On 2026-02-13 11:49:34, user Prof. T. K. Wood wrote:
Reminiscent of 1st report of one anti-phage defense controlling another: TA cascade in which RNase (type II) toxin MqsR controls type V toxin GhoT (pore former, ATP-depleting) by cleaving antitoxin GhoS mRNA during stress (doi:10.1111/1462-2920.12063, 2013). Please cite.
On 2026-02-13 09:10:33, user Angus O'Ferrall wrote:
This article has since been published in Microbial Genomics: https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001480
On 2026-02-13 00:49:10, user Simon Tang wrote:
This has now been published here:<br /> https://www.ecmjournal.org/journal/ECM/path/vol054/10.22203/eCM.v054a05
Walk RE, Broz KS, Jing L, Potter RS, Gonzalez CE, Beeve AT, Scheller EL, Setton LA, Gupta MC, Tang SY. The neurovascular and inflammatory signatures of the degenerating intervertebral disc. Eur Cell Mater. 2025; 54:65-78.
On 2026-02-12 14:30:08, user Nuria Torres wrote:
This preprint was now been published in BMC Biology:<br /> https://link.springer.com/article/10.1186/s12915-026-02522-w
On 2026-02-12 13:59:29, user Denis Omelchenko wrote:
The article has been published https://doi.org/10.1007/s11248-026-00482-z
On 2026-02-12 09:52:20, user Prof. Emad M. Abdallah wrote:
Dear Authors,<br /> This is an intriguing and well-designed study. However, there is a major biosafety concern that must be addressed before the work can be considered for publication.<br /> Pseudomonas aeruginosa is a well-known opportunistic human pathogen and is listed among clinically important multidrug-resistant organisms. The use of such a species as a biocontrol agent raises significant safety, environmental, and regulatory concerns.<br /> Thank you
Prof. Emad Mohamed Abdallah, FRSB<br /> Professor of Microbiology.<br /> Top 2% world scientists (2023, 2025)<br /> https://scholar.google.com/citations?user=6BSPm_QAAAAJ&hl=en
On 2026-02-12 06:14:42, user Johnathan wrote:
Overall, the research direction of the paper is promising and novel. However, there were a few statistical choices that were unclear. <br /> 1. Reasoning was not given for the removal of certain outliers, and certain characteristics were included as covariates in different analyses. <br /> 2. GAMLSS was used, but there were no independent observations with cognitive decline. Additionally, data was not defined to be parametric and usable in GAMLSS. <br /> 3. Statistical analysis is not reproducible, the paper did not state which distribution was used for any of the analyses or associated fit metric values (e.g. AIC, SBC)<br /> 4. Unclear if preliminary analysis was run to determine which independent variables to include<br /> 5. Unclear which post-hoc test was used, and if they were corrected for multiple comparisons<br /> But, direction of the experimental design is intriguing and very promising.
On 2026-02-11 07:04:27, user Subashika wrote:
Its excellent research on salt stress and dissectins mechainsms on high salt stress induced adapatation. We are not unfortunately able to access the supplementary information, We would appreciate if the supplementary is uploaded, so we can make better sense of the paper.
On 2026-02-10 23:29:48, user Edward Davis wrote:
I don't see the supporting data attached. I was able to find three of the tables here: https://zenodo.org/records/15632161
But the document S1 doesn't seem to be available anywhere. Am I just missing something?
On 2026-02-10 20:08:45, user Deepthi Sudarshan wrote:
Very interesting paper. Is it normal that the figures are pixellated? I cannot read gene names in some figures.
On 2026-02-10 14:56:11, user Tom wrote:
Hi,<br /> Nice, but I think we've been a few groups to propose a related approach:<br /> - https://pubs.acs.org/doi/full/10.1007/s13361-016-1460-7 <br /> - https://pubs.acs.org/doi/10.1021/acs.analchem.0c00328 <br /> - https://pubs.acs.org/doi/full/10.1021/acs.jproteome.9b00819 <br /> Comparing them would be nice!<br /> best,<br /> Tom
On 2026-02-10 10:19:01, user Tomàs Montserrat-Ayuso wrote:
This preprint is already published: https://doi.org/10.1093/nargab/lqag013
On 2026-02-09 15:08:53, user Christian S wrote:
This article has been published in Nature Communications in December 2025. The published version has a different title, see citation below.
Clowsley, A. H., Meletiou, A., Janicek, R., Bokhobza, A. F. E., Lučinskaitė, E., Bleuer, G., Jansen, I., Jones, P. P., Louch, W. E. & Soeller, C. MINFLUX microscopy resolves subunits of the cardiac ryanodine receptor and its 3D orientation in cells. Nat Commun 17, 1044 (2025).
On 2026-02-09 11:16:44, user Holroyd, Natalie wrote:
This paper has now been pubished here: https://doi.org/10.1002/nbm.70236
On 2026-02-09 07:55:14, user Masahiro Kasahara wrote:
I found some errors in the pseudocode on the paper. We've mistakenly swapped ev and fv; in the "if (dir is DOWN)" block and the corresponding "else" block, "fv <- shift_right fv" and "ev <- shift_left ev" don't make sense.
On 2026-02-06 23:36:39, user Michael Keogh wrote:
Now published in NAR [doi: 10.1093/nar/gkaf1061 / PMID 41182902]
On 2026-02-06 15:01:25, user Yijie Deng wrote:
Thank you for taking time to read our manuscript. We would like to respond your comments here. <br /> 1. We already showed in 2013 that Abs induce persistence by converting the whole population into persister cells without inducing death by pre-treating with rifampicin, tet, and CCCP (doi:10.1128/AAC.02135-12) so please add this to your paper. We vetted these persister cells 9 ways to show they are true persisters in later publication. This method has been used by over 60 groups to date in the persister field.
Response: Thanks for pointing out. We totally agree that bacteriostatic antibiotics and drugs, by definition, can convert most of a bacterial population into persister cells without inducing death. Therefore, in this study we focus on bactericidal antibiotics, mostly used in time-kill assays, to examine and quantify persisters induced by lethal stresses. Broadly, your work agrees with our proposed drug-induced persistence spectrum (DIPS) model and a more general stress-induced-persistence-spectrum model. Your work will acknowledged in the Discussion.
Response: Thank you for this clarification. We agree that most persister cells, once they wake, rapidly resume normal growth and proliferate at rates comparable to susceptible cells. Only a minority remain in a dormant state and constitute the pre-existing persisters, which are the persisters referred to in this context (line 85). We would like to clarify that “persister replication” in line 85 refers specifically to the rare events in which a persister cell divides to produce two persister cells, rather than to persister resuscitation and growth. We believe such events are rare and negligible relative to the contribution of pre-existing persisters.
Response: Thank you for this comment. We agree that the vast majority of persisters, found in exponential-phase culture, originate from stationary-phase inocula and that carryover can contribute substantially to observed persister populations (when seed dilution factors are low, e.g, 100x). At the same time, we note that the existence of truly spontaneous persisters remains a theoretical possibility and has been suggested by several single-cell studies, although this remains a subject of debate. Such spontaneous persisters could arise from stochastic fluctuations or rare glitches in transcription, translation, metabolism, and/or asymmetric allocation during cell division, leading to unusual levels of ppGpp, toxins, or other effector proteins in a small subset of cells. If such events occur, we expect them to occur at extremely low frequencies.
Response: Thank you for your suggestion. We agree that these studies are relevant and will be talked in our Discussion.
On 2026-02-02 07:29:46, user Prof. T. K. Wood wrote:
Line 218: we previously showed the relA spoT mutations reduce persistence by 1000X but do not eliminate it (DOI: 10.1038/srep20519). Please cite the relevant literature.
On 2026-02-01 23:11:09, user Prof. T. K. Wood wrote:
We already showed in 2013 that Abs induce persistence by converting the whole population into persister cells without inducing death by pre-treating with rifampicin, tet, and CCCP (doi:10.1128/AAC.02135-12) so please add this to your paper. We vetted these persister cells 9 ways to show they are true persisters in later publication. This method has been used by over 60 groups to date in the persister field.
We were the first to show, using single cells, in 2018 (doi:10.1111/1462-2920.14093) that persister cells wake in minutes. Please update your line 85 text which is false as, we have shown and other groups corroborated, nearly all persister cells resuscitate within minutes of being introduced into fresh medium so they wake and multiply at the same growth rate of exponentially-growing cells within seconds.
There is no credible evidence for ‘spontaneous’ persisters, only sloppy carryover from the inoculum.
Please replace your ref 23 single cell work of Van Melderen as the first single cell work with the same conclusions was https://doi.org/10.1016/ j.isci.2019.100792 and doi:10.1111/1462-2920.14093.
On 2026-02-05 20:13:34, user Michael Henry wrote:
This manuscript is now published: https://doi.org/10.1016/j.celrep.2025.116908
On 2026-02-05 10:41:47, user Anna Pashkova wrote:
The link to the code used to generate Figure 2 on Zenodo (10.5281/zenodo.1793665) is incorrect and returns the message "This DOI cannot be found in the DOI System". Also, a record under https://zenodo.org/records/1793665 is irrelevant to this publication.
On 2026-02-05 07:55:06, user Delna Cherian wrote:
This was a very informative paper. The authors undertook a variety of different experiments, which was impressive, but also may have lessened the quality of their research. While much of the science appeared to be quite convincing, a closer look reveals some inconsistencies between stated findings and figures. I noticed many typos within the legends on the figures, and differences in the experimental process described in words versus the experimental process reflected by figures.
Some things to take note of: in Figure 1, procedures are not clear; when were the measurements taken? Was the glucose checked in the mice? What is the "endpoint" for the experiment, and why does it change from experiment to experiment? Did the mice die or were they sacrificed? Survival curves would also have been appreciated. Furthermore, i believe it would benefit the research to have conducted studies on male and female mice for all conditions, to test for any changes between sex.
In Figure 2, I noticed that different cancer cell lines were utilized in the experimental process, but no explanation was given for why this was the case.
In Figure 3, many of the colors and shapes do not match across panels, which makes it difficult to track the data (ex. for E.coli). Similar to above, the data in Figure 3F does not match the analysis given in the "results" section.
Figure 4 and 5 featured a bubble plot, which presented very informative data, however the paper seemed to focus on aspects of the heat map that were not necessarily proven by the data. For example, the passage states: “This analysis revealed a prominent activation of the tryptophan metabolic pathway in the MedDiet group” (260), but this is not necessarily proven by figure 4; the data shows that there seems to be other metabolic pathways that are upregulated by the MedDiet group than the Tryptophan metabolic pathway. It might be worth considering addressing this issue, to avoid introducing any accidental bias into the findings.
Some other issues that were noticed: it was assumed that the reader had context for this study, but many readers may be coming in to read this paper with no background on the MedDiet. Many acronyms were used without providing appropriate definitions which made it difficult to follow the paper. It seemed as though the paper jumped to many conclusions without providing an accurate backing or "proof". Much of the statistical analyses used in this paper also seemed to be inconsistent.
Some things that can be appreciated about this paper: the authors covered a lot of bases and tried to include many sample groups (different diets, cancer lines, mice sexes, etc.). I appreciate that they tested for reproducibility, at least at the beginning. They also tried to investigate the mechanism of the MedDiet, not just general effects. They also used a variety of different techniques to evaluate their hypothesis: flow cytometry, genomic sequencing, immunohistochemistry, etc.
All things considered, this was a huge undertaking. I am sure that with further review, this could become quite beneficial for the scientific community. Thank you for sharing!
On 2026-02-04 10:17:28, user Gabriel Axel wrote:
Interesting work. I suggest having a look at ZincSight https://onlinelibrary.wiley.com/doi/full/10.1002/pro.70350 in which we addressed rotamer sampling, interpretability, and high-throughput transition metal binding site prediction, which seems relevant to your proposed pipeline.
On 2026-02-04 02:22:53, user shane wrote:
Thank you for sharing this interesting pre-print. As a researcher also working on mechanical stimulation of solid cancer, I’m particularly interested in building a similar setup.
Could you please provide more details on how sterility was maintained throughout the experiments? Specifically:
How were the custom-built pressure chambers and tubing sterilized (e.g., autoclaving, chemical sterilants)?
What was the standard operating procedure for cell seeding, medium exchange, and sampling while the system was under pressure?
Were any sterility tests (e.g., negative controls in culture medium) performed during the long-term pressure experiments?
Any insights would be greatly appreciated and would help tremendously in our own experimental design.
On 2026-02-03 21:59:04, user Jordan Hiatt wrote:
For the RESTful API supplementary notes can you name the supplementary doc RestApi or something other than Supplementary 13? Or say that the REST API's are in supplementary 13?
On 2026-02-03 18:36:40, user Alejandro Leyva wrote:
Great Work!
On 2026-02-02 16:13:21, user Benedict Onu Onoja wrote:
I appreciate the bioRxiv preprint server for the articulate manner in which this manuscript was processed and posted online. The content is original and worthy of reading to gain new insights about schistosomiasis in Nigeria.
