016/j.cell.2025.06.048

https://doi.org/10.1016/j.cell.2025.06.048

On 2025-07-26 21:09:05, user Scientist2025 wrote:

This manuscript was published in Nature Metabolism on April 8, 2025. DOI: 10.1038/s42255-025-01250-9

On 2025-07-25 18:54:52, user Brian Coullahan wrote:

Thank you for posting on BioRxiv, I appreciate the opportunity to read about the work that you and your team are working on. At Element Biosciences, we're particularly excited to see our AVITI platform used to help enable your discoveries. I did notice that our platform was referenced as the Illumina AVITI instead of the Element Biosciences AVITI and are hoping that you would be open to correct. Thank you.

On 2025-07-25 15:17:02, user Marc Delarue wrote:

Excellent discussion of the Enthalpy-Entropy Compensation, offering profound insight int the thermodynamics involved and resolving, in passing, an issue that had escaped researchers for more than 40 years (see the work of R.L. Baldwin on the denaturation of proteins).<br /> Also proposes a nice analytical evaluation of a thermodynamics integration, which I did not know was possible.

On 2025-07-25 12:42:02, user Evolutionary Health Group wrote:

We at the Evolutionary Health Group ( http://evoheal.github.io ) really enjoyed this paper.

Here are our highlights:

Established the largest experimentally determined fitness landscape for antibiotic resistance to date

Demonstrated drug-dependent effects of antibiotic selection, from weak to strong, higher-order epistasis

Presented the more general finding that adaptation to novel substrates is characterized by higher-order epistasis while native substrates display smoother fitness landscapes

Partial fitness measurements show that accurate reconstruction of fitness landscapes with similar ruggedness could be reconstructed with fewer experimental measurements than previously expected – indicating scalability.

On 2025-07-24 21:32:08, user Matthew Shoulders wrote:

Please refer to v3 https://www.biorxiv.org/content/10.1101/2023.10.19.562780v3 for the correct version of the preprint at this DOI and ignore this v4. A member of our team mistakenly uploaded this v4 as a revision to the wrong preprint. It was instead intended to be uploaded here https://www.biorxiv.org/content/10.1101/2024.11.07.622468v2 where it now also resides. bioRxiv informed us they could not correct the upload error by simply removing the mistaken v4 from this DOI location and instead their administrators suggested adding this comment to v4 to help clarify any resulting confusion from readers.

On 2025-07-24 19:55:18, user Nicholas wrote:

It is unclear to me why counts of Trem2 increased in Microglia after applying RESOLVI (Figure 2D). I understand how transcripts are removed due to diffusion. Are these diffusion- or background-removed transcripts also added to certain cells?

On 2025-07-24 18:15:49, user enthusiast wrote:

In Fig4 why do SftpcCre-ert2(blh)Stk3f/f/Stk4f/f mice appear to do better than ctrl at 14 days post bleomycin injury but worse at 28 based on Ashcroft Score and total Collagen? If fibrosis is progressive in SftpcCre-ert2(blh)Stk3f/f/Stk4f/f mice why is Ashcroft better at 56days than at 28 days? Why is WT total collagen at 28 days in Fig 4f significantly lower than in Fig4c? Why is there barely any injury in WT H&E images? WT total collagen is supposed to be worse at 28 days than at 14 days but there is no injury in H&E. Total collagen in SftpcCre-ert2(blh)Stk3f/f/Stk4f/f mice at 28 days in Fig. 4f seems to caused by this 1 outlier sample. In Fig 5b why does the vehicle in YTact seems to cause more fibrosis at 14days compared to Fig.4b? Does Tam treatment after injury cause inactivation of Stk3f/f/Stk4f/f in additional cell populations like airway compared to treatment prior to injury?

