On 2020-12-20 12:03:45, user GoranM wrote:

You write that "The study cohort consists of 147 unrelated individuals from Serbia". However, Serbia has a significantly diverse population (nationally) and it would be of interest to know from which regions of Serbia they were. Were the recruited only from the Belgrade region or did you also recruit subjects from Northern Serbia, Eastern Serbia, South-East Serbia, South Serbia (of Romanian, Bulgarian, Albanian, Hungarian, Czech ... descent)? If yes, that would mean that "Serbian" genom, which you showed nicely, overlap perfectly with the European, and that observed changes and differences might mainly be attributed to the epigenetic changes. Serbia is, unfortunately, one of the mots polluted European countries with no enforcement of environment protection laws and very rudimentary public health protection, and with extremely high air pollution and the country with the most active cigarette smokers.

On 2020-12-19 18:35:43, user Clara B. Jones wrote:

really useful treatment... how do these ideas relate to hypothesis that evolution of sexual dimorphism in body size between the sexes "allows" males to ESCAPE direct competition for limiting resources with females [in the same conditions] which reduces fitness, impacting males? clara b. jones @cbbjones1943 foucault03 at gmail dot com

On 2020-12-18 20:40:29, user Gavin Douglas wrote:

Hi Pat,

My lab discussed this preprint at a recent journal club because we definitely agree this is an important area to investigate. However, overall we disagreed with the conclusions and we had issues with several key analysis steps. We have written up a review of the preprint with specific comments, which we hope is of some use: http://dalmug.org/filter-re...

All the best,

Gavin

On 2020-12-15 10:36:24, user Julian Marchesi wrote:

Can anyone answer me this<br /> 1: what % of singletons i.e. 1 read in one sample are real and what % are due to sequencing errors and bioinformatic artefacts? It always amazes me how people grab the latest idea like it must be right, so ASVs are in and OTUs are out. Well if you missed the memo, we don't even have a robust definition of what a bacterial species is, so anything we use is always a compromise and biases out analysis.<br /> 2: if you don't sample to the same read depth how can you create comparable alpha diversity indices? Won't a sample with a read depth of 20,000 reads have a different Shannon index to one with 1500 reads?

On 2020-12-18 17:33:30, user Leandro de Mattos Pereira wrote:

In my opinion, this type of research that involves the genetic manipulation of sarcov-2 should be banned, given the little knowledge we have of genetic recombination between sarcov-2 and exogenous sequences is yet limited. The ethics committee should not approve this type of exploratory research using vectors with reverse transcriptase together with cells infected with sarcov-2.

On 2020-12-16 14:27:27, user Albert Heim wrote:

As a clinical virologist I am suprised about the introduction and background of the study which resulted in a (form my view) peculiar hypothesis (genomic integration of SARS-CoV-2). I don't want to comment on the way this hypothesis was tested, merely on its background.<br /> Long term detection (several weeks to a few months) of any respiratory virus (e.g. Rhinovirus, Influenzavirus) after an acute infection is "business as usual". However, systematic follow up testing of these patients was not usual, but if a patient was diagnosed with Flu A in January and comes down with another respiratory infection in March, it is not surprising to detect e.g. HMPV and Flu A in March. If the analysis is done with real time PCR, you will find e.g. Ct 18 for HMPV and CT 37 for Flu A, so the diagnosis in March is "HMPV infection" and the detected Flu A is a little bit "left overs" from January. <br /> In general: If you use multiplex PCR diagnostics about 5 to 10% of all diagnostic respiratory samples can be positive for two or three viruses, usually one of these is highly positive (the real culprit) and the other(s) are found close to the LOD (left overs of previous infections). <br /> In COVID-19 patients, we follow up virus loads in respiratory specimens. These decline rapidly with convalescence but remain at levels close to the LOD (and therefore intermittently positive) for many weeks. This is an anticipated result as with other respiratory viruses. The respiratory tract contains hairs, mucus, tonsillary clefts, sinus and many other structures where a little bit of any "dirt" (e.g. a few of the billions of capsids produced in an infection) can persist. Even on "clean" surfaces (e.g. stainless steel) of a laboratory, you can find these viral contaminations by highly sensitive PCR if not meticulous decontamination measures were performed. No one would however build a hypothesis from this finding that SARS-CoV-2 has a specific mechansm to perist on (or: integrate in) stainless steel. Such a PCR result merely shows imperfect decontamination of a surface (but there are no decontamination at all done in the respiratory tract, neither brushing with SDS nor with sodium hypochloride nor flushing with fresh water as the least cleaning measure). Anyway, these results do not show infectious particles. Even if a few of these capsids were (theoretically) infectious, these were too few to cause an infection.

On 2020-12-15 13:13:04, user Χρίστος Δαγρές wrote:

The authors cited Bo Yuan et al ("Recurrence of positive SARS-CoV-2 viral RNA in recovered COVID-19 patients during medical isolation observation") where the case of approx. 20 patients from China were re-tested positive after they had recovered from COVID-19. <br /> The authors suggest as a possible explanation the possibility that parts of SARS-CoV-2 RNA were reverse transcribed in human genome and then they were expressed later leading to positive PCR-tests.

What's interesting though in the paper of Bo Yuan et al is that none of the 39 pts with severe COVID-19 symptoms were re-tested positive. Given that pts with severe clinical symptoms are expected to have a higher viral load, wouldn't the authors expect that patients with severe symptoms should have higher risk for SARS-CoV-2 RNA intergration in their genome and thus, lead to higher re-positive rates?

On 2020-12-15 11:05:02, user Dominik wrote:

As others pointed out, this paper is seriously flawed in many aspects and should be retracted, especially considering that many people are afraid of a new type of vaccine (mRNA) and conspiracy theorists certainly will take this paper to "proof" that mRNA vaccines can in fact alter your genetic code.

On 2020-12-15 04:33:03, user Cedric Feschotte wrote:

The authors tackle an important question, but the data presented in this preprint are unconvincing and insufficient to claim SARS-CoV-2 is reverse-transcribed and integrated in the human genome. Others in this thread have already pointed at some of the flaws, but here is my own take.

To prove retrotransposition events, the standard in the field is to isolate and report the sequence of the integrants along with flanking genomic sequences (junction sequences spanning both viral and flanking DNA). This can be achieved using a number of approaches, including a variety of PCR-based assays (inverse, vectorette, adapter-ligation, Alu-anchored, etc.), whole genome sequencing (ideally using long reads), or capture high-throughput sequencing (e.g. akin to RC-seq). None of these approaches is flawless, so multiple, orthogonal approaches are requisite to draw firm conclusions. Here, the authors do not report any junction sequences of integrants or the sites of chromosomal integration.

Obtaining junction sequences is critical because it provides not only validation of chromosomal integration, but also important clues about the mechanism of integration. If LINE1 (L1) is involved one expect to see: target site duplications (short direct repeats flanking integrant), integration at preferred L1 endonuclease cleavage site (TTTT/AA), polyA tail at the 3’ end (or chimera with the 3’ end of endogenous L1/Alu). The authors suggest that the L1 machinery is involved in the alleged retrotransposition events, but do no report any of the hallmarks of L1-mediated retrotransposition. Again, this is because they do not report sequences for any integration events, neither from infected patient nor cell culture experiments. qPCR and RNA-FISH are inadequate approaches to prove genomic integration.

There are pitfalls with the analysis of chimeric reads in Fig. 1 that the authors can and should address. These reads seem exceedingly rare and could represent artifacts of RNA-seq library prep or aberrant template-switching events from Cov-2 subgenomic RNAs to cellular mRNAs. The latter would not be surprising because coronaviruses use a process of discontinuous transcription during replication involving template switching. Both library prep artifacts and template switching mechanisms predict that SARS-CoV-2 RNA would form chimeras with human mRNAs and therefore largely exonic sequences (which derive from only 1-2% of the human genome sequence). By contrast, if chimeric RNAs originate from readthrough transcription of integrated SARS-Cov-2 sequences, as the authors evoke, they would most likely form chimera with a variety of inter and intragenic human sequences. The authors should provide a more detailed analysis of the chimeric transcripts and the host sequences involved. In any case, the detection of human-SARS chimeric RNAs, even if substantiated, does not constitute evidence for viral reverse transcription or integration into the genome.

Experiments in cell culture (Fig 2) with L1 overexpression vectors are highly artificial and no more convincing than those in human patient samples: no integrants are isolated/sequenced and they lack important controls (e.g. RT mutant constructs, which are available). While these experiments would be important in establishing proof-of-principle that retrotransposition of SARS-CoV-2 RNA is possible in a cell culture system, of course it would still be premature to conclude that the phenomenon occurs in infected individuals and has clinical relevance. Thus, even if the results in cell lines were to be substantiated, the title should reflect the in vitro nature of the work and the abstract should state explicitly that in vivo integration of SARS-CoV-2 sequences remains a matter of speculation.

On 2020-12-15 00:07:54, user bahaa wrote:

I have some questions to the author regarding the samples and procedures of collection and analysis of these data to be sold in front of discussion and evidence bases article

On 2020-12-14 23:38:15, user Michael Eisen wrote:

I am skeptical of these claims, and surprised by the timing of this paper's release.

This is obviously a topic of great interest and extreme import, given the release of this preprint right as an RNA based COVID vaccine is entering wide distribution and another is on the way. The authors have raised the possibility that host retrotransposes have to potential to integrate viral RNAs into the host genome (an unsurprising result) but have not demonstrated that this occurs with appreciable frequency in infected individuals or that it has any clinical relevance.

The idea that endogenous RTs could integrate viral RNAs into the host genome is not surprising. Indeed it is seems almost certain that it happens at at least low frequency given the presence of intronless paralogs and pseudogenes. So the experimental observations that it can happen under ectopic conditions isn't of significant clinical relevance.

The real question is whether this is a rare curiosity, or if it is sufficiently common to warrant public health concern. And here the only evidence presented is the presence of chimeric (human:COVID) reads in a handful of infected cell lines and a couple of clinical samples. The problem with this observation, as the authors allude to but only passingly address, is that chimeric reads are a well-known artifact in RNA sequencing data. And several of the observations - the increased frequency of such reads with increasing viral loads, and the bias of such reads towards the most abundant viral RNAs - are exactly what you'd expect if they were artifacts. There are a number of things the authors could do to rule this possibility out and make a more compelling case, but none of them were presented here.

Given the absence of any other data to support the clinical relevance of this observation, all of the speculation about how this might impact testing, vaccination, drug screening etc.. and how this might be an adaptive strategy to store viral antigens to guard against future infections is pure speculation and should be treated as such by anyone with interest in the topic.

It is unfortunate that a paper is making highly speculative yet frightening claims of COVID integration into the human genome was released right as an RNA vaccine is being introduced to the population, and amidst well-known, and widespread, opposition to vaccination. Obviously, if the authors feel they possess evidence of clinical relevance, it is their duty to release it as expediently as possible. However, the paper makes it clear that even the authors agree they have not proven their case. Given that this is one of those rare circumstance where a scientific result has the potential to immediately impact public behavior in a way that undermines critical public health measures, I think both more thorough experiments and analyses, and more caution, were warranted.

On 2020-12-14 22:35:27, user Stuart wrote:

This preprint has the unfortunate character of having a title that over-reaches the data presented. The model systems are contrived, and the central data are unconvincing.

On 2020-12-14 22:09:59, user Stylianos Antonarakis wrote:

The data are not sufficient to support the conclusions. The authors should show genomic DNA sequencing with the integration site. And also the fraction of somatic cells with the integration.

On 2020-12-14 18:30:37, user Rachael Tarlinton wrote:

As others with more experience in Bio-informatics than me have pointed out the chimeric reads reported here are likely an artifact of the sequencing method. The authors have also used a very artificial cell culture system to specifically drive the phenomenon they were seeking and even then have not actually demonstrated integration of virus into the genome (this would as others have pointed out require sequencing of the DNA of the cells rather than the RNA to capture the integration sites between cellular and viral DNA). <br /> There does seem to be a case (in general) that viral infections in cells lead to increased expression of retroelements (we have reported on this ourselves) but in no case that I am aware of has anyone demonstrated that this then leads to integration of the virus (or the retroelement) into the genome. In people the accumulation of new retroelement integrations is a very rare occurrence indeed (these types of evolutionary events are measured in millions of years, not an individuals life span) . This is not the case in species with more recent and active retroviruses (such as pigs, sheep, koalas, mice, chickens) but even in those species they do not typically pick up or insert sequences from other virus classes (these types of events are even rarer than new retroelement insertions). The mechanisms speculated here have also never been known to occur with HIV infections in people (an incredibly well studied retroviral infection). <br /> This paper certainly does not demonstrate that SARs-Cov-2 is or is likely to become integrated in a human genome.

