On 2020-02-25 04:25:13, user Hsiao-Huei Chen wrote:
More than E/I... Rethinking Autism? See how 2 neurons tango! PV-SOM compensatory interaction alter information filtering @ the ACC!
See Chen's lab work @ Nat Commun 2020 Feb (https://rdcu.be/b16IK) "https://rdcu.be/b16IK)").<br /> "Hyperactivated PTP1B phosphatase in parvalbumin neurons alters anterior cingulate inhibitory circuits and induces autism-like behaviors"
On 2020-12-17 16:53:38, user Raffi Aroian wrote:
This article is now published: https://aac.asm.org/content...
On 2020-10-02 18:57:09, user ravi chandra wrote:
Is there a control for this experiment? tried to look for SARS COV2 sequences in a healthy and COVID negative individuals? What is the confirmation that the amplified rna sequences originated from SARScov2?<br /> Which was the first SARScov2 virus sample or gold standard that was considered in this study ? Any reference cited as such ?
On 2016-12-21 15:00:29, user ???? wrote:
Published as a part of proceedings BIBE2016<br /> https://doi.org/10.1109/BIB...
On 2018-11-14 15:56:42, user dalloliogm wrote:
This is an interesting method, however I don't understand the application to GWASes. Isn't the p-value in a GWAS dependent on the allele frequency?
On 2018-05-14 14:23:32, user Eduardo J. Villablanca wrote:
Intriguing! Interesting Figure 4F, in which ileum and C1 draining lymph nodes are removed and 7B8 cells proliferate in all LN (e.g. D1, D2, etc). Wondering if the SFB is spread through out the GI tract or ileal DC now can migrate to D1?
On 2021-01-24 12:48:14, user alejandro wrote:
Please cite this paper
On 2018-09-26 14:38:20, user Natsuhiko Kumasaka wrote:
Dear authors,
I think the conditional distribution just above the equation (6) in p.25 is flipped. Correctly b|\hat{b}, but not \hat{b}|b.
On 2018-02-26 16:01:24, user Helder Maiato wrote:
I must apologize to Dr. Paola Vagnarelli for not mentioning in my previous discussion her recent paper (De Castro et al., Oncotarget, 2018) where, in addition to data supporting a role for Aurora B in the regulation of proper nuclear envelope reformation on lagging chromosomes in human cells, they show that “core” nuclear envelope components (Lamins A/C) are uniformly recruited to lagging chromosomes.
On 2020-08-13 12:06:59, user kdrl nakle wrote:
It would be great if you would have any real manufacturing support.
On 2019-10-22 22:09:58, user DKF wrote:
Great to see anything re genetics in relation to France - considering the present official attitude towards DNA testing ("recreational" or otherwise). None the less, Y chromosome male line and mtDNA female line uniparental markers are the most informative for understanding the origins of regional groups - when combined with data from history and archaeology. Apparently none presented here. Perhaps in a subsequent publication? In addition, until there are ancient DNA studies of key French sites (e.g., LaTene Celtic) we are flying blind in many respects since migration for example during the Industrial Age will have had a strong impact on the population of today. We need to know "what is under our feet". Why is it that neighboring countries are flooding the literature with immensely informative ancient DNA studies? We need to integrate this data with similar work from France before we can make conclusions about how history and prehistory have affected the population of France today. More broadly, there is an expanding body of knowledge from Spain, Italy and Germany concerning for example Bronze Age Bell Beaker sites. Those from France would help to tie things together coherently so that we can provide an accurate story of Europe through the ages.
On 2022-03-01 07:08:40, user Mark Fisher wrote:
Interesting work, but where is the supplementary information? I can't seem to find it.
On 2018-02-23 10:15:21, user Ferran Aragon wrote:
Dear authors,<br /> Congratulations for these very interesting results. We are struggling to get good yields for long ssDNA (3-8Kb). I don`t understand very well how the yielding result indicated in the text when doing aPCR with AccuStart HiFI (695+/-35 ng in 50 ul, thus 14ng/ul aprox) fits with the purification results shown in Fig.S7 where the most efficient purification method gave a yield of about 250ng/ul. Could you clarify this? Thanks a lot!
On 2018-02-28 18:19:51, user Leslie Vosshall wrote:
The Vosshall Lab discussed this pre-print at our journal club on 2/28/2018. We agreed that it was a very exciting series of observations.
The following discussion points came up:<br /> 1. The experiments refer to control as 100% humidity, but was ambient relative humidity measured directly? It is very difficult to get a room to 100% humidity!<br /> 2. Figure 1A, how does the time on the X axis relate to the entrained circadian cycle of these animals? Is the big peak at 40 hr modulated by circadian time or is it an absolute peak dependent only on dehydration?<br /> 3. Figure 1A, what are the dehydration levels of the animals in this experiment? How tight is the correlation of dehydration to that activity peak? We were interested in comparing the curve in Figure 1C to the activity data in Figure 1A.<br /> 4. Figure 1C, is this behavior specific to blood-feeding? Or if you gave the animals the option of drinking water or sucrose would you see the same increase in feeding correlated to dehydration?<br /> 5. Figure 1C, what happens if you repeat this experiment with gravid females who previously blood-fed, who have a lower drive to blood-feed? i.e. can you disentangle the drive for blood from the drive to rehydrate from any source, including blood?<br /> 6. Figure 3D-E: it would have been good to include the GFP dsRNA control that was used in the sugar measurements in Figure B-C.<br /> 7. Figure 4A refers to n=8, but there are many more than 8 data points. Is this a typo in the legend?<br /> 8. Figure 4A, can the authors clarify what “wet conditions” and “dry conditions” refer to? Did they measure relative humidity?<br /> 9. Figure 4B, the X-axis is very confusing. Do you mean 1.94 cases/10,000? Or do you mean 19,400 cases? Or is 10[4] a typo given that there are closer to 2000 WNV cases per year – did you mean 10[3] as a multiplier? Also starting the axis at a non-zero value is misleading.<br /> 10. Do male mosquitoes have some of these phenotypes? It would be good to see how much of this is a general effect of dehydration vs a specific drive of females to seek blood sources<br /> 11. Given how low the blood-feeding rate on the Hemotek devices was, we wondered why the investigators did not use live hosts, especially in Figure 4.
On 2023-05-12 17:40:58, user Maurice Franssen wrote:
Fascinating research and results. One comment: the moth shown in Supplementary Figure 1i is not Noctua pronuba but its sister species Noctua fimbriata. I do not think that species will behave differently but the authors better show a specimen of N. pronuba.<br /> Maurice Franssen, amateur entomologist, Wageningen, the Netherlands
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 2020-06-14 08:47:04, user Ivan Ansia wrote:
Please find companion manuscript at https://doi.org/10.1101/202...
On 2016-06-24 16:37:11, user Peter wrote:
We appreciate all the comments and will address them individually in due time.
One comment was that we are measuring stable gene transcripts rather than the up regulation of genes. As stated in lines 905 to 925, one would not expect a gene transcript to be stable at one time, unstable at another time and then stable later on (see Figure S3). We see this pattern in many of the transcriptional profiles. This is difficult to explain by the 'stable gene transcript' idea. Moreover, many of the gene transcriptional profiles show putative feedback loops. This is also difficult to explain by the 'stable gene transcript' idea. It cannot be attributed to 'noise' because the behavior of each probe is calibrated and 'noisy probes' are not used.
We are not the first to report the postmortem up regulation of genes as pointed out on lines 927 to 947 (using a different technology) and the other paper mentioned by mit_opinion below. The difference in our study from the others is that we measured the precise abundances of hundreds of genes through post-mortem time.
Lastly, one comment stated that we were measuring absolute transcript abundances. We never said anything about absolute concentrations. Our measurements are always relative to the live control.
On 2019-08-18 18:27:53, user A wrote:
This has been peer-reviewed and published, with significant modifications: https://www.mdpi.com/2072-6...
On 2020-02-10 16:30:13, user Virginia Savova wrote:
Now published with Springer Nature in Scientific Reports https://rdcu.be/b1sYv
On 2023-08-13 02:56:12, user Takanobu A Katoh wrote:
This preprint is published from DOI: 10.1126/science.abq8148
On 2022-03-21 23:11:00, user Soso wrote:
This paper has so much information and all the data looks great. However, I do have a few questions and suggestions on the methods and materials section of your paper.
First, fecal sample collection was mentioned but not the process of how the samples were collected. Was the feces collected after it passed from the monkey or was there some process to collect upper GI samples? The difference in collection methods may affect the presence of certain bacterial species, such as anaerobic species.
Second, I did not see internal controls for DNA extraction, PCR, or the sequencing process. Were there any internal controls used to verify the results of each step? So, DNA extraction for example, known bacterial species grown in the lab can be included at specific concentrations and used to calculate how much DNA should be extracted from this known species, this way we can check to make sure the DNA extraction process worked as expected.
Third, were there any steps taken to minimize PCR errors (such as ambiguous bases, etc.) and chimeras? It would be beneficial to mention these steps and what programs were used to minimize them in the materials and methods section, for example ChimeraSlayer is often used for removing chimeras. Also, it was mentioned that analysis was performed on samples after rarefaction to 10000 sequences/sample, but how many sequences/sample were there before this rarefaction?
Last, in the Microbiota analysis section for 16S amplification, the link for the earth microbiome project does not seem to work for me. I apologize if this is an error on my end, but it says the page cannot be reached. Is there another way I can find this information? It may be beneficial to also include PCR steps and cycles you followed in the methods and materials section so that if anything ever happens to the link and it no longer works, you still have the steps you followed in the paper.
Overall, I really enjoyed your paper. I hope you find these questions and comments helpful!
On 2019-12-30 06:58:01, user Koki Tsuyuzaki wrote:
I'm a developer of scTensor.<br /> Thanks for adding scTensor in your experiment,<br /> but there are many misleading or wrong parts as below,
so please consider the modification.
In Figure 1C and the caption, you use "the database of scTensor", but please use "LRBase" (the name of our L-R database) instead.
Please note that the scTensor is the name of algorithm or the software package, and not L-R database.
Actually, scTensor can be used with any L-R database.<br /> https://rdrr.io/bioc/LRBase...
I think you should separately consider the effect of selection of L-R database and CCI detection algorithm based on the database.
In the INTRODUCTION, you said
to the best of our knowledge, it is the largest database of this kind.
but in the Figure 1C, LRdb seems not so large.
There are many blank elements in Table 1 scTensor column.
If you will add our method in your experiment, you should investigate it more.<br /> I still do not understand your intention of
complete pipeline<br /> the other items are as follow:
Accept preprocessed data Y
Export types<br /> tables Y<br /> circualar plots N<br /> graphML or equiv. N
Perhaps the complete pipeline means the built-in call type calling using t-SNE, k-means, or SIMLR but I don't think such name is appropriate, any tool can perform such task by combinined with the other tools.
Besides, if the user want to use other dimensional reduction, clustering, and cell type identification methods not included in your tool, your tool can be used with them?
In the Comparison with other tools, you said
Swissprot annotations (secreted/membrane) automatically
but UniProt/Swissprot is based on the manual annotation.<br /> https://www.uniprot.org
We also used UniProt/TrEMBL and this database is based on the prediction by cellular localization algorithms.<br /> So please explain more accurately.
In the AVAILABILITY, you said
the LRdb package is submitted to Bioconductor
but I couldn't confirm the submitted R/Bioconductor package,
although I could confirm that a TSV file is put on the GitHub.
https://github.com/Biocondu...<br /> https://www.bioconductor.or...<br /> https://github.com/SCA-IRCM...
Where was the package published?
In the manuscript, you compared your method with other methods,
but the benchmark is not well designed; each method use different L-R databases and different algorithms, so even if your tool showed the good performance, the reader cannot understand why the tool was good.
Again, you should separately consider the effect of selection of L-R database and CCI detection algorithm based on the database.
As the criticism against scTensor, you said
We found 2 reliable LR pairs whereas scTensor returned 14 pairs, none in common<br /> or<br /> we found significant discrepancies with PyMINEr and scTensor
but there are no detail explanation or no quantitative evaluation,<br /> and these parts are just your impression.
Acutually, some L-R pairs detected by scTensor (Supplementary Table 3) are still curated and not "none in common".<br /> https://string-db.org/cgi/n...
Besides, as you said, LRBase includes many purative (not known) L-R pairs,<br /> you cannot simply say which L-R pair is correct or not.
On 2021-12-20 19:58:34, user Carles Fèlix Calatayud Aristoy wrote:
Brilliant idea! We are currently giving it a try in the lab!
On 2018-04-01 17:29:36, user Modou wrote:
Hi I am very honoured to be a participant and one of the Ambassadors
On 2017-09-18 04:17:00, user JocelynSP wrote:
I have just uploaded an edit to add the data accessions. Sequences are now available in SRA, and OTU tables in Figshare, if anyone wants to replicate or critique.
On 2020-03-31 21:48:04, user Brett Pike wrote:
Is CBCAS more likely to produce THC than CBDAS?
On 2024-01-30 05:25:01, user Sergey Ovchinnikov wrote:
See additional reply concerning RfaH pLDDT here:<br /> https://twitter.com/sokrypt...
Lauren used different alphafold models. When you correct for this, the conclusions in AF-cluster hold.
On 2015-11-17 02:30:57, user Daniel MacArthur wrote:
Thanks everyone for the comments so far! We will make these changes in the next revision.
On 2019-01-11 10:59:25, user PTRRupprecht wrote:
This is a really useful resource!
Something I did not fully understand: "To allow easier and faster access to the exposed brain, all pipettes are positioned on one side of the preparation." Also from Fig. 1B, I cannot see immediately why one should not position the pipettes one all sides of the craniotomy. What am I overlooking?
And it would be really cool to have (in the supplementary material) a video which shows both the 2P image and the oscilloscope (or something similar) during the procedure.
Kind regards,<br /> Peter
On 2016-08-31 11:54:15, user Aleksey Belikov wrote:
All attempts of field normalization for citation indices are basically useless, because this is a non-issue. Nobody in his right mind would compare a biologist with a mathematician based on a citation index, and then give preference to the one who has a higher index. Indices are used for hiring and promotion for a particular open position. If this position is for a mathematician, would anybody hire a biologist, even if his citation indices are 20 times higher?
On 2023-07-14 23:30:00, user Zach Hensel wrote:
The revised manuscript overlooks the dispositive analysis first suggested to the authors, to my knowledge, in the first week of September 2022. The manuscript’s hypothesis of an endonuclease “fingerprint” of a synthetic origin in the SARS2 genome makes a testable claim: if regions around the sites composing the “fingerprint” are sampled in nature, engineered nucleotides will stick out like a sore thumb.
Authors were told about this test in the first week of September 2022 when people independently noted the recombinant evolutionary history and that almost all elements in the “fingerprint” are sampled in a handful of the most closely related genomes. Others rephrased essentially the same test, with Francois Balloux commenting to Alex Washburne on September 5, 2022:
Assuming we wished to follow up on this, the next step would be to test if high homology can be found to different Sarbecoviruses for (some of) the 6 fragments defined by the restrictions site (ie. there's no reason to expect natural breakpoints to match restriction sites).
This step was not taken. And it was not a difficult step. Shortly after the manuscript’s publication, Crits-Cristoph and colleagues rigorously showed that the hypothesis fails this test: https://github.com/alexcritschristoph/ancestral_reconstruction_endonucleases – the conclusion is noteworthy considering the public record, which demonstrates bias in site selection and post hoc selection of statistical tests. In fact, this manuscript’s hypothesis gained attention only after Justin Kinney, who is acknowledged for his assistance on the manuscripted, prompted the discussion by suggesting a different hypothesis about a different restriction endonuclease, BsaXI.
