On 2025-09-17 12:32:29, user manez wrote:

Information for readers: this preprint has been published and the link will be available soon.

On 2021-07-16 07:49:59, user Gerhard WINGENDER wrote:

This manuscript was used in class at IBG to practice peer-reviewing. This was the final version:

In this manuscript Classon et al. show that following the intestinal infection with the helminth H.polygyrus (Hp), Hp-specific CD4+ T cells enter the skin and become tissue-resident in the skin. This is an interesting finding. Furthermore, the authors show that the Hp-infected mice have a weaker recall-responses to intra-dermal injection of M. tuberculosis lysate (WCL). However, this point remains observational as no mechanistic explanation is offered. The authors suggest in their discussion that skin-resident Hp-specific Th2 cells would dampen the IFN? production in response to mycobacterial products locally in the skin, but no data to that effect are shown. Would Hp-specific CD4+ T cells produce IL-4/-13 after WCL, or at least, do more total skin CD4+ T cells do so? How do the authors exclude differences in WCL-induce priming in the skin-draining LNs (rather than local effects in the skin as proposed)? Given that it is known that intestinal helminth infection can dampen immune response at other sites of the body, the novel knowledge gained here appears limited. Moreover, several aspects require attention.

M&M section:<br /> - The B6 mice were 4-5 weeks of age at the start of the experiment. Can the authors show experimental results that similar data could be obtained with adult mice?<br /> - It is not clear if the authors used Fc-block for their flow cytometric staining.<br /> - The description of the BM-DCs+WCL cultures is not entirely clear and the experimental procedure is not explained in the main text or figure legends (only M&M), although that would be helpful. The BM-DCs were incubated with WCL over-night, but then the WCL was not washed off, but rather the leukocytes were added, is this correct? In that case a direct impact of WLC on the single cell suspensions from the skin cannot be excluded. What is the reasoning for this approach? This<br /> potential confounding factor needs at least be discussed.

• Figure 1 <br /> - Three of the dot-plots in fig.1b (and in other figures) do not show any dots. The authors should use density plots with outliers for all flow cytometry dot-plot data throughout the manuscript (including the supplements).<br /> - To the legend: (i) “Representative FACS plots illustrating the gating strategy” - the link to the supplement is missing; (ii) “BMDCs expressing WCL overnight“ - the DCs to not express WCL, they were incubated<br /> with it o/n, right?; <br /> - Why is the y-axis as CD4+ cells when the cells were gated for T cells? Writing ‘CD4+ T cells’ appears more appropriate. <br /> - The figure SF1b suggests that most of the cells purified from the ear are dead. Is this also the case for the CD45+ cells? Is the frequency of dead CD45+ skin cells comparable between the groups? What is the author’s argument that this would not skew the results?

• Figure 2 <br /> - The authors treated the mice twice for one week with DSS, which did not lead to changes in the numbers of CD4+ T cells in the skin. However, 2 weeks after the Hp infection there was no such difference either. Therefore, the conclusion that bacterial translocation does not lead to increased CD4+ T cells frequency in the skin cannot be made based on this DSS-timing alone. Furthermore, the levels of translocation (with Hp or DSS) would need to be comparable to make such conclusions even with identical timing. However, the sCD14-levels were not measured following the DSS treatment. In either case, the DSS-experiment is in its current form not sufficient to exclude the possibility that bacterial translocation is not involved in the skin homing. However, to this reviewer, excluding this option is a minor point that does not appear essential.<br /> - It is not clear to this reviewer why the cohousing of the dewormed mice with the chronically infected mice would not lead to reinfection.<br /> - As the experiment in fig.2j has only been performed once, the results are preliminary and should be moved to the supplements and the text should reflect the preliminary nature of the data. Furthermore, the relative percentage of CD4+ T cells should be given, additional to the numbers.<br /> - The figure legend lists figures n-p (for the replicates), which are not shown. Furthermore, the abbreviation ‘Dw’ is not explained. Please adjust.

• Figure 4 <br /> - For figures 4h+i the authors claim that the difference “was more pronounced in H. polygyrus-infected mice”. It is not clear how the authors arrive at this conclusion. Obviously, the difference in the p-values that compare ST2-pos and -neg cells is meaningless in this regard. One would need to perform an Anova analysis of the control groups (ST2-pos/-neg) vs. the Hp-infected groups. It appears, however,<br /> that this was not done. Please do so and include the values or adjust the language.<br /> - Furthermore, even if the Anova indicates a difference between controls and infected mice, the claim that “TH2 cells … especially targeted to the skin in worm-infected mice” cannot be kept, as the authors did not check other organs to see if this migration is specific to the skin.<br /> - Finally; the statement “ST2+ cells expressed higher levels of CCR4 and CCR10 … compared to ST2-cells” does only hold true for CCR4, not CCR10. The authors should be more careful not to claim things in the text that are not supported by their data.<br /> - The IL-4 cytokine increase in the ICCS appears questionable. A second method to identify IL-4 production should be included.

• Figure 5 <br /> - The authors wanted to show “the reactivity of skin-localized CD4+ T cells … and … analysed cytokine mRNA expression”. Obviously, the total-tissue mRNA response cannot be linked to a particular cell and does not show actual cytokines. This requires protein data on a single cell level. This applies similarly to suppl.fig.5 for which the authors claim in the text to have tested ‘cytokines’ when they actually only checked the mRNA.<br /> - The statement “CD4+ cells that accumulate in the skin of infected mice are H. polygyrus-specific” is not supported by the provided data as the authors did not clarify if indeed the majority of the accumulating skin CD4+ T cells are Hp-antigen-specific. All that can be said, is that the skin CD4+ T cells contained some antigen-specific cells. Either their relative frequency needs to be established or the claim in the text needs to be removed.<br /> - Similar, the data with N. brasiliensis cannot indicated that the skin CD4+ T cells were Hp-specific. All that this result indicate is that the resident CD4+ T cells are not cross-reactive against N. brasiliensis. The text should be adjusted.

On 2021-08-04 19:35:28, user Jing wrote:

A revised version of this story is now published at -

https://stm.sciencemag.org/...

On 2020-05-03 01:17:28, user Gianguido Cianci wrote:

Could you share a reference for this please? Thanks!

On 2020-06-13 03:31:18, user Ray wrote:

Introduce both mutations into the virus and test if one can outcompete the other in cell culture. If yes repeat with model animals. Only then you can say that. Everything else is jumping on the COVID-19 train to get an easy publication. But I guess that's the only way to get money for your lab atm. Science has become a commercial product that is being milked by mass media and journals. The more scary the better it sells. This doesn't help. This just makes things worse.

On 2020-03-05 04:06:51, user Adam Taranto wrote:

This paper was a great read and will hopefully spark others in the field to look at TE dynamics in their own pathogen genome collections! It was exciting to see real data backing up the usually speculative relationships between TE dynamics and population level processes in fungi. Fantastic work by all involved - thanks for sharing this preprint.

There were a few points which were unclear to me. Notes included below.

163: Did you use the handful of existing TEs from RepBase or call everything from scratch with RepeatModeler?

215-216: Here you say that a TE was considered absent if "no evidence for spliced junction reads" was found, but on lines 207-208 you say "spliced reads are indicative of ... absence of the TE in a particular isolate".

246: I don't think consensi as a plural of consensus exists in english (it does in Italian though!). I might be wrong.

312: Does "singleton TE" mean that there is only one instance of that TE family across all isolates? or, that only one isolate has that particular TE at that particular locus?

Fig 1. D. ii) For the leftmost example (Splice junction reads in query isolate + no TE annotation in reference) the fig indicates that this is called as an TE absence in the query isolate. How did you rule out these loci as unannotated repeats in the reference?

351: Fig 2. E. caption. Should this be "mean" copy numbers?

On 2018-06-10 04:05:55, user Jahangheer Shaik wrote:

How does this deal with mixed infections? What if assemblies are not available for all species of interest? What if genomes are not syntenic? Intra-strain hybrids?

On 2022-03-07 15:26:54, user Rafael Yuste wrote:

We have some technical and theoretical concerns about the experiments. Hopefully our comments will help the authors to improve their manuscript and clarify the issue for the readers. <br /> There are some methodological issues that could be important in the interpretation of their results. Because the authors used wide-field imaging with one-photon excitation, which results in PSFs that are likely several times larger than the size of a spine (after tissue scattering), it is likely that the spine signals were contaminated by dendritic ones and by out of focus contributions. Also, since the experiments were performed in brain slices, and near the cut surface of the tissue, the studied spines may not have been in a physiological state. Moreover, the repeated patching of the neurons could lead to cellular damage, and the long periods of whole cell dialysis and high light exposure add serious risk of incident photo damage, affecting neuron’s biophysical properties. Indeed, dendritic beading, a classic sign of tissue damage already described by Cajal, is evident in most of their images. Also, although glutamate uncaging has been broadly validated by many groups, including our own, it is still not equivalent to the response of spines when synaptically activated in a physiological state, which could involve different set of receptors, conductances, inhibitory signals, etc.. <br /> With respect to the criticisms they raise about our recently published work (Cornejo et al, 2021), aside from major experimental differences in species (rat vs. mouse) and age (developing vs. adult animals) and without dwelling in the details of the analysis, we would simply encourage the authors to view our movies of voltage imaging of dendrites in vivo. In these movies, included as supplementary material in our recent paper (https://www.science.org/sto... "https://www.science.org/stoken/author-tokens/ST-255/full)"), one can directly see with one’s own eyes how individual spines are often activated in the absence of any significant depolarization in the dendrites. Also, while the authors suggest that the voltage compartmentalization could be an artifact of the slow sampling, in fact, the known frequency-depending filtering of electrical signals would predict the opposite. Finally, we would note that the authors own data (Fig. 1, for example) confirms the large amplitude of spine potentials made in our recent paper and in the intracellular recordings of Jayant et al. 2016, which they criticize. <br /> It is important to mention that many previous experimental or calculated explorations of spine voltage compartmentalization (Harnett et al., 2012; Tonnesen et al., 2014; Jayant at al., 2017; Kwon et al., 2017; Cornejo et al., 2022), have revealed a significant heterogeneity in spine responses. Indeed, even disregarding the technical issues mentioned above, inspections of the authors’ own data, for example Figure 1D (or in Popovic at al., 2015), demonstrates that a significant number of spines are compartmentalizing voltage to a similar extent than what we have measured in vivo. The authors ignore these data points and the heterogeneity that their results reveal. Given this, and the methodological problems of their approach, we would encourage the authors to soften their tone in their one-sided conclusions and do justice to their own data. <br /> We are looking forward to constructively conciliate different experiments and interpretations in order to better understand together spine physiology and biophysics.