On 2020-12-14 17:47:26, user Kevin McKernan wrote:

This is an important topic for qPCR fidelity and our ability to discern infectious versus non-infectious patients.

The majority of the qPCR assays are targeting the N gene and as a result we have an atrocious process of quarantining society on non-infectious qPCR positivity and this work may shed important light on this egregious human rights problem.

It would be helpful to know if the sgRNA in DMVs persists longer than chromosomal integrations. It may help the general public to speak about epithelial cell turn over as I have seen several people mistake these integration events as a permanent addition to their germline when these cells likely turn over in a few weeks to months.

Some discussion on SARs-CoV-2 long persistence in the GI where there is high cell turn over but not successful viral culture in Vero cells may also be in order.

Some discussion on the propensity of Spike protein mRNA in vaccines and their capacity to do or not do this may help address the public confusion on the applicability of this work to mRNA vaccines.

Despite other comments on this thread, the authors do provide evidence of genomic integration with FISH and chromosomal isolations. Their comments would be more productive detailing why these methods are unconvincing.

To nevertheless address their concerns, the manuscript would be enhanced with more scrutiny on the RNAseq methods in particular the ligation methods used to make these libraries to rule out Chimera formation in RNA-Seq. Perhaps RNase and DNase studies to prove the DNA integrations are not artifacts of library construction methods?

The integration events correlate nicely with Kim et al sgRNA expression patterns. This biological signal likely rules out random chimeric formations but might support higher copy number sgRNAs being more prone to chimeric formation in RNA-Seq libraries.

Calls to censors this are unscientific and political.

There is a typo on line 142 with SRAs instead of SARs.

On 2020-12-14 16:00:32, user Jim Woodgett wrote:

Since this preprint has already attracted the attention of the anti-vaccine crowd, it is important to note that the evidence shown for reverse transcription of SARS-CoV2 into the genome is a proof of principal that used some extraordinary and non-natural steps to achieve in isolated cells. This included specific over-expression of exogenous reverse transcriptase derived from HIV1 and LINE-1. The strength of the scientific evidence for direct integration is not entirely compelling as artifactual formation of chimeras between genomic fragments and the viral sequences during library generation isn't excluded. There are no data on whether there are common integration sites. Moreover, as the authors state in their discussion (page 7, line 146), even under these artificially forced conditions, "The retro-inserted SRAS-CoV-2 (sic) sequences are most likely sub-genomic fragments, as the integration junctions are mostly enriched at the N sequence (Fig. 1d-e), excluding the production of infectious virus." Indeed, their primary message of the implications of the results is that this may account for examples of PCR tests remaining positive long after infection. There's no direct evidence for this being a mechanism (rather than, for example, low level re-infection, trapping of viral debris, etc.).

Before coming to the conclusion that SARS-CoV2 can be incorporated into the genome under non-laboratory forced conditions, there needs to be evidence presented of such integration in cells derived from SARS-CoV2 infected patients with careful control of the possibility of contamination. Moreover, it really should be clarified that RNA based vaccines such as Pfizer/BioNTech and Moderna pose no risk in terms of genomic incorporation as they express, transiently, an RNA that encodes a single viral gene (Spike) with no associated genomic expression sequences. This is part of their intrinsic design for safety.

On 2020-12-14 15:49:23, user Dan Harkness wrote:

It's an intriguing observation. It would have been nice to see some longitudinal data. Is this a persistent or transient event? It seems like LINE-1 up-regulation is associated with "disease" via general genome instability perhaps mediated by its RT activity. This would make sense if these datasets came from productively infected individuals. What's missing is the follow up data e.g. 1-week, 4-week, 16-week post-infection, to demonstrate and quantify the persistence. The counter-hypothesis is that of the 100s of millions of cells that contributed to these single-snapshot sequencing libraries, there are some reads from a group of sick cells who are being actively cleared from the body via standard immune response. Is this particular group of cells the ones with the integrated COVID-19 sequences? Utilizing single-cell RNA and DNA approaches - in addition to follow-up time-points - would make a very elegant dataset. Cheers.

On 2020-12-14 15:47:40, user Jonathan Sebat wrote:

The evidence supporting the claims is not compelling and consists of (1) observation of chimeric transcripts of SARS-CoV-2 (a common artifact of RNA-Seq) and (2) correlation (not causation) of LINE element expression with infection. Weak IMO. The genomic sequences could be inferred from the chimeras and then confirmed. However there is no evidence of the actual genomic integration sites.

On 2020-12-14 15:23:10, user Ben wrote:

@reporters<br /> Please read the abstract (or even just some tweets from scientists) before you write your report. The title is overstated and walked back immediately in the abstract. Please be mindful of your influence.

On 2020-12-14 08:37:18, user Mick Watson wrote:

The evidence provided in the paper does not support the conclusions, and the most likely explanation is PCR artefacts. I highly recommend this preprint be taken down.

On 2020-12-13 23:49:19, user marius w wrote:

Can you show that the chimeric reads are with intron or intergenic sequences, and not only with exons?

On 2020-12-13 23:25:13, user Alex Crits-Christoph wrote:

Could the authors release a BAM or list of mapped reads (including read quality information and mapping information) of the chimeric sequences they show? Ideally a BAM filtered to just chimeric sequences would be good. This would help evaluate whether these sequencing reads represent real biological events.

On 2020-12-18 16:14:26, user Sam Smith wrote:

Here is a similar study. Also this study was in vitro and I don't know are they going to test the mouth washes/rinses in vivo. Perhaps they didn't publish at a very high-quality journal?<br /> https://www.ijeds.com/journ...<br /> Volume 9, Number 1, January-June 2020<br /> Comparative Analysis of Antiviral Efficacy of Four Different Mouthwashes against Severe Acute Respiratory Syndrome Coronavirus 2: An In Vitro Study

On 2020-11-29 15:29:35, user Sam Wheeler wrote:

I'm confused. Official Dentyl website only mentions the Dual, not Fresh as of 29th Nov 2020:

https://www.venture-life.co...

5 varieties! Which of the 5 was tested?<br /> At least one of the 5 contains double amount of fluoride.

Dentyl brand names and official websites outside UK? In Finland this is the official site, brand name is Apteq:<br /> https://apteq.fi/tuotteet/s...

You tested PVP-iodine 0.5%. In many countries it is sold as PVP-iodine 1.0%, could you please test that with humans when do the 12-week human study?

On 2020-12-18 15:49:32, user AG wrote:

Social selection can also produce consequence. The very fact of y-chromosome with high mortality rate during world war 2 can result a population which tend to produce more female offsprings since y-chromosome functions as unfit genes for survival in population went through major selection by wars. Russia has extraordinary high female offspring birth rate, which might be the historical selection against y carriers during ww2.

On 2020-12-18 15:38:26, user AG wrote:

Earlier studies indicated that older fathers also produced offsprings with longer telomeres. It is very likely that same mechanism affect both female and male parents to produce gametes at older age. My hypothesis is that gametes produced in older age parents are from the pool of primordial germ cells with longer telomeres than younger parents. Or at least sperm and oocytes from younger parents have higher proportion of shorter telomeres.

On 2020-12-18 10:07:47, user disqus_32giU6NoIA wrote:

Really nicely written and helpful paper. It would be good if you stated in the paper what PacBio technology you used. Is it correct in assuming you used CLR data, rather than CCS/HiFi?

On 2020-12-18 07:44:50, user herbette wrote:

Their results confirm those of this study: https://doi.org/10.1104/pp....

On 2020-12-17 20:05:29, user Colm Ryan wrote:

Somehow dropped the supplemental tables from submission - they're all available here: http://www.cancergd.org/sta...

On 2020-12-17 18:25:18, user Hanjoong Jo wrote:

A revised version with additional validation of the single cell RNAseq and ATACseq results is now published in Cell Reports. PMID: 33326796 DOI: 10.1016/j.celrep.2020.108491

On 2020-12-17 17:30:30, user Sui Huang wrote:

I noticed that the controls are just saline buffer, and not some empty lipid nanoparticle, which would have been a more stringent control (even better: LNP carrying an unrelated, or non-coding mRNA). It may be that the LNP alone exerts some non-specific adjuvant effect tat would have protected recipients if infected with the real virus? (A similar mechanism as postulated for BCG). Also in the human trial, the placebo is just saline solution. This also prevents us from knowing if the LNP has some biological (beneficial or adverse) effect... unless this has been shown before separately?

On 2020-12-17 16:53:38, user Raffi Aroian wrote:

This article is now published: https://aac.asm.org/content...

On 2020-12-17 16:02:34, user Lamya Ghenim wrote:

The text has been improved as well as some of the figures, and that a link will be forthcoming to the accepted version shortly. The paper has been accepted in Scientific reports (Nature).

On 2020-12-17 12:39:56, user Javi wrote:

Interesting approach to tackle antimicrobial resistance

On 2020-12-17 08:52:05, user Priyanka Kadam wrote:

Congratulations to Kartik and team for this very important paper. Great to see the new species of Krait named after Rom Whitaker :)

On 2020-12-17 08:04:10, user Joerg Schneider wrote:

Can you please point me to or post supplemental material referred to in the text? (supplemental Table 1, supplemental information 1, supplement information 2). Thank you.

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 2020-11-30 16:52:59, user Baptiste Gouyou wrote:

I am pleased to announce that this manuscript has been accepted for publication in Experimental Biology and Medicine.

On 2020-12-16 09:58:50, user Jean Marie Frachisse wrote:

SUPER , MSLs are spreading in the green world with FLYC1 of Venus flytrap

On 2020-12-16 06:06:23, user Boris E. wrote:

The github link is not working.

On 2020-12-16 01:00:27, user Ziqiao Yin wrote:

Hi, everyone! The revised version of this article has been published on Briefings in Bioinformatics, https://doi.org/10.1093/bib...

This version has not been linked to the published one, welcome to the website above the access the latest version!

On 2020-12-15 19:21:33, user johnLK wrote:

Surprised that there's not more mention of hippocampal maps. As I see it, the "contexts" long-described in the place-cell literature are essentially "models", making virtually all notions of how hippocampal place cells contribute to navigation, "model-based" theories. Pfiefer and Foster points that direction, but the literature is deeper than that.

On 2020-12-15 16:50:22, user Olivier Le Gall wrote:

Another form of SARSr-CoV previously epidemic in humans, SARS-CoV, is found in sweat glands and possibly excreted (DOI:10.1002/path.1560). More recently, this has also been suggested for SARS-CoV-2 itself (DOI:10.1038/s41421-020-00229-y). <br /> Therefore, maybe the affirmation that "Sweat does not appear to be a route of excretion for SARS-CoV-2 virus", relying on two articles not directly focused on this particular question, should be somewhat tuned down?

On 2020-12-15 13:49:25, user Matteo Vecellio wrote:

This mansucript has now been accepted in Arthritis and Rheumatology and will be published online soon. A link will be fortcoming

On 2020-12-15 08:28:37, user TN wrote:

I found a typo. Not perosin, peropsin.

On 2020-12-15 07:00:51, user zj wrote:

maybe SNV not SNP？

On 2020-12-15 04:51:49, user Jaelyn Rae wrote:

Does this suggest how Covid-19 might impact those with rare metabolic conditions, such as acute hepatic Porphyrias, or more specifically, Hereditary Coproporphyria? Would the metabolic disruption caused by Covid-19 cancel the overproduction of porphyrins in those with these rare genetic mutations?

On 2020-12-15 02:06:55, user richieju520 wrote:

First genome-centric quantitative metatranscriptomic analysis of WWTPs microbiome and key functional and antibiotic-resisant populations

On 2020-12-14 22:47:21, user Stephanie Gogarten wrote:

Really interesting paper and visualization approach! Grouping populations by current residence rather than ancestral origin makes a lot of sense, but I'm curious why you didn't group the GIH (Gujarati Indians in Houston) in the AMR super-population as well.