In the comments section of V1 of this manuscript, Alex Washburne proposed a second test of his hypothesis, claiming that “the rapid loss of this pattern is indicative of its evolutionary instability, suggesting what we observe in the SARS-CoV-2 ancestral state is not a stable pattern resulting from recombination, but a transient, unstable pattern that perhaps went against selection and reverted back once the infectious clone was subjected to selection from considerable onward transmission.” While this statement makes some dubious claims and another test is not needed, this comment shows that Washburne considers fitness changes in mutations at these sites to be another test of his hypothesis. This is a test that Washburne can conduct based upon published analysis of the fitness impacts of mutations: https://github.com/jbloomlab/SARS2-mut-fitness – as Washburne and co-authors have not published the results of this test, I will briefly do so here.
The mean, median, maximum, and minimum fitness change estimated for point mutations in the “fingerprint” of the 5 BsmBI or BsaI sites in SARS2 are -1.7, -1.4, 2.2, and -6.5. The same calculations for 1000 random samples of 30 nucleotides give -1.7, -1.5, 1.8, and -6.4 (see link above on interpreting these numbers, or simply note their similarity). A search on https://cov-spectrum.org/ shows that point mutations or deletions for one or more of these 30 nucleotides have been reported in 0.75% of sequences sampled in the most recent 3 months. Point mutations or deletions for one or more of 30 random nucleotides (a single random sample; results will vary) have been reported in 0.96% of sequences in the same period. All in all, the main point of interest in these 30 nucleotides is the attention given a hypothesis of a “fingerprint” of synthetic origin that was effectively disproven before this manuscript was published.
Finally, considering the countless number of equivalent hypotheses, I suggest that a better effort would be immune to these tests (and I can think of at least one example myself). It is critical that a manuscript of this type demonstrate that there is an unbiased rationale behind the hypotheses tested and that is plainly not the case here. One simply needs to observe that “longest fragment” is referred to 20 times in the manuscript, while “shortest fragment” goes unmentioned.
On 2018-12-12 21:01:26, user Michael Neel wrote:
Thanks for the really interesting paper! I recently reviewed this paper for a class assignment and decided to share my comments with you.
Paper Summary:<br /> This paper investigates mechanisms that help to establish centriole number in multi-ciliated cells (MCCs). The authors investigate this using an ex vivo airway culture model that produces mouse tracheal epithelial cells which are MCCs. They investigate whether the parental centrioles (PCs) are involved in regulation of centriole abundance. Using centrinone, the authors ablate PCs from their cell cultures and present data they claim shows PCs loss does not inhibit centriole amplification, deuterosome biogenesis, or affect amplification dynamics. The authors also presented data they claim shows that PIk4 levels do not affect centriole abundance, although it may delay amplification. Lastly, the authors investigated the relationship between cell surface area and centriole abundance. They present data that suggests centriole abundance correlates with cell surface area and that they were able to affect centriole abundance by manipulating cell size. Overall, the authors propose that cell surface area is a determining factor of cilia abundance in MCCs.<br /> Overall, I liked the authors experimental approach and the amount of quantification attempted. In particular, I like how they not only investigated PCs, but also PIk4 and surface area as possible regulators of centriole abundance. I also deeply appreciate their attempts to quantify many of their immunofluorescent images. However, the paper contains a number of issues predominantly including insufficient sample sizes, and graph choices which I address in more detail below.
Comments and suggestions <br /> 1. In many of the graphs (2b-g, 3b, 5c,d,f,g, SF3b) the authors present data that include error bars and statistical tests based on averages of 2 independent experiments. This means that most of the data have an n of 2. While an n of 2 is not technically insufficient for statistical testing, data with n=2 lack statistical power and presenting SEMs with n=2 can be misleading. I would advise the authors to perform addition independent experiments to increase their n and possibly a power analysis to determine a sufficient sample size. <br /> 2. For fig 2d-g, authors show bar graphs depicting percentages of cells with 0, 1, 2, 3, 4, >4 centrioles from cultures stained for markers of various centriole assembly stages. They claim these graphs show that loss of PCs did not affect the overall timing of centriole amplification stages, but the graphs shown do not appear to be appropriate for this type of analysis. I would suggest the authors instead include graphs quantifying the % of cells positive for the various markers in graphs similar to fig 2 b and c.<br /> 3. In their results section on page 6, authors say that deuterosomes are lost by ALI8 in control cells. However, fig 3a clearly shows some Deup1 immunostaining at ALI8 and fig 3b shows 20-30% of control cells are positive for Deup1 at ALI8. Authors should amend this statement.<br /> 4. On page 8, authors claim that manipulating PIk4 protein levels does not alter deuterosome number, which contradicts data in fig 5e that shows increased deuterosome number when PIk4 is knocked down. <br /> 5. Authors mention in results that the centrinone concentration used is roughly 3-8 times higher than needed in most cells, but do not provide their rationalization for using such a concentration. This can be addressed by including a sentence or two explaining why such a concentration was used<br /> 6. On page 7, authors state that fraction of MCCs at ALI12 show no overall difference between control and PIk4-depleted cells, but do not reference any data. Authors can address this by including a bar graph displaying this data.
On 2020-10-14 13:10:38, user Brian wrote:
In your methods, you note using 4 ul of collagenase I, however the catalog number provided refers to a solid. Could you provide the concentration of the stock solution you used?
On 2020-08-13 12:25:42, user kdrl nakle wrote:
That will too complex and too complicated to treat people that are days away from dying. It is OK for cancer but I bet it is not going to work effectively for acute infections. It is interesting so try to prove me wrong.
On 2020-03-20 03:52:25, user Shiya Song wrote:
Still confused on how feature vectors for x_v1 is calculated? Does it use b_v1 to b_vm?
On 2021-08-15 09:17:23, user David Pellow wrote:
Will the performance of this tool be compared to the standard tools for metagenomic plasmid assembly?
On 2023-11-12 00:05:45, user Elizabeth Duncan wrote:
Recently, a group of trainees read and discussed this preprint as part of a journal club at the Markey Cancer Center at the University of Kentucky. We thought the findings suggesting that SETD1A may be driving the increase in H3K4me3 in MLL1 mutated cells (and possibly leukemic cells with MLL1 translocations) were very intriguing. However, we have several questions and suggestions:
In figure 2B (metagene analysis) and C (pie charts), you plot the mean read counts from H3K4me3 ChIP-seq. We interpret the unexpected lack of enrichment of H3K4me3 at gene TSSs in the WT sample as a reflection of the relatively significant increase of H3K4me3 at new gene loci in the MT1 and MT2 cell lines. Is this correct?<br /> If so, we believe this point could be made stronger by adding, for example, a Venn diagram of the genes with MAC2 peaks in the WT cells and those with peaks in the MT1 and MT2 cells. You could also create two separate metagene plots based on the data in Figure 2B: one looking at H3K4me3 in all three cells lines at genes with MACS2 peaks in WT, and one looking at H3K4me3 at genes with MACS2 peaks in MT1+MT2.<br /> Given that there is likely variability in the chromatin state in different iPSC lines, we also wonder if you performed these experiments and/or analyses using a separate iPSC line?<br /> It is unclear how you performed the differential expression analyses in figures 3, 4, and 5. The heatmaps show changes in both the WT and the mutated cell lines, even though we assume the differential expression is in relation to the WT cells? We appreciate there are many ways to perform these analyses, however we would like to understand the details of how they were done here to better understand their implications.<br /> What happens if you knock down SETD1 expression in the MLL1-R3765A cells?<br /> Do you see the same effects if you KO or KD MLL1? Versus this mutation that prevent association with WRAD?
We look forward to seeing your paper in publication.
On 2022-04-10 10:59:21, user Yutaro Ueoka wrote:
Thank you for interesting article.<br /> Fig4a and Fig4b seems to be completely same graph. mistake?
On 2021-05-12 20:17:50, user Ujváry István wrote:
Interesting report on the effect of the 7-hydroxylated metabolite of CBD. However, experimental evidence in humans for your statement "7-OH-CBD is the active ingredient for the treatment of epilepsy" has been lacking. For a hypothesis I advanced recently, see:<br /> https://www.liebertpub.com/...<br /> http://innovationinfo.org/a...
On 2018-02-14 10:38:49, user Benoît Girard wrote:
A purely formal comment: on fig 3A, it is quite difficult to spot the lonely additional blue spike (I had to read the legend to learn about its existence, and to subsequently search the figure to find it).
On 2016-08-05 05:12:03, user Jason Chin wrote:
Try this one: [https://downloads.pacbcloud...](https://downloads.pacbcloud.com/public/dataset/PhasedDiploidAsmPaperData/FUNZIP-PhasedDiploidAssemblies.tgz "https://downloads.pacbcloud.com/public/dataset/PhasedDiploidAsmPaperData/FUNZIP-PhasedDiploidAssemblies.tgz")
We will correct it in the revision.
On 2022-10-22 00:15:10, user CDSL JHSPH wrote:
This is interesting research, not only because it corroborates past findings, but also because it confirms and arouses mixed reactions concerning microbial diversity in equal measure. It is my pleasure to make these remarks. The work is well structured, well researched, and properly presented, easy to read even for non-scientific audiences. When going through the details though, I could not keep the concepts of hospital-acquired infections, antibiotic resistance, and the emergence of novel diseases out of my mind, particularly because of how they are linked to the overall concept of microbial diversity and adaptability. For antimicrobial resistance, for instance, the underlying factor has everything to do with the transfer of mobile genetic elements (MGEs) between two genomes. When MGEs access the chromosomes of new bacterial hosts, the outcome is phenotypical alteration. If the MGEs contained antibiotic resistance then novel or ongoing pathogenesis may result. Nevertheless, your study has demonstrated that bacterial species rarely cross environmental barriers. However, it is interesting to note that this is not the entirety of the results because there are distinct transitions between aquatic biomes, which, noteworthy, are ancient, rare, and often directed towards the brackish biome. At the same time, there are frequent transitions into brackish sites, which are harder to explain. I am just concerned, are there tests that can ascertain these claims? Previous studies have identified that bacteria are opportunistic and may manipulate any loophole to establish supremacy. The concern is further aggravated by your additional findings, that brackish bacteria often exhibit enriched gene functions for various physiological responses, including transcriptional regulation, which is integral in the re-writing genetic information, further begging the question should there be a cause for worry.
On 2018-06-22 16:01:11, user Jun wrote:
Dear authors
Very outstanding works. But I have some concerned about the article.<br /> 1) You mentioned "Despite many attempts, and using several different versions of Cas9 under control of different promoters, we were never able to generate mutants showing altered pigmentation, among the few transformants which resulted from transformations with either vector." <br /> Any detailed information about this statement? Which promoter you guys already tried? Which version of Cas9 you guys already tried? It will be a very useful information for whom wanna work on CRISPR in Magnaporthe oryzae.
2) You mentioned Cas9 is toxic to Mo, but do the transformants without pigment change has Cas9 expression? Did you find any difference in the growth rate, sporation and virulence between the transformants even without pigement and WT?
Thanks
On 2017-03-08 22:08:46, user Kobi wrote:
I would suggest expanding the definition of reproducibility to include experimental work, not just computer code. This will help the definition be more generally applicable to all sciences.
On 2021-10-08 11:57:25, user Eric Fauman wrote:
There are many p-values listed as 0 in the supplementary tables. You need to either report the -log10(p), or include the standard errors and subject counts for each variant so researchers can calculate the p-values for themselves.
On 2018-10-10 13:34:39, user Tony Warne wrote:
PDBs will be released on 17th October. We would welcome comments and questions, also by email.
On 2019-01-16 18:36:27, user Xuanting (William) Hao wrote:
Good job!
On 2017-04-05 02:08:41, user Zhiyong Shen wrote:
hi everyone,<br /> I try to install the panX on my desktop, the process of installing is well.<br /> However, i always get the error report as follows when i run the example data!<br /> Did anybody run the demo data success?
warning: ./data/TestSet/geneCluster/GC_00001981_na.aln is not a core gene<br /> core_list============== []<br /> step07-call SNPs from core genes:<br /> 0 minutes 0 seconds (0 s)<br /> fasttree time-cost: 0 minutes 0 seconds (0 s)<br /> Traceback (most recent call last):<br /> File "./scripts/run-pipeline.py", line 128, in <module><br /> aln_to_Newick(path, params.raxml_max_time, params.threads)<br /> File "/home/shenzy/soft/pan-genome-analysis-master/scripts/SF08_core_tree_build.py", line 39, in aln_to_Newick<br /> resolve_polytomies('initial_tree.newick0','initial_tree.newick')<br /> File "/home/shenzy/soft/pan-genome-analysis-master/scripts/SF08_core_tree_build.py", line 6, in resolve_polytomies<br /> tree = Tree(newickString);<br /> File "/usr/lib/python2.7/site-packages/ete2-2.3.10-py2.7.egg/ete2/coretype/tree.py", line 218, in __init__<br /> read_newick(newick, root_node = self, format=format)<br /> File "/usr/lib/python2.7/site-packages/ete2-2.3.10-py2.7.egg/ete2/parser/newick.py", line 231, in read_newick<br /> raise NewickError('Unexisting tree file or Malformed newick tree structure.')<br /> ete2.parser.newick.NewickError: Unexisting tree file or Malformed newick tree structure.
i past part of the results from the directory of geneCluster as follows:<br /> -rw-r--r-- 1 root root 73369 Apr 5 01:51 GC_unclust006_1.fna<br /> -rw-r--r-- 1 root root 0 Apr 5 01:51 SNP_whole_matrix.aln<br /> -rw-r--r-- 1 root root 6 Apr 5 01:51 core_geneList.cpk<br /> -rw-r--r-- 1 root root 0 Apr 5 01:51 core_geneList.txt<br /> -rw-r--r-- 1 root root 18658 Apr 5 01:51 gene_diversity.cpk<br /> -rw-r--r-- 1 root root 16578 Apr 5 01:51 gene_diversity.txt<br /> -rw-r--r-- 1 root root 54 Apr 5 01:51 snp_pos.cpk
Did any one can help me, many thanks in advance!
On 2023-01-03 08:55:04, user Pustelny Katarzyna wrote:
Thank you. Currently, we have MS data confirming Tyr273 phosphorylation in the activation loop and it is also clearly visible on the electron density map. Detailed analysis of pTyr273 is on-going.
On 2018-02-15 17:45:44, user Gaurav wrote:
Hi
A quick comment about using symbols for isoforms.<br /> In the Methods section, reference isoform refers to A1 (Line 4 of Overall design and problem formulation) and alternatively spliced to A2, however Figure 1 represents A as reference and A1 as alternatively spliced.<br /> The entire text uses A1 for reference and A2 for alternatively spliced.
This is confusing.
On 2019-07-30 22:49:30, user Charles Warden wrote:
Thank you for putting together this paper.
I was a little concerned when I saw "We estimate that a sample sequenced to the depth of 70 million total reads will typically have sufficient data for accurate gene expression<br /> analysis." for a couple reasons:
1) For most gene expression projects, I think 10 million aligned reads is OK and 20-30 million total reads is often pretty safe. While the exonic percentage varies for library protocol, and I'm not sure about the unique read conversion (or if that conversation also varies between library protocols and sample types).
2) I think the specifics have to be figured out for specific protocols (and raw data can be used for research purposes in different applications, or to check the validity of processed data).
For 1), I think that was justified from both my own experience (with 50 bp single-end reads), as well as Liu et al. 2014 / Wang et al. 2011 / Tarazona et al. 2011. I noticed those papers while responding to this discussion.
