Proofreading while rewriting, structuring, or doing the thinking or creative parts of writing is a form of bikeshedding. It is easy to focus on the small and picayune fixes when writing, but this distracts from the more important parts of the work which really need one's attention to be successful.

Get your ideas down on paper and only afterwards work on proofreading at the end. Switching contexts from thinking and creativity to spelling, small bits of grammar, and typography can be taxing from the perspective of trying to multi-task.

Link: Draft #4 and using Webster's 1913 dictionary for choosing better words/verbiage as a discrete step within the rewrite.

Linked to above: Are there other dictionaries, thesauruses, books of quotations, or individual commonplace books, waste books that can serve as resources for finding better words, phrases, or phrasing when writing? Imagine searching through Thoreau's commonplace book for finding interesting turns of phrase. Naturally searching through one's own commonplace book is a great place to start, if you're saving those sorts of things, especially from fiction.

Link this to Robin Sloan's AI talk and using artificial intelligence and corpuses of literature to generate writing.

I chose this line and it peaked my interest because I bet there is a way to solve most cases of social death. First of all, spreading awareness to the subject will hopefully cause people to think more about their actions, such as withdrawing less from a dying family member.

https://phys.org/news/2016-06-social-death.html

How quickly does men's bone mass deteriorate? https://www.nia.nih.gov/health/osteoporosis

https://vimeo.com/232545219

from: Eyeo Conference 2017

• http://eyeofestival.com/2017/speaker/robin-sloan/
• https://vimeo.com/channels/eyeo2017/232545219

Description

Robin Sloan at Eyeo 2017 | Writing with the Machine | Language models built with recurrent neural networks are advancing the state of the art on what feels like a weekly basis; off-the-shelf code is capable of astonishing mimicry and composition. What happens, though, when we take those models off the command line and put them into an interactive writing environment? In this talk Robin presents demos of several tools, including one presented here for the first time. He discusses motivations and process, shares some technical tips, proposes a course for the future — and along the way, write at least one short story together with the audience: all of us, and the machine.

Notes

Robin created a corpus using If Magazine and Galaxy Magazine from the Internet Archive and used it as a writing tool. He talks about using a few other models for generating text.

Some of the idea here is reminiscent of the way John McPhee used the 1913 Webster Dictionary for finding words (or le mot juste) for his work, as tangentially suggested in Draft #4 in The New Yorker (2013-04-22)

Cross reference: https://hypothes.is/a/t2a9_pTQEeuNSDf16lq3qw and https://hypothes.is/a/vUG82pTOEeu6Z99lBsrRrg from https://jsomers.net/blog/dictionary

Croatian acapella singing: klapa https://www.youtube.com/watch?v=sciwtWcfdH4

Writing using the adjacent possible.

Corpus building as an art [~37:00]

Forgetting what one trained their model on and then seeing the unexpected come out of it. This is similar to Luhmann's use of the zettelkasten as a serendipitous writing partner.

Open questions

How might we use information theory to do this more easily?

What does a person or machine's "hand" look like in the long term with these tools?

Can we use corpus linguistics in reverse for this?

What sources would you use to train your model?

References:

• Andrej Karpathy. 2015. "The Unreasonable Effectiveness of Recurrent Neural Networks"
• Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al. "Generating sentences from a continuous space." 2015. arXiv: 1511.06349
• Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017. "A Hybrid Convolutional Variational Autoencoder for Text generation." arXiv:1702.02390
• Soroush Mehri, et al. 2017. "SampleRNN: An Unconditional End-to-End Neural Audio Generation Model." arXiv:1612.07837 applies neural networks to sound and sound production

Arg4: Les ressources minérales sont également très convoitées

• les utilisations technologiques minerais: Cobalt, cuivre, nickel, or, diamant terres rares: cérium, scandium Nodules polymétalliques = hautes technologies (tel, odrinateurs)

• jeu géopolitique dps 2010's fouilles Etat // monopole chinois Chine = 90% terres rares M

Arg 4: Les choke points et les EM sont menacés Pirtarie maritime 2018: 201 attaques // navires marchands 4000 attaques depuis 20 ans selon l'IRIS 330M $ de rançons en 7 ans = financement activités criminelles Golfe de Guinée Golfe d'Aden Asie du Sud (Bangladesh) Asie du Sud Est (Détroit de Malacca) Amérique du Sud (Bolivie et Venezuela) = 2 régions les + touchés => next to routes maritimes

简单的说

有可能, 后面接一个宾语从句

Opinions are partially correct they are actually: Opinion of the court: Brennan Concurring: Kenny Dissenting: Rehnquist, Stevens

Decision was not 7-2... it was 5-4, ruling that that the Ohio school-voucher program did not violate the establishment clause of the First Amendment

No

Incorrect- it is a Texas law in question / violation

He had a concurring opinion

Establishment clause

incorrect - it was the state that set up the program (according to text book), not the district

parents were the one's who got to choose among the options

Wouldn't that be unconstitutional? To not abide to the laws enacting by congress? Isn't it up to the Judiciary to interpret the acknowledged powers?

incorrect: not necessarily union but "Can the President constitutionally authorize the Secretary of Commerce to take possession and operate steel mills?"