On 2020-12-14 18:41:06, user Daniel Schachtman wrote:

Be sure to check out and cite the published version of this paper as there were substantial changes/additions made during the review process.

On 2020-12-14 04:04:12, user Kevin McKernan wrote:

Folks,<br /> There is a >3Mb N50 Type II cannabis plant in NCBI with 97% BUSCO scores. <br /> The Male genome is in NCBI as well. <br /> Its been there for a 10 months. <br /> https://www.biorxiv.org/con...

On 2020-12-14 00:11:14, user Corinne Vacher wrote:

Justin Byrne Thank you very much for your constructive comments. Our article is now published in Molecular Ecology Resources: Barroso-Bergada et al. 2020. Microbial networks inferred from environmental DNA data for biomonitoring ecosystem change: strengths and<br /> pitfalls. Molecular Ecology Resources,online https://doi.org/10.1111/1755-0998.13302

On 2020-12-13 21:18:43, user Patrick Sexton wrote:

I have some questions where additional information would help me interpret the presented data:

The in vitro experiment is poorly described and does not appear to be robustly performed...<br /> What is the scale (axis labels)? Is this an accumulation assay (+IBMX)? <br /> Were the data converted to actual cAMP levels?<br /> How long is the antagonist pre-incubation? How long is the total stimulation with GIP?<br /> This looks like a single experiment with duplicate repeats - what is the experimental "n"?

Is there anything known of potential activities of the antagonists for other signaling/regulatory processes for the mGIPR (e.g. pERK, receptor internalisation)?

Caveat on the next comments - I am not a physiologist, so it might just be my ignorance: <br /> Fig. 1H. Why does the GIP2-A antagonist "increase" blood glucose in the IPGTT in fasted, lean mice? Isn't this experimental design supposed to bypass the endogenous GIP response?<br /> Fig. 1J. Why does exogenous mGIP stimulate insulin secretion in 4 h-fasted lean mice, prior to IP glucose bolus? Why is there no rise in insulin secretion with mGIP with high glucose from the IP bolus? Is the administered GIP below effective concentration by this time?

It would also be good to understand the metabolism and clearance of the antagonists used in the chronic studies.<br /> What is the mouse PK on the GIP1-A? On what basis is the claim made that the osmotic mini-pumps will maintain an effective antagonist dose? Where is the evidence that this occurs?

What is the mouse PK for the GIP2-A? How does this compare to the PK for liraglutide?

On 2020-12-13 21:07:59, user Nikhil M wrote:

Interesting work, Could you please tell me that this method work to model ssDNA structure which is not solved experimentally.? Also, the CMD doest shows mcuh folding of the structure, why?

On 2020-12-13 17:30:59, user Imre Kovesdi wrote:

The cassette design consists of 2 CMV promoters and 2 SV40<br /> poly A signals. This design has been shown<br /> before to result in an unstable virus configuration that recombines and eliminates<br /> one of the transgenes. Two different<br /> promoters (eg. CMV & RSV) and two different poly a sequences (eg SV40 &<br /> BGH) should have been used.

On 2020-12-13 11:22:04, user Nimrod Shteindel wrote:

Very nice work - you might find this method useful in future work - it allows kinetic high throughput quontification of adhesion in a standard microtiter plate using a commecially availeble plate fluorimeter<br /> https://link.springer.com/a...

On 2020-12-13 10:29:54, user Matt wrote:

1) Is there any potential to test your topology by adding WGS of Ust-Ishim (45kya) or Sunghir (36kya)?

These Whole Genome Sequence samples precede the estimated 23kya divergence date within your model, and therefore a test of whether subsequent samples form a clade to them would provide a test the validity of your model in which the later samples within your model are descended from a population which was unstructured until 23kya.

2) The PRS score for height is estimated from the paper 2015 Chan et al (inc. GIANT Consortium), which identifies variants in a population of "3,545 African Americans and 21,590 individuals of European ancestry". Could you include any explanation within your paper for your choice of this set of SNPs?

Significant concerns have emerged in more recent papers testing the validity of SNP sets identified under GIANT on European populations on the larger and more homogenous population of the UK Biobank (and within sibling sets within this set). See Berg 2019 - https://elifesciences.org/a.... This suggests that GIANT Consortium's SNP identification is confounded by European population stratification. A similar paper by Sohail 2019 - https://elifesciences.org/a... - explicitly identifies this effect as driving a previous estimated polygenic height score difference between Early Farmers and later populations of Steppe ancestry.

Would it be possible to extend this section to add estimation of PRS using SNPs identified under UK Biobank (WB subset / sibs), as in Berg above, and/or identified using Biobank Japan, as in Chen 2020 - https://www.sciencedirect.c...

On 2020-11-27 09:20:00, user Joachim I. Koch wrote:

Very interesting, as this accounts for a big proportion of Europeans' ancestry.

It's unclear why there is not included the Pinarbasi (ZBC) Anatolian HG that <br /> is 15 ky old from Feldmann et al (2019) in the discussion. As this was <br /> said to have been close to later Barcin individuals, this was probably a<br /> "mixed" HG from after the massive Iron Gates HG contribution.

The thesis where Loschbour and Bichon ("west1" and "west2") "branches" <br /> are placed at the LGM seems not applicable, as they derive basically <br /> 100% from the Villabruna cluster, that first showed up in the Northern <br /> Adriatic at abt 17 kybp

( https://www.biorxiv.org/con... )

, while there were HGs with GoyetQ2-like genetics in the Western<br /> Alps, Iberia, France and Western Germany (at least), see

https://www.cell.com/curren...

and

https://advances.sciencemag...

Also it's fully speculative to assume the HGs called "east" in this<br /> paper to originally have been in the Fertile Crescent. They could have <br /> been in Anatolia as well. Earlier finds lacks.

On 2020-12-12 14:26:48, user Specious Allegations wrote:

This cannot be applied in a rehabilitation context as in it cannot be applied to a dog who already has significant issues with behavior (ie the dogs in the exclusion criteria). So for anyone reading it, be aware that it *only* applies to a dog that has been raised correctly from birth with impeccable breeding history in terms of temperament. It doesn't apply when you've got a nearly grown up dog where you've made mistakes or the rescue you've brought home and they didnt tell you the truth about their aggression issues.

On 2020-12-12 12:26:33, user David Peters wrote:

Pterosaurs are not archosaurs (Peters 2000) and nest within a third clade of lepidosaurs (Peters 2007). A valid phylogeentic context is needed in these studies. Details and links here: https://pterosaurheresies.w...

On 2020-12-12 11:16:08, user M Hahn wrote:

Now published https://doi.org/10.1289/ehp...

On 2020-12-11 18:07:03, user Georgie Metters wrote:

Interesting stuff, looks like this measurement could be of use in my work!

On 2020-12-11 13:37:08, user george mcnamara wrote:

Zeiss does not sell a 1.55 NA objective lens (re: historially and current search at https://www.micro-shop.zeis... ). I hope the authors start proofreading their work. <br /> Since they have an LSM880,if it has AiryScan, they could acquire at "better than standard" confocal microscope resolution (approximately sqrt(2) better than 1.0 Airy unit pinhole size on standard confocal microscope - pinhole size not specifed in methods). The methods section does not specify the pixel size and Z step 0.75 um under-samples voxels. <br /> For those with confocal microscopes, I also note: (i) shorter wavelength fluorophore better resolution; Brilliant Violet 421 (BV421) fluorescence enables ~20% better resolution than 520 nm (Alexa Fluor 488, AausFP1 GFP, etc) if all settigns optimized, (ii) pinhole ~0.666 about ~10% better OR pinnhole ~0.333 ~15% better [Zeiss published nice application note loing ago on this]{photon throughput goes down by pi*r^2 so stable fluorophore best, or even better nanoparticle that reflects=backscatters light, and light path optimized for reflection confocal}, (iii) quantitative deconvolution is superior to unsharp masking (deconv ~10% better resolution), (iv) ALL can be combined: wavelength (0.9) * pinhole (0.85) * deconv (0.9) = 0.685, inverse: 1.45, about the same as Zeiss LSM880 AiryScan.

On 2020-12-11 17:58:16, user Steven Burden wrote:

Have the authors tested whether the mutated virus is infectious (e.g. in cultured cells), and if so whether infectivity is attenuated? Have the authors tested whether sera from vaccinated individuals carry antibodies that recognize the mutated virus and block infection?

On 2020-12-11 17:34:27, user kfos wrote:

Just when I think I have a hold on one part of single-cell RNAseq analysis... Another cool new papers comes out... Overwhelming!

On 2020-12-11 02:03:12, user Rahul Satija wrote:

Thanks for posting this! We’ve written a brief response that compares the results of the sctransform model with the modifications proposed here (‘offset model’) at https://satijalab.org/pdf/s...

On 2020-12-11 16:49:31, user Roeland Nusse wrote:

Comments from Bruce Wang, Ludan Zhao, Matt Fish, Catriona Logan, Roel Nusse

In this manuscript, the authors raise a number of issues related to our publication from 2015 [1]. Most importantly, they report varying degrees of labeling of Axin2 expressing cells in the liver as well as dominant phenotypes in mice in which one or both Axin2 alleles are disrupted by insertion of the CreERT2 cassette.

May et al. report that in their hands, Axin2-CreERT2 homozygous mice could not be generated at all and that Axin2-CreERT2 heterozygous mice are born at sub-Mendelian ratios. In various labs, including our own, mice that are homozygous mutant for Axin2 have been used and characterized. The first such mice were generated by the Birchmeier lab [2], which have a LacZ insert at the exact same nucleotide position where we later inserted the CreERT2 cassette [3]. Both Axin2-CreERT2 and Axin2-LacZ, as well as other 5’ Axin2 knock-in strains, are considered to be null alleles of Axin2. Nevertheless, homozygous Axin2-LacZ animals are viable and fertile with relatively minor phenotypes reported in the literature (including a shortened head, abnormal eye morphology and enhanced osteoblast differentiation; see http://www.informatics.jax....:gUBZYT9emZ6SC9C7gbkwv4OS-ug "http://www.informatics.jax.org/allele/MGI:3579503)").

In our lab, all records from previous personnel spanning 2012-2016 have demonstrated that Axin2-CreERT2 homozygotes could be obtained despite mild phenotypes, and these animals were generated at expected frequencies. Axin2-CreERT2 heterozygotes bred to wild type mice also gave progeny at expected Mendelian ratios. Current crosses of Axin2-heterozygotes to wild-type continue to give expected ratios.

That being said, it is conceivable that rederivation and backcrossing of Axin2-CreERT2 animals to different backgrounds and their maintenance in different facilities might change the penetrance of Axin2 loss-of-function phenotypes via as of yet unknown modifier loci or other, non-genetic variables. This was recently described by the van Amerongen lab [4], which reported non-Mendelian offspring ratios from Axin2-CreERT2 mice (two rederivations removed from the line at our facility and three rederivations removed from the mice originally described in [3] or the mice deposited at Jackson labs) in heterozygous backcrosses to C57Bl/6 but not FVB/N (see Supplementary Table 2 in [4]). In August of 2017, we added this information to the description of the Axin2-CreERT2 mouse line on the Jackson Laboratory website (https://www.jax.org/strain/.... These results are in line with what is seen by May et al. and they underscore the importance of keeping track of the strain background and on using wildtype littermate controls for experiments.

With respect to the differences in the subset of cells that is labelled and the degree of labeling as reported by May et al., in our study we used both low (1 x 4mg tamoxifen/25gm body weight) and high (5 x 4mg tamoxifen/25gm body weight) tamoxifen dosing aimed at low and higher frequencies of labelling. With both doses we continued to see long-term expansion of labeled cells more than 300 days after initial tamoxifen dosing. Unlike May, with the high dose labeling we saw no displacement of pericentral labeled cells by unlabeled cells and this was the dosing used to quantify expansion of labeled cells. We interpret this as evidence that the Axin2 labeled cells in zone 3 expand, more so than other cells, and that lingering tamoxifen (which should be long gone from the system) was not the cause of the increased labeling over time.

