{"messages":{"status":"ok","interval":"2013","cursor":"10","count":25,"total":35}, "bioRxiv Disqus comments":[{"date":"2013-11-20","doi":"10.1101\/000570","name":"Larry","time":"2013-11-20T14:54:06","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/18\/000570","comment":"
This is an interesting finding, especially considering other findings of SMO (smoothened in humans): SMO drives insulin-independent glucose uptake in muscle and BAT in vivo (Teperino Amann 2012 Cell 151:414-426, PMID 23063129)<\/p>"},{"date":"2013-11-20","doi":"10.1101\/000711","name":"Aaron Berdanier","time":"2013-11-20T18:24:30","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/19\/000711","comment":"
This is exciting work. I have a few quick comments.<\/p>
It seems like an important aspect of this is that you are getting a much more nuanced picture of water use. I agree that this will be relevant for efforts to predict water use responses to the environment. I'm wondering if you could include some discussion about other efforts to do this (e.g., with time lags, etc.). I think that this will provide definite mechanistic improvements, but it seems like relevant literature to discuss.<\/p>
Also, I like how you used light sensors for individual leaves. I wonder how many hysteresis analyses use light data that is not representative of the canopy. I would imagine that most light sensors are either on the ground or on top of a tall tower (above canopy), which could be biased indices of what a tree actually experiences. What are the implications of this 1:1 (sap flow to light) connection (and its potential absence in other studies) for your findings?<\/p>"},{"date":"2013-11-21","doi":"10.1101\/000448","name":"sciencefanseattle","time":"2013-11-21T06:11:08","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/15\/000448","comment":"
Nice work, this is how I envisioned synthetic biology would look like. Same goes for their other paper in the series on this site: \"Negative autoregulation matches production and demand in synthetic transcriptional networks.\"<\/p>"},{"date":"2013-11-21","doi":"10.1101\/000547","name":"Kristian","time":"2013-11-21T09:49:57","url":"https:\/\/www.www.biorxiv.org\/content\/early\/2013\/11\/16\/000547","comment":"
Figure 4 is difficult to visually interpret because it uses a 3D projection. I would just use a simple 2D plot a la Figure 2.<\/p>"},{"date":"2013-11-22","doi":"10.1101\/000141","name":"Jacob G Scott","time":"2013-11-22T03:37:05","url":"https:\/\/www.jnl-biorxiv01.drupal-qa-mobile-web01.highwire.org\/content\/early\/2013\/11\/07\/000141","comment":"
This paper has just been accepted by PLoS Computational Biology - look for it there soon...<\/p>"},{"date":"2013-11-22","doi":"10.1101\/000752","name":"Larry","time":"2013-11-22T16:03:50","url":"https:\/\/www.www.biorxiv.org\/content\/early\/2013\/11\/19\/000752","comment":"
This is work of high value as it gets at the higher level interpretation (by the genome and its expression apparatus) of genomic variation. I would add some caution with regard to the LDL result because of the high number of variants in the large LDL receptor gene that contribute to non-normal values of this commonly measured blood lipid. On the other hand, this approach seems to be worthwhile and I would like to see a comparison between main effect associations and those modified by environmental factors (gene-environment interactions) for a given trait. Do the results shift in any significant way?<\/p>
@Larry_Parnell<\/p>"},{"date":"2013-11-23","doi":"10.1101\/000224","name":"Graham Steel","time":"2013-11-23T14:18:51","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/11\/000224","comment":"
Thanks for the comment. Myself and Prof Wiggins wrote this up in 2008. My involvement was part of the Abstract, helping out with the references and formatting it. Prof Wiggins wrote the main body. I've not had any contact with her since then. She retired several years ago. I'll see if I can evoke a response for you.<\/p>"},{"date":"2013-11-25","doi":"10.1101\/000752","name":"Larry","time":"2013-11-25T15:43:49","url":"https:\/\/www.default\/content\/early\/2013\/11\/22\/000752","comment":"
This is work of high value as it gets at the higher level interpretation (by the genome and its
expression apparatus) of genomic variation. I would add some caution with regard to the LDL result because of the high number of variants in the large LDL receptor gene that contribute to non-normal values of this commonly measured blood lipid, but that is minor overall.<\/p>
On the other hand, this approach seems to be worthwhile with much to be gained by its application. I would like to see a comparison between main effect associations and those modified by environmental factors (gene-environment interactions, GxEs) for a given trait. Do the results shift in any significant way? In other words, if X% of SNPs for a given trait influence protein sequence (or DHSs or miR interactions), does that percentage change when looking at GxEs for that same trait?<\/p>
@Larry_Parnell<\/p>"},{"date":"2013-11-25","doi":"10.1101\/000711","name":"Adam Roddy","time":"2013-11-25T16:15:19","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/19\/000711","comment":"
Thanks for your feedback. Yes, I agree that the main point of this manuscript is to point out that with these sensors we can gain better, more nuanced insight into leaf-level responses to the environment. I appreciate your feedback and will consider including some more discussion about the other ways people have tried to do this based on stem level sap flow measurements.<\/p>