On 2025-07-24 17:14:11, user Bettina Böttcher wrote:

The preprint is now peer reviewed,revised and published as<br /> Griessmann, M., Rasmussen, T., Flegler, V.J. et al. Structure of lymphostatin, a large multi-functional virulence factor of pathogenic Escherichia coli. Nat Commun 16, 5389 (2025). https://doi.org/10.1038/s41467-025-60995-9 <br /> Please add the link to this preprint

On 2025-07-24 08:35:11, user Borja Ibarra wrote:

Already published in https://www.nature.com/articles/s41467-025-60289-0

On 2025-07-24 01:51:24, user Wyatt Clark wrote:

Warris et al (2018) documented the same phenomena, which they referred to as palindromic sequences.

https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-5164-1

On 2025-07-23 15:41:21, user VIKRAM GANESAN wrote:

Hello, is the data for this preprint available anywhere? We are developing a machine learning method for spatial data that might suit this dataset very well.

On 2025-07-23 15:35:02, user Kate Nyhan wrote:

Interesting analysis. <br /> In light of the reliance on MeSH subject indexing, I draw your attention to NLM's own data on the performance of machine indexing approaches in different categories, documented in the NLM Technical Bulletin: https://www.nlm.nih.gov/pubs/techbull/ma24/ma24_mtix.html . The check tag category (which includes the species labels on which the OPA iCite tool relies) F1 score (combining precision and recall) for MTIX (introduced in 2024) was 87% versus the original (human) indexing approach -- that is, significantly lower performance. And for a period of time before the introduction of MTIX, NLM was using a different machine indexing system, MTIA, whose F1 score for the check tag category was only 62% compared with human indexing. So, depending on when MTIA started to be used, and the proportion of records that were indexed with MTIA versus human indexers, I wonder how confident we can be that the relative proportions of different categories of MeSH terms truly reflect the prevalence of different categories of research over time. <br /> I also note, in the same source, that the performance of MTIA and MTIX at appropriately labeling Medline articles with supplementary concept terms was even worse than their performance with check tags: 39% and 71% versus human indexing. Supplementary concept terms are especially relevant to innovative, novel science (including basic science) -- terms that may in the future become MeSH terms. It's perhaps not surprising that tools trained on historical data are not great at handling novel concepts, but poor performance by machine indexing tools at applying appropriate supplementary concept records may be another factor in the apparent decline in basic science research. <br /> I'd also like to comment on the iCite Translation Module (of which the Human/Animal/MCB category assignment is part). I'm not really clear on how many PubMed records get such category labels. On the one hand, iCite includes all PubMed records. On the other hand, presumably only articles with MeSH terms can be assigned in the Triangle of Biomedicine -- that is, articles in journals that are indexed in PMC but not Medline are not included in the human/animal/MCB analysis. I assume that the proportion of PubMed records with Medline indexing has gone down, as NIH-funded authors publish more papers in journals that aren't indexed in Medline (many of which didn't exist at the start of this longitudinal analysis). Indeed, thanks to Ed Sperr's handy tool PubMed-By-Year, we can see that Medline records (ie, records with MeSH terms that can be analyzed by the human/animal/MCB categories in iCite) as a proportion of PubMed records was above 90% until (I am eyeballing the figure at https://esperr.github.io/pubmed-by-year/?q1=medline [sb]&startyear=1990) around 2011, at which point Medline coverage started declining quite precipitously. So, any analysis that relies so heavily on MeSH indexing is going to be leaving out a large number (and an increasing proportion) of recent papers.

On 2025-07-22 21:06:15, user Huy Le wrote:

Now has been published in the Journal of Biological Chemistry; DOI: 10.1016/j.jbc.2025.110408

On 2025-07-22 07:29:00, user Thomas Kierspel wrote:

The following relevant articles were not cited in the original publication. A request to publish an erratum was declined.

A. R. Milosavljević, C. Nicolas, J. Lemaire, C. Dehon, R. Thissen, J.-M. Bizau, M. Réfrégiers, L. Nahon and A. Giuliani, Photoionization of a protein isolated in vacuo, Phys. Chem. Chem. Phys., 2011, 13, 15432–15436.

A. R. Milosavljević, F. Canon, C. Nicolas, C. Miron, L. Nahon and A. Giuliani, Gas-Phase Protein Inner-Shell Spectroscopy by Coupling an Ion Trap with a Soft X-ray Beamline, J. Phys. Chem. Lett., 2012, 3, 1191–1196.