On 2026-02-01 11:17:31, user Anneke wrote:
In the final version, will you also be reporting SD in the values in the tables for the biochemical parameters?
On 2026-02-01 09:59:17, user Prof. T. K. Wood wrote:
These results are exciting since we have shown phages induce persistence to protect the host (2024, doi 10.1111/1751-7915.14543) and that (p)ppGpp makes persisters by ceasing translation (2000, https://doi.org/10.1016/j.bbrc.2020.01.102 ), so it makes sense that now it has been found that phages inhibit (p)ppGpp to prevent persistence. Authors should cite the relevant literature.
This is similar to our seminal discovery that toxin/antitoxin systems stop phage in 1996 ( https://journals.asm.org/doi/10.1128/jb.178.7.2044-2050.1996) , then phage proteins like antitoxins were found to inhibit TA systems.
On 2026-01-31 19:51:56, user shanlong wrote:
A peer-reviewed version of this article has been published in Proceedings of the National Academy of Sciences of the United States of America. <br /> https://doi.org/10.1073/pnas.2504583122
On 2026-01-31 16:39:43, user Xu Yitao wrote:
I am sorry to correct a typo in the author's name: 'Weichua Yu' should be 'Weichuan Yu'.
On 2026-01-30 15:39:36, user Ronald wrote:
Now published in:<br /> Halbach R, van Rij RP. Annotation of piRNA Source Loci in the Genome of Non-model Insects. Methods Mol Biol. 2025;2935:125-139. doi: 10.1007/978-1-0716-4583-3_6. PMID: 40828277.
On 2026-01-30 15:22:26, user Richard Fox wrote:
Impressive work and much of interest (and some surprises e.g. positive effects of urbanisation contrary to many other studies). There are some very important caveats in the latter part of the main text i.e. the analysed species are relatively widespread and scarcer species (which may have suffered longer term declines) are excluded; change in species distribution is not necessarily the same as change in abundance - you mention that species with stable distributions may have suffered abundance decline but can also be true for species with increasing distributions. These important caveats are not reflected in the Abstract, nor the fact that 700 species (while impressive) is a very small proportion of European arthropods. I'm concerned that, without some additional qualification, some of the strong statements in the Abstract may be taken out of context and misused in the discussion around biodiversity change.
On 2026-01-28 13:32:37, user Roel van Klink wrote:
Hi, have you somehow accounted for the increase in observer activity? I find it a bit suspicious that The Netherlands shows a distinct increase in occupancy in fig 1c, whereas it is also the county with by far the highest density of observers (almost all data for NL on GBIF are from waarneming.nl), and we also know the environmental quality there is not exactly good...
On 2026-01-29 22:42:04, user Ningxuan Zhang wrote:
Could you please upload the supplementary figures? <br /> Thank you very much!
On 2026-01-11 16:00:52, user Alex Crits-Christoph wrote:
The "10-fold cross validation" accuracies are all in excess of 99% for every disease in this work. This is clearly indicative of over-fitting and inaccurate application of cross-validation. Regardless of the actual correlation of gut microbiome composition with disease, it is scientifically implausible that it could accurately predict "heart failure" and "schizophrenia" with >99% accuracy as depicted here.
It is also worth noting that in Figure 3C on "external validation" the model does not particularly outperform a simple random forest on any of the examples.
The abstract states "Furthermore, its attention patterns reveal biologically plausible microbial signatures", but this is clearly not correct from a cursory reading of Figure 4. The top feature in predicting "Healthy vs Disease" is V. cholerae, but that is simply because one of the studies included in this analysis was on patients selected because they were known to be infected with V. cholerae. This is a particularly good example of why simply predicting "healthy vs disease" across unrelated and disparate studies is not a particularly scientifically meaningful exercise.
Further, the other top features across studies are Staphylococcus epidermis, a skin microbe that only residues transiently in the gut microbiome. This is a decent indicator of contamination, and it is therefore likely that this feature is because the model is overfitting on signals of contamination endemic to particular studies. Staphylococcus is unlikely to be involved in a causal role in any of these diseases. Mixta calida and Zymomonas are also not residents of the human gut microbiome.
On 2026-01-29 22:07:46, user Thomas Jones wrote:
This article has been published, please see:<br /> https://doi.org/10.1186/s13059-025-03557-y
On 2026-01-29 20:03:55, user Lev Petrov wrote:
Now published in Cell Reports Medicine: https://www.cell.com/cell-reports-medicine/fulltext/S2666-3791(25)00358-1
On 2026-01-29 18:02:13, user Alexander Mitchell wrote:
One small typo: on the legend of figure 4 you make reference to a "generalized liner model (GLM)".
On 2026-01-29 09:59:23, user Cosseau Céline wrote:
Thank you for this work! This is a wonderful demonstration of the microbial education effect! I particularly appreciate the discussion on the possible selection of Roseobacter species through AMP production. This is a promising avenue to pursue! I am also amazed that a one-hour treatment is sufficient to induce beneficial effects without causing any detrimental impact during larval rearing. This is very promising as well.
On 2026-01-27 20:49:50, user Yuting Xiao wrote:
The peer-reviewed version of this work is now available:<br /> Xiao, Y., Stolzer, M., Wasserman, L. et al. Evolution of the Metazoan Protein Domain Repertoire Revealed by a Birth-Death-Gain Model. J Mol Evol 93, 777–799 (2025). <br /> https://doi.org/10.1007/s00239-025-10286-0
On 2026-01-05 18:47:06, user Yuting Xiao wrote:
This preprint has now been published in a peer-reviewed journal. The published version will be linked here once available through the bioRxiv system.
On 2026-01-27 19:29:23, user Rebecca Leuschen-Kohl wrote:
This has now been published: https://onlinelibrary.wiley.com/doi/full/10.1111/pce.70164
On 2026-01-27 18:12:46, user Derek Narendra wrote:
This manuscript has now been published:
Thayer JA, Petersen JD, Huang X, Gruel Budet LM, Hawrot J, Ramos DM, Sekine S, Li Y, Ward ME, Narendra DP. A unified mechanism for mitochondrial damage sensing in PINK1-Parkin-mediated mitophagy. EMBO J. 2026 Jan;45(1):64-105. doi: 10.1038/s44318-025-00604-z. Epub 2025 Nov 20. PMID: 41266657; PMCID: PMC12759083.
On 2026-01-27 14:49:16, user Prof. T. K. Wood wrote:
No compelling evidence of abortive infection, just two vastly different MOI used (0.05 and 5) such that at MOI 5 most antiphage systems would be overwhelmed and results based on non-physiological conditions (i.e., a T7 promoter) so nothing meaningful could be deduced about whether ApeA works by Abi.
On 2026-01-27 09:49:07, user Luis Graca wrote:
This preprint was published in 2024: https://www.nature.com/articles/s41421-024-00681-0 <br /> Citation for the peer reviewed publication:<br /> Kumar S, Basto AP, Ribeiro F, Almeida, SCP, Campos P, Peres C, Pulvirenti N, Al-Khalidi S, Kilbey A, Tosello J, Piaggio E, Russo M, Gama-Carvalho M, Coffelt SB, Roberts EW, Geginat J, Florindo HF, Graca L (2024) Specialized Tfh cell subsets driving type-1 and type-2 humoral responses in lymphoid tissue. Cell Discov 10, 64. 10.1038/s41421-024-00681-0
On 2026-01-26 23:37:54, user Oladapo wrote:
Commentary on obesity impairs the antitumor activity of CAR T cells in triple-negative breast cancer.<br /> Chimeric antigen receptor (CAR) T cell therapy has achieved substantial success in hematological malignancies but remains largely ineffective in solid tumors, including triple-negative breast cancer (TNBC). In this preprint, the authors address this important challenge by examining how obesity alters the tumor microenvironment (TME) to limit CAR-T cell efficacy, with a focus on the inhibitory checkpoint molecule B7-H3. The experimental rationale is well-conceived, and the development of a CAR-T platform targeting a checkpoint pathway relevant to TNBC is innovative and timely. The study provides valuable insight into the interaction between host metabolic state and immunotherapy outcomes. However, some aspects of the experimental design, data analysis, and interpretation require further clarification to strengthen the <br /> study's impact and significance.<br /> A major assumption in Figure 1 is that obesity-associated inflammatory cytokines promote B7-H3 expression in TNBC. Based on this, the authors focus primarily on IFN-γ and TNF as mediators of this effect. While both cytokines are established regulators of immune checkpoint pathways, it is unclear whether their selection was informed by preliminary data demonstrating their elevation in the obesity-associated TNBC models used here. Obesity is a complex inflammatory milieu that includes not only pro-inflammatory cytokines, but also anti-inflammatory and immunoregulatory mediators such as IL-10 and TGF-β, which have also been implicated in immune suppression and checkpoint regulation within the TME. Background cytokine profiling or broader screening should be conducted to provide a strong justification for choosing specific cytokines.<br /> The experimental design presented in Figure 2 includes four biologically distinct groups: lean control and obese mice bearing either scramble or B7-H3–knockdown E0771 tumors. However, the analytical approach used relied on splitting these groups and performing multiple Student’s t-tests. A direct comparison across all groups using a one- or two-way ANOVA, as appropriate, is more statistically rigorous and better suited for this setting.<br /> The authors report differences in immune cell frequencies within the TME, which represents an important strength of the study. However, total frequencies were presented without gating strategies or phenotypic characterization. Assessment of tumor immune infiltration requires more detailed profiling because immune cell activation, exhaustion, or functionality can differ substantially even with similar total frequency. Including gating schematics and markers defining functional states would improve data interpretation and provide a better understanding of how obesity reshapes the immune landscape in TNBC.<br /> The authors did not assess changes in B7-H3 expression during tumor progression. Kinetic analysis of B7-H3 expression would help understand constitutive expression and changes driven by tumor growth, immune infiltration, or obesity. Such information could clarify whether obesity accelerates checkpoint upregulation during tumor progression.<br /> CAR-T cell cytotoxicity was inferred primarily from cytokine production (IL-2 and IFN-γ). Although these cytokines reflect T cell activation, they do not directly measure cytolytic activity. Degranulation assays assessing granzyme B, perforin, and CD107a expression would provide a direct and widely accepted measure of T cell cytotoxicity. <br /> An inconsistency is noted in the reported age of mice used in Figure 6. The text describes animals aged 25–30 weeks, but the schematic indicates 15 weeks. The strong influence of age on immune function and metabolic status necessitates consistency in animal age. This discrepancy should be corrected, and age should be clearly reported across all experiments.<br /> An interesting observation is that CAR-T cells generated from younger mice were able to reject tumors in both lean and obese hosts. In contrast, CAR-T cells from older mice failed to suppress tumor growth in DIO mice. This finding suggests an age-dependent decline in CAR-T cell functionality. However, this aspect is not fully explored. Additional discussion or mechanistic investigation of how donor age influences CAR-T fitness would substantially enhance the study's impact.<br /> Finally, the memory and recall experiments in Figure 7 raise important questions regarding differential survival after tumor rechallenge. The authors should report CAR-T cell persistence levels in lean and obese mice prior to rechallenge and provide tumor growth kinetics following rechallenge. Clarifying whether differences in survival are driven by primary tumor burden, metastatic dissemination, or immune memory failure would strengthen the interpretation of these results.<br /> Overall, this study addresses a timely and important question at the intersection of obesity, immune checkpoints, and CAR-T therapy in TNBC. The experimental rationale is strong, and the focus on B7-H3 as a mediator of immunotherapy resistance is well justified. Addressing the points outlined above would further strengthen the rigor, clarity, and translational relevance of the work. Also, this will help define how host metabolic state, age, and immune regulation collectively shape CAR-T efficacy in solid tumors.
On 2026-01-19 17:46:14, user Jncbge wrote:
Final Remarks
Overall there were some very interesting talking points to this paper. It really brings up some interesting considerations when using CAR-T cell therapy that should be researched further. We hope that the submission and review process goes well!
On 2026-01-19 17:45:59, user Jncbge wrote:
Figure 7<br /> It would be helpful to report the body mass of the mice throughout these experiments. With these longer experiments where the mice are exposed to a multitude of agents (tumor cells, CAR-T cells, and more tumor cells), were the DIO mice still significantly more obese than the low-fat diet mice throughout the roughly 20 weeks? It should also be reported whether or not the mice were kept on their high-fat or low-fat diet throughout these experiments.
It would be helpful to report endpoint tumor mass or tumor volume after rechallenge.
It is not explained why the timepoint of 72 hours post rechallenge was chosen, is there a reason for this?
On 2026-01-19 17:44:47, user Jncbge wrote:
Figure 6<br /> The finding that tumor volume is not significantly different when given CAR-T cells from either a DIO or CON mouse should be investigated further. It would suggest that there is not an inherent deficiency in CAR-T cell function, at least initially, based on diet despite the earlier finding in Figure 4 that the different CAR-T cells exhibit differences in exhaustion.