Moreover, in our original publication [1] we wondered whether Axin2 heterozygosity affected our results but found no evidence that this was the case. First, we measured cell cycle parameters by EdU incorporation in heterozygous Axin2-CreERT2 mice compared to wild type and found no difference in proliferation rate with EdU labeling for 7 days. While we did not discriminate between male and female animals in Wang et al. [1], the results by May et al. suggest that this could be important. This is also part of a larger debate and movement towards appreciating sex as a biological variable. Particularly in the case of stem cells, a difference between males and females has been reported earlier [5], and it is tempting to speculate that this might actually be directly due to a difference in Wnt/beta-catenin pathway activity, as the results by May et al. would seem to suggest.

In addition to our lineage tracing experiments with Axin2-CreERT2, we also used the Axin2-rtTA transgenic mouse in which rtTA expression is driven by an Axin2 promoter fragment and where the wildtype Axin2 gene locus is kept intact. Using this model, we found a similar pattern of initial labeling of pericentral hepatocytes followed by expansion of labeled cells as with Axin2-CreERT2 mice, further supporting the importance of this cell population in particular, and arguing against reduced gene dosage of Axin2 as the reason for the observed proliferation of zone 3 cells and their progeny. However, we acknowledge that these were relatively short-term experiments.

Cre/lox mediated lineage tracing is a powerful method, but there are challenges and limitations in its design and interpretation [6, 7] which could affect our own as well as May et al.’s experiments. We emphasize that apart from our data, independent DNA label dilution experiments performed almost twenty years ago also indicate that the pericentral area (or zone 3) has a higher rate of DNA replication compared to other zones [8]. In the adult liver, both Wnt signaling and expression of the Wnt target gene Tbx3, known to be essential for embryonic hepatocyte proliferation [9, 10], continue to be active in pericentral cells [11]. Moreover, in adult liver tissue, pericentral cells express relatively high levels of c-Myc and CyclinD, hallmarks of cells that are active in the cell cycle [11]. In experimental models of mouse hepatocellular carcinomas, the cells of origin of the tumors are located pericentrally [12, 13]. We therefore believe our findings are consistent with the important role of Wnt/beta-catenin signaling in postnatal growth of the liver [14] and for the repair of liver tissue after chemical injury [15, 16]. Whether pericentral cells in adult livers are quiescent or divide and at which rate will depend on the specific context the cells are in and this will likely be affected by uncontrolled variables and environmental parameters.

References<br /> 1. Wang, B., et al., Self-renewing diploid Axin2(+) cells fuel homeostatic renewal of the liver. Nature, 2015. 524(7564): p. 180-5.<br /> 2. Lustig, B., et al., Negative Feedback Loop of Wnt Signaling through Upregulation of Conductin/Axin2 in Colorectal and Liver Tumors. Molecular and Cellular Biology, 2002. 22(4): p. 1184-1193.<br /> 3. van Amerongen, R., A.N. Bowman, and R. Nusse, Developmental stage and time dictate the fate of Wnt/beta-catenin-responsive stem cells in the mammary gland. Cell Stem Cell, 2012. 11(3): p. 387-400.<br /> 4. van de Moosdijk, A.A.A., et al., A novel Axin2 knock-in mouse model for visualization and lineage tracing of WNT/CTNNB1 responsive cells. Genesis, 2020. 58(9): p. e23387.<br /> 5. Nakada, D., et al., Oestrogen increases haematopoietic stem-cell self-renewal in females and during pregnancy. Nature, 2014. 505(7484): p. 555-8.<br /> 6. Becher, B., A. Waisman, and L.F. Lu, Conditional Gene-Targeting in Mice: Problems and Solutions. Immunity, 2018. 48(5): p. 835-836.<br /> 7. Kretzschmar, K. and F.M. Watt, Lineage Tracing. Cell, 2012. 148(1-2): p. 33-45.<br /> 8. Magami, Y., et al., Cell proliferation and renewal of normal hepatocytes and bile duct cells in adult mouse liver. Liver, 2002. 22(5): p. 419-25.<br /> 9. Ludtke, T.H., et al., Tbx3 promotes liver bud expansion during mouse development by suppression of cholangiocyte differentiation. Hepatology, 2009. 49(3): p. 969-78.<br /> 10. Suzuki, A., et al., Tbx3 controls the fate of hepatic progenitor cells in liver development by suppressing p19ARF expression. Development, 2008. 135(9): p. 1589-95.<br /> 11. Bahar Halpern, K., et al., Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature, 2017. 542(7641): p. 352-356.<br /> 12. Nicholes, K., et al., A mouse model of hepatocellular carcinoma: ectopic expression of fibroblast growth factor 19 in skeletal muscle of transgenic mice. Am J Pathol, 2002. 160(6): p. 2295-307.<br /> 13. Wang, R., et al., Activation of the Met receptor by cell attachment induces and sustains hepatocellular carcinomas in transgenic mice. J Cell Biol, 2001. 153(5): p. 1023-34.<br /> 14. Apte, U., et al., beta-Catenin is critical for early postnatal liver growth. Am J Physiol Gastrointest Liver Physiol, 2007. 292(6): p. G1578-85.<br /> 15. Walesky, C.M., et al., Functional compensation precedes recovery of tissue mass following acute liver injury. Nat Commun, 2020. 11(1): p. 5785.<br /> 16. Zhao, L., et al., Tissue Repair in the Mouse Liver Following Acute Carbon Tetrachloride Depends on Injury-Induced Wnt/beta-Catenin Signaling. Hepatology, 2019. 69(6): p. 2623-2635

On 2020-12-11 16:06:50, user José L Medina-Franco wrote:

Very nice work! Two previous diversity analysis of fungal products and metabolites have been published in Chemoinformatic expedition of the chemical space of fungal products FUTURE MEDICINAL CHEMISTRY, 2016 8, 1399-1412. http://dx.doi.org/10.4155/f... and Scaffold Diversity of Fungal Metabolites FRONTIERS IN PHARMACOLOGY, 2017, 8, 180. http://dx.doi.org/10.3389/f...

On 2020-12-11 08:54:13, user Mauro Maver wrote:

The previous reported issue:

The on-line resolution of Figure 1C was sub-optimal: we have now provided the repository with a newer version of it.

is now fixed!

On 2020-12-09 10:11:23, user Davide Bulgarelli wrote:

Hi-there seems to be an issue with Fig 1C (the heatmap) when opened in a browser-please do download the doc and visualise it with a pdf reader for a better resolution.

@Stramon1um and I are working to fix it-apologies for any inconvenience this may cause!

On 2020-12-11 02:24:54, user theasdgamer wrote:

This paper is very much needed to put to rest the asymptomatic covid superspreader myth.

On 2020-12-11 02:21:34, user Jim Edmonds wrote:

How long can you use the peptide without side effects?

On 2020-12-06 01:12:37, user James Eichenbaum wrote:

Congratulations on this great work! I am intrigued to see how you continue the study. I especially appreciate how approachable the writing and data presentation is to a general audience. What you propose could have a great impact in prophylactic treatment against SARS-2.

I believe you can further improve the clarity of the results section by including qualitative data, namely some images demonstrating the transition threshold for cytopathic effect used for TCID50 and viral neutralization. Additional quantitative analysis of cytopathic cell signals could make this even more convincing. As it stands, these sections are vague and rely on the reader to make assumptions about cytopathic effect or have prior knowledge of the subject.

You could provide statistical methods for more sections, similarly to how you present it in figure 1. Figure 4 and S4 would be more clear if significance/non-significance was explicitly stated.

I would be interested to see a further study in which the vulnerable population, which received mock doses, were continually separated. The abstract states that the mock group were 100% infected, but does not clarify that this was accomplished in the designated transmission period as one might infer from Figure 3.

Further investigation of the leukocytes and antibodies would be helpful to demonstrate the compound's prophylactic effect. Antibody presence is only indirectly demonstrated, so you could potentially use ELISA for a direct assay. Immune cell markers and inflammation signals could distinguish the mock treatment group from the compound-treated group.

Excited to see your future work!

On 2020-12-03 07:49:55, user Natalie Noble wrote:

Thank you this was an enjoyable paper to read! The implications of it are exciting. There were a few minor suggestions for the paper. The paper could be structured better, as it stands if feels unfinished. Separating your information into sections (introduction, results, discussion, etc) would help organize the paper, making it easier to understand and navigate. There were only two sentences discussing figure 4, adding to the unfinished feel of the paper (Figure 4 could use more analysis or perhaps discuss the implications of its results). The basis of the paper is that this peptide prevents infection of SARS-CoV-2 into the cell by disrupting the spike protein S, however the mechanism is unclear. It would be great to include a figure detailing the molecular mechanism of inhibition between the peptide and S, and the host cell. I don't understand why the ferrets were given the peptide in DMSO instead of the sucrose. Not only is the sucrose relevant to human application (since humans can’t have DMSO), but it looked like in the sucrose the peptide had a higher percentage inhibition of infection at a lower peptide concentration than in the DMSO (figure 2B). It just seems more effective. The implication of this work is intriguing. As potential vaccines are in the works for the general population, maybe these findings would be applicable to protect at risk populations that are unable to receive a vaccine.

On 2020-12-02 22:44:20, user Emma Leshan wrote:

Thank you for this wonderful work! This seems very promising.

In figure 1D, it seems that some of the data points don't have error bars, and it would be good to be consistent with the inclusion of error bars in all data points. It would also be nice to see a ribbon diagram showing how the spike protein and HRC peptides interact if possible.

In figure 2A, it would be good to label the x-axis as well so it is more clear that you are comparing different peptide concentrations.

I also wondered why you used DMSO in the buffer given to the ferrets, when using sucrose would be more relevant for translational potential in humans.

It would also be interesting to discuss the relevance of this technology now that vaccines are on the horizon. It would likely be applicable for use in cancer patients, babies, the elderly, etc.

On 2020-12-10 23:41:36, user Kathleen Lyons wrote:

This article has been published in PLOS ONE<br /> https://doi.org/10.1371/jou...

On 2020-12-10 22:44:51, user Isabel wrote:

I enjoyed reading this paper and learning about a very promising combination treatment to reduce pancreatic cancer in mice. I was very impressed with the evidence presented in this paper and I thought it was great that it is understandable for people with many different scientific backgrounds. After looking at this paper, I noticed that a slightly different version was published later. I think that it was a good idea to not include the PD-L1 data in the published version of this paper because it might be confusing for some readers and does not contribute to the hypothesis of this paper. However, I am interested in this data and I wonder if this is being looked into further, and if it could possibly be the subject of a new paper following this one. I thought the way you presented the data in figure 1 was very clear, and it allowed the readers to rule out any bias or statistical errors by showing them the raw data on the graphs. I also really enjoyed looking at the tumor cross-sections in figure 3 and being able to see the tumors at different magnifications made the evidence even more convincing. Lastly, I thought the potential mechanism of NAM+GEM figure was accurate and made sense, but the way it was presented was a little confusing. A simpler flowchart with more descriptions and less arrows might be helpful. Overall, I thought this paper was very clear, had an excellent introduction, and was very convincing. I am excited to see the therapeutic application of these results.

On 2020-12-09 16:47:00, user Sausan wrote:

I enjoyed the ease with which I read this paper as the writing and figures were presented in an easy-to-understand format. The resolution of figures 2 and 3 are good allowing me to better interpret the data presented. Another component that I appreciated is that for figure 3 slice sections from the same sample were used for the trichrome staining and the immunohistochemistry staining which maintained consistency between the experiments. While analyzing the figures, the labeling of the individual panels within each figure was a little confusing as we read from left-to-right but the labeling made it so to read from right-to-left. <br /> I did notice that the published version has the peritoneal panc-02 model that was treated with anti PD-L1 in figure 1 and the schematic in figure 5 excluded. All in all, it was an interesting and informative paper to read.