For.

During the transatlantic slave trade, Europeans essentially enlisted the “help” of Africans to assist enslavement of their own peoples. They did this by giving small rewards of weapons, luxury goods, and winning wars against neighboring tribes. During initial explorations, “free” slaves guided the colonizers through the land and water. For any of this to occur, it was a plotted strategy using persuasion and even coercion. With the births of “mulattos” (children of Europeans and Africans), were bought back to Africa and infiltrated to continue the enslavement of African people. This was the beginning of the mental programming and trauma that has been engrained in the beings of POC and passed down for generations.

Não existem mais animais assim, apesar de com essas dobras produzir mais lã a tosquia desses animais é muito mais complicada o que gastava mais tempo, animais mais susceptíveis a parasitas, produziam mais suardas (sujeira) o que dava mais prejuízo, lã mais irregular.

DOI: 10.1016/j.devcel.2021.09.005

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What is this?

DOI: 10.1016/j.cub.2021.08.049

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What is this?

Community-based research

i think he realizes that to speak a language doesnt only mean you have to know basic words. you have to undersatnd the flow of it the reasoning behind it. just becasue it sounds insulting doesnt mean that it is.

does she mean im sick of you not understanding what i mean but understand what i say ?

he is starting to realize maybe her words that are insulting dont mean what they sound like. in order to speak a language you have to know not everything means what is sounds like .

atleast he isnt alone . seems like there is noone competing against eachother the teacher basically has it out for everyone

trying really hard to make himself stand out. spending alot of time on his work maybe going above and beyond. its all for nothing though teacher doesn't seem amused

DOI: 10.1016/j.devcel.2021.07.021

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What is this?

DOI: 10.1016/j.devcel.2021.07.021

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What is this?

DOI: 10.1016/j.devcel.2021.07.021

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What is this?

DOI: 10.7554/eLife.66078

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What is this?

Reviewer #4 (Public Review):

This research fills a valuable gap in our understanding of neural cell populations. There is immense complexity in the neuron subtype landscape of the dorsal root gangion (DRG). Profiling had been previously conducted in mouse, but not within human. Providing the data and analysis of the human DRG is a valuable resource because substantial differences in cell populations and expression programs can exist between mouse and human. Any research that is focussed on the translational potential of a gene or pathway should verity its conservation across species.

However, additional evidence is required to support a major claim of the manuscript: that there are mouse-specific and human-specific neuron subtypes. This claim is based on two major pieces of evidence. First, cluster comparison and co-clustering identify some cell populations that are species specific. Although this approach is suggestive, it is not definitive. Clustering separates populations of cells based major axes of variability, but those axes may not perfectly align across conditions or species. For example, excitatory cortical neurons may vary based upon cortical layer or whether they originate from the primary or secondary visual cortex. It is possible that one source of variation is stronger in one species and another source of variation is stronger in another species, leading to differences in clustering. The co-clustering may overcome of those limitations, but if the differences across species and experimental parameters are large enough, then even cells that come from the same population may not align. The in situ hybridization experiments also provide some support for species specificity, but it the overlap of specific markers could be confounded when the expression of individual marker genes evolve while the overall cell population remains consistent.

DOI: 10.1523/JNEUROSCI.0983-19.2021

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What is this?

DOI: 10.7554/eLife.47061

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What is this?

DOI: 10.1016/j.neuron.2018.06.035

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What is this?

DOI: 10.7554/eLife.25727

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What is this?

DOI: 10.1242/dev.105718

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What is this?

DOI: 10.1016/j.stemcr.2015.02.006

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What is this?

DOI: 10.1083/jcb.201503115

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What is this?

I forget that data and visualization show up in entertainment as well. It is like this section says, you have to look outside of spreadsheets and text files to see that photos and status updates could also qualify. This just reminds me that data can be used in so many different ways and not just the more common ones you may think of off the top of your head. People like their entertainment so Facebook and OkCupid were most likely successful in using their data in that way.

This is very true that it is easy to spout averages and numbers while lumping another human being in as a statistic. I agree that the numbers do represent individuals so the data should be approached that way too. If we start talking about the people being directly affected by it instead of just going by numbers and data points more people would probably relate to it and learn more about it. This link https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410028703 shows both the percentage and the actual number of people affected. This way we can see that the percentage does not seem all that big but the actual number of people affected is thousands.