A. Giuliani, A. R. Milosavljević, K. Hinsen, F. Canon, C. Nicolas, M. Réfrégiers and L. Nahon, Structure and Charge-State Dependence of the Gas-Phase Ionization Energy of Proteins, Angew. Chem. Int. Ed., 2012, 51, 9552–9556.

A. R. Milosavljević, C. Nicolas, M. Lj. Ranković, F. Canon, C. Miron and A. Giuliani, K-Shell Excitation and Ionization of a Gas-Phase Protein: Interplay between Electronic Structure and Protein Folding, J. Phys. Chem. Lett., 2015, 6, 3132–3138.

A. R. Milosavljević, K. Jänkälä, M. Lj. Ranković, F. Canon, J. Bozek, C. Nicolas and A. Giuliani, Oxygen K-shell spectroscopy of isolated progressively solvated peptide, Phys. Chem. Chem. Phys., 2020, 22, 12909–12917.

On 2025-07-22 05:46:03, user Shubhankar Ambike wrote:

Amazing work!

I would appreciate clarification on the gating strategy presented in Supplementary Figures 7 and 8. In panel A of both figures, the initial "IgD-" population identified in PBMCs (S7) appears to be subsequently labelled as "CD27+ MBCs" in the swab samples (S8) - includes rather both CD27- and + populations. Is the subsequent gating (S8) then performed exclusively on CD27+ population or total IgD-?

Thank you.

On 2025-07-21 20:35:45, user DmitryGordenin wrote:

Interesting work. This paper may suggest an additional detail for discussion: https://pubmed.ncbi.nlm.nih.gov/18267974/ In non-dividing yeast MMS causes DSBs that are prevented by BER branch relying on Apn1 and Apn2.

On 2025-07-20 00:26:39, user Artem K. Efremov wrote:

The study has now been published in Nature Physics: <br /> https://www.nature.com/articles/s41567-025-02964-z

On 2025-07-18 19:42:45, user Melissa Collier wrote:

This article is now published in Communications Biology https://doi.org/10.1038/s42003-025-08161-1

On 2025-07-18 14:26:51, user Laleh Haghverdi wrote:

Don't miss the supplemental figure S3 of the Bioinformatics published version for application of Compound-SNE on single-cell time-series data, for comparison of data manifolds at different time points.

On 2025-07-18 12:54:57, user Bram Bloemen wrote:

Very interesting paper!

I'm wondering whether other DNA extraction protocols might improve your viability inference, as other protocols might better retain original DNA fragment sizes (which are likely lower for extracellular DNA).

For example, we usually use enzymatic lysis and magnetic bead purification for ONT sequencing, since it seems to better protect DNA integrity: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-023-09537-5 .

We generally see larger reads for freshly extracted isolates than for stored metagenomes, and we see large differences in read sizes between strains in microbiome samples. We think this could be related to how easily different species are lysed throughout the protocol, but we didn't test this yet.

In our hands, bead-beating and spin columns caused read lengths to be lower and to have a more homogeneous size distribution.

On 2025-07-17 23:48:32, user Korena K Mafune wrote:

Super neat approach and glad to see the MinION being used more. I really liked the different methodologies.

Thanks for citing my original methodology (Mafune et al. 2020), but I also wanted to point you toward a more recent one that used a diverse mock community (gene copies controlled for concentrations), DNA extracted from roots, and then compared the sequencing results between the MinION and Illumina (Illumina is in supplemental). This paper has a lot of information on how well MinION resolved the diversity in the mock community to species level ITS-partial LSU, and also demonstrated that temporal and spatial patterns were significantly consistent across both Illumina and MinION. It's a bit dated chemistry, but even then it was demonstrating potential power of MinION and I love to see more and more pipelines and methodologies being tested now that chemistry is doing very well.

https://doi.org/10.1080/00275514.2023.2206930

On 2025-07-17 19:35:01, user Biswapriya Biswavas Misra wrote:

Dear Authors,

The text says, " Finalized .msp files for both ionization modes are provided in the Supplementary Material" but I can not find any .msp files that are downloadable as supplementary material. Just a word file with other tables. Kindly upload/ share.

