On 2020-03-09 13:57:40, user Diogo Borges Provete wrote:

Interesting paper indeed. However, I'm not sure if the linear morphometric variables you made could be called functional traits in the sense of Violle et al. 2007 Oikos and others. The approach of partitioning the measurements into intraspecific and interspecific variation and also among sampling sites is up to date.

But certainly the measurements you took are not feasible to be used in this framework. <br /> I'd strongly advice you to take a morphometric approach more explicitely, relating the multivariate space of measurements to the local environmental variables. This is clearly a ecomorphology paper, not a functional ecology paper and you should better use the data collected.

On 2020-09-16 09:32:40, user ?? wrote:

Hi.

Is the data available for us to try out?

On 2019-06-03 11:47:35, user aquape wrote:

Thanks a lot, very interesting findings, but the interpretation seems to assume that all these fossils were fossil relatives of humans, but not of the African apes. This is an unproven assumption. Asian apes have lots of fossils relatives, it's believed, but for some reason (anthropocentric bias?) it's traditionally assumed that the African apes have virtually no fossil relatives, whereas humans are thought to have innumerable fossil relatives or even ancestors. This is statistically impossible, of course: if orangutans have so many fossil relatives, why nhy not chimps, bonobos or gorilla?<br /> The solution is not so difficult IMO: most so-called human traits of australopithecines (e.g. vertical spine, thick enamel, low pelvis, full plantigrady etc.) are not uniquely-human-derived, but are hominid- or even hominoid-primitive, and were probably already present in most Miocene hominoids (and sometimes lost in African ape evolutions). All apes have centrally-placed spines (vs. dorsally-placed spines in monkeys & most mammals), this suggests that ape ancestors were already "vertical", not for running over open plains, but for climbing vertically (arms overhead) and/or wading bipedally (google e.g. "bonobo wading") and/or hanging from branches (suspensory).<br /> It is likely IMO that the East-African and the South-African australopithecines were no close relatives of each other, but that both branches evolved in parallel (allopatric parallel evolution) from more gracile to more robust (e.g. afarensis->boisei // africanus->robustus), google e.g. "ape and human evolution 2018 Verhaegen". This would help explain the different "stages" the paper describes in australopithecine limb bone evolution, with early australopiths Lucy & Little Foot resembling the ancestral condition, and Pan and Gorilla apes evolving in parallel longer upper limbs, but humans evolving longer lower limbs.

On 2020-09-03 19:37:57, user mark bear wrote:

This paper reads like a detective story, starting with close (and previously missed) observations of altered behavioral responses in the NLGN3 rat and tracing the underlying cause to changes in the excitability of neurons in the dorsal periaqueductal grey. The authors are to be congratulated, and the study underscores (again) the power of the genetically engineered rat models of disease.

On 2020-08-14 07:27:43, user Kapil Gupta wrote:

It seems authors might have missed our paper. We already published same findings 2 months ago. We even have shown more experiments to further identify the lipid there and also activity assays of lipid bound spike.

Here is link for our paper.<br /> https://www.biorxiv.org/con...

On 2022-07-16 07:41:26, user Iratxe Puebla wrote:

Review coordinated via ASAPbio’s crowd preprint review

This review reflects comments and contributions by Richa Arya, Luciana Gallo, Lauren Gonzalez, Sam Lord, Dipika Mishra, Arthur Molines, Mugdha Sathe, Ryman Shoko, Ewa Maria Sitarska. Review synthesized by Ehssan Moglad.

Study conducted by Chieh-Ren Hsia et al. which looked at nuclear deformation in confined migration and its effect in chromatin organization and function.

Major comments

Results ‘To distinguish between true changes in chromatin modifications and effects of physical compression of the nuclear content due to deformation, we normalized the heterochromatin mark intensity to the euchromatin mark intensity in each cell.’ - The results are normalized to H3K9ac, with the assumption that its levels do not change during migration/confinement. Has this assumption been confirmed? For example, by normalizing both H3K27me3 and H3K9ac to total H3 instead - and showing that K27me3 increases with confined migration while H3K9ac doesn't.

Results ‘Increased heterochromatin formation should result in an increased ratio of heterochromatin marks to euchromatin marks, whereas physical compression of chromatin would increase both marks, and thus not alter their ratio…’ - Can some comments be provided on what the meaning would be for heterochromatin to "increase" and euchromatin to not change? There are two ways in which heterochromatin could "increase" - either the portion of the genome in heterochromatin could increase (which would mean the portion in euchromatin would decrease), or the portion of the genome in heterochromatin could stay the same but K27me3 levels could be higher in those regions (which might not affect euchromatin levels). One way to distinguish between these would be to stain for K36me3 as the "euchromatin" marker instead of K9ac - because K36me3 and K27me3 are mutually exclusive.

Figure 1 <br /> - Could the effects seen be due to cells spending different amounts of time in the channels? Do all cells migrate at a similar speed? <br /> - Panels D, F, I: it is unclear if the cells shown in the plot for the change in heterochromatin marks are all that migrated or only those that show the difference. Suggest including a dot plot to also show individual data. Can some clarification be provided for how to interpret that controls "before" in 1D and 1F are statistically different?

Counts in Fig S2A-D are sometimes very low (same applies to Fig 1I, Fig 2B,C,E.), it may be nice to compare some more cells.

Results ‘Although the effect was less pronounced than in the <=2×5 um2 confined channels (Fig. 1C-F)’ - Can the normal size of these cells be reported ? Also the size of nuclei. is it bigger than the pore size?

There are concerns about the statistical analysis related to SEM and p-values based on multiple measurements or cells within each sample. The t-test and ANOVA assume that each measurement is independent, and multiple cells within the same sample are not independent. Suggest to either not report p-values or average together the values from each sample and calculate the p-value using those sample-level means. For more information, see https://doi.org/10.1371/jou... and https://doi.org/10.1083/jcb...

Minor comments

Results ‘custom-made polydimethylsiloxane (PDMS) microfluidic devices with precisely defined constrictions that mimic interstitial space’ - The manuscript report the size of the channels, and notes that it mimics interstitial spaces, it would be helpful to also report the size range for interstitial spaces in vivo.

Figure IH: Are these the same cells as in the reference (cells in which vertical confinement is sufficient to induce a nuclear response)? Are 5 um channels squeezing the nucleous?

“significantly larger increase in heterochromatin than cells migrating through the 10-um tall channels (Fig. 1H, I), demonstrating that the observed effect is primarily attributed to the confinement and not the migration process per se” - There is a statistical difference between the confined migration and non-confined migration groups, but there is also a statistically significant increase in heterochromatin in the non-confined migration group compared to baseline (and with larger sample sizes than in the confined group), so it may be worth commenting on the possibility of the effect of migration alone.

“Cells maintained CMiH even after completing at least one round of mitosis, without any trend of reversion in their heterochromatin levels (Fig. 2C; Fig. S4A, B), suggesting that the epigenetic modifications were inheritable through DNA replications” - This is an intriguing concept, however, it is unclear whether the cells that migrated did so before or after dividing. To support the claim about inheriting CMiH, it would be relevant to see heterochromatin levels in a mother cell increase after it squeezes through a channel, then the daughter cell (which doesn't squeeze through a channel) having a higher heterochromatin level than the "before" cells. That's not possible with immunofluorescence, maybe the GFP-HP1a could be useful for such a live-imaging approach? Otherwise, if all these "mitotic cells" divided after squeezing through a channel, that could be stated in the text, legend, and/or methods. Alternatively, the conclusion could be nuanced/toned down.

Figure 3 - The number of samples analyzed in some cases appears small. Suggest showing the data as dot plots to allow interpretation of the sample sizes for each group and the differences between the groups.

On 2025-04-11 10:18:57, user Bacillus Biofilms wrote:

Now published in Communications Biology https://doi.org/10.1038/s42003-025-07712-w

On 2017-05-31 21:04:57, user Mohit Kumar Jolly wrote:

Please see the final version of the article in Molecular Oncology here -<br /> https://www.ncbi.nlm.nih.go...

On 2017-10-19 05:20:51, user Biswapriya Misra wrote:

Very useful tool towards integration of -omics data sets.

However, few issues which may be addressed in due course of time:

1. Name is ditto to another popular tool/ work : http://www.nature.com/nmeth... and hence in longer run might be confusing to many/ some.

2. InChi Keys are fine, but HMDB, KEGG should be supported as well.

3. What purpose does FASTA sequence (large!) help than Gene/ Protein IDs/ accession number? Are not they species-specific?

4. Limiting to 10,000 FASTA seqs.is understandably not enough for transcriptomes of plants or higher organisms.

5. Better statistical treatment approaches/ rationale for the integration would be useful as well.

Thanks,<br /> Biswa

On 2023-05-18 06:20:49, user Ícaro Raony wrote:

Congratulations to all authors for this manuscript. This work potentially adds new pieces to the complex AD puzzle, showing that brain ACE2 levels correlates with AD pathology in two different cohorts of humans. Furthermore, the study shows that the spatial distribution of ACE2 in the brain of humans differs from mice, which has important implications for translational studies.The manuscript is also very well written, so it was easy for me to understand the main hypothesis, methods, results and author's conclusions, although I don't completely agree with some interpretations.