I like the way that this was worded. I always thought of data as just numbers that you plug in and learn things from but that was all it was to me. The fact that it can be as complex or as simple as you want or as long or as short as you want means that each piece of data is unique to the person who created it. This has reminded me of the class and all of our final projects. We may be using some of the same software or tools to make our projects or we may even have a similar topic to someone else but each one is still going to turn out different. We will use the software and tools in our own way to represent the point we are making. This is something I have found throughout the whole course which is that even though each piece of digital humanities seems like there would only be one way to do it like data sets, there are actually so many interpretations and ways you can go with it.

DOI: 10.7554/eLife.66596

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What is this?

DOI: 10.7554/eLife.54894

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What is this?

From OS 7.3

We should actually define spillover somewhere

DOI: 10.1016/j.cub.2021.05.042

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What is this?

DOI: 10.1016/j.celrep.2021.109255

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What is this?

DOI: 10.7554/eLife.62155

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What is this?

Prestige Group Sector 150 in Noida is the latest project of a well-known real estate builder i.e Prestige group’s pioneer to yield one of the best residential property in Noida including 2/3/4 BHK luxury & lavish apartments with great amenities. There are lots of residential facilities such as Vaastu compliant design, double-height entrance lobby, Tower heights- G+19 & G+22, and facing green landscape. etc. Apart from that, you can also get state-of-the-art facilities such as a green area, swimming pool, clubhouse, children play area, power backup, etc.

Having identified the cases in which action is not voluntary, Ar. finishes this chapter by telling us what voluntary action is: it is those actions which are initially caused by us (find their origin in us) and in which we are aware of the particulars of the situation. He also argues that even actions caused by non-rational desires are in a sense voluntary.

1111a22-1111b3 So, given that counter voluntary...to count these things as counter-voluntary.

DOI: 10.1016/j.devcel.2020.07.015

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What is this?

DOI: 10.1016/j.devcel.2020.07.015

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What is this?

DOI: 10.1016/j.cub.2020.06.086

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What is this?

confirmation de l'hypothèse selon laquelle la désinformation doit aussi être étudiée sous l'angle de la perception de l'information selon les contextes de vie sociale. Cependant l'échantillon est faible, la généralisation est donc moins évidente.

second argument en faveur de l'idée selon laquelle la désinformation n'est pas seulement le fruit d'une diffusion massive de la fake news.

premier argument démontrant qu'une diffusion qui peut paraitre massive n'est pas nécessairement le signe d'une désinformation effective.

Reviewer #4 (Public Review):

In this paper, the author uses an impressive comparative dataset of 172 species to investigate the relationship between intraspecific genetic diversity and census (actual) population size. They find that even when they use phylogenetic comparative methods, the relationship between neutral diversity and population size is much weaker than predicted by theory and that selection on linked sites is unlikely to explain this difference. The paper convincingly demonstrates that the paradox of variation first pointed out by Lewinton in the 70s remains paradoxical.

This paper is exceptionally strong in multiple ways. First, it is statistically rigorous; this is particularly impressive given that the paper uses methods and data from multiple fields (genomics, macroecology, conservation biology, macroevolution). This is the most robust estimate of the relationship between diversity and population size that has been published to date. Second, it is conceptually rigorous: the paper clearly lays out the various hypotheses that have been put forth over the years for this pattern as well as the logic behind these. The author has done a great job at synthesizing some complex debates and different types of data that are potentially relevant to resolving it. Third, it is exceptionally well-written. I sincerely enjoyed reading it. Overall, I think this is a major contribution to this field and though the paper does not resolve the challenge laid down by Lewinton, I think these analyses (and curated data/computational scripts) will inspire other researchers to dig into this question.

I do however, have some suggestions as to how this paper could be strengthened.

First, in phylogenetic comparative methods (PCMs) there has been a persistent confusion as to what phylogenetic signal is relevant -- when applying a phylogenetic generalized linear model with a phylogenetically structured residual structure (which the author does here), one is estimating the phylogenetic structure in the errors and not the traits themselves. The comparative analysis are well-done and properly interpreted but at some points in the text, particularly when addressing Lynch's conjecture that PCMs are irrelevant for coalescent times and comments/analysis on the appropriateness of Brownian motion as a model of evolution, that there is some conceptual slippage and I suggest that author take a close look and make sure their language is consistent. Strictly speaking the PGLM approach doesn't assume that the underlying traits are purely BM -- only that the phylogenetic component of the error model is Brownian. As such running the node-height test on the both the predictors and the response variable separately -- while interesting and informative about the phylogenetic patterns in the data (including the shift points you have observed) isn't really a test of the assumptions of the phylogenetic regression model. It is at least theoretically plausible (if not biologically) that both Y and X have phylogenetic structure but that the estimated lambda = 0 (if for instance, Y and X were perfectly correlated because changes in Y were only the result of changes in X). To be clear, I am fine with the PGLM analysis you've done and with the node-height test; I just don't think that the latter justifies the former.