Thanks again,<br /> Biswa

On 2025-07-17 18:36:02, user Smriti Pehim Limbu wrote:

An updated version of this preprint has been published now with the link forthcoming.

On 2025-07-17 13:08:08, user Amir Fallahshahroudi wrote:

The work is now published: https://www.nature.com/articles/s41586-025-09256-9

On 2025-07-17 10:45:06, user Hannah Esser wrote:

Dear authors,

congratulations on this manuscript. The dysregulation of the DDR in deciliated cholangiocytes in intriguing. <br /> However, I am surprised to see you never mention the process of cellular senescence in your manuscript. Cellular senescence is known to be linked to a disturbed DDR and is frequently induced using the genotoxic stress models (irradiation, induction of double or single strand-DNA breaks) you use for your experiments. It would therefore be very interesting if deciliation in your model impacts the rates of cellular senescence (e.g. changes in cell morphology, markers of senescence, SASP, etc).

In your manuscript you also show, that deciliation affects the ATM-p53-p21 axis and that p53 and p21 levels following genotoxic stress are lower in deciliated NHCs. <br /> p53 and p21 are again markers frequently used to assess cellular senescence and if downregulated would indicate lower rates of cellular senescence, a finding contradicting our recently published results where deciliation of primary cholangiocytes (K19Cre Kif3a flox) triggered a DDR and induced cellular senescence both in vitro and in vivo.

I therefore think it would be beneficial to discuss this contradictory findings in your discussion section. I would also recommend to add a paragraph about cellular senescence as the genotoxic assays you use are frequently used to induce cellular senescence in vitro, yet this important biological mechanism is never mentioned in your manuscript.

On 2025-07-17 03:49:26, user Mike Kalwat wrote:

published: https://www.cell.com/cell-reports/fulltext/S2211-1247(25)00605-9

On 2025-07-16 23:29:44, user Jianhai Chen wrote:

https://doi.org/10.1186/s12711-025-00986-y <br /> Hi guys! Our paper has been published in GSE.

On 2025-07-16 15:33:43, user Rongbin Zheng wrote:

This manuscript has been published at https://academic.oup.com/nar/article/53/12/gkaf569/8174779

On 2025-07-16 15:01:42, user Björn Wallner wrote:

Nice study, but you should really compare to AFsample2, which is better than the methods in your benchmark.

On 2025-07-16 13:13:34, user Knotpleased wrote:

This is now published as Espregueira Themudo, G. et al. (2025) ‘Roman Atlantic garum: DNA confirms sardine use and population continuity in north-western Iberia’, Antiquity, pp. 1–16. doi:10.15184/aqy.2025.73.

On 2025-07-16 11:18:12, user Verena van der Heide wrote:

This preprint is now published here: https://www.cell.com/immunity/abstract/S1074-7613(25)00246-8

On 2025-07-16 04:21:45, user Alfred Ray wrote:

Perhaps the key to Rapid Extinction in the Carolina Parakeet lies with cockleburrs. If they are poisonous to all animals except Carolina parakeets there would have to be a reason why that is. Were cockleburrs consumed in conjunction with something else which made them non-poisonous? If the environment lacks that other plant resulting in a mass poisoning it would explain a mysterious and sudden population collapse.

On 2025-07-16 03:30:08, user mcdull wrote:

the cited references do not support the stated role of hypoxanthine. hypoxanthine is actually decreased in serum of CRC patients

On 2025-07-15 22:07:24, user Åshild Telle wrote:

Links to movies (Supplementary Material):

https://www.dropbox.com/scl/fi/pa00vq7h29jlptegmkmp3/Patient1.m4v?rlkey=8xj6oula1ys68vdpzprhmlu61&dl=0 <br /> https://www.dropbox.com/scl/fi/7daf5rwkbh907lhxq03yk/Patient2.m4v?rlkey=8td1vwxhl4f70w2151owcmful&dl=0 <br /> https://www.dropbox.com/scl/fi/m0rd44brd5mhxllcm9cra/Patient3.m4v?rlkey=6t6er8qicg1t5pfgpuhnk05es&dl=0

On 2025-07-15 19:28:02, user Mnimi wrote:

Thank you for your submission of this relevant and interest research to the preprint server, it will be a valuable reference for further studies in this field.