On 2025-04-29 21:33:20, user Jalees Rehman wrote:

Dear Biorxiv,

we have published this paper here in Nature Communications.

https://www.nature.com/articles/s41467-025-57047-7

Best wishes,<br /> Jalees Rehman

On 2018-02-26 16:36:46, user Joseph Colorado wrote:

Wow ... 11 conferences and that is all they need to have a conclusion ... guess when I learned about research methods I was taught poorly in believing more is better when you want good data and less is better when you have an agenda.

On 2016-07-22 03:25:08, user Jong Wha Joo wrote:

Joint Fine Mapping of GWAS and eQTL Detects Target Gene and Relevant Tissue.

On 2018-05-01 19:51:12, user nanocyde wrote:

I wonder if we can tie this to the A0 haplogroup in Cameroon

On 2020-01-05 08:53:18, user sunburnt wrote:

This is great news.

Am I right in observing that it took a while to go from the original Yaminaka research from what.. the mid 2000s to now.. over 10 years later & we are just now trying to in vivo epigenetic resets?

What was the hold up? Was there a general assumption that all in-vivo resetting would cause teratomas?

Also, now that Lu, & Sinclair has shown it may be possible, can we now expect a global tidal wave of research into this area?

On 2021-07-07 15:33:36, user Antônio Medeiros wrote:

Now published in Science: https://doi.org/10.1126/sci...

On 2017-07-19 19:21:33, user AdamMarblestone wrote:

-"Neuroscience inspired artificial intelligence" http://www.cell.com/neuron/...

On 2017-04-10 01:52:09, user AdamMarblestone wrote:

-"Superficial layers of the medial entorhinal cortex replay independently of the hippocampus" http://science.sciencemag.o...

On 2017-10-21 19:00:44, user AdamMarblestone wrote:

-"Top-Down Feedback Controls Spatial Summation And Response Gain In Primate Visual Cortex" https://www.biorxiv.org/con...

On 2020-07-30 05:07:24, user ASM wrote:

Summary of this study:<br /> 1. We have sequenced 137 and analyzed 184 whole-genomes sequences of SARS-CoV-2 strains from different divisions of Bangladesh.<br /> 2. A total of 634 mutation sites across the SARS-CoV-2 genome and 274 non-synonymous amino acid substitutions were detected.<br /> 3. The mutation rate estimated to be 23.715 nucleotide substitutions per year.<br /> 4. Nine unique variants based on non-anonymous amino acid substitutions in spike protein were detected relative to the global SARS-CoV-2 strains.

On 2014-03-20 17:18:02, user Casey Brown wrote:

Great paper, thanks for posting. Given the controversy over the frequency of buffering vs. reinforcing effects of transcription and translation a little more discussion on the sources of this discrepancy. There are a bunch of variables here: MA vs OLS, ratios vs. denominators, mass spec vs. ribosome profiling, phyogenetic distance, etc.

1. Major axis estimation. What is the effect of when error rates are larger for one variable? A supplemental figure, similar to S4, comparing major axis estimation with OLS regression would be informative (perhaps with differing levels of measurement error?).
2. On the parsimonious interpretation of a single variant affecting translation and steady state RNA. Is there evidence for shared (or distinct) causal variants from eQTL and pQTL studies? Would a conditional regression, Mendelian randomization, or similar approach be informative? Similarly, would RNA and foot printing allelic imbalance studies performed in multiple individuals be informative?
3. On the specific mechanism of translational efficiency leading to increased mRNA stability. Doesn’t the relative paucity of variants associated with mRNA decay rates (e.g., Pai 2012, PMID 23071454) suggest that eQTLs are not primarily driven by variation in RNA stability? Could the application of GROseq to the same samples as those studied here address this issue directly?
4. Validation. It sure would be cool if someone could identify coding variants predicted to be causally relevant to TE and steady state RNA and validate their function in reporter assays…
5. Great figures. Figure 4C is a really nice result.

-Casey

On 2015-03-17 12:48:40, user David Lovell wrote:

Published in PLoS Computational Biology <br /> Published: March 16, 2015<br /> DOI: 10.1371/journal.pcbi.1004075

On 2017-10-28 16:46:48, user Lionel Christiaen wrote:

Student #2<br /> Justin Crocker and his team examine how brief protein-DNA binding drive transcriptional regulation. Prior studies reveal low affinity binding is critical for transcription factors to interact with their targets, and increasing the strength of the DNA- protein binding drives gene expression dysregulation. To show how low-affinity DNA binding regulates transcription, the group utilize the shavenbaby (svb) enhancer locus, the Hox gene Ultraabithorax (Ubx) low- affinity binding, and the Ubx cofactor Homothorax (Hth). <br /> They first examine the Ubx distribution across the Drosophila embryos with immunofluorescence staining and super resolution confocal imaging. To better visualize the protein distribution, the team expanded the embryos four-fold. The expansion procedure could have distorted the distribution of clusters across the cells. To validate Ubx interaction with DNA, the Ubx transgene is mutated to disrupt DNA binding, which was an important control for the continuation of the story. They observe the spatial heterogeneity of Ubx clusters is dependent on DNA binding. Additionally, Ubx clusters were localized near active svb transcription sites. They creatively containing intronic mRNA and Ubx protein, they’re able to visualize the distribution of nascent transcripts as they relate to Ubx clustering. The article was concisely executed to tell a compelling story.

On 2018-12-18 00:49:46, user Peter Rogan wrote:

This has been published in F1000Research: https://f1000research.com/a...

On 2019-04-11 12:09:55, user Yiheng Hu wrote:

Nice paper! I am just curious that did you also do the 16S copy number adjustments?

On 2018-08-13 20:08:36, user Jeff Barrett wrote:

I was asked to review this manuscript for biOverlay, and I am posting my review here as well.

There has been a lot of attention to the role of de novo coding mutations in autism and other neurodevelopmental disorders, and a natural next question is whether it's possible to identify non-coding mutations that confer disease risk. One of the major challenges to this is how to understand the "regulatory code" and distinguish "synonymous" from "non-synonymous" mutations outside of genes. This paper applies a deep learning (as the authors note six times) algorithm, DeepSEA, to the this problem.

The major result is that DeepSEA successfully predicts a systematic difference between de novo mutations in individuals with autism and their unaffected siblings, which is an impressive achievement. One of my major suggestions for this paper is to provide more information about the input data (de novo mutations called from whole genome sequence), as this is notoriously tricky. I'm somewhat less concerned because the dataset provides a natural internal control between affected individuals and their siblings, but it would still be good to see more detail. For example:

• How many de novos were called per proband and per sib? This is a basic QC metric, but I couldn't find it.
• More info would be helpful: "Further filtering was then applied to remove variants that were called in more than one SSC families."
• The paper refers to 127,140 de novo SNVs. I assume these are only non-coding (and coding mutations are stripped out), but it's not totally clear.

DeepSEA predicts biochemical disruption, and these predictions were further trained on curated HGMD disease mutations and variants observed in 1000 Genomes. What happens if the predictions from DeepSEA are used directly in the autism data? The noncoding disease mutations in HGMD might be a problematic training set, as there are not that many known, and some may not be actually pathogenic, even in the curated set.

Further analyses (e.g. of tissue specific expression and enriched biological functions) provide additional support for the main findings.

For a follow-up paper, someone (the authors or another interested party) should run this analysis on the Deciphering Developmental Disorders dataset (which I was involved in), which should have good power to find specific causal mutations: https://www.nature.com/arti...

Minor comments:<br /> The authors suggest that 30% of simplex ASD probands have a de novo coding cause (and their point is that this is not very much), but I think that's high. I'm not sure where the number comes from, as ref 3 finds diagnostic mutations for 11%, and their Sup Note says 2.4%.

The comparison between versions of DeepSEA is described only fleetingly: "leading to significantly improved performance, p=6.7x10-123, Wilcoxon rank-sum test". More generally, one needs to read that paper to really understand what's going on. This is often the case, but a bit more of a summary of the method would help.

On page 18 there's a repeated word in "40 SSC families families".

On 2024-03-27 13:05:36, user Kai-jie Liu wrote:

This article has been published in nature chemical biology.<br /> Ziegler, M.J., Yserentant, K., Dunsing, V. et al. Mandipropamid as a chemical inducer of proximity for in vivo applications. Nat Chem Biol 18, 64–69 (2022). https://doi.org/10.1038/s41...

On 2025-02-03 17:44:55, user disqus_2m2wL3bGCz wrote:

I cannot find the methods part in the uploaded preprint ??????

On 2021-06-02 06:26:47, user Claudio Tennie wrote:

The following is PART 3 (of 3) of our response to Mielke (we had to split up our reply, due to character limitations here on disqus)

The claim that “the simulation rules used are undistinguishable from copying”.

Answer: This is an opinion that was also voiced by another participant in the original twitter debate and so we shall explain in more detail. In that twitter debate we already mentioned that they can be clearly distinguished, but that the difference underlying them is often not acknowledged or implemented. The resulting confusion is based on the tendency in other cultural modelling work (indeed, in most cultural modelling work) to blackbox and exclude the details of form copying. In our model, as all behaviours are latently present in the individuals (i.e. can individually be reinnovated) there is no need to copy new behaviours (and with it, no need to introduce new behaviours). This is because the simulation rules never implement the necessary copying. This exclusion of form copying is by design - in our model. The fact that the output of this our model of non-form-copying is indistinguishable from real life ape culture - or other cultures identified by the method of exclusion - is exactly the point that we are making.

Form copying is best defined as the causal copying of the actual details of demonstrated forms - i.e. their internal and/or linear structure to each other (Tennie et al. 2020 Bio & Phil). In other words, the know-how, must be causally transmitted. It is easy to see that the way in which most cultural models are implemented do not in fact model form copying in this way at all. In such a model, typically an agent might, for example, be faced with the problem of “copying” the production of a kayak. But the way that this is modelled then is usually by assigning a certain likelihood that a kayak is later produced by the observer. But then, none of the actual details of the kayaks are causally copied here - the kayak is either developed by this agent after observation, or it is not. But here is the catch. The kayak design cannot evolve using this type of model. But in real life the kayak design is even bound to (!) evolve culturally - via copying error alone (as this type of error is unavoidable). These models are often modelling a type of match that can in principle be solved either by copying or by socially mediated reinnovation - that is, by mere triggering. Another way of making clear the lack of actual form copying in these models is this: such models could not recreate the outcome even of the “telephone game” as played by children. This is because the initially whispered message (e.g. “the fox jumps over the fence”) cannot culturally evolve alongside the whispering chains in such models. The “funniest” outcome here would merely be the failure to pass on this message (after which there would be no more message at all transmitted further down the line). Therefore, the critique raised here by Mielke and others and in the original online twitter debate is not relevant. It is not, and cannot be, our responsibility that the field does not usually model real life form copying.

