On 2020-02-11 21:18:28, user lindsey rim wrote:

' SARS' the new name of coronavirus check it outt here https://www.chillandbuzz.co...

On 2020-02-11 19:13:42, user Humberto Debat wrote:

Following WHO Director-General briefing on 2019-nCoV on 11 February 2020 available at https://www.who.int/dg/spee... authors may update figure 5B lower right panel to include: Corona Virus Disease (COVID-19)

On 2020-02-11 20:21:47, user Anita wrote:

This paper is published in nature: https://www.nature.com/arti...

On 2020-02-11 18:34:42, user Richard G. Lanzara wrote:

This type of analysis may show that the "net shift" is a better measure for receptor activity than either the fractional or proportional response.

On 2020-02-11 17:54:52, user Richard G. Lanzara wrote:

Measuring the initial receptor response is certainly important. Dr. Colquhoun has commented on the possible flaws, which are also important to consider. Since the conception of enzymology and pharmacology, a major assumption has been that the initial response is a function of the fractional or proportional occupancy of the enzyme or receptor. This harkens back to the original Michaelis–Menten equation on which much of our subsequent modeling efforts have largely depended. Although relatively recent developments have shown that the fractional or proportional occupancy fails to account for the experimental findings, such as for spare receptors and the responses from receptor over expression, there have been relatively few models that attempt to account for these observations. This is why I have been touting the measurement of the "net shift" (as the chemical representation of Le Chatelier's principle) as a much better representation. https://www.google.com/sear...

On 2020-01-23 16:16:30, user David Colquhoun wrote:

This paper puts emphasis on the rates of action and that is laudable, given that many processes are not in a steady state in real life.

If you can estimate all of the microscopic rate constants for a realistic reaction mechanism then you can predict the rates of any macroscopic process from p(t) = p(0) exp (Qt) where p(t) is the vector of occupancies of each state at time t, and Q is the transition rate matrix. So far. that has been achieved only for a handful of ion channels, using single channel analysis. I fear that we are nowhere near to achieving it for GPCR, partly because the methods have insufficient resolution, and partly because there are no mechanisms sufficiently detailed and realistic to allow such predictions. For example, as far as I know, nobody has yet worked out how to allow properly for the concentration of G protein. This means, I think, that attempts to interpret the rates of events at GPCR in mechanistic terms are unlikely to cast much light on physical reality.

There are examples that illustrate these in Colquhoun & Lape (2012) (that was my last contribution to this field): available at http://www.onemol.org.uk/Co...

On 2020-01-22 17:50:51, user David Colquhoun wrote:

"determine empirical drug parameters (e.g. EC50 and Emax), which are then used to calculate chemical parameters such as affinity and efficacy."

Sorry, but it's simply not true that you can calculate affinity and efficacy from those data.<br /> It's been known since 1987 that Stephenson's analysis has a fatal flaw: see http://www.onemol.org.uk/co...<br /> or, for a more recent analysis: http://onemol.org.uk/Colquh...

On 2020-02-11 17:53:45, user Partho Sen wrote:

This paper is now published in Diabetologia (https://link.springer.com/a...

On 2020-02-11 07:06:29, user PE DI wrote:

Question from a layman: So in reference to the RaTG13 genome found in the 2019-nCoV means that this virus is 96.3% similar to the SARS-CoV ? Also if RaTG13 is not the exact genome that caused the outbreak in humans then does that mean that there is another bat like genome that needs to be identified as the cause ?

On 2020-01-31 22:20:39, user Hongda Liang wrote:

Question from a layman: On Line# 123~ 124. " We then successfully isolated the virus (named nCoV-2019 BetaCoV/Wuhan/WIV04/2019)" . Does this mean the nCoV-2019 is also called WIV04? It seems Wuhan Inst. of Virus has used this name (WIV4) in previous years papers.

On 2020-01-30 09:44:07, user Prometheus wrote:

Dear team, i was not able to find the original publication of the (recent?) isolation of the above mentioned Coronavirus. Could you inform us who made this isolation and where we can find the related publication?

On 2020-01-28 08:53:07, user OlivierLG wrote:

There is no evidence in refs [1] or [2] that any member of the family Comoviridae is naturally found in fish. In fact, within the order Nidovirales, this seems to be only the case of bafiniviruses, now clustered in the family Tobaniviridae and in a neighbouring sub-order (see https://talk.ictvonline.org....

On 2020-02-11 03:11:41, user Minxing Pang wrote:

Paper updated. Thanks for Tim Stuart 's suggestions!

On 2020-02-06 15:55:26, user Tim Stuart wrote:

The first abstract sentence:

"The recent maturation of single-cell RNA sequencing (scRNA-seq) technologies has coincided with transformative machine learning methods to profile genetic, epigenetic, spatial, proteomic and lineage information in individual cells."

Has significant duplication with the first abstract sentence in a review by Stuart and Satija (2019, Nature Reviews Genetics):

"The recent maturation of single- cell RNA sequencing (scRNA- seq) technologies has coincided with transformative new methods to profile genetic, epigenetic, spatial, proteomic and lineage information in individual cells."

On 2020-02-11 01:17:35, user Emre O wrote:

Let me know if anyone needs genetically engineered epitopes for their vaccine development efforts for testing.

On 2020-02-10 16:30:13, user Virginia Savova wrote:

Now published with Springer Nature in Scientific Reports https://rdcu.be/b1sYv

On 2020-02-10 10:39:23, user Jan Zaucha wrote:

Hi guys, our group has already published extensively on the topic of mutations in TM proteins, thus your claims in the abstract are not really true:

https://www.ncbi.nlm.nih.go...<br /> https://onlinelibrary.wiley...<br /> https://www.ncbi.nlm.nih.go...

On 2020-02-10 08:04:05, user Aaron wrote:

Wait - so n=1 ?

On 2020-02-05 19:40:03, user Gawor Zenon wrote:

How angiotensin converting enzyme inhibitory affect a number of cells with ACE2 expression in the lungs of patients with atrial hypertensions and ischaemic heat disease.

On 2020-02-03 15:21:13, user the other guy wrote:

Even though they are working with a low sample size, the correlation with gender can be useful information. If you look at MERS and SARS both impact males more than they do females. <br /> The hypothesis that they propose could prove itself useful with more data or research to refute or back it up.<br /> Understanding that the paper is not peer reviewed and preliminary is important,but in the current atmosphere, finding the importance of it and the insight that it makes in its hypothesis and correlations gives it credence and credibility.<br /> When time is of the essence, any bit of information we can use to give us clue may hold true importance. It is good to poke holes in research, but it is also important to find peer reviewed research that may add credence or take away from the probability of the papers credibility.<br /> It might have holes methodologically, or in sample size, but it still has promise to a novel insight to a novel disease we are racing to understand and treat.

On 2020-02-01 16:51:18, user Serge wrote:

As for analysis - tSNE best use is visualization, it is not quite as reliable as principal component extraction method.

On 2020-01-31 18:26:50, user rongmin wrote:

I think their report has problem and is wrong. ACE2 related hypertension, at least he should tell blood pressure. Also they mentioned female is larger than male, based on current report, it is not true at all. all the problem are from small sample size. I believe if the ACE2 related gene is the same between race, then there are no difference between race.

On 2020-01-31 00:58:11, user Hans Ratzenburger wrote:

"This new coronavirus has resulted in <br /> thousands of cases of lethal disease in China, with additional patients <br /> being identified in a rapidly growing number internationally." According to other sources the death count from novel coronavirus is approximately 170 at 31/01/2020. Why does it say thousands of cases of lethal disease?

On 2020-01-30 16:57:21, user Ying Zhang wrote:

In general, single-cell analysis is still at very early stage, especially for cell-type identification (how many markers were used for each cell-type?). Also, as Seurat developers stated the clustering result is sensitive to the parameters chosen (and they are still using Seurat v2 vs the current version is Seurat 3), it is not convince to draw some of the conclusions in the paper, such as the composition of cell types in the samples.

Given all these technical details, I don't think they could meaningfully comment on the comparison between ONE Asian sample with other samples.

On 2020-01-30 08:42:32, user Aaron Parmet wrote:

Fascinating but seriously needs more data.. and fast

On 2020-01-30 01:50:31, user Jeff Mah wrote:

The purpose of this report is to present the possibility, the conclusion will come from everyone else.

On 2020-01-29 07:59:31, user Chang Lu wrote:

As an ethnic Chinese, I have a strong negative feeling about this result. However, I do want to point out that this team has only examined 8 samples (only one of them is Asian). Therefore, this result somehow lacks credibility. I wonder if other team would love to further examine the ACE2 expressing ratios among a relative larger Asian sample pool.

On 2020-01-29 04:00:33, user Tong Wang wrote:

A comparison between eight individual samples demonstrated that the Asian male one has an extremely large number of ACE2-expressing cells in the lung.

So is nCov a virus specifically likes to infect Asian male? <br /> That will be very interesting.

On 2020-02-09 16:03:12, user Craig Kaplan wrote:

The authors might consider this recent work: https://www.ncbi.nlm.nih.go...

On 2020-02-09 15:49:43, user ResearchGuy wrote:

I see several commenters have asked about the COMPOUND probability of ALL FOUR sequences occurring naturally in what would seem to be a section of nCoV that affects what kind of cells that can infect. I have seen no answers to that question. Someone, preferably several someone's, please answer it. If I had the skills I would do so myself, but I don't think any of the posts have even stated the exact individual probabilities so I can't multiply them together for myself.

On 2020-02-08 07:31:36, user jean-claude perez wrote:

Please read https://www.preprints.org/m...

On 2020-02-05 11:13:24, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong Uni, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-04 13:28:25, user Ironman wrote:

In the 2011 research paper by Y. Kawaoka and two colleagues at his animal virology lab at the University of Wisconsin-Madison, titled "HIV reverse-binding protein is essential for influenza A virus replication and promotes genome-trafficking in late-stage infection". Published in the Journal of Virology, September 2011. Is this current published study a reflection of the scientific reality of binding HIV to flu viruses as suggested by the Indian team? If so what purpose would that serve in Wuhan?

On 2020-02-03 19:18:31, user Hannah Davis wrote:

Out of curiosity, I just did a quick check of how many HIV-1 protein sequences there are in the NCBI database, because I suspected that the virus might be over-represented.

Via the NCBI Taxonomy Browser, out of 6 012 978 total viral protein sequences, 1 169 134 are from HIV-1 alone.