I have noticed a point that may generate some confusion, in page 20 when describing your methods for hemolysis assays you write "(...) the choice of the percentage cutoff<br /> for determining samples with substantial hemolysis (20% for most blood types with the<br /> exception of two samples set to 40%)". The use of the term blood types to reference the different sample types evaluated in this study may cause confusion as the same term is commonly used to refer to the different groups in human blood group classification systems (ABO blood group system being the most relevant one for this confusion). One would advise the use of slightly different terminology such as "types of blood" "blood samples".

On 2025-07-15 13:28:04, user Michael Rist wrote:

Here is the peer reviewed manuscript: https://doi.org/10.1371/journal.ppat.1013087

On 2025-07-15 03:20:13, user Karmella Haynes wrote:

This is an intriguing paper. Does provide any insight into how different chromosomes might interact with each other (i.e. a single compartment containing unlinked loci), or why they tend to stay separated?

On 2025-07-14 15:39:34, user Zhixun Dou wrote:

This manuscript has been published: https://www.nature.com/articles/s41586-025-09234-1

On 2025-07-14 11:57:21, user Jakub Gemperle wrote:

Final story published here https://www.science.org/doi/full/10.1126/sciadv.adu6361

On 2025-07-14 03:15:22, user Karmella Haynes wrote:

I appreciate that this study focuses on the relationship between diet/ metabolism and chromatin states. My group recently published a study showing that triple negative breast cancer cells induced to take on a lipogenic state (lipid droplet accumulation) also epigenetically repress a reporter gene along with hundreds of endogenous genes (PMID: 40625278).

On 2025-07-14 03:01:24, user Karmella Haynes wrote:

As a scientist who specializes in epigenetic engineering, this paper immediately caught my attention. A few years ago, I became interested in islet cell transdifferentiation, and read studies that used chromatin-modifying enzyme inhibitors to convert alpha cells into beta-like cells. I’m excited to see that you've taken this further by applying epigenome editing to activate insulin expression directly, this is a powerful and promising approach. Your results are intriguing and could be made even stronger with some restructuring of the narrative. For example, it would help to clarify the rationale for your cell model choices (e.g., in Fig. 3), and reviewers may be curious to see whether your system could also be applied to other islet cell types such as alpha or epsilon cells. If you’re preparing this for submission, I work with researchers to strengthen the clarity and strategy of their manuscripts, particularly those in molecular cell biology and chromatin engineering.

On 2025-07-10 18:10:54, user PEGGY COTTER wrote:

https://uploads.disquscdn.c...

On 2025-07-10 17:37:31, user Jink wrote:

I was wondering why Indian genomes lack X and Y chromosomes altogether for 50,000 years in figure 4c..!! Yet, Indians managed to top the table of population explosion..!! As this is published in "Cell" now, I guess the authors, editors and reviewers will have to give an explanation what happened at figure 4c, how the editor and reviewers missed the so obvious thing, and whether or not X and Y chromosome data affects other figures..!!

On 2025-07-10 15:28:16, user Mina Bagheri wrote:

Hi, I have a few questions<br /> For counterfactual generation you brute-force over all the potential perturbations in the cell. How do you define this search space? How many iterations is this?<br /> Also did you consider using gradient-based cf generation methods? My understanding of counterfactual generation was to use the model weights directly, otherwise this is just insilico testing

On 2025-07-10 15:20:31, user Sara Sarkhosh wrote:

Interesting work! The chemical library is limited to roughly 200 compounds. Any plans to expand this? Does the chemical model have to be retrained?<br /> Where can we get a list of these compounds you already trained on?