For 2), I don't exactly have a paper to show this, but I would say differential expression between groups requires testing / optimization per-project. So, you couldn't really define criteria that will work in all possible gene expression projects. While kind of messy, I have some notes from a Twitter discussion this past weekend.
However, I think part of the discrepancy for b) is different interpretations for "differential expression," "over-/under-expression," and "outlier expression". I am mostly thinking of the 10-20 total million polyA reads for differential expression and genes with clear expression / over-expression. If you talking about a pattern that would more more likely to be a technical artifact, I can see how extra effort would be needed for gene expression analysis. For example, if you could have 2-3 biological replicates from slightly different sections of a sample (each with 10-20 million reads), that starts getting close to a total of 70 million total reads for that sample.
I think your Figure 1A and Figure 4C (and possibly Figure 3C) makes me think there is more agreement than I originally expected from the abstract (since that emphasizes something with a threshold of 10-20 million MEND reads). However, I would say 90% specificity may be more reasonable for sensitivity (instead of 95%), for whatever metric is captured by that test. In general, I think 80% accuracy for a genomic signature is pretty good, and I think you need to be careful about over-fitting. That was part of the Twitter discussion that I linked above, but that is also described in my genomics for "hypothesis-generation" blog post.
On 2017-12-21 22:01:25, user awcm0n wrote:
Mollie, great work, but I think there's a problem with your code for simulating from a fitted model in Appendix B:
simdatsums=lapply(simdatlist, function(x){ <br /> + ddply(x, ~spp+mined, summarize, <br /> + absence=mean(count==0), <br /> + mu=mean(count))<br /> + })
Error in .fun(piece, ...) : argument "by" is missing, with no default
On 2023-10-02 00:06:33, user LEVIn - Unicamp wrote:
We discussed this preprint in our journal club and enjoyed reading it. We collectively agreed it's an exciting contribution to understanding how biological invasions shape invasive species' trophic niche and functional morphology in new environmental contexts. We all think the manuscript is well written and the figures are excellent! During our discussion, a major point that came up deals with how the hypothesis (lines 88-90) is motivated and then connected with the results. A more conceptual contextualization of the hypothesis in the introduction (e.g., explaining the ecological release hypothesis in the 3rd paragraph) could help readers to generalize the results beyond the study system and attract a more diverse readership interested in niche variation and biological invasions. Also, as the results combine a substantial body of statistical analyses aiming to understand variation in functional morphology and trophic niches across species, ontogenetic stages, sexes, and invaded vs. native ranges, presenting predictions after the hypotheses could help readers to navigate the results. For example, in light of the ecological release hypothesis, what is expected regarding morphological and body size variation across native and invaded areas? Our final point of discussion is related to the interpretation of the observed niche contraction in the invaded range. As replicates representing invaded vs. native ranges are sampling sites in space (Fig. 1), clarifying whether observed niche contraction emerges via lower variability in resource use across sites and/or within sites would be interesting. This is a key point to connect the results with the ecological release hypothesis. I hope you find these comments constructive; discussing this manuscript in our journal club was great. Congrats on your work, and good luck with the following steps!
Laboratório de Ecologia das Variações Individuais (LEVIn), State University of Campinas (Unicamp), Brazil
On 2016-05-14 10:53:56, user Arjun Raj wrote:
Interesting paper! Perhaps I missed it, but I'm wondering if there's any way to know whether the putative trans-splicing or circRNA events are not due to template jumping, which I believe reverse transcriptase is (or at least was) prone to.
On 2018-04-02 05:54:08, user Arun wrote:
"...Using admixture linkage disequilibrium, we estimate a date of 107 ± 11 generations ago for Iranian agriculturalist and AASI-related admixture in the Palliyar, corresponding to a 95% confidence interval of 1700-400 BCE assuming 28 years per generation."
118 generations at 28 years per generation gets us to 3300 years before present, i.e., 1300 BCE, not 1700 BCE. This would kill the idea that the Palliyar admixture with Iranian agriculturalists originated with the collapse of the Indus Valley Civilization.
Moreover, I would take P. Moorjani's establishment of 26-30 years per human generation since the Neanderthals with a big pinch of salt. The !Kung are measured to have a generation time of 25.5 years. This would further kill this idea about Iranian agriculturalist - AASI admixture. That extra 2.5 years is significant.
On 2018-03-31 20:18:53, user Richard Stevens wrote:
You guys have Mal'ta Boy listed as R1b1a1a2 (R1b-M269), among other errors.
On 2020-04-17 10:22:59, user Rajesh G wrote:
Great article. We would like to discuss this research paper feasibility on API 5500 triple quadruple. Please share our contact details or skype id so that we can discuss further.
On 2018-10-19 12:45:54, user E.K. wrote:
Great study! Really convincing data.
On 2020-06-10 08:25:42, user Renzo Huber wrote:
This is a timely manuscript of exceptionally high quality. <br /> I believe that the flexibility of this sequence approach is a quantum leap forward for the emerging field of high-resolution fMRI at high magnetic field strengths. <br /> The combination of multi-shot readouts and CAIPI-based undersampling will allow future neuroscientists to choose the matix-size and spatial resolution as desired. Despite T2*-constraints of conventional fMRI approaches.<br /> I am looking forward to using skipped-CAIPI in many of my future experiments.
On 2019-04-18 18:06:07, user Paul Schanda wrote:
This is a really useful development. We have used FLYA ourselves and managed to assign a 12 x 39 kDa protein from solid-state NMR data in a fully automatic manner - the largest protein so far assigned in solids. About a year of manual work -- or a few hours with FLYA, leading to the identical result. (https://www.biorxiv.org/con... "https://www.biorxiv.org/content/early/2018/12/16/498287)")
Having this tool now - finally - for methyl assignments is very welcome and I am sure it will boost solution-NMR of large proteins further.
On 2021-05-21 06:34:43, user phil_lefty wrote:
https://www.nature.com/arti...
We found complementary results with an RNA silencing effect without Cas13 in mosquito cell lines.
On 2023-10-03 21:24:35, user Herwig Walter Lange wrote:
It is not correct to state that the large interneurons are not lost in striatum. As i could show in 1981 (Verh. Anat. Ges. 75, S. 923-925), 52 % of the macroneurons are lost in HD, compared to a loss of 86 % of the microneurons.
On 2016-04-18 17:37:35, user Julie Dunning Hotopp wrote:
You should read and cite this paper by Aravind: http://biologydirect.biomed...<br /> His group already demonstrated some of the things you describe about the latrotoxin domain proteins. They talk about some other protein that might relate to these as well. We talk about it in the BMSB transcriptome paper at<br /> http://download.springer.co...
I think you need to address convergent evolution in this case. It might not be convergent evolution (I can't tell from what you present). But if you don’t bring up and address the topic head on, you could set yourself up for criticism.
The literature is becoming riddled with LGTs from X to Y, where X was found first and Y was found second (or vice versa). But really there are probably intermediates in between. For example, you could imagine a gene moving from a eukaryote to a Rickettsia endosymbiont to Wolbachia, or something like that. So I would look at your text to see if you can clean-up any references to that line of thinking. One of the benefits to working on recent transfers is that it isn’t an issue! ;)
On 2021-02-05 00:28:34, user Steve Are wrote:
And still there are reports coming in from credible, knowledgable people. There will be another very interesting release about the Thylacine coming out later this year. Stay tuned...
On 2016-06-22 21:47:00, user PornHelps wrote:
In addition, sexual images are not considered sexual rewards by anyone. You do realize they are jacking it to these images every single time they see them, don't you? Yet you pretend like sexual stimulation doesn't exist. You are comparing apples (money reward) and oranges (sexual images). Your use of the term "porn" also is very telling. No scientist uses that term. Sexually explicit media (SEM) is an actually non-based term. You show your true inability to think or write objectively about this media.
On 2019-08-23 18:40:05, user IJ wrote:
Interesting manuscript!
However, I would like to point out a minor error. The manuscript incorrectly states that Li and Zhang have disputed the results of Jungreis et al. "Drosophila melanogaster has been shown to have significant functional (“programmed”) readthrough (Jungreis, et al. 2011). While this is disputed (Li and Zhang 2019)..." Li and Zhang found evidence that the readthrough extensions of most of the 307 Drosophila genes found to undergo readthrough via ribosome profiling by Dunn et al. are non-adaptive. However, this set has very little overlap (only 43 genes) with the 283 genes found by Jungreis et al. to show evolutionary signatures of adaptive readthrough. While Li and Zhang have found evidence that most stop codon leakage is non-adaptive, they do not dispute that it can be adaptive for some genes. They state, "That most read-through events are nonadaptive does not preclude the possibility that a small proportion of such events have been co-opted in evolution for certain functions." Thus, Li and Zhang 2019 did not dispute the results of Jungreis et al.
On a related note, the Dunn et al. 2013 ribosome profiling experiments on readthrough in Drosophila and yeast seem very relevant to your manuscript, and you might considering discussing, or at least citing, their work.
On 2020-12-11 17:34:27, user kfos wrote:
Just when I think I have a hold on one part of single-cell RNAseq analysis... Another cool new papers comes out... Overwhelming!
On 2024-07-16 00:37:36, user Lana wrote:
Nice work, I didn't know ENTs could have so many phenotypes. Interesting
On 2018-10-18 18:37:33, user SIYUAN ZHENG wrote:
The statement about PRADA not able to run on 100nt is incorrect. We ran all TCGA datasets including glioblastoma which has the read length of 101 bp. <br /> Siyuan ZHENG
On 2015-03-31 14:05:45, user Leslie Vosshall wrote:
Thanks, glad you found it useful! I also hope that our experience will encourage people to post pre-prints on bioRxiv without fear that the manuscript won't be accepted subsequently by a peer-reviewed journal (disclaimer: i am on the bioRxiv board)
On 2018-01-15 02:11:20, user anonymous wrote:
Is the definition of an "interference domain" in this paper, having an area of ~1/rho around it's focal point, equivalent in any direct way, with the definition of a "linkage block" from Good et al. 2014**? i.e., sites separated by a map length of r < 1/TMRCA?
Also, with respect to: "The transition [between interference regimes] occurs when the interference probability e^–? becomes of order 1; the transition point marks the onset of nonlinearity in the fitness variance."
How was this determined from the simulated data? For example, in figure 2a, it isn't completely clear from those data points that there is a "transition to nonlinearity" at ?=1. Kind of looks like it, but it's not absolutely clear. How did you determine that?
enjoyed this paper a lot, thanks!
On 2017-11-06 23:47:42, user John Altin wrote:
Nice study. Are the TCR seqs available for download somewhere?
On 2020-01-27 15:38:01, user Tom Featherstone wrote:
I'm very intrigued by this concept. It has been a while since there has been any update on this project and I'm wondering whether the company has started considering looking at alternative methods for the study of neural transmissions. Rather than just using electrodes to measure the impulses from neurons , having just read a paper on scientists using trans genetic flies to study neural path ways it would be interesting to see if they start utilizing this technique to further understand the neural pathways. It may have already started taking place however there is no mention of such at the moment neither the use of viral vectors to transmit markers round neural pathways. Really looking forward to see developments of this project and the future to come. Good luck guys! :)
On 2020-09-16 15:30:36, user Raghu Parthasarathy wrote:
The observation of cool fungi is fascinating. However, I don't understand many aspects of the proposed "mushroom-based cooling device." Since the mechanism is evaporative cooling, how is putting mushrooms in a box any better than putting the equivalent amount of water in the box? Perhaps the argument is that the mushrooms have greater surface area, but this requires that the cooling be surface-limited rather than flow-limited, and this isn't discussed; moreover, if how is mushrooms-in-a-box better than water-soaked sponges in a box (or something else with a large surface area)? Clarification would be welcome!
On 2023-05-03 06:39:42, user Felipe G. Grazziotin wrote:
Dear Peter,<br /> This dataset doesn't include several taxa that are key to evaluate the taxonomy of Dipsadini. A more comprehensive analysis regarding that was recently published by Oliveira et al. in Syst. and Biodiversity (https://doi.org/10.1080/147... "https://doi.org/10.1080/14772000.2022.2153944)").
On 2020-09-12 14:29:24, user Philippe Henry wrote:
A peer reviewed version of this article can be found here:
On 2021-02-17 17:45:07, user chikheang Soeng wrote:
Hello,<br /> My colleagues and I recently chose to present your paper in a journal club. We think that Artemisinin-resistant malaria is a major health threat and that repurposing Alisporivir as an anti-malaria drug, as demonstrated in this article, is a promising solution. <br /> I would like to share some of the comments that were brought up during our discussion. In Figure 1 and Figure 2, the interaction between Alisporivir and Cyclosporin A was demonstrated using computer simulations. However, we believe that this conclusion could be better supported by conducting an in-vitro protein binding assay. Also, in Figure 2C, the colors of the graph and the figure legends do not match, making it difficult to interpret the results. Since the main focus of this article concerns the effectiveness of Alisporivir against Artemisinin-resistant malaria, it might be a good idea to move them to the supplemental figure section. In Figure 3C, we think that the third column was mislabeled; it should be DAPI + Cyp. Otherwise, the quality of the microscopy images was excellent. When reading the methods section, the sample size could not be found and we hope to see it included there.<br /> Overall, I think that this paper is very interesting to read. I like the fact that the result section was broken down into smaller sections which makes it easy to follow. I am looking forward to reading more in the future.
On 2022-01-20 16:38:23, user Mathurin Dorel wrote:
Just a few remarks that would improve an overall rather good paper:
On 2019-08-03 00:24:50, user Heteromeles wrote:
Anthropocene refugia is not a novel term or concept, as it was proposed it in 2015 in the book Hot Earth Dreams by Dr. Frank Landis, and others are pursuing the same concept with plants in California. The analysis is quite welcome.
On 2021-03-04 12:55:16, user S.c. Daniel Choi wrote:
Thank you for your RT! I am so excited that this work came out here.
On 2021-02-01 02:14:52, user Hamid Gaikani wrote:
GREAT JOB!<br /> HZE stands for high (H) atomic number (Z) and energy (E)<br /> I thought maybe the actors want correct that before the papers appears in a journal.
On 2017-02-24 17:08:01, user AdamMarblestone wrote:
-"Bidirectional Backpropagation: Towards Biologically Plausible Error Signal Transmission in Neural Networks" https://arxiv.org/pdf/1702....
-"FROST: A Distributed Neurocomputational Model of Working Memory Maintenance" https://www.ncbi.nlm.nih.go...
-"Neural Episodic Control" https://arxiv.org/abs/1703....
On 2022-10-31 05:04:22, user Ashraya Ravikumar wrote:
Summary:
In this work, the author asks how protein structures change based on analyzing the torsion angles. Through examples they show that the distribution of points in this representation correlates with resolution and data collection temperature of the structures. They also construct the RoPE space of a protein using time-resolved experiment datasets and show that minor changes in the linear coordinate space are clearly observed in the RoPE space. This work demonstrates the utility of a non-linear representation of the conformational space in visualizing changes throughout the structure which are originally considered subtle. This work is very interesting and can have significant impact on ensemble studies on protein structures and in crystallization/cryo-EM and fragment screening efforts by showing the impact of temperature and resolution. The manuscript is very concise (perhaps too concise?) and well written.
Major points:
Minor points:
To highlight the advantage of RoPE space, the author can show clustering of the same protein chains when clustered based on RMSD. The crowding of points when using RMSD vs. the separation of points when using torsion angles can make the utility of RoPE space obvious to the reader.
Ashraya Ravikumar and James Fraser, UCSF
On 2024-01-21 18:02:51, user Joana Mourão wrote:
This preprint was already published on Microbiol Spectr. 2023 Aug 17;11(4):e0138623. doi: 10.1128/spectrum.01386-23.