For example, I agree that ACE2 may play a role in AD pathophysiology. This is corroborated by previous data (discussed by the authors in lines 419-435) and new data from this present study, showing that brain levels of soluble ACE2 (sACE2) were positively correlated with A? and tau neuropathology in humans, but inversely correlated with cognitive scores. <br /> However, I have some concerns regarding the authors' hypothesis that higher levels of sACE2 in AD patients might contribute to higher risk of CNS SARS-CoV-2 infection.

So I have some questions and suggestions that I would like to share (I hope they contribute to your study):

Major points<br /> 1) The manuscript suggests that increased levels of ACE2 in individuals with AD may increase the risk of CNS SARS-CoV-2 infection, since the SARS-CoVs use ACE2 as entry point into host cells. However, no alterations was observed in the levels of membrane ACE2 (i.e. in detergent-soluble fractions), although higher levels of sACE2 was reported. I believe that the role of sACE2 was not properly discussed in the paper, but this is fundamental for the interpretation of your results.<br /> a) Where are most of TBS-soluble ACE2 in the AD brain? Inside or outside the cell? New data on this could help in the interpretation of current findings.<br /> b) If the receptor predominates in the extracellular parenchyma, as suggested in the lines 451-455, would they be acting as a decoy receptor or increasing SARS-CoV-2 infection by presenting the virus to host cells? There is an interesting literature on this, with some conflicting findings, but relevant to this discussion. These points are important to understand whether higher levels of sACE2 would be a detrimental or compensatory/protective mechanism.

2) In the present study, the APOE4 allele was present in 45% of individuals with AD (vs. 9% in control group in the cohort #1; p < 0.01). Accordingly, APOE4 is the greatest genetic risk factor for AD. Recent findings indicate that APOE4 also correlate clinically with COVID-19 severity through interaction with ACE2 and/or modulation of ACE2 expression (Signal Transduct Target Ther. 2022 Aug 1;7(1):261 / J Transl Med. 2023 Feb 9;21(1):103). Thus, it would be interesting to assess whether APOE4 also influences brain levels of ACE2 in the cohorts.

3) It is important to provide information about the race/ethnicity of the individuals enrolled in the present study, since African Americans/Black and Hispanic populations are at higher risk to have AD and experience disproportionately higher rates of SARS-CoV-2 infection and COVID-19-related mortality. Also, I think it is important to consider in the Discussion possible limitations of the study, such as not being able to measure the impact that medications for AD may have on ACE2 expression.

Finally, I believe that in vitro experiments could greatly contribute to the understanding of possible cellular mechanisms by which A? and/or tau can affect ACE2 expression and SARS-CoV-2 infection independent of other factors (e.g. age, obesity, DM, APOE genotype and some medications). Furthermore, I would like to emphasize my congratulations on the manuscript: it was an enjoyable read!

Best regards,

Ícaro Raony

On 2018-06-17 14:58:01, user kamounlab wrote:

As we wrote, it is certainly possible to identify PCR conditions, reagents and thermocyclers that would only amplify the WB12 sequence and not the related WB12-like sequences using the published MoT3 primer pair. However, in ours and other colleagues experience, these primers can readily yield false positives for wheat blast isolates. This is consistent with the genome sequence analyses described in this Gupta et al. paper.

It would be fairly straight-forward to generate a new set of MoT3 primers that distinguish more robustly between WB12 and the WB12-like sequences based on, for example, the alignment of Figure 4. This would be much easier than trying to identify the optimal PCR conditions and reagents.

But that would only solve half the problem. The second issue is that some South American wheat blast isolates do not seem to have the target WB12 sequence and at least one non-wheat isolate from Bromus has it.

Clearly, we need less ambiguous genetic markers and assays. Our understanding is that several labs are working on this challenge and we look forward to more advances on the subject.

On 2020-04-05 18:33:55, user Sinai Immunol Review Project wrote:

Summary: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infects cells through S spike glycoprotein binding angiotensin-converting enzyme (ACE2) on host cells. S protein can bind both membrane-bound ACE2 and soluble ACE2 (sACE2), which can serve as a decoy that neutralizes infection. Recombinant sACE2 is now being tested in clinical trials for COVID-19. To determine if a therapeutic sACE2 with higher affinity for S protein could be designed, authors generated a library containing every amino acid substitution possible at the 117 sites spanning the binding interface with S protein. The ACE2 library was expressed in human Expi293F cells and cells were incubated with medium containing the receptor binding domain (RBD) of SARS-CoV-2 fused to GFP. Cells with high or low affinity mutant ACE2 receptor compared to affinity of wild type ACE2 for the RBD were FACS sorted and transcripts from these sorted populations were deep sequenced. Deep mutagenesis identified numerous mutations in ACE2 that enhance RBD binding. This work serves to identify putative high affinity ACE2 therapeutics for the treatment of CoV-2.

Critical analysis: The authors generated a large library of mutated ACE2, expressed them in human Expi293F cells, and performed deep mutagenesis to identify enhanced binders for the RBD of SARS-CoV-2 S protein. While these data serve as a useful resource, the ability of the high affinity ACE2 mutants identified to serve as therapeutics needs further validation in terms of conformational stability when purified as well as efficacy/safety both in vitro and in vivo. Additionally, authors mentioned fusing the therapeutic ACE2 to Fc receptors to elicit beneficial host immune responses, which would need further design and validation.

Significance: This study identified structural ACE2 mutants that have potential to serve as therapeutics in the treatment of SARS-CoV-2 upon further testing and validation.

Review by Katherine E. Lindblad as part of a project of students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine at Mount Sinai.

On 2013-12-12 14:30:41, user Dennis Evangelista wrote:

This preprint has been accepted to PLoS ONE (PONE-D-13-23480R3) and will appear under doi 10.1371/journal.pone.0085203 - I will update the bioRxiv info once I have the url and other final bibliographic information.

On 2016-09-22 20:49:23, user Rory Coleman wrote:

Thank you for the great paper Munetoshi & Joe. What a remarkable example of the convergent evolution of suite of complex traits. I just have one question.

In the discussion you make the point that your results contradict Gould’s view of evolutionary contingency because of the repeated convergence over such a long evolutionary time scale. However, it seems that Aleocharines fit the view of contingency in the set of preadaptations that you posit to be necessary for this convergence. Is this not so much a contradiction of the contingency principle but more a rare case where the preadaptive ground state has been maintained across free-living Aleocharines? This seems to differ from Gould’s view only in that long evolutionary time hasn’t led to the divergence of the preadapted ground state, but since that has not occurred convergence may happen, as you argue, contingent on that ground state.

The paper is beautifully written and was a pleasure to read.

Best<br /> Rory Coleman

On 2025-04-07 16:29:49, user Eduard Porta wrote:

The paper is now published in a peer-reviewed journal:

https://www.cell.com/cell-reports/fulltext/S2211-1247(24)01580-8

On 2017-10-19 19:49:50, user Serbulent Unsal wrote:

A very nice paper which is strongly needed. But methylPipe uses Wilcoxon or Kruskal test without any regression fit. I think you may want to consider this approach in your comparision.

On 2019-03-26 23:36:25, user Charles Warden wrote:

Thank you for positing this.

I think Figure 1 is very helpful. Would it be fair to say these are causes for concern in the Luo et al. 2018 paper?

1) In all 3 examples, both members of the pair at the top of the family tree have one mitochondrial haplotype. Since one of them should have the hypothetical nuclear factor, shouldn't that individual have a mixed haplotype (if that was the true cause)?

2) Likewise, shouldn't individuals with the nuclear factor show increased mixing after each generation? In other words, you show 2 mixed haplotypes for each example in Figure 1, but I thought it seemed odd that only one of the 2 previously mixed haplotypes gets inherited in the next generation (I would expect the number of mixed haplotypes to increase with each generation).

On 2024-02-22 21:54:05, user Davidski wrote:

Hello authors,

It's extremely unlikely that there are any significant genetic differences between Sarazm_EN_1 (I4290) and Sarazm_EN_2 (I4210), and also unlikely that the former has significant South Asian ancestry while lacking Anatolian farmer ancestry.

The only significant difference between them is that I4290 is lower coverage. I suspect that this, coupled with your use of the very low quality Iran_Mesolithic_BeltCave in the outgroups, might be the problem in your qpAdm analysis.

I4290 and I4210 appear to be very similar in all of the PCA, qpAdm and ADMIXTURE analyses that I've done. Indeed, they're close to each other in all of my PCA, including across many different dimensions, except of course the PCA that reflect different levels of coverage in the samples being run.

For instance, here's a PCA that looks specifically at differences in South Asian and Anatolian genetic affinities. As you can see, there's practically no difference between I4290 and I4210.

https://blogger.googleuserc...