In Figure 6B, it would be more informative to include nontransduced control on same graph or at least match the axis values to figure 6D.
Why was the study in figure 4D stopped at 15 days when it is shown in figure 6B that tumor growth continues despite injections even in healthy mice?
I’m not sure it can ultimately be concluded that these results indicate changes in the TME. I think that more analysis would need to be done as all these figures indicate is that DIO mice appear worse at controlling tumor volume. Additionally, it doesn’t say anything about T cell function either as regardless of T cell donor, the tumors are shown to have reduced volume. I think that this is an overstatement of what the results are showing.
On 2026-01-19 17:44:22, user Jncbge wrote:
Figure 2<br /> It is not clear to me how simply suppressing the expression of B7H3 in tumors would lead to a reduction in tumor size. This would suggest that you don’t even need CAR-T cells to reduce tumor burden in obese patients. What are your thoughts on this?
In Figure 2E-L, The graphs should be combined to show all 4 experimental groups on one graph (scramble E0771 administered to control mice, shB7H3 E0771 administered to control mice, scramble E0771 administered to DIO mice, and shB7H3 E0771 administered to DIO mice) and statistical analysis should be performed across all 4 groups (with an ANOVA). As an example, 2E should be combined with 2I.
In figure 2M, comparing these 2 groups is not informative in terms of assessing the transcriptomic changes that occur when B7-H3 suppressed tumor cells are administered to lean vs obese mice. The comparison between control mice that received tumor cells that were not B7-H3 suppressed vs DIO mice that received B7-H3 suppressed tumor cells is not entirely useful unless the other two groups are presented. The data presented do not adequately support the claim that suppressing B7-H3 in obesity helps restore immune function, especially without seeing the transcriptomic changes that occur in control mice given B7-H3 suppressed tumor cells. Additionally, from a graphic design perspective it is difficult to interpret this figure without some way to indicate differences in circle size aside from just hoping the reader will observe it.
On 2026-01-19 17:43:52, user Jncbge wrote:
Figure 1 <br /> Lines 256-259 You connect B7-H3 expression to lower survival in breast cancer and increased PD-L1 expression in patients with breast cancer. They then decide to investigate IFNy and TNF as “obesity derived inflammatory cues” which could impact B7-H3 expression. I am unsure about why these two cytokines were chosen specifically. It may be helpful for readers to outline the choice of cytokines here more.
In the supplemental figures for figure 1, you observe no significant difference in B7-H3 relative expression when using TNF and IFNy for either human cancer cell line. I would think that if there is no significant difference when both cytokines are present in your assay, in vivo this may not affect B7-H3 expression when both cytokines would be elevated. What are your thoughts on this as I saw no mention of it in the discussion.
On 2026-01-19 17:43:14, user Jncbge wrote:
Hello,<br /> Your pre-print was recently shared in a journal club at our school. Some of the graduate students thought it might be a good exercise to practice writing feedback and questions about your paper. Please find below some of the comments we came up with.
Overall thoughts
The title seems to overstate what is actually found in the paper. In a mouse model, you observed that CAR-T cells specific for B7-H3 were found to reduce tumor volume in a murine E0771 model. Furthermore, the analysis you did in figure 4 revealed that there appeared to be differences in exhaustion phenotype and glycolytic activity, but not in cytolytic killing or cytokine secretion. In figure 6, it is further shown that non transduced DIO mice display a tumor volume on average of 600 mm3 by 15 days, whereas when DIO mice are given CAR-T cells from a DIO donor, the average tumor volume is around 325 mm3 by 25 days. This would suggest that the CAR-T cells are still working in the obese mice. Perhaps something else is contributing to the change in volume.
Regarding DIO mice, have they developed poor glycemic control at the time of the experiments? Further, would performing experiments when the mice have been on high-fat diets for different lengths of time (eg. 15 weeks of HFD vs 18 weeks of HFD vs 25 weeks of HFD) affect glycemic control? Without performing a glucose tolerance test, for example, it is not possible to rule out glycemic control as a possible confounding variable and attribute the phenotypes noted to obesity alone.
The timepoints should be consistent across experiments of the same type. As an example, in Figure 2, body mass is reported from day 0 - day 18, but tumor volume is reported from day 0 - day 21. Although it is unlikely that any significant change in body mass occurred in days 18 - 21, there is no way to know without reporting it. This is more relevant when looking at figure 6B and 6D. In figure 6B, the last timepoint was after 20 days, whereas in figure 6D, 15 days was the latest timepoint.
On 2026-01-26 20:42:39, user Lua Koenig wrote:
This paper was published on Jan 19th, 2026: https://doi.org/10.1093/nc/niaf064
On 2026-01-26 19:55:50, user kamir bouchareb st wrote:
thanks for this
On 2026-01-26 15:26:04, user Ole Kjaerulff wrote:
Final paper published in Journal of Cell Biology:
Viktor Karlovich Lund, Antony Chirco, Michela Caliari, Andreas Haahr Larsen, Kristoffer Tollestrup Tang, Ulrik Gether, Kenneth Lindegaard Madsen, Michael Wierer, Ole Kjaerulff; A Syd and RUFY dynein adaptor complex mediates axonal circulation of dense core vesicles. J Cell Biol 2 March 2026; 225 (3): e202507071. doi: https://doi.org/10.1083/jcb.202507071
On 2026-01-26 03:18:53, user Alexander Wolf wrote:
Jaijyan et. al. "New intranasal and injectable gene therapy for healthy 357 life extension" has been retracted.
On 2026-01-25 13:05:08, user Fabio Alfieri wrote:
This article has been accepted for publication in Zoological Journal of the Linnean Society, Published by Oxford University Press (DOI: 10.1093/zoolinnean/zlag021)
On 2026-01-25 10:53:02, user Ayan Sadhukhan wrote:
link to published version:<br /> https://onlinelibrary.wiley.com/doi/10.1111/pce.70399
On 2026-01-25 09:07:45, user Prof. T. K. Wood wrote:
On 2026-01-25 04:41:15, user Gracie Kroos wrote:
Published article now available: https://onlinelibrary.wiley.com/doi/10.1002/edn3.70240
On 2026-01-24 22:07:32, user Vojtech wrote:
L438 - this might be correct: compounds with higher NOSCs and less positive values...
On 2026-01-24 21:36:24, user Marco Fumasoni wrote:
By popular demand, we are measuring all cell size distributions also in the exponential phase. These and other new results will soon be posted here in a revised manuscript.
On 2026-01-24 07:40:19, user Alan Rees wrote:
doi:10.6620/ZS.2025.64-29<br /> Exponential Increase in a Loggerhead Sea Turtle Nesting Population: Investigating the Role of Multi-decadal Nest Protection in Kyparissia Bay, Greece<br /> This would make a good addition to you references and global analyses.
On 2026-01-23 21:45:14, user Hajime Ino wrote:
This work is currently published in Cell Reports!<br /> https://www.cell.com/cell-reports/fulltext/S2211-1247%2825%2901637-7 <br /> Thank you!
On 2026-01-23 17:50:49, user Hugo Verli wrote:
The work is extremely interesting. From the textual aspect, there are a lot of broken referentes and figures from latex. From the results, I was curious about the ligand on Cyp450. It's not clear from the text, but it seems to be the heme group. But this is not a ligand, it's a co-factor covalently bounded to the protein. Perhaps a better comparison would be with real ligand-receptor complexes with different Kon and Koff, derived from literature through methods like tau RAMD (in comparison to experimental data), as conventional MD struggle with such predictions. But the work is very promising, congratulations to the authors.
On 2026-01-23 13:59:03, user Raymond Clarke wrote:
On 2026-01-22 02:48:27, user Raymond Clarke wrote:
On 2026-01-23 11:49:36, user Jay wrote:
The text invokes “phasic activation” and “phasic dopamine transients,” yet never measures neuronal firing or dopamine release, in practice, only a light train is applied, and its relationship to actual in vivo phasic dopamine transients is left entirely unvalidated. The Introduction likewise fails to clarify this conceptual and mechanistic gap and is, in addition, noticeably out of step with recent work on subsecond dopamine dynamics and their behavioral relevance.
On 2026-01-23 09:54:27, user Soham Gupta wrote:
Author Comment: During the journal peer-review process, we noted that the anti-S titres for the OC2 group were not correctly visualized in two heatmap panels (Figure 2A and Figure 2F) in the preprint version. This was a plotting inconsistency affecting only the displayed values; the underlying data and conclusions remain unchanged. Although the issue was corrected during preparation of the published article, the corresponding update to the preprint version was inadvertently not made at that time. The corrected visualizations appear in the final published article, which also includes the complete antibody titre and qPCR datasets for transparency.<br /> Published version: https://doi.org/10.1016/j.biopha.2025.118858
On 2026-01-23 01:30:29, user Zhiyong Wang wrote:
Here is some information for the authors and readers. <br /> 1. BSL/PPKLs are not plant orthologs of human PP1s,. Plant genomes encode many PP1s that are more similar to human PP1s than BSLs to human PP1s in the catalytic domain. <br /> 2. BSLs/PPKLs are conserved in green algae, plants, and Apicomplexa, but are absent in fungi and animals (10.1128/mbio.02254-23). <br /> 3. Human PP1-gamma displayed tyrosine phosphatase activity (FEBS Letters 397 (1996) 235-238).<br /> 4. PP1 substrate specificity varies with metals (Journal of Inorganic Biochemistry 149 (2015) 1–5), and metal loading to PP1 depends on chaperones (FEBS Letters 598 (2024) 2876–2885). <br /> 5. The peptide (RKLRRKYGKRGSY) synthesized and tested in this study is based on a substrate sequence of animal PP1, and is distinct from the two reported BSL substrates, BIN2 (anisyicsrfy, Nat Cell Biol 11 (2009):1254-60) and CDKB (grgtygkvyk, Nat Plants, 2025 Nov;11(11):2395-2408), which share some sequence similarity (Maybe BSLs/PPKLs are sequence-specific, not residue-specific phosphatases? Both pT14 and pY15 of CDKB seem to be dephosphorylated – see Fig. 5d in Nat Plants, 2025 Nov;11(11):2395-2408). <br /> 6. The authors acknowledged that "It remains formally possible that a single BSL2 or BSL3 allele can support BR signaling to wild type-like levels (Fig. 2 D and E).”. I was confused by other statements inconsistent with this.
On 2026-01-22 15:06:36, user Sangeeta Nath wrote:
The article is published, please update https://www.sciencedirect.com/science/article/pii/S0925443925004983
On 2026-01-22 14:27:23, user Yi wrote:
On 2026-01-22 11:02:21, user Javier de Haro Arbona wrote:
Very cool method! Was wondering if the MULTI-ATAC_Sequences spreadsheet mentioned in the supplementary pdf is provided anywhere? I would like to check the validated Barcode & TruSeq primer sequences. Thanks!
On 2026-01-22 08:51:45, user Tomas S wrote:
This study is now published in Nucleic Acid Research: https://doi.org/10.1093/nar/gkaf1488
On 2026-01-22 03:14:26, user Jacob Schimelman wrote:
Really nice work with interesting implications! The soft/stiff labels in Figure 2 and especially Figure 3 have errors.
On 2026-01-21 09:19:45, user Wakefield, James wrote:
Really like this paper, reinforcing that the rheology of the spindle, generated by MTs, is crucial for "normal" chromosome alignment. Using variable concentrations of nocodazole to stabilise (low) or destabilise (high) MTs allows precise temporal control of spindle density/dynamics. However, it's a global change to the MTs and it's not clear what relative effect the Noc has on interpolar, kinetochore, centrosomal and augmin-mediated MTs. It would be interesting to know if these distinct populations are affected differentially and therefore what can be said about the relative contributions to spindle-chromosome rheology. In our previous work in Drosophila embryos (Hayward et la., Dev Cell 2014), we used an anti-Dgt6 antibody to specifically inactivate Augmin upon entry into mitosis (Augmin recruits the MT nucleator, g-TuRC to pre-existing spindle MTs increasing the overall density of the spindle ~2-fold). Augmin inhibition results in the dramatic loss of short spindle MTs, a reduction in spindle density and increase in pole-to-pole distance. Something we noted was that chromosome movement (as well as congression) was affected. Additionally, using a Rod-GFP fly line in the presence of Augmin inhibition, we saw all sorts of abnormal Rod-GFP movements along the kinetochore MTs that remained, suggesting something wrong with the forces between the kMT and the kinetochores. I think we talked a bit about this in the discussion - suggesting the abnormal congression was due to the rheology of the overall spindle being compromised by loss of the Augmin-generated (non-kinetochore) mass of short MTs.
On 2026-01-20 13:33:47, user Mario López Martín wrote:
This is a very cool study and really helps contextualize some of the data we got for AbaM in Acinetobacter baumannii.
In Acinetobacter, we observed some variance in AHL production depending on the culturing conditions, which in light of your results, could be closely related to RsaM/AbaM expression in WT strains.
Any clue on what culturing conditions might induce the AHL system activation?