It would seem that the lack of form copying is a potential shortcoming of this field of modelling. When the explanatory target involves actual form copying in one way or another then such a model will no longer work, will no longer be useful (however, note that the explanatory target of many of these models are nevertheless unaffected by these particulars). Thus, for example, any good model of the telephone game must truly implement form copying (the details of the sentence must be attempted to be copied).

In our model, instead, we intentionally chose this very model design - i.e. one that is lacking form copying - and we choose it precisely because (!) it excludes form copying. We fully required the implementation of a mechanism that absolutely cannot copy form to test if form copying is and must be necessary before wild ape cultural patterns can be reproduced (or, more generally, before general positive outcomes of the method of exclusion can be reproduced). Ours is therefore a null-model. Contra Mielke’s claims, our socially mediated reinnovation is therefore not form copying - it can be clearly distinguished from form copying, by not transmitting the necessary details. Our model would not be able to produce real life outcomes of children's telephone games even. But again, this is intentional - it is so by design in our model. Our guided reinnovation of form A after social contact with form A is socially mediated reinnovation - it is a social triggering of this form in another. We know from experience that this implementation is unintuitive to us humans, precisely because humans base nearly everything they do instead on form copying. Were this not the case, and were human behavioural forms more often merely triggered, we would have a much easier time publishing our papers. Unfortunately for us, humans rarely show such triggering, and when we do, we do so in ways that do not closely match the types of learning underlying ape cultures (who are triggered in this way; see above). Nevertheless, it is still at least illustrative to consider such a case: a yawn merely triggering a yawn in another human does not transmit the yawn’s form (even blind-born people yawn). Again, this is being proof of principle, that not all culture needs form copying. Details in the ape case differ to yawning - but the outcome (triggering, not copying) is the same.

Needless to say, this difference (form copying yes or no) matters especially in the long run. With mere socially mediated reinnovation, a system is essentially restricted to the kinds of forms that it can self-produce (i.e. it is restricted to its zone of latent solutions; Tennie et al. 2009). Instead, humans are not restricted in this way, due to our reliance on actual form-copying. Here, error-copying alone will ensure, over time, and in a path-dependent way (!) that more and more forms are not only being produced, but also copied and maintained. This has two very strong consequences (e.g., Tennie et. al. 2020 Bio & Phil; Motes-Rodrigo & Tennie 2021). 1. This will produce forms that no individual could reinnovate anymore (as Richerson & Boyd have originally pointed out; or what we call copying-dependent forms; Reindl et al., 2018) 2. This will create a large number of these types of forms. Indeed, both effects can clearly be seen in humans - humans show billions (!) of copying-dependent forms by now (Motes-Rodrigo & Tennie 2021). This contrasts with the few thousands shown by the other apes combined, of which only zero to three show noteworthy indirect evidence for being copying-dependent (Motes-Rodrigo & Tennie 2021). Overall, ape behaviour is currently best explained instead via the ZLS account - in at least most cases, if not all - and our oranzee model is another piece of the puzzle that shows this to be the best explanation.

In summary - across all three parts of our response - we thank Mielke for correcting our ‘specifics claim’ (see Part 1 of our response), which we have therefore removed from our manuscript - but we disagree on the other claims Mielke raised, for all the reasons given in our remaining response (Parts 2 and 3).

Claudio Tennie and Alberto Acerbi

We thank Elisa Bandini for helpful comments on an earlier draft of our response.

On 2024-01-17 12:14:46, user Lihua Song wrote:

This preprint paper is being misinterpreted on social media. I would like to state the following facts:

1. The GX_P2V virus has been published in Nature in 2020 (doi: 10.1038/s41586-020-2169-0). It is not a brand-new virus.

2. The GX_P2V(short_3UTR) mutant was published in Emerging Microbes & Infections in 2022 (doi: 10.1080/22221751.2022.2151383). This cell-adapted mutant is the actual isolate published in the Nature paper. So, the original GX_P2V virus was not isolated. Clearly the original GX_P2V virus in the pangolin sample has severe growth deficiency in Vero cells.

3. The GX_P2V virus is not a human pathogen, although, based on molecular and animal infection experiments, it can infect a broad spectrum of host species, like human, cat, pig, golden hamster, mouse, rat et al. There is no evidence of the original GX_P2V virus circulating in these animals, not even consider this GX_P2V(short-3UTR) mutant. Please refer to publications: EMBO J, doi: 10.15252/embj.2021109962 and J Virol, doi: 10.1128/jvi.01719-22.

4. The GX_P2V(short_3UTR) isolate is highly attenuated in in vitro and in vivo models. In Vero, BGM, and Calu-3 cell lines, the virus induced only mild cytopathic effects, notably failing to produce viral plaques even on the human lung cell line Calu-3. In golden hamster and BALB/c mouse models, the virus can infect the animals' respiratory tracts but did not result in any observable disease symptoms. The attenuated nature of GX_P2V(short_3UTR) was also validated in two distinct human ACE2-transgenic mouse models. Please refer to publications: Emerging Microbes & Infections, doi: 10.1080/22221751.2022.2151383 and J Virol, doi: 10.1128/jvi.01719-22.

The attenuation of GX_P2V(short_3UTR) was also hinted in the Nature paper on the GX_P2V(short_3UTR) isolate (doi: 10.1038/s41586-020-2169-0). In Extended Data Figure 1, after infecting Vero cells for five days, GX_P2V caused noticeable cytopathic effects, but which were limited to cell rounding and mild cytolysis, which starkly contrasted with the severe cytopathic effects reported in SARS-CoV-2.

1. The public has developed a high level of population immunity against GX_P2V due to SARS-CoV-2 immunizations and infections. Collectively, the biological safety risk posed by GX_P2V(short_3UTR) is extremely low. I don’t think there is any immediate risk of spillover into the human population. Please refer to publication: J Med Virol, doi: 10.1002/jmv.29031.

2. Based on previous reports on ACE2 humanized mouse models with SARS-CoV-1 and SARS-CoV-2, there is significant variability in the outcomes of infection in these models, a topic extensively documented in the literature. A single ACE2 humanized mouse model does not constitute a reliable paradigm for evaluating viral pathogenicity. While GX_P2V(short_3UTR) proved lethal in our mouse model, it's important to consider that it did not cause disease upon infecting two other distinct ACE2 humanized mouse strains. The findings reported in this paper do not alter the fundamental nature of GX_P2V(short_3UTR) as being highly attenuated.

3. Several other research groups have repeatedly reported the spillover risk of this virus based on its spike protein binding to human ACE2. Those reports have not caught much attention. In our study, using a unique lethal model, we inadvertently reinforced the perception that this virus has a strong tropism for human brains and causes 100% mortality. We need to revise this in the subsequent revision of the paper and provide additional clarification on the intrinsic attenuated nature of the virus.

4. The GX_P2V(short_3UTR) mutant is a promising live attenuated vaccine against pan-SARS-CoV-2. Partial results can be found in this preprint paper: https://www.researchsquare.....

On 2020-05-18 14:30:58, user OxImmuno Literature Initiative wrote:

https://www.immunology.ox.a...

On 2022-10-14 11:40:10, user Zach Hensel wrote:

Most of the C/C sequences discussed in this manuscript come from a single study (Lin et al 2021 DOI: 10.1016/j.chom.2021.01.015) that reports methods inconsistent with Washburne et al concluding that associated GISAID records represent complete, full-length sequences. For example, the very first sequence shown in Table 1 in Washburne et al, EPI_ISL_451351, corresponds to sample SC-PHCC1-030. Table S2 shows that this sample has only 89.4% coverage with at least 1 read and only 63.2% coverage with at least 10 reads. Yet, the associated GISAID record is full length with zero Ns. Clearly these are consensus Wuhan-Hu-1 genomes modified by detected variations, and this is confirmed in the manuscript by Lin et al that is cited by Washburne et al:

For Nanopore sequencing data, the ARTIC bioinformatics pipeline for COVID (https://artic.network/ncov-... "https://artic.network/ncov-2019)") was used to call single nucleotide changes, deletions and insertions relative to the reference sequence. The final consensus genomes were generated for each sample based on the variants called in each position.

This is not limited to Sichuan sequences, but also to Wuhan samples from the same study.

Furthermore, Table 1 in Washburne et al includes a sample that was, in fact, considered in Pekar et al. EPI_ISL_453783 is a second record for EPI_ISL_452363 (identical sample ID, patient age, sampling date, and sequence).

Multiple authors of this manuscript have promoted their claimed discovery of new intermediate genomes on social media for the past several weeks and have been repeatedly been informed of these and other errors in their claims and have yet to make any corrections.

Edit 17/October/2022 -- Authors Washburne and Massey have responded that they are aware of this comment.<br /> Washburne: "I stand by every word."<br /> Massey: "grist to the mill lol"

On 2016-11-09 02:31:27, user Isaac Sánchez-Juárez wrote:

I am an economist, but I like to read this class of papers.

On 2025-04-02 17:03:58, user Arval wrote:

This paper has now since been published. Link at: https://doi.org/10.1128/mbio.03428-23

On 2021-05-19 15:03:33, user Peter Uetz wrote:

A revision of this paper has now been published in the Journal of Biological Chemistry: https://pubmed.ncbi.nlm.nih...

On 2022-06-18 19:15:13, user Alex Cope wrote:

Published in Plos Genetics: https://doi.org/10.1371/jou...

On 2018-05-06 12:02:11, user Layman wrote:

What is this Hamilton zuk hypothesis?

On 2025-05-17 03:17:17, user UrNewStepDaddy wrote:

In this study, the authors refine an established FDA method (FDA C010.02) originally developed for extracting PFAS from food to enable analysis of smaller volumes of Dolphin milk than previously possible, demonstrating that Dolphin milk may be a major source of PFAS for nursing calves. The major success of this paper was the ability to quantify the concentration for 13 targeted PFAS species and additional untargeted species in dolphin milk over a 2-year nursing period for the characterization of the PFAS most likely to be transferred from mother to calf. The major weakness of this study is the presence of several unsupported claims which undermine the rigor of the manuscript and weakens the credibility of the interpretations made. Nevertheless, this study provides important groundwork for future research on the transfer of accumulated PFAS from parent to offspring and the effect of PFAS on the development of aquatic newborns. Although the environmental accumulation of PFAS is well established, further research is needed to elucidate the horizontal transfer of these forever chemicals.