It is possible that I4290 and I4210 both have some sort of minor South Asian-related ancestry, but if so, then this type of low level South Asian-related admixture was ubiquitous in Eneolithic/Chalcolithic Central Asia.

For more details please refer to this blog post and comments in which I show that both I4290 and I4210 can be modeled in qpAdm as mixtures between Botai Eneolithic and a subset of Geoksyur Chalcolithic samples.

https://eurogenes.blogspot....

On 2020-01-31 23:32:13, user ewyler wrote:

In supporting the previous comment from Jason Weir: the alignement of the spike protein of the novel Coronavirus (protein ID QHD43416) with the bat spike protein mentioned by Jason Weir shows very high conservation (see attached image), particularly also in regards to the claimed "inserts" in Figure 2 of the preprint. This makes the bat Coronavirus a much more likely origin than the proposed connection to HIV.

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

On 2020-02-01 12:33:09, user Pauline wrote:

@ Alex Crits - I appreciate the comment, but I'm missing something crucial here. You've searched the database seperately, once for every of the four insertions. Then you're talking about the E-value, the number of times we'd expect to see this result purely by chance.

But if you want a fair comparison, it's not about the chance that you find only ONE of the four sequences somewhere in the genome of some species. And then test the other ones seperately.

We want to know about the chance to find ALL four sequences in another virus at the location of a binding site.

We want the know about the chance that ALL four mutations together occur at some point in the gap between the bat CoV and the human CoV (so with limited virus generations thus limited numer of replications).

Talking about finding just one sequence is like you just want to demonise the authors, instead of being actually scientific.

On 2019-03-27 15:55:29, user Xinwei Cao wrote:

In this manuscript and the 2017 Genome Research paper by de Pretis et al., you suggest that the amount of Pol II may be limited. Is there a way to measure whether this is indeed the case?

On 2018-10-10 10:27:12, user Benedikt Sundermann wrote:

The following articles present additional depression-subtyping approaches based on functional connectivity and may provide further insight into this topic:<br /> https://doi.org/10.1016/j.b... <br /> https://doi.org/10.1016/j.j...<br /> https://doi.org/10.1038/s41...

On 2019-04-15 18:58:02, user Michael McLaren wrote:

This looks like a very valuable resource for the community! Can you clarify the status of the data availability? The study identifier given in the manuscript does not seem to be currently available (https://www.ebi.ac.uk/ena/d... "https://www.ebi.ac.uk/ena/data/search?query=PRJEB30924)"). Also, which of the non-human data will be available in the ENA and which is to be made available on request? Thanks!

On 2020-06-05 15:20:13, user David Melville wrote:

I should have cited: Loftus, A. F., Hsieh, V. L. & Parthasarathy, R. Modulation of membrane rigidity by the human vesicle trafficking proteins Sar1A and Sar1B. Biochem. Biophys. Res. Commun. 426, 585–589 (2012). They found some evidence of SAR1A dimerization with their study as well.

On 2025-09-16 21:55:02, user disqus_FNcjH0JLKv wrote:

This paper has been published in the Computational and Structural Biotechnology Journal: https://doi.org/10.1016/j.csbj.2025.09.018

On 2025-10-27 15:42:44, user Katie Paris wrote:

For the article, Divalent siRNA for prion disease, the methods used seem appropriate; however, authors should provide more details on why specific techniques were used. Monovalent siRNA was mentioned multiple times, which was confusing because the project is focused on divalent siRNAs. There were many times where it said to “see above” but it was unclear where to look. In addition, Figure 1 is unclear and needs additional labeling. The text says Chol-TEG s1 is monovalent, but that is not indicated in the figure. Figure 2 demonstrates that siRNA extends the lifespan of mice exposed to prion particles, but it is not shown in the humanized mice and 2439-s4. Why is it not the same?

The section expanded screen for potent human siRNA sequences, discusses cell death but did not explain the technique used and why the authors chose that technique. For example, it was described as “any wells with cell death or rounded cells were noted.” Clarification on how authors determined if the cells underwent cell death or if they were rounded is needed. In addition, the generated mouse line description is unclear. Are the C57BL/6 mice replaced with human locus? The generation of the mice used for the experiments is not described sufficiently. Specifically, the transgenic mice were back crossed until generation 5; however, the following section discussed using generation 3 and 6 for transgene mapping. Furthermore, how much murine DNA was removed and how much human DNA was inserted? Is it the same chromosomal location? <br /> In addition, there needs to be a better explanation on how the targeted siRNA dose levels were chosen, simply saying “determined by UV absorbance” is not enough. The administration of divalent siRNA to mice was unclear. Why were two different types of anesthesia used? The statement “this procedure was performed first on the right and then on the left” needs to be explained. A figure detailing the procedure would help. How was the location of injection (between the right ear and midline) was chosen?

Finally, why use ChatGPT to generate a Python script? How was the script deemed accurate? The use and accuracy of using ChatGPT needs to be clarified.

On 2018-06-15 19:15:10, user Kote wrote:

Good work! I do have one suggestion: you don't seem to mention that Chertemps 2007 found that eloF was expressed in mel but not sim. You cite their paper, but fail to mention that your main result is preceeded by theirs. This comes across as disingenuous. Certainly, their result seems somewhat preliminary, and was comparing mel/sim, so I think your newer results put everything on a much firmer footing. Nonetheless, it certainly seems like you should mention their result and explain why yours is an advance! You work seems great — don’t diminish it by ignoring their previous result!

On 2016-05-17 19:44:57, user James Wilson, M.D. wrote:

Pierre et al, strongly suggest incorporating a financial impact assessment in your study.

On 2020-03-25 11:34:19, user Kasra wrote:

Very nice and important finding

On 2020-05-15 16:00:28, user Emiliano Trucchi wrote:

We would like to report a graphical mistake in Figure 2B: the same plot showing the diffusion of the two spike variants in NY was inadvertently inserted as inset in both the NY and the WA main plots. The WA inset is then missing. This will be amended in a corrected version of the manuscript to be uploaded asap. Sorry for the inconvenience! If you spot other mistakes, please let us know!

On 2022-02-11 19:56:15, user smd555 smd555 wrote:

" especially when we consider individual I4110 from Dereivka I (Ukraine Eneolithic) as one of the earliest representatives of their genomic makeup" - and what about another samples from Dereivka, such as I5882 and I5884 - did you involve them in the analysis?

On 2019-11-01 07:55:21, user Pierluigi Scerbo wrote:

Wow! A new paper about in vivo reprogramming! It is amazing and looks like my PhD paper about in vivo reprogramming of Xenopus muscles to Xenopus-IPS (XiPS) (PMID: 22232554).

On 2019-03-14 20:49:17, user Tara Thorpe wrote:

Isn’t cannabis sativa technically European hemp? The cannabis we consume would technically be cannabis Indica & afghanica. Please correct me if I’m wrong, my sources are loose- although I am a cannabis industry professional.

Thank you!

On 2023-10-02 12:32:20, user Joshua E Flack wrote:

This work has now been peer-reviewed and is available here: https://www.frontiersin.org...

On 2024-04-12 16:31:13, user Hisashi Tanaka wrote:

The manuscript has been published online in Nucleic Acids Research Cancer.<br /> https://academic.oup.com/na...

On 2018-07-13 08:12:08, user Pooran Dewari wrote:

That's brilliant. Indeed synthetic cr:tracrRNA approach is much better than IVT sgRNAs, much faster, hassle-free, and efficient. We have tested them head to head in neural stem cells and found synthetic 2-part RNA approach works better for insertion of small epitope tags. <br /> https://elifesciences.org/a...

On 2020-05-07 04:03:26, user GetOffMyLawn wrote:

None of this is really new news there has been two real known strains one weaker and one stronger. Seems the European one is the same that arrived in the US - the weaker version would be the one that many people had and never knew it almost like a weak or somewhat inert strain. It doesn't seem like there is any known differences in the US outside of the two?

On 2019-11-01 13:24:46, user Anna wrote:

Hey, cool method! Where can I find the supplementary tables? Thanks!

On 2020-04-03 12:14:32, user pedrobeltrao wrote:

Could you please share the list of interactions as a supplmentary file as well ? or provide a link in the comments section to a file containing this information?

On 2020-12-16 16:03:37, user Mattia Matasci wrote:

We are pleased to announce that this manuscript has been accepted for publication in "Experimental Biology and Medicine"

On 2021-02-25 04:32:39, user Miles Davenport wrote:

For a study using mixed effects to model SARS-CoV-2 immunity see:

https://www.nature.com/arti...

On 2021-02-26 08:28:41, user Sharon wrote:

Really nice information. amino acids is actully a big source of protein. I also like this information about bcaa-<br /> https://www.ajinomoto.com/a...