For comparison, there are only 57 759 protein sequences in the database from ALL Coronaviridae combined.

This over-representation of HIV-1 in the database, combined with its famously high mutation rate, makes it VERY likely that any given short NT or AA sequence will show up in one or more HIV-1 sequence via blastp. Even if you ignore the effects of selection on viruses that may need to fold their proteins/interact with membranes/etc. in the same way.

On 2020-02-03 13:44:16, user David Murphy wrote:

Where's the link to the specific HIV-1 protiens?

Why does it not cite the relevant nuccore entries?

Looking at an example HIV-1 GP120 protein sequence (which I have to since I don't see a specific one cited)

https://www.ncbi.nlm.nih.go...

I see none of these sequences:

GTNGTKR

HKNNKS

GDSSSG

QTNSPRRA

Running a blastp alignment between these sequences and the linked HIV-1 GP120 the only match I find is 2 proteins long.

https://blast.ncbi.nlm.nih....

Also, just for fun, lets run a BLASTN between Wuhan-Hu-1

GenBank: MN908947.3

https://www.ncbi.nlm.nih.go...

And HIV-1 complete genome

GenBank: AF033819.3

https://www.ncbi.nlm.nih.go...

With the most permissive settings possible we do get some hits.

4 hits with an "expect"(number of times we expect to see matches of this type by chance in the given search) score of 2.8<br /> 8 hits with an "expect" score of 9.8

AKA: chance

https://blast.ncbi.nlm.nih....

None of them are any of these 4 "inserts"

This is entirely bunk and bunk with bad citations and sourcing at that.

On 2020-02-03 09:18:44, user Dottor Leopardo wrote:

identity /similarity to amino acid residues in key structural proteins of HIV-1 is QUITE COMMON in nature (starting from the human Red Blood Cells surface).

On 2020-02-02 15:53:27, user Jason Weir wrote:

I give credit to the authors who have now withdrawn this manuscript and have stated that they are reworking it to incorporate feedback from the research community.

On 2020-02-02 14:14:03, user Death Syndrome wrote:

If it express gp120 so why it doesn't infect immune system?

On 2020-02-02 04:13:59, user jay wang wrote:

I BlastPed the region that spans the first 2 “insertions”, and found no so called insertions at all in the alignments with other bat-cov viruses. On the contrary the alignments showed very natural diversities around the two ”insertion” regions. The two “insertions” are obviously products of evolution，not engineered artifacts！ Furthermore，even human has huge number of proteins that are homologous with those of vegetables，so why it is a surprise that there are short homologous regions between 2 viruses？

On 2020-02-02 03:41:00, user jay wang wrote:

I BlastPed the region that spans the first 2 “insertions”, and found no so called insertions at all in the alignments with other bat-cov viruses. On the contrary the alignments showed very natural diversities around the two ”insertion” regions. The two “insertions” are obviously products of evolution，not engineered artifacts！ Furthermore，even human has huge number of proteins that are homologous with those of vegetables，so why it is a surprise that there are short homologous regions between 2 viruses？

On 2020-02-02 02:08:23, user Connor wrote:

I'm a logician so I'm fond of synopsis<br /> I'm not a geneticist

Reading through the board though

There was bat virus = A<br /> There's now ncov19 = B

The difference between A and B rna is the insertion/addition of 4 sequences<br /> These 4 sequences are present in HIV<br /> They are also present in some related bat stuff and also not that uncommon generally

There is also an artefact of the complexity of this stuff that a possible and previously seen (1919 flu) change in a very small common sequence can precipitate the rest<br /> We don't know the correlations there

What I'd like an opinion on is

How likely is it that <br /> The change from A to B happened in such a time frame commensurate with the emergence of B purely as an organic process

Can I get a breakdown of probabilities (what u guys call 'E values'

Thanks

On 2020-02-01 23:01:05, user AronF wrote:

We really ought to be given the 'E value' of the BLAST hits to the HIV sequences in order to determine the actual "unlikely[hood]" of the 2019-nCov matching the HIV-1 inserts. That is the very reason the E-value exists. The fact of 100% coverage means little if there is an abundance of hits with 95% coverage for example - in this case the E value would be high.

On 2020-02-01 22:10:51, user Zhenguo Zhang wrote:

The study shows something interesting, but the title is just exaggeration. Furthermore, if you look at Table 1, the inserts are not so similar to HIV proteins except insert 1 and 2. Also these inserts have been found in the bat virus (Fig. S2). But these findings has potential to explain the contagiousness of this new virus.

On 2020-02-01 21:47:08, user Milwaukee wrote:

The 1/30/2020 Lancet study of 99 patients from Wuhan found that T-cell count was significantly suppressed. If there are GP120 amino acids present in 2019-nCOV spike protein that could allow it to bind to CD4, it could explain the low T-cell count.

On 2020-02-01 20:26:49, user JoshP wrote:

Interesting observations and discussion below, requires further inquiry. Things to keep in mind: (1) Blasting each insert individually unsurprisingly identifies multiple hits. But I am unable to find any virus besides HIV-1 that contains ALL FOUR inserts in their totality together (in the gp120 and gag proteins). This can be confirmed at both the nucleotide and amino acid levels. This, to my mind, changes the probability calculus and requires further study to understand the basis of these findings. (2) A great deal of weight is being placed on this single uploaded sequence (RaTG13, QHR63300.1), stated to be from 2013 Yunnan bat feces, deposited by the Wuhan Institute of Virology on 1/29/20. Clearly it will improve confidence in the scientific community if the provenance of this one critical linking sequence can be independently verified as an actual, naturally-occurring sequence isolated as stated in 2013 from bat feces. (3) Interestingly, the nucleotide sequences of inserts 2 and 3 in RaTG13 are identical to those in the 2019-nCoV virus, not even a single synonymous substitution since 2013. This strikes me as intriguing and indeed worthy of further study. It will be interesting to see how stable the nucleotide sequences of inserts 2 and 3 remain in this human outbreak in thinking about how likely it is that they would be unaltered since 2013 in the natural bat (or other reservoir or intermediate) population.

On 2020-02-01 18:36:30, user Dr. Andy Crispr wrote:

I think their findings are interesting and merit further scientific investigation. Specifically, because of its novelty, we still have quite a low number of nCoV samples sequenced and, given the virus' high mutation rate and given the intrinsic variability of genome editing techniques, it would be interesting to see if more sequence data would come up that potentially further underscores this proposed connection to HIV. The fact that this connection, if weak, has been found so early after the first discovery/sequencing of the virus is astounding.

On 2020-02-01 17:59:39, user Laurie McGee wrote:

SARS Coronavirus and HIV minute similarity are mentioned in this research back in 2003. https://link.springer.com/a...

On 2020-02-01 17:25:30, user Prashant Pradhan wrote:

This is a preliminary study. Considering the grave situation, it was shared in BioRxiv as soon as possible to have creative discussion on the fast evolution of SARS-like corona viruses. It was not our intention to feed into the conspiracy theories and no such claims are made here. While we appreciate the criticisms and comments provided by scientific colleagues at BioRxiv forum and elsewhere, the story has been differently interpreted and shared by social media and news platforms. We have positively received all criticisms and comments. To avoid further misinterpretation and confusions world-over, we have decided to withdraw the current version of the preprint and will get back with a revised version after reanalysis, addressing the comments and concerns. Thank you to all who contributed in this open-review process.<br /> : Authors of the Manuscript

On 2020-02-01 16:05:38, user Dzogchen wrote:

This report highlights the dangers of assuming significance to a highly improbable yet random occurrence. If one calculates the probability of finding all four peptides within the HIV-1 genome it is improbable but that does not infer non-randomness. Lots of highly improbable events happen in nature that are in fact random. Even if you constrain to just the viral sequences in the database which are nearly 6 million residues (protein) the probability is quite low that all 4 peptides match HIV-1 but the authors fell into the trap of assigning significance to randomness.

On 2020-02-01 15:57:16, user torque wrote:

Jason, I took a look at the blast results. The Wuhan seafood market virus does seem to match the bat coronavirus. However, if you click on the Accession (QHR63250.1 and QHR63300.1) you can see that both were submitted on the same day, 27-JAN-2020 by CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology. There are some subtle differences in "ORIGIN". It may be instructive to see what those differences are.

On 2020-02-01 15:50:25, user 戸谷剛 wrote:

.. Is this suggesting that the primary Coronavirus infects to HIV patients in Wuhan and mutated with transferring from hiv gene ?? Very aweful scenarios but possible.

On 2020-02-01 15:37:54, user illumined wrote:

A layman has a question if I may. The arguments against HIV having been artificially spliced into this coronavirus make sense, but leaves me to wonder if there isn't really a relationship been this novel coronavirus and HIV then why does the coronavirus respond to HIV protease inhibitors? Is it just something about those types of drugs that makes it work in diseases beyond HIV? Thank you.

On 2020-02-01 14:34:29, user N_Anthem wrote:

How about the "phenotypic mixing"? If there is an early case that has been infected by both CoV & HIV,wouldn't there be a chance bringing out the nCoV with that 4 inserts？

On 2020-02-01 13:56:29, user Jing Hou wrote:

As discussed by Jason Weir, Song Yang, Brian Hanley and others, I agree that the conclusion made by the authors lacks scientific merits.

As already pointed out in multiple comments, the so called unique insertions in the Wuhan isolates compared to the SARS isolate are cherry picked. In fact, a simple blast returned alignments with Bat SARS-like coronavirus that does contain 3/4 insertions in the most recent isolate from 2015, strain SL-CoVZXC21, from bats in the Hubei province, where the novel infectious virus supposedly originated (see attached figure).

All of the insertions sites coincides with positions variable across homologs, which make sense in that these positions are important for host interactions. This is not "uncanny", it's simply how selection works. As for the so called "identity" with HIV gag proteins, again, as pointed out by others, is spurious. Both HIV and coronaviruses are RNA virus and are hypermutable. The fact that positions important for host-virus interactions, i.e. where the new insertions were found, can be variable in the new infectious Wuhan isolate is expected and there is no evidence suggests that this is a result of human manipulation.

This preprint already gained notice in the media, as fear spread across nations, especially in China where the epidemic is currently escalating. This kind of fear mongering pseudo-science is harmful for the general public, who are less equipped to distinguish the merits of non peer-reviewed researches.

I strongly suggest that the authors revise or retract this manuscript.