Major Points<br /> 1. The manuscript states that dolphin milk was stored at the Smithsonian’s Mammal Milk Repository at -20C for the past 30 years, but provides no detail regarding the type of containers used or whether potential contamination from storage materials was assessed. Since PFAS are hard to avoid and known to leach from plastics, contamination from the storage material could significantly impact results, leading to the question: Were these samples stored in a plastic container that could have leeched PFAS into the milk? According to pictures from the Smithsonian website ( https://nationalzoo.si.edu/conservation/news/making-sense-animal-milks) "https://nationalzoo.si.edu/conservation/news/making-sense-animal-milks)") the dolphin milk seems to be stored in plastic containers, however, the milk was harvested 30 years ago before the widespread knowledge of PFAS contamination. Were any blanks, storage container controls, or background correction measures collected to account for the PFAS introduced during storage? This study reports these chemicals in nanograms so even minimal leaching from storage materials could have introduced measurable contamination.

1. The methods sections states that the fish fed to the dolphin, Slooper, at the Naval Command Control and Ocean Surveillance Center were not screened for persistent organic pollutants (POPs). This raises a critical concern on whether the PFAS detected in the milk were primarily pre-existing maternal PFAS levels or diet-induced? Is there a chance that a species of fish had a higher amount of POPs within them than the others? At the same time, was there a regular feeding schedule that regularly spaced out the type of food? If Slooper was fed a more common/affordable food that happened to be more abundant in POPs at the beginning of the milking period, it could explain why there were so any PFAS detected initially and then tapered down later when she was fed other fish lower in POPs. Hence, the potential for dietary exposure to skew the results should be addressed in the discussion.

Minor points<br /> 1. Citations are needed for the sentences listed below:

-Line 43: “Since scientists have recently suggested that humanity has surpassed the planetary boundary for PFAS, major uncertainties must be addressed.”

-Line 217: “Additionally, most studies have only performed targeted quantitative PFAS analyses and not looked for new and unknown PFAS.”

-Line 283: “Previous studies have demonstrated that the lactational burden of POPs decreases following birth.”

-Line 386: “Although research on neonatal PFAS exposure is expanding, many epidemiological studies examine only one compound, failing to capture the complexity of mixtures encountered in the environment.”

-Line 467: “Although previous studies have linked traditional legacy PFAS, PFOS and PFOA, to adverse outcomes in dolphins and other marine mammals, there remains virtually no data on the impact of these chemicals or their replacement compounds on growth and development of neonatal marine mammals, especially with dosages of this magnitude.”

None of these claims are backed up by any evidence, which only helps to erode the work done within this study.

1. Some scattered typos are listed below:<br /> -In line 110, the title of the section has the method name wrong. It is correctly stated in the section as FDA C10.02.<br /> -In line 201, Administration does not need “ ’s ”.<br /> -In line 313, there is a red underline in the space in “illustrated that”.

2. Weekly tolerable intake of PFAS from the European Food Safety Authority and Food Standards Australia New Zealand is specifically stated twice within this paper (lines 22 and 368), however, it is only revealed during the 2nd mention that this is the weekly tolerable intake of PFAS for humans. From the source it could be surmised that the data was for humans, but having those numbers used for dolphins implies an equivalence between humans and dolphins that is not properly justified or supported with data (line 462). If human values are used for reference purposes, this should be clearly labeled or explicitly stated.

3. The wording in the methods section about sample collection and handling is unclear. In the sentence starting on line 90, does “During this time” refer to during the process of being milked or during the 603-day period in which Slooper was milked or during her life at the Naval station?

4. This manuscript would benefit from references to recent studies on PFAS amounts in dolphin carcasses: Sciancalepore G et al. (2021) and Foord CS et al. (2024) to name a couple. From this paper alone, PFAS do not seem like a huge problem, but put into the context of the papers I listed, it paints a more concerning picture.

On 2021-08-31 14:27:55, user Greg Keele wrote:

The final peer-reviewed paper is now available from Cell Genomics.

https://www.cell.com/cell-g...

On 2017-09-21 23:45:21, user L Kushner wrote:

Any correlation or link between de novo variants at probands and the types of damage observed in the recent nature autism paper by Powell? Amazing what a contributing factor all of these are!

On 2017-12-19 23:04:26, user chloe goose wrote:

This is fascinating. Check it out. Clinically important sex differences in GBM biology revealed by analysis imaging, transcriptome and survival data https://t.co/z7PmAHDVr2

On 2021-10-25 18:16:45, user Peter Rogan wrote:

This article is in press in the International Journal of Radiation Biology. DOI: 10.1080/09553002.2021.1998709

On 2021-04-20 12:55:09, user Nelii cheps kips wrote:

Our recent work on bacterial attachment in high salt environment #brunlab #Caulobacterales #holdfast #polysaccharides

On 2018-05-16 12:54:35, user Michael Monaghan wrote:

When searching for primer and fragment-length information (I could not find either) I notice that (line 128) Sherwood and Presting (2007) is not in the References.

On 2023-11-08 20:29:54, user P. Bryant Chase wrote:

Molecular basis for the "Abbott effect"? Bud Abbott was thrilled to know it was still being investigated in the 1980's, and would surely be thrilled to see this work if he was still living.<br /> Abbott BC & Aubert XM. (1952). The force exerted by active striated muscle during and after change of length. J Physiol 117, 77-86.

On 2017-02-06 10:39:29, user B C M Ramisetty wrote:

Kindly note an error made by us regarding disk diffusion assay results in the text. Thanks to Dr. Xavier Charpentier for spotting the errors.

Until a correction is posted, kindly read it as "We observed that zone of inhibition of MG1655 with ciprofloxacin (10 ug) was 3 cm (averages) while that of ?10 strain was 3.6 cm (Figure 3B)."

"With ampicillin (10 ug), the zones of inhibition for MG1655 and ?10 strain were 2.1 and 2.45 cm, respectively."

"With nalidixic acid, the zones of inhibition for MG1655 and ?10 strain were 1.78 and 1.98 cm, respectively."

Thank you

On 2021-03-29 19:30:31, user PaleFlesh wrote:

Interesting study. However I am concerned with the usefullness of these findings since only two species were tested, which is too small of a number to definitively say these findings are universal. It would be interesting to see if these results could be replicated with trees, grains, or even algae.

On 2021-06-04 18:54:07, user jasonrasgon wrote:

We are aware of an error in this manuscript regarding the small RNA analysis, the data have been reanalyzed and a corrected version will be uploaded shortly.

On 2022-03-17 17:00:47, user Joram wrote:

This work is now published in Frontiers in Digital Health: https://doi.org/10.3389/fdg...

On 2021-04-09 16:25:37, user Cyril Falentin wrote:

interesting paper, is it possible to get Supp Fig/Table and Supp Material 1 please ? can't find it.

On 2019-07-09 10:18:30, user Peter Manning wrote:

Hi Noemie- you're probably aware of it but we took a similar approach, but no SEM, in an old Ecotron experiment. Details here: https://www.sciencedirect.c...

On 2023-10-26 14:53:28, user Jordan Hamm wrote:

This paper is now published in PNAS. https://doi.org/10.1073/pna...

On 2020-06-25 16:59:55, user Jitin Singla wrote:

Please refer latest version

On 2022-05-13 17:10:25, user Prof. T. K. Wood wrote:

May wish to cite the literature relevant to MqsR/MqsA since we discovered it in biofilms, characterized it as a TA system, and got the structure for the toxin, antitoxin, and antitoxin binding DNA (all not cited here). Moreover, we linked it to resistance to bile acid in E. coli.

On 2022-09-30 22:29:03, user MIT Microbiome Club wrote:

It is know that the effect of a drug, and therefore perhaps a bacteria, can be non-linear with concentration, and that dose-additivity (Bliss) predicts drug combinations better than effect-additivity (DOI: 10.1038/s41564-018-0252-1). How might this impact the results? Of course, it can hard to half the concentration of the bacteria in the setup to create the Bliss model (although maybe something with lower glucose might help?) Might the fastest grower in each pair/trio reach the highest concentration, limit the growth of other species, and therefore provide an effect quite similar to itself in isolation? How would a "fastest grower" model compare to a "strongest" model? The authors note that growth rate did not correlate with effect size for "some" focal species, but might such a model work for the remaining focal species?

On 2023-07-20 09:13:24, user Dmitrii Kriukov wrote:

This is a great paper I found so long! Thank you for your work! You express many thoughs I had and even more.

Minor comments to your work:

• Fig 3: "Black indicates observed variance; grey unobserved". - there is no grey entities, only black circles.

• Fig 10: "MRL" in the legend

• I would be excited to see also the experiment with KD method versus real data and its comparison to different MLRs.

On 2016-12-01 10:47:51, user Torbjørn Ergon wrote:

This paper has now been published as Open Access in Journal of Evolutionary Biology. Download at https://www.researchgate.ne...

On 2022-10-02 17:56:40, user Carrie Partch wrote:

The labs of Seth Rubin and Carrie Partch at UCSC jointly reviewed this preprint. This manuscript examines how the two transactivation domains (TADs) of ?-catenin interact with several domains of CBP/p300 to potentially control transcriptional activation. A combination of biochemistry, NMR, and ITC studies narrow down several binding sites for TAZ1 and TAZ2 domains. Overall, the manuscript is well organized and provides new details on these interactions that may play a role in ?-catenin function. We have some suggestions that might enhance the clarity of the work below. Thanks for an enjoyable read!<br /> Figure 1: <br /> • The schematics do not depict consistent widths/domain lengths and CBP/p300 is missing some domains, including one implicated in ?-catenin binding (Emami et al. 2004, PNAS).<br /> • It would be helpful if your schematic also illustrated all of the constructs used in the study and these names were used consistently.<br /> • If space allows, a simplified diagram of the pathway described in the text could be helpful.

Figure 2:<br /> • It would be helpful to add dashed line for predicted secondary structure cut-off at 0.3 in panel B.<br /> • It would enhance the rigor of the work to show expression levels for the constructs used in panel C.

Figure 3:<br /> • Labeling the MW markers, light and heavy IgG chains, and proteins (does the 666-781 fragment overlap with the light chain?) in panel A, along with the input, would make this figure easier to read.<br /> • The results of the pulldown seem pretty straightforward so quantification from n = 2 experiments seems unnecessary. If you do so, please define what ‘relative’ means in the quantification and make sure that your statistical methodologies are appropriate for this low n.

Figure 4:<br /> • There is some concern that the ITC data might be overfit to a two-site binding model without more information on the fits. Additional rationale or evidence that justifies use of the two-site model would also be welcome.

Figures 5 & 7:<br /> • It might be easier to interpret the binding interface if you used surface representation for the TAZ domains instead of ribbon.

Figure 8:<br /> • It was a bit confusing to show an analysis of the NMR data from the construct used in Fig. S3 in panel A, but then use data in panels B – E from a larger construct. We struggled a bit throughout the manuscript to match domain names and fragments (see Fig. 1 comment above) with the data.<br /> • It could be helpful to conclude with a cartoon or schematic that illustrates what was learned here.