On 2020-12-05 23:18:07, user Maria wrote:

Thank you for your work on this paper! I found it enjoyable, and its language and presentation is accessible to a variety of readers. For Figure 1, I am curious as to why the published version does not include the PD-L1 results or the Peritoneal Panc-02 model data. Additionally, labeling all the figures on the right of the images rather than the left made it a bit difficult for me to keep track of which figure was which. Figure 2e and 2i had very good resolution, which made the images easy to interpret. I noticed that in Figure 3, similar slice sections were used for Collagen I, αSMA, and CD31 staining. This provided a lot of consistency in the data, which I appreciated. However, one way I thought the consistency in these images could be improved is by staining the same area of each slice when looking at Collagen I, αSMA, and CD31. In Figure 3j, the spread for the Saline and NAM groups was large, which made the overall results a bit less convincing. For Figure 4b, it is difficult to see the staining clearly. I assume the image is zoomed out to demonstrate what is meant by “peritumoral”, which is helpful. I think the best way to present the data would be to replace the big image with a zoomed in version that allows the readers to analyze the staining, and to place the current zoomed out photo in the upper right hand corner of the image.

On 2020-12-10 21:21:34, user ToGo wrote:

Interesting, since Prevotella was found to be descreased in H1N1 infected pneumoniae patients (https://www.clinicalmicrobi..., virally infected respiratory tract (https://link.springer.com/a... and in pneumonia patients (https://www.nature.com/arti...

On 2020-12-10 20:13:54, user Eric A Brenner wrote:

What does Figure 3 look like when including smaller values of Nind? Or when including sum-based pseudobulking rather than mean-based?

On 2020-12-10 15:13:33, user Susana Vazquez wrote:

An improved version of thispreprint has been accepted for publication and a link will be forthcoming.

On 2020-12-10 09:45:18, user Sam Andre wrote:

Since there is a lot of debate about whether clathrin plaques/ flat lattices are artefacts of interactions with the coverslip, it would be interesting to see the dynamic lifetimes of plaque vs. pit assembly, and whether they are, at least in part, specific to coverslip facing surfaces. The authors have previously used diSPIMs to observe clathrin and EGFRs (10.1016/j.bpj.2018.11.545). Do they observe distinct modes of clathrin assembly in both coverslip facing and dorsal free surface of the cell? That would be crucial to absolve the clathrin flat lattices of being artefacts. They may be specific to cell-cell adhesion, dependent on alternative splicing. That concept again, needs further experimentation and is probably best done in live organisms as demonstrated by Kirchhausen.

On 2020-12-09 21:06:58, user Joy wrote:

Hello - I am a layperson, not a scientist. I've had to learn a lot about my alpha-gal allergy, since medical providers are largely not up to speed about how to help extremely reactive persons like myself avoid exposure. What does this finding of the negative correlation between alpha-gal IgE and COVID-19 severity mean for people who test positive for alpha-gal IgE? The article suggests that the IgE in COVID-19 patients is likely a result of the infection, not a cause of asymptomatic or milder symptoms. Any thoughts?

On 2020-12-09 19:33:42, user kirienkolab wrote:

My lab has published a significant number of papers on the role of pyoverdine in C. elegans virulence (PMIDs: 23601103, 25624506, 27579370, 28662060, 28928729, 29532717, 30687293, 31551982, and 32962519). I am surprised to see that you spend half a paragraph discussing this siderophore and this model organism and discuss fast killing and red death, but completely neglected our body of work on it.

On 2020-12-09 00:50:44, user Thomas Weitzel wrote:

The peer-reviewed article is now available: doi 10.1016/j.tmaid.2020.101942

On 2020-12-08 17:27:11, user Community builder wrote:

It would be great to see the authors acknowledge all the work that the Folding@home community has done on spike opening.

On 2020-12-08 17:20:48, user Yossi Farjoun wrote:

Now this is published in Nature Communications Biology: https://rdcu.be/cbRRi

On 2020-12-08 16:06:32, user uzenzo wrote:

Can it cause syncytia formation? Have the vaccines been tested for possible organ-level dysfunction due to Spike?

On 2020-12-08 14:48:43, user Follicle Thought.com wrote:

Dr. Paus seems to have his hand in most of the important hair research going on. I wonder if there is an early stage therapy in the works for this. The grey hair cure market has been quiet for a long time.

On 2020-12-08 06:04:22, user debernardis wrote:

I would like to have greater detail on the preparation of the CS extract for the in-vitro experiment. Was it obtained in the lab, and which was the technique? Or was it a commercial tobacco condensate extract?<br /> Thanks.

On 2020-12-08 00:25:17, user Andrew Watkins wrote:

If you want to take a look at some additional FARFAR2 model sets for these stem-loops and more, by the way, check our our preprint from April: https://www.biorxiv.org/con...

We do agree that SL6 looks like it has the most plausible binding pocket!

On 2020-12-07 18:20:29, user Steffen Thiel wrote:

To the authors

You state that AAT is a better inhibitor af infection than, e.g. A2M. This is not what you show in the figures. You show that AAT and A2M give IC50s of 14.47µg/mL and 54.20µg/mL, respectively, i.e. a 3.7 difference on a weight basis. Remember, the mol weight of ATT is 3.5 times smaller than A2M - thus you have more or less excatly the same potency of A2M as by ATT on a molar basis - which is what counts.

On 2020-12-07 14:13:02, user ravi wrote:

So similar to immune paralysis found in septic shock patients; what such patients need will be immune activation

On 2020-12-05 14:54:19, user feng qin wrote:

Thanks for share your work on the prostate cancer, Could I ask how do we get the Supplemental Table?

On 2020-12-05 11:19:41, user Soumendranath Bhakat wrote:

Dear Authors,

The occurrence of Tyr inhibited conformation (H-bond interaction between Tyr and Asp) has been predicted by Bhakat & Söderhjelm (https://www.biorxiv.org/con.... Please cite the original article. You reinvented a measure of flap opening which takes the distance between Tyr-OH and Asp-CG but it can be deceptive as it depends on the torsional degrees of freedom associated with Tyr side-chain. A more stable measure is to take CA distance between flap tip residue and catalytic aspartic acids which has been discussed in the following articles (similar distance metrics have been proposed by Caflisch and others):<br /> 1. https://www.biorxiv.org/con...<br /> 2. https://pubs.rsc.org/en/con...

Could you please discuss how your distance metrics is better compared to the one mentioned in those articles with proper citation to them. Finally, Bhakat & Söderhjelm proposed a generalised theory of flap dynamics in pepsin-like aspartic proteases which was completely ignored in the discussion section of this pre-print. I think most of the outcomes of this paper confirmed their hypothesis. A proper discussion surrounding that will be a good take-away for the community.

Improvement:

Maybe a free energy plot showing distance between Tyr-Trp and Tyr-Asp H-bond interaction during simulation.

Best regards,<br /> Soumendranath Bhakat

On 2020-12-05 10:35:36, user Michael Cook wrote:

I belive the first statement is incorrect. The flagellum in not helical. In the rest state it is straight. But driven asymetrically from offcenter through the 'hook' and when the drive rotates, the hook sweeps the flagellum in an arc, and in a viscousl liquid (nanoscale water is viscous) the flagellum takes on a helical path driving the microbe forward. Michael Cook

On 2020-12-05 09:35:54, user Mamta Rani wrote:

Interesting and complex article, evolution of complex multicellularity in fungi, while the several morphogenesis aspects suggests convergent evolution, the fruiting body development process conserved genetic mechanisms in different lineages indicating single origin

On 2020-12-04 18:48:54, user Reza and Nasim Bekheirnia wrote:

Very interesting work. Congratulations! I was wondering if FACS is a required step? It seems that scRNA-seq could be done w/o FACS?

On 2020-12-04 18:31:34, user Jordan Berg wrote:

Metaboverse v0.3.1b is live!

https://github.com/Metabove...

• Improved direct-CHEBI mapping stability
• Other minor bugs fixed

See https://metaboverse.readthe... for a full list of updates.

And thank you to all who have helped track down bugs and suggested new features! More to come!

On 2020-12-04 17:07:14, user phreak123 wrote:

Fig. 1a was created using BioRender.com (e.g. diseased lung image) but not cited properly. This sheds a bad light on the authors.

https://help.biorender.com/...

On 2020-12-04 13:29:21, user Umakanta Swain wrote:

Our preprint on multilayer regulation of translesion DNA synthesis (TLS) by TENT4A. TENT4A poly(A) polymerase regulates translesion DNA synthesis and is mutated in endometrial cancer https://t.co/fx4fqoXwLs #bioRxiv. Comments and suggestions are welcome.

On 2020-12-04 04:56:07, user Greg wrote:

Beautiful electron microscopy of those mitochondria.

On 2020-12-04 01:24:20, user jeremy jewell wrote:

Cool paper, Marta! You probably don't remember me, but we met at an ASPB meeting. I was wondering if you had seen our recent paper that shows CAMTA3 is involved in the transcriptional response to the DAMP extracellular ATP:<br /> http://www.plantphysiol.org...

(I admit, I'm scrounging for a cite, if you have room.)

On 2020-12-03 18:00:45, user Casey Greene wrote:

It was interesting to see this style of regularization in autoencoders. Would it be possible for the authors to compare the method that they describe with PLIER ( https://pubmed.ncbi.nlm.nih... )?

On 2020-12-03 16:34:54, user Alexander wrote:

Dear authors,

We carefully read this article that could help us to control efficiently the Newcastle and Infectious Laryngotracheitis diseases, but we have some concerns:

-In the method section (treatment section) the authors said "At 4 days after treatment, 4 hens were randomly selected from the row that received ivermectin, and 4 hens from the control group row from the hen house affected only with NDV". What was the purpose to select those animals? What were the reasons to think that 4 chickens were a representative sample from 125 hens?

-As the ELISA test and molecular testing are described in the methods section, we think that is necessary and relevant to show the data obtained with these techniques. Otherwise, what is the sense of describing these techniques in the methodology? The other relevant point is that the study does not include the results of the 10 000 laying hens as the authors mention in the methods section.

-In the results section the authors mentioned "It was notable to observe that there were no clinical signs of avian infectious laryngotracheitis (Figure 1B). In contrast, the untreated group exhibited conjunctivitis (Figure 1A) and dyspnea". However, in the Methods section (treatment section) the authors said that only the animals infected with NDV have a control group (no treatment), and all the animals infected with NDV and ILTV received the multivitamin supplement and Ivermectin (indicating that these animals didn´t have a control group). So, how reliable can you compare the clinical signs between 2 groups that were infected with different viruses? If Figure 1 represents the clinical signs of the animal before and after the treatment, then the authors cannot say the chicken of the Fig1A is part of the untreated group as mentioned in the text. Because that would mean that the authors have a control group of the animals infected with NDV and ILTV and that is not the case.

-Subsequently, the authors mention “At 4 days after treatment, the ivermectin treated birds, showed clinically healthy birds with clean eyes compared to untreated birds, and no evidence of viral DNA was found in the molecular test” As only the group infected with NDV have a control group we assume that the authors refer to these animals. Is it correct? It is important to mention in the text if the viral DNA was detected in the control group and in the animals that only received the multivitamin doses. It is also important to mention the number of chickens that were used to evaluate the presence of DNA.

-In the article, the authors said, "In addition, the birds treated with ivermectin showed visibly greater mobility and vivacity". Watching the video is really difficult to appreciate if the animals treated with ivermectin (and multivitamins) have more mobility compared to the untreated birds. As the authors mention a control group, we also assume that the authors referred to the animals infected only with NDV.

-In the result section the authors evaluated egg production. The authors said, “Regarding egg production, after 3 days of treatment, birds that received ivermectin showed a slightly higher percentage of egg laying (66.01%) compared to birds that did not receive ivermectin (61.90%) (P= 0.15, Proportion test)”. As a control group exists, we assume that the authors evaluated the egg production in animals infected only with NDV. So, the affirmation of the authors is just valid to the animals infected only with NDV.

-In the discussion section, the authors said, "a recovery of egg production was shown in treated birds in a shorter time than usual (2 weeks versus 8 weeks that usually takes recovery)". However, it is well known that depending on the virus strain the recovery process could be more or less than 8 weeks. Considering this information and that the authors didn´t have a control group is difficult to support the authors’ asseveration. Could the authors send us a bibliography reference to support their asseveration?

Based on the information described above and the data presented by the authors we think that the title is not valid to this work. We would be grateful if the authors can provide more information about their research that could have a positive impact on the veterinary field.

Thank you for your attention and we hope that this information could be helpful to your research.