Jing Hou (The Donnelly Center, University of Toronto)

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

On 2020-02-01 13:35:49, user re ro wrote:

Between the consensus sequence and the SARS sequence, there is good similarity with no notable gaps. This novel 2019 nCorV sequence is 19 amino acids longer, in 4 regions the authors identified - this is both notable and significant. The inserts may match other known sequences but they also match known HIV surface protein sequences. I believe this is a significant finding that should continue to be investigated.

On 2020-02-01 13:31:03, user Jacob B wrote:

We work on detection and identification of pathogenic sequences in DNA screening orders. These purported hits are far too short and sparse to serve as a detection: at these lengths, the likelihood of false positives via coincidence or coevolution is overwhelming.

On 2020-02-01 07:48:14, user ngschen wrote:

This paper is fake. I aligned all 4 insertions. 3 of them share with BAT sars-like virus (GISAID no.: BetaCoV bat Yunnan-RaTG13 2013 EPI_ISL_402131). The fourth insertion (CTCCTCGGCGGG), which is the only one 2019-nCov specific insertion, has the best match to Marine virus AFVG_250M1136. Since the 2019-ncov outbreaks from the seafood market, the possibility of marine virus rcombination might be much more persuasive.

On 2020-02-01 07:11:51, user 강석하 wrote:

Those are not insertions. It is "DELETION" of SARS clade.

On 2020-02-01 07:05:39, user Anon wrote:

I noticed that several people have pointed out that QHR63300.1 has all of the same insertions and is from Bat. Can anyone explain why this is the only Bat CoV with these insertions?

If you search for matches to QHR63300.1 the best hit by far is the Wuhan Seafood Market CoV, which infects humans.

It's also hard to understand why QHR63300.1 was uploaded 4 days ago (Jan 27, 2020) from Wuhan Institute of Virology.

On 2020-02-01 02:39:46, user Ilya Tsyrlov, MD/PhD/DSci wrote:

Dr. Konermann of Stanford just checked their results. The similarity is spurious. Out of 4 inserts they identify between NCov and SARS, 2 are found in bat coronavirus. Of the remaining two, only one is most similar to HIV, and is so short (6 AA) that the similarity is not higher than chance given database.

On 2020-02-01 02:37:10, user matale0 wrote:

https://twitter.com/trvrb/s...

On 2020-02-01 00:06:29, user Cole Knight wrote:

Is part of the Abstract true? The part about " 4 insertions in the spike glycoprotein" I see the other post calling out the people who wrote this paper. I agree 100% of course with what they are saying, that these sequences show up in a large amount of life. <br /> But, <br /> Is it true that these sequences do NOT show up in any other Coronaviruses ?

"We found 4 insertions in the spike glycoprotein (S) which are unique to the 2019-nCoV and are not present in other coronaviruses."

Seems that is what is NOT being referenced by the others. They are saying that these 4 insertions are not found in any other Coronavirus. Is that true? If so, that seems like it is still "tampering" to me.

So, what I get from it is that these 4 insertions are all in this one 2019-nCoV, but they do not show up in any other known Coronaviruses. Correct? <br /> Think about that for a minute. <br /> I am definitely not the smartest person on the planet and I don't know it all, but this still seems suspect based on the actual "Aspect" if you read it.

On 2020-01-31 23:59:45, user Kenrod wrote:

It strikes me that the phrase "uncanny similarity" and continued use of the word uncanny in the manuscript is not scientific. Unless there is a way to measure or gauge a comparison via some sort of statistics this reads more like astrology and is irresponsible.

On 2020-01-31 23:40:09, user Song Yang wrote:

In the supplemental Fig S2, the author mentioned that “the Bat-SARS Like CoV in the last row shows that insert 1 and 4 is very unique to Wuhan 2019-nCoV”. In fact, the Bat-SARS Like CoV, discovered in 2013, contains all the four insertions. Insertion 2 and 3 of 2019-nCoV are identical to Bat-SARS Like CoV. Insertion 1 involves two synonymous and one Thr-Ile mutation. Insertion 4 contains one synonymous mutation and a 12-bp insertion. Therefore, the two viruses have very high sequence similarity, and are likely evolutionarily related, naturally. Indeed, the four identified insertions are the result of the pair-wise comparison of Wuhan 2019-nCoV and 2013 SARS virus (Fig 1), and are an artifact when comparing only two viruses. The ‘insertions’ regions also appear in other coronavirus, as indicated in the multiple comparison in Fig.S1, possibly functionally important.

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

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

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

On 2020-01-31 23:13:13, user Gaetan Burgio wrote:

I performed an alignement of these sequences and indeed found that these 4 insertions mentioned in the preprint are real. However I blasted each of these insertions to the non-redundant protein database and found over 100 hits for every single of these 4 insertions. The hits are others coronaviruses, plants, parasites, bacteria. This indicates the hits to HIV seems fortuitous and the evolutionary link between 2019-nCoV and HIV is to me not ascertained. Additionally, the authors in the manuscripts did not provide a e.value for their findings, nor they have explained in their methodology why they restricted their search for viral genomes only and not others organisms. Therefore I would argue that the results presented do not appear "uncanny" to me based on a flawed methodology. Therefore the results presented in this paper should be taken very cautiously.

Gaetan Burgio (the Australian National University)

On 2020-01-31 22:58:57, user A_a_a_a wrote:

This is a really dumb study and these scientists should be ashamed. Those amino acids are so short. They just went and looked for a virus to match. You can go and blast the amino acids yourself. Just copy and paste from the journal entry into NCBIs BLASTp. I did it and there's hundreds of matches to those sequences. HIV didn't even come up in the first 100. The 4th residue is missing like 6 amino acids. There are conserved regions in viruses. Their "gp120" match compares 6 amino acids out of 850 in the whole protein for example.

They found 4 sections that were in the new virus but not SARS. They then took these differences and ran them against all known viral proteins. They only looked at proteins with 100% matches, but if you look at the table they didn't match 100% for alignment. So like one is ABCEFG and they match it to an HIV protein that is ABCXYZEFG and they are calling those total matches. There's also tons of viruses that match these tiny sequences, they just noticed all 4 have HIV matches so they ignore the other matches and only looked at HIV.

Go blast it yourself if you want.

These would be their blastp results if you don't exclude the vast majority of known proteins:

"GTNGTKR" https://blast.ncbi.nlm.nih....

"HKNNKS" https://blast.ncbi.nlm.nih....

"GDSSSG" https://blast.ncbi.nlm.nih....

"QTNSPRRA" https://blast.ncbi.nlm.nih....

You can look for significant virus hits yourself though by clicking on my blast results and filtering for "viruses" (you'll see that they don't hit HIV, nor any other virus). The reason for not reproducing their results is that when you consider the whole protein sequence space, the hits for viruses are too random to be significant.

But, if you insisted to repeating the searches only within viruses, here are the blastp results only looking for "Viruses (taxid:10239)" as Organism:

"GTNGTKR" https://blast.ncbi.nlm.nih....

Here is a HIV hit, BUT the number of expected random hits for this kind of similarity is 224, which is incredibly high.

"HKNNKS" https://blast.ncbi.nlm.nih....

Here is an HIV hit, but similar likely is a Bat coronavirus, a Tupanvirus, and a Herpesvirus; it is expected to find 86 similar sequences by chance.

"GDSSSG" https://blast.ncbi.nlm.nih....

There are over 1000 expected random hits for this sequence! And even then, the list is lead by a Hepatitis E virus, an Edafosvirus, a Bat coronavirus, some phages and Hepatitis B virus.

"QTNSPRRA" https://blast.ncbi.nlm.nih....

No HIV seen. However there are some phages, a papillomavirus ...

There's just no sense to it, this is pseudo-science.

On 2020-01-31 22:02:47, user Dave Baltrus wrote:

It is likely that the evolutionary relationships found between these two protein sequences of both viruses are due to a complete coincidence and, stepping back, do not appear "uncanny" to multiple experts that have also examined the sequences. In short, the authors base their analysis on a short sequence of the spike protein from 2019-nCoV, but a much more comprehensive search outside fo the viral sequences queried in the manuscript demonstrates that this sequence is also found in *many* *many* other places than HIV. Thus, while the 2019-nCoV strain does appear to have a sequence difference from other closely related viruses, there is not enough resolution to clearly demonstrate the evolutionary history of this change let alone trace it to HIV.

see analysis here for instance: https://twitter.com/trvrb/s...

On 2020-01-31 21:55:30, user Alex Crits-Christoph wrote:

All four of the identified amino acid insertions are extremely short and are found in the genomes of many other organisms, not just HIV. In other words, the primary finding of this work are entirely a highly expected coincidence.

All organisms contain a DNA code that has the genetic instructions for development, functioning, and growth - this is known as the "genome". You can imagine each genome as a book of instructions. What these authors did is look in the genome book of the 2019 novel coronavirus and identified 4 sets of letters that aren't found in the genome book of SARs, a related coronavirus. They then compared these letters to the genome book of HIV, and found some places where they looked somewhat similar - but not even identical. However, because these sets of letters were so short, they are often found in many genome books by chance - they way you might search for the phrase "can be there" in Google Books and find that thousands of books contain those words - but this is not an example of plagarism.

Note here: We call these sets of letters "insertions" because they are in one genome, but not in a close relative - "insertion" does not imply human interference or engineering - it is an evolutionary term and refers to a natural evolutionary mutation.

Here are the four insertions:

TNGTKR

HKNNKS

RSYLTPGDSSSG

QTNSPRRA

These four insertions are protein sequences, that are encoded by a DNA sequence (which you may know uses molecular "letters" of A, G, C, and T to encode for proteins, which uses 20 molecular amino acid "letters").

You, dear reader, do not have to take anybody's word for it that these letters are a concidence - you can do the bioinformatics yourself!

If you would go to:<br /> https://blast.ncbi.nlm.nih....

You will arrive at a search engine for these genome books, kind of like the Google of biology. Click on "Protein Blast", because are going to search for these protein sequences.

Under where it says "Enter accession number", you can paste any one of the four sequences above.

And then you can hit the "BLAST" button at the bottom of the screen. In a few minutes you will get a set of results.

Let's go through the results for the longest sequence, "RSYLTPGDSSSG", together.

Under the "Description" field you can see resulting hits. The first hit you see is to "spike glycoprotein [Wuhan seafood market pneumonia virus]" - this is good, because we know that this sequence came from this genome. Under "Per. Id" you can see the similarity of this sequence to other hits - in this case, you can start by seeing that this sequence is also found in Bat coronavirus, so isn't actually novel at all! And there are many comparative hits that as equally as good, or often better, than the HIV comparison.