On 2023-03-23 13:49:31, user wonderfulponderfulponds wrote:

Good analysis. All points agreed. A valuable contribution to the field. Except the attribute given to the causal factors such as feeding, I could not grasp: (a) how and where the authors quantified bioturbation or uprooting effects of foraging cyprinids?; (b) where and how the authors quantified repeated feed application in littoral zone/ bed made them unsuitable for recurrent aquatic macrophyte growth?; (c) what is the redfield ratio of feed input and how it dilutes or upconcentrates the same ratio in littoral bed making them unsuitable?. The authors show nicely temporal trends of littoral machrophyte zone shrinking (OKAY), but do not show direct causal relationship with attributes for which they are blaming the reason (e.g., feeding or no feeding). One can say, the same inference could be drawn for climate change too (perhaps stronger after evaluating a multi-decadal water stress in the territory). If fishpond management is to blame, why chasing feed application alone, when there are bigger causes such as farmers preferring not to keep them as they interfere with netting/ harvesting operations. Why not discuss these? Lastly, an intuitive point to consider, higher the littoral macrophyte vegetation (especially the emergent ones), more intense is the evapotranspiration by the pond body; because there is more surface area which actively evapo-transpires. This is further compounded by water stress (climate change), see the IPCC report published recently. Is not the relationship between shrinkage of littoral vegetation cover and a good littoral vegetative cover, universally juxtaposed forever? As a matter of fact, if recent IPCC report is true, one could question if keeping dense macrophyte beds (littoral) is even reasonable to combat water stress, and not making green belts around the pond instead. Which is efficient and not counter-productive? To conclude, the publication has a strong logic, but it could easily discuss its results on a broader context; instead of localizing its focal point with things that are more socio-politically charged and less of science. I recommend the study to be published; but also request the learned authors (with good legacies of work behind their names) to consider this request. The writing is good.

On 2020-04-02 17:59:16, user ricky wrote:

Are there followup studies to define the interaction maps either:<br /> -using less-pathogenic strains of coronaviruses (like the seasonal cold)<br /> -using SarsCov2 proteins in cells from a species that does not get severe disease (such as bats)

On 2017-02-24 16:40:53, user Matthew Gemmell wrote:

Hello

I though the manuscript was very. It gives a lot of reasons why preprints are good and I will definitely look into submitting a preprint in the future. You asked on Twitter and I would not call the tone too fanboy.

I would say that their are some fears that people may have of the idea of preprints that could be addressed in updated versions possibly. These are some suggestions.

1. As you hint at in the preprint the engagement of scientists commenting on preprints is important but can be hard. How will scientists be encouraged to do this?<br /> I think one answer is that preprints would be a good avenue for new collaborations to occur and start. If people comment on an author's work and they gain a good rapport and work in similar fields or complementary ones they could collaborate on future papers. It may be possible that an individual may be able to vastly improve on a preprint by an idea or skills and co author it together.

2. On the topic of scooping. You could mention that research coming out earlier will help scientists to not start something that is near final publication at another research group.

3. A major hurdle for the acceptance of preprints i think is the fear that it will open the floodgates of poor science and so good research will be obscured. Although you have good examples of quick preprints to post publication peer review a person may rush publishing a preprint which is wrong and another scientist or even the media may run with this. Unfortunately it can be very hard to get the wrong information out of people's heads. I think this is unfortunately an issue of places where anyone can post stuff. <br /> This is a hard issue to counteract and i unfortunately don't have an answer to it but I think it would be good to acknowledge this fear and possibly give suggestions to try and prevent this.

4. There are 2 main preprint servers. In most online forums there eventually reaches a point were two main groups have such different opinions on the use of the forum a schism occurs and the one forum becomes two separate ones. Considering this is still early days for preprints do you think this will occur for preprint servers? Do you think there is ways to prevent this or do you think this is just a natural process that needs to occur. This point may be beyond the scope of this paper but it might be interesting to address.

Thanks for writing this preprint I think it will be a great resource to show collaborators who are hesitant to use preprints and it definitely showed me the benefits of it. I hope my comments will be useful to you.

Thanks for reading<br /> Matthew Gemmell

On 2015-11-03 00:15:16, user Qiongshi Lu wrote:

This paper (with a minor change in title) has been published in Bioinformatics. http://bioinformatics.oxfor...

On 2018-05-03 23:23:05, user Utku Perktas wrote:

An important consortium produced an interesting paper that includes pool seq of D. melanogaster. A wide geographic coverage is very important for these kind of studies. This paper looks have a very good sampling coverege. That is certainly worth reading.

On 2020-03-29 07:31:19, user Robert George wrote:

with regard to enigmatic Chermuchek people, the text states ''This model fits even when ancient European farmers are included in the outgroups, showning that if the long-distance transfer of West European megalithic cultural traditions to people of the Chemurchek culture that has been suggested in the archaeological literature occurred, it must have been through<br /> spread of ideas rather than through movement of people. '''

However, a possible link entails the documented movement of Eur-farmer ancestry toward steppe (e.g. GAC groups - Mathieson 2018). In turn, Yamnaya groups (putative parental source of Afansievo) have ~ 10% EEF admixture c.f. Progress steppe Eneolithic (Wang et al 2019). Thus, we have more than a diffusion of ideas.

On 2025-02-13 19:40:38, user Pick Up Litter wrote:

This paper will help move science away from studying "cute" species and to be objective. Perhaps the most severe example is the housecat-- still portrayed as cute in media, but in the feral form a worldwide destroyer of birds. One critique concerning the Ivory-billed Woodpecker-- the number quoted by Troy et al, 20 million dollars spent for studies, is misleading. Most of the efforts are university and private, not governmental, and if the bird is proven to be extant, will have conservation benefits since it is a wide-ranging and keystone species. I help with research for the Ivory-billed Woodpecker. The growing body of evidence that this species exists is more rational than the critique-- see other BioRxiv papers and the work of Mike Collins for example. John D Williams

On 2019-04-03 16:41:34, user Ariane Nunes Alves wrote:

This is a very nice paper! I loved it!

I have some comments:<br /> - for figures 2, 3 and 4: I did not like the representation of the data in the y axis. It is a bit hard to make comparisons for different tracers with different diffusion rates. Maybe you could change it to deltaL/L0, or Dtrans/(Dtrans at infinite dilution);<br /> - it would be nice to know the fraction of occupied volume for the amount of crowder you used in the experiments;<br /> - I saw figure S5, and I am not convinced that charges do not play a role in the enhancement in the transport of tracers. What are the net charges of the tracer particles and of the crowder? If charge really does not affect the enhancement in the transport of tracers, this contradicts the results of ref. 15 in the main paper. You could discuss possible reasons for such contradiction in the discussion.

On 2019-08-22 08:55:34, user Felix Heeger wrote:

The article is now published in Methods in Ecology and Evolution: https://doi.org/10.1111/204...

On 2016-07-19 21:47:27, user Francisco De La Vega wrote:

It would be very useful for the community to have a site allele count summary across the genome, like the open tier of ExAc. Hope this becomes available.

On 2019-10-23 15:16:41, user Alessia Indrieri wrote:

Nice work! We recently published a paper in@EmboMolMed demostrating that miR-181a and miR-181b control mitochondrial biogenesis and mitophagy in neurons. This is our paper https://www.embopress.org/d...

On 2024-12-07 20:21:15, user Amir Rahmani wrote:

Now published in Optics Express https://doi.org/10.1364/OE.520845

On 2017-11-22 06:33:42, user Partha Ray wrote:

Thank you for downloading and viewing our Abstract/Manuscript. We look forward to your questions, comments and thoughts on this and other related research directions. Partha S. Ray, MD

On 2018-11-10 15:11:38, user Michael Hoffman wrote:

This manuscript is incomplete as it is missing a Methods section referred to within. Methods are not described in the usual level of detail for a scientific publication.

On 2017-02-12 19:58:16, user Gary Miller wrote:

Just about 4 months after posting the original version to bioRxiv an extensively revised version has been accepted at PNAS. We will update soon.

On 2020-09-04 14:52:39, user zack troilo wrote:

Seems like this is the best in class vaccine. Little Arcturus Therapeutics is going to come out one of the big COVID vaccine winners

On 2020-10-22 08:32:28, user Saverio Brogna wrote:

The data suggesting a role of Upf1 in transcription, Figure 5 of this preprint, is now published in microPublication Biology - https://micropublication.or...

On 2018-06-28 09:25:08, user Julien Gagneur wrote:

See also the companion manuscript: <br /> A deep proteome and transcriptome abundance atlas of 29 healthy human tissues<br /> https://doi.org/10.1101/357137

On 2016-01-06 17:07:26, user Barry Jacobson wrote:

I have now posted the second paper on this topic titled, "Frequency Transformations and Spectral Gaps in Cochlear Implant Processing", available on BioRxiv. Currently at work on a third, to address some remaining issues, which should be completed shortly.

On 2024-08-01 16:35:16, user John McCusker wrote:

I just saw ( https://www.science.org/content/article/bad-agar-killing-lab-yeast-around-world-where-it-coming ). Many years ago, I had a similar problem with S. cerevisiae and C. albicans (but not E. coli) growth on agar. (Multiple vendors/suppliers, none of whom found anything wrong.) I eventually found that exposure of agar plates to light while drying (or incubating) caused the problem. Dried/incubated plates in dark and no problem.