On 2020-12-03 15:52:11, user debernardis wrote:

Very interesting. My suggestion is to test also the citrullinated analogue of LL-37 which is associated with tobacco smoking (https://pubmed.ncbi.nlm.nih...<br /> Several reports show that active smokers are less frequent than expected among hospitalized Covid-19 patients, indicating some kind of protection. Maybe citrullinated LL-37 could have a higher binding to the Spike protein?

On 2020-12-03 07:01:32, user Gareth J Sullivan wrote:

Here is the latest liver organoid research from the lab on BioXriv

On 2020-12-02 21:30:36, user Alexis Rohou wrote:

I was asked by a journal to review this manuscript. Below is my review

***

This manuscript explores the observation that Thon rings visible in amplitude spectra of micrographs decrease in amplitude as a function of spatial frequency (distance from the origin in F space) and that this decrease is more pronounced in micrographs collected with larger objective lens defocus.

Since the height of Thon rings from image of test specimens can be taken as an estimator of recoverable signal-to-noise ratio in experimental data recorded under identical conditions, this has led many practitioners to prefer to collect data as close to focus as possible. The dominant assumption in the field has been that the observed defocus-dependent contrast attenuation is due to imperfect spatial coherence of the electron source, but this manuscript provides compelling evidence that another phenomenon is responsible.

The authors note that a significant amount of signal is delocalized beyond the edges of the field of view and so cannot be recovered. Further, the authors point out that single-sideband (SSB) signal in the collected image (be it from features in the field of view but near its edges, or delocalized from features not present in the field of view), while it contributes power to the image, does not contribute to Thon rings because its amplitude is not modulated by the CTF.

I find the authors' evidence in support of this compelling:<br /> - experimentally, the nodes (local minima) between Thon rings to not reach the "noise floor" as would be predicted if all contrast in the image arose from phase contrast attenuated by a spatial-coherence envelope. Computationally, the authors show that this "Thon ring floor" is raised under conditions where more of the recorded image power consists of SSB signal (increased defocus or small field of view)<br /> - theory predicts that, at the fluencies normally used in cryoEM, the spatial coherence of the illumination supplied by modern eletron sources is such that one would not expect significant defocus-dependent attenuation effects<br /> - most compelling, the relative intensity of Thon rings in actual images is well predicted by the fraction of image features for which signal for both side bands is recorded (Fig 4)

My only significant reservation with this manuscript is about the "messaging", and specifically this sentence of the abstract: "The principal conclusion is that much higher values of defocus can be used than is currently thought to be possible". <br /> While the authors have convinced me that the negative effects of defocus were misunderstood and overstated, their claim that higher defocus could be used with no ill effect should be qualified (preferably in the abstract, and in the main text) to make it clear that they are only referring to the imaging part of the experiment, and not the image processing part of experiments, where high defocus values would force users of most packages to use very large box sizes at various parts of the process creating unusually large computational burdens, and/or other problems may occur. If the authors want to keep the claim as is, they should add experimental results that support it, e.g. high-resolution apoferritin reconstructions obtained from both low and high defocus datasets, along with characterization of the mean SSNR, ResLog plot, or similar, in each case. Probably better to keep the paper more or less as is and just qualify this claim, in my opinion.

Beyond that, I have more minor suggestions / questions.

(1) Abstract: I'd encourage the authors to consider removing the sentence remove about correcting mag distortion ("We also show (...) many orientation") - if I understood correctly, this becomes very significantly only at very large defocus, and only if averaging spectra to 1D curve before fitting. For these reasons, I think this is a rather minor point of the paper. In the context of the abstract, I think this aside distracts from the main message

(2) Abstract: "and Ewald sphere correction". Perhaps I missed it, but I don't recall reading in the main text an explanation of why defocus should allow for better Ewald sphere correction, or a demonstration that this is the case. I suggest removing this from the abstract, or adding text explaining this, or a citation to a reference that does (on that note, after a quick re-read of Russo & Henderson 2018, I also don't see an obvious demonstration there that higher defocus yields better Ewald sphere curvature correction, but I'd happily stand corrected).

(3) Page 3: "This is because compensating information, which unfortunately is of no use, may enter the image from features that are outside the field of view." On first read, this sentence confused me - I think because the phrase "compensating information" threw me off. How about something like "This is because unrelated single-side-band signal delocalized from features outside the field of view may enter the image."?

(4) Page 4: "Since delocalized (...) high defocus values to record images (Russo and Henderson 2018b)". I think readers who like me are not well versed in the optics and maths of SSB imaging, this statement is difficult to understand. Could it be explained a little further / clarified? To spell out my confusion: why does the feasibility of recovering SSB information even the absence of the Friedel mate mean that it should be advantageous to operate at higher defocus?

(5) Same paragraph ("We note that information in (...) become greatly reduced"). This whole paragraph argues (I think) that collecting highly-defocus images is OK, yet wasn't one of the points of Downing & Glaeser (2008), cited in this paragraph, that the larger the defocus the lower the more CTF correction schemes or Wiener filters fail at retrieving all of the information (due to the "twin image" problem). My apologies If I'm mis-understanding - if that's the case perhaps other readers will also need a bit more hand-holding through this paragraph.

I loved all the detail poured into M&M, so I suggest specifying further:<br /> (6) Page 5: "annular zones of 1 reciprocal-space pixel" - how was interpolation done here? Nearest neighbor?<br /> (7) Page 5: "floated" - I assume this means adding a constant so that the average value is zero?<br /> (8) Page 6: "Smooth curve" - fix capitalization. Also, what kind of smooth curve?

Results:<br /> (9) Page 6: "The integrated power at 2.35 Å" - measured how? In real space in the white box?<br /> (10) Page 6: "(67% of intensity)" - 67% of which intensity?<br /> (11) Page 6: "~0.23 nm" - to guide the eye, please add a second x axis in figure 2, or replace the existing one, so that we can look for the 0.23 nm feature.

(12) Page 7: "The mean value of this noise spectrum can be regarded as the "zero baseline" for the power spectra of images recorded with a specimen". This noise floor will rise as a function of the number of electrons incident upon the detector. The choice of illumination condition when collecting "no-object"/"beam-only" images for these experiments is therefore important. I assume that the authors used the same illumination conditions as had been used in the actual experiment with a specimen. Is this correct? Either way, could the authors briefly mention somewhere what illumination conditions were used for this? <br /> -- I expect that using the same illumination condition would lead to an overestimate of the height of the noise floor. Indeed, during experiments with specimens, some fraction of electrons will be lost to apertures, leading to an overall decrease in the average number of eletrons reaching the detector. One may thus expect the actual noise floor in "with-specimen" experiments to be even lower, perhaps making the authors' point even more striking.

Discussion:<br /> (13) Page 7: "did not prevent images at 8 um defocus from being recoded at a resolution of 1.44 Å". Is this shown somewhere? Fig 1C shows 1.3 um defocus, not 8 um.

(14) Figure 2a: could the X axis be re-labelled, or also labeled with spatial frequency in nm-1 or Å-1 - this would help locate the 3.5 Å bump mentioned in the discussion

(15) Suppl Figs 4 and 5: here also, having a second X axis, or a second set of labels with spatial frequencies would be helpful.

(16) Figures S4 and S5: The lower bound of the Thon rings is "raised" with increased defocus, as predicted by the increase in SSB signal, but why is this lower bound so much higher at around 0.5 Nyquist, while remaining low at the origin and edges of F space? Is this predicted by the model? Does it correspond to the FT of the shape of the circular mask used in generating the simulated images?

(17) Page 9: "to interference between the contributions (...) which is 2a". This sentence reads as though the two SSB beams are interfering constructively or destructively with each other. Unless I'm mistaken the interference is between the scattered beams and the unscattered beam, is it not? That's certainly what the next sentence seems to say.

(18) Page 9: "The persistence of lattice images within (...) displaced from the particle". Likely because of my lack of expertise, and specifically because I do not know what the "coherence diameter" is, this sentence was lost on me.

(19) Page 10: "We note that this behavior is different (...) envelope function". For completeness, how about adding a supplementary plot overlaying the observed behavior (as in Fig 4) and the prediction from the spatial coherence (at whatever beam characteristics best fit the data, to point out perhaps that an unrealistic illumination semi-angle would be needed to fit the data)? This would help readers like myself who are not quite certain what one would expect such plots to look like if spatial coherence were really at play here.

(20) On the subject of Figure 4, I am curious about why the last few points of the 2.3 Å series seem so far off the prediction. The authors made a point of saying that the power spectra were so oversampled that even at that frequency, they had 3 pixels sampling each ring. So why the discrepancy, if not undersampling/aliasing? This made me curious: what would an equivalent plot from the simulation data look like? Would the Thon ring amplitudes from this synthetic experiment be a closer match to the predictions (dashed lines in Figure 4)? If not, perhaps this mismatch is due to poor sampling of these very fine rings at high defocus after all?

Summary and conclusions<br /> (21) Here might be a good place to formulate some caveat about the practicalities of processing data collected at very large defocus.

Figures & supplements<br /> (22) Figure S5: this would seem to argue strongly against evaluating the power spectrum using patches - would the authors agree? if so, how about mentioning it in passing somewhere? The optimal way to compute power spectra for the purpose of CTF parameter fitting is still a topic being discussed in the literature of late, and this observation would seem to be relevant.

On 2020-12-02 19:38:41, user Enrique Flores wrote:

Interesting work defining a new small protein regulating C/N balance in Synehcocystis. The discussion, however, may be an oversimplification, since the ornithine-ammonia cycle is just a side activity of the arginine catabolism pathway that renders glutamate as final product. The key enzyme in that cycle, called ArgZ in Synechocystis and AgrE in Anabaena, produces proline form arginine, with ornithine as an intermediate. The authors, however, do not report on proline levels, which would had been of much interest.

On 2020-12-02 18:03:33, user Eric Bilotta wrote:

The experimental design to analyze the ATP/ADP ratio at different stages of proliferation is an interesting and unique approach.

However, the manuscript needs to be proofread more intensely. There are two Figure 1s. For the second Figure 1a, it is stated that the ATP/ADP ratio increased with higher cell density, but a quantitative graph would be useful to visualize the statistical significance and variations in energy levels. There is also no analysis in the results section for the second Figure 1b but has similar photographs of the experiments compared to the second Figure 1a. Another numerical graph is needed to quantitatively analyze the effect of the pharmaceutical treatments. This could open discussion into the ATP/ADP ratio at the cell cycle checkpoints.

The first half of the paper does not feel well connected with the second half. The transition from an ATP/ADP ratio analysis into OXPHOS genes in cancers and ischemic kidneys does not work well. OXPHOS genes are not discussed in the abstract or introduction, so more information on their function and how those genes relate to the ATP/ADP ratio is needed before including experimental results. The manuscript seems more like two separate papers that need more content or maybe a connecting experiment.

On 2020-11-30 23:38:53, user Kelly Kiremidjian wrote:

I thought the hypothesis of this paper was very novel and interesting.

However, figure 2 could use some clarifications. The text regarding this figure states that the ATP/ADP ratio peaks at mitosis before dropping dramatically. In the figure, I can see high ratio levels starting around 240, but it would be easier to interpret if each time stamp was labeled with what point in the cell cycle was occurring. I was also curious about what happens to the ATP/ADP ratio following cytokinesis, which is not discussed in the text. Following cytokinesis in these images, is the new daughter cell being tracked for ATP/ADP ratio or is it just the original cell? Quantification of the ATP/ADP ratio color scale would also be helpful to determine how large the differences in ratio are.

Figure 2b could also be represented more clearly. I found the inter-mitotic gap region not very helpful in my understanding of the experiment. Perhaps you could continue the graph so that we can see what happens between Mitosis 1 and 2. Instead of blocking out the whole region you could bracket and label it as the inter-mitotic gap if that is important to note. The labeling here is also very confusing. The red and purple lines signifying pifithrin and tenovin in mitosis 1 should stay consistent and not switch to representing statistical significance or non-significance. It is unclear what points are being compared and determined as significant or not. I also found the X-axis to be confusing, especially through the inter-mitotic gap.