One note about the ancestral character reconstruction: I think it is a fine visualization and realize you didn't put too much emphasis on it but strictly speaking the ASR's were done under a constant process model and therefore they wouldn't provide evidence for (a probably very real shift) between phyla. I think it was a good idea to run the analyses on the clade specific trees (particularly given how deep and uncertain the branches dividing the phyla are) but I just don't think you could have gotten there from the ASR.

I am not convinced that the IUCN RedList analysis helps that much here and in my view, you might consider dropping this from the main text. This is for two reasons: 1) species may be of conservation concern both because they have low abundance in general and/or that their abundance is known to have experienced a recent decline -- distinguishing these two scenarios is impossible to do with the data at hand; and 2) there is of course a huge taxonomic bias in which species are considered; I don't think we can infer anything ecologically relevant from whether a species is listed on the RedList or not (as you suggest regarding the lynx, wolverine, and Massasauga rattlesnake) except that people care about it.

This is not really a weakness but I find it notable that recombination map length is correlated with body size. I realize this is old news but I was left really curious as to a) why such a relationship exists; and b) whether the mechanism that generates this might help explain some of the patterns you've observed. I would be keen to read a bit more discussion on this point.

The tone wasn't awkward and felt more like someone talking than the other poems. They used repetition well.

This one was one of the few that had a more dramatic and entertaining telling of what it's like to live in the strange world of the pandemic. I think this one is my favorite.

Reviewer #4 (Public Review):

The authors analysed flavinylation across different species. They analysed impressive number of 31.910 prokaryotic genomes. They mined flavinylation associated gene clusters using a bioinformatic approach. They define five different protein classes responsible for transmembrane electron transfer. Moreover, they predicted and validated flavinylation of two domains with unknown functions (by ApbE). Unfortunately, the vast majority of predictions made in this study were not experimentally validated. It is therefore very difficult to judge the reliability of predictions, proposals and claims made in the manuscript.

Wenn die Temperaturen bis 2100 um 4 Grad steigen, werden ca. 40% des antarktischen Schelfeises mit hoher Wahrscheinlichkeit kollabieren.

DOI: 10.7554/eLife.59687

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What is this?

Reviewer #4 (Public Review):

Higashi et al. provide a new "Brownian ratchet" model for DNA loop extrusion mechanism by cohesin, a member of SMC protein family complexes. Based on previous works on crystal structures, cryo-EM structures, and DNA-protein crosslinking experiments, they shed light on two HEAT-repeat DNA binding modules on cohesin - Scc2-head and Scc3-hinge - and their relationships. They hypothesized that the association between Scc2-head and Scc3-hinge modules were dissociated and Scc2-head released DNA upon ATP hydrolysis, driving DNA slipping. By performing FRET experiments, they found that Scc2 and hinge modules indeed come close only in ATP-bound "Gripping" state, while hinge and Scc3 are always close to each other. Therefore, they suggest that, for DNA loop extrusion model, 1) upon ATP binding to the head domains, both Scc2-head and Scc3-hinge modules grip DNA, 2) when ATPs are hydrolyzed, Scc2-head module releases DNA so that DNA-associating Scc3-hinge module pulls DNA depending on stochastic Brownian motion of Scc3-hinge module, then 3) both Scc2-head and Scc3-hinge modules release DNA and go back to the state 1). This "Brownian ratchet" model also provides an explanation of how cohesin entraps DNA by opening the gate between Smc3 and Scc1, which also nicely explains the known facts regarding Scc1 cleavage-dependent DNA release and in vitro behaviors of single cohesin molecules that topologically bound to DNA. In addition, by performing computational modeling, they showed that the Brownian ratchet model well fits all previously reported in vitro loop extrusion assays by cohesin and condensin, making their model rigid and reliable.

Their model is mostly well supported by data, but several detailed points need to be explained or clarified.

1) In Figure 2C FRET experiments, proximity of Scc3-C and Scc2-N does not seem to be drastically increased in Gripping state compared to the case of hinge and Scc2-N. This could be because the FRET pairs (Scc3-C and Scc2-N) are still far. If the authors could label internal part in Scc3, this could solve the problem. In addition, if Scc3-C and Scc2-N are always close to each other irrespective of Gripping state, the authors should consider this fact in their modeling.