Closely following this, very nice work!
On 2026-01-20 11:20:19, user Evolutionary Health Group wrote:
We at the Evolutionary Health Group ( https://evoheal.github.io/) really enjoyed this paper. Here are our highlights:
Authors propose a "theory-to-practice" bridge for phylogeny: take a mathematically defined "forest" algorithm (that most biologists have never used) and then test it under simulation settings chosen to look biologically reasonable (Jukes-Cantor, short branches). The work deliberately departs from the standard paradigm of "always returning a fully resolved tree". The algorithm is optimized to avoid false splits and is allowed to output partial structures or abstain entirely. This places the method firmly in a precision-first regime rather than traditional phylogenetic benchmarking.
The main onservation: the value of forest methods lies in explicitly identifying which parts of the data are informative and in providing downstream analyses with a more faithful representation of uncertainty. While the current approach outperforms NJ only in narrow regimes, the conceptual shift toward partial, conservative outputs (especially hybrid workflows that combine forests with standard tree-building methods) appears promising.
The paper data are generated under a simple but biologically valid model, and the authors release the complete pipeline for data generation and experimentation. This makes the work portable and extended in other projects focused on reliability regimes rather than "maximal resolution".
On 2026-01-20 09:20:33, user Norbert Bittner wrote:
In Figure1 the blue stretch for the collagen binding domain from Gly489 - Gly510 is 4 amino acids too long. The correct sequence stretch is GFRGPAGPNGIPGEKGPAGERG
On 2026-01-20 03:06:42, user Nosheen wrote:
This preprint presents a novel biological strategy to address PET plastic pollution by engineering environmental bacteria capable of directly utilizing PET as a carbon source. PET is widely used in packaging and textiles and persists in the environment as macro- and microplastics, posing environmental and health concerns. While PET-degrading enzymes have been studied extensively in vitro, practical whole-cell microbial solutions for environmental PET degradation have remained limited.<br /> The authors isolated a strain of Pseudomonas umsongensis that can metabolize terephthalate, a key monomer released from PET hydrolysis. To enable direct PET degradation, the strain was genetically engineered to secrete the high-activity PET hydrolase PHL7 using a recombinant twin-arginine translocation (TAT) secretion signal. This allowed extracellular degradation of PET into assimilable products. Additionally, PET was pre-treated with an organic solvent to create an amorphous and macroporous structure, significantly improving enzyme accessibility and bioavailability.<br /> The study demonstrates that the engineered bacterium can grow using PET-derived carbon, providing evidence of true microbial consumption rather than simple enzymatic breakdown. This represents an important advancement toward sustainable plastic upcycling and bioremediation approaches that could operate outside controlled laboratory conditions.<br /> However, the work remains a preprint and has not yet undergone peer review, so conclusions should be considered preliminary. The requirement for PET pre-treatment and the existence of a related patent may also influence scalability and environmental application. Despite these limitations, the study offers a valuable proof of concept for whole-cell microbial systems in plastic waste management and highlights a promising direction for future research.
On 2026-01-19 21:53:31, user Pär Jonsson wrote:
On 2026-01-19 17:46:39, user Jonathan Schatz wrote:
I am the corresponding author. A revised version of this article was published 10/1/25 in Cancer Research:
On 2026-01-19 14:37:48, user Marco Mariotti wrote:
This has now been published at https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013885 <br /> The official link will appear soon.
On 2026-01-19 10:26:20, user Nikolas Vellnow wrote:
This is a very interesting preprint. I really enjoyed reading it. You might be interested in our recent opinion piece discussing sex-based genomic differentiation as well: https://onlinelibrary.wiley.com/doi/10.1111/mec.70061
On 2026-01-19 06:30:38, user Manga yellow wrote:
I was wondering how the authors ruled out off-target effects as a potential cause of the observed recorded changes. There is a strong need to perform a gold standard WGS to rule out the off target edits.
On 2026-01-18 11:37:46, user Troy Kervin wrote:
I recommend reinterpreting the lipid raft content as there are simpler explanations.
Kervin, T. A. Factory Reset: How to Uninstall Lipid Raft Bloatware and Migrate to the Proteolipid Code. Zenodo (2026). https://doi.org/10.5281/zenodo.18225636
On 2026-01-18 05:06:42, user Tiffany Smith wrote:
I am extremely interested to see how these observations are integrated into further research. I think we are very much onto something that could potentially change many lives for the better. Good work!
On 2026-01-17 06:11:27, user Prof. T. K. Wood wrote:
Thank you for including my groundbreaking work showing CRISPR-Cas is active in E. coli, contrary to first reports by prominent labs (and our discovery has been validated). However, I do not agree with your text on line 316 that indicates “the drivers of this pattern remain unknown." We proved CRISPR-Cas is active in E. c. K-12 and determined the mechanism was silencing cryptic prophages, so the ‘driver’ for the spacers was determined and is not ‘unknown”.
On 2026-01-17 04:09:26, user Biotech Analytics wrote:
This study presents an impressive telomere-to-telomere (T2T) genome assembly for looseleaf lettuce (Lactuca sativa var. crispa cv. Green Elegance). The authors’ integration of ultra-long ONT reads with previously published HiFi and Hi-C data to close remaining gaps in Green Elegance v1.2 is technically solid and clearly described.<br /> The resulting assembly metrics are outstanding, particularly the contig N50 of 282 Mb, complete recovery of nine centromeres and 18 telomeres, and the high QV, LAI, and BUSCO scores. These results convincingly demonstrate a high-quality T2T assembly and represent a meaningful improvement over previously released lettuce genomes.<br /> This resource will be valuable for comparative genomics within the Lactuca genus, especially for studies of centromeric structure, repeat organization, and domestication-related variation among cultivated lettuce types. The high functional annotation rate further enhances its utility for breeding and functional genomics.<br /> Overall, this work provides an important genomic reference for looseleaf lettuce and makes a strong contribution to the growing collection of plant T2T assemblies.
On 2026-01-16 23:46:41, user Andrew Orr wrote:
This represents an important step forward in understanding the molecular pathways underpinning emmetropization.
On 2026-01-16 22:50:18, user Farouk Barguellil wrote:
This work was published in the journal The Lancet Microbes : https://www.thelancet.com/journals/lanmic/article/PIIS2666-5247(23)00407-X/fulltext
On 2026-01-16 20:13:51, user Yaowen Wu wrote:
Correction from the authors: The experiments shown in Fig. 4D and E were carefully repeated by the original experimenter and co-author, Shuang Li, together with an independent colleague. These repeat experiments did not reproduce the previously reported interaction between ALG-2 and LC3B. Consequently, these data have been removed from the revised manuscript.
On 2026-01-16 15:25:24, user Jonathan Perelmuter wrote:
This is a lovely manuscript; I've been waiting for someone to do these kinds of experiments in zebrafish. You cite both Yanez et. al. 2022 and the Kenney 2021 AZBA atlas, but these are not in agreement on how to anatomically defined Dc in zebrafish. How do you reconcile this?
On 2026-01-16 14:18:58, user René Gato Armas wrote:
The article is interesting, as is often the case with studies that seek to challenge established paradigms. Nevertheless, the results presented appear to describe rare, stress-induced physiological edge cases rather than a widespread or ecologically dominant behavior. The very low frequency of successful blood acquisition from intact vertebrate hosts, together with the highly artificial dehydration conditions required to elicit this behavior, suggest that the epidemiological relevance of male blood-feeding under natural conditions remains uncertain.<br /> These findings are best interpreted as an expansion of the known physiological limits of male mosquitoes, rather than as evidence warranting a fundamental revision of established knowledge in medical entomology.
On 2026-01-16 12:51:17, user Kirk Overmyer wrote:
This work has now been published, please see the reference below:<br /> _<br /> Agate Auzane, Margaretta Christita, Kai Wang, Timo Sipilä, Sitaram Rajaraman, Gugan Eswaran, Jasmin Kemppinen, Alejandro De La Fuente, Klaas Bouwmeester, Petri Auvinen, Lars Paulin, Jarkko Salojärvi, Maija Sierla, Mikael Broché, Kirk Overmyer (2025) A Novel Pathosystem With the Model Plant Arabidopsis thaliana for Defining the Molecular Basis of Taphrina Infections. Environmental Microbiology Reports 17(3) e70118. DOI: https://doi.org/10.1111/1758-2229.70118
On 2026-01-16 11:04:40, user Terezia wrote:
Dear authors,
Thank you for this interesting work! Some supplementary files referenced in the text seem to be missing—would you be able to upload them?
Thank you in advance.
On 2026-01-16 09:47:21, user Changqing Zhang wrote:
I am posting the following technical comment on behalf of Professor David Galbraith (University of Arizona).
Technical Note regarding the history and capability of flow cytometric sorting of plant protoplasts.
We read with interest the description of the PIVOT platform and its application to high-throughput functional genetics in Nicotiana benthamiana. The use of viral superinfection exclusion to ensure single multiplicity of infection (MOI) per cell is an elegant and clever approach to pooled library delivery.
However, we would like to offer a technical correction regarding the stated incompatibility of Fluorescence-Activated Cell Sorting (FACS) with N. benthamiana protoplasts. The manuscript suggests that current FACS instruments are not compatible with fragile protoplasts sizing 20-100 µm in diameter. On the contrary, the plant flow cytometry community has successfully utilized large-bore, low-pressure flow sorting for these exact cell types for over forty years.
Historically, specialized configurations—including the use of large flow tips (up to 200 µm) and reduced sheath pressure—have allowed for the high-purity sorting of intact, viable protoplasts ranging from 40 to nearly 100 µm. Furthermore, it has been demonstrated that Nicotiana protoplasts sorted via FACS remain totipotent and can be regenerated into fertile, whole plants, demonstrating that the shear forces of a correctly configured sorter are not inherently lethal to these wall-less cells.
While Magnetic-Activated Protoplast Sorting (MAPS) provides a valuable biochemical alternative for labs without access to specialized large-particle sorters, we believe the manuscript would benefit from a more accurate characterization of flow cytometry's historical and current capabilities in plant biology.
Supporting Citations for the Authors:<br /> • Harkins, K. R., & Galbraith, D. W. (1987). Factors governing the flow cytometric analysis and sorting of large biological particles. Cytometry, 8(1), 60-71. (This study details the sorting of particles up to 95 µm using specialized large flow tips).<br /> • Afonso, C. L., Harkins, K. R., Thomas-Compton, M. A., Krejci, A. E., & Galbraith, D. W. (1985). Production of somatic hybrid plants through fluorescence activated sorting of protoplasts. Nature Biotechnology (Bio/Technology), 3(9), 811-816. (Documenting the viability and regeneration of Nicotiana protoplasts following FACS).<br /> • Harkins, K. R., & Galbraith, D. W. (1984). Flow sorting and culture of plant protoplasts. Physiologia Plantarum, 60(1), 43-52.<br /> • Galbraith, D. W. (2021). Protoplast Analysis using Flow Cytometry and Sorting. In: Flow Cytometry with Plant Cells: Analysis and Sorting, Wiley-VCH.
On 2026-01-16 00:00:13, user Damien F. Meyer wrote:
This study provides compelling experimental evidence that direct host membrane contact primes Type IV secretion systems (T4SSs) through lipid mixing, independently of ATP hydrolysis or full apparatus assembly. The demonstration that lipid exchange precedes or accompanies substrate transfer in both Dot/Icm (Legionella pneumophila) and RK2 (Escherichia coli) systems is particularly elegant and mechanistically informative.
However, the concept that host contact itself acts as the primary trigger for secretion system activation is not unprecedented and was demonstrated more than 25 years ago for Type III secretion systems (T3SSs). In a seminal study, Brito et al. (1999) showed that expression of hrp genes in the plant pathogen Ralstonia solanacearum is specifically induced upon direct bacterium–plant cell contact, independently of secretion activity itself. This contact-dependent induction requires the outer membrane protein PrhA, which functions as a bacterial receptor sensing a non-diffusible signal from the plant cell wall, thereby activating virulence gene transcription (EMBO Journal, 1999).
Together, these studies suggest that contact-dependent sensing of host surfaces is a conserved and ancient principle governing the activation of bacterial secretion systems, albeit implemented through distinct molecular mechanisms (transcriptional induction in T3SSs versus lipid-mediated priming in T4SSs). Explicitly acknowledging this conceptual continuity would strengthen the broader biological context of the present work and highlight how it extends a long-standing paradigm from transcriptional regulation to biophysical membrane-level priming.
Reference<br /> Brito B., Marenda M., Barberis P., Boucher C., Genin S. (1999). PrhA, a conserved outer membrane protein of Ralstonia solanacearum, is required for sensing plant cell contact and for activation of hrp gene expression. EMBO Journal, 18(22): 5767–5778. https://doi.org/10.1093/emboj/18.22.5767
On 2026-01-15 16:18:55, user Sarah Boothby wrote:
If mitochondria are present in every cell, this study demonstrates every part of the body is affected. <br /> We need to understand what is damaging the mitochondria.<br /> This damage has been known about in post infection diseases (post viral syndrome) in England since 1989, Behen published in 1991. It's a good study. As is this - but its not only Covid 19 that triggers this peculiar metabolic illness.