Let's then take a look at the second sequence, "HKNNKS", together.

If you go through the same search process for this sequence and look again at the results, you can see hundreds of perfectly identical matches. Maybe you see Sipha flava - that's an Aphid, or Tetrahymena - that's an Amoeba. Drosophila is a fruit fly. Clearly this sequence is found in thousands of genomes.

Fortunately, the search has a built in way of answering the question "How likely was this result to have occurred by chance?". It is called the E-value, or Expect Value - the number of times we'd expect to see this result purely by chance. As you can see here, many of the E-values listed on this page are greater than 7829 - so we'd have expected to see 7829 instances of matches like these completely by chance! This is not evidence for gene transfer or gene similarity - it's simply a coincidence. As you now search for the other insertions described by this paper, you'll see that all of them hit hundreds of other genomes simply by chance. It is no surprise at all that they could have matches with some similarity in the HIV genome.

Congratulations! You are now a more careful and proficient bioinformatician than the authors of this paper.

On 2020-01-31 21:32:38, user Jason Weir wrote:

I blasted each of the four 2019 - nCoV inserts shown in Table 1 and received 100% identity with a number of other hits other than HIV-1. For example, BLAST-P results for insert RSYLTPGDSSSG received 100% identity with Spike glycoprotein from a bat coronovirus with Genbank accession number GenBank: QHR63300.1. It is thus much closer to a known bat coronovirus than it is to HIV-1. Likewise each of the other three inserts have 100% amino acid identity to other non-HIV sources. The paper is thus highly misleading in that it does not discuss the other blast hits to non HIV-1 related sources, some of which have higher similarity than those from HIV-1. The implications of the paper that 2019 - nCoV coronovirus has elements of HIV-1 virus inserted into it should be treated with skepticism.

-Jason Weir (Department of Ecology and Evolutionary Biology, University of Toronto)

On 2020-01-31 21:30:00, user Nemo wrote:

"The finding of 4 unique inserts in the 2019-nCoV, all of which have identity /similarity to amino acid residues in key structural proteins of HIV-1 is unlikely to be fortuitous in nature."

Quick question: Are you using "fortuitous" to mean lucky, or random?

On 2020-02-09 05:26:04, user Anon wrote:

I do not see much value in this manuscript. The first publication discussed in this paper (“Uncanny Similarity...”) has already been retracted and its flaws have been pointed out in much depth. Similarly, the second paper has also been discussed much elsewhere, and alternative mammals have already been proposed with supporting evidence to contradict the snake hypothesis. Disappointment and waste of funds for this paper.

On 2020-02-09 05:03:28, user Troubled Reader wrote:

After reading this manuscript, I am troubled by the lack of acknowledgements and citations to previous research in the field.

I do not understand the justification for the ex vivo nature of these experiments. In vivo hydrogen and methane production from humans is routinely measured using hydrogen and methane breath tests in clinical settings for SIBO diagnosis. There have been numerous studies examining hydrogen and methane production in people who were administered a prebiotic, including inulin and pectin (Geboes et al. 2003, Chinda et al. 2004, Rumessen et al. 1994, Flatz et al. 1985, Andrieux et al. 1993 etc…). I do not see discussion of these results in the manuscript nor do I see discussions the merits of breath testing in humans versus an ex vivo model. What type of validation did the authors do to this model to establish its physiological relevance? I think if the authors read the aforementioned manuscripts, they will find that these results are largely established in vivo through breath testing so it is unclear exactly what these ex vivo experiments add. Not discussing this wealth of literature on the evolution of gases from the gut microbiota in humans after prebiotic treatment measured by breath tests will mislead the reader.

Additionally, the authors state that “methane production was dependent on the presence of Methanobacteria” without appropriate citations. The production of methane by gut methanogens is well established, but these manuscripts are not cited nor are their results acknowledged. As written, the manuscript may mislead readers into thinking that this study discovered that methane production is dependent on the presence of methanogens. Please consider citing the manuscripts listed below.

Miller et al. 1982 Enumeration of Methanobrevibacter smithii in human feces<br /> Miller et al. 1982 Isolation of Methanobrevibacter smithii from human feces.<br /> Pochart et al. 1992 Interrelations between populations of methanogenic archaea and sulfate-reducing bacteria in<br /> the human colon<br /> Bond et al. 1971 Factors influencing pulmonary methane excretion in man. <br /> Christl et al. 1992 Production, metabolism, and excretion of hydrogen in the large intestine.

On 2020-02-08 23:52:10, user Chung-chih Lin wrote:

https://uploads.disquscdn.c... thanks for your software. however, i have problems in segment neurons with their neurites. can you help me how to improve the setting in cellpose?

On 2020-02-08 18:40:02, user Worg Wis wrote:

Just a comment from the author group: There is a mistake in the above author order, Liron Rozenkrantz is first author, Noam Sobel is last author. This is correct in the attached pdf. We have asked bioRxiv to fix:-)

noam

On 2020-02-08 10:23:25, user Fernando Real wrote:

Great work! Would this parasite exposure favor a stealthy cell-to-cell spreading of L. amazonensis as we have previously demonstrated?https://onlinelibrary.wiley... <br /> Best wishes,

On 2020-02-08 02:03:41, user Mohamad Koohi-Moghadam wrote:

Great work! We developed a pipeline to discover metagenomics biomarkers without using reference database. It can be used also to discover novel viruses which their sequence is not available in the reference database. If you have whole genome sequencing it may useful.

https://www.ncbi.nlm.nih.go...

On 2020-02-07 15:48:11, user ahamad wrote:

I am Abdel Hamad, the senior author of the Cell paper describing dual expressers (DE) lymphocytes that are clonally expanded in patients with type 1 diabetes (T1D) and whose BCR encodes an autoantigen that cross-activates insulin-reactive T cells in T1D patients. These cells are rare in healthy controls (HCs) but detectable by imaging or those expressing HLA permissive to T1D.<br /> I read with amusement the above manuscript by Dr. Peters’s group. I have several comments on the manuscripts:<br /> First, we are glad that the group has been able to reproduce<br /> part of our findings of detecting CD5+CD19+TCRb+ cells in peripheral blood of a<br /> healthy control.<br /> Second, we are happy that the group has been able to detect DEs. We are happy that the group has been able to detect what they called real DEs using imaging cytometry. <br /> In Fig. 4F, the group detected six real DEs by OPT imaging, confirming<br /> our results that DEs or X cells are real cells that exist in peripheral blood<br /> even in healthy controls – These cells are generally much higher in T1D<br /> samples.<br /> However, we are a little bit taken back and amused by how<br /> the manuscript was written given my previous discussion with Dr. Peters. I have<br /> clearly told Dr. Peters that there are two subpopulations of TCRb+IgD+<br /> lymphocytes and that those expressing high level of TCRs are doublets whereas<br /> most of TCRb-low subpopulation are DEs. He was receptive to that conclusion and<br /> acknowledged it. <br /> I clearly told him in my email that we were able to distinguish<br /> between DEs and doublets by rerunning sorted lymphocytes. When we do so,<br /> doublets always fall apart whereas DEs remain as singlets. However, Dr. Peters<br /> group failed to do so in their analysis and they included both TCR-hi and<br /> TCR-low thereby reducing frequency of DEs.<br /> In addition, the group did not include analysis of coexpression of TCRb and IgD, which is the main characteristics of DEs and from which the name is based to denote coexpression of immunoglobulin and TCR in the same cell.

In conclusion to this first part of my comments, Peters<br /> group has been able to detect DEs in peripheral blood of healthy control. In<br /> addition, they detect a lot of doublets which is expected given the way they draw<br /> their gating and given the paucity of DEs especially in healthy controls.

In my second coming comment that I will write later, I will<br /> go in some specifics and include figures on how to distinguish between DEs and<br /> doublets.

On 2020-02-06 22:08:49, user ahamad wrote:

Comment #2 from Dr. Hamad, senior author on DE cell paper.

In continuation to my previous response to the article by Dr. Peters group (see comment#1), I am reiterating that Dr. Peters group did see what they called real DEs in peripheral blood of healthy control even though they did not use a stringent gating strategy. <br /> In our hands, we do our best to minimize inclusion of doublets by using careful series of gating.

To distinguish DEs from doublets, we carefully gate CD5+CD19+ lymphocytes and then select DEs based on the coexpression of TCRb and IgD (IgD+ DE cells, main focus of Cell paper, see Fig. S5A and 5B and attached plots). In addition, we do as much as possible to avoid TCRhi IgD+ cells. This is because when TCRhi CD19+CD5+ cells were sorted and FACS re-run and analyzed for TCR and IgD expression, they often turn out to be mostly doublets that fall apart into Bcon and Tcon compartments. On the other hand, the majority yet not all TCRint CD19+CD5+ cells remain singlets and identified as DEs. Here is a link to the paper: https://www.cell.com/cell/f...

In the case of Dr. Peters group, they jumped immediately from CD5+CD19+ to analyze for TCRb vs SSCA (I wonder why they did not gate for TCRb+ IgD+ to identify real DEs).

In another mischaracterization of our data, Peters group admitted that our imaging data show a convincing DE. Then they wrote “Thus, our concern is not that the DE cell presented in the Ahmed study is not real, but rather that large parts of their subsequent experiments were solely based on non-imaging flow cytometry and the assumption that DE cells are always singlets”. This assumption is not true because in the Figure legend we show a representative DE out of at least 10 per sample (Fig. 1). In addition, in supplementary Fig. S2 we showed representative CD4+, CD8+ or double negative DEs. In addition, in same Fig. S2 we showed coexpression of lineage markers. Moreover, functionally we showed that DEs remained intact upon TCR activation for weeks (see Fig. 3). <br /> On a practical note, we would have never identified a clonally expanded DE population in T1D patients if we were chasing doublets given the extreme diversity of the BCR repertoires. Thus, our findings that DEs in three unrelated T1D patients who are analyzed at different time points over more than one year span by an independent agent (Adaptive biotechnologies) have the same dominant clone in the three different individuals would be mathematically impossible if we were chasing an artefact/doublets due to extreme diversity of B cell repertoire. Moreover, the idiotype expressed by the clonally expanded DEs in T1D patients is biologically relevant as it encodes a potent T1D-related autoantigen. .