On 2016-10-18 02:18:13, user Philip Ashton wrote:
Hello! Great paper. I could be being dense, but where is the supplementary info available from? Thanks!
On 2017-05-17 14:31:06, user Jóhannes Guðbrandsson wrote:
There is a linkage map for arctic charr available. Published this february in G3 http://www.g3journal.org/co...
On 2022-02-03 16:00:38, user Xiaofei Bai wrote:
We published a very similar story back in 2020.<br /> https://doi.org/10.1242/dev...
On 2018-06-21 06:27:08, user gcochran wrote:
Wasn't there a paper by Scott Williamson that hinted in this direction?
"Localizing Recent Adaptive Evolution in the Human Genome"
On 2019-09-10 00:30:16, user Holly Beale wrote:
Congratulations on your paper. I really enjoyed it.
A couple of notes: <br /> I'm working on something related in bulk RNA-Seq, and I also did subsetting of fastq with seqtk. The behavior wasn't exactly what I expected. If I used the same random seeds to take two subsets, one with one million reads and the other with two million reads, the second set included all the reads from the first set. I ended up using different random seeds for each subset.
I think I eventually got it, but I had trouble parsing figure 3. It might be easier to understand if you omitted 2/3 of the groups from each plot. You could include the full figures in the supplement.
On 2016-05-28 15:43:57, user Davidski wrote:
Aren't the stats f4 (Steppe, Neolithic Farmer; Pop1, Pop2) potentially confounded by geography?
Steppe has more hunter-gatherer ancestry than Farmer, so if Pop1 has more hunter-gatherer ancestry than Pop2, and hunter-gatherer ancestry is usually positively associated with higher latitude in Europe, then the stat might be significantly positive as a result of Pop1 living at a higher latitude.
No wonder then that more northerly UK populations score more Steppe affinity in this test. That's not to say that they don't have more steppe ancestry than the southeast English. But the question is whether these particular stats can pick that up specifically, as opposed to just picking up extra hunter-gatherer ancestry in more northerly populations.
On 2021-03-18 06:53:46, user Michele Nunes wrote:
Hello,<br /> A group of undergraduate students at UCLA had the pleasure of discussing this BioRxiv paper during one of our journal clubs. Many of us were fascinated by the background information on phosphodiesterase inhibitors in relation to lipid metabolism. However, since the background consists of all text, it was a bit difficult for some of us to truly understand the signaling pathway in regards to how natriuretic peptides, PPAR?, and PDE9 were all related. We thought that including a visual aid such as a signaling map in the first figure or a visual summarizing the entire introduction would be helpful to engage readers who are not as familiar with the field.
Specifically, in the liver photos (Figure 1f), some of us found it difficult to distinguish a change in size between the placebo and PDE9-I group solely based on the images. We thought that including a line with a known measurement or showing the livers in cylinders with weights attached would be a more helpful metric to justify the results.
In addition, you state that these experiments were done in both OVX-female and male mice, but the only figure that includes both data is Figure 2g. The rest of the male mice data is pushed to supplementary. We were curious if there was a reason for only including a portion of male mice data? The ability to easily compare the data to OVX-female mice could bring to light important differences.
Finally, one of my colleagues was quite interested in the notion of estrogen having a protective effect against cardiometabolic syndrome. They suggested a future rescuing experiment where if OVX-female mice with induced obesity-cardiometabolic syndrome were injected with estrogen, could estrogen reverse the effects? I thought this was a great suggestion for possible future research in this area.
Thank you for your time!
On 2021-02-18 00:17:56, user Gernot Kaber wrote:
Nice paper! The Addgene reference numbers in Table 1 do not seem to exist in the Addgene database. Is that in the works? GK
On 2025-03-31 12:37:24, user Kshitish Acharya wrote:
Our observations from a detailed, quantitative comparisons of pathway databases can help scientists make rational choices among a plethora of options!
On 2024-06-06 17:27:56, user Prof. T. K. Wood wrote:
The first TA system found to inhibit phage was Hok/Sok in 1996 (that makes it seminal). So 26 years before retrons (your ref 47) and 25 years before ToxIN (your ref 48), Hok/Sok set the precedent of stopping phage by interpreting a phage process (transcription shutoff), rather than reacting to a specific phage protein. Curious as to why this discovery does not merit citation.
On 2016-07-11 18:45:07, user Ludo Waltman wrote:
I would like to announce that I have written a blog post commenting on this paper: https://www.cwts.nl/blog?ar.... The blog post discusses the difficulty of distinguishing between the use of impact factors at the level of journals and at the level of individual papers.
In addition to the comments made in the blog post, I also would like to raise the following issue.
In my view, the skewness of citation distributions can be interpreted in different ways, with different implications for the use of impact factors. Let me give two interpretations:
(1) This interpretation starts from the idea that citations provide a reasonable reflection of the quality of papers. Therefore the fact that within a single journal there are large differences in the number of citations received by papers indicates that there are large differences in the quality of papers. Consequently, the impact factor of a journal doesn’t properly reflect the quality of individual papers in the journal.
(2) This interpretation combines two ideas. The first idea is that citations are weak indicators of the quality of papers. Papers of similar quality on average have a similar number of citations, but there is a large standard deviation. Due to all kinds of ‘distorting factors’, papers of similar quality may differ a lot in the number of citations they receive. The second idea is that journals manage reasonably well to carry out quality control. Therefore the papers published in a journal are of more or less similar quality, so the standard deviation of the quality of the papers in a journal is relatively small. It follows from these two ideas that the impact factor, which is the average number of citations of the papers in a journal, provides a reasonable reflection the quality of individual papers in the journal (especially if the journal is sufficiently large, so that the above-mentioned ‘distorting factors’ in the citations received by individual papers cancel out). The fact that some papers in a journal receive many more citations than others is not the result of quality differences but instead it results from citations being weak indicators of quality, so it results from the above-mentioned ‘distorting factors’. In this interpretation, impact factors are a stronger rather than a weaker indicator of the quality of individual papers than citation counts.
The interpretation that the authors seem to follow in their paper, and that for instance also seems to be followed in the DORA declaration, is the first one. However, the empirical results presented by the authors, showing that citation distributions are highly skewed, are compatible with both interpretations provided above. In the second interpretation, there is no reason to reject the use of IFs to assess individual papers in a journal. Therefore, if the authors want to reject the use of IFs for this purpose, I believe they need to provide an additional argument to make clear why the first interpretation is more reasonable than the second one. I do think that the first interpretation is indeed more reasonable than the second one, but a careful argument is needed to make clear why this is the case and on which assumptions this is based.
On 2016-07-07 07:00:51, user Trish Groves wrote:
Thanks for this proposal, Stephen and colleagues. <br /> We're interested in implementing this at The BMJ; could you please email me tgroves@bmj.com to discuss practicalities? Thanks
Trish Groves, BMJ
On 2018-07-25 15:01:22, user Flydoc wrote:
Supplemental material is at https://figshare.com/s/e95b...<br /> Python scripts are also at https://github.com/flydoc20...<br /> -Alan Christensen
On 2020-11-09 14:28:32, user Amartya Sanyal wrote:
This article is now published: Please cite:<br /> Khalil, A.I.S., Muzaki, S.R.B.M., Chattopadhyay, A. and Sanyal, A. Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines. BMC Bioinformatics 21, 506 (2020). https://doi.org/10.1186/s12...<br /> Share this article: https://rdcu.be/b98I1
On 2020-04-16 10:49:14, user Darren Martin wrote:
I think that we maybe need to find more viruses that connect to the tree in the branch that separates SARS-CoV2 from the MRCA node of SARS-CoV2 and RATG. Without the genome sequences of these missing relatives we're not going to get very far wrt figuring out what actually happened.
On 2021-01-17 06:24:27, user hannah wrote:
Hi may I know, any treatment for infected plant or I just burn it and bury dip?
On 2021-02-25 19:44:23, user Cluster 7 wrote:
Interesting findings. The preprint is missing supplemental figures.
On 2022-10-22 14:34:27, user M T wrote:
It might be best to rephrase the conclusion of this preprint. With only 15 participants in each group, only very lage effects would have resulted in a statistically significant result.
On 2019-10-29 03:19:33, user mismatch_repair wrote:
I had a number of questions/concerns about this manuscript and its co-submitted counterpart on which I would appreciate feedback from the authors:
Some of my concerns are the following:
1) The manuscript states that I-PpoI "recognizes ~20 sites in the genome." However, in addition to a number of unique sites in genes and noncoding regions, which comprise the 20 sites you refer to, I-PpoI cuts within every 28s rDNA repeat (which you mention as a target, but which seems to be counted only once). Mammalian genomes contain many identical rDNA repeats spanning multiple chromosomes, and copy number can vary by an order of magnitude between individuals in a species because these repetitive sequences are highly prone to recombination. These repeats are difficult to sequence and not annotated on the Mus musculus reference genome. Per the NCBI entry on the murine 28s gene: "The sequences coding for ribosomal RNAs are present as rDNA repeating units distributed on chromosomes 12, 15, 16, 18 and 19. The number of rDNA repeating units varies between individuals and from chromosome to chromosome, although usually 30 to 40 repeats are found on each chromosome. These rDNA repeats are not currently annotated on the reference genome." Several publications even report an ability of 28s rDNA units to undergo coordinated copy number expansion in response to deletion events.
2) The claim that it is possible to generate "non-mutagenic" DSBs by simultaneously creating hundreds of compatible sticky-end cuts throughout the genome (primarily in highly repetitive sequences) is quite unprecedented. I am not aware of any prior publications on DNA repair claiming the existence of a 100% non-mutagenic DSB. The burden of proof for this should be high. However, the evidence provided here is insufficient to support this claim. There are numerous types of mutations: point mutations, minor indels, insertion and deletion of larger chromosomal regions, duplications, inversions, and chromosomal translocations. All of the larger chromosomal rearrangements are anticipated outcomes of simultaneously freeing compatible sticky ends throughout the genome. Point mutations/minor indels may occur but at lower rates. However, these minor mutations are the only ones directly assessed, by sequencing the genome and checking mapped reads. Detecting these larger genomic rearrangements is a challenging task even for experts in the field, and it seems the sequencing efforts did not extend beyond this. The genome reads are based on 500-bp fragments, which would make detection of most of these events impossible, even if you were looking for them. In the rarer case of a chimeric 500-bp read resulting from fusion of compatible but non-homologous sequences, the read would not map to the genome and have been discarded by your analysis. In the more likely case of a fusion between 28s cuts on different regions of a chromosome or on different chromosomes, the read would merely show a normal sequence in the 500 bp surrounding the cut but it would be impossible to discern where or on which chromosome the sequence is located among the numerous repetitive tracts throughout the genome.
3) You use a few additional methods like the Surveyor assay to assess 28s mutation, but this again can only detect point mutations. Furthermore, it relies on PCR amplification so if 2 different sequences are fused, the 28s primers would no longer amplify this. And the small size to which the DNA analyzed by Southern blot was fragmented render it similarly unable to detect rearrangements. While you prepared metaphase spreads, you did not do any banding analysis which drastically limits the ability to detect chromosomal rearrangements that do not lead to obvious changes in the shape of the whole chromosome. I do not know why your ligation-based method did not detect 28s cuts, but my guess would be failed PCR. I took a look at your target amplicon and the region between the primers is 64% GC, and immediately adjacent to one of the primers is a stretch of ~70 bp with 90% GC content. This would likely make for an extremely difficult PCR- one publication describing special conditions for amplifying 28s DNA reports that "the cloning of the rDNA gene family is very difficult" and "Sequencing primers should be far from the sequences with stretches of G or C repeats." (DOI:10.17221/3960-cjas). Your baseline "aberrant metaphase" level also seems very high. Mladenov et al. (Chromosome Translocation 2018) reported that 15 aberrant chromosomes/100 metaphases as a result of 8 single I-SceI cut sites and transient transfection leads to 30% lethality in CHO cells. 12 clusters of 4 cut sites lead to 90% cell lethality.
4) Your findings of a lack of mutagenicity from I-PpoI cutting contradict a substantial number of publications using this system. Ray Monnat, whom you cite in these manuscripts, reported that "These endonuclease-induced breaks can be repaired in vivo, although break repair is mutagenic with the frequent generation of short deletions or insertions," and also mentioned that the human genome contains ~300 28s cut sites for I-PpoI across chromosomes (1999). Other publications report the same phenomenon in yeast. Your own paper from 2015 found large deletions in mice. I-PpoI has been incorporated into a "gene drive" in mosquitos to "shred" the X chromosome and prevent the birth of female offspring. I-PpoI is derived from a mobile genetic element and its evolved purpose is to catalyze the insertion of a new sequence into the genome. Yet, you claim that in your system, it causes no genetic changes. If 100% re-ligation of cut sticky ends in the presence of many other compatible sticky ends was as likely as you suggest here, restriction enzyme-based cloning would not work, nor would numerous DNA repair reporter constructs based on this principle.
I do not see in this manuscript data that is sufficient to support the claims being made. One manuscript claims that mutations do not accumulate substantially with age and the other cites multiple sources showing they do. It appears you have generated an artificial progeroid model with genomic instability due to DSBs and that is why you see the same phenotypes as human progeroid syndromes and mouse models based on DNA repair deficiencies. It is impossible to claim epigenetic changes are responsible for the observed phenotypes when you are in all likelihood causing extensive genetic changes to these mice.
I also wonder how the following statements from a 2015 paper on the same mouse model (the only difference being cell type specific rather than ubiquitous expression) can be reconciled with the current manuscripts:
2015: "To induce nuclear translocation of ERT2-I-PpoI, PpoSTOP/+; lck-Cre mice were subjected to 2–4 intraperitoneal injections of 1 mg TAM (Sigma, resuspended in corn oil) at 24 h intervals. Animals were analyzed 4 h after the final TAM injection."
2019: "ICE mice were generated by crossing I-PpoI STOP/+ mice to CreERT2/+ mice harboring a single ERT2 fused to Cre recombinase that is induced whole body (Ruzankina et al., 2007). 4-6 month-old Cre and ICE mice were fed a modified AIN-93G purified rodent diet with 360 mg/kg Tamoxifen citrate for 3 weeks to carry out I-PpoI induction."
2015: "33% of break-spanning DNA segments yielded a chimeric DNA sequence, in which one end of the I-PpoI-flanking DNA was joined to that of a second, polymorphic I-PpoI site located ~1 Mb downstream. No evidence for aberrant junctions was observed in break-flanking DNA from lck-Cre controls, demonstrating I-PpoI-dependent formation of these distal fusions."
2019: "Unlike other methods of creating DSBs, such as CRISPR, chemicals and radiation, I-PpoI creates "sticky DNA ends" that are repaired without inducing a strong DNA damage response or a mutation (Yang et al., co-submitted manuscript)."
2015: "Although moderate transcriptional changes can be detected in DSB-bearing genes, persistent DSB formation and repair is associated with a surprisingly stable transcriptome in vivo." "Our findings further suggest that DSB repair is necessary and sufficient to ensure the maintenance and/or restoration of break-proximal gene expression profiles and, by extension, epigenetic integrity in vivo." "Consistent with cell-intrinsic epigenetic deregulation being a minor consequence of continued DSB exposure in vivo, a recent study shows that DNA damage-induced, age-associated functional decline can be attributed in large part to systemic consequences of DSBs, including cell death, tissue atrophy and the ensuing, non-cell-autonomous inflammatory response."