On 2020-11-25 19:13:11, user KAORI SAITO wrote:

The figure legends for Figure 4a and 4b should be switched.<br /> Also, in Figure 4a and 4b, the p-value is shown in the upper lefthand corner but it wasn't clear on which groups this p-value is representative of.

On 2020-12-02 16:30:13, user Alan Herbert wrote:

Really nice work! An important part of the puzzle. Great confirmation of the role of the Z-binding domain in ADAR biology!

On 2020-12-02 12:49:37, user Alan Herbert wrote:

The P193 residue is in the Zα domain of human ADAR . Along with N173, it is directly involved in binding the left-handed Z-conformation. Mutations to these human residues directly map to Mendelian disease confirming a biological function for the left-handed alternative Z-DNA conformation and its role in regulation of interferon responses. Citing the earlier work would help readers and strengthen the case made by the authors.<br /> "Herbert, A. Mendelian disease caused by variants affecting recognition of Z-DNA and Z-RNA by the Zα domain of the double-stranded RNA editing enzyme ADAR. Eur J Hum Genet 28, 114–117 (2020). https://doi.org/10.1038/s41..."

On 2020-12-02 14:10:53, user Anil wrote:

doi: 10.1038/s41598-019-52872-5.

On 2020-12-02 12:26:25, user Elin Sørhus wrote:

Article is now published in Science of the total environment: Doi: 10.1016/j.scitotenv.2020.143896<br /> https://authors.elsevier.co...

On 2020-12-02 09:56:01, user Martin R. Smith wrote:

This looks like a very promising new method. In evaluating its performance, I wonder whether you considered using alternatives to the Robinson–Foulds distance, e.g. Smith 2020, https://doi.org/10.1093/bio... ? As the RF distance suffers from a number of potential biases, it would be interesting to see whether a more robust tree distance measure would make the case for wQFM even stronger, and whether the seemingly better performance of ASTRAL on the avian dataset is robust to the choice of tree distance method.

On 2020-12-02 02:43:35, user Anil wrote:

This manuscript got published<br /> https://doi.org/10.1016/j.b...

On 2020-12-01 23:43:34, user Adrian Barnett wrote:

This is a useful experiment given the shortage of experiments into funding. As Guthrie et al (reference #1) stated: "We need to overcome the reluctance of funders and scientists to acknowledge the uncertainties intrinsic to allocating research funding, and encourage them to experiment with peer review and other allocation processes". The results are broadly supportive of a simpler and cheaper peer review system.

The agreement between reviewers was not adjusted for chance (e.g, using Gwet’s statistic). I agree with this approach as the raw agreement is what researchers are interested in (their only question is always, “Was I funded or not?”). We can account for chance by setting a threshold for an acceptable difference, e.g., an agreement of 75%. This threshold would ideally be based on discussions with the research community.

The differences in agreement were tested using chi-squared, but these are paired categorical data and so I think McNemar's test would be better. Although I'm not sure that p-values are useful given the sample size and the potential for a p-value of 0.05 to be interpreted as demonstrating equivalence. I would focus on the confidence intervals and whether they rule out an important difference in agreement.

The authors use Wald intervals but the sample size is small and the proportion is sometimes close to one, hence the normal assumption may start to be strained. I would consider using a bootstrap interval.

Although face-to-face meetings for peer reviewers may increase trust they also are a networking opportunity and could disadvantage those not invited or unable to attend (e.g., researchers caring for children). It is also a great learning opportunity for the reviewers about what makes a good application.

Minor comments<br /> - Table 1 shows summary statistics not "the distribution" <br /> - "no negative or positive reactions to the use of random selection were received from applicants" but was feedback asked for or were there only unsolicited comments?<br /> - The success rates here are very high success rate compared with other schemes. This may put less pressure on the system and allow it to conduct more novel experiments such as modified lotteries.

On 2020-12-01 19:58:12, user Sean Corbett wrote:

Gireesh Bogu Hi there -- it looks as if the link for the supplementary files for this paper is broken. Is there another place I could see them? Thank you.

On 2020-12-01 18:03:57, user Daniel Himmelstein wrote:

I reviewed this preprint (version 1) for a journal and have posted my review online.

Copying my conclusion below:

The study addresses an important problem. A unified dataset of gene-trait associations based on GWAS would be valuable resource. However, the manuscript is lacking details and intermediate results regarding the crucial steps of variant-to-gene mapping and association integration. Furthermore, the methods for association integration appear suboptimal, although more discussion of the reasons behind the design decisions might sway my opinion.

Integration into DISEASES and PHAROS suggest the TIGA data will make a lasting impact.

On 2020-12-01 16:55:46, user klevan wrote:

Thanks so much for posting, it's a good read!

We also greatly appreciate that you put the list of datasets used in the supplementary materials (it makes it easy for us to track use!). The citation guidelines (posted here: https://www.neonscience.org... recommend putting a reference in the references section along the lines of:

"NEON (National Ecological Observatory Network). DP1.10072.001, DP1.10092.001, DP1.10093.001. https://www.neonscience.org (accessed 21 October 2019)."

On 2020-11-30 19:34:24, user Iruka Okeke wrote:

Most of this pre-print has since been published as Monárrez R, Braun M, Coburn-Flynn O, Botelho J, Odetoyin BW, Otero-Vera JI, Quartey NKE, Peixe L, Aboderin AO, Okeke IN. A large self-transmissible resistance plasmid from Nigeria contains genes that ameliorate a carrying cost. Sci Rep. 2019 Dec 23;9(1):19624. doi: 10.1038/s41598-019-56064-z. PMID: 31873110; PMCID: PMC6927977.

On 2020-11-30 14:43:51, user Clarissa F. D. Carneiro wrote:

The article is well written and of interest to all stakeholders involved in fast dissemination of knowledge. I have only a few notes on readability and presentation of the data. Please note that I did not review the data itself or data analysis at this moment.

• Overall, I missed more interaction with the current literature both in the introduction<br /> and in the discussion sections. Although some of it is cited, the goals and results<br /> presented here are not well contextualized.

• On the other hand, the introduction is quite extensive about history of preprints, but<br /> the data presented is not proportionally focused on their usage or acceptance in the scientific community. While it is well-written, I do not see it as essential.

• One important issue for me that is lacking in the discussion is: if there is a favoring of publication of COVID-related research, are other diseases being neglected or are they still being published at the same quantities and speed? In other words, is the speed of COVID publication impacting the natural speed of other fields in biomedical sciences or is it a proof-of-concept that we can do better? If you think answering these questions is outside the scope of the current project, maybe these points can be raised and discussed at least based on the available literature.

• Supplementary materials are only referred to in the discussion section, but I believe they should also be described in the results section.

• I did not understand the use of colors on figures 1 and 2. If they should represent a<br /> particular distinction, it should be mentioned in the figures’ legends.

• Color codes are representing different things in different figures and panels. While there<br /> is a legend for all of them, I’d suggest reviewing the figures so that the variables<br /> used for different colors, bars and subpanels are constant.

• Would it be possible to also separate the data presented on fig 3B by COVID and non-COVID (as in fig 3A)? I think there could be useful information lost and highly recommend this change.

• Lastly, I’d recommend shifting each figure so that they appear closer to (ideally immediately after) its first mention in the text.

On 2020-11-30 14:10:41, user UAB BPJC wrote:

Title: “Antisense inhibition of accA in E.coli suppressed luxS expression and increased antibiotic susceptibility”<br /> Authors: Tatiana Hillman<br /> source location: https://www.biorxiv.org/con...

Description of selection<br /> This pre-print was selected by the UAB Bacterial Pathogenesis and Physiology Fall 2020 Journal Club 1) as it discusses the relationship between metabolism and antibiotic susceptibility of a common human pathogen, and 2) as the associated data were collected in a community lab (a novel concept for a new era of public science).

Summary<br /> This study attempted to ascertain the relationship between the gene products of accA and luxS in Escherichia coli and how these metabolic sensors influence biofilm formation and antibiotic susceptibility. Notably, these genes play respective roles in the fatty acid biosynthesis and quorum sensing systems of E. coli and serve to link metabolic sensing with general cell morphology. The author shows that transcription of accA, a gene associated with fatty acid biosynthesis, a pathway necessary for the maintenance and formation of the inner lipid membrane of E. coli, is increased with the addition of glucose to cultures in a dose-dependent manner. Additionally, the author shows that inhibition of accA by antisense RNA reduces luxS transcription. Finally, the author shows that inhibition of accA by antisense RNA increased susceptibility to three classes of antibiotics (beta-lactams, chloramphenicol, and tetracycline).

Major comments<br /> • Figures 1 and 2 are replications of previously published figures. These could be combined into a larger figure to include the total relevant fatty acid biosynthesis pathway. Additionally, the abbreviations used for gene and protein names (e.g. BCCP, Carboxyltransferase, Biotin Carboxylase, accA, accD, etc.) are not consistent from the text to the figures.

• While this may be journal-specific, the results section is formatted more as a technical methods write-up and the manuscript lacks the rationale for each experiment, interpretation of the results, or the impact of the findings on the current field.

• Explanation of how carbon (specifically glucose) is limited in the base LB media prior to experimental glucose addition is lacking.

• Statistic-specific data should be moved to be combined with the related experimental data or moved to supplemental.<br /> o Figure 5 details the statistics for normality of the accA transcriptional measures and should be included with the relevant plots of the source data or moved to supplemental<br /> o Tables 1 and 2 detail the results of comparison between accA and luxS transcription (or RNA amounts) and should be included with a plot of the source data and relevant comparisons or moved to supplemental<br /> o Figure 8 compares the results from the antibiotic susceptibility shown in Figure 7 and should be combined or moved to supplemental.

• Transitions and flow of logic are not clear in the results section. For example, the transition to the section on luxS and accA is abrupt and not explained.<br /> • Antibiotic susceptibility should be assessed on the same plate (e.g. bacteria with and without the antisense RNA plasmid should be struck onto separate parts of the same plate as to verify comparisons are equivalent<br /> • The title and abstract draw conclusions on the biofilm formation resulting from the accA and luxS transcription in various metabolic conditions but the author does not assess biofilms in any way. These potential impacts can be part of the implications and future directions of the discussion section but should not be a main claim of the paper as they are not assessed within.

Minor comments<br /> • Rationale for the use of the strain TOP10, a cloning strain of E. coli, was not explained. The cloning-optimized genetics of this strain has implications on the interpretation of results and should be addressed.

• Growth rates between the antisense RNA-expressing strain and the controls should be plotted as to verify any potential defects of the transformant which may influence results of subsequent tests.

• The results section is written with numerous improper sentences or sentence fragments and should be edited to correct this.

• The figure labeling is not consistent from figure to figure (e.g. text size, font, panel letter labels, etc.).

• Not all abbreviations are defined the first time they are used in the text (e.g. asRNA).

On 2020-11-30 10:04:28, user Pinkie Cherian wrote:

Good work... Brassinosteroids have greater effect on Arabidopsis gene

On 2020-11-30 09:16:49, user Niko Popitsch wrote:

Nanopanel2 is now released on github: https://github.com/popitsch/nanopanel2

On 2020-11-30 05:00:07, user Sergio Munoz wrote:

It would be a good idea to compare this to other more recent and presumably accurate trimming software such as ZORRO and Divvier. Cheers,

On 2020-11-30 00:33:52, user Andres Garriz wrote:

Dear authors, it is a very interesting work. Have you checked what is the origin of DNA damage? could it be a rise in the production of ROS at stationary phase? thanks a lot.

Dr. Andrés Gárriz<br /> UB1-INTECh (CONICET-UNSAM)<br /> Intendente Marino KM 8.200<br /> Chascomús, Buenos Aires<br /> Argentina<br /> CP 7130

On 2020-11-29 22:33:24, user Simon Burgermeister wrote:

Hi, the GitHub repository contains the processed result analysis but not the original data. Would it be possible to have access to it as well in order to test the execution of the code with a working example?