On 2020-02-02 05:25:34, user Babu M wrote:

Dear authors,

Amazing findings, Congrats. Out of curiosity, authors has collected and cryopreserved <br /> Human PBMC's first; and performed experiments later on. Based on published literature, cryopreservation has significant role on adhesion molecules of cells. Either way, is there any possibility of correlation in between cryopreservation with cell-cell complexes modulation on this article context ? <br /> Thanks in advance.

Best regards, <br /> Babu Mia<br /> mdbabumia777@gmail.com

On 2020-02-07 13:38:28, user Keith Robison wrote:

Nanobind disk in description should add (Circulomics)

The paragraph on turnaround time would benefit from specific estimate of the time required for this process and for the currently clinically used methods (karotyping and array methods).

In addition to the list of abbreviations, the first use should explain the abbreviation

On 2020-02-07 11:42:41, user mlhnrca wrote:

"Among acylcarnitines, acetylcarnitine (C2) and the hexanoylcarnitine (C6-DC/C8-OH) showed the greatest absolute differences in baseline values between cases and controls (7.54 µM versus 9.92 µM (p=0.54) and 0.12 µM versus 0.08 218 µM, respectively)."

Those p-values are not significantly different, so it's misleading to state that there were concentration differences.

On 2020-02-06 23:47:49, user Hualan Liu wrote:

This is pretty cool, Casey! We just had a DOE SFA call and tracking GMOs is one of the main tasks. Looking forward to your work on this area!

On 2020-02-06 16:59:44, user Francisco Ferreira wrote:

Paper published with the title "Transcriptomics and proteomics reveal two waves of translational repression during the maturation of malaria parasite sporozoites" in Nature Communications.

On 2020-02-06 16:06:15, user Clive Thomason wrote:

Regarding figures, Wuhan as a population 11m, is assumed hospital beds at 1:400/1:500 , so 22,000 to 27, 500 beds. 50% allocated to flu cases, giving average 12400. Adding clinics and temporary approx 6,000, plus the 2 new prefabricated additional 2300. In total some 20,700 available. <br /> On 27th January they received 31,934 fever patients. They have RO of 1.237. 1.192. 1.194. 1.191. 1.158.from 1st February to 5th. <br /> With a suspected ratio to confirmed of 7:1 that would mean currently over 196,000 fever/suspected cases as of 6th February with 20,700 bed places. As it is flu season, not to be unexpected, but it will account for various figures as such.<br /> The RO value will drop as more will be quarantined at home due to lack of beds. At least 50% would have mild symptoms and not recorded.The reported deaths will be a lower % of infected due to figures only reporting those that died after testing. Therefore as a lower end of 1.158/196,000, the true death rate could be 2,254. <br /> Conclusion, the true infected rate most probably could be 3.5 x and true death rate 4x.

On 2020-02-05 11:11:05, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs:<br /> nCoV-nsp1, nCoV-nsp2, nCoV-nsp3N(adrp), nCoV-nsp3c(PLP), nCoV-nsp4, nCoV-nsp5, nCoV-nsp6, nCoV-nsp7, nCoV-nsp8, nCoV-nsp9, nCoV-nsp10, nCoV-nsp11, nCoV-nsp12, nCoV-nsp13, nCoV-nsp14, nCoV-nsp15, nCoV-nsp16, nCoV-S, nCoV-orf3, nCoV-M, nCoV-orf6, nCoV-orf7a, nCoV-orf7b, nCoV-orf8, nCoV-orf9, nCoV-orf14, and nCoV-N; SARS-nsp1, SARS-nsp2, SARS-nsp3N(adrp), SARS-nsp3c(PLP), SARS-nsp4, SARS-nsp5, SARS-nsp6, SARS-nsp7, SARS-nsp8, SARS-nsp9, SARS-nsp10, SARS-nsp11, SARS-nsp12, SARS-nsp13, SARS-nsp14, SARS-nsp15, SARS-nsp16, SARS-S, SARS-orf3, SARS-M, SARS-orf6, SARS-orf7a, SARS-orf7b, SARS-orf8, SARS-orf9, SARS-orf14, and SARS-N; and the receptor human ACE2

On 2020-02-04 16:45:35, user Clive Thomason wrote:

Not being a medical person, the statistics and analysis interest me. The EG, ML an<br /> d R are so variable at present due to reliability of reporting. As the confirmations can run from 4 to 14 days from first presentation to clinic, then the R value can be from 1.195 to 2.2 as so far extrapolated. When putting this into my spreadsheet, it can give a figure by 29th feb of EG from 550,00 to ML 2.2m. So very variable. Then also as within a given % of infected how many of those are positive or negative within a 4 day window that would not show in statistics. I also take into account on R value, the infrastructure of a country, the health care available and the lifestyle at large, which gives the R value of China compared to USA as 1.196 to 1.091. So very difficult to tell until 6 weeks statistics are available

https://docs.google.com/spr...

On 2020-01-27 10:40:55, user New CoV wrote:

the generation time is fixed for the new coronavirus to be the same as for Sars in the analysis and r0 for new coronavirus is somewhat higher - an alternate explanation would be shorter generation time for the new coronavirus?

On 2020-02-06 15:59:37, user Nathanael Rollins wrote:

Hi Surge and Grig, shortcutting hard experiments by leveraging natural sequences is a great goal- in that direction, I think you need to benchmark against unsupervised models that enable “no N”

There’s enormous data already available in natural sequences- so the burden of “high N” doesn’t necessarily fall on wet lab, it’s often satisfied by existing sequence databases. Unsupervised models with “no N” initial variants can be used to engineer novel proteins, e.g. Socolich (2005). And unsupervised training on just natural sequences can create accurate generative models for many proteins, see Hopf (2017), Reisselman (2018) & (2019-preprint).

Your model UniRep is also using natural sequences- maybe layering it behind a second supervised learning task is creating a false bottleneck? Not all sequence design faces the constraint you outline, so consider moderating the text. Likewise, I’m curious, see if these designs could be found using an unsupervised model and not even require supervised data points!

On 2020-01-30 13:43:45, user frédéric cadet wrote:

Dear Authors, Supplementary Figure 12b is not correct. Indeed, Cadet (2018) is clearly "Extrapolative". See Figure 10 for Ref 32. Best regards.

On 2020-02-06 13:42:24, user didier Fesquet wrote:

"We show that APEX2 labeling of the NL is robust and requires as little as 20 seconds."...so highly better than BioID...

On 2020-02-06 10:17:06, user Stefano Campanaro wrote:

Dear Daniel and Kiran,

we read your paper and we think it is really outstanding and has the potential to become a milestone of MFB applied to microbial community functional organization. Since the microbial communities considered for the analysis are really diverse in terms of ecological niche, we were just wondering how you defined the medium and how you integrated it into the simulation.

Thank you in advance for any answer, for posting the preprint and for making pipelines available in Git (sharing is caring).

Sincerely,

Stefano Campanaro and Arianna Basile

On 2020-02-05 23:58:01, user Tamara Potapova wrote:

Great paper! Is it possible to take a look at the Table S1? I don't see a link to it anywhere for some reason.<br /> Thank you!<br /> Tamara

On 2020-02-05 19:13:31, user Llevar wrote:

This manuscript is now published Nature Biotechnology - https://www.nature.com/arti...

On 2020-02-05 11:57:49, user giuliocatalano wrote:

The paper was modified after referees suggestions.

On 2020-02-05 11:15:23, user Pei-Hui Wang wrote:

Forward to you friends who needs. Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs:<br /> nCoV-nsp1, nCoV-nsp2, nCoV-nsp3N(adrp), nCoV-nsp3c(PLP), nCoV-nsp4, nCoV-nsp5, nCoV-nsp6, nCoV-nsp7, nCoV-nsp8, nCoV-nsp9, nCoV-nsp10, nCoV-nsp11, nCoV-nsp12, nCoV-nsp13, nCoV-nsp14, nCoV-nsp15, nCoV-nsp16, nCoV-S, nCoV-orf3, nCoV-M, nCoV-orf6, nCoV-orf7a, nCoV-orf7b, nCoV-orf8, nCoV-orf9, nCoV-orf14, and nCoV-N; SARS-nsp1, SARS-nsp2, SARS-nsp3N(adrp), SARS-nsp3c(PLP), SARS-nsp4, SARS-nsp5, SARS-nsp6, SARS-nsp7, SARS-nsp8, SARS-nsp9, SARS-nsp10, SARS-nsp11, SARS-nsp12, SARS-nsp13, SARS-nsp14, SARS-nsp15, SARS-nsp16, SARS-S, SARS-orf3, SARS-M, SARS-orf6, SARS-orf7a, SARS-orf7b, SARS-orf8, SARS-orf9, SARS-orf14, and SARS-N; and the receptor human ACE2

On 2020-02-05 11:14:40, user Pei-Hui Wang wrote:

Forward to you friends who needs. Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-05 11:13:37, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-05 11:13:06, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-04 21:18:33, user Arunachalam Ramaiah wrote:

Authors Response: <br /> Thank you for highlighting the insignificant homology of the 39 bases with fish and we have removed this sentence. The updated version has been submitted that will be available shortly. Our key conclusions are that the 2019-nCoV may have evolved from bat-CoV and described T-cell epitopes with high binding affinity to HLA-DR alleles from different population sets, which can be useful for vaccine development.

On 2020-02-04 09:30:07, user Rhys Parry wrote:

In the past few weeks we have seen some interesting in silico analyses about the genomes that have been sequenced for the novel Coronavirus (2019-nCoV) outbreak. Some attempt to infer the potential host range or evolutionary history from the genome. Here Ramaiah and Arumugaswami suggest that a 39nt insertion in the 2019-nCoV genome bears similarity to the fish genomic sequence of Myripristis murdjan. BLASTn analysis of this 39nt insert reveals that 31nt of that 39nt (TTGAAGGTTTTAATTGTTACTTTCCTTTACA) has 90.2% similarity to the region 11671777-11671807 of Myripristis murdjan genome, chromosome: 21 (LR597570.1) TTGAAGGTTTTACTTGTTATTTTCCTTGACA.

While it looks very much like these two nucleotide strings have high 'Identity', in terms of pairwise alignment, it does not imply that there is a meaningful or ancestral link between the two sequences. In fact the expected value (E-Value) of this alignment is 0.24 which has been omitted from the paper. If you keep in mind that the BLAST E-value is the number of expected hits of similar score that could be found just by chance. Given the entire non-redundant database size the alignment between nCov-2019 and Myripristis murdjan has a score of 43.7. Therefore we expect find 0.24 hits based on chance alone given this score and this size of library.