Other:<br /> • Discussion text mentions a possible role for phosphorylation of serines; if citations for this exist, please add them or perhaps broaden this to a possible role for PTMs in general.<br /> • Consistent labeling of ITC data throughout the paper would help clarify which fragments of b-catenin were used in each experiment.

On 2017-03-02 23:39:01, user Stephen Williams wrote:

FYI the supplemental data is in a .tar ball not .txt.

On 2023-11-24 14:29:41, user eldad-a wrote:

Afik, E., Liu, T.J.B. <br /> & Meyerowitz, E.M. Macroscopic waves, biological clocks and <br /> morphogenesis driven by light in a giant unicellular green alga.<br /> Nat Commun 14, 6204 (2023). https://doi.org/10.1038/s41467-023-41813-6

On 2018-08-07 08:16:05, user matthewcobb wrote:

As an alumnus (1992, I think - the year Seymour Benzer came on the course as a student...), I thought this was a really interesting article. However, I think it could be strengthened quite a bit by being more critical/taking the long view and exploring some of the following questions:

How has *what* is taught changed over time, and *how* it is taught?

In retrospect, did the course get obsessed with certain techniques that turned out to be dead ends? How were the topics chosen? A summary of the topics taught in a table, together with some analysis, even hand-wavy, would be really useful.

How did the course contribute directly to the spreading of techniques, or did it only teach things that were well-established?

You describe how students are recruited, but what about the staff? You say where they are from, but what kind of 'social network' underpins staff selection? Has this changed over time? Why (not)?

CSHL has a tradition of highly influential summer courses (the Phage course in the 50s and 60s would be the obvious example). How does the fly course compare to this? Has it been as influential (probably not, although maybe in the early years), and if so how do you measure this?

Finally, I think you need to be a bit more critical about the claims for the role of the course in future careers. Understandably, you don't have a proper control group – as you explain, the students you recruit are generally the best/most motivated (I exclude myself from this ), so you can't compare their success with the overall grad school figures. You can make the comparison, but your suggestion that the course has 'a dramatic impact on trainee outcomes' isn't supported by it.

Good luck with the publication of this!

Matthew Cobb

On 2019-09-11 15:31:45, user Vesta Bahrami wrote:

Hi,

A question! What about those Zorastrians who converted to Islam recently? I also have a comment: I am from Iran and I have been told my family (from my mother side) were practicing this religion until 1900. My mom is from a place close to Hamedan in central Iran. My grandpa told us that they were from a big family (Bahrami) and they practiced persian religion not Islam until recent. They do not practice Islam now anyway, but are registered as muslims. They are from Persian_A group (I guess) since they live in that area. And also another comment. In Iran, in old days, people mixed mostly with local people who they shared similar genes with. Do u know if it is the same in other groups that Iranian Zartoshtis? And I know some Bahai people are mixed with zoroastrians in Iran.

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

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

By Petting My Dog

On 2022-10-24 23:44:43, user CDSL JHSPH wrote:

Thank you for giving us the opportunity to review your preprint article! I enjoyed reading the article and it was fun to learn a little more about whale songs and their potential influences. Understanding how vocal learning and conformity is especially important as the noise environment continues changing in the ocean. Overall, the article had a lot of information that supported how much fin whales depend on vocal learning and conformity.

I felt that your abstract and introduction requires additional information to understand the paper. There was a clear definition for vocal learning, but conformity and what a singing season is was not well defined. Additional information on fin whales would have also been nice to better understand their behavior not in the context of song. I liked how you included other examples of species to gain a better understanding and it also helped show that this study could potentially translate to those species as well. It was clear what questions you were trying to answer with your study, and you defined your results clearly without going too deep into it.

For the most part your methods and results were clear to understand even for someone who has no background in what was studied! In Figure 2, I thought that I had was to potentially add a comparison in Panel C to the 1998/1999 season. It would be interesting to see the change that occurred in all the locations in the ONA region instead of just seeing the one shown in Panel B. Figure 3 was clear to understand and it supported most of the claims that were made in the introduction. I thought it was very cool to see how many ways these figures could be interpreted. An additional suggestion that I have is for Figure 4, I felt like the figure caption was bare and was missing some information to make it easier to understand and there was not much detail into what this figure was supporting so I had to make my own inferences into what was being shown there. Additionally, frequency of note was spoken throughout the article so the frequency on the y-axis was confusing so potentially changing or clearly defining that axis title would be beneficial.

The discussion section in your paper went into a lot of detail and at times felt like too much. The discussion of the results that you obtained were lost in a lot of the extra information that was in it and at times were confusing since it felt like it was jumping around too much. At times it felt like I was reading a review article on animal songs instead of results from a study, but some of this information may be beneficial to have in the introduction section instead. Overall, I thoroughly enjoyed getting to understand whale songs a little bit better and the results that came out of your work are very interesting and hopefully this can form a basis for future studies in other animals that use song.

On 2025-03-17 14:47:47, user Gabriele Scheler wrote:

It looks like you omitted this paper https://pubmed.ncbi.nlm.nih.gov/29071065/ and the earlier paper by Koulakov etal., which showed that Hebbian learning alone - for instance in a homeostatic setting - is sufficient to result in lognormal distributions of synaptic strengths, also intrinsic strengths and spike rates. This was first discovered by SchelerSchumann2006, taken up by Hromadkaetal2008 and then explained by Scheler2017. With the exception of Buzsaki, the whole discussion is missing.

On 2021-02-05 18:43:15, user Morgan wrote:

Nice work from the Stavrou lab! I do have a question about the statement that the MARCH proteins addressed in this study target viral glycoproteins for degradation. Do you think MARCH proteins could be targeting various viral GPs through different mechanisms? For example, I noticed levels of cell lysate EBOV-GP2 was assessed in the presence of MARCH1/2/8, but did you assess the level of EBOV-GP0? Other studies on MARCH antiviral activity suggest EBOV-GP sequestration to the golgi and inhibiting processing of GP0 to GP1/2. How might you explain or reconcile conflicting reports? Also curious, do you have localization data or inhibitor experiments performed not only with MLV but also HIV-1, EBOV-GP, IAV, and the other viral GPs assessed in this study? I think those data would be interesting to see! Thanks for your time and efforts!

On 2020-05-18 13:31:12, user Jessica C Kissinger wrote:

My research group and collaborators are pleased to share our research on the complex & novel mitochondrial genome of Toxoplasma and related parasites with the larger parasite and evolution communities @WiParasitology @ISEPprotists @CTEGD. We welcome your feedback.

On 2019-04-01 07:40:24, user Jubin wrote:

The authors have missed to mention/compare a related tool called SVAMP that has already got a nice and user-friendly GUI: https://github.com/raeece/s...

The original paper for the same can be found here: https://www.ncbi.nlm.nih.go...

On 2019-03-31 00:38:04, user Gokul Rajan wrote:

Nice work. :) It's really interesting that the microbes were necessary for this learning task; but isn't it an overstatement to call them sufficient for cognition?

On 2021-03-18 21:47:49, user Raghu Parthasarathy wrote:

This looks useful, and I'm glad you found my work valuable! I strongly feel, though, that science doesn't need more acronyms (see e.g. here: https://elifesciences.org/a... "https://elifesciences.org/articles/60080)"), and simply combining my radial symmetry localization with FISH doesn't warrant a new term.

Also, by the way, I generalized my algorithm to 3D many years ago, but never formally published it (https://pages.uoregon.edu/r... "https://pages.uoregon.edu/raghu/Particle_tracking_files/radial_symmetry_3D.html)"). Other people also made a 3D version, as noted in the link above. If you had contacted me, I'd have happily told you about this and saved you some work.

On 2021-03-08 14:39:24, user @DrySci wrote:

Nice article @benjraphael et al... are there possibilities to apply in targeted sequencing data ?

On 2021-11-05 16:17:02, user Alizée Malnoë wrote:

The manuscript by Seydoux et al. investigates the role of proton potassium antiporter KEA3 in diatoms. The authors first demonstrated the pH dependence on photoprotection, specifically non photochemical quenching (NPQ) and showed that NPQ can be induced in the dark by acidic pH. They found that KEA3 modulates NPQ by impacting the proton motive force (PMF); indeed generated kea3 mutants showed increased partitioning into deltapH. Importantly they showed that diatom KEA3 in contrast to plant KEA3 possesses an EF hand motif which can bind Ca2+ and proposed that it controls KEA3 activity. The role of KEA3 and pH in affecting the NPQ response has been previously shown in other photosynthetic organisms however the novelty of this study lies in the demonstration that NPQ can be induced in the dark by acidic pH and the proposed role of Ca2+ in regulating KEA3 function.

Major comments<br /> - Page 5, you state that pH-induced quenching in the dark was accompanied by the conversion of DD into DT. Please provide de-epoxidation state (DES) at t15 time (Fig. 1B) to substantiate this statement. Starting DES would also be informative to ensure there was no retention of DT/zeaxanthin in the dark. <br /> - Also to ensure there is no sustained NPQ (and/or damage or disconnected antenna) at t0, please provide Fo and Fm levels for all NPQ kinetics experiments. Assessing PSII accumulation by D1 immunoblot could be done to ensure PSII damage does not occur.<br /> - In Fig. 2F, it is not clear which data points represent HL or ML treatment as well as which ones come from light or dark period. Please indicate them in different colors or symbols. Also clarify whether you have averaged data from the kea3 mutant alleles.<br /> - To confirm that lack of complementation by deltaEF is not due to mislocalization, please show whether deltaEF accumulates at the thylakoid membrane.

Minor comments<br /> - Page 3, Introduction, specify qE after NPQ response; PSBS should be written PsbS<br /> - Page 4, DD-dependent NPQ should be DT-dependent<br /> - Page 4, we suggest changing “crucial” to “Given the unknown role” if pH-dependence of NPQ in diatoms hasn’t been fully established before<br /> - Page 8, KEA3 most likely homolog, were there other homologs than the two shown in Fig. S5? also discuss conservation of other ion channels (is Phatr J11843 thylakoid-localised?) and if they could compensate for the absence of KEA3 in KO mutant (by being upregulated for instance).<br /> - Fig2B, comment on the band at ~80kDa in OE, is that from cleavage of GFP?<br /> - Fig2G, shouldn’t you expect a lower dpH in the OE? Please comment.<br /> - Page 13, for the statement that only dpH can modulate NPQ, we would suggest to tone down or specify that this is the assumption made here as it could be that dpsi modulates NPQ but has yet to be shown!<br /> - Most of the protein analyses were performed loading samples based on protein content, when possible please provide proof that chlorophyll levels are comparable between the genotypes (at least for the native gels)<br /> - Abstract, extra ‘of’ between capacity and via; page 23, extra ‘being’ between likely and less important<br /> - Define acronyms when used for the first time<br /> - There is a lot of ‘peculiar’ in the text ;-)<br /> - Fig. 2D, star symbol instead of square symbol, check consistency of symbols

Pushan Bag, Pierrick Bru (Umeå University) - not prompted by a journal; this review was written within a preprint journal club with input from group discussion including Alizée Malnoë, Maria Paola Puggioni, Jingfang Hao, Jack Forsman, Wolfgang Schröder, Emma Cocco, Jianli Duan.