On 2026-01-14 22:42:50, user Lucas Jeay-Bizot wrote:
This preprint relies on prior claims of a relationship between spontaneous respiratory phase and RP amplitude (e.g., Park et al., 2020). However, those were later shown to arise from an analytical confound; when corrected, Bayesian analyses favor the null hypothesis, indicating no association between uninstructed respiratory phase and RP amplitude (Jeay-Bizot et al. preprint https://doi.org/10.31234/osf.io/b5ka2_v1 ). In light of these results, we are left with the question of how there can be causation without correlation. In the absence of covariation, it is unclear how respiratory phase could exert a direct causal influence on the amplitude of the RP. The authors need to clarify how a causal relationship can exist without a corresponding correlation. This is essential for supporting the interpretation advanced in this preprint.
On 2026-01-14 18:58:59, user Paul Kent wrote:
FLC is not related to HCC nor is it a variant or subset. FLC is likely related to neuroendocrine tumors. It reduces credibility to still refer to FLC as "subtype" of HCC.<br /> Indeed, we and many other FLC experts have tried for 10+ years to get the WHO to stop calling FLC a "variant" when no one else does.<br /> Happy to discuss or share articles/ research on this critical point.
On 2026-01-14 17:46:06, user Joy wrote:
Hi, thank you for this paper, it was very interesting! I will be discussing it next week in my lab as it is highly relevant to my project. I am trying to use the figures as a way to visually explain the paper, but I find that they are very poor quality. Is there a way you can re-upload the figures?
On 2026-01-14 12:51:18, user Josephine Tan wrote:
This manuscript has been published in Nature Cardiovascular Research (october 2025 issue)
https://www.nature.com/articles/s44161-025-00737-8 News & Views highlight about this paper in the same issue:
On 2026-01-13 17:12:31, user Vincent J. Lynch wrote:
Any one find the Zenodo alignments yet?
On 2026-01-13 04:29:42, user Heather Lee wrote:
This is a very interesting study. However, it's unclear to me if the transcriptional and epigenomic profiling studies (Fig. 2 and 3) were conducted on D2A1-d cells grown in culture, or purified from mouse tissues.
On 2026-01-12 20:18:33, user Kat Ficalora wrote:
If possible, federal funding language should be updated to the most recent template, found here: https://www.hhs.gov/sites/default/files/hhs-grants-policy-statement-oct-2025.pdf
On 2026-01-12 08:02:30, user Alejandro Burga wrote:
Please provide the link to published manuscript. Thank you!
On 2026-01-11 14:57:12, user Ozge A. Cavus wrote:
Dear Authors,<br /> We read your paper with great interest and are attempting to apply the RegFormer framework for fine-tuning on a specific cancer dataset. The integration of GRN priors with Mamba blocks presents a promising approach.<br /> However, we are unable to reproduce the fine-tuning process or utilize RegFormer as a foundation model due to two critical missing components in the provided GitHub repository:<br /> 1. The Vocabulary File: The code calls for default_gene_vocab.json, which is essential for aligning gene token IDs with the pretrained model. Generating a new vocabulary from HGNC (as suggested by the helper functions) creates a mismatch with the pretrained embedding dimensions.<br /> 2. Pretrained Model Checkpoints: While the paper mentions pretraining on 26 million cells, the pretrained weights (checkpoint files) are not available in the repository or linked in the "Data Availability" section.<br /> Several users have raised similar concerns in the GitHub Issues section without a response. Could you please provide a link (e.g., via Stomics Cloud or Zenodo) to these essential files?
While the manuscript claims RegFormer, as a foundation model, is distributed as an open-source repository, the omission of critical checkpoints renders this claim invalid in practice. The current repository is merely a strictly code-based implementation, not a usable open-source foundation model.
Thanks for your work!
On 2026-01-11 13:53:13, user Salma Fareed wrote:
Supplementary materials are available on Zenodo: https://doi.org/10.5281/zenodo.17929370 <br /> (concept DOI: https://doi.org/10.5281/zenodo.17688981 <br /> ). Direct record: https://zenodo.org/records/17929370 <br /> .
On 2026-01-11 12:16:07, user Ben Liesfeld wrote:
Publishing these detailed benchmarks is very helpful for the community. However, the GiaB SV v0.6 reference data set is outdated in my view, and the new HG002 T2TQ100 benchmark would provide a more accurate and comprehensive assessment. Would love to see those results.
On 2026-01-11 04:15:57, user Diorge Souza wrote:
This bioRxiv preprint has been published in a peer-reviewed journal: https://link.springer.com/article/10.1038/s44319-024-00060-6
On 2026-01-10 00:42:43, user Jean-Michel Ané wrote:
Great manuscript. You could consider citing this paper, showing that pairwise interactions are the major drivers of a small SynCom dynamics:<br /> https://link.springer.com/article/10.15252/msb.20178157
On 2026-01-09 20:46:37, user Sam Zimmerman wrote:
Hello, I am very excited for this paper and tried out the latest version on my own data and it worked well!
But apologies if I missed this in the pre-print, but have you evaluated what happens if there is not a perfect 1:1 matching of cell types in the spatial and single cell reference? For example, what happens if there is a cell type in the single cell data that is not in the spatial transcriptomics data. Will the expression data be over-corrected and create a cluster of cells not really there? And also, what happens if there are cell types (e.g. neutrophils) in the spatial transcriptomics data that is not in the single cell reference? Will the adjusted expression valuesn hide cell types only in the spatial data but not in the RNAseq?
Thank you for making a great tool.
Best Regards,<br /> Sam Zimmerman
On 2026-01-09 12:40:02, user Benoit Lefebvre wrote:
Now published in Frontiers in Plant Science doi: 10.3389/fpls.2025.1705961
On 2026-01-09 12:39:02, user Benoit Lefebvre wrote:
Now published in The Plant Cell, doi: 10.1093/plcell/koaf201
On 2026-01-08 22:10:57, user Przemyslaw Gorzelak wrote:
Manuscript accepted and published in Acta Biomaterialia: https://doi.org/10.1016/j.actbio.2026.01.016
On 2026-01-08 20:18:20, user Gonzalo Marin wrote:
There is a lot of work in this study and the results are very interesting. However, I think the claim already implicit in the title suggesting that the mice GABAergic cells surrounding the Pbg represents Imc neurons of birds is unfounded. To begin with, Imc neurons are strongly motion selective, as are the entire isthmic circuit and tectofugal system of birds, and do not respond to static gratings. In fact, a missing aspect of this very complete study is to record from the PLTI's neurons and see if they have some selectivity to the orientation of the gratings used in the behavioral paradigm. In this respect, why using gratings in the behavioral tests and looming stimulation in the electrophysiological recording experiments in in intermediate layers of the SC?.<br /> The avian isthmotectal system, composed by the Ipc, Imc and SLu nuclei, is an incredible mechanism that seems to mediate stimulus competition, perhaps spatial attention, and it is very tempting to look for a similar system in mammals. However, there are substantial anatomical and physiological differences between the Ipc and Pbg to assume that they are homolog or play a similar function, and the same applies for the Imc and the PLTi. It seems this study found an important component of a neural mechanism mediating stimulus competition in mice, but my guess is that it is entirely different to the avian one.
On 2026-01-08 17:50:25, user Eleonora Bartoli wrote:
Updated Competing Interest Statement:<br /> S.A.S. is a consultant for Boston Scientific, Neuropace, Koh Young, Zimmer Biomet, Varian Medical, Sensoria Therapeutics and Abbott Laboratories, and a co-founder of Motif Neurotech. The remaining authors declare no competing interests.
On 2026-01-08 17:39:41, user Charles McAnany wrote:
This was a delightful paper! I've found in my work that translational positioning is almost entirely motif-driven, but I'd found that motifs didn't tend to set a 10 bp register for nucleosomes even though the 10 bp signal was present in the data. Your work convincingly shows that the 10 bp register is almost entirely intrinsic to the nucleosomal DNA sequence. The results on P falciparum are particularly neat; I never expected that a eukaryotic genome would lose its nucleosomal positioning signals.
On 2026-01-08 16:17:40, user GoFUN wrote:
By seamlessly integrating proteomics and genomics through the Phase-APEX2-MS and Phase-APEX2-seq platforms, the authors have not only achieved unprecedented mapping accuracy but also uncovered profound 'molecular grammars' that fundamentally advance our understanding of nucleolar and stress granule dynamics.
On 2026-01-07 23:58:44, user Công Minh wrote:
You have said "In targeted SRM, the data for a given transition and matrix are one-dimensional time series, I(t), measured as a function of retention time t. We exploit<br /> this structure by using a continuous wavelet transform (CWT) with a Mexican-hat mother wavelet to identify peaks across wavelet scales in blank and sample chromatograms.". As I know, the peak in LC-MS/MS have the shape of peak are Gaussian or EMG functions, and CWT with a Ricker Wavelet (Mexican-hat wavelet) have meaning is Gaussian's peak. So, how do you clarity to it?
Between Monte Carlo and Machine/Deep Learning which one better to predict what is peak or noise?
Thank you so much!
Harley
On 2026-01-07 23:35:32, user Dario A. Vitturi wrote:
This manuscript has been accepted for publication in Redox Biology. https://doi.org/10.1016/j.redox.2026.104009
On 2026-01-07 19:37:34, user Clint Canal wrote:
We conducted further tests of the affinities of lurasidone and SB-269970 at 5-HT7Rs in room-temperature SBB and abECF with the addition of 0.1% BSA (N=5, 96-well plates per medium), and observed no impact of the media on their affinities; there were no statistically significant differences in each ligand's affinity at 5-HT7Rs in SBB compared to abECF when BSA was included. Lurasidone Ki = 35 nM in SBB with BSA and 37 nM in abECF with BSA; SB-269970 Ki = 4.1 nM in SBB with BSA and 6.3 nM in abECF with BSA. Also, in the recipe for abECF, "21.0 mM Na2HPO4" should be "0.21 mM Na2HPO4."
On 2026-01-07 15:43:46, user Black Wang wrote:
Is this non-coding function of PINK1 specific to muscle cells? It would be nice to test it out in HeLa cells as well. To detect PINK1 protein level, you can either treat cells with MG132 or CCCP. This will be a good control. Will mouse or rat PINK1 mRNA rescue Tet2 KO phenotype? The paper can be more informative by identifying the specific PINK1 mRNA sequence required for binding to YME1L1.
On 2026-01-07 14:19:15, user Tom Langton wrote:
On 2026-01-07 13:34:55, user kamounlab wrote:
I thank the authors for sharing this impressive large-scale analysis of AlphaFold models for host–pathogen PPIs and for going beyond benchmarking by classifying mimicry modes (domain / structural motif / linear motif) and experimentally testing selected peptide interactions.
One related piece of work seems missing from the discussion/citations: Ibrahim et al. (2023). That paper uses AF2-multimer specifically to identify functional short linear motifs (AIM/LIR) that mediate ATG8/LC3 interactions, including noncanonical motifs and pathogen/virus-encoded virulence factors targeting host autophagy, and it combines modeling with phylogenetic analysis and binding/functional assays.
Given the conclusion that linear-motif mimicry is frequent, a discussion of Ibrahim et al. would help place the findings in the context of prior AF2-multimer-enabled SLiM discovery—while also clarifying what’s novel here (scale across thousands of host–pathogen PPIs and comparative interface/mimicry analysis versus a focused, mechanism-driven motif family).
Citation: Ibrahim T, Khandare V, Mirkin FG, Tumtas Y, Bubeck D, Bozkurt TO (2023) AlphaFold2-multimer guided high-accuracy prediction of typical and atypical ATG8-binding motifs. PLoS Biol 21(2): e3001962. https://doi.org/10.1371/journal.pbio.3001962
The story behind the paper: Unleash your inner Ninja — when the research tempo accelerates https://kamounlab.medium.com/unleash-your-inner-ninja-when-the-research-tempo-accelerates-364344c043f6
On 2026-01-07 08:47:30, user Erwan Gueguen wrote:
This article is now published here: https://enviromicro-journals.onlinelibrary.wiley.com/doi/full/10.1111/1758-2229.70111
On 2026-01-07 08:47:00, user Erwan Gueguen wrote:
This article is now published here: https://enviromicro-journals.onlinelibrary.wiley.com/doi/10.1111/1462-2920.70095
On 2026-01-07 07:17:54, user Elisabeth Bik wrote:
Several figure panels in this preprint, now published in Oncogene, appear to match those in older papers from the same research group, where they are labeled as different experiments. More details here: https://pubpeer.com/publications/747DF57C1B267504ED4488B2EA9B4A
On 2026-01-06 20:30:20, user Camilo Duarte Cordon wrote:
This preprint has now been published in a journal of biomechanical engineering at https://doi.org/10.1115/1.4070349
On 2026-01-06 16:17:32, user Brian O'Rourke wrote:
The final version of this wonderful paper has been published in JCI Insight in December 2025. <br /> Link: https://doi.org/10.1172/jci.insight.193164
On 2026-01-06 11:02:27, user Holroyd, Natalie wrote:
The peer-reviewed version of this article has been published in Biology Methods and Protocols. It is available here - https://doi.org/10.1093/biomethods/bpaf087
On 2026-01-06 06:21:43, user Florian Pflug wrote:
This article was published in Nature Communications 16, 10523 (2025), DOI 10.1038/s41467-025-65530-4. https://www.nature.com/articles/s41467-025-65530-4
On 2026-01-05 18:31:02, user Ben Zaepfel wrote:
Could the authors please upload the supplemental figures referenced within this manuscript?