On 2025-07-09 15:23:58, user Vlada Bogushevskaya wrote:

Can we apply our own custom molecular-embedding model? There are models that outperform Uni-Mol+ on the OGB right now.<br /> Also are the embedding results cached, or generated on the fly?

On 2025-07-10 14:19:16, user Huanyuan Zhang wrote:

Hi This manuscript has been published here: https://www.nature.com/articles/s42003-025-08420-1

On 2025-07-10 14:15:29, user Prof. T. K. Wood wrote:

Seems like yet another toxin/antitoxin that inhibits phage; should ref first publication in 1996.

On 2025-07-10 14:09:47, user Huanyuan Zhang wrote:

Hi, the information in the related manuscript area is not correct. It links to another paper, this one is now published here: https://www.nature.com/articles/s41467-024-53949-0

On 2025-07-10 11:58:54, user Benoit Lefebvre wrote:

Now published in PNAS doi: 10.1073/pnas.2426063122

On 2025-07-10 11:57:39, user Benoit Lefebvre wrote:

Now published in Nature Communications doi: 10.1038/s41467-025-60717-1

On 2025-07-09 16:28:45, user Marija Orlic-Milacic wrote:

This is a very important study that expands the knowledge on the role of progesterone receptor (PGR)-positive subpopulation of bipotent mammary cells/MaSCs. Some of the terminology used in the paper is somewhat ambiguous, in particular "basal population". In the literature, basal is used both to refer to the bipotent/MaSC-like cells that reside in the basal layer and for myoepithelial cells and myoepithelial progenitors that are also basally located. Basal cells described in this manuscript are said to be EpCAM+CD49fhi, which is consistent with basally located bipotent/MaSC-like progenitors. Luminal progenitors also express both of these markers, but they would be EpCAMhiCD49f+ (or EpCAM+CD49flo - these cells in the paper are just labeled as luminal, not as luminal progenitors, although mature luminal cells are expected to be CD49f-). The findings of the study would be communicated in a much clearer way if ambiguous terms were made more specific (e.g. "basal bipotent progenitors" instead of "basal cells", and "luminal progenitors" or "mature luminal cells" instead of just "luminal cells"). In one sentence, CD49 instead of CD49f is used, which should be corrected. Have the authors observed the phenomenon reported by Hilton et al. 2012, where PGR expression drops to low levels in luminal progenitors (compared with PR+ bipotent progenitors), but then increases in ER+ mature luminal cells upon estrogen treatment?

On 2025-07-09 15:55:47, user Michael Ailion wrote:

This paper examines the evolution of X chromosome dosage compensation in nematodes. There are several interesting findings. The condensin-mediated dosage compensation complex is shown to have evolved recently in the Caenorhabditis lineage. In addition, a different duplication of SMC-4 occurred in two Pristionchus species, suggesting that Pristionchus independently evolved a similar condensin-mediated mechanism of dosage compensation (“parallel evolution”). Caenorhabditis and Pristionchus share other signatures of condensin-mediated dosage compensation, namely X-specific topologically-associating domains (TADs) and enrichment of the H4K20me1 chromatin mark on the X chromosome. The data supporting these conclusions are strong and the underlying experiments are rigorous. Additional interesting observations are made regarding dosage compensation mechanisms in two other nematode lineages, Oscheius and Steinernema. Oscheius is found to lack X-specific TADs, but has enrichment of H4K20me1, while Steinernema lacks both X-specific TADs and H4K20me1 enrichment. These results suggest that condensin-mediated dosage compensation may have evolved in the presence of an existing mechanism that involves H4K20me1. Additionally, Oscheius is shown to have X chromosome dosage compensation, but in Steinernema, dosage compensation is found to be incomplete. Unlike the results for Caenorhabditis and Pristionchus, some of the data for Oscheius and Steinernema are not as clear-cut and thus, the support for some of the conclusions is not as strong. There are perhaps a few places where the caveats could be pointed out and the conclusions toned down, but for the most part, I think the authors are appropriately cautious in interpreting their data. Overall, this is an interesting study that raises further interesting questions about how dosage compensation mechanisms evolve and are constrained. I have only relatively minor comments.