2019: "We present evidence that the response to DSBs changes the compartmentalization of chromatin and introduces transcriptional and epigenetic noise that closely mimics what happens during normal aging, including hallmark changes to the histone modifications, gene expression, and DNA methylation patterns." "After repair, the epigenome is reset but not completely, leading to progressive changes to the epigenetic marks and chromatin compartmentalization of the genome." "In the parlance of Waddington, the youthful epigenetic landscape is eroded to the point where cells head towards other valleys, losing their identity in a process we have termed "exdifferentiation.""
On 2019-11-08 16:26:18, user V Blaine wrote:
THCA might be the diet pill that could revolutionize the obesity industry. I suppose it is related to cannabinoid hyperemesis syndrome. And it is based on the theory that reducing a drug causes the opposite of what the drug causes. THC increases appetite and THCA causes limited appetite. I am only giving my two cents based on my experiences so that researchers can perhaps test some of these hypotheses as cannabis becomes more accepted.
On 2021-02-09 15:44:10, user Jasmina Wiemann wrote:
The data provided in this Preprint have been quantitatively analyzed in the context of a larger spectral sample set, and no similarities between the disputed spectra and edge filter artefacts were recovered. Please find the detailed response to this study here: <br /> https://t.co/nFE4pqi9wx?amp=1
On 2019-02-05 09:10:55, user Ian Collinson wrote:
Congratulations on your study. We’d like to draw your attention to one of ours. <br /> Allen et al eLife 2016;5:e15598<br /> The similarities are indeed very interesting for such a diverse system. <br /> Best wishes<br /> Ian Collinson (ian.collinson@bristol.ac.uk)
On 2022-03-23 16:24:04, user Sam Lord wrote:
Did the authors not see our reviews? The statistics are wrong in Fig 5, but the published version made ZERO effort to fix this problem. Very disappointing.
On 2019-05-14 05:17:04, user Preeti Garai wrote:
This manuscript from Garai et al. has been recently accepted for <br /> publication in PLOS Pathogens. Significant changes have been made to the <br /> preprint during the revision process and a link to the published article <br /> is forthcoming.
On 2020-09-01 22:09:23, user Alexander Novokhodko wrote:
Dear Authors,
I believe figure 3 has two residues labeled 490 in the RBD. It looks like it should just be the phenylalanine and the leucine should be labeled differently. Please correct this typo, or let me know if I am misunderstanding something.
Thank You,<br /> Sincerely,<br /> Alexander Novokhodko
On 2020-11-06 09:24:59, user Katsushi Kagaya wrote:
This preprint is published: https://www.life-science-al...
On 2020-07-09 22:43:43, user Giovanna Sassi wrote:
I do not see the supplemental Tables (Excel spreadsheets) under the Supplemental materials link, only the .doc file is available. Please, can you provide the Excel sheets?
On 2020-11-04 13:51:19, user Antonio Hohn wrote:
Published!!!<br /> https://doi.org/10.1371/jou...
On 2018-09-15 09:33:43, user Andrea Martinez Vernon wrote:
Published in Bioinformatics: https://doi.org/10.1093/bio...
On 2023-01-31 22:59:50, user Bruce Kirkpatrick wrote:
The data presented in Figures 1C and 1D seems to internally conflict — it would be unusual for the mesh size to increase past the size of the soft, non-degradable condition without the modulus decreasing correspondingly (i.e., it is odd that a mesh size 50% greater in the stiff vs. soft condition could be achieved in the context of a G' that is 3-fold greater in the stiff than soft condition).
On 2023-02-13 00:52:12, user John Barry Gallagher wrote:
The article as it stands makes it not possible to verify their results or conclusions: 1) there is no data or presentation of the 210Pb geochronology or independent validation, especially important in these not ideal dynamic depositional environments; 2) no disentanglement between seaweed and their epiphyte remaining deposits and allochthonous deposits, importantly that have been consumed before deposition; 3) While the title focusses on deposits under the farm, there should thus be a discussion or quasi estimation of the amount of export that survives consumption and the role of calcareous epibionts and benthic fauna on the sequestration rate the article implies from organic carbon soil accumulation; 4) how does sequestrtaion of biomass related to atmospheric flux, driven but not equivalent.
On 2025-10-03 08:55:58, user Tomáš Strecanský wrote:
Dear authors,
Great work on this study, thank you for sharing it as a pre-print.
I have a few quick questions about the methods that would be helpful for clarification:
What was the centrifugation speed and time used to obtain the blood plasma?
Could you specify the brand and material of the filter used for the plasma filtration?
What were the sample plasma volumes used for the cfRNA extractions?
For the sequencing, could you clarify the number of samples pooled per PromethION flowcell and the resulting sequencing depth and per sample number of reads (for both long and short reads) for each sample?
Thanks in advance for the details. I'm looking forward to the next version of the paper!
All the best,<br /> Tomas Strecansky<br /> PhD student<br /> Institute of Molecular Biomedicine<br /> Comenius University in Bratislava
On 2024-07-11 13:25:32, user Pookey532 wrote:
A small correction in Table 1.<br /> CRISPR gRNA vector wrongly including PAM sequence, the consequence should say "gRNA plasmid becomes target of CRISPR cleavage" with the caveat that this would only be the case if the wrongly included PAM is followed by another PAM, which is not the case in many CRISPR plasmids such as the pX330 derived ones. This would obviously affect cleaving at the target if its PAM is not followed by a second PAM.
While some errors in the table are almost certainly errors in design (ex stop codons before a 2A sequence, mutations in ITRs, etc...) I'm curious why some of the other design "errors" are deemed errors. For example, using CMV in AAV vectors can be a perfectly acceptable choice depending on the use of the virus, especially if it isn't intended for long term expression. Likewise, use of "unstable" sequences in high copy plasmids can be a problem, however if those plasmids are maintained in bacteria that maintain plasmids at a low copy (Epi400, Stbl2, etc...), the replication origin of the plasmid becomes less relevant as the copy number becomes more dependent on the host strain. Similar to this, "Vectors containing toxic genes to E. coli host" is not necessarily a design error. Sometimes this simply the only option.
On 2024-04-23 17:09:36, user Moira C wrote:
Hello, the Yadav lab has shown data on a protein structurally similar to SLK in humans called TAOK1, I have linked their paper here https://www.science.org/doi.... Do you have any comment on the similarity between these two proteins especially since this other kinase seems to have an I-bar domain as well.
On 2021-03-04 22:45:49, user Dawson White wrote:
Thanks for your hard work elucidating these processes. I am very curious, what happens to within vs among group turnover when the numerous singleton clades are removed? I am also keen to understand the elevational distribution of your clades with >2 samples. Good luck moving forward!
On 2015-10-02 16:36:40, user turnersd wrote:
Why not link directly to the github page (semi-permanent), then link to your lab website (not-so-permanent) from the github README?
On 2016-08-30 09:33:53, user Matilda Katan wrote:
For quite some time we and others working on FICD were concerned about its true enzymatic function. In particular, having to use an E234G variant to show AMPylation raised many doubts. Now, Preissler et al. not only solve this puzzle but also place FICD in a physiological context i.e. protein folding homeostasis in the ER. Great manuscript!
Matilda Katan
On 2015-07-06 13:09:25, user David Curtis wrote:
We were wondering how this compared with simply using LD-pruning? What results do you get for the same datasets when you just try to correlate the effects of an LD-pruned set of SNPs?
On 2023-12-01 00:33:58, user Rex Mitchell wrote:
Now published in Biological Reviews
On 2020-12-14 18:30:37, user Rachael Tarlinton wrote:
As others with more experience in Bio-informatics than me have pointed out the chimeric reads reported here are likely an artifact of the sequencing method. The authors have also used a very artificial cell culture system to specifically drive the phenomenon they were seeking and even then have not actually demonstrated integration of virus into the genome (this would as others have pointed out require sequencing of the DNA of the cells rather than the RNA to capture the integration sites between cellular and viral DNA). <br /> There does seem to be a case (in general) that viral infections in cells lead to increased expression of retroelements (we have reported on this ourselves) but in no case that I am aware of has anyone demonstrated that this then leads to integration of the virus (or the retroelement) into the genome. In people the accumulation of new retroelement integrations is a very rare occurrence indeed (these types of evolutionary events are measured in millions of years, not an individuals life span) . This is not the case in species with more recent and active retroviruses (such as pigs, sheep, koalas, mice, chickens) but even in those species they do not typically pick up or insert sequences from other virus classes (these types of events are even rarer than new retroelement insertions). The mechanisms speculated here have also never been known to occur with HIV infections in people (an incredibly well studied retroviral infection). <br /> This paper certainly does not demonstrate that SARs-Cov-2 is or is likely to become integrated in a human genome.
On 2017-01-07 05:47:25, user Toni wrote:
My son was recently diagnosed with this also and I'm so lost and confused. I have so many questions about TAF1, any info greatly appreciated.
On 2017-12-08 13:32:38, user Nesrecna wrote:
Dear parents, lets form a group to share info about taf1, and do more for our kids, i am more than willing to do anithing to know more about taf1, and to do more about the research itself, we need to find a way . You can contact me on my e-mail aleksandrav87 @gmail.com. Please share every info that you can remember if there was problem during the pregnancy, during birth and after...I have had many problems during the pregnancy(polyhydroamnion etc), premature delivery in 35 week(natural birth), my baby boy sufferd severe perinatal aspyhyxia, haemorrhagia IlI and many problems after. His look is not anything like tipycal Taf1, but hypotonia, reduction of white brain matter and breathing problems are present etc.If there are any mistakes in my writing, forgive, english is not my native language.
On 2023-03-28 20:25:39, user Alexander Nikitin wrote:
The authors would like to add Blaine A. Harlan and Minseok Kim as co-authors of this manuscript. The list of authors in this preprint should read as Dah-Jiun Fu, Andrea J. De Micheli, Blaine A. Harlan, Mallikarjun Bidarimath, Minseok Kim, Lora H. Ellenson, Benjamin D. Cosgrove, Andrea Flesken-Nikitin and Alexander Yu. Nikitin, with DJF, AJDM and BAH indicated as equal contributors.
On 2020-11-18 14:18:48, user Olga Matveeva wrote:
High quality paper. There are two recently published papers with similar messages "The genetic structure of SARS-CoV-2 does not rule out a laboratory origin" https://doi.org/10.1002/bie... and " SARS-Cov-2 Natural or Artificial? That is the Question" <br /> DOI: 10.31487/j.CMR.2020.01.06
On 2021-03-22 22:22:39, user Anuradha Wickramarachchi wrote:
Congratulations on your work.
We would like to know if there is an implementation made available for this tool. Furthermore, could you clarify a bit more on the logistic regression classifier trained? Is it trained on k=3-7'mers or something else.
Thanks in advance!
On 2024-01-02 10:57:26, user Anita Bandrowski wrote:
Trying to track down the "Sema4B+/– mutant mice" from MMRRC. Can you please provide the RRID for that resource?<br /> Thank you in advance, <br /> anita
On 2016-03-22 15:54:40, user Jonathan Eisen wrote:
I wrote a short blog post about this paper for microBEnet: http://microbe.net/2016/03/...
On 2020-12-22 13:08:44, user ?? ?? wrote:
This manuscript has published online in the Rhinology journal website.<br /> https://www.rhinologyjourna...
After reviewing, we made some important changes to the content of the paper that reflected the results. Unfortunately, bioRxiv said they was not able to link it to the website, because the manuscript was published as "letter", not "original article".<br /> Please see the following link. https://www.rhinologyjourna...<br /> Thank you.
On 2021-06-18 18:06:01, user Briana Rivera wrote:
Hello.<br /> I really liked the paper, it was enjoyable and I learned a lot about the Ash1L gene. Overall, I thought the figures were beautifully put together. I appreciated how Figure 3 was organized and how the abnormal behaviors of adult mice were observed and measured. I understand autistic-like behaviors were the focus of the research but I wondered if other specific neurodevelopmental disorders were considered, since the clinical manifestations listed might also overlap with other disorders. I also appreciated seeing the differences between the global and conditional knockouts respectively. In regards to the conditional knockout, I wondered if perhaps a different promoter, like the neuron specific enolase promoter, was ever considered and if it would yield similar results. I also wondered if a conditional knockout after maturity, such as one conducted through a tamoxifen inducible cre system, would be of interest to then compare subsequent effects on brain morphology and mice behavior alike. I also appreciated Figure 4. I thought maybe as a separate or supplemental figure it would be of interest to do a gene expression comparison of cell lines derived from humans without an ASD diagnosis and those with an ASD diagnosis with an Ash1L mutation to then see if the pattern of gene expression might be similar to the results in Figure 4.<br /> Thank you for sharing all of your hard work.
On 2025-08-13 17:34:25, user Ruslan Dmitriev wrote:
Now published as:<br /> Okkelman, I.A., Zhou, H., Borisov, S.M. et al. Visualizing the internalization and biological impact of nanoplastics in live intestinal organoids by Fluorescence Lifetime Imaging Microscopy (FLIM). Light Sci Appl 14, 272 (2025). https://doi.org/10.1038/s41377-025-01949-0
On 2017-07-06 10:55:22, user Anonymous wrote:
Scales of the figures are off. Also inches seem inappropriate
On 2020-12-08 16:06:32, user uzenzo wrote:
Can it cause syncytia formation? Have the vaccines been tested for possible organ-level dysfunction due to Spike?
On 2023-07-19 14:11:28, user Karel Muller wrote:
Would it be interesting to compare the evolution rate with other CO2 fixing enzymes in plants (PEPC)? Maybe add a word or two in the discussion?
On 2022-02-02 15:23:28, user Xiaojie Qiu wrote:
After 3.5+ years of perseverance, this work is finally online in Cell today! https://www.sciencedirect.c.... Feel free to read (we made it open access) and please let us know how do you think.
On 2023-11-15 21:29:07, user Arshia Zernab Hassan wrote:
Now published in Molecular Systems Biology https://doi.org/10.15252/ms...
On 2018-10-25 09:53:41, user m wrote:
Is there a typo in equation 1, or is the second sum supposed to be all zero terms?
On 2015-05-13 16:35:53, user Josiah Zayner wrote:
A protein with a single mutation can become sub.neofunctionalized. Some may even argue that mutations to a coding region in a gene that don't change the protein sequence could change the translation rate, which changes the folding, which changes the function. It appears you are looking at genes that are not identical so how do you know they aren't sub.neofunctionalized?
On 2020-05-12 09:48:20, user Gilthorpe Lab wrote:
'As of April 29, 2020, COVID-19 has claimed more than 200,000 lives, with a global mortality rate of ~7% and recovery rate of ~30%' - where is the citation for this? It is simply unjustified to state figures such as this.
On 2020-02-13 02:33:59, user Kittichai Jookjantra wrote:
Do the rats have normal immune systems, especially Interferon?
What is the difference in viral load in mice before and after the experiment?
On 2018-11-20 13:13:47, user Ingmar Claes wrote:
Very proud of being part of the bacterial revolution! At YUN we are convinced that the live biotherapeutic products (LBP) field can jointly reduce the (over/mis)use of antibiotics!
Many thanks to the University of Antwerp and the University Hospital of Antwerp! This wouldn't have been possible without this collaboration. <br /> @SarahLebeer @Eline_Oerlemans @Filip_Kiekens @Tim_Henkens @Julien_Lambert
On 2017-05-18 10:50:50, user Sankar Chandra Basu wrote:
Accepted in Journal of Molecular Modeling. Currently In-press.
On 2020-02-14 15:52:22, user Sebastian Dresbach wrote:
Dear Johanna Bergmann, Andrew Morgan, & Lars Muckli,
Thank you for providing your interesting manuscript as a preprint. Recently, we discussed this preprint in a journal club concerning layer (f)MRI at Maastricht University and would like to provide some comments.