On 2026-01-04 21:57:43, user Elisabeth Bik wrote:
There are several concerns about this paper, illustrated in more detail on PubPeer: https://pubpeer.com/publications/4AA04A4E8D27C178FE42F91EC1327C
Issues found:<br /> * Several undisclosed splices in Figures 5E and S6, where lanes might have been reused in combination with lanes from different blots<br /> * A white rectangle in Figure 4B that appears to cover up one or two bands<br /> * A duplicated Ran panel between Figures 1C and 2E.
I hope the authors can address these issues - so far the corresponding author has only replied with a screenshot complaining about "Pubpeer attacks".
On 2026-01-04 20:04:49, user Elisabeth Bik wrote:
Several panels in Figure 1 appear to be inappropriate duplications. This was already pointed out on PubPeer in July 2024, but the authors never uploaded a new version to address these concerns. In addition, Figure 3 also appears to contain two sets of duplications. I hope the authors are willing to address these as well.
On 2026-01-03 13:53:18, user German Dziebel wrote:
Suppl Mat, P. 182-183 (my underlining); " We see that Native Americans exhibit lower match rates to Denisova 3 and Vindija 33.19 for both Denisovan-like and Neandertal-like segments, respectively, than other populations (except Oceanians, where some Denisovan segments may be misidentified as Neandertal segments Fig.S102 and Fig. S103 suggesting a higher false positive rate in Native Americans (i.e. modern human ancestry misidentified as archaic ancestry). Consistent with this observation, the average match rate in Native Americans (and Oceanians) for segments of at least 0.1cM does not stand out from that of other populations (Fig. S104). It is likely that the results for Native Americans are confounded by greater genetic drift between the allele frequencies of Native Americans and those of Africans used as reference for distinguishing archaic and modern human ancestry."
So basically the research team apriori assumes that Amerindians are recent and hence label Amerindians' excessive matches to a 200,000 year old Denisovan sequence as "false positives". This does not take into account the hypothesis that modern humans originated from an East Asian hominin, speciated in the New World into anatomically and behaviorally modern humans and expanded out of America as a single wave into the Old World where they admixed with later Denisovans (in Oceania and Asia), Neandertals in Asia and Europe and with archaic Africans in Africa. See anthropogenesis.kinshipstud....
On 2026-01-03 05:14:10, user Kien Xuan Ngo wrote:
It has been published: https://link.springer.com/chapter/10.1007/978-981-95-4963-4_7
On 2026-01-02 22:30:26, user Alex wrote:
The manuscript has been published for several weeks (since Nov 10) but failed to be linked<br /> https://www.sciencedirect.com/science/article/pii/S016836592500803X
On 2026-01-02 18:58:56, user Aleksandar Milosavljevic wrote:
The article claims difference between uRNA and exRNA by narrowly defining exRNA as being carried by vesicles (see the Discussion section). This is inaccurate, per the results of the US NIH Common Fund Extracellular RNA Communication Consortium (ERCC) (see https://isevjournals.onlinelibrary.wiley.com/doi/10.1002/jev2.70016 ) which found much exRNA to be carried by lipoproteins and a diversity of protein aggregates. None of the hundreds of papers produced by the consortium members were cited.
On 2026-01-02 17:10:17, user Junyi wrote:
Hi All,<br /> this manuscript has been published on communications biology https://www.nature.com/articles/s42003-025-09150-0
On 2026-01-02 12:28:50, user Kumar Saurabh Singh wrote:
@bioRxiv The manuscript has been published now. Could you link the preprint to the publication?
https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003307
On 2026-01-02 11:00:36, user bin ni wrote:
This manuscript has been published in Cell Host & Microbe entitled “Soil organic carbon mediates plant immunity-rhizosphere microbiome interactions and controls colonization resistance to microbial inoculants”. For details, please check: https://doi.org/10.1016/j.chom.2025.10.002
On 2026-01-02 03:51:51, user Michael wrote:
A lot has changed in the two years since this was posted. https://microscopynotes.com/AI/NanoBanana/
On 2026-01-02 02:01:42, user Matthew Niepielko wrote:
Very interesting study highlighting a functional role for Vasa in Drosophila germ granule development.
In Valentino et al. 2022 ( https://pubmed.ncbi.nlm.nih.gov/35288123/) the authors mathematically predict that Drosophila germ granule proteins have a functional role in mediating mRNA localization and germ granule composition of nos and pgc. By adding several new theoretical germ granule behaviors to the mathematical model, the authors conclude “that the germ granule protein ensemble has a significant influence on germ granule mRNA composition [mRNA localization], which is consistent with studies showing the importance of protein-based condensation mechanisms in the assembly of RNA-rich P granules in C. elegans (Folkmann, et al. 2021and Schmidt et al. 2021)."
For example, one parameter includes a soft cap for germ granule mRNA carrying capacity that represents Osk’s biophysical ability to fluctuate between granules, first identified in Trcek et al. 2020. “The soft cap allows for granules to recruit and contain mRNA clusters that are larger than their carrying capacity.” By incorporating a soft cap that can recapitulate biological data, their results support “the presence of support proteins within the granule that can stabilize [mRNA] clusters.”
Given the mathematical predictions of the existence of functional roles for non-Osk germ granule proteins in mRNA localization from Valentino et al. 2022, it would be helpful to the field and exciting to read about a more detailed introduction and discussion connecting the experimental results of this study to the mathematical modeling results from previous Drosophila germ granule research.
On 2026-01-01 18:03:37, user Eric Kernfeld wrote:
This is terrific work, really super thorough and interesting.
I think you may need to update the description of the Norman 2019 data -- it's in K562 erythroleukemia cells, not A549 lung epithelial cancer.
On 2026-01-01 17:24:31, user Jean-Michel Ané wrote:
Dear colleagues,
I want to preface this comment by stating that I am not, and did not, serve as a reviewer for this manuscript. We discussed it in my lab recently and have a suggestion for the authors.
Briefly, we are concerned that the claim that GBP1 is a negative regulator of biological nitrogen fixation may be affected by the normalization approach used for nitrogenease activity (ARA). In this manuscript, as far as I understand, the ARA data were normalized with the nodule weight. The authors show that the number of nodule per plant is not affected by the gbp1 mutations, but the images of nodules provided suggest that gbp1 nodules are slightly smaller than wild-type nodules. If the nodule weight is smaller in gbp1 mutants than in wild-type plants, the normalized ARA activity may appear larger in the gbp1 mutants than in wild-type plants.
We suggest that the authors add data on nodule weight in gbp1 mutants and wild-type plants, and present ARA data normalized per nodule or per plant, in addition to the data already shown. They probably already have this data, and it could strengthen their manuscript. I hope that this will help a bit!
Sincerely,
Jean-Michel
On 2026-01-01 16:34:23, user Saikat Mukhopadhyay wrote:
Final revised version published in PLOS genetics.<br /> https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1012008 <br /> https://pubmed.ncbi.nlm.nih.gov/41474822/
On 2026-01-01 13:23:44, user Javier Babi Almenar wrote:
This preprint is now published as a peer-reviewed article in Ecosystem Services. The doi is: https://doi.org/10.1016/j.ecoser.2025.101804
On 2025-12-30 17:41:37, user Ismatullah Khan Niazi wrote:
The methodology is clearly explained, and the potential impact on genome engineering is significant.
On 2025-12-30 17:06:38, user Antonio Cassone wrote:
When I suggested that Epithelial Cells, an essential component of innate immunity , were likely to learn from experience (be trained) (see Cassone A, mBio<br /> . 2018 May 22;9(3):e00570-18.<br /> The Case for an Expanded Concept of Trained Immunity) I proposed the vaginal infection by Candida albicans as a study model. Now I see this important contribution by Sekar and collaborators working with oral epithelial cells and Candida albicans, and showing TI with a distinctive metabolic induction( fatty acids). While the expectation remains that some investigators will approach VVC/TI, I hope this novel contribution with oral EC/Candida could be quickly reviewed and published in a Journal with a large audience.
On 2025-12-30 09:40:06, user Sangeeta Nath wrote:
Please add the original link of the paper DOI: 10.1016/j.isci.2024.110565
On 2025-12-30 06:26:06, user THT wrote:
Three structures of HSV-1 HP and HPI have already been published several months ago, with coordinates released, and an additional manuscript is available on bioRxiv. The authors of the current submission have chosen not to reference these studies or to compare their data with the existing structural information.
On 2025-12-30 04:25:55, user Mojtaba Madadi Asl wrote:
This article has been certified by peer review, and published in the following journal:
PLoS Computational Biology 19(2): e1010853 (2023)<br /> DOI: https://doi.org/10.1371/journal.pcbi.1010853
On 2025-12-30 04:23:15, user Mojtaba Madadi Asl wrote:
This article has been certified by peer review, and published in the following journal:
Physical Review Research 7, 023128 (2025)<br /> DOI: https://doi.org/10.1103/PhysRevResearch.7.023128
On 2025-12-29 21:14:03, user Cornett, Evan M. wrote:
published 10.1021/acs.jproteome.4c00685
On 2025-12-29 21:12:51, user Hector Franco Loponte wrote:
This article has been published on Nature Communications ( https://www.nature.com/articles/s41467-025-65265-2 ).
On 2025-12-29 19:42:33, user Scott Zawieja wrote:
In the discussion the paragraph including the following "It also reasons that telocytes are involved in cLV contractions, as LMCs are akin to smooth muscle cells that lack the ionic mechanisms required for action potential regeneration and electrical signals that efficiently propagate between muscle cells (64). Thus, LMCs likely rely on a telocyte network for signal conduction. Consistently, telocytes mediate rhythmic electrical activity in other tissues (65), which is believed to depend on ion channels for generating pacemaking currents (66, 67). Interestingly, electrically coupled cells are typically connected by gap junctions (63), and evidence demonstrating this physical link between telocytes and LMCs does not exist (6). " should be corrected.
LMCs have been shown to express the calcium activated chloride current Ano1/TMEM16a in multiple publications and this channel is responsible for pacemaker activity in ICCs (PMID: 30862712, 37851027, 38704841, 40932335, 41279936. Furthermore, LMCs have gap junctions, specifically Cx45 (Gjc1) and its role in LMC-LMC electrical communication is well established (PMID: 30355030, 33050046, 40932335).
On 2025-12-29 19:21:43, user Renzo Huber wrote:
Nice exciting studies. <br /> To include this manuscript into the table of all human layer-fMRI papers , could you confirm few details that i could not find in the manuscript:
I assume the GRE BOLD sequence was a 2D-sequence, (not 3D that is used for most of other studie)?
I assume you used a SIEMENS 7T Magntom scanners (e.g. a 7T plus), not a clinical Terra or Terra.X scanner?
unrelated, are you sure that you had 32 transmit channels and 4 receive? I suspect it to be the other way around?
On 2025-12-27 21:28:41, user Suleman khan Zadran wrote:
This is indeed a nice work using a bispecific antibody targeting both CD276 and GD2. I would really appreciate including the amino acid sequences of anti-GD2 and anti-CD276 moieties in the method and material section.
On 2025-12-25 21:13:22, user Meinhard Simon wrote:
This manuscript is now published in Microbiome<br /> ( https://link.springer.com/article/10.1186/s40168-025-02259-8 )
On 2025-12-25 15:51:18, user Noam Guetta wrote:
This paper is very interesting. I just couldn't find the Asgard ESCRT-IIIA protein's N' terminal sequence from the accession number, can you refer me to it? Thank you!
On 2025-12-25 14:30:25, user Wenxing Yang wrote:
Hi all, this is Wenxing. This paper has been published in a Chinese Journal, which is indexed by Pubmed ( https://pmc.ncbi.nlm.nih.gov/articles/PMC12709095/ ). Please cite as: Feng L, Zhao R, Zhang K, Yang W. From the 2^-ΔΔCT Method to the 2^-CT Method: A More Rigorous Approach to Real-time Quantitative Polymerase Chain Reaction Data Analysis. Journal of Sichuan University (Medical Sciences). 2025. 56(5):1405–1411. DOI: 10.12182/20250960402.
On 2025-12-24 14:30:56, user Fabio wrote:
Are there plans for a similar study on Ethiopian Jews lineages?