1. TADs. Hi-C data shown in Fig 2B are used to infer whether X-chromosome TADs are present. The data are quite clear for P. pacificus (TADs), C. elegans (TADs), and O. tipulae (no TADs). C. remanei is also scored as having X-specific TADs, though the TAD features are less obvious. It is argued that this is because the C. remanei data come from mixed-stage and mixed-sex worms (published elsewhere), so features specific to female X chromosomes in somatic cells would be diluted out. This is a reasonable argument. Also, in Fig 2B, Steinernema hermaphroditum is inferred not to have X-specific TADs. But to my eye (admittedly untrained for Hi-C data), the S. hermaphroditum pattern looks very similar to C. remanei. And the S. hermaphroditum data (also published elsewhere) has the same caveat as C. remanei of coming from mixed-stage animals that makes the TAD features less obvious. Additionally, the S. hermaphroditum data were obtained using a different Hi-C method that is restriction enzyme-independent. So it is unclear how it is conclusively determined that C. remanei has TADs and S. hermaphroditum doesn’t, especially given that the data come from different labs using different methods. Further explanation of the criteria used to score these data and make these conclusions would be useful.

2. Dosage compensation. Data show that all species analyzed except Steinernema carpocapsae have clear dosage compensation. S. carcocapsae data are somewhat less clear. Fig 4E shows that for two X-linked scaffolds, expression in females is higher than males, indicating a lack of complete dosage compensation. However, the difference is less than two-fold, suggesting that there is some dosage compensation. Also, of the two-scaffolds, the difference is only statistically significant for one of the two (Fig S11), even though both are X-linked, weakening the conclusion that this species lacks dosage compensation. Is it possible that the lack of full dosage compensation could be due to contamination of the data with more germline expressed genes?

3. The authors suggest the interesting possibility that the lack of complete dosage-compensation in Steinernema may be due to a couple of autosome to sex chromosome fusions in this species. In this case, one might expect full dosage compensation in some parts of the chromosome, and no dosage compensation in others. Can the data be analyzed to determine if dosage compensation varies in different regions of the Steinernema X chromosome, especially corresponding to different nigon elements? Or is there partial dosage compensation all along the X?

4. H4K20me1. Based on the data in Fig 5, the authors conclude that like C. elegans, P. pacificus and O. tipulae have H4K20me1 enrichment on the X chromosome, but S. hermaphroditum does not. The data for C. elegans and S. hermaphroditum are quite clear. However, there appears to be less H4K20me1 enrichment in P. pacificus and O. tipulae in the chromosome-wide data shown in Fig 5A. In both these species, there appears to be a higher level of H4K20me1 on the representative autosome, and to my eye, O. tipulae does not even show enrichment on the X. Is it possible to quantify levels of enrichment between species on autosomes and the X? It would be nice to see the ChIP-Seq tracks for all autosomes in a supplemental figure, not just the single representative autosomes shown in Fig 5A. To their credit, the authors recognize that X enrichment of H4K20me1 is weaker in O. tipulae and do statistics to back up their claim, but the statistics seem to be done only on H4K20me1 enrichment in gene bodies. Is there a difference between enrichment on the whole chromosome versus gene bodies in O. tipulae?

5. In the discussion, the authors suggest based on parsimony that dosage compensation was present in the common ancestor of the different nematode groups, but lost in the lineage leading to Steinernema. Though I agree this is the most likely scenario, isn’t it equally parsimonious to say that the common ancestor lacked dosage compensation, but that it evolved separately in Brugia (i.e. two gains of dosage compensation in nematodes instead of one gain and one loss)? So should it be stated that the authors’ model is the most parsimonious?

Reviewed (and signed) by Michael Ailion

On 2025-07-09 12:16:50, user Jan Štefka wrote:

The paper is now published in MBE under the doi: https://doi.org/10.1093/molbev/msaf163