On 2020-11-29 20:13:10, user Dr Brian Dowling DVM wrote:

Mink could be an excellent model for determining how infective the virus is once it has settled on a surface. Is it only infective if inhaled? Is it able to escape a surface? We have all been erring on the side of caution and possibly wasting a lot of time and effort disinfecting surfaces that may be no risk at all. In vitro isn't real life.<br /> House an infected animal in a cage for a day. Empty, but don't clean, the cage, do several air exchanges and introduce test animals to the cage after differing time periods. Determine the risk from surfaces.<br /> Note I have known people who don't wear masks because they think the risk from surfaces makes the mask useless.<br /> Of course mink are in far more intimate contact with their environment than humans but if they don't get infected then we can put more effort into effective tactics and waste less in pointless busywork.

On 2020-11-29 16:40:44, user Graeme Walker wrote:

Dear Dr Bernardo<br /> This is a most interesting paper. However, it is factually incorrect to state that only short-term synchronisation of yeast has so far been achieved. Dr Peter Dawson developed a method to "continuously synchronise" yeast populations in the 1980s. I may have referred to his work in my review paper:Walker, G M (1999)<br /> Synchronization of yeast cell populations. <br /> Methods in Cell Science 21: 87-93.

Best regards, Graeme Walker

On 2020-11-28 10:50:06, user Marco van de Weert wrote:

I was made aware of this manuscript, as the authors cite a paper I wrote, in which I and my colleague Lorenzo Stella critically assessed the type of work presented in this manuscript. Unfortunately it appears the authors did not fully understand our paper, as we point out several issues with the procedure used. Most importantly, we discuss the double log equation the authors used for analysis of their data (page 4, line 100), pointing out several pitfalls. One important pitfall is that the equation assumes the complex is totally non-fluorescent, an assumption that is very questionable. Beyond this, the authors use an overly complex version of this equation (after all, -log 1/x is the same as +log x). Moreover, it contains an attempt to correct for the difference between added and free ligand concentration (through [L]-[P]*((F0-F)/F)), but this implicitly assumes 1-to-1 binding (as well as a non-fluorescent complex), meaning one could just as well use a slightly modified version of the Stern-Volmer equation, as the double log equation refers back to the Stern-Volmer equation if there is 1-to-1 binding. Note that the double log equation the authors used contains the Hill coefficient (n - notably not defined by the authors in the manuscript), which is a measure of cooperativity between binding sites. Such cooperativity obviously makes no sense if the authors in the same equation assume there is only one binding site.

The issues with assuming a non-fluorescent complex are not trivial, as they cast doubt on what binding the authors actually are investigating and what binding they can actually observe. HSA has one single Trp residue that is responsible for most of its fluorescence. If the ligand binds anywhere else but Sudlow Site I, it is far away from this Trp residue. Depending on how the ligand quenches the Trp fluorescence (direct interaction, FRET, or local structural changes), one would expect that each binding site has a different impact on the fluorescence quenching. In fact, it is my contention that the ligand used here likely cannot give any FRET-induced quenching (the absorbance, if real at all, is extremely low), and thus likely can only quench the fluorescence if it binds in Sudlow Site I, very close to the Trp, either through a direct interaction or by causing some local changes in structure. Whether it fully quenches the fluorescence when bound in Sudlow Site I is obviously unknown, but in my opinion it is unlikely to be the case - the authors themselves find no direct interaction between the Trp residue and their ligand in the molecular docking, so how would it completely quench its fluorescence?

Another part of the manuscript relates to the synchronous fluorescence. Some years ago I and colleagues pointed out that the chosen "deltaLambda" values of 15 and 60 nm may not be sufficient to separate Trp and Tyr contributions, and that there is a much easier and more robust way (https://doi.org/10.1016/j.m... just use excitation at 280 and 295 nm to get Tyr + Trp and Trp-alone contributions, subtract the latter from the former, and you get the Tyr-alone contribution. An issue I have with the data presented in Figure 2A+B is that the authors do not indicate what wavelength is plotted on the x-axis; I assume it is the excitation wavelength in both cases. If a correct assumption, this then immediately shows a major problem: the "Tyr" fluorescence (Fig 2B) then supposedly comes with a maximum excitation wavelength around 295-300 nm. This would be very surprising, since Tyr does not absorb in this spectral region! In fact, its absorbance is essentially absent already above 290 nm, hence the common use of 295 nm as excitation wavelength to get Trp-specific fluorescence.

My final comment relates to the connection with pharmacological treatment. The authors indicate some level of concern that warfarin and DHLA bind to the same site, and that this means that patients on warfarin would not get the same benefit of DHLA as those without. This is based on the often-overstated impact of (changes in) albumin binding on the pharmacokinetics, in the mistaken belief that significant (i.e., >10%) binding to albumin has a major effect on the therapeutic efficacy, primarily through prolonged circulation. This is, however, incorrect. Several papers have been written in the past to debunk this myth, pointing out the many other factors that are of importance, and often much greater importance - see e.g. https://dx.doi.org/10.1002/... and https://doi.org/10.1067/mcp....<br /> The concern here is thus extremely speculative, even more so if one realizes that most humans have HSA concentrations in plasma of around 600 micromolar, and that warfarin is typically dosed at 10 mg per day for two days, followed by much lower maintenance doses (3 mg/day). This amounts to some 33 and 10 micromoles a day. Even if it were all to accumulate in the HSA, one would need weeks of treatment before a significant percentage (>10%) of the available HSA has warfarin bound.

On 2020-11-28 02:04:51, user Aaron wrote:

Thank you for this. I preproduced a lot of these protocols and never formed leaf primordia. I remember our CEO saw these papers and thought we were not paying attention to the literature, but he didn't know they were all trash.

On 2020-11-28 00:21:52, user kdrl nakle wrote:

This is quite a bit of a mutation. I was under impression that is not not that much, at least we were told that in the beginning. This indicates to me that this thing will be mutating more than what is generally expected.

On 2020-11-27 19:30:15, user Camilla Forsberg wrote:

This preprint is has now been peer-reviewed and published in the journal Development - check out the final version there!

On 2020-11-27 19:28:11, user Camilla Forsberg wrote:

This preprint is now published in the peer-reviewed journal Experimental Hematology - check out the final version there!

On 2020-11-27 19:25:49, user Camilla Forsberg wrote:

This paper is now published in the journal Stem Cells - check out the final version there!

On 2020-11-27 12:45:00, user Martin R. Smith wrote:

It's very useful to see an objective evaluation of each stage in a pipeline, and interesting to see the magnitude of the differences that method choice can account for. One suggestion, if I may: the Robinson–Foulds distance has a number of known shortcomings, and I wonder whether you might obtain more discrimination between approaches – particularly in the Ebola case where there's quite a wide spread of unweighted RF values – using a more robust metric? I have reviewed the performance of a subset of candidate alternatives in Smith (2020, Bioinformatics): https://doi.org/10.1093/bio...

On 2020-11-27 08:09:35, user Pierre Schembri-Wismayer wrote:

Interesting work. I think cyclophosphamide providing preconditioning should be considered across the board in all cancers

On 2020-11-26 20:37:06, user anthony samsel wrote:

Pere,

Just to let you know, I first notified the US EPA and other US government agencies that glyphosate disrupted gut bacteria and digestion a decade ago and published 6 papers on the subject available at ResearchGate. I have appeared before the US EPA, California EPA and provided consulting to Baum & Hedlund attorneys that won the billion dollar lawsuits against Monsanto gleaning additional cancer data from Monsanto's studies. The EPA gave me all of Monsanto's research files for my assessment. I have gleaned important information from these files including from the marginal notes of their pathologists. It spurred my continued research. I have a new paper coming out in 2021 based on many years of field and lab work that explains how glyphosate destroys biology and is in fact a causal agent in disease. The work contains lab analysis of glyphosate and metabolites I found bioaccumulated in different types of human tissues as well as those from other animals, plus my work with glyphosate and enzymes, proteins, lipids and more. Please feel free to access my papers in my authors file ~

On 2020-11-26 14:03:20, user Matteo Pina wrote:

Hi I have 4 samples from this Sicilian studio with whom I share cm, my father is Sardinian and my mother is from Calabria, the mytrueancestry website says that the modern population most similar to these samples are Sardinians. In your opinion how is this possible? I don't remember historical migrations from Sicily to Sardinia.

On 2020-11-26 08:49:10, user Joe Canepa wrote:

There is another Arrhenius equation that may expand this groundbreaking paper. <br /> Arrhenius and Hannes Alfven derived an equation that limited the radius of particle by which the particle’s motion will be controlled by electromagnetic forces rather than gravity.

RLm = ( 3VBTgy ) 1/2<br /> ( 8pi2 Oc)

RLM = Radius limit

V = voltage in esu

B = magnetic field in gauss

Tgy = time of gyration in seconds

O = density in g/cm2

c = speed of light

See Paragraph 5.4 Limit between Electromagnetically and Gravitationally Controlled Motion. Arrhenius and Alfven, Evolution of the Solar System. NASA SP 345

This equation could explain why some small aerosoles remain suspended in the air, while larger particles fall to the ground, a may be an important factor the abatement of the virus and the transmission of the virus. The equation calls for the particle to be charged and thus effected by EMF. This yields a transmission mechanism that allows viruses or virus carriers to move great distances at high velocity.

On 2020-11-26 06:56:34, user Alvin wrote:

Hey guys, we are working on DR clustering as well. Since those peptides you are using on the origami structures are monovalent, binding only one receptor at a time, not like TRAIL, which can activate three DR receptors. How would the propsed hexagonal patten promote network formation of trimer-of-dimers or dimer-of trimers? Wouldn't it just activate 6 DR reseptors in close proximity?

On 2020-11-25 15:17:37, user Terry Robinson wrote:

Harraz et al., report an extremely interesting and exciting finding concerning a novel target (receptor) for cocaine; the membrane-associated brain acid soluble protein-1 (BASP1). They provide compelling evidence that cocaine’s action at the BASP1 mediates its’ locomotor activating effects (although see below). Harraz et al. also claim that BASP1 depletion, “markedly reduces the acquisition of locomotor sensitization” and “abolishes the expression of locomotor sensitization”. However, they do not appear to provide statistical evidence for such effects on locomotor sensitization. To clarify, in the case of drugs, sensitization refers to an increase in a drug effect with repeated drug administration. Therefore, to claim that a manipulation influences the “acquisition” (induction) or expression of sensitization, relative to a control group, requires showing that it influenced the rate or degree of change in a drug effect, not just in the drug effect per se.

As best I can tell, Fig. 4b shows a main effect of group, indicating that BASP1 depletion decreased the locomotor activating effects of cocaine on each of the four days mice were given a cocaine injection, consistent with the effects of BASP1 depletion on the acute locomotor activating effects of cocaine, as shown in Fig. 3. To claim that BASP1 depletion decreased sensitization (the rate or degree of change in drug effect) requires their ANOVA produce a significant group by time interaction. In Harraz et al., it is not stated whether the results of their ANOVA reflect a main effect of group (indicating BAPS1 depletion decreased locomotor activity) or a group by time interaction (indicative of an effect of BAPS1 depletion on sensitization, that is, indicating that with repeated injections locomotion changed over time differently in the two groups). Inspection of the figure suggests it is a main effect. Similarly, a significant interaction is not reported for the data shown in Fig. 4c. As an aside, in Fig. 4c there also does not seem to be an effect of BASP1 depletion on locomotor activity in saline pretreated mice given cocaine for the first time, on Day 14 – did past experience with saline injections alter the effect of BASP1 depletion on the acute locomotor activating effects of cocaine?

In summary, unless additional information is provided it appears that the claim an action of cocaine at the BASP1 influences locomotor sensitization is not supported by the data, and thus not justified. This may be another example of a dissociation between effects of a neurobiological manipulation on the acute psychomotor activating effects of cocaine versus its ability to induce behavioral sensitization – these are very different processes. Of course, this does not detract at all from the exciting report of a novel cocaine receptor.

Terry E. Robinson, University of Michigan

On 2020-11-25 13:47:52, user Aldo Badiani wrote:

I wonder whether the authors tested the effect of the virus on cocaine self-administration. If yes, it would be nice to publish the data along with the rest.

On 2020-11-25 15:13:27, user Chris Bridges wrote:

Hi, Great work. We went out straight away and tried you primers on Samples of adult Beluga males and females but unfortunately the first results were not encouraging. We will try again with fresh samples. We also have access to samples from the north of Germnay.<br /> At what size (weight or length) could you detect sex accurately in small sturgeon?<br /> Again a fine piece of work.