On 2023-10-09 11:26:07, user Arda Sevkar wrote:

It appears that an incorrect strain was used for the alignment of Mycobacterium leprae. As indicated in the supplementary materials, the MRHRU-235-G strain was utilized for this purpose. Notably, the NCBI genome page designates this strain as the "reference strain". Unfortunately, that's not true. In the literature, alignment and genotyping are consistently carried out using the strain labeled as "TN" (NCBI Genbank accession number: AL450380.1)."<br /> Additional information regarding this subject is available in the following sources: Pfrengle2021, Krause-Kyora2018, Schuenemann2018/2013, Benjak2018, Monot2009

On 2022-05-31 06:39:26, user Prof. T. K. Wood wrote:

Original JBac 1996 manuscript that discovered phage inhibition by toxin/antitoxin systems should be cited:

doi:10.1128/jb.178.7.2044-2050.1996.

On 2025-09-13 04:10:37, user duckman wrote:

Using the score_interface function in BindCraft (with binder_chain set to A), I tried to reproduce the AF3 Rosetta metrics for several binders, but the values did not match those in final_data.csv (e.g., Motif0030_ems_3hC_714_0001_0003_6877_0001 and Pdl1_binder_AF2_54). However, I did succeed in reproducing the af3_ipSAE_max and af3_ipSAE_min metrics for these binders. Are there any caveats I should be aware of when generating AF3 Rosetta metrics?

On 2018-03-31 19:11:56, user Richard Stevens wrote:

Sorry to say this, but I think you may have a problem with some of the y-dna haplogroup assignments in your spreadsheet, but maybe you can clear it up. You have ZVEJ27 from Latvia (I4628) listed as R1b1a1a2a1 (L51), and in the original paper it was listed specifically as xR1b1a1a2a1.

You have I5235 from the Iron Gates in Serbia, a Mesolithic HG, listed as R1b1a1a2a1a1b1a1a, which is R1b-S5741, well downstream of U106 (S21), even though I5235 was listed as xR1b1a1a, xR1b1a1a2 in the original paper.

You also have I8998, dated 1000-800 BC, from the Swat Protohistorical burials in Pakistan, listed as R1b1a1a2a1a1c2b2b1a2, which, according to ISOGG, is R1b-S21728, downstream of R1b-Z9, i.e., a U106 subclade. Anything is possible, I guess, but does that seem likely?

On 2024-07-10 07:25:49, user Constantinos Constantinides wrote:

Published version: https://onlinelibrary.wiley...

On 2020-01-04 22:25:11, user Leonardo wrote:

Yeah I've always said that about "genome-wide association studies" - so is there a stupid patient-level explanation of this?

On 2024-06-28 16:26:14, user Yat Ho Chan wrote:

Hi everyone,

We are excited to share that our article has been peer-reviewed and published in Nature Communications! You can find the article at the link below.

https://www.nature.com/arti...

On 2019-09-02 08:53:55, user Mika Gustafsson wrote:

Thanks for an interesting article, which in many ways are related to our 2014 article (Gustafsson et al Genome Med 2014, PMC4064311) were we also proposed the same principle of shared and specific disease modules that could stratify patient responses. I recommend you read also that. //Thanks Mika

On 2024-01-02 10:08:48, user Anita Bandrowski wrote:

I am looking for the mouse that you got from MMRRC, but you state that you got the PG00171_Y_4_H09–Nfkbia vector from them. I don't think that is possible because they don't sell vectors. Can you check your lab records? Usually Addgene sells vectors, MMRRC sells mice. This is really odd.

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

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

On 2020-06-30 16:50:46, user Bruno Lopes Abbadi wrote:

Dear, I would like to congratulate you on the manuscript and say that I have some observations to make. In the methodologies section on cell culture, limiting dilution and isolation, the final volume in each well after adding the medium, virus, and cells is not very clear; would it be 150 uL? What was the final FBS concentration in each well? In addition, it was not very clear why you performed serial dilutions of the virus along lines 2-12. What is the purpose of this? Another question: from which well was the collection of 50 uL to infect the cells in the 24-well plate, since several wells may have a cytopathic effect? Finally, what is the purpose of infecting cells in 24-well wells? Did you use them only to count plaque-forming units, or to increase the virus titer? I hope that these considerations can further improve the quality of your manuscript. All the best.

On 2017-03-30 13:05:18, user Mateusz Iskrzynski wrote:

Just a small spotted misprint :

Figure 1:<br /> "A and D are unweighted", while in the picture A and B are unweighted

On 2020-02-26 16:34:05, user Sophie wrote:

Exciting work. I found it particularly relevant to a work we published in 2017 (link below), which showed the interaction of BCL-XL to KRAS mutant was necessary to maintain the expression of stemness genes. At the time, we thought that BCL-XL promoted a full RAS signalling because the expression of only some clusters of genes decreased after BCL-XL KD. Now, with this work and the recent work of Amendola et al. in Nature showing that KRAS4A specifically interacts with proteins at the mitochondria membrane, I think that by knocking down BCL-XL (a mitochondrial protein), we were only disrupting the signalling from KRAS4A and maybe not KRAS4B. <br /> https://www.nature.com/arti...

On 2024-02-07 11:17:19, user Mark Hahn wrote:

Now published: https://onlinelibrary.wiley...

On 2020-09-06 19:55:07, user Erik Welk wrote:

Hello,

library(lcvplants)<br /> LCVP("Hibiscus vitifolius")<br /> Error: 'tab_position' is not an exported object from 'namespace:LCVP'

Best wishes<br /> Erik Welk

On 2021-09-30 17:05:14, user Jin Yu wrote:

Published with MSDE from Royal Society of Chemistry:<br /> https://doi.org/10.1039/D1M...

On 2014-09-02 13:03:12, user Jomar Fajardo Rabajante wrote:

New abstract:

The well-known Waddington’s epigenetic landscape of<br /> cell-fate determination is not static but varies because of the dynamic gene regulation<br /> during development. Mathematical models of bistability cannot fully characterize<br /> the landscape’s temporal transformation because of limited number of state<br /> variables and fixed parameters. Here we simulate a model of gene regulation with<br /> more than two state variables and time-varying repression among regulatory factors.<br /> We are able to show sequential multi-lineage differentiation at different timescales<br /> that portrays the branching canals in Waddington’s illustration. We also show<br /> that a repressilator-type system activates suppressed genes by producing sustained<br /> oscillations in a flattened landscape, hence providing an alternative strategy<br /> for cellular reprogramming. The time-varying parameters governed by gradient-based<br /> dynamics dampen these oscillations resulting in dedifferentiation. The<br /> high-dimensional model integrates the theories of branching and oscillations in<br /> cell-fate determination, which further explains the mechanisms of cell differentiation<br /> and associated diseases, such as cancer.

On 2022-09-23 12:58:38, user Laura Rossini wrote:

Pleased to announce that the final updated and peer-reviewed version of this manuscript was published in Frontiers in Plant Science. Laura Rossini

Bretani G, Shaaf S, Tondelli A, Cattivelli L, Delbono S, Waugh R, Thomas W, Russell J, Bull H, Igartua E, Casas AM, Gracia P, Rossi R, Schulman AH and Rossini L (2022) Multi-environment genome-wide association mapping of culm morphology traits in barley. <br /> Front. Plant Sci. 13:926277. doi: 10.3389/fpls.2022.926277

https://doi.org/10.3389/fpl...

On 2021-06-11 01:06:47, user Sriharsha Talapaneni wrote:

For Figure 2, no WT shown which would be good for a reference. In 2C, it is unclear what is happening. A suggestion is to zoom out for a better image or do a zoomed out pic with a zoomed in figure beside it. Additionally, are both prox1a and tfa necessary? One subfigure could potentially be put in supplemental. Labels for arrows would also be helpful for 2D, F, and H. There also appears to be an inconsistency with dpf in the figure. Is the prox1a expression gone by 4 dpf? The reasoning for only showing 2 dpf might be needed. Concerning Figure 2F, a suggestion is to have a graph show foxa2 expression over time (1.5 dpf to 2.5 dpf). There also seems to be a resolution issue throughout the figure. A potential fix would be for 2F, to possibly trace it. To support claim and significance, we would also like to see more animals and different time points.

A potential future experiment could be the use of an organoid.

Moreover, I understand that the main idea of the paper is prove that zebrafish can be used as model system by conducting the experiments in various organ systems. But I believe that this point is kind of understand and people would normally get lost in the details of the figure and forget why you conducted experiments in different organ systems. Therefore, for this it would be better to mention and repeat it so that we understand the reason for the transition.

On 2016-02-09 23:05:52, user roedert wrote:

test2

On 2018-11-18 13:13:33, user Erlembaldo wrote:

Very interesting paper. I was wondering if they have been released the raw data about the samples used.