The authors suggest that "This observation suggests an interesting hypothesis that a marine CoV affecting fish could be a possible source for the virus recombination and evolution." Given that the only evidence for this statement presented is this BLASTn analysis it appears unlikely that this is due to anything but chance.<br /> Rhys Parry - University of Queensland

On 2020-02-05 11:12:53, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-05 11:12:33, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-05 11:08:51, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, orf3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-05 11:01:00, user Pei-Hui Wang wrote:

Prof. Wang Pei-Hui Lab in Shandong University, China, all orf clones of 2019-nCoV / SARS in pcDNA6B-FLAG can be freely requested, please contact him. Email: wphlab@163.com covering the following orfs: nsp1-16, S, 3, E, M, orf6, orf7a/b, orf8, orf9, orf14, N; and ACE2

On 2020-02-05 05:33:27, user Aaron wrote:

The article is now peer reviewed and published - why not update? https://www.nature.com/arti...

On 2020-02-03 14:00:09, user jean-claude perez wrote:

Please visit https://www.preprints.org/m...

On 2020-02-02 11:45:57, user Jubin Rodriguez wrote:

Quick questions: a) How many million PE reads were generated in total per sample and what percentage of these raw reads were represented by human DNA? b) What is the virus database that the authors used in their analysis? In case its an in-house database, I'm curious to know if it is based on sequence info available on NCBI and how it was built? c) I'm also curious to know if the authors tried any of the metaviromics tools out there (as opposed to read-mapping against a database of known viruses) so as to detect this novel corona virus? My guess is that most metaviromics tools (for e.g., FastViromeExplorer, virMine) may miss this virus.

On 2020-02-01 17:46:50, user Hongda Liang wrote:

WIV4 is first mentioned here: https://www.microbiologyres...

On 2020-01-28 18:03:17, user John Harris wrote:

A clinical trial is in progress, using Abbvie's Kaletra (R) as a medication against 2019-nCoV. Kaletra(R) combines two protease inhibitors. It was developed to act against the viral protease of HIV 1. This is an aspartic type protease.

Curious to know if the bat sequence shows the nature of the protease encoded by 2019-nCoV, and if it is also an aspartic protease.

On 2020-01-27 10:58:37, user jean-claude perez wrote:

Please find here an updated release including 2 releases of wuhan coronavirus génome.

Using the following theoretical numerical approach of génomes data (pdf), I proove évidence of long range numerical standing waves structuring DNA genomics séquences:

https://www.google.com/url?...

THEN, <br /> I briefly analyzed the standing waves of 7 SARS genomes ranging between 2003 and Wuhan 2020:<br /> There is an evolution increasingly directed towards Fibonacci waves, as follows:

Fibonacci Wave Genomes:<br /> Sars2003. No. 5<br /> Sars2004. No. 5<br /> Sars2004b. No. 5<br /> Sars2015. 5 8. 13<br /> Sars2017. 5 8. 13<br /> Wuhan2020old 5 8 13 21<br /> Wuhan 2020. 5 8. 13. 21<br /> Where 5 8 13 21 are Fibonacci numbers numerical standing waves.<br /> That is a formal proof of an évolution increasing global structure of SARS whole genomes, probably linked with génome intégrity and coherence and, probably pathogeneciity.

On 2020-01-24 13:44:23, user Yen Shu Chen wrote:

The authors did not share (no GenBank/GISAID accession number are <br /> provided) the genome sequence of the critical bat-CoV that represents a <br /> close relative to human 2019-nCoV. <br /> No way to access/reproduce/further use their result. Do scientific journals accept such practice?

On 2020-01-24 13:09:06, user Yen Shu Chen wrote:

The authors did not share (no GenBank/GISAID accession number are provided) the genome sequence of the critical bat-CoV that represents a close relative to human 2019-nCoV. <br /> No way to access/reproduce/further use their result. Do scientific journals accept such practice?

On 2020-01-24 09:36:54, user Dirk Jochmans wrote:

Great paper, a lot of info on the nCoV and the first patients. Thanks!

On 2020-01-24 09:13:52, user ani1977 wrote:

Very timely publication! And thanks for releasing the data :) I see the genome https://www.ncbi.nlm.nih.go... based on mapping as far as i could read the M&M, wondering if de-novo assembly was also performed? Otherwise the read shared generously seem to be there at http://virological.org/t/pr... and I can give it a go... BTW why HeLa for "Determination of virus infectivity" (Fig. 4) as we think it may not be good system for it given that we have shown antiviral response just with mock transfection https://www.sciencedirect.c...

On 2020-01-23 18:56:53, user Xiaotong Yao wrote:

This is why we do open science. Timely release of raw data and analysis can make a huge difference to the society and people's lives.

On 2020-02-04 18:15:39, user Federico Giorgi wrote:

Currently under review

On 2020-02-04 18:13:39, user David Curtis wrote:

The approach seems to be somewhat similar to the one we used in these papers:<br /> https://www.biorxiv.org/con...<br /> https://www.nature.com/arti...<br /> https://link.springer.com/a...

Also, in this paper we used ExAC to provide control allele frequencies: <br /> https://journals.lww.com/ps...

However we found this did not work well, presumably because of some difference in the genotype-calling algorithms. ExAC claimed variants were extremely rare whereas in reality they were quite common in UK subjects. That was a few years ago, so maybe things are better now.

On 2020-02-04 16:05:19, user PZM Diagnostics wrote:

This article has been accepted for publication in Fetal & Pediatric Pathology, published by Taylor & Francis"

On 2020-02-04 13:04:44, user Benjamin Orsburn wrote:

Extended figure #4 may be my favorite visualization of anything I've seen in 2020. I hope it makes it into the main part of the final paper (or features more prominently than where it is.

On 2020-02-04 13:02:37, user Triex Keiseki wrote:

I am just curious, why has no one considered something like the Oral Polio Vaccine. eg; 'Sugar cubes' with the live-attenuated virus to induce immunity?

'This study is among only a handful, many of which were performed decades ago, to study OPV transmission at the community level, as well as being among the very few in environments that mimic those required by the Polio Eradication and Endgame Strategy, where OPV and IPV are used concurrently during a controlled switchover. [sic:https://www.ncbi.nlm.nih.go...]

Not my field, but seemed like something to put forward.

On 2020-02-04 10:53:08, user David Escors wrote:

The published peer-reviewed version of this paper can be found in: https://www.mdpi.com/2072-6...<br /> https://doi.org/10.3390/can... (registering DOI)

On 2020-02-04 09:03:12, user Sebastian wrote:

Great paper! Regarding Fig. 6b: IL-11 tends to activate stat in vitro only at rather high concentrations and when the cells are cell lines and become transformed through extended culturing. I would blot for non-canonical pathways such as ERK and you should see the activation in organoids and primary cells. Keep up the good work, Sebastian Schafer

On 2020-02-03 17:39:23, user Mohammed David Zhang-Singh wrote:

How's abaout a T cell epitopes and generating memory T cells? A much faster approach.

On 2020-02-01 05:34:09, user Robert Kruse, MD, PhD wrote:

Given that this antibody does not block receptor binding, it can not be described as neutralizing in the classic sense, since viral replication should continue forward. Furthermore, it is likely that the virus could easily escape whatever pressure is exerted by this antibody since it appears to not bind to an essential epitope. The authors should emphasize that in vitro infection assays need to be undertaken to truly interrogate how these antibodies might work. The findings of a lack of cross-reactivity of the SARS RBD antibodies is interesting though, emphasizing the challenge it will be to identify new monoclonal antibodies for 2019-nCoV.

On 2020-02-03 17:15:55, user ncc wrote:

Hi

Nice setup, and well described. I enjoyed reading the paper. However, I disagree with the overall focus: that high-throughput, or obtaining the maximum number of replicates, is a desirable goal in respirometry.

I have built similar IFT setups, as have *many* others. I would suggest the only really "innovative" aspect of this setup is that you are utilising the downtime during flushes to measure oxygen in different chambers. That is, getting maximum utility out of your 10 channels. However, this is only useful in **very** limited circumstances where the measurement period is comparable in length to the flush period. That is, species with very high metabolic rates and/or at high temperatures.

However, i would question the entire practice of doing flushes so frequently if this is the case. It suggests to me your chambers are not large enough if the oxygen is being depleted so rapidly.

High throughput should not be an end in and of itself if the resulting data are not representative of SMR or RMR. This is especially true of experiments where the specimen may be easily disturbed, as in fish respirometry. Are you absolutely sure your fish were not disturbed by the pumps coming on every 8 minutes, either via increased vibration, sensing the water has been changed, or changes to the water flow patterns? Is the 1 minute of data you exclude from the start of each measurement period sufficient time for the specimen to resume "normal" behaviour after a flush?

I have recently run IFR flow experiments on a fish. These were on a temperate species, in a fairly large relative volume and took roughly 2-3h to show a decrease of around 10%, whereas a flush took 5 minutes. However, we found that for around 2h after a flush, the fish's metabolic rate was still decreasing, that is, it was still elevated and had not yet reached what could be defined as RMR, let alone SMR. As a result we decreased our replicates from 4x 2h replicates to to 2x 3/4h ones, and as a result got much more consistent data. In this case, high throughput, numerous replicates would not have given us a better estimate of RMR, in fact would have provided a much worse one. Every species is different, but i would 100% **always** choose fewer longer duration replicates, than numerous high-throughput replicates as described here.

A few other points:

There is NO fundamental difference between closed and IFR respirometry. IFR is simply having an apparatus that allows for multiple, sequential closed respirometry experiments to be run easily, minimising disturbance to the specimen. They are otherwise identical in nature. IFR respirometry is simply multiple closed respirometry experiments, and comes with *exactly* the same drawbacks that you suggest for "closed" respirometry. How important these are or if they are of no consequence at all depends on multiple factors in the experiment: the organism, water volume, duration, temperature etc, but most importantly the oxygen saturation level the experiment is allowed to reach. It is **completely incorrect** to say closed chamber respirometry is inherently associated with accumulation of nitrogenous waste and carbon dioxide, and increased stress, and that IFR is not. You can have these occur in both methods depending on how low long the experiment proceeds.

The article you cite here (Snyder et al. 2016) is concerned with a completely different question, that of critical oxygen tensions, and the difference between *methods of inducing hypoxia*, either via degassing with nitrogen or via the animals own metabolism. This study is *not* a comparison of these two methods for determining SMR or RMR, but for determining hypoxia tolerance.