On 2025-12-23 19:31:04, user Olivier de Jong wrote:
Final manuscript has been published: https://doi.org/10.1038/s41467-025-65995-3
On 2025-12-23 15:46:04, user SanACVE wrote:
This article is now published at https://doi.org/10.1016/j.isci.2025.113831
On 2025-12-23 11:02:16, user Kana M Sureshan wrote:
Metabolism has long been mischaracterized as a static, background process. This study challenges that view, demonstrating that core metabolic pathways and nutrient uptake fluctuate in sync with the cell cycle. By actively driving proliferation and cell fate, metabolism emerges as a dynamic regulator rather than a passive observer—a significant shift in our understanding of cellular biology. I wonder if the same sync can be seen in eukaryots ! Anyways, its a great study. Congratulations to the authors
On 2025-12-22 17:19:15, user Soumitra Pal wrote:
For EvoGeneX, could you please cite this paper? https://www.liebertpub.com/doi/10.1089/cmb.2022.0121 . Thank you.
On 2025-12-21 21:44:12, user Zhang Cheng wrote:
The article was published in Environ. Sci. Technol. 2025, 59, 42, 22624–22637.<br /> DOI: https://doi.org/10.1021/acs.est.5c05925
On 2025-12-21 08:01:33, user Bart De Spiegeleer wrote:
This is an interesting study. An attention point is the data-set used: it is recommended to include also recent studies with particular peptides (eg Biomolecules 2023, 13(2), 296; https://doi.org/10.3390/biom13020296 ), next to the mentioned databases.
On 2025-12-20 17:34:48, user Philipp Niethammer wrote:
A substantially revised version of Zaza's outstanding PhD work is accepted (in principle) at Nature Communications. Many thanks to the reviewers and editor for their constructive comments and guidance!
On 2025-12-20 16:11:26, user Ibrahim Hasan wrote:
Now published in IEEE IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) doi: 10.1109/TNSRE.2025.3635012
On 2025-12-20 03:42:54, user Misha Koksharov wrote:
Is there a way to easily do something similar to Protein Blast on the public server (preferably, with taxonomy filtering)?
On 2025-12-19 20:20:10, user Michael Ailion wrote:
This manuscript documents careful genetic analysis to better understand where and how Rho signaling acts in the C. elegans egg laying circuit. The authors demonstrate that Rho functions in mature neurons to promote egg laying, as well as in vulval muscle. By using calcium imaging, the authors were able to demonstrate how Rho signaling (specifically in the HSN neurons) regulates cell excitability presynaptically (HSN) and postsynaptically (vulval muscles). We found the experiments to be well designed and the data to be robust, with the major conclusions to be supported by the data.
Minor comments:
1) The introduction included a detailed analysis of the Gq signaling pathway and the candidate targets that regulate neuronal activity (i.e. DAG-regulated effectors and ion channels), but the scope of the paper does not include testing or identifying the targets downstream of TrioRhoGEF/Rho. On the other hand, the focus of this manuscript is neurotransmission in the egg laying circuit, and little detail is provided about how and what neurotransmitters are released by HSN. Only in the results section is NLP-3 mentioned, but it is known that both serotonin and NLP-3 released from HSN each contribute significantly to egg laying. <br /> 2) The authors conclude that Rho promotes synaptic transmission, and this is on the whole correct, but the authors could be more careful/precise with their wording and interpretations. As noted in comment 1, both serotonin and NLP-3 contribute to synaptic transmission in the egg laying circuit, but it is not known how directly these two components act in synaptic transmission. For example, NLP-3 is a neuropeptide that is released from dense core vesicles (DCVs), and it is possible that serotonin is also incorporated into DCVs as well as synaptic vesicles. In addition, serotonin and NLP-3 are known to act extrasynaptically as well as synaptically, and it is possible that Rho contributes to extrasynaptic release of serotonin and NLP-3. <br /> 3) When analyzing their data, the authors bin calcium imaging measurements in the active vs inactive state. The active and inactive egg laying states are characteristic for wildtype worms, but as the authors show, altering the activity of the HSN affects egg laying. Another interpretation of their data is that when Rho is activated (HSN::Rho-1(G14V)) the worm is always in the active egg laying state, and when Rho is inhibited (HSN C3 Transferase) the worm never enters the active egg laying state. While we don’t think they need to change how they analyze the data, the authors could just add this interpretation to the discussion. <br /> 4) We feel like the authors should include a more detailed discussion of why they see a difference in the effect of expressing dominant negative Rho (T19N) vs the C3 transferase in HSN. Why did Rho-1(T19N) expressed in HSN not show such a clear inhibition of calcium activity and egg laying as the C3 transferase expressed in HSN?<br /> 5) In general, gain-of-function experiments are hard to interpret. Activated Rho could increase cell excitability, but that does not necessarily mean that is the function of Rho normally. The loss-of-function experiments are more convincing, aside from the discrepancy we noted in comment 4. This could be noted in the discussion. <br /> 6) Lines 148 & 179: provide more detail or a reference for how extrachromosomal arrays were integrated.<br /> 7) Lines 195 & 214: it is unclear how GCaMP arrays were confirmed by mCherry fluorescence (nlp-3p::mCherry) given that these strains also have arrays carrying tph-1p::mCherry and both nlp-3p::mCherry and tph-1p::mCherry should express in the HSNs.<br /> 8) Line 339: the authors conclude that Rho acts “downstream of Trio RhoGEF.” However, the data show that a Trio mutant is only partially bypassed by expression of activated Rho – i.e. # of eggs is intermediate between the Trio mutant alone and activated Rho alone. These data are consistent with Rho acting downstream of Trio, but with RhoGEF activity still contributing to full activation of the “activated” Rho(G14V). The data would also be consistent with Trio and Rho acting at least partially in parallel, which could occur within the same cell or in different cells. A further complication to the interpretation of these data is that different activated Rho arrays are used in the WT and Trio mutant backgrounds. These different arrays could have different expression levels, which is a big caveat to making these comparisons. Ideally, one would use the same array in the WT and Trio mutant backgrounds.<br /> 9) p. 16, lines 348-459: many of the Fig 2 callouts on this page refer to the wrong panel.<br /> 10) Line 347: says 70%, but the data in the figure show >80%.<br /> 11) Line 348: says 3 +/- 1 eggs, but Fig 2B says 3 +/- 0.2 eggs for same strain.<br /> 12) Line 363: we were confused by this. Are the authors suggesting that you can’t quantitatively compare the effects of the HSN vs. muscle specific expression of activated Rho(G14V) because the arrays are mosaic? While it is true that the arrays may be mosaic, they also carry an mCherry marker expressed in the same cells, so they should know whether the array is expressing activated Rho as intended in the worms assayed, and it is unclear why mosaicism is an issue. A bigger issue to quantitatively comparing these strains is that they probably have different expression levels of activated Rho.<br /> 13) Line 396: “outside of egg-laying active states (Figure 3A).” However, the data in Fig 3A shows HSN activity “during an egg-laying active state” according to the figure legend. Data showing activity outside egg-laying active states are not shown, but should be presented.<br /> 14) Line 423: it is unclear how “instantaneous” transient frequency is defined. This should be added to the methods or figure legend.<br /> 15) Line 428: says “more than 5 transients per minute” but the data in Fig 3C show it to be just under 4 transients per minute.<br /> 16) Line 561-562. “This difference largely resulted from a lack of twitch transients around egg-laying events in C3T-expressing animals.” This argument doesn’t make sense to us. How could a lack of twitch transients affect the amplitude of the transients that are seen?<br /> 17) Line 648: “we do not see dramatic effects on HSN morphology and presynaptic structure upon Rho inactivation.” Presynaptic structure was not assayed, so this should be cut.
Reviewed (and signed) by Amy Clippinger and Michael Ailion
On 2025-12-19 16:32:52, user Fernando Govantes (Fernan) wrote:
This is now published in Microbiological Research. doi: 10.1016/j.micres.2024.128033
On 2025-12-19 15:34:37, user Prof. T. K. Wood wrote:
Authors confuse the stress response with persister formation as persister cells are dormant and stressed cells become persisters by literally down-regulating ALL genes.
Line 103 is patently false: "However, these studies neither comprehensively characterize persister motility nor explore the potential interplay between swimming motility and persistence" since we discovered persister cells resuscitate using chemotaxis machinery (CheA, CheY) to sense nutrients and discovered the mechanism is via cAMP and (p)ppGpp (ref 39, 2020, iScience).
line 106 is false (see item 2) as we discovered how motility affects persister resuscitation.
Line 55 is incorrect: persister cells do NOT form stochastically and claims of stochasticity are bad science with carryover due to the inoculum.
Line 60: the seminal paper which discovered acid and oxidative stress induce persistence is Microbial Biotechnology (2012) 5(4), 509–522 doi:10.1111/j.1751-7915.2011.00327.x
line 73: "a definitive mechanism or universal determinant that fully explains the persister lifecycle remains elusive" is patently false. The ppGpp ribosome dimerization persister (PRDP) model should be cites as, unlike the PASH model that is cited and provides no mechanism, the PRDP model is universal and provides the current best mechanism (Biochemical and Biophysical Research Communications 523 (2020) 281e286).
line 716/723: we discovered chemotaxis machinery impacts persister resuscitation (your ref 39) and so it should be cited here.
If these matters are not addressed, I will ask the that the final publication be corrected.
On 2025-12-19 13:36:26, user William Cawthorn wrote:
Very interesting paper! One minor request: please abbreviate bone marrow adipocytes as BMAds and not as BMAs, as outlined in the standard nomenclature for the field:<br /> https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2019.00923/full
(this is because 'BMA' is the officially recognised abbreviation for 'bone marrow adiposity')
On 2025-12-18 18:35:07, user Pat Johnston wrote:
...ok, so if I understand this correctly, there is little to no size difference in adults? what of the possibility that boys develop their bnst to maturity sooner than girls, for it to play a more active/involved role in their early male hormonal development? is their comparative size differences at pre-pubescent age ranges, and does that correlate to consequent emergence of any missized dysmorphic basis for gender dysphoria?
On 2025-12-18 17:04:15, user Lucia Jajcay wrote:
The fMRI and personality data are publicly available on the Open Science Framework (OSF) and have now been assigned a DOI: https://doi.org/10.17605/OSF.IO/795HB .
When using the dataset, please cite the published article: https://doi.org/10.1111/psyp.70203 .
On 2025-12-18 07:59:33, user Cryptex Technologies wrote:
Interesting preprint and a promising approach using real-time volatilomics for non-invasive analysis of microbiota–pathogen interactions. Looking forward to seeing how this method performs in larger and clinical studies. Thanks for sharing this work.
On 2025-12-18 02:37:38, user M Timothy Rabanus-Wallace wrote:
Hi Eds -- this work has been published (after a lot of revision) here: https://link.springer.com/article/10.1186/s12870-025-07328-6
On 2025-12-18 00:14:57, user Casey Nichols wrote:
Hello! I wanted to leave some constructive feedback on the way the common garden assays were described. On my initial read, I found that the generational framework was a bit hard to understand. When the paper introduces the “F1” flies used for the phenotypic assays, it wasn’t immediately clear as to what “F1” was referring to. I had initially interpreted this as an “F1” relative to the start of the experiment. This left me confused since it wouldn’t make sense to perform the phenotypic assays on the F1 experimental populations. It wasn’t until I read through the supplementary materials that it became clear how “F1” was being defined in this context. There, you explained that the assays were conducted on the F1 generations of the experimentally evolved populations. I think this clarification is extremely important for interpreting the rest of the paper correctly. Perhaps making this more explicit in the main text would likely prevent similar confusion for other readers. The experimental design made a lot more sense to me once to me once this confusion was cleared up. Overall, a great read!
Cheers,<br /> Casey
On 2025-12-17 07:52:26, user Emma Piraino wrote:
I found this paper to be very cohesive and organized in a very understandable way, including the order in which information was presented as well as the utilization of figures that were crucial to the findings of the paper, nothing less and nothing more. Throughout the paper I thought of several questions that I had regarding rationale behind parts of the study, interesting expansions that could be made to the study, and topics that were answered later on in the paper, such as what is a common-garden assay. Before I get to my questions/suggestions, I also wanted to note that I appreciated how consistent the paper was and that the authors mentioned important themes and contributing factors to the experiment throughout the paper, such as defining why phenotypic plasticity was such an important factor to study and analyze in this experiment.
A few of the main questions I had are regarding the impact of bleach on fly eggs and how that can impact the experiment. I understand that F1 flies were used in their assays, according to their supplementary information, but I wanted to know more about how the bleach could impact the flies, even the F1 offspring. Another question, or even interest, I had was regarding why the comparisons of the experiment were between populations with microbes vs. without, instead of possibly comparing the effects of microbes that originated from different fly line populations. I understand why they only transferred fecal microbes from one fly line to keep all variables consistent, but I think further experiments on this could be interesting. The transfer of the fecal microbes leads to my next question, why were the MB flies created involving bleaching as well, with a reintroduction of microbes from one of the fly populations. From my understanding, if the microbes were transferred from a different fly line than the one chosen, this could have completely altered the outcome of the experiment, due to the variation of microbiomes between populations.