On 2021-12-09 13:30:13, user R. Rocca wrote:

You have misstated that haplogroup I2a2 is most common in Serbia. In fact, it is most common in places like Germany. See the SECOND frequency map on this link for reference: https://www.eupedia.com/eur...

On 2021-06-02 19:55:27, user Charles Warden wrote:

Hi,

Thank you for posting this preprint.

As a minor point, I think there is some grant information missing:

"National Institutes of Health grant X (CBB)"

Best Wishes,<br /> Charles

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

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

On 2017-07-25 01:24:22, user nextgennacrri Cornell wrote:

Genome-wide association mapping and genomic prediction unravels CBSD resistance in a Manihot

On 2017-05-02 19:34:19, user Jonas Richiardi wrote:

We have performed several additional experiments, and replied to this commentary in detail at https://doi.org/10.1101/132746. In brief, contrary to what is claimed here, spatial distance alone does not explain our results, which still stand.

On 2022-05-12 10:40:58, user Ramon Crehuet wrote:

very nice and clean work. I have a technical question. From what I understand, in general you use AF monomer except for the case of 1 peptide competing for MDM2/MDMX, is that right? In detail, you use:

https://colab.research.goog... for all cases, except the the MDM2/MDMX competition, where you use:<br /> https://colab.research.goog...<br /> Is the reason why you don't use AF-multimer in all cases the clashes found in version 1? If so, do you expect version 2 to work better and be the best option for these competition assays?

On 2022-10-28 22:50:28, user Nathan Bowen wrote:

what output from gnomix and additional software did you use to produce figure 8b. Chromosome painting of a Xoloitzcuintle (Xolo) dog ? thanks.

On 2022-09-16 12:07:25, user EM wrote:

This is a very important paper. It indicates that classifying and understanding the crystal polymorphisms that occur during protein/enzyme reactions with its ligand in crystals can lead to a detailed understanding of protein reaction mechanisms. This paper will become increasingly important with the development of the 4th generation synchrotron radiation facilities.

On 2023-11-28 16:09:01, user Fraser Lab wrote:

Deep mutational scanning has revealed the impact of individual point mutants on protein function and improved computational predictors of mutational effects. However, many mutations observed in evolution and disease are the result of insertions or deletions (indels) and the impact of these mutations are poorly predicted computationally relative to missense mutations. While a few other papers have profiled InDels in a systematic way, the major contributions of this paper are: 1) profiling indels across many different proteins (9), 2) profiling InDels for both stability and function, 3) introducing the concept of high throughput profiling of DelSub mutations (Mutations that remove an aa and substitute an aa in a single event)

The authors make a library of substitutions, insertions and deletions of 9 protein domains. They carry out deep sequencing coupled to fragment complementation assay (aPCA) that is well correlated with expression/stability. They then go deep on two peptide binding domains, comparing functional mutational scans as well. This provides a rich set of data to compare to computational predictions, where notable limitations in current prediction methods are identified. The major limitation of the paper is in the presentation - there is a lot of data and the figures are quite complex - but the text is brief and difficult to follow in parts. An expanded text and breaking up the figures into more figures would likely improve the ability to extract insights from these impressive datasets. Additionally further discussion of the results within the context of past literature would be helpful in guiding interpretation of the study.

**Major points:**

• The authors included 9 domains that span classical motifs to include in their indel scan. From our reading, it is unclear what rationale the authors used to include these domains. What makes these a diverse set of domains (a/b content? size? eukaryotic/prokaryotic origin? other topological features? etc)? This will help the reader understand how to generalise the results.

• In section “Evaluating indel variant effect prediction”, authors can comment on why PROVEAN is better suited to predict insertions and deletions relative to substitutions. In contrast, why CADD predicts substitutions better than PROVEAN? What design choices can distinguish PROVEAN from CADD? Is there a way a model could be trained that could perform well on both?

• In the section “Structural determinants of indel tolerance,” the authors mention multiple features that seem potentially important for the effects of insertions and deletions. Currently specific patterns are discussed for the substitutions but the main draw of this manuscript it contains indel mutagenesis across many proteins and the discussion in this section regarding indels are vague beyond that indels are more tolerated at the N and C termini, that the secondary structure is important, and where the indel is seems to have an impact. Currently in our reading these are vague descriptions and perhaps it would be possible to describe general trends? What specific lengths are tolerated vs not? Which secondary structural elements are more sensitive? It would be helpful to clarify these trends with existing literature. For example, previous work in a potassium channel kir2.1 (Macdonald, CM, Genome Biology 2023) found that deletions were more disruptive than insertions in beta sheets especially. Is that also seen?

• The authors train a model as described in the ‘Accurate indel variant effect prediction’ section to predict the effects of indels within all the proteins that are contained within the screen and another manuscript Tsuboyama et al. However, there are other previous indel scans that have been done including one within a viral AAV capsid protein (<https: <a href="www.science.org" title="www.science.org">www.science.org="" doi="" 10.1126="" science.aaw2900="">), a potassium channel kir2.1 (<https: <a href="genomebiology.biomedcentral.com" title="genomebiology.biomedcentral.com">genomebiology.biomedcentral...="" articles="" 10.1186="" s13059-023-02880-6#citeas="">), and an amyloid protein that involved the senior author (<https: <a href="pubmed.ncbi.nlm.nih.gov" title="pubmed.ncbi.nlm.nih.gov">pubmed.ncbi.nlm.nih.gov="" 36400770=""/>). It may be useful to test performance of the model on these datasets that were not generated within the same study and discuss where the model performs well vs those that do not perform as well.

• The authors find that insertions can generate gain-of-function molecular phenotypes at higher rates relative to deletions and substitutions. Overall, the manuscript presents the results of deep indel mutagenesis on several protein domains, but lacks thorough discussion of the results. A discussion addressing the possibility of non-native ligand binding following indel mutations would provide an evolutionary perspective that contextualises this research.

• The authors mention that some gain-of-function mutations occur due to short insertion mutations. While some domain insertions have been shown to have stabilising effects (<https: <a href="doi.org" title="doi.org">doi.org="" 10.1371="" journal.pcbi.1006008="">, <https: <a href="doi.org" title="doi.org">doi.org="" 10.1038="" s41467-018-08171-0="">, <https: <a href="www.nature.com" title="www.nature.com">www.nature.com="" articles="" s41467-021-27342-0="">), the findings presented here are novel for being short insertions but prior work on domains and deletions of varying type being beneficial would be useful. Emphasising this in the “Insertions generate gain-of-function molecular phenotypes” section and considering how the insertions in the PSD95-PDZ3 domain might increase stability would enhance the understanding of the underlying mechanisms driving these gain-of-function phenotypes.

• Related to gain-of-function: The last sentence of the discussion section references the potential usefulness of indel mutagenesis for protein engineering. As the paper notes, the results here will impact the protein engineering field significantly, so further discussion here will help extend the reach of this paper. Discussing what protein engineering strategies would be enhanced (e.g. directed evolution) would help the reader in evaluating the impact of the data presented. There are a few related papers in the literature (e.g. [https://doi.org/10.1073/pna...](https://doi.org/10.1073/pnas.2002954117 "https://doi.org/10.1073/pnas.2002954117") "https://doi.org/10.1073/pnas.2002954117))") that could support this.

**Minor points:**

• Several of the figures are very information-dense. This manuscript would benefit from breaking up these figures and reorganizing them to make them easier to understand. It may be helpful also to focus the figures on the main points the authors would like to make within the manuscript as currently the sheer amount of data and analyses makes it difficult to follow the narrative. Additionally, figures could benefit from having secondary structure representations above or below heatmaps to aid in interpretation.

• Figure 1 contains A-C labeled sections but contains 9 comprehensive experiments with 6 subpanels each. It is very difficult to evaluate the data when it is so densely represented. aligning an “unfolded” secondary structure below the heatmap for all domains might be clearer than colouring by secondary structure. We find secondary structure coloring to obscure the patterns.

• Figure 2 would benefit from significant reorganization perhaps around SH3 and PDZ domains specifically. The spacing within this figure makes it difficult to follow the immense amount of comparisons contained here. Perhaps it would be worth separating this figure up or moving some of the comparisons to the supplement. As in Figure 1 secondary structure above or below the heatmaps would be helpful.

• In figure 5E data is shown for GRB2-SH3 in which some mutants show high binding and low abundance. Additionally these mutants are most prevalent in the core and surface. What could be an explanation for such a phenotype for core mutants, since they are bound to have the most destabilizing effect. For the surface mutants, are those residues close to the binding site? Additionally the distributions of these two plots look fundamentally different (with a much higher correlation between binding and abundance for PDZ and a distinct change in the pattern of binding residues being gain or loss of function across the two domains). What does that say about the baseline stability of GRB2 vs PSD95? Or is this more representative of some methodological aspect of the dynamic range and sensitivity within respective assays when run on these specific proteins?

• In the heatmap figures the coloring is confusing. Currently they are colored from red to white to blue - in the corresponding color bars next to the heatmaps white is not centered at 0. Presumably 0 is wildtype fitness and blue and red are greater and less than wildtype fitness, respectively. This should be explicitly stated within all figure legends. White should correspond to 0 otherwise it makes it difficult to determine the effect of a mutation.