I have run many "closed" respirometry experiments over long durations where oxygen decreased by only a few percent, and there was negligible build-up of waste or CO2. Given these experiments allowed specimens to be completely undisturbed for many hours, I would argue this is more likely to provide better estimates of SMR or RMR than any number of high-throughput, replicates that this or other IFR methods may produce.

Whether or not to use closed or IFR methods is a mostly practical question, but fundamentally these methods are exactly the same.

Other comments:

• You mention no correction for tubing volume. The water volume of each experimental loop consists of the water in the chamber plus that in the tubing in the loop. If this was exactly the same for all chambers then that is an easy correction. However the fact that (according to your schematic) your recirculation pump was at one end of the apparatus suggests a possibility there might have been different lengths for the close chambers than the ones furthest away, which will cause a systemic error. Happy to hear otherwise, but either way it is a necessary correction (i don't see it mentioned in the R script either, but there the volume is 0.375 not 0.300, so maybe this is it?)

• You also mention no correction for fish displacement volume. Your 300mL chamber does not contain 300mL once you put the fish in. The fish displaces some of the volume, and bigger fish will displace relatively more, so this leads to systemic error across body size ranges. Working from your data sheet, this is anything from 2-8% of the volume (assuming the fish are roughly neutrally buoyant) which would cause a misestimate of oxygen use, directly biased towards larger specimens. Your true "effective volume" is the chamber volume, plus tubing volume, minus fish volume.

• There are at least two open-source software solutions for conducting and reporting respirometry analyses (full disclosure - i am developer of one of them) which you should mention:

Harianto, J., Carey, N. & Byrne, M. respR -An R package for the manipulation and analysis of respirometry data. Methods Ecol. Evol. 10, 912–920 (2019).

Morozov, S., McCairns, R. J. S. & Merilä, J. FishResp: R package and GUI application for analysis of aquatic respirometry data. Conserv. Physiol. 7, (2019).

These allow investigators to report their analyses transparently and in reproducible form. Investigators who are skilled coders might choose to use their own workflows, but these are aimed at those who are not. I have another package with some utility functions: https://github.com/nicholas...

Please do get in touch if this was useful. Happy to discuss these aspects more!

Regards, Nick

On 2020-01-29 18:27:35, user Chelsea Grace Drown wrote:

This is the best methods paper ever! So insightful and innovative! Ecology is headed in the right direction

On 2020-02-03 15:55:19, user Sudin Bhattacharya wrote:

Now published as https://link.springer.com/a...

On 2020-02-03 09:31:09, user Douglas Philip Dyer wrote:

Interesting paper, we had a couple of recent (ish) papers that might be of interest to you in respect to the interaction between CCL5 and GAGs and the biophysical effects of this interaction.<br /> https://www.ncbi.nlm.nih.go...<br /> https://www.ncbi.nlm.nih.go...

On 2020-02-02 22:33:40, user Andrew Rambaut wrote:

When the sequence EPI_ISL_403928 was first submitted to GISAID on the 11th of January it contained numerous artefacts of the sequencing method used. This was later fixed and the current version of EPI_ISL_403928 contains none of these errors. It has 1 SNP difference from most of the other Wuhan genomes. These artefacts are what give the authors the apparently divergent strain. They should download EPI_ISL_403928 again and redo their analysis to confirm this.

On 2020-02-02 07:28:12, user tian maller wrote:

I want to use durgbank's dataset .How can you modify the code to see the prediction of the drug-target

On 2020-02-02 06:36:32, user Xifeng Lu wrote:

Hi Frederique, nice piece of work! Adds lots of information on how (P)RR and its soluble form regulate lipid metabolism. Would be very interesting to explore how hepatic (P)RR deletion signals to the adipose tissue to increase PRR expression.

On 2020-02-01 18:29:02, user Donna Carpenter Smythe wrote:

Insightful read..congratulations on your methods for sterile inner core sampling..looking forward to further research on these extremely important glacial novel microbes and their implications.

On 2020-01-25 22:51:02, user Adrian wrote:

A fascinating report. I'd love to know whether the gene sequences found are related to those obtained from ocean samples, as I suspect they will be. Sea spray dried, and then blown everywhere, deposited with snow on glaciers?

On 2020-02-01 17:07:00, user Chengxin Zhang wrote:

Supplementary material, especially Table S4 is unavailable, even though it was<br /> mentioned in the manuscript: "To explore other potential reservoirs, we <br /> scored all the available vertebrate viruses in GenBank, filtered viruses<br /> that have similar infectivity pattern with 2019-nCoV (Table S4)". Are these data are available for download somewhere?

Also,<br /> is the Convolutional Neural Networks developed in this work available <br /> either as a web-sever or a standalone package to allow reproduction of results?

On 2020-02-01 15:40:37, user Levi Yant wrote:

Magdalena Bohutinska and Mark Alston contributed equally.

On 2020-01-31 21:27:17, user Chris Merrikh wrote:

This paper is written in a deceptive and unprofessional manner. The authors' claims about our 2018 Nat. Comm. manuscript (PMID 30405125) are factually incorrect. We will address this matter in the form of a peer-reviewed response.

On 2020-01-31 17:46:16, user Arthur Brandao, PhD wrote:

Congratulations to all authors for having<br /> done this work. I hope the authors can increase the number of participants (F<br /> and M) to further support all these interesting results.

On 2020-01-31 16:37:32, user Jonathan Weissman wrote:

The more complete descriptions with of our analysis of pharmaceutical grade Rigosertib is now available at https://www.biorxiv.org/con...

On 2020-01-31 13:22:11, user Silas Kieser wrote:

Thank you for this preprint. I was looking up your parameters for the gene clustering. For your information, the parameter you used wouldn't prevent partial genes to become the cluster representatives according to the docs (https://github.com/soedingl....

On 2020-01-31 06:11:16, user Dai Mitsushima wrote:

I modified Figure 7, because some neurons seem to be less plastic. Version 7 or later is OK.

On 2020-01-31 00:46:52, user Charles Warden wrote:

Thank you for posting this interesting and well-organized paper!

On 2020-01-30 17:48:43, user Ming Ming wrote:

Correction (Line 192): <br /> to 34,736 as of 10th February<br /> compared to 115,355 without public health interventions (Scenario 2).

On 2020-01-28 21:51:23, user Cyborg Gabe wrote:

A 14% daily probability of death if hospitalized vs only 1.5% daily recovery probability if hospitalized? That means ~90% of hospitalized cases will die. Can that be correct?

On 2020-01-30 17:29:39, user K. Amikura wrote:

All your feedback is really welcome!

On 2020-01-30 17:28:42, user Ayush Arpit Garg wrote:

Hi, this is really impressive work and a great follow up article from your previous Nature Materials article. Esp the aspects of the spatio-temporal control using this novel bioreactor address the critical need to modernize the electrotaxis chambers for better control and enhance our overall understanding of electrotaxis. I had a few follow up questions:

1) One of the main findings of this article was the ability of cells to rapidly sense electric fields. As a matter of fact, the time scales suggested are on the order of less than 10 sec. In this study, the EF strength was approximately 2 V/cm, do you think there is any correlation between field strength (or more accurately current density) time scales of cells to sense such fields.

2) Following up to the previous question, is there a minimum threshold of field (or current density) above which the cells can sense and respond to these external fields. The literature points out that for electrotaxis, field strength should vary between 0.5 V/cm to 10 V/cm. Can you speculate, if the cells respond to fields weaker than this threshold value.

3) In your previous article, you had shown that the leader cells have different responses to EFs compared to the cells in the bulk. The speculation was that the leader cells are indeed different as they do not have the same cell-cell junctions like the cells in the bulk. Is there any evidence suggesting that the time scales of their response might be different from cells in bulk?

4) Have you guys looked at F-actin and/or FAK changes at different time points. Is there any evidence suggesting that cells gradually time-average the net electric fields other than their ability to migrate in the direction of applied electric fields. Moreover, the force on the cell membrane components due to these external fields is what causes cell polarization leading to directed migration, so does it not in turn mean that the net force of these external fields is indeed responsible for migration?

5) This is my final question, so the final idea is to be able to control and direct cell migration for real world application. What is the long term vision in terms of clinical translation of this technology? Moreover, most cells respond to such electrotactic/galvanotactic cues, therefore, when they are applied to a complex tissue with different cell types, depending on their nature they can decide to move towards the positive or the negative electrode, have you guys though of any solutions on how to target migration of specific cells in a complex tissue.

Overall, this is a really great article with novel methodology and some very intriguing results.

Thanks!

On 2020-01-30 16:06:45, user jimi Zeng wrote:

A related paper: https://doi.org/10.1038/s41... <br /> Single-cell analysis reveals new evolutionary complexity in uveal melanoma

On 2020-01-30 13:34:31, user M AKI wrote:

Is supplemental data available? Would be nice to provide it.

On 2020-01-30 11:45:12, user Gabba Gabbawui wrote:

Hi! is there in BITE any function to plot MDS using the same colors as given in the admixture membercoeff.circos components?

On 2020-01-30 09:30:32, user Dirk Jochmans wrote:

It should be clearly stated that this is all in-silico screening. Just to be clear. I also don't understand that there are <br /> 8,000 clinical drug libraries with guaranteed safety? I believed there are only ~2000 approved drugs?

On 2020-01-30 06:26:08, user Elina Kivovich wrote:

the link to the software is not working

On 2020-01-29 22:19:10, user Vivek Bhardwaj wrote:

Hello. Congrats on this quick TSS profiling method! It would be nice to have at least a qualitative comparison of your protocol with our MAPCap method, published last year.

https://www.nature.com/articles/s41467-019-11115-x

On 2020-01-29 19:47:53, user Daniel Corcos wrote:

A follow up of this article has been published in the New England Journal of Medicine: <br /> Corcos D, Bleyer A (2020). "Epidemiologic Signatures in Cancer". N Engl J Med. 382 (1): 96–97. doi:10.1056/NEJMc1914747. PMID 31875513.

On 2020-01-29 15:17:36, user David Minde wrote:

fully published now: <br /> Biotin proximity tagging favours unfolded proteins and enables the study of intrinsically disordered regions https://t.co/oNY0QtIRjq https://t.co/6cLLtRu60j

On 2020-01-29 08:05:36, user elsässerlab wrote:

Dear authors, thank you for citing our work, please note that our quantitative study (here https://www.biorxiv.org/con... or at Cell Reports) does not support your hypothesis that H3K27me3 is reduced at CGIs in the naive state.