Some other overall comments I had regarding the paper would be include more examples that were specific to drosophila, (the existing examples of things such as the stinkbugs were also important to the paper, though). Also, I believe there is a typo under the desiccation resistance portion of the methods section, (till al -> until all).
Overall, I found this paper to be very interesting and left me with several questions regarding microbiomes and how this experiment could be further expanded upon, as well as how important these findings are.
On 2025-12-17 19:16:43, user Misha Koksharov wrote:
Very interesting. <br /> 1) Though, as someone currently interested in evolution of several enzymes throughout the Tree of Life, I would note that the proper term for an existing protein of this kind is "archaic", not "ancient". "Ancient" is more appropriate for those proteins which are no longer around. E.g. there are works where people try to resurrect ancient proteins from phylogenetic trees of the existing ones.
For example, lungfishes are "archaic" while "ancient alpha-proteobacteria" or even "ancient proteobacteria" are remarkably different from those we can study today, by the benefit of being able to infer some of their complexity from proteins of mitochondrial origin in eukaryotes.
Originally I've seen this point made by one of the linguists about languages: Latin is an ancient language while some Baltic and Slavic languages may be considered archaic relative to the Proto-Indo-European.
2) Figure 2. <br /> Why no melanopsins as a natural outgroup in the phylogenetic tree? As I understand, it is the closest clade to arthropod's r-opsins.
On 2025-12-17 15:16:52, user Jacob Podesta wrote:
The data supporting this research is openly available from the research data repository of the University of York at https://doi.org/10.15124/6c307f02-b229-4d5a-8dda-760e088abd26
On 2025-12-16 19:56:10, user Michael Pusch wrote:
The authors should consider the following paper:<br /> https://pubmed.ncbi.nlm.nih.gov/26033718/
On 2025-12-16 10:56:23, user Evolutionary Health Group wrote:
We at the Evolutionary Health Group ( https://evoheal.github.io/) really enjoyed this paper! Here are our highlights:
The authors demonstrate that extremely small RNA-guided nucleases can be deliberately redesigned to yield dozens of active variants, by extracting evolutionary signals that indicate which residues are safe to modify and which must remain untouched. The result is a set of compact, efficient DNA-cleavage "tools" that nature never explored but that nevertheless prove to be functional.<br /> A simple and elegant scheme for expanding the sequence space was used: an evolution-informed mask, derived from large paired datasets = protein + its native nucleic-acid-partner, locks functionally essential positions while leaving peripheral regions free to vary. The generative model is allowed to modify only these safe-to-vary positions, effectively unlocking large new areas of sequence space that expand natural evolutionary solutions.<br /> This approach can serve as a prospective strategy for “filling in the gaps” within sequence space regions where no experimentally annotated variants exist. Given large sets of evolutionarily linked pairs (protein-protein or protein-DNA/RNA), co-evolutionary signals identify functional anchor points, while generative models safely and systematically explore the vast surrounding regions. This enables the design of new sequences in those areas that natural evolution never sampled, thereby expanding the functional repertoire of biomolecules beyond the observable space.
On 2025-12-16 06:46:28, user Giorgio Cattoretti wrote:
The complex and advanced type of analysis described, SpaCEy, unveils spatially-contiguous expression of proteins associated with low survival in breast cancer and MYC is reported to be one of those.<br /> The antibody used to identify MYC in the cohorts is an IgG1 mouse clone, 9E10, which is not recommended for that purpose in FFPE sections by a knowledge-based Ab resource ( https://ibeximagingcommunity.github.io/ibex_imaging_knowledge_base/reagent_resources.html) and does not recognized MYC in flow cytometry, immunohistochemistry and IF (doi: 10.1074/jbc.L119.011910. PMID: 31924671) and performs poorly for the only assay where it may be used, immunoprecipitation (10.1126/scisignal.aax9730). Assuming that it recognizes in tissues the linear epitope used for the Ab generation, it may detect three different proteins bearing such epitope. To include MYC among proteins associated with survival in breast cancer is premature at best.
On 2025-12-15 22:38:23, user Simon Delagrave wrote:
This manuscript is now published: https://www.nature.com/articles/s41467-024-51064-8
On 2025-12-15 17:08:43, user Prof. T. K. Wood wrote:
Authors appear to ignore previously-published work about the most-prevalent anti-phage system, toxin/antitoxins, where the transcriptional regulation is well-studied during stress. Their methods are also skewed by using DefenseFinder, which ignores most TA systems. Odd to think the environmental/physiological factors can be discerned if the most-prevalent systems are ignored.
On 2025-12-15 15:12:34, user Jonathan Michaels wrote:
Please link to published article: https://journals.physiology.org/doi/full/10.1152/jn.00407.2025
On 2025-12-15 15:11:10, user Jonathan Michaels wrote:
Please link to published article: https://www.nature.com/articles/s41586-025-09690-9
On 2025-12-15 11:13:45, user Emmanuelle Munger wrote:
Now published in nature communications https://doi.org/10.1038/s41467-025-63122-w
On 2025-12-15 03:24:33, user Misha Koksharov wrote:
This is a very interesting and useful paper which was apparently published 3 years later in 2025 in the International Journal of Molecular Sciences: https://www.mdpi.com/1422-0067/26/12/5569
On 2025-12-12 23:57:22, user Noriko Osumi wrote:
This preprint has now been accepted in Lab Animal after all the review process.
On 2025-12-11 08:47:39, user Sultan Tarlacı wrote:
The preprint "Somatic mutations impose an entropic upper bound on human lifespan" presents a significant methodological advance in gerontology by developing a structured, incremental modeling framework to dissect the complex process of aging (Efimov et al., 2025). A key contribution of this work is its demonstration of a fundamental asymmetry in how somatic mutations affect different tissue types. The finding that post-mitotic cells (neurons and cardiomyocytes) act as critical longevity bottlenecks, while highly regenerative tissues like the liver can maintain functionality for millennia through cellular turnover, provides crucial guidance for future therapeutic prioritization (Kirkwood, 1977; López-Otín et al., 2013). Furthermore, the application of reliability theory, modeling the human body as a system of serially and parallelly connected components, successfully translates engineering principles to a biological context, offering a robust quantitative foundation.
However, the model notably overlooks critical evolutionary and biophysical determinants of human lifespan, particularly the deeply entrenched allometric relationship between brain size, metabolic rate, and maximum longevity. Anthropological and comparative biological studies have long established a robust scaling law, often expressed as Maximum Lifespan ≈ k * (Brain Mass)^α, where α approximates 0.56 (Sacher, 1959; Hofman, 1993). This relationship is not merely correlative but is underpinned by the immense metabolic cost of neural tissue. The human brain, representing only ~2% of body weight, consumes ~20-25% of the body's basal metabolic rate (BMR) (Aiello & Wheeler, 1995). This "expensive tissue" imposes a fundamental constraint: extending cognitive function and neural integrity over the model's predicted 134–170 year median lifespan would require not just resisting mutational entropy, but also sustaining this disproportionate energy allocation for over a century beyond current norms.
This biophysical reality directly engages with the model's parameters. The study's calculated theoretical non-aging baseline of 430 years (at age-30 mortality) and its subsequent reduction by somatic mutations, while mathematically sound, exist in an evolutionary vacuum. As noted in ancillary paleoanthropological analyses, a projected increase in maximum lifespan (AÖ) to 200 years is evolutionarily coupled with a required expansion of brain capacity to nearly 5,700 cm³ and a significant rise in total caloric consumption (Bozcuk, 1982). The current model, by treating organ capacity (K) as a static, log-normally distributed variable, fails to incorporate the dynamic, co-evolutionary feedback between longevity, encephalization, and the body's energy budget. Sustaining a ~1.4 kg brain for 150 years is metabolically challenging; sustaining the larger brain implied by such longevity evolution would dramatically alter the energy landscape, potentially intensifying oxidative stress and influencing mutation rates themselves—a variable currently held constant.
Thus, by isolating somatic mutation accumulation from the broader context of human encephalization and its requisite metabolic investment, the study risks presenting an upper bound that is neurobiologically and evolutionarily untenable. The "entropic upper bound" imposed by somatic mutations might be preempted by an earlier "energetic upper bound" imposed by the escalating cost of maintaining the very organ most critical to survival—the brain. A comprehensive model must integrate these scaling laws, recognizing that lifespan extension is not a singular process of damage repair but a systemic renegotiation of energy allocation and neural architecture (Robson & Wood, 2008; Fonseca-Azevedo & Herculano-Houzel, 2012).
A further significant limitation is the model's disconnection from life history evolution and fertility dynamics. A core tenet of evolutionary biology is the trade-off between longevity and reproduction (Stearns, 1992). Historical and paleoanthropological data suggest that increases in lifespan are accompanied by delayed sexual maturation and extended reproductive periods (Bogin & Smith, 1996; Gurven & Kaplan, 2007). For instance, a lifespan extending to 150 or 200 years would logically shift the onset of reproduction to later ages (e.g., 22-27 or 30-37 years, respectively). The study's "somatic-mutations-only" scenario does not account for how such a dramatic shift in the reproductive window would impact population dynamics, intergenerational intervals, and genetic diversity. Ignoring these demographic and evolutionary feedback mechanisms limits the realism of the proposed lifespan extension, as reproductive strategy is a fundamental pillar of a species' survival and adaptation.
Additionally, the model gives limited consideration to energy metabolism and other primary aging processes. Longevity is intricately linked not only to the accumulation of cellular damage but also to the economics of energy production, allocation, and consumption—concepts central to the Disposable Soma Theory (Kirkwood, 1977). The human brain is a metabolically expensive organ, consuming a disproportionate share of the body's energy budget (Aiello & Wheeler, 1995). Supporting its function over 150-200 years would impose immense metabolic costs, potentially exacerbating other aging hallmarks like mitochondrial dysfunction. By focusing predominantly on somatic mutations, the model sidelines the potential compounding effects and interactions with other critical aging processes such as loss of proteostasis, altered intercellular communication, and stem cell exhaustion (López-Otín et al., 2013). A comprehensive upper-bound estimate must integrate these interconnected mechanisms.
In conclusion, Efimov et al. provide a valuable and sophisticated starting point for quantifying the theoretical limit imposed by one fundamental aging process. Yet, a truly holistic model of human longevity must integrate constraints from evolutionary biology, life history theory, and systems metabolism. Future research should aim to create integrative frameworks that simulate not only the accumulation of somatic mutations but also the co-evolution of brain and body, shifts in reproductive strategies, and metabolic adaptations required for extreme longevity. Such a multidisciplinary approach, bridging gerontology, evolutionary anthropology, and systems biology, will deepen our understanding of human lifespan limits and provide a more robust foundation for evaluating potential intervention strategies.
References
Aiello, L. C., & Wheeler, P. (1995). The expensive-tissue hypothesis: the brain and the digestive system in human and primate evolution. Current Anthropology, 36(2), 199-221.
Bogin, B., & Smith, B. H. (1996). Evolution of the human life cycle. American Journal of Human Biology, 8(6), 703-716.
Efimov, E., Fedotov, V., Malaev, L., Khrameeva, E. E., & Kriukov, D. (2025). Somatic mutations impose an entropic upper bound on human lifespan. bioRxiv. https://doi.org/10.1101/2025.11.23.689982
Gurven, M., & Kaplan, H. (2007). Longevity among hunter-gatherers: a cross-cultural examination. Population and Development Review, 33(2), 321-365.
Hofman, M. A. (1993). Encephalization and the evolution of longevity in mammals. Journal of Evolutionary Biology, 6(2), 209-227.
Kirkwood, T. B. (1977). Evolution of ageing. Nature, 270(5635), 301-304.
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013). The hallmarks of aging. Cell, 153(6), 1194-1217.
Robson, S. L., & Wood, B. (2008). Hominin life history: reconstruction and evolution. Journal of Anatomy, 212(4), 394-425.
Sacher, G. A. (1959). Relation of lifespan to brain weight and body weight in mammals. *Ciba Foundation Symposium - The Lifespan of Animals, 5*, 115-133.
Stearns, S. C. (1992). The evolution of life histories. Oxford University Press.
On 2025-12-10 22:00:45, user Thomas O'Dell wrote:
This article was published in the November 2025 issue of the journal Hippocampus: https://doi.org/10.1002/hipo.70043
On 2025-12-10 15:33:46, user Sungwhan Oh wrote:
This preprint is now published in a peer-reviewed journal.<br /> doi: 10.1038/s41564-025-02141-1
On 2025-12-10 12:42:53, user Rui Wang wrote:
This preprint has not undergone peer review. The final version of record of this article is published in the journal Biology of Sex Differences, and is available online at https://rdcu.be/eTRja and https://link.springer.com/article/10.1186/s13293-025-00801-9