• Figure 3E contains violin plots however a boxplot is missing from these that indicates the median, interquartile range, and whiskers to represent non-outlier distributions. This would be useful in comparing across these variant types

• In ‘Materials and Methods’ section, we were confused by the filtering steps taken in the ‘sequence data processing’ section. It would be helpful to include the minimum read cut-off.

• Figure 4b should be explained more completely in the figure legend. It is very difficult to make out what the difference in colour for each panel means.

• In the last paragraph of the introduction, it would provide additional support and context if you referenced other work with similar findings. These papers (<https: <a href="doi.org" title="doi.org">doi.org="" 10.1186="" s13059-023-02880-6="">, <https: <a href="doi.org" title="doi.org">doi.org="" 10.1101="" 2023.06.06.543963="">) would support the statement, “In general, indels are better tolerated in protein termini than in secondary elements.”

Reviewed by Priyanka Bajaj, Karson Chrispens, James Fraser, Willow Coyote-Maestas

On 2019-05-31 23:25:09, user Charles Warden wrote:

Very interesting paper:

What if you plot precision (for breast cancer), with pathogenic variants for BRCA1 versus BRCA2 (versus current PRS predictions)?

On 2023-10-05 12:53:24, user Matteo Brilli wrote:

I was checking the multialignment provided for download on the website. I am not an expert of supermatrix approach, but I have 20 years experience with phylogenetics, even if it is not my main occupation. Now, it turns out the multialignment has NO positions where all sequences have a non-missing character. The median number of Ns per sequence is around 32k and the alignment has 36327 sites. Across those sites, the minimum number of Ns is over 700, with a median number of Ns per site around 4000. Now, my question is, is ML able to reconstruct a satisfactory phylogenetic tree in these conditions? I understand missing data can be accounted for during reconstruction, but I suspect that if there are only (or almost only) missing data, the approximation will be far from reality.

On 2020-08-14 12:38:44, user qx jiang wrote:

The structures are pretty good and record-making. <br /> The channel behavior, ion selectivity sequence, and electrical recordings, esp. S2 appear strange without matching regular opening/closing events.

On 2016-06-23 17:34:00, user Simon Schultz wrote:

Please note this paper was published as:

S. Reynolds, C. S. Copeland, S. R. Schultz and P. L. Dragotti, "An extension of the FRI framework for calcium transient detection," 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, 2016, pp. 676-679.?doi: 10.1109/ ISBI.2016.7493357.

On 2025-05-20 21:39:39, user Chase Clark wrote:

https://github.com/medema-group/BiG-SCAPE/tree/master/Annotated_MIBiG_reference

Doesn't exist in the current master branch, needs to be updated to reference the permalink

e.g. https://github.com/medema-group/BiG-SCAPE/tree/bb2264c8101f8f7204f2799e41aeef2a2505da72/Annotated_MIBiG_reference

On 2015-02-07 15:47:52, user Peter L Borst wrote:

For openers, the English in this paper is absolutely atrocious. But beyond that, the authors have no idea what CCD is. The seem to conflate it with death of the colony by any factor. Colonies that are poisoned do NOT exhibit symptoms concomitant with CCD, which has never been clearly defined nor have any actual cases of it been documented. Honey bee colonies are very susceptible to poisoning, but this does not prove that colony die-off is correlated to widespread use of insecticides, especially since colonies have been failing in non-agricultural regions at near the same rate. The most likely cause of widespread die-off is honey bee viruses, exacerbated by the stress of varroa mites and seasonal dearth.

On 2017-12-07 09:24:36, user Bayazit Yunusbayev wrote:

Very interesting! I wonder if you can also report average Fst between simulated parental populations?

On 2019-05-28 21:15:48, user Kristof Theys wrote:

All R code will be shortly posted on https://github.com/ktheyss/..., to be used in future studies or to be improved.

On 2021-10-04 08:50:43, user Ramon Crehuet wrote:

I find it intriguing that AF2 outperforms experimental structures (Fig. 3A) when used to predict variant effects. That comes from the regions where AF2 has high confidence but where it could not use a template (Fig 2B)! Is this reporting on the quality of experimental structures? And does it depend on the experimental method? I guess this could be obtained from data in Fig. 6, but it is not straightforward.

The fact that the template reduces the quality when pLDDT also suggests that AF2 could be improved by allowing it to discard a bit experimental templates, right?

On 2018-02-21 11:00:04, user Benjamen White wrote:

My unpopular opinion would be to rename your tool to avoid confusion and increase uptake. I know a lot of people are moving onto Canu now, but the FALCON assembler is still very prevalent. https://github.com/PacificB...

On 2019-04-14 08:05:38, user Arpan Parichha wrote:

I was thinking of using the SABER technique in our system and wanted use its multiplexing feature for our purpose. I am unable to use the oligominer pipeline. Can anybody tell me how to design the PER primers?

On 2020-05-18 16:18:00, user Anita Bandrowski wrote:

"Hi, we're trying to improve preprints using automated screening tools. Here's some stuff that our tools found. If we're right then you might want to look at your text, but if we're not then we'd love it if you could take a moment to reply and let us know so we can improve the way our tools work. Have a nice day.

Specifically, your paper (DOI:10.1101/2020.04.03.023846); was checked for the presence of transparency criteria such as blinding, which may not be relevant to all papers, as well as research resources such as statistical software tools, cell lines, and open data.

We did not detect information on sex as a biological variable, which is particularly important given known sex differences in COVID-19 (Wenham et al, 2020).

We also screened for some additional NIH & journal rigor guidelines:<br /> IACUC/IRB: not detected ; randomization of experimental groups: not detected ; reduction of experimental bias by blinding: not detected ; analysis of sample size by power calculation: not detected .

We found that you used the following key resources: cell lines (1) . We recommend using RRIDs to improve so that others can tell exactly what research resources you used. You can look up RRIDs at rrid.site

We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

More specific comments and a list of suggested RRIDs can be found by opening the Hypothes.is window on this manuscript, direct link https://hyp.is/U4WZvo-tEeqx...<br /> References cited: https://tinyurl.com/y7fpsvzy"

On 2022-02-22 16:06:32, user Shahan Derkarabetian wrote:

The paper has been published:

https://frontiersinzoology....

On 2022-06-21 13:17:37, user Davidski wrote:

Hello authors,

Thanks for making the genotype data available so quickly. A few points after running the data, copy pasting from my blog...

• in terms of fine scale ancestry, the Erfurt Jews show enough variation to be divided into three or four clusters, as opposed to just two as per Waldman et al.

• some of the Erfurt Jews show excess "Mediterranean" ancestry, while others excess "North African" ancestry, and this cannot be explained with ancestral populations similar to Lebanese and/or South Italians, but rather with significant gene flow from the western Mediterranean and possibly North Africa

• several of the Erfurt Jews show relatively high levels of "East Asian" ancestry that cannot be explained with admixture from Russians, or even any Russian-like populations, because such populations almost lack this type of ancestry, and instead show significant "Siberian" admixture

• as far as I can see, there are no correlations between any of the observations above and the quality of the samples. That is, low coverage doesn't appear to be causing the aforementioned excess "Mediterranean", "North African" and/or "East Asian" ancestry proportions.

More at this link:

https://eurogenes.blogspot....

Cheers, David Wesolowski

On 2019-10-05 15:54:37, user Dr. David Ludwig wrote:

BMJ STUDY CO-AUTHOR RESPONDS

In the multiple versions of their preprint here, and in a final version in International Journal of Obesity, Hall & Guo criticize our BMJ study that showed higher energy expenditure on low- vs high-carbohydrate diets.

We now respond in full in the same journal (full text linked here):<br /> https://www.nature.com/articles/s41366-019-0466-1

We show that all these criticisms are fundamentally misleading or simply wrong. Specifically, we consider why:

1. The post-weight-loss baseline is the most appropriate for studying metabolism during weight-loss-maintenance.

2. The change in our registry was proper.

3. Non-adherence would not plausibly account for our findings, based on several sensitivity analyses.

In summary, there is substantial support for the carbohydrate-insulin model of obesity, and assertions to have disproven ("falsified") the model are without merit. At the same time, admittedly, neither is the model proven. Pending additional high quality studies with complementary design, scientist on both sides of the debate would do well to avoid premature conclusions.

On 2015-03-12 19:12:25, user paulhummerman wrote:

Nice paper. 2 minor comments. It would be nice (though unsurprising) to show that strengths of synapses made by the same axon on different dendrites of the same postsynaptic neuron were also highly correlated, but of course this would require more extensive 3D reconstruction. Second, since most connections are made of several synapses, it seems likely that the bit resolution of connections is even higher than 4.6

On 2017-03-02 14:27:17, user Steve Shea wrote:

I posted a comment on this paper to my blog: https://idealobserverblog.w...