On 2022-09-26 12:05:30, user Miha Moškon wrote:

The final version of this paper has been published at https://doi.org/10.1016/j.biosystems.2022.104778

On 2017-07-12 17:39:25, user guillemaud wrote:

PREPRINT PEER REVIEWED AND RECOMMENDED by PCI EVOL BIOL

This preprint by Clemente has been peer-reviewed by Michael D Greenfield and Joël Meunier and recommended by Vincent Calcagno for Peer Community in Evolutionary Biology. Peer-reviews, decisions, author's replies and the recommendation can be found here: https://evolbiol.peercommun...

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

On 2016-07-31 09:08:38, user Steven Wilson wrote:

This manuscript has been revised and accepted after peer-review, and should be available for open access reading in about a month!

On 2020-07-18 08:25:51, user Önder Kartal wrote:

Our paper has now been published by Genome Biology, <br /> see https://genomebiology.biome...

On 2023-09-26 21:25:26, user Victor M Faundez wrote:

Paper is now in press at Human Molecular Genetics<br /> https://doi.org/10.1093/hmg...

On 2018-12-11 22:42:03, user Andrew Leifer wrote:

Thank you for reading our manuscript closely and for sharing your comments with the community. We welcome a robust scientific discussion about our findings. In fact, this is one of the primary reasons why we post to the bioRxiv. Your group, in particular, has done pioneering work in this area and we value your thoughts. Below we provide a brief response to your note, highlight areas where we disagree, and discuss specific analyses to support our claims.

• The major concern expressed in your comment relates to noise in our measurements in (Scholz et al., 2018). The strongest argument that counters concerns about noise is that our neural recordings predict the animal's behavior in held out data, while control GFP recordings do not (Fig 2G). Thus, noise in our recordings are not sufficiently strong to swamp out relevant behavior signals in moving animals nor are they strong enough to mimic those signals in control animals.

Extrapolating from your pioneering work, we had expected to see a dominant behavior signal in the first three PCs of neural activity, but we did not find such a signal. You express concern that perhaps noise may be present to such an extent during movement that it precludes drawing any conclusions from our PCA analysis. We do not think that is the case. Nonetheless, it is worth imagining what such noise would have to look like for it to both invalidate our PCA analysis yet simultaneously preserve our ability to successfully predict behavior. To be consistent with our measurements, such noise would have to have the following properties: 1) Be comprised of at least three independent orthogonal components that are the most dominant features in the recording. 2) Be distributed across many neurons (because otherwise these signals would not dominate in PCA, which involves z-scoring each neuron's signal). 3) Not overpower a signal that we observe in the first three PCs that is slightly predictive of the animal's velocity in GCaMP worms but absent in GFP control worms (Fig 2G) and 4) still preserve our ability to predict velocity and turning from the activity of a subset of neurons on held out data. While we cannot rule out noise with such unique properties, we think a much simpler explanation is that the first three PCs are not dominated by noise. We therefore merely conclude that the first three modes lack predominant behavior signals. In retrospect, it may not be surprising that moving worms have other signals dominating their neural dynamics. These could, for example, be related to sensory signals or to internal states.

• You also express concern about our ability to observe the manifold that you report in immobile conditions (Kato et al., 2015). We agree that perhaps the recording shown in Fig 1F is too short to clearly see multiple cycles on the manifold. We chose this recording because it allowed us to directly compare moving and immobile states in a single trial. Longer recordings provide a better example. When we look at longer recordings (BrainScanner20171017_184114 from Table 3) we clearly recover a very similar manifold to the one your group published (see Comment Figure 1, below, two views of same recording). Thank you for urging us to push this comparison further, we will include this plot in future versions of the manuscript.

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

• You also express concern that our velocity prediction is dominated by switches between positive and negative velocity. Comment Figure 2, below, shows that this is not the case (the same trace is shown here as is in Fig 2). The fit is not dominated by forward or backwards velocity, but rather accurately fits and predicts intermediary velocities. We will add these plots to future versions of the manuscript. Thank you for encouraging us to look more critically at this.

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

• We are aware that estimating neural IDs is extremely challenging. We have tried to be very transparent in our estimates. Table S2 and the supplementary methods give details. We are also happy to answer any specific questions you might have.

• Sparse models have been successfully used before in neuroscience (Pillow et al., 2008; Tankus et al., 2012). We are aware of potential concerns with fitting sparse models. We mitigate them by 1) using elastic net which is suitable for highly collinear datasets such as ours, 2) using cross-validation to evaluate the robustness of our fits (Roberts et al., 2017), and 3) assessing model performance on held-out data, which we note is a higher standard than typically used for linear regression in the field. <br /> In fact, reference (Wu et al., 2007) that you mention in your note claims that LASSO performs best for datasets like ours where the variables have correlations, and we note that our elasticnet model incorporates the LASSO penalty.

• Thank you for finding the typo in Fig 2D. We will fix it in future versions of the manuscript.

We appreciate your comments as they help us to strengthen the manuscript and anticipate reviewer comments.

Sincerely,<br /> Monika Scholz and Andrew Leifer

REFERENCES

Kato, S., Kaplan, H.S., Schrödel, T., Skora, S., Lindsay, T.H., Yemini, E., Lockery, S., and Zimmer, M. (2015). Global brain dynamics embed the motor command sequence of Caenorhabditis elegans. Cell 163, 656–669.

Pillow, J.W., Shlens, J., Paninski, L., Sher, A., Litke, A.M., Chichilnisky, E.J., and Simoncelli, E.P. (2008). Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature 454, 995–999.

Roberts, D.R., Bahn, V., Ciuti, S., Boyce, M.S., Elith, J., Guillera-Arroita, G., Hauenstein, S., Lahoz-Monfort, J.J., Schröder, B., Thuiller, W., et al. (2017). Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913–929.

Scholz, M., Linder, A.N., Randi, F., Sharma, A.K., Yu, X., Shaevitz, J.W., and Leifer, A. (2018). Predicting natural behavior from whole-brain neural dynamics. BioRxiv 445643.

Tankus, A., Fried, I., and Shoham, S. (2012). Sparse decoding of multiple spike trains for brain–machine interfaces. J. Neural Eng. 9, 054001.

Wu, Y., Boos, D.D., and Stefanski, L.A. (2007). Controlling Variable Selection by the Addition of Pseudovariables. Journal of the American Statistical Association 102, 235–243.

On 2024-03-27 20:38:47, user Chris Buck wrote:

I've posted some further thoughts about this manuscript on my Substack page:<br /> https://open.substack.com/p...

On 2021-09-14 14:35:27, user Donald R. Forsdyke wrote:

The final peer-reviewed version of this paper may be found in Computational Biology and Chemistry 94:107570

On 2014-05-15 07:55:24, user Daniel Klevebring wrote:

Very nice work.

For some reason, I can't see the figures in the PDF of the main paper. The suppl figs show nicely, but only white boxes in the main PDF. Any idea why that is?

thanks

On 2017-04-20 18:45:48, user Loren Hauser wrote:

Interesting, but unfortunately this doesn't tell me if the variation is planned or just due to mis<br /> takes by the splicing system in cells. You really need to combine this with proteomic measurements that tell which splice variants are actually translated and inserted into the membrane.

On 2019-05-01 16:07:38, user Bert wrote:

Interesting, but there is no evidence yet that there is actually a TonB-dependent (outer membrane) transporter that imports these compounds.

On 2023-07-06 12:26:49, user Felix Hernandez wrote:

This MS has been published in International Journal of Molecular Sciences - MDPI

https://www.mdpi.com/1422-0...

https://doi.org/10.3390/ijm...

On 2018-05-09 17:37:56, user Uri David Akavia wrote:

Congratulations Dylan!<br /> Is the source code going to be available at some point?

On 2021-10-12 13:47:56, user Luisa Hugerth wrote:

The github link in the abstract leads to a 404 Page Not Found error. Maybe the repository is mistakenly marked as private?

On 2022-06-24 01:15:41, user Jichen Bao wrote:

The manuscript has been accepted by ACS synthetic biology. https://pubs.acs.org/doi/10...

On 2022-11-22 11:33:47, user Deepali Pal wrote:

Part of this study has been pre-print as below:<br /> https://www.cell.com/cell-r...

On 2020-07-22 19:33:46, user Richard Sanchez wrote:

interesting work from Ferdosi et al. It beautifully illustrates PTEN as a<br /> novel marker for neddylation inhibition as well as further exemplifying<br /> the integration of multi-omic data.

On 2018-07-31 11:29:06, user H. Etchevers wrote:

Accepted in a special issue of the journal "genesis" (Wiley) for the 150th anniversary of the neural crest, to appear at http://dx.doi.org/10.1002/d...

On 2018-10-02 19:55:41, user BU_Fall_BI598_G3 wrote:

Reinhard et al. performed transsynaptic tracing of retinal ganglion cells (RGCs) from targets in the superior colliculus (SC) projecting to either the lateral pulvinar (LP) or the parabigeminal nucleus (PBg), in order to determine how visual features are routed to the two areas. Analysis of dendritic morphology showed that retinal inputs to the parabigeminal and pulvinar circuits differ in size and stratification, and labelled RGCs were also characterized by their molecular identity. Morphological and molecular data was then used to identify twelve clusters of RGCs; each cluster contained cells of similar dendritic profile and molecular makeup. The LP and PBg receive input from distinct clusters, and the authors argue that each cluster contains a single cell type, which may encode a unique feature of the visual environment. They show that the SC demonstrates a relatively high degree of regularity in its guidance of inputs to various targets.

Overall, this study offers an in-depth look at the pulvinar and parabigeminal pathways. Reinhard et al. were successful in identifying which RGCs provide input to the LP and/or PBg, and the identifications made in this paper are helpful in indicating what type of input each nuclei is receiving. Another key strength of these experiments is the ability to express GCaMP in specific RGCs based on their downstream projection pathways. Such a technique is very useful for future experiments to precisely characterize ganglion cell response to a visual stimulus. Finally, Table 1 offers a nicely detailed summary of the structural and functional information on the pulvinar and parabigeminal circuits gathered in this study as well as in other studies. This summary allows clear understanding of the pathways and hints at possible future studies.