2) Major differences between topological loading and loop extrusion is kleisin-gate opening and head gate passage. Even if kleisin-gate wouldn't be opened, DNA should be released after head opening like in the topological loading. In case it happens, DNA and Scc1 would be tangled and it seems to be difficult to come back to next gripping state again. It would be helpful to add the explanation of why such tangling DNAs do not have to be considered in the model.

3) In the manuscript line 338, the authors mention "After DNA dissociation from the Scc3-hinge module, there is a time without tight contact between the cohesin ring and the DNA loop." However, both in Figure 3B and 4F, it seems that head-Scc2 always associates with DNA. This could be discrepancy. The authors should clarify the point if certain free time without any contact to DNA is assumed in the modeling.

4) Generally, initial DNA bending is the most challenging part in loop extrusion models. Especially in Figure 3B-a, such a bent DNA seems to be impossible if we consider the persistence length of DNA is 50 nm. The authors should discuss how DNA loop extrusion could be initiated.

Where it started

Reviewer #4 (Public Review):

This article describes the results of an impressive meta-analysis based on a high number of published effects investigating the relationship between sexual dimorphism in men and their mating and reproductive success.

The article is very well written and covers a vast amount of literature.

Most of my comments are not corrections, but rather subjective ideas on how the text could be restructured. In my opinion, the article is clearly written and the rationale behind research questions and methodology is well explained. I appreciate how the authors present the entire analysis, adding multiple robustness tests and presenting their results in an easy to follow manner (which was not easy, due to the complexity of the methodology implemented).

I cannot criticise any major issues in this manuscript.

The main outcomes of the article not only present a robust test of previously mixed results, but also provide a strong recommendation of how future studies should be conducted (i.e. how to use mating success proxies, and what samples to include).

Reviewer #4 (Public Review):

The goal of the manuscript was to add to the research on the rates of success of African American/Black PI in their pursuit of NIH funding. The authors specifically addressed variability in funding levels of NIH Institutes and Centers(ICs). The authors were successful in identifying that there are differentials rates of award rates by IC. The authors describe that topic choice was not associated with funding after accounting for IC assignment which vary in their funding rates.

Reviewer #4 (Public Review):

Using a transgenic line of Platynereis, in which GFP is expressed under the control of cis-regulatory elements for r-opsin, the study isolates r-opsin expressing cells from the head (eye photoreceptors) and trunk region (a population of segmentally repeated r-opsin expressing cells associated with the parapodia) by FACS. Subsequent RNA-Seq establishes that both populations of cells express genes for all components of the rhabdomeric phototransduction cascade, while the population of trunk sensory cells additionally expresses genes encoding proteins involved in mechanosensation. Using heterologous expression in a mammalian cell line, it is shown that the Platynereis r-opsin responds to blue light via coupling to Gαq suggesting that it mediates photoresponses via a canonical rhabdomeric phototransduction cascade. Transcriptomic analysis of an r-opsin mutant created by TALEN mediated gene editing then reveals that expression levels of the mechanosensory Atp2b channel are modulated by protracted exposure to blue light, a response abolished in the mutant. Behavioral analysis further suggests that undulatory movements of the worms are equally altered under these illumination conditions. Taken together this suggests that the r-opsin expressing trunk sensory cells act as both photo- and mechanoreceptors and that their mechanosensory properties are modulated in response to light. In combining the transcriptomic analysis of cell types with experimental studies of gene function and behavioral analyses, this study provides exciting new insights into the evolution of sensory cells. Several prior studies have found co-expression of photosensory and mechanosensory proteins in sensory cells of various bilaterians, and comparative studies suggested that photo- and mechanosensory cells may share a common evolutionary origin. However, the current study goes far beyond these findings in establishing a direct functional link between photo-and mechanosensation in a population of sensory cells suggesting that these sensory cells function as multimodal cells and that their mechanosensory properties are altered in response to light. Furthermore, the behavioral data (based on a novel machine-learning based tool of analysing the animals' movement) suggest that these cells have a behaviorally relevant function. Because r-opsin was found to be expressed in mechanoreceptors not only in lophotrochozoans (including Platynereis) but also in ecdysozoans and vertebrates (although functional studies are lacking here) and r-opsins belong to a large family of opsins, almost all of which are responsive to light, the present study suggests that r-opsins may have an ancestral bilaterian role in modulating mechanosensory function in response to light (in addition to their purely photosensory role in the photoreceptors of the eyes). Light-independent functions of r-opsin as recently revealed in Drosophila may, thus, be secondarily derived.