On 2018-07-10 20:54:23, user DHelix wrote:

Very helpful. Thanks a lot for sharing the information!<br /> I was wondering how your HEK293 ATAC-Seq tagmentation looked like on DNA gel or Agilent profile. I'm trying to perfom ATAC-Seq on HEK293 cells. I could see bands but it also had quite high background (the bands were not very clear and sharp). Any ideas? Thanks!

On 2023-04-21 15:46:40, user Manolis Kellis wrote:

We thank Murphy, Fancy, and Skene for their attention to our manuscript, and for their efforts in reprocessing and analyzing our data. We acknowledge that there can be advantages to pseudobulk methods, and that no single method is likely to outperform all others in all settings. As the technologies and methods used in our paper are now over four years old, in a rapidly moving field, we expect many newer analyses will be able to clearly outperform previous papers in the field, including ours. More broadly, we encourage students and practitioners to revisit previous papers as a general practice of open science, and to share the results in open, respectful, and transparent ways, which can move the field forward collaboratively and constructively.

That said, in this particular case, Murphy et al.'s results fall short of their claims, and they fail to demonstrate any advantages of their approach compared to our manuscript, due to several technical and logical mistakes in their analysis, which we outline here: http://compbio.mit.edu/scAD...

Briefly: <br /> * Murphy et al. do not compare to our actual 1,031 reported differentially expressed genes (DEGs), they exclude our mixed-model results from their comparison, thus misinterpreting our work as cell-level-only with 14,274 DEGs, which is a misrepresentation of our results.

* They interpret any differences between their results and ours as improvements (conflating false positives with true predictions and lack of power with specificity) without providing any independent support – by contrast, our paper validated our DEGs using both targeted experiments and comparison with previous human and animal studies.

* Their central claim that our reported DEGs are false positives lacks any substance: indeed, they are not found by their pseudobulk method, but they could simply be missed due to lack of power, and Murphy et al. provide no independent evidence that their method is sensitive or accurate.

* Conversely, the 16 DEGs that they do report lack any independent evidence that they are biologically meaningful, and Murphy et al. provide no evidence that their method is specific. In fact, their 16 DEGs show unrealistically-high ~1200% median changes, and only implicate the rarest cell types, suggesting they may represent false positives stemming from unaddressed statistical artifacts due to outliers and small cell counts.

* Murphy et al. also make general claims about the advantages of pseudobulk methods by applying only one method, erroneously, to only one dataset, without any benchmarks, and without comparison to current state-of-the-art methods, while misusing statistical terminology.

* Lastly, they overstate their previous results from a similar Matters Arising commentary, which also advocated for pseudobulk using the same pattern of only analyzing a single dataset, methodological shortcomings, overstated conclusions, and not addressing corrections suggested by the original authors.

This is a helpful example to discuss potential pitfalls in comparing bioinformatic pipelines, and to recommend perhaps more constructive strategies for such comparisons, including: applying candidate methods to more than one dataset, comparing to the actual results of the original paper without misrepresenting them, using independent validation metrics to evaluate differences instead of assuming that they are all improvements, using well-established and rigorous benchmarks, including comparisons with other state-of-the-art methodologies, scrutinizing their own predictions for potential confounders, and seeking to understand the biological or technical drivers of potential differences.

We provide a more detailed response here: http://compbio.mit.edu/scAD...

On 2018-08-04 13:38:26, user Peter Rogan wrote:

Great paper.

"Indeed, although not identified by haplotype, allelic differences in accessibility and volume have been noted at the level of individual genes (47)" <br /> Thanks for the citation, however, we did identify DA by haplotype...

A haplotype is a group of genes within an organism that was inherited together from a single parent, and this precedes the current genomic definition based on SNPs and CNVs. Our preceding paper (PMID 25520753): showed that differential accessibility was allele specific by marking chromosomes in which the DA loci were linked unrelated structural abnormalities (translocations) and an instance of familial transmission of a linked structural abnormality (microdeletion). So we have demonstrated DA based on haplotypes. We suggest that you add this reference as well and remove the incorrect qualifier during peer review..

On 2020-11-22 03:46:09, user Jingyi Jessica Li wrote:

Thanks for pointing us to the SERGIO paper. In fact, scDesign2 and SERGIO require different inputs. While scDesign2 learns gene correlation from a real gene-by-cell count matrix, SERGIO requires a user-specified GRN as input and does not estimate gene correlations from real data.

A quote from the SERGIO paper: "It is worth noting here that several existing single-cell expression simulators employ a probabilistic model whose parameters are directly estimated from a real dataset and then sample synthetic data from the model. This approach is not feasible in SERGIO since the true GRN underlying the real dataset is unknown and notoriously hard to reconstruct, and the explicit use of a GRN is a crucial distinguishing feature of SERGIO."

Thanks to the comment, we have revised our manuscript and updated it on bioRxiv. Please check out our next version.

A feature of scDesign2 is to guide experimental design by mimicking input real data and varying cell number and sequencing depth.

On 2018-04-17 16:30:35, user gwern wrote:

"However, the individual effect sizes of these variants are small, and all variants identified to date jointly explain only ~20% of the heritability of height."

50%. See "Accurate Genomic Prediction Of Human Height" https://www.biorxiv.org/con... , Lello et al 2017.

On 2020-04-03 02:13:57, user Tamara Terzian wrote:

Here is the podcast on the article from Chris Casey at the CU Anschutz newsroom:

https://news.cuanschutz.edu...

On 2019-04-01 03:12:11, user Stephan Anagnostaras wrote:

neat paper

On 2020-04-24 22:25:46, user Xander de Haan wrote:

“In conclusion, we have discovered that GAGs can facilitate host cell entry of SARS-CoV-2 by binding to SGP in the current work.” This study shows binding, not enhancement of infection. MHV-a59 also has a furin-cleavage site at S1/S2. Binding of this virus to HS probably has a negative effect on entry, which can be overcome by PBS-DEAE. MHV/BHK does depend on HS for entry (PMID: 16254381). Its furin cleavage site at S1/S2 is no longer cleaved in the producer cell (similarly for FCoV ref 28, ref does not deal with IBV or MHV btw). So cleavage at the furin/multibasic cleavage site appears inversely correlated with HS binding. To what extent were the S proteins in this study processed by furin? Furthermore, binding to HS may not necessarily be helpfull for infection, as HS may probably also function as a decoy receptor.

On 2015-11-01 16:08:23, user Keith Robison wrote:

While writing a blog entry on this paper, http://omicsomics.blogspot...., I noticed that the imaging buffer recipe is probably incomplete, as catalase would be needed to complete the oxygen scavenging reaction series

On 2018-09-07 17:18:34, user Alexander Predeus wrote:

Congratulations to the authors on this preprint - very promising result, which could be useful for numerous applications. Would it be possible to publish the R code used for finding the associations on github? Thank you in advance!

On 2023-11-17 10:21:46, user EML wrote:

Really interesting paper, will dive into this deeper. Quick comment and question already:<br /> - would it be possible to do segregation testing in pedigree 1? As the affected individuals are still alive it might be possible to obtain DNA (no large amounts needed).<br /> - It would be helpful if the pedigrees in figure 6 would be redrawn in such a way that the first generation does not appear to have offspring of two females...<br /> best wishes,<br /> Elisabeth Lodder

On 2020-10-19 19:02:04, user Marion06 wrote:

Calcium channel blockers also inhibit the effects of electromagnetic fields on cells. EMF increase calcium inside the cells.

On 2023-02-20 18:47:32, user Donald R. Forsdyke wrote:

Despite this feedback, the paper was published in Physics Reports. The authors have continued to disregard the feedback. A new paper in eLife has passed peer-review and is now formally accepted for publication. I have added a brief comment to the corresponding bioRxiv preprint.

On 2016-04-21 13:03:39, user Kyung Mo Kim wrote:

This preprint manuscript is an extended version of an eLetter posted by Harish et al. commenting on the article by Nasir and Caetano-Anolles, "A phylogenomic data-driven exploration of viral origins and evolution”, which was published in Science Advances 1(8): e1500527 (2015). A response to this eLetter by Nasir et al. entitled “No ‘small genome attraction’ artifact” can be found at http://advances.sciencemag..... An extended version of this eLetter is forthcoming.

On 2016-05-27 16:08:26, user dcx_2 wrote:

Yeah, 6W/kg and it was _whole-body_ SAR, too. The researchers upped the wattage as necessary whenever the animal gained weight. Meanwhile, the FCC measures the SAR on the one-gram mass absorbing the most signal.

Further, they were blasting these animals with the radiation in-utero *from day 5*. I don't know any blastocyst that has a cell phone...

There's also this gem on page 9 of the study: "At the end of the 2-year study, survival was lower in the control group of males than in all 2 groups of male rats exposed to GSM-modulated RFR." In other words, the animals *not* exposed to the radiation were more likely to die.

On 2016-05-29 19:56:45, user guy wrote:

90 seems like a pretty small sample size to me, but I'm not a biomedical researcher or a doctor.