In general, we enjoyed the idea of applying depth dependent imaging to investigate the complex architecture underlying mental imagery and visual illusions, rather than probing basic mechanisms. Furthermore, we liked the way in which you use the stimuli to distinguish between the short-range and long-distance connections between proximal and distant cortical regions and V1. However, we were wondering about the use of distinct ROIs representing foveal and peripheral space for the two types of feedback. Specifically, we reasoned that using identical shapes and ROIs would have rendered the comparison between the depth-dependent profiles of mental imagery and illusory percept more straightforward.
We liked that you first delineate the ROIs in surface space and subsequently project the selected vertices back to volume space, as this seems less susceptible to cortical depth artefacts. On the other hand, several issues can be raised concerning the (presentation of the) data quality and results. For example, providing tSNR maps and/or a few slices of the functional images would give a better feel for the data quality and provide a reference for the future studies. Furthermore, the r²-threshold for voxel selection appeared lower than what we are used to seeing in other similar studies (e.g. minimum around 0.3 to 0.5 range). We would be curious to hear your thoughts on this.
Your main results are based on the group-level averages of decoding accuracy for different conditions. We highly appreciate that you also report the single subject data in the supplementary materials. As it is often the case, the single subject plots seem to be quite different than the group-level results in multiple subjects. We think that a discussion on how this influences the overall conclusions would be worthwhile.
Minor points concern the reporting of (f)MRI parameters: Some units (e.g. for TE) are missing and we believe there is a typo in the voxel size reporting throughout. Instead of “0.8mm³”, we guess that you have meant 0.8 mm isotropic or 0.8³ mm³ or 0.8×0.8×0.8 mm³. Finally, reporting the partial Fourier-type you employ might also be important to report as this choice highly influences the resulting image quality and might provide some insight with regards to the effective image resolution.
We hope that our input is valuable to you in some form for the next iteration of this article
With kind regards,
Sebastian Dresbach, Lonike Faes, Johannes Franz, Faruk Gulban, Renzo Huber, Amanda Kaas, Till Steinbach, & Yawen Wang
On 2023-02-03 08:53:18, user Marc RobinsonRechavi wrote:
Nice work. Checking the LEUTX gene in our Bgee database, I noticed that its top expression is in male germ line, maybe this is relevant to the fast evolution of this gene?
On 2018-12-06 11:08:08, user Elmar Tobi wrote:
Dear all, this article has now been published at Cell Reports: https://www.cell.com/cell-r...
On 2022-01-11 20:42:36, user Mina Bizic wrote:
I would like to congratulate Rachel Szabo and colleagues on their great work and effort put into this manuscript. The goal of analyzing such a high number of particles has been something I have been calling for ever-since my work cited in the comment by Dr. Jacob Cram (Bizic-Ionescu et al., 2018). It’s exciting to see the efforts you have made in this direction.
It’s equally exciting to see that my conclusion from 2018 that the initial colonization of particles is stochastic, is strongly featured in your paper title and well supported by your results.
As Dr. Cram has mentioned in his comment, we discussed your study and have come up with several aspects that we feel deserve some attention and most likely to be better addressed in the manuscript. Some of these aspects were raised by Dr. Cram in his comment. However, we felt that our opinions on this manuscript were dissimilar enough to warrant separate comments, with some observations that overlap and some that differ.
My general query goes to the applicability of the results to the natural environment, given several biases introduced by the chosen experimental system. I will list here my opinion on the source of these biases.
1) The concentration of seawater is likely to have generated an unrealistic microbial community. This is for three reasons (A) concentration of particle-attached microbes, (B) concentration of large bacteria, and (C) non-concentration of DOM: <br /> (A) Filtering the water through a 63 µm mesh should leave all particles smaller than this size in the water The subsequent step of gentle centrifugation most likely further concentrated these microparticles increasing their abundance above natural concentrations. <br /> (B) The gentle centrifugation likely selected for larger bacteria, as smaller cells may not be concentrated by a 5 min 4000 g run. <br /> (C) Finally, the seawater DOM on which bacteria can feed was not concentrated in this process. <br /> Therefore, the resulting inoculum used for the experiment contains a size-selected microbial community and a microparticle enrichment which in the absence of ambient DOM will rapidly drive the experiments towards consumption of the particulate organic matter at rates not representing the natural environment.
2) The incubation time and small volumes: While samples have been collected already after 12 h the experiment ran for 166 h in a closed microwell. It has been shown by many as well as by my colleagues and I that after 24 h at the latest, the community in the experiment does not represent the environmental one (for example: Baltar et al., 2012; Ionescu et al., 2015; Herlemann et al., 2019). Therefore, seeing such long experiments conducted in fully closed systems, as in this paper, makes me wonder to what degree the rates of events observed in the lab are similar to rates in nature.
3) One possible problem with the incubation system used, is the effect of the microwell surface on microbial activity. Ploug and Jorgensen (1999), for example, came up with the net-jet system for measuring microprofiles on organic matter aggregates. However, aside of the effect of direct contact of particles with surfaces on particle properties and the microbial activity on it, a second issue is the formation of biofilms may form on the surfaces of the incubation system. Heterotrophic activity is known to increase in closed incubation systems (e.g. Fogg and Calvario-Martinez, 1989; Ionescu et al., 2015). Though it was shown that these biasing effects will occur regardless of bottle size (Hammes et al., 2010), these will likely have a stronger effect in very small incubation volumes (Herlemann et al., 2019), consuming oxygen and nutrients. I don’t recall reading whether the O2 concentration was monitored? My guess is that the system became anoxic relatively fast, unlike it would be in a natural environment. How does this affect the nature of associated (and active) bacteria?
Having said that, I support the authors’ overall conclusion and applaud the effort that went into the data collection and analyses I am aware from my own work on the difficulties to obtain and maintain such a large number of particles in open systems, such as the one my colleagues and I designed. However, I think that the biases introduced by an experimental system should be openly discussed in the manuscript and if possible, explain how your results remain valid despite them. This is even more important when you often discuss late-stage particles, that are the most to be affected by aspects mentioned above.
Sincerely,
Mina Bizc
References
Baltar, F. et al. (2012) Prokaryotic community structure and respiration during long-term incubations. Microbiology open, 1, 214–224.
Bizic-Ionescu, M. et al. (2018) Organic Particles: heterogeneous hubs for microbial interactions in aquatic ecosystems. Front. Microbiol., 9.
Fogg, G. E. and Calvario-Martinez, O. (1989) Effects of bottle size in determinations of primary productivity by phytoplankton. Hydrobiologia, 173, 89–94.
Hammes, F. et al. (2010) Critical evaluation of the volumetric “bottle effect” on microbial batch growth. Appl. Environ. Microbiol., 76, 1278–1281.
Herlemann, D. P. R. et al. (2019) Individual physiological adaptations enable selected bacterial taxa to prevail during long-term incubations. Appl. Environ. Microbiol., 85.
Ionescu, D. et al. (2015) A new tool for long-term studies of POM-bacteria interactions: Overcoming the century-old Bottle Effect. Sci. Rep., 5.
Ploug, H. and Jørgensen, B. B. (1999) A net-jet flow system for mass transfer and microsensor studies of sinking aggregates. Mar. Ecol. Prog. Ser., 176, 279–290.
On 2022-02-16 01:03:10, user Michael wrote:
Recording useful metadata in a standard format is definitely a laudable goal. Building on OME, as discussed, is great. But I find that a far larger problem than instrument settings is not having information on the biology (and other reagents). Knowing that an image was taken with a 60x N.A. 1.4 Nikon planapochromat lens at 100 ms with an Andor Zyla 5.5, LED excitation at 555 nm, bandpass emission 580+/- 40 nm, with Micromanager 2 beta with ImageJ 1.53q23 running under Java 1.8.005.93b is irrelevant if you don't know the cell type and molecule labeled. In fact, we could change every detail of the technical minutiae about the microscope to digital file and the only important thing would be the cell type and molecule labeled. Metadata need to prompt the user to include details about the experiment. Proprietary systems do save the technical details pretty well, at least for standard imaging, but none record the biology (or whatever is being imaged). One critical field that’s should be added a phrase stating the goal of the experiment (like a tweet). Every notice that when you go for a clinical diagnostic medical procedure that the technician enters all sorts of data about the patient or pulls them out of an existing record? This is what is missing from microscopy metadata. This is where there really is a crisis.<br /> Sample prep and biological samples are mentioned in the introduction, but are largely absent throughout the text. However, these are the most important data that need to be recorded with the images.
On 2015-02-25 20:42:24, user Lutz Froenicke wrote:
How many MinIon flow cells were sequenced for the project in total? The manuscript reports that the data of four cells were used. The yields tend to vary - e.g. page 6 here: http://schatzlab.cshl.edu/p...
On 2018-05-14 22:02:04, user Wentao Zhu wrote:
Early Accepted by MICCAI 2018
On 2019-07-12 23:16:36, user Charles Warden wrote:
I believe a peer-reviewed version of this paper has been published:
https://www.sciencedirect.c...
I remembered this as a pre-print, so thank you for posing this!
On 2025-11-07 10:51:52, user Tatsuya Yamashita wrote:
Dear authors,
at first, congratulations to this important findings. This data, paired with other ancient DNA evidence, can further clarify the demographic patterns of the peopling of Eastern Eurasia and Oceania, as well as their interactions with archaic human groups. Different deeply branching Denisovan components can be very useful data points for possible migration routes and or population substructure scenarios.
In your pre-print, you argued for a possible earlier southern route into Oceania, followed by a later wave of the ancestors of South Asians (AASI) and East Asians, with East Asians via a possible northerly route: "This supports an early migration of the ancestors of Oceanians through South Asia followed by the later arrival of the ancestors of present-day South Asians. East Asians do not share this Denisovan component in their genomes, suggesting that their ancestors arrived independently, perhaps by a northerly route".
One major problem with this scenario is the observed genetic affinity between the different "basal Asian" populations (e.g. Tianyuan, Önge, Hoabinhian, Xingyi_EN, Jomon/Shiraho_27k, AASI, and Australasians/Oceanians such as Papuans); also known as "eastern non-Africans" (ENA) or "East Eurasian Core" (EEC). The aDNA data strongly suggest a single dispersal route and subsequent rapid diversification into multiple basal Asian lineages (presumably in the South-Southeast Asia region via a single Southern route).
E.g. Oceanians/Papuans can successfully be modeled (qpAdm/qpWave) as simply Önge-like + additional Denisovan; or alternatively as Tianyuan-like + additional Denisovan. They do not fit as outgroup to "West/East Eurasians" either, but are nested within the "Eastern" clade (e.g cluster with Önge, Tianyuan, or present-day East Asians).
Although it is possible to reproduce a signal affilated with a distinct earlier southern coastal route (proxied by ZlatyKun_45k); this wave however left only minor ancestry among present-day Oceanians/Papuans (and or South Asians), with the majority ancestry of them being derived from the same source as Önge or Tianyuan: e.g. ZlatyKun + Önge-like + extra Denisovan, in a 3–5%, 92–95%, and 2–3% ratio respectively. (qpGraph models allow higher "early ancestry" for Oceanians/Papuans: 12–24% when splitting before or at around the same time as ZlatyKun/Ranis, or up to 44% when splitting at the same time as Ust'Ishim.)
Beyond that, a northern route entry for the ancestors of East Asians seems to be only partially possible, as the majority ancestry of East Asians seems to be from an Önge-like source (except Önge also used a northern route entry).
This means that present-day eastern non-Africans (ENA) descend primarily from a single migration wave eastwards, presumably via a route South of the Himalayas; and which possibly absorbed an earlier less successfull wave, at least regionally (Oceania and South Asia).
This may also have happened via a more substructured wave: e.g. both a southern coastal route (along the coast of the Indian subcontinent) and a southern interior route (via an interior route along the southern Himalayan mountain range) into Southeast Asia and beyond. – It is however well possible that the southern coastal wave pre-dated the southern interior wave, and thus display different Denisovan signals. E.g. timely separated migrations waves of a shared clade.
Regional Denisovan admixture events (or their partial absence as in the case of Jomon HGs [see the recent paper by Jiaqi Yang et al. 2025 "An early East Asian lineage with unexpectedly low Denisovan ancestry"]) can be explained that way, without needing several different distinct waves, which would contradict the observed genetic affinities of the different Basal Asian lineages. The low Denisovan ancestry of Jomon hunter-gatherers may or may not be affilated with the Shiraho_27k specimen, who appearently contributed some ancestry to later Jomon. For more information on the Shiraho_27k specimen, please contact your co-author Svante Pääbo or Hideaki Kanzawa-Kiriyama.
Note that Tianyuan40k can successfully be modeled as Önge-like + IUP-affilated admixture (BachoKiro_IUP); which fits the presence of IUP material sites in nearby NW China and Mongolia. Such IUP admixture has also been noted to explain the observed affinity to the GoyetQ116-1 specimen in Europe, which similarly can be modeled as Kostenki14/Sunghir_UP + BachoKiro_IUP (see Hajdinjak et al. 2021 "Initial Upper Palaeolithic humans in Europe had recent Neanderthal ancestry").
It is possible that this Siberian IUP group absorbed the EA-specific Denisovan component and via its admixture into Tianyuan, contributed it to other Eastern Asians in lesser amount. – Present-day East Asians in turn can be successfully modeled as Tianyuan-like (c. 25%) + Önge-like (c. 75%); (see McColl et al. 2018 "The prehistoric peopling of Southeast Asia" for example). – Via Tianyuan-like or Denisovan-admixed IUP groups, this archaic ancestry may have also reached regions further West (as with the supposed Denisovan signal in Sunghir etc.).
You can also review Bennett et al. 2024 "Reconstructing the Human Population History of East Asia through Ancient Genomics", a recent summary paper on the peopling of Eastern Asia and beyond; as well as Tianyi Wang et al. 2025 "Prehistoric genomes from Yunnan reveal ancestry related to Tibetans and Austroasiatic speakers".
A summary of my points regarding your postulated "earlier southern route" for Oceanians and a possible "northerly route" for East Asians:
• The available genetic data strongly suggests a single shared migration wave for the primary ancestral source of all eastern non-Africans (Papuans, AASI, East Asians, Önge/Hoabinhian, and Tianyuan). The presence of multiple deeply branching EEC lineages in Southeast Asia and southern China suggest it to be a major place of diversification from a shared ancestral source.<br /> • Papuans/Oceanians (and AASI) may have limited amounts of admixture from an earlier wave, but primarily share ancestry with Önge and Tianyuan.<br /> • Tianyuan can be modeled as either an admixture between Önge-like (61–67%) and BachoKiro_IUP-like (33–39%) ancestries; or represents a deep split from the rest of eastern non-Africans; although with some geneflow into later East Asians.<br /> • Ancient and present-day East Asians can be modeled as primarily Önge-like (c. 75%) with Tianyuan-like admixture (c. 25%).<br /> • The different Denisovan introgression events, if not shared, may have happened regionally to explain the observed affinities, but the differences in Denisovan components among each group.