The study is very carefully conducted and well presented. The only minor flaw is that in its present form, the discussion of the evolutionary implications of the finding lacks in clarity and specificity. The authors here often refer ambiguously to an "ancient" or "ancestral" role of r-opsins without specifying the lineage referred to (ancestral for lophotrochozoans? bilaterians? eumetazoans? metazoans?). The discussion should, therefore be revised with an explicit phylogenetic framework in mind.

AssayResult: 0.01 µM: 100; 0.1 µM: 65; 0.8 µM: 18; 1 µM: 15

AssayResultAssertion: Abnormal

Approximation: Exact cisplatin concentrations and assay result values not reported; values estimated from Figures 4b and 4d.

AssayResult: 0.01 µM: 80; 0.1 µM: 52; 0.8 µM: 18; 1 µM: 5

AssayResultAssertion: Abnormal

Approximation: Exact cisplatin concentrations and assay result values not reported; values estimated from Figures 4b and 4d.

AssayResult: 0.01 µM: 102; 0.1 µM: 65; 0.8 µM: 18; 1 µM: 10

AssayResultAssertion: Abnormal

Approximation: Exact cisplatin concentrations and assay result values not reported; values estimated from Figures 4b and 4d.

AssayResult: 0.01 µM: 85; 0.1 µM: 40; 0.8 µM: 20; 1 µM: 13

AssayResultAssertion: Abnormal

Approximation: Exact cisplatin concentrations and assay result values not reported; values estimated from Figures 4b and 4d.

AssayResult: 0.01 µM: 90; 0.1 µM: 60; 0.8 µM: 15; 1 µM: 15

AssayResultAssertion: Abnormal

Approximation: Exact cisplatin concentrations and assay result values not reported; values estimated from Figures 4b and 4d.

AssayResult: 0.01 µM: 65; 0.08 µM: 50; 0.8 µM: 30; 8 µM: 20

AssayResultAssertion: Abnormal

Approximation: Exact Olaparib concentrations and assay result values not reported; values estimated from Figures 4a and 4c.

AssayResult: 0.01 µM: 102; 0.1 µM: 85; 0.8 µM: 55; 1 µM: 25

AssayResultAssertion: Normal

ControlType: Normal; wild type PALB2 cDNA

Approximation: Exact cisplatin concentrations and assay result values not reported; values estimated from Figures 4b and 4d.

AssayGeneralClass: BAO:0003009 cell viability assay

AssayMaterialUsed: CLO:0036938 tumor-derived cell line

AssayDescription: Transient expression of wild type and variant mCherry-tagged PALB2 cDNA constructs in Trp53 and Palb2-null mouse cell line; exposure to increasing concentrations of cisplatin for 5 days induces interstrand-crosslink DNA damage; cell survival is determined by measuring fluorescence intensity after staining with a cell viability reagent.

AssayReadOutDescription: Percent cell survival after treatment with cisplatin

AssayRange: %

AssayNormalRange: Cisplatin resistance levels comparable to that of cells expressing wild type PALB2; no numeric threshold given

AssayAbnormalRange: Not reported

AssayIndeterminateRange: Not reported

ValidationControlPathogenic: 0

ValidationControlBenign: 0

Replication: Not reported

StatisticalAnalysisDescription: Not reported

AssayResult: 1

AssayResultAssertion: Abnormal

Approximation: Exact assay result value not reported; value estimated from Figure 3e.

AssayResult: 0.8

AssayResultAssertion: Abnormal

StandardErrorMean: 0.14

HGVS: NM_024675.3:c.104T>C p.(Leu35Pro)

AssayResult: 81

AssayResultAssertion: Not reported

PValue: Not reported

Approximation: Exact assay result value not reported; value estimated from Figure 6C.

AssayResult: 8

AssayResultAssertion: Indeterminate

PValue: Not reported

AssayResult: 76.21

AssayResultAssertion: Indeterminate

PValue: 0.0001

Comment: Exact values reported in Table S3.

HGVS: NM_024675.3:c.136C>T p.(His46Tyr)

AssayResult: 19.52 foci/cell

AssayResultAssertion: Indeterminate (described as "minor effect")

Range: 0 - 70

Comment: Exact values reported in "Source Data" file

AssayResult: 15.80 foci/cell

AssayResultAssertion: Indeterminate (described as "minor effect")