On 2020-01-29 05:19:38, user Jessica Bellworthy wrote:

Small comment: In your methods for carbohydrate analysis you write that the standards are BSA protein - i think this is an error

On 2020-01-29 01:10:43, user carlk2 wrote:

New Ludicrous Speed #GWAS feature: Multiple phenotypes at (almost) no extra compute cost. Do 1M individuals x 1M SNPs x 1000 pheno w/ accuracy and sensitivity of linear mixed models.

See an example in the notebook: https://nbviewer.jupyter.or...

On 2020-01-28 21:29:13, user Kevin King wrote:

This paper is quite interesting, but I'm skeptical as to how exactly microgravity alters the expression of the Hfq mRNA. Could you propose a possible mechanism?

On 2020-01-28 21:11:15, user Charles Warden wrote:

It looks like there is an updated, peer-reviewed version of this article (although the title mentions 70,000 rather than 54,000 Exomes):

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

On 2020-01-28 16:42:23, user Philippos Tsourkas wrote:

Do you have plans to release a tool to identify Acrs in phage genomes?

On 2020-01-28 13:14:28, user Paulina Deptula wrote:

Very interesting work. I would be particularly interested in browsing the proteins in Supplementary Table 2. How can I access it? Currently Supplementary Material does not get displayed together with the manuscript.

On 2020-01-27 10:38:47, user Wiep Klaas Smits wrote:

May I suggest changing the Peptoclostridium to the (nowadays commonly accepted) Clostridioides?

On 2020-01-28 14:02:01, user Bowen Zhang wrote:

Nice work! but I think there is some Dec. 1st patient, would it be great if you can find those sample's sequence? as they may help to locate a more ancestral ancestor.

On 2020-01-28 00:52:49, user Charles Warden wrote:

I am not sure if this is something that can be changed at this point. However, there is another genomics suite (for mutation analysis) with the same name, and the same set of upper-case and lower-case letters:

https://gmt.genome.wustl.ed...

It's not unusual for names to get used for different purposes (especially for commonly used words), but I thought this might be worth keeping in mind.

On 2020-01-27 19:02:57, user Simon Frost wrote:

Some quick comments:<br /> 1. Add acknowledgements to the people who generated the data.<br /> 2. Include the data as analysed in the manuscript - the data themselves are not accessible directly via the link, and are rapidly being updated.<br /> 3. Include the code used to fit the model.<br /> 4. Describe how confidence intervals were obtained.<br /> 5. Discuss how/why the estimates of R0 are higher than those obtained by other groups.

On 2020-01-27 15:02:51, user Bernhard Ahrens wrote:

The manuscript would be benefit if the authors could provide the vertical resolution their root biomass estimates are referring to. What is the sampling depth of the individual studies? Can we be sure that all the roots were sampled or would it makes sense to include depth as an additional predictor in the random forest?

On 2020-01-27 01:34:19, user Petting My Dog wrote:

So according to the formula a 1 year old dog would be aged to 31 Years right?

By Petting My Dog

On 2020-01-26 23:51:15, user Bobb Craig wrote:

I realize that the following two publications were not peer-reviewed, but it is well know that both the Danes and Norwegians Vikings sailed to and had encounters with the Scots living in the Shires of Aberdeen, Kincardine and Forfar. My wonder is why there is no mention in your document at all, and especially on Fig. 1 "Map of the “Viking World” from 8th till 11th centuries." Was this just that you do not have any relevant DNA data for these areas?

"AN ACCOUNT OF THE DANES AND NORWEGIANS IN ENGLAND, SCOTLAND, AND IRELAND."

BY J. J. A. WORSAAE, For. F.S.A. London:

A Royal Commissioner for the Preservation of the National Monuments

of Denmark; author of “Primæval Antiquities of Denmark,” &c., &c.

WITH NUMEROUS WOODCUTS.

LONDON:

JOHN MURRAY, ALBEMARLE STREET.

1852.

and

https://www.electricscotlan...

On 2020-01-26 23:06:15, user rikster wrote:

R naught has almost no predictive value. Post mortem value only. For example, it never takes seasons into account, Norovirus for example. Its not only seasonal but the British call it Winter Vomiting Disease and they euphamize most everything!

Influenza is highly seasonal and its not one bug either. In fact its practically a variant or multiple variants for every infected person. What's its R naught? It depends not only on the bug but events in the season which we at welloinc.com have the data organized to show. We saw Wuhan on December 30th go through a low friction few days for big spread. Twice again in January. With a 10-14 day incubation period (spitballing), the events combined were resonant and hence the beginning of the epidemic. We see more to come. We can only see 3-5 days ahead. The problem with knowing this is the problem of the invisibility of infection. Countdown 10-14 days to knowing how things went. Right now we expect events from last week to see large upticks of cases in early February.

Not pretending to know much about this new coronovirus but the events that drove Wuhan are different than SARS2003. That SARS2003 blew up in and around South China gave it friction for spreading. I have all the indoor humidity data from 2003, most cities in the world. You'll see Toronto with very little friction, Hong Kong in March with three periods of low friction (high spread). You'll see the ease of spread at Amoy area (sewerage leak) and the days where the ease of spread at Prince of Wales led to two big waves in the hospital to visitors and health care workers.

We automated the marvelous work that Singapore did with SARS in 2003. They shut it down faster than any other country. They did it at borders, schools and hospitals. Turned out that except for one case, all the cases came from non-patients at hospitals.

This is a standard of care in some hospitals in the US. Also childcare and jails. www.welloinc.com for more informaiton rik.heller@welloinc.com . Put an exclamation mark or mark it important so I'll notice it over my daily deluge. Rik

On 2020-01-26 14:22:29, user Marty Chandler wrote:

Great job on the model … no question about that! But I was hoping to see some simulation results based upon real world data.

On 2020-01-23 19:51:51, user OriginalGangsta wrote:

I'm not a mathematician so I still don't know the R0. R we Naught above SARS or R we Naught below ebola? An actual number would be great here for us (majored in anything other than math) people.

On 2020-01-26 20:12:15, user Ken Spacek wrote:

Bastin report: When you consider how natural high biomass forests maintained the water cycle and now that they are severely reduced to less than 25% of their old growth state, due to current forest practice rules. High biomass reduces the amount of run off and this water is used to grow more biomass across continents, sequestering more carbon. Forests through photosynthesis and evapotranspiration ET transfer this water to the atmosphere for redistribution far from the source, at least 65% of all water that reaches land is from ET and the best producer of this water is high biomass forest. Water from this source maintains climates across continents lessening drought conditions. The Redwood climate connection

On 2020-01-26 06:00:30, user MD BABU MIA wrote:

Congratz , Dr. Daniel Heller. It's such a brilliant work. As per my working experience with carbon nanotubes ( as we are nanoparticles lab. ), in vivo administration of AF-SWCNT has significant effect on bone marrow. In term of spleen lymphocytes, they targetedly disrupts B cells & T cells, though T cells disease model yet to verify ( submiting nanotoxicology this month ). I would be very much interested to know, did you found the presence of AF-SWCNT in BM or lymph node ? <br /> Either way, i will happily cite your work in recent manuscripts.<br /> Best regards, <br /> Babu Mia<br /> (https://www.researchgate.ne... )

On 2020-01-26 05:28:00, user Nerd Tunnel Vision wrote:

Enhancers do encode RNA molecules.

On 2020-01-24 21:07:57, user MW wrote:

Is there actually some data or code s.t. I can get my hands on some actual AGs?

On 2020-01-24 18:29:36, user Lars Fritsche wrote:

Part of this research has been conducted using both the UK Biobank Resource under application number 24460 and also using results and data generated by previous researchers who have used the UK Biobank Resource.

On 2020-01-24 17:56:49, user Wang Gang wrote:

Our work develops a novel and practical strategy that achieves highly efficient genome editing in large animals. We used this approach to generate a selective germline genome edited pig (SGGEP)and xenotransplantation in several animal models, including NHPs were performed to test whether these genetic modifications combinations are justified for translational medicine applications and launching the clinical trial.

Our results showed that SGGEP skin graft could survive functionally on NHP up to 25 days without the administration of immunosuppressive drugs. Considering that a pig skin graft does not affect the success of a subsequent allograft, or vice versa, therefore, this is a major milestone for skin xenotransplantation and serves as a proof of concept to initiate investigator-initiated clinical trials (IITs) in severe, life-threatening burn patients.

As the skin is considered the vital, unique and immunogenicity organ, our preliminary success in skin xenotransplantation using the combination of multi-gene modified pig in NHP provides the approval of the concept, paves a way to initiate the other organ preclinical trial and clinical trial, implies a success of these organs’ xenotransplantation. Therefore, SGGEP could have the potential to become an unlimited organ source for future clinical transplantation.

Furthermore, our work provided a conceptual framework for selective genome editing for other large animals with other important purposes such as human diseases modeling, establishment of the disease resistant-large animals, etc.

On 2020-01-24 16:58:19, user Marcin L Pekalski wrote:

With regards to the above publication, we propose the possible mechanism and role that host-genetics, microbiome and dysbiosis play in the pathogenesis of Type 1 diabetes (T1D), please check: https://www.biorxiv.org/con...

On 2020-01-24 05:26:00, user Jeffrey Ross-Ibarra wrote:

Super cool. I believe this inversion on chr4 is the same that Mano and colleagues have found in Z. nicaraguensis and Z. luxurians. See here and related articles. I think it may also share at least one breakpoint with Inv4m in highland maize and Z. mays ssp. mexicana

On 2020-01-24 05:22:55, user Ramawatar Nagar wrote:

This is a great piece of work! Wondering what would be the case with other formae speciales of Fusarium oxysporum.

On 2020-01-24 01:12:11, user Nerd Tunnel Vision wrote:

The intrinsically disordered regions of most developmental transcription factors undermine the topological constancy of gene regulatory networks. This challenges their characterization as directed graphs.

On 2020-01-23 19:07:02, user Nejc Stopnisek wrote:

We have a revised version submitted here. Now including additional spatial and temporal data.

On 2020-01-23 19:04:19, user Nejc Stopnisek wrote:

A revised version of our manuscript #727461 on the identification of the common bean core microbiota. It includes additional spatial and temporal data supporting the relevance of identified microbial core taxa.