Below some qpAdm results on this (AADR v.62 + Ranis dataset); allsnps=TRUE:
Model1<br /> target: Papuan<br /> left: Hoabinhian, ZlatyKun, Denisovan<br /> right: Mbuti, Ranis13, Ust'Ishim, BachoKiro_IUP, Tianyuan, Önge, Kostenki14, Sunghir_UP<br /> Results: Hoabinhian: 93,9%; ZlatyKun: 3,2%; Denisovan: 2,9%;<br /> p-value: 0.061
Model2<br /> target: Papuan<br /> left: Japan_Jomon, ZlatyKun, Denisovan<br /> right: Mbuti, Ranis13, Ust'Ishim, BachoKiro_IUP, Tianyuan, Kostenki14, Sunghir_UP<br /> Results: Japan_Jomon: 94,1%; ZlatyKun: 2,4%; Denisovan: 3,5%;<br /> p-value: 0.094
Model3<br /> target: Tianyuan<br /> left: Önge, BachoKiro_IUP<br /> right: Mbuti, Ranis13, Ust'Ishim, Oase1_IUP, Papuan, Hoabinhian, Kostenki14, Sunghir_UP<br /> Results: Önge: 65,5%%; BachoKiro_IUP: 34,5%%;<br /> p-value: 0.170
Model4<br /> target: Japan_Jomon<br /> left: Önge, Amur33k<br /> right: Mbuti, Ranis13, Ust'Ishim, BachoKiro_IUP, Tianyuan, Papuan, Hoabinhian, Kostenki14, Sunghir_UP<br /> Results: Önge: 79,0%%; Amu33k: 21,0%;<br /> p-value: 0.053
Model5<br /> target: Han_Chinese<br /> left: Önge, Amur33k<br /> right: Mbuti, Ranis13, Ust'Ishim, BachoKiro_IUP, Tianyuan, Papuan, Hoabinhian, Kostenki14, Sunghir_UP<br /> Results: Önge: 73,6%%; Amu33k: 26,4%;<br /> p-value: 0.090
Etc.
(Önge = ONG Mondal; Jomon = JpOd181/274/282).
E.g. it is not likely that Oceanians were part of a distinct earlier wave into Oceania, separate from other mainland Asian groups, nor that East Asians reached East Asia along a distinct northern route (independently of Önge-like groups etc.). Next to qpAdm/qpWave or qpGraph models, f3/f4 statistics are quite clear on this. Papuans are (beyond their extra Denisovan ancestry and possible minor "earlier group" admixture) nested in eastern non-African diversity (e.g. EEC).
It is plausible that after the OoA exit, and the IUP/EEC dispersals from a Hub on the Persian plateau, Eastern non-Africans (ENA/EEC) shared a secondary Hub somewhere in Northwest India, from which Oceanians expanded first, via a coastal route towards Oceania. Along the coast of the Indian subcontinent (South India?), they absorbed the Deep Denisovan ancestry and continued to expand to Oceania. – Some time afterwards, the remainder ENA/EEC group (residual) expanded along an interior route South of the Himalayas into Southeast Asia and Southern China; not admixing with the Deep Denisovan group. – There, one branch split and head towards Japan (low Denisovan), while another group headed northwards coming into contact with IUP groups & the EA-specific Denisovan (Denisovan3-like) component (=Tianyuan_40k); while the remainder absorbed a local Denisovan group in Southern China or Southeast Asia (=Önge-like). – This Önge-like groups expanded back into South Asia/India, absorbing the group with Deep Denisovan introgression (becoming the AASI). The Önge-like groups staying in Southeast Asia became the Hoabinhians, while early East Asians formed along a cline of Tianyuan-like and Önge-like ancestries.
Of course the above scenario is just one of many possibilities; it is well possible that Oceanians used a southern route, while the ancestors of both East Asians and Önge used as northerly route. – Or any other scenario which can explain the aDNA data and genetic affinities.
My suggestion is to define a model which alignes with both aDNA data and archaic components (for ancient and present-day populations), as well as, if possible, archaeologic and paleoenvironmental evidence.
E.g. including a set of ancient and present-day groups to test on their Denisovan components and their overall genetic affinities (not just modern groups to prevent bias from ancient geneflow events): For South Asians: AASI-rich tribal groups from Southern India, such as Irula and Paniya; for SEA: Önge, Hoabinhians; for EA: the newly analyzed Xingyi_EN samples, Jomon, Longlin, Amur14k, Qihe3, Tianyuan and Amur33k, as well as present-day East/Southeas Asians; for Oceania: Papuans, Australians, and Aeta. Maybe a chart comparing shared/distinct Denisovan components and f3/f4 statistics of each test group to each other would help clarify the exact affinities, shared routes or geneflow events. Perhaps, your co-author Svante Pääbo can share informations on the Shiraho_27k specimen and its Denisovan components.
A strong model should explain the genetic data/affinities of ancient/present-day populations, their different Denisovan components, and in best case also include archaeologic and paleoenvironmental data. To determine the influence of ancient geneflow, comparison between ancient specimens could help (Tianyuan vs Önge vs Jomon vs Longlin vs Amur14k etc.).
I hope this information can help to tangle out some possible scenarios on the dispersal, contact and introgression events for the different deeply branching Denisovan components and present-day Asian populations. Or maybe inspire future studies on this topic.
I am looking forward for the publication of your paper and more exciting findings!
Thank you.
Yours sincerely,<br /> Yamashita Tatsuya
On 2021-07-21 02:01:35, user ygc_smu wrote:
now published on The Innovation, https://doi.org/10.1016/j.xinn.2021.100141
On 2018-07-31 11:27:24, user H. Etchevers wrote:
Just so I remember, the article has been accepted for a forthcoming Special Issue of genesis in honor of the 150th anniversary of the discovery of the neural crest. There has been a production glitch for most of the articles in this issue, but it should be out by the autumn, 2018. The future DOI of the accepted version will be: http://dx.doi/org/10.1002/dvg.23221
On 2018-01-19 02:16:43, user Xiaojian Li wrote:
Considering the "integrate and fire" model of the neuron, Statistically the step of firing spike which is a strong non-linear phenomenon only plays the role as pulse density modulation coding for better transferring analog signals...
On 2020-02-11 03:11:41, user Minxing Pang wrote:
Paper updated. Thanks for Tim Stuart 's suggestions!
On 2018-11-19 21:06:35, user Orob350 wrote:
Peer-reviewed version has been published:
On 2019-09-14 18:29:07, user Justin Perry wrote:
While this is a valiant amount of work on a very important topic, the likelihood that the TCR+ macrophages you see ex vivo are because of clearance of T cells by macrophages (RNA, including polyA-RNA, is incredibly stable in the phagolysosome) is high. These would likely not be removed by any of the standard single cell-RNAseq "doublet" removal techniques. The issue of RNA "contamination" has been shown independently by Dennis Discher (https://www.ncbi.nlm.nih.go... "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846676/)") and Steffen Jung (https://www.ncbi.nlm.nih.go... "https://www.ncbi.nlm.nih.gov/pubmed/29777220)"), and anecdotally seen by a host of groups attempting RNAseq (especially single cell RNAseq) of macrophages. I would urge caution in interpreting TCR+ macrophages as anything other than a macrophage doing its job of efferocytosis, and be wary of interpreting much from the gene signatures of macrophages because of this potential T cell contamination. Engulfment of T cells by macrophages shows a frustratingly high level of T cell-associated genes, especially prevalent genes such as those associated with signaling. None of the data presented in this preprint negate the likelihood of efferocytosis. In fact, CD68 is most commonly associated with LAMP1 and the endo-lysosomal compartments, and is often used as a marker of phagocytic macrophages in situ. Furthermore, FACS analysis of ex vivo TAMs could just as easily be of a T cell binding to TAMs, a TAM with a partially eaten T cell, or a manifestation of the tissue digestion process, where digestion at 37C for as little as 15-30 minutes can result in transfer of intact proteins (such as intact TCR), trogocytosis, or phagocytosis (like we frustratingly observed and reported previously https://www.cell.com/immuni... "https://www.cell.com/immunity/fulltext/S1074-7613(18)30144-4?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1074761318301444%3Fshowall%3Dtrue)").
On 2021-06-08 18:04:03, user Charles Warden wrote:
Hi,
Thank you very much for posting this preprint.
I am working on trying to read through the manuscript more carefully, which I hope can improve my understanding of STARsolo as well the regular STAR alignment. I also thought the different results with varying settings of Alevin was interesting and important.
However, in the meantime, I believe that you have a minor error in one of your references:
[30]. R. S. Brüning et al. Comparative Analysis of Common Alignment Tools for Single Cell RNA Sequencing. preprint. Bioinformatics, 2021. doi: 10.1101/2021.02.15.430948.
I think this should be a bioRxiv preprint (not a Bioinformatics preprint)?
For example, the DOI leads to this reference:
https://www.biorxiv.org/con...
Thanks Again,<br /> Charles
On 2020-05-01 23:34:33, user Aaron wrote:
The title of the manuscript seems a bit disingenuous. The authors show an increase in prevalence for G614 alongside increasing case numbers, but that is correlation, not causation. To make the jump that this is a more transmissible form of the virus would require functional studies. It seems that authors decided to go with the more sensational title rather than the more important one that this mutation didn't show any significant difference in patient outcome.
Importantly, we have millions of cases and only thousands of genomes sequenced at this point. There is likely to be some amount of bias in which genomes are being collected, with localized founder effects apt to skew proportions of mutations for a given country or region, i.e. a majority of sequences for a country/state coming from a single center.
On 2023-08-14 17:54:14, user Ioannis Tzanetakis wrote:
Now published in Plant Disease as https://doi.org/10.1094/PDI...
On 2018-11-05 17:25:57, user Dr. James D. Johnson wrote:
Wondering why you guys chose not to use INS as the marker for beta-cells?
On 2025-02-20 12:15:37, user kei wrote:
Thank you for your interesting paper.
I am curious about the behavior when only the non-natural amino acids in cyclic peptides are not tokenized at the atomic level, and all cyclic peptides are represented using SMILES. I am thinking of investigating this.
That said, I have one question:<br /> What is the input format when inferring complexes of cyclic peptides containing non-natural amino acids and proteins?<br /> (In other words, how are non-natural amino acids formatted in the input?)
If possible, I would appreciate it if you could share an example of the YAML file or other input data used for Boltz1.
Thank you in advance.
On 2017-07-04 10:03:15, user Bastian Pfeifer wrote:
The methods proposed in this paper are now available within the updated PopGenome package (version 2.2.4) on CRAN.
On 2020-08-01 04:30:38, user MS wrote:
The whole finding depends crucially on the "fact" that RaTG13 was indeed found in nature (bat feces), in 2013. Given that RaTG13 was made public in 2020, jointly with the virus itself, makes this assumption at least doubtful.
On 2021-02-10 11:15:08, user Guy wrote:
This is great .Are there plans to make the phone app available upon publication? I would observe it would be very useful to have more details physical setup, particularly of the lightning used for the phone work (from above or below, or both) and wether the brand of 96 well plates was important to the results.
On 2021-03-03 02:42:24, user Anna Octavera wrote:
The cell incorporation picture was not like incorporation of PKH-26 labelled cells. The author should show the clear picture showing cell incorporation. Many red spot in the genital ridge doesn't mean the incorporated cells. or if so, the author should show it in the high magnification view.
On 2025-10-07 17:56:56, user Marcelo R. S. Briones wrote:
This preprint is now published as peer review paper in Nucleic Acids Research Molecular Medicine https://doi.org/10.1093/narmme/ugaf034
On 2024-02-05 02:52:52, user Lily Cheung wrote:
This article has now been published under https://doi.org/10.1016/j.j...
On 2022-04-04 15:23:35, user Daniel Baldauf wrote:
Hi Frederik, nice study, congrats! I thought you might be interested also in the Bagherzadeh et al., 2020 Neuron paper. Also our paper from last year DeVries et al., 2021, JN might be of interest, showing single-trial decidability of attention from the alpha band.
On 2022-10-18 00:52:00, user Hypo wrote:
So please describe all of the protocols that are in place to prevent this prototype variant from escaping the Laboratory.
On 2021-08-02 16:04:51, user Dr Richards wrote:
The data shown in this publication is INCORRECT and is not endorsed by Charles River. The data shown to represent efficacy of camostat-colloid gold is actually that from the Oseltamivir control. No efficacy was seen with the camostat-colloid gold treatment.
On 2023-03-27 14:32:48, user Jphn Chatham wrote:
The authors of this very interesting study might want to consider the papr by Olson et al., PMID: 31915250
In that study they used LC-MS to quanitfy UDP-GlcNAc levels in the heart. In Figure 8 they report the concentration of UDP-GlcNAc to be about 500 nmoles/g heart protein, which is the equivalent to approx. 25 pmoles/mg tissue. This is a little lower than reported here, but is in roughly the same range and therefore supportive of the methods described here.
On 2017-11-15 06:51:58, user Christoph Nowak wrote:
Hi - great approach! I may have missed it - did you provide some (sample) code alongside the paper on github or similar? Thanks!<br /> Chris
On 2020-09-17 14:25:23, user michalopoulosgk wrote:
Could this be done in the liver in vivo by injecting relevant plasmids?<br /> George K. Michalopoulos
On 2020-04-20 15:32:48, user Nikhil Gopalkrishnan wrote:
Beautiful work! How did you guys get access to negative human saliva sample? Any commercial source you can point me to?
On 2018-03-24 12:28:19, user Davidski wrote:
Hello authors,
In your analysis you found that the Russian samples that you ran were Uralic-like, with a lot of Siberian admixture.
That's probably because these are the HGDP/Human Origins Russians from Kargopol district, which is a former Uralic-speaking region. In other words, your Russians are likely to have a lot of Uralic ancestry.
So there's nothing surprising about this result, and in contrast to what you stated in your preprint, these Russians actually support your overall conclusions, not contradict them.
It might be useful to sample and run a couple of ethnic Russian groups from well southwest of Moscow. They're likely to come out a lot less Uralic-like, which would help to further elucidate the impact that Siberian ancestry has had on Uralic-speaking and former Uralic-speaking populations of Europe.
By the way, to second Capra's comment below, the qpAdm analysis does look rather shaky. It'd be pretty easy to improve it by throwing in a few more ancient outgroups.
On 2023-08-12 13:52:44, user Youssef M Eltalkhawy wrote:
Very impressive and promising model
On 2020-08-04 08:06:21, user OxImmuno Literature Initiative wrote:
On 2017-04-12 21:40:20, user Liberate Science wrote:
This paper is missing a COI statement. These authors have actual COIs that are being hidden. Why is that? Secondly, the authors should make the full original data set open access, i.e., in accordance with open data policies that this group at METRICS promotes. The public needs to verify the exact papers and the exact images that were analyzed. Why was PubPeer not mentioned in this paper as part of the methodology? It was widely used by the last author, Bik, to report image issues.