Given that most analyses of sap flow hysteresis with light are based on stem-level sap flow measurements, I would say that most studies don't accurately characterize the light environment. Really, though, the issue depends on what scale you are interested in. If you want to be able to predict a basic transpiration response from stand-level light data, then what has been done before is probably pretty good. However, I don't think those previous studies can be used (yet) to understand leaf-level processes precisely because microenvironmental conditions of leaves vary so widely throughout the canopy. Just in this present study, we saw significant differences even between adjacent leaves with different orientations. Imagine how different sun- and shade-leaves may be.<\/p>
Thanks for your thoughtful feedback.<\/p>"},{"date":"2013-11-30","doi":"10.1101\/000687","name":"Gholson Lyon","time":"2013-11-30T00:15:08","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/18\/000687","comment":"
Ah, yes, it should say 6 billion nucleotide pairs, or otherwise ~12 billion nucleotide, as you rightly point out. Will correct in next version. Thanks!<\/p>"},{"date":"2013-12-01","doi":"10.1101\/000141","name":"Guest","time":"2013-12-01T20:44:51","url":"https:\/\/www.jnl-biorxiv01.drupal-qa-mobile-web01.highwire.org\/content\/early\/2013\/11\/07\/000141","comment":"
Awesome news! Congrats :)<\/p>"},{"date":"2013-12-05","doi":"10.1101\/000109","name":"Yaniv Brandvain","time":"2013-12-05T18:45:01","url":"https:\/\/www.biorxiv.highwire.org\/content\/early\/2013\/11\/07\/000109","comment":"
Thanks! we're submitting data soon! posting code sounds fun too at minimum I'll be sure to put the HMM code up<\/p>"},{"date":"2013-12-06","doi":"10.1101\/000448","name":"Dome","time":"2013-12-06T04:29:16","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/15\/000448","comment":"
Really enjoyed your paper! Noticed that in the \"Characterization of step response\" section you mistakenly refer to Figure 5B as Figure 5A and Figure 5C as Figure 5B.<\/p>"},{"date":"2013-12-11","doi":"10.1101\/001214","name":"jipkin","time":"2013-12-11T21:20:10","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/12\/10\/001214","comment":"
A couple thoughts as I'm reading:<\/p>
In 2.3.1, I'm curious about using 2us for the ballpark calculation, since I've seen datasets that have acceptable quality for synapse ID and segmentation with 0.5 us dwell times.<\/p>
For the discussion of development costs, it should be mentioned that the technology to reliably and uniformly stain large volumes of tissue (like the mouse brain) is still under development. Talk to Shawn Mikula from the Denk lab for more.<\/p>
It seems strange to speak about the capital costs of the microscopes as if these machines are going to be used once for the mouse brain and then put out to pasture. It may be worth mentioning that these machines have lifespans hopefully longer than 3 years and can therefore be used for other projects, increasing their value.<\/p>
Finally, while I understand the focus of this piece on the mouse connectome as an example (and the current Holy Grail in the field), this seems like the perfect venue for cross-species comparisons. Wouldn't it make a sweet table to see the costs for species like drosophila, larval zebrafish, leech ganglion, stomatogastic ganglion, larval ciona intestinalis, maybe even the human brain?<\/p>
Jason Pipkin
Kristan Lab
UCSD<\/p>"},{"date":"2013-12-12","doi":"10.1101\/001297","name":"Dennis Evangelista","time":"2013-12-12T14:30:41","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/12\/05\/001297","comment":"
This preprint has been accepted to PLoS ONE (PONE-D-13-23480R3) and will appear under doi 10.1371\/journal.pone.0085203 - I will update the bioRxiv info once I have the url and other final bibliographic information.<\/p>"},{"date":"2013-12-12","doi":"10.1101\/001214","name":"AdamMarblestone","time":"2013-12-12T17:18:38","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/12\/10\/001214","comment":"
Thanks for these excellent comments! Will be incorporated into the next version.<\/p>"},{"date":"2013-12-13","doi":"10.1101\/001214","name":"jipkin","time":"2013-12-13T16:46:23","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/12\/10\/001214","comment":"
Oh one more thing, in 2.1 Reliability and cost of sectioning, the 10k limit before damage for diamond knives feels very conservative. Maybe that's true for some knives but not others? I work with the folks at NCMIR and the knife in the Gatan ultramicrotome in their SBFSEM systems does 10k sections in a matter of a weeks and I know they don't replace it that often (you can also move the knife laterally to expose areas that haven't cut anything if the blockface is small enough). Perhaps I'm misreading the section and that part is meant only to apply to the sectioning needed to cut the larger volume into chunks.<\/p>"},{"date":"2013-12-17","doi":"10.1101\/001297","name":"Dennis Evangelista","time":"2013-12-17T22:15:50","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/12\/10\/001297","comment":"
This preprint has been accepted to PLoS ONE. I will post the updated doi and bibliographic information once I have them.<\/p>"},{"date":"2013-12-24","doi":"10.1101\/001248","name":"B. Schwessinger","time":"2013-12-24T21:36:22","url":"https:\/\/www.default\/content\/early\/2013\/12\/11\/001248","comment":"
In the introduction you are suggesting the following:
'If true, conservation of important effector-target interactions
may form another important means besides convergent evolution, by which targeting of
important host proteins by divergent pathogen effectors, is achieved.'