While we appreciate this manuscript’s strengths, we identified a few areas of major critiques, addressed below.<br /> Some important controls to verify the validity of the experimental setup are missing. Although using Cre-inducible viral cargo in injections to the lateral pulvinar is a good experimental design, it is not proven that the floxed TVA-G-mCherry is expressed in pulvinar-projecting neurons only. To verify this specific expression pattern, in a NSTR1-GN209-Cre brain injected with HSV-flox-TVA-G-mCherry and stained for pulvinar-projecting neurons, all fluorescent cells should be double-labelled. Additionally, does the experimental technique label cells in the superior colliculus that project to both the lateral pulvinar and parabigeminal nucleus? Such cells would take away from the claim that visual information is, for the most part, routed separately to these two areas. To test this possibility, we suggest injecting HSV-GFP into the pulvinar and HSV-mCherry into the parageminal nucleus and subsequently studying the superior colliculus for any double-labelled yellow cells. Also, rabies virus is known to destroy cells about ten days after infection. Therefore, significant variations in cell morphology created by the rabies virus could be present in the later stages of infection . We would like the authors to show that at the time of retinal extraction, the RGCs are still healthy and not yet negatively impacted by the rabies virus. Finally, though it is important to be able to extract out individual dendritic trees for analysis, does choosing cells only with non-overlapped dendrites create bias in the morphological or molecular identities of the chosen cells?<br /> Throughout the paper, techniques and ideas could be explained more clearly. Confusing wording and sentence structure make the paper difficult to follow at times (for example, the sentences starting on lines 112, 115, and 205). Additionally, the authors’ experimental setup is not entirely clear from the first few paragraphs of the paper. More detail about the viruses used, their cargo, and the expected expression patterns would be helpful for the reader to understand the overview of the experiment. A cartoon or an improved diagram of injection locations and expected labelling of the cells within the circuits could help with clarity. In other areas of the paper, the authors’ rationale for experiments is ambiguous. For example, with the description currently given in the text (lines 145-158), Figure 5 is very confusing. A more complete explanation of the rationale behind clustering the cells and brief descriptions of the three validation indices would make Figure 5 significantly more clear and highlight its importance for the rest of the paper. Another area that could benefit from further explanation is the comparison of 7 clusters to groups of PV cells in Figure 7. I.e., why were only 7 clusters shown and why were PV cells used for the comparison?<br /> The content and style of various figures made assessing the experimental design and results challenging. Small image/diagram size and low contrast was a recurring problem in several figures. For example, confirming injection specificity in Figures 1B and 1F is difficult simply due to image size. However, specific verification that fluorescent cells shown are truly in either the parabigeminal (1B) or pulvinar nucleus (1F) should be included also. Additional images verifying the placement of the EnvA-RV-GCamp6 superior colliculus injection would also be beneficial for readers. Image size and contrast was also an issue in Figures 1C,1G, 4A, and 4D. Low image magnification in figures 3C, 3G, and 4B made it difficult to see the colocalization of fluorescent labels. Similarly, to identify the lack of colocalization, Figures 4E and 4F should have been merged. Figure 2B should show percentages of cells rather than number, to provide more context for the data. Figure 1A and 1E depicting injection sites were confusing due to the color scheme chosen to represent HSV-TVA-G-mCherry and GCamp6. While we appreciated that two different colors were used to represent HSV-TVA-G-mCherry for the pulvinar injection (green) versus the floxed version for the parabigeminal injection (orange), this became confusing because the word GCamp is highlighted in green in the figure. Additionally, Figure 4 could be further improved if a quantification of CART+ cells was included, similar to what was done in Figure 3 for SMI32+ cells.

Additionally, there were a few minor weaknesses that, if addressed, could improve the quality of the paper. <br /> 1. The RGC clusters and their projections to the pulvinar and/or parabigeminal circuits identified in these experiments are useful in identifying the clustering of cells and subsequent circuitry implicated in routing visual inputs through the superior colliculus. However, an important distinction should be made between the identification of clusters versus cell types, as it cannot be necessarily concluded that cluster is equivalent to cell type. The 12 clusters identified in these experiments are referred to as putative cell types (line 161), and we do not believe the data presented in this paper is enough to make such a claim. Clusters may very well contain different types of cells that had similar morphology resulting in them being grouped into the same cluster, and the molecular data is not robust enough to validate these clusters as cell types. Moreover, the 3 clusters that were found to project input into both the pulvinar and parabigeminal circuits were referred to as ‘3 visual features’ (line 243). While separate clusters may represent distinct features of the visual space, this conclusion cannot be inferred from the data in this paper. <br /> 2. For both Figures 5 and 6, adding a color legend that identifies each cluster by the descriptive name given to it in the text (and Table 1) would help clarify the figures for readers. <br /> 3. In Figure 5, a 3D plot of the clusters could be added in the supplement for better visualization of the clusters along all three axes. <br /> 4. Use of PV-Cre mice as wild type mice is not discussed or validated.

On 2015-12-04 13:27:31, user Hiren Ghosh wrote:

Have any one tested this algorith with his/her own dataset ???

On 2023-11-10 16:44:10, user KJ Benjamin wrote:

Interesting approach, but I'm confused why the authors would model population instead of genetic ancestry? The authors use ADMIXTURE to show a great degree of mixed ancestry, but do not examine the effect of genetic ancestry, but "population grouping". This would be extremely influenced by environmental factors that are differences across and within continental groups.

On 2016-05-13 00:51:27, user Donald R. Forsdyke wrote:

Please note that the case has been made that "BDM" should be "DM". See Heredity (2011) 106, 202 (http://post.queensu.ca/~for... ).

On 2025-07-15 22:07:24, user Åshild Telle wrote:

Links to movies (Supplementary Material):

https://www.dropbox.com/scl/fi/pa00vq7h29jlptegmkmp3/Patient1.m4v?rlkey=8xj6oula1ys68vdpzprhmlu61&dl=0 <br /> https://www.dropbox.com/scl/fi/7daf5rwkbh907lhxq03yk/Patient2.m4v?rlkey=8td1vwxhl4f70w2151owcmful&dl=0 <br /> https://www.dropbox.com/scl/fi/m0rd44brd5mhxllcm9cra/Patient3.m4v?rlkey=6t6er8qicg1t5pfgpuhnk05es&dl=0

On 2019-03-27 19:49:57, user Andrew Johnson wrote:

Nice work. A few minor comments: <br /> 1) the 1st report of IQGAP2 rare variant association with MPV was Ref. 49 - comment is that this was an Exome chip study rather than GWAS<br /> 2) rare variants in KALRN first reached genome-wide significance for MPV in Gieger et al., 2011 PMID 22139419 (not currently cited here), subsequently replicated in Eicher et al. Ref 49 and then Astle et al. Ref 29

On 2020-05-27 15:45:40, user OxImmuno Literature Initiative wrote:

https://www.immunology.ox.a...

On 2023-03-29 14:06:54, user Sarah Chellappa wrote:

Thanks for sharing these important insights. It is unfortunately not surprising that race/ethnicity and socioeconomic status are not frequently reported. Most sleep and circadian studies come from study samples comprised of individuals who are white, middle-class and from high-income countries. Hence, there is a historic imbalance that perpetuates until today. One of the perks of addressing this issue is that it will help foster more research into the socioeconomic determinants of health.

On 2021-01-05 00:58:07, user Charles Warden wrote:

Hi,

Thank you for posting this pre-print.

I see that this pre-print has both supplementary material and a link to code:

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

https://github.com/OSU-BMBL...

However, the section for "Supplementary Materials" says "Supplementary Data are available at Science Advance online".

Is this intentional (perhaps part of an automatic submission from a journal?), or should the section say something else?

Best Wishes,<br /> Charles

On 2015-09-03 07:53:42, user Pierre Boursot wrote:

Spectacular finding. However I am surprised that the interspecific introgession hypothesis is not evoked. There are numerous examples of massive interspecific mitochondrial introgression not accompanied by any detectable nuclear introgression (and here with three nuclear fragments, the power to detect it is very limited anyway). This would in my opinion be a much more plausible explanation than long term high effective population size, which should anyway leave even more marked traces in the nuclear genome. There would remain to find the donor species, but they may be extinct. An analysis of the coalescent in each of the divergent mitochondrial lineages segregating in a given species might give hints about which lineage is likeky to be introgressed, since the most likely source of massive introgression is during range expansion into the territory of another species, and this is expected to leave a signature of expansion of the lineage that introgressed from the species whose territory has been invaded.<br /> Sorry for the self-citation, but you could read this paper and several references therein:<br /> Melo-Ferreira, J., L. Farelo, H. Freitas, F. Suchentrunk, P. Boursot, and P. C. Alves. 2014. Home-loving boreal hare mitochondria survived several invasions in Iberia: the relative roles of recurrent hybridisation and allele surfing. Heredity 112:265-273.

On 2018-04-11 02:12:06, user Emily Stephen wrote:

Great paper, thanks for sharing! I think you have a mistake in the methods: "Each 200 ms epoch was multiplied with a Hann taper, zero padded to 1 s, and Fourier transformed, resulting in an FFT spectrum with a frequency resolution of 1 Hz." -- actually, the frequency resolution should be more like 10 Hz. With 200 ms windows and one taper, the half-bandwidth will be 1/0.2 = 5Hz. Zero-padding doesn't affect the frequency resolution, just the interpolation of the frequency axis.

On 2018-07-06 11:00:09, user kamounlab wrote:

In response to some comments we received, here is a comparison of the sequence chromatograms corresponding to Fig. 3. They show that MoT3 reverse primer sequences were recovered in amplicons from M. oryzae isolates including Bangladeshi wheat and rice blast fungi.

We conclude that:

1. The reverse primer showed mis-priming despite the single mis-match at the 3' extension end (based on FR13 sequence), allowing WB12-like sequences to be amplified.

2. There could also be degradation of primer at the 3' extension end that enabled amplification in rare cases: there is only one putative evidence (the double peak in chromatogram from RB-11).

3. The wheat blast isolate BR32 lacks the WB12 region.

Joe Win and Sophien Kamoun

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

On 2019-04-29 17:55:26, user Charles Warden wrote:

I hope we can find a way to get more comments on bioXriv, so that they could be discussed prior to submission to a peer reviewed-journal:

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

I would much rather have a revised pre-print than a correction / retraction in a peer-reviewed paper.

You can see any comments for an individual from their Disqus account, but I think this worked well in terms of keeping a friendly tone and asking questions that I think could improve reader understanding: https://www.biorxiv.org/con...

On 2022-02-21 19:22:36, user MA wrote:

The supplements tables are NOT included?!

On 2025-01-14 04:06:08, user Yi-Cheng Yang wrote:

This study contributes to the establishment of personalized treatment, such as considering the use of EZH2 inhibitors combined with PSMA-targeted therapy for NE type II patients, providing new treatment options for cancer patients.