On 2025-03-24 20:40:02, user Sara, Rosangela e Lucas wrote:
This review resulted from the graduate-level course "How to Read and Evaluate<br /> Scientific Papers and Preprints" from the University of São Paulo, which aimed<br /> to provide students with the opportunity to review scientific articles, develop<br /> critical and constructive discussions on the endless frontiers of knowledge, and<br /> understand the peer review process.<br /> DHRS7 Integrates NADP+ 1 /NADPH Redox Sensing with Inflammatory Li2 pid<br /> Signalling via the Oxoeicosanoid Pathway<br /> Yanan Ma1 , King Lam Hui1 , Yohannes A. Ambaw1 , Tobias C. Walther1,3 3 ,<br /> Robert V. Farese, Jr1 , Miklos Lengyel1 , Zaza Gelashvili1,2 , Dajun Lu1 , and<br /> Philipp Niethammer1,4<br /> Reviewer Team: Lucas Athayde, Rosangela Silva Santos, Sara Ventura.<br /> Summary<br /> Employing a variety of methodological approaches including structural modeling,<br /> phylogenetics, gene silencing, and mass spectrometry, the authors investigate 5-<br /> HEDH activity in A549 cells, an enzyme associated with lipid dehydrogenation<br /> that leads to 5-KETE formation. After confirming 5-HEDH activity through<br /> detection of its reversible oxidation products, 5-KETE and 5-HETE, the study<br /> proceeds with a gene-level investigation and screening for potential microsomal<br /> dehydrogenases involved in this lipid peroxidation. Additionally, the authors<br /> provide insights that may extend to other types of cells, as evidenced by<br /> functional studies in zebrafish.<br /> The authors uncover the role of DHRS7 in redox signaling, demonstrating its<br /> NADPH-dependent regulation of 5-KETE production. Unlike classical redox<br /> signaling based on thiol oxidation, they present DHRS7 as a redox-regulated<br /> enzyme that acts in 5-KETE biosynthesis, which is a highly novel and interesting<br /> mechanism. Under stress conditions, DHRS7 facilitates rapid inflammatory<br /> signaling and leukocyte recruitment through the 5-KETE pathway.<br /> Major Comments<br /> Identification of DHRS7 as a 5-HEDH Candidate<br /> The screening successfully identified DHRS7 as a candidate enzyme with 5-<br /> HEDH activity. LC-MS profiling of wild-type cell lines revealed increased 5-KETE<br /> levels in cells exposed to 5-HEDE and vice versa, with a stronger effect observed<br /> in 5-KETE accumulation. Surprisingly, 5-KETE production appeared to be<br /> favored under non-stress conditions. We would like to see a description of the<br /> data normalization to exclude the possibility that these differences arise from<br /> variations in cell viability, abundance, or any other experimental conditions.<br /> Alternative Pathways and Metabolic Compensation<br /> Another observation is the reduction in 5-KETE and 5-HETE levels in DHRS7<br /> knockout cells, corroborating the proposed DHRS7 role. But the persistence of<br /> these metabolites in silenced cells even at lower concentrations is curious, which<br /> leads to a few hypotheses such as the activation of endogenous compensatory<br /> mechanisms and exogenous uptake of these metabolites from the media. To<br /> further investigate the origin of these residual metabolite levels, it is essential to<br /> quantify 5-KETE and 5-HETE in the culture medium to test if the cells' knockouts<br /> exposure to these lipids could explain these residual levels. To evaluate if these<br /> residual metabolites could have originated from endogenous mechanisms, a<br /> transcriptome analysis could be used to identify other redox-active enzymes<br /> differentially expressed that could exhibit potential 5-HEDH activity thereby<br /> compensating DHRS7 silencing.<br /> Subcellular Localization of DHRS7<br /> The authors employed GFP-tagged DHRS7 constructs for subcellular localization<br /> and genetic complementation assays in DHRS7 KO A549 cells and zebrafish<br /> Dhrs7 KO models. This strategy successfully restored the wild-type phenotype,<br /> as evidenced by increased 5-HETE and 5-KETE levels upon treatment with<br /> precursors, corroborating the initial hypothesis of DRS7 as a 5-HEDH. However,<br /> the conclusion that DHRS7 localizes to microsomes lacks experimental<br /> validation, as no microsomal markers were used in confocal imaging. Indeed,<br /> cellular fractionation and Western blot assays indicate DHRS7 also localized in<br /> the nucleus, granules, and microsomes, but GFP fluorescence was absent in the<br /> nucleus. Given that the antibody used for Western blotting was available, it’s not<br /> clear why the authors did not employ an anti-DHRS7 antibody for<br /> immunofluorescence to precisely determine its intracellular distribution rather<br /> than relying on GFP-based localization assays.<br /> Kinetic Characterization of DHRS7 Activity<br /> The authors conducted enzymatic kinetics assays for DHRS7 and applied a<br /> Michaelis-Menten model for data fitting. However, the fitting shows clear<br /> deviations, with a notably low coefficient of determination (R²), suggesting that<br /> this model may not adequately describe DHRS7’s catalytic properties. In fact, a<br /> typical Michaelian model does not appear to fit the data distribution. To ensure<br /> that these discrepancies are not due to experimental artifacts, we recommend<br /> repeat the experiments performing additional replicates. Furthermore,<br /> considering the probable reversibility of 5-KETE conversion, alternative kinetic<br /> models that account for this factor should be explored.<br /> Minor Comments<br /> ? Lines 13-15: The authors state, "As the DHRS7 (but not DHRS3)<br /> knockdown effect was consistent with 5-HEDH activity, we tested whether<br /> DHRS7 also promoted 5-KETE reduction. This was the case." However,<br /> Figure S1D shows a reduction in 5-HETE, not 5-KETE. More clarification<br /> is needed.<br /> ? Cell Line Justification: The authors discuss DHRS7 expression in<br /> various contexts but do not justify their choice of A549 cells. Since none<br /> of the cited references mention DHRS7 expression in this line, a<br /> description of the rationale for model choice is necessary.<br /> ? Figure 1E: We recommend a dose-time response curve for DOX<br /> treatment to monitor DHRS7 expression levels. This would determine if<br /> DHRS7 expression remains at physiological levels or becomes<br /> supraphysiological, thereby ensuring that subsequent treatments also<br /> occur under physiological conditions.<br /> ? Figure 1F: We recommend a more clear description that these are cells<br /> lacking the DHRS7 construct to enhance reader understanding.<br /> ? Figure 2B: H2O2 is not a direct intermediate in the 5-HETE/5-KETE<br /> pathway, though it may indirectly influence it by activating 5-LOX, altering<br /> redox balance (NADP+/NADPH), and contributing to ferroptosis. The<br /> statement "Lipid peroxidation stimulates 5-KETE production through<br /> DHRS7" would be more robust if 5-LOX activity was assessed. We<br /> suggest a validation experiment: Treat DOX-induced DHRS7-expressing<br /> cells with H2O2 and measure markers of lipid peroxidation, such as<br /> malondialdehyde (MDA), isoprostanes, or 4-hydroxy-2-nonenal (4-HNE).<br /> This would confirm lipid peroxidation’s role in 5-KETE production.<br /> ? Figure 3D: Overexpression methodology in HEK cells is unclear. The<br /> knockout was achieved using CRISPR/Cas9, not shRNA. More<br /> clarification is needed on whether overexpression was introduced via a<br /> separate construct post-knockout, whether a CRISPR activation<br /> (CRISPRa) or DOX-inducible system was used, or if overexpression was<br /> performed in a different cell line.<br /> ? Figure 4A: The heatmap visualization of metabolite concentrations was<br /> clear, but cluster analysis would provide more information related to the<br /> significance of observed alterations.
On 2021-02-16 17:37:21, user Tyler Benster wrote:
Thought provoking paper, thanks for posting!
analysis of cell ROI outputs appears to be on CNMF-E output, which includes opinionated and parameter-dependent reshaping of calcium transients, while the neuropil ROI is averaging the raw data. To what extent is the difference in correlation due to CNMF-E preprocessing vs averaging raw data? This could be tested by comparing to average raw trace of cell ROI (eg using same, close-to-raw pipeline for both cell ROI and neuropil ROI)
in ephys data, do LFPs better correlate with fiber photometry? This would seem to be predicted by the calcium neuropil data and may add to strength of argument
On 2021-06-28 14:28:04, user Laurent Seroude wrote:
Where one can find the Videos for this article?
On 2022-12-20 20:09:18, user Tim Breitenbach wrote:
I think the manuscript could benefit from providing at least an outlook how the strengths of existing methods for CRE selection like https://academic.oup.com/bi... and the presented one can be combined for a more powerful pipeline.
On 2023-06-26 08:44:48, user Jonathan wrote:
Hi,<br /> Thank you for this very interesting paper.<br /> The current manuscript refers to supplementary figures but they don't seem to have been uploaded. Could you please share them ?<br /> Best regards<br /> Jonathan
On 2021-05-10 14:25:20, user cloois wrote:
This paper is now available here : https://www.cell.com/cell-r...
On 2020-03-20 21:37:58, user Steven Salzberg wrote:
It's rather misleading to emphasize, as the abstract does, that they found "almost 2,000 contaminant sequences" without any context. In our African pan-genome sequences, they claim that 1,475 are contaminants, total length 3.07 Mb, which is only slightly over 1% of our pan-genome collection of 296 Mb. So if all of their identified contigs are indeed correct, it's still not a huge problem, although worth cleaning up. It's also misleading to report-in the abstract again-that the contaminans "harbour genes totalling 4,720 predicted proteins"; our paper didn't report any novel proteins (or genes) in these sequences. This report makes it sound like we did.
On 2021-02-05 05:14:42, user AKANKSHA SINGH wrote:
Manuscript is currently 'under review' at Experimental Biology and Medicine.
On 2023-02-19 20:15:19, user Justin wrote:
This is neat. No method on packaging, IVT, cloning of Sindbis? Which strain was used? Sindbis itself is highly mutagenic and IVT + packaging will change the barcodes quite a bit. Was the barcode identity needed a priori of sequencing or is random fine?
Diane Griffin has identified several less neuronally toxic Sindbis variants you may find useful for this application.
On 2019-10-22 23:31:39, user Maria Magdalena Klicznik wrote:
Please note that this pre-print was combined in the revision process of another manuscript, and is now part of the pre-print:
A novel humanized mouse model to study the function of human cutaneous memory T cells in vivo in human skin
On 2016-11-01 03:49:36, user Anders Goncalves da Silva wrote:
Sounds very interesting. But, it is a pet peeve of mine when software papers do not include a link to the code or page directly in the abstract.
Ok, I retract the comment. It is there once you open the PDF.
And kudos on supplying a Docker image. You should consider submitting to JOSS (http://joss.theoj.org/) "http://joss.theoj.org/)")
On 2024-09-04 21:15:50, user Alex Grossman wrote:
Hello, as a heads up you call Xenorhabdus Gram-positive in your abstract. It appears to be correctly listed as Gram-negative elsewhere in the text.
On 2017-07-11 14:40:18, user Mathew Beale wrote:
This looks very nice - can't wait to try it out. I wonder about the use cases though for intra-host deep sequencing - you build phylogenies based on sliding windows of reads (using 454 or MinION obviously gives you longer reads), but would this approach work with Illumina data from pathogens that are less SNP dense (i.e. not an RNA/retro-virus)? Would there be enough signal to infer a phylogeny within a ~200bp window for a large DNA virus (e.g. CMV) or a bacterial genome?
On 2018-06-29 19:15:43, user Ricardo Scrosati wrote:
This preprint has been published in a peer-reviewed journal as:<br /> Scrosati, R.A. & J.A. Ellrich (2018) Benthic-pelagic coupling and bottom-up forcing in rocky intertidal communities along the Atlantic Canadian coast. Ecosphere 9 (5): article e02229. doi: 10.1002/ecs2.2229
On 2020-04-07 16:39:29, user Rasmus Møller wrote:
How much active replication do you get in your primary monocytes? What titers does SARS-CoV-2 reach in those cells?
On 2022-01-14 16:09:05, user Iratxe Puebla wrote:
The manuscript reports the result of a survey of authors of preprints posted to bioRxiv in the period November 2013 to December 2018. The survey asked respondents about their motivations for posting preprints -or not- for the papers they published in scientific journals the previous five years. The main additions compared to earlier surveys on the topic relate to the fact that the survey asked for answers according to whether the respondent was a corresponding author or a co-author on the paper(s), and that for the group of respondents who had posted preprints for some papers but not others, the survey asked about any differences between the papers (e.g. on self-reported novelty or quality of the work), to establish whether a selection bias by authors may take place when making decisions on what papers to post as preprints.
The results around motivations for posting preprints correlate with the results of earlier surveys: main motivations are quick dissemination of research and increasing awareness of the research. The respondents also reported an expectation that posting the preprint would bring a benefit in terms of online dissemination of the work e.g. via social media.
The survey responses according to whether the author acted as corresponding author or not are interesting as they suggest that preprinting decisions are mostly driven by researcher choice: a higher proportion of respondents posted preprints when they acted as corresponding author, compared to a lower proportion when they were a co-author, as this involved less autonomy in decision making.
The preprint landscape in the life sciences has changed hugely in the last two years. The survey was carried out in early 2020 for authors who had published a preprint in the 2013-2018 period, and it is likely that many researchers previously not familiar with preprints are now at least aware of this publication model. It would thus not be surprising if trends have evolved since the survey was done, a follow-up survey (as a follow-up study) would be informative and allow for an interesting exploration of trends around motivations and decision making for preprint use in biological sciences.
I am not sure I agree with the interpretation that the responses displayed in Figure 8 are at odds with each other. Even if an author considers the papers with and without preprint of similar novelty/quality, I do not think it is surprising for them to have an expectation that the preprint may boost attention/citations, for several reasons: prior research has noted an association between having a preprint and levels of attention/citations, the fact that the preprint disseminates the work earlier and thus may start accruing citations earlier, there is a preprint community on Twitter so the author may expect wider dissemination via those community channels.
Survey design - It may be interesting to learn more about how the survey was developed? Were the questions chosen according to the authors’ knowledge or were question options from earlier surveys considered? Was the questionnaire pilot tested prior to deploying the survey, and if so, were any changes made to the wording of specific questions?
Analysis of free-text comments - Is there some context/justification for having a single coder for the comments? Was the option of additional coders considered to check for any differences between coders/reduce potential bias?
I realize the sample size for certain disciplines may be too small but I wondered about some discipline-level analysis for the responses. Different disciplines are at different stages of use and experimentation with preprints so there may be discipline-level differences on whether authors are making choices based on the perceived quality or novelty of their paper. The qualitative comments note that some authors choose to preprint as protection from scooping while others choose not to preprint due to fear of being scooped, I wondered if views here may be driven by discipline-level variation in use of preprints, i.e. if in my discipline preprinting is common, I may be more likely to preprint as a scooping-protection approach than the opposite. This goes beyond the scope of this paper, but may be a follow-up exploration.
There is a thorough discussion of the limitations of the survey, a few additional items for consideration:<br /> - This is a survey based on self-reported responses, it may be worth noting that there is no stipulated benchmark for quality or novelty, and thus this may introduce nuance or subjectivity in how the question around novelty or quality is interpreted.<br /> - The survey was run in March-April 2020, when there were lockdowns in place in different countries, may lockdown measures have affected response rates by certain groups (certain locations, gender) particularly impacted by lockdowns?<br /> - It is noted that the survey is focused on a single preprint server, there are different preprint servers for biological sciences, it may also be relevant in the future to explore comparisons across servers for biology. Even within biological sciences there may be differences between authors who post to preprint servers directly, and those who post preprints via deposition offered by publishers at the stage of journal submission.
On 2022-03-22 23:17:06, user Brent wrote:
This method section conveys about using BLAST nucleotides in order to identify species of bacteria on the ISS, they mention using Metagenomics to read the 100-bp. Another point that interested me, was that they didn’t identify the variable region they’re targeting in the experiment. There was also no mention of the standard filtering of the sequence, what did the team use in this experiment? There was also no variance of the genome size mentioned in the article. The sample retrieving method is mentioned, they extracted the bacterial samples from the vacuum filters and dust collected from the ISS, as well from the astronaut’s skin to characterize. However, what steps were taken to ensure no contamination was introduced within the samples retrieved? The article doesn’t mention how the bacterial samples were kept in sterile environments before shotgun-sequencing. They do mention the method used to quantify the Antibiotic resistance bacterial genes, subculturing the samples retrieved from the space station then comparing them with the same species of bacteria pre- and post-launch for uniqueness. I would suggest adding how the team collected the samples before sequencing, to give the reader insight on what steps were taken to isolate the bacterial genes. If they’re mentioned in another article, I would provide a link to the article within the methods section. I really enjoyed this paper, it's fascinating to learn about how microorganisms originating from earth can survive beyond the stars.