Do you mean that effector-target interactions might be evolutionary conserved between fungi, phytoplasma and oomycete.This seems rather unlikely given the evolutionary distance between these pathogens.<\/p>"},{"date":"2013-12-26","doi":"10.1101\/001552","name":"Davidski","time":"2013-12-26T08:18:47","url":"https:\/\/www.default\/content\/early\/2013\/12\/23\/001552","comment":"
Thanks for putting out this awesome paper here before formal publication.<\/p>
Now, I might be way off, but it seems to me that despite the patchy sampling across time and space of pre-Neolithic North Eurasians, the WHG, SHG and ANE groups seem to be the same ancestral population. In other words, they appear to be three meta-populations or regional variants of essentially the same Northwest Eurasian forager gene pool.<\/p>
That's probably why Motala12 can be fitted as a mixture between Loschbour and MA1. I suspect that ancient samples from pre-Neolithic Eastern Europe, particularly the Volga-Ural region, will come out like Motala12, but with the ancestry proportions from Loschbour and MA1 reversed (ie. they'll be much more MA1 than Loschbour).<\/p>
Following on from that, perhaps it's better to name the WHG as Western Hunter-Gatherer, as opposed to West European Hunter-Gatherer? Note that the WHG component today peaks among Lithuanians, who are located in the East Baltic region, and can't really be described as Western Europeans.<\/p>
In any case, I'm looking forward to more ancient genomes, particularly from Eastern Europe. Cheers<\/p>"},{"date":"2013-12-28","doi":"10.1101\/001552","name":"Matt","time":"2013-12-28T12:09:24","url":"https:\/\/www.default\/content\/early\/2013\/12\/23\/001552","comment":"
Question: Did you try and model the present day Near East and Caucasus populations, like Lezgins and Druze, as admixed only between the final Basal Eurasian population in the model and the ANE populations?<\/p>
I'm curious as to whether this model would work because in the supplementary material, these populations are modelled with Stuttgart and MA1 to ascertain admixture proportions of Near East and ANE populations. However Stuttgart has an ancestral contribution from the ANE-like West European Hunter Gatherer population that may have happened in Europe. Modelling populations in the present day Near East and Caucasus as combinations of ANE and Basal Eurasians seems intuitively like it could fit better with the PCA and graph results.<\/p>
thanks<\/p>"},{"date":"2013-12-30","doi":"10.1101\/001552","name":"Michael Wangler","time":"2013-12-30T02:51:02","url":"https:\/\/www.default\/content\/early\/2013\/12\/23\/001552","comment":"
Fantastic paper! Thanks for sharing this prior to publication. I wonder if you have analyzed genes involved in urea cycle, protein catabolism and carbohydrate metabolism? It seems the transition to agriculture could provide selective pressure on some variants in these loci and this might be observed comparing the hunter-gatherer individual to the early farmers.<\/p>"},{"date":"2013-12-30","doi":"10.1101\/000950","name":"B. Schwessinger","time":"2013-12-30T20:41:38","url":"https:\/\/www.default\/content\/early\/2013\/12\/25\/000950","comment":"
This pre-print version of this manuscript has been accepted for publication in Molecular Plant Sunday 12\/29\/2013.<\/p>"},{"date":"2013-12-30","doi":"10.1101\/001552","name":"Matt","time":"2013-12-30T23:32:09","url":"https:\/\/www.default\/content\/early\/2013\/12\/23\/001552","comment":"
Ken Nordvedt writes that further ydna I SNP testing has shown that so far no living descendants have been tested and these form a unique branch of the I haploid group.<\/p>
http:\/\/archiver.rootsweb.an...<\/a><\/p>"},{"date":"2013-12-31","doi":"10.1101\/000927","name":"Jacob G Scott","time":"2013-12-31T01:57:24","url":"https:\/\/www.biorxiv.org\/content\/early\/2013\/11\/25\/000927","comment":" some discussion here: http:\/\/mathematicaloncology...<\/a><\/p>"}]}