Range: 0 - 74

Comment: Exact values reported in "Source Data" file

AssayResult: 13.96 foci/cell

AssayResultAssertion: Abnormal

Range: 0 - 69

Comment: Exact values reported in "Source Data" file

AssayResult: 3.19 foci/cell

AssayResultAssertion: abnormal

Range: 0 - 32

Comment: Exact values reported in "Source Data" file

AssayResult: 1.24 foci/cell

AssayResultAssertion: Abnormal

Range: 0 - 25

Comment: Exact values reported in "Source Data" file

AssayResult: 24.90 foci/cell

AssayResultAssertion: Normal

Range: 1 - 90

ControlType: Normal; wild type PALB2 cDNA

Comment: Exact values reported in "Source Data" file

AssayGeneralClass: BAO:0000450 fluorescence microscopy

AssayMaterialUsed: CLO:0003684 HeLa cell

AssayDescription: Transient expression of wild type and variant PALB2 cDNA constructs in HeLa cells following PALB2 siRNA knockdown; exposure ionizing radiation induces DNA damage; RAD51 foci formation is measured by immunofluorescence microscopy 4 h after irradiation

AssayReadOutDescription: Number of RAD51 foci per S-phase cell (determined by cyclin A detection)

AssayRange: foci/cell

AssayNormalRange: RAD51 foci numbers comparable to that of cells expressing wild type PALB2; no numeric threshold given

AssayAbnormalRange: RAD51 foci numbers comparable to that of cells expressing empty vector; no numeric threshold given

AssayIndeterminateRange: Not reported

ValidationControlPathogenic: 0

ValidationControlBenign: 0

Replication: 3 independent experiments

StatisticalAnalysisDescription: Not reported

AssayResult: 83.16

AssayResultAssertion: Not reported

ReplicateCount: 2

StandardErrorMean: 0.2

Comment: Exact values reported in “Source Data” file.

AssayResult: 67.82

AssayResultAssertion: Not reported

ReplicateCount: 2

StandardErrorMean: 10.97

Comment: Exact values reported in “Source Data” file.

AssayResult: 44.9

AssayResultAssertion: Not reported

ReplicateCount: 2

StandardDeviation: 9.75

StandardErrorMean: 6.89

Comment: Exact values reported in “Source Data” file.

HGVS: NM_024675.3:c.110G>A p.(R37H)

AssayResult: 0.1

AssayResultAssertion: Abnormal

ReplicateCount: 19

StandardErrorMean: 0.1

Comment: This variant had loss of function of peak current (<10% of wildtype), therefore it was considered abnormal (in vitro features consistent with Brugada Syndrome Type 1. (Personal communication: A. Glazer)

HGVS: NM_198056.2:c.1058C>T p.(Thr353Ile)

AssayGeneralClass: BAOCL:20:0010044 targeted transcriptional assay

AssayMaterialUsed: CL:2000001 peripheral blood mononuclear cell from patients

AssayDescription: Comparative transcriptomic analysis using reverse transcription to compare peripheral blood mononuclear cells of patients with wild type or pathogenic TP53 variants in the context of genotoxic stress induced by doxorubicin treatment. p53 RNA levels were evaluated and expressed as a percentage of the mean levels obtained for the three wild-type TP53 individuals.

AdditionalDocument: PMID: 23172776

AssayReadOutDescription: The p53 mRNA levels were expressed as a ratio of the normal values obtained for 3 TP53 wild-type control individuals.

AssayRange: UO:0000187 the p53 RNA levels were evaluated and expressed as a percentage of the mean levels obtained for three wild-type TP53 individuals.

AssayNormalRange: >65%

AssayAbnormalRange: <65%

AssayIndeterminateRange: N/A

AssayNormalControl: wild type TP53

AssayAbnormalControl: LFS patient cells

ValidationControlPathogenic: 8 individuals had seven distinct TP53 variants which could be considered as likely pathogenic or pathogenic based on their ClinVar classification or their truncating nature.

ValidationControlBenign: 51 individuals had no detectable germline TP53 variant

Replication: at least two wells were seeded per patient (treated and untreated) and duplicates or triplicates were performed whenever possible.

StatisticalAnalysisDescription: Differentially expressed genes between doxorubicin-treated and untreated cells were arbitrarily defined using, as filters, a P<0.01 and fold-change cutoffs >2 or <2, for up and down regulation, respectively. The resultant signal information was analyzed using one-way analysis of variance (ANOVA, P= 0.001), assuming normality but not equal variances with a Benjamani–Hochberg correction for multiple comparisons using three groups: controls, null, and missense mutations.

SignificanceThreshold: P=0.001

Comment: statistical analysis and P value from previous publication.