On 2018-11-14 09:36:55, user Carlos Santiago wrote:

Quite interesting paper. Do you plan to extend it to evoked-potentials <br /> as well? There's another pipeline that deals with evoked and <br /> resting-data that has been validated in both healthy and schizophrenia <br /> patients that you guys could discuss: "An automatic pre-processing <br /> pipeline for EEG analysis (APP) based on robust statistics".

Further, there are the new guidelines for EEG pre-processing on https://osf.io/a8dhx that you could discuss. Nice work!

On 2019-05-07 01:17:57, user Keith Robison wrote:

I've written a pair of analyses on this -- some key criticisms are the lack of technical detail and that the analysis of errors is much less detailed than desired. There's also the lack of specificity in the text as to which data was deposited publicly -- only the E.coli is available. Also, the phred quality scores are overestimated at the high end by perhaps as many as 5 points.<br /> Poking at Genapsys Preprint<br /> Genapsys' Base Caller: Mysterious, But Not Ideal?

On 2023-01-11 04:42:12, user Leslie Vosshall wrote:

Konopka et al. produce a valuable reagent for the Anopheles mosquito community – a QF2 knock-in into the bruchpilot (brp) locus. They use this strain to quantify the number of neurons in the major sensory appendages using an existing QUAS-CD8:GFP reporter strain. The images in the paper are beautiful and the cell counts are a valuable resource for the field. No one has attempted to do cell counts like this before, and this reagent made this possible.<br /> A few suggestions to improve the paper:<br /> 1) The authors have not formally shown that the brp-QF2w line is in fact pan neuronal. It would require significant additional work to prove this, e.g. double label antibody staining with RNA in situ hybridization against a pan-neuronal gene to show a 1:1 correspondence. I do not suggest that they do this, but it’s important to note the caveat early in the paper that the genetic reagent is assumed to be pan neuronal because the targeted locus is a neuronal gene.<br /> 2) Speculation on phenotypic/behavioral variability caused by variation in cell number (Line 283-299) seems premature to me. It could be variation in the expression of the driver or reporter, rather than underlying variation in the number of chemosensory neurons. More experiments would need to be done to confirm that what is seen with the genetic reagents reflects actual biological variability. I might suggest that this paragraph be toned down or removed.<br /> 3) Figure 2E-F, Figure 3E: could the authors clarify how the data are plotted and what the sample sizes are. I have the impression that the small dots are individual experiments, but it is not clear. For transparency, it might be best to not use bar plots and instead use dot plots where all of the data points are clearly visible.<br /> Review prepared by Leslie Vosshall

On 2015-04-04 02:08:22, user Rat_Fink_Forever wrote:

What percentage is showing up? I have 4.4% Denisovan according to the Human Genome Project and my near term history is from the Baltics, with 50% northern European and a hefty percentage of SW Asian.

On 2023-08-16 13:06:21, user Pierre-Luc Germain wrote:

Very interesting contribution, I'd just like to make two comments.

First, it's wrong to write that scDblFinder is "formerly known as doubletCells". They're two methods developed independently, and it's simply that doubletCells was moved to the same package, but still as an independent method.

Second, your results are in contrast with other benchmarks, which you explain by more "realistic scRNA-seq datasets". I'm obviously not entirely disinterested here, but I think this is very misleading: you don't show any evidence that the traditional benchmark datasets do have unrealistic patient or batch effects, and omit to mention the critical fact that, as far as I know, the fatemap samples are homogeneous cell lines, which is far from being more realistic (people do scRNAseq on complex tissues much more often than on cell lines). I think a fairer description would be to abandon the "realistic/unrealistic" labels, describe your data as it is, and hence that your observations are basically about homotypic doublets, which the tested methods are very bad at detecting (but also don't claim to do). The lack of real difference between adjacent/distant seems to indicate pretty clearly that you're essentially dealing with homotypic doublets.

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

Magdalena Bohutinska and Mark Alston contributed equally.

On 2015-07-27 15:52:01, user Maria Zavodszky wrote:

Hi, Thanks for sharing this manuscript. I have found that the manuscript mentions supplementary tables that I could not find in the word document posted here under Data Supplements. I would be interested in seeing them. Is is possible?<br /> Thanks,<br /> Maria Z.

On 2018-04-12 18:47:01, user H. Etchevers wrote:

Because this paper is behind a paywall, I will try to upload a revised version that includes the five references that had been missed in the first authors' version.

On 2019-11-25 09:30:11, user Daniel Žucha wrote:

Dear readers, <br /> I would like you to be notified that this preprint has been already published in the Clinical Chemistry journal with minor changes. It is accessible under DOI: 10.1373/clinchem.2019.307835. The direct link to this site is forthcoming shortly.

On the behalf of authors,<br /> Daniel Zucha

On 2020-07-07 11:41:45, user Rhyothemis wrote:

"SARS-CoV is known to repress ACE2 expression [4]. ACE2 regulation involves chromatin remodeling and structural chromatin changes [19]."

Could this type of change persist post-infection?

On 2021-02-18 06:24:22, user Ruoying Zheng wrote:

I totally enjoyed reading this paper. The experiment designs are great. It would be better if some parts of the article can be improved. In Fig 5, the biological model should be always mice instead of using human erythrocytes in 5A and using infected mice in 5C. Having a consistent biological model can rule out unnecessary variables. If both mice and human biological models are used here, then a vitro experiment about mice erythrocytes malarial infection and related treatments should be added here. In 5C, infected erythrocytes should have a higher FITC-A fluorescent binding properties than uninfected erythrocytes. More detailed explanation should be added in 5C to clarify the difference between each group. In the linear graphs of Fig 6A and 6C, different groups should have different colors, which would make it easier to read. As for the cell pictures in Fig 6A and 6B, the color scheme is not unified, the colors of the parasites should be the same in each picture so it would be less confusing. Besides, more background information about DHA(active metabolite of all artemisinin compounds) and why the author set up experiments to test efficacy of DHA+Alisporia should be explained.

On 2018-11-28 10:17:24, user Tanai Cardona Londoño wrote:

Hi, interesting proposal. I like it. A couple of comments.

The fossil heterocystous cyanobacteria reported by Pang et al., (2018) are not just akinetes. They are entire filaments with cells that do resemble heterocysts. I spent all of my PhD studying heterocystous cyanoabcteria, purifying them, extracting their thylakoids membrane, staining them, seeing them in a variety of microscopes... I have to say that those filaments are excellently preserved and are virtually indistinguishable from extant heterocystous cyanobacteria. I would dare to say that the fossils presented by Pang et al., (2018) are unequivocal fossils of heterocystous cyanobacteria. But I'm not a paleontologist.

You cited the review by Butterfield (2015) to validate your statement that the best fossil heterocystous cyanobacteria are from the Devonian, but in that paper that is Butterfield's own assessment, which predated Pang et al.'s paper. The Devonian fossil's cited by Butterfield are reported in a 1959 paper that I was not able to access. Were you able? Are those truly better preserved that Pang et al.'s? Butterfield does not show the Devonian fossils in his review... So, your argumentation there can be strengthened. Don't be so quick to dismiss Pang et al.'s fossils!

Your proposal also makes me wonder about the light-independent protochlorophyllide reductase. It is a nitrogenase-like enzyme and it is also oxygen sensitive (http://www.plantphysiol.org... "http://www.plantphysiol.org/content/142/3/911.short)").

Could it be that the oxygen sensitivity of protochlorophyllide-reductase limited the rise of oxygen prior to the Great Oxidation Event, before the diversification and expansion of today's taxa of cyanobacteria, and before the origin of the light-dependent protochlorophyllide reductase?

Thanks.

All the best,<br /> Tanai

On 2023-12-15 19:31:50, user Jordan C Rozum wrote:

This preprint has been accepted in PRX Life under a new title "Models of cell processes are far from the edge of chaos" and is openly accessible here: https://doi.org/10.1103/PRX...

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

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

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

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

On 2020-04-13 08:00:30, user Tartaglia Lab wrote:

This work is interesting and we find quite useful that the authors shared it. Thanks!

In our work (https://www.biorxiv.org/con... "https://www.biorxiv.org/content/10.1101/2020.03.28.013789v3)") we studied protein interactions with SARS-CoV-2 RNA using advanced computational approaches.

Just focusing on the RNA binding proteins present in the two studies, we found a significant overlap of genes such as Janus kinase and microtubule-interacting protein 1 JAKMIP1 (Q96N16), A-kinase anchor protein 8 AKAP8 (O43823) and A-kinase anchor protein 8-like AKAP8L (Q9ULX6), which in case of HIV- 1 infection is involved as a DEAD/H-box RNA helicase binding protein (among others).

It is very curious that our list of protein- RNA binding partners contains elements identified also in this protein-protein network analysis. Yet, it must be mentioned that ribonucleoprotein complexes evolve together and their components sustain each other through different types of interactions.

On 2025-04-04 09:28:15, user Volkmar Lessmann wrote:

Great work by the authors!! High profile research disentangling the role of phospholipid metabolism in rescuing AD phenotype with FTY720. Congratulations!

On 2021-02-18 21:31:48, user Dr. Tyeen C Taylor wrote:

This article is in review at Frontiers in Forests and Global Change

On 2015-06-03 14:54:48, user Kasper Hansen wrote:

This preprint was revised June 3rd, 2015. The major change in the revision is analysis of single cell epigenetic data (both ATAC-seq and WGBS). This has led to a change of abstract, introduction, a new results section and discussion; these changes simply reflect the additional data types. We have also included a very short analysis of the overlap of A/B compartments with various types of methylation domains (as has been previously done in for example Berman et al (2012) Nature Genetics. Typos etc. have been corrected and three new figures have been added.

On 2019-03-11 10:00:25, user Justin Andrushko wrote:

Fantastic paper investigating the cortical underpinnings of fatigability.The things I really like about this paper - no salami slicing! The authors conducted multiple experiments to investigate the observed mechanisms. The authors also included effect sizes on all statistical measures, something more people should consider to include. Effect sizes really help with data interpretation and meaningfulness of results. Great paper!

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

On 2020-03-06 22:44:50, user Luis Yáñez wrote:

this is a veyr useful paper, hopefuly will be published soon

On 2022-06-30 16:45:44, user Tatiana Mikhailova wrote:

Is raw .idat data from this study available for download?

On 2014-08-03 13:59:42, user Richard Rocca wrote:

Can you please post what where European samples ETR2, ETR5 and ETR9 are from and their archaeological context?

On 2018-03-30 13:00:18, user Markku Varjosalo wrote:

This preprint was published in Nature Communications on 22th of March titled as “An AP-MS- and BioID-compatible MAC-tag enables comprehensive mapping of protein interactions and subcellular localizations”