Reviewer #4 (Public Review):

Coombs et al. aimed to establish a pharmacological tool to distinguish calcium-permeable (CP) AMPA receptors (AMPAR) from calcium impermeable AMPA receptors unambiguously. Towards this end, the authors examined the effects of intracellularly applied NASPM, PhTx-433, PhTx-74, and spermine. The authors showed that NASPM completely blocked outward glutamate-evoked currents with a desensitization blocker, cyclothiazide, from outside-out patch membranes from HEK cells expressing GluA1. In contrast, spermine and PhTx-433/74 partially blocked the outward currents in a voltage-dependent manner (Figure 1). TARPg-2 co-expression reduced potencies of spermine and NASPM, and altered shapes of their conductance-voltage relationship (Figure 2) as well as various kinetics of GluA1, including decay kinetics and recovery kinetics (Figure 3). Further, the authors showed that NASPM blocked GluA1 co-expressed with one of the AMPAR auxiliary subunits, TARPg-2, g-7, CNIH2 GSG1L (Figure 4). Finally, the authors showed that NASPM blocked AMPAR-mediated mEPSC events at +60 mV, but not -70mV, in cultured cerebellar stellate neurons from GluA2 knockout mice. Overall, this manuscript provides high-quality data and critical information about TARPg-2, GluA1, and GluA2 knockout mice.

This provides a solid analysis of GluA1, TARPg-2, 7, CNIH2, GSG1L, and GluA2 knockout neurons. However, it remains unclear whether intracellular NASPM allows an unambiguous functional measure of CP-AMPAR, especially considering many combinations of AMPARs and auxiliary subunits, e.g., GluA1-4 with splicing isoforms, six TARPs, four CNIHs, GSG1L and CKAMP44, etc.

Strengths:

The experimental design to evaluate drugs and receptors with outside-out patch membranes and a piezoelectric device provides the highest-resolution analysis and meaningful information.

Both experiments and analyses are rigorous and of high quality. However, it remains unclear if intracellular NASPM allows an unambiguous functional measure of CP-AMPAR.

Weaknesses:

Because the authors tested a limited combination of receptors and auxiliary subunits, it is difficult to conclude whether NASPM blocks all CP-AMPAR unambiguously.

Slopes of the conductance-voltage relationships are changed upon TARPg-2 co-expression or different concentrations of NASPM.

Speranza, T., Abrevaya, S., & Ramenzoni, V. C. (2021). Body Image During Quarantine; Generational Effects of Social Media Pressure on Body Appearance Perception. PsyArXiv. https://doi.org/10.31234/osf.io/y826u

ReconfigBehSci. (2021, February 26). RT @PsyArXivBot: Body Image During Quarantine; Generational Effects of Social Media Pressure on Body Appearance Perception https://t.co/Y6… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1366708215900176385

DOI: 10.7554/eLife.63595

Resource: (ZFIN Cat# ZDB-ALT-190104-4,RRID:ZFIN_ZDB-ALT-190104-4)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-190104-4

What is this?

Reviewer #4 (Public Review):

This paper describes the transmission of Trypanosoma brucei by the Tsetse vector. As part of these studies, the authors discovered that (i) a single parasite is sufficient for transmission and (ii) two stages of the Trypanosoma brucei life cycle (slender and stumpy forms) can be efficiently transmitted by the Tsetse vector. This was unexpected (as mentioned in the title) because only stumpy forms were known to be adapted for transmission.

The life cycles of parasites are text-book knowledge that researchers rely on and rarely question. It's the slide #2 of every talk in parasitology. In the mammalian host, the life cycle of Trypanosoma brucei comprises two stages: the dividing slender forms and the cell-cycle arrested stumpy-forms, which are pre-adapted to survive in the midgut of the next host (Tsetse fly). In this report, Schuster, Subota et al. show that slender forms are sufficient to establish an infection in the Tsetse fly and thus ensure transmission. The claims and conclusions are justified by the data presented.

Channel 4 News. (2021, January 17). “It’s working in mainland China with 1.4 billion people. It doesn’t depend on being an island.” A pandemic adviser to the New Zealand government says achieving zero cases isn’t about the size of a country, but about “strong leadership”. Https://t.co/SSpc8DjZXi [Tweet]. @Channel4News. https://twitter.com/Channel4News/status/1350834342709358593

DOI: 10.7554/eLife.54491

Resource: (ZFIN Cat# ZDB-ALT-170927-4,RRID:ZFIN_ZDB-ALT-170927-4)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-170927-4

What is this?

DOI: 10.1038/s41598-020-78398-9

Resource: (IMSR Cat# OBS_4,RRID:IMSR_OBS:4)

Curator: @scibot

SciCrunch record: RRID:IMSR_OBS:4

What is this?

DOI: 10.7554/eLife.42881

Resource: (ZFIN Cat# ZDB-ALT-060821-4,RRID:ZFIN_ZDB-ALT-060821-4)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-060821-4

What is this?

AssayResult: 111

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 69, 73

AssayResultAssertion: Normal

Comment: See Table S3 for details; The blood sample used to test this variant was derived from an individual carrying the variant in homozygosity.

AssayResult: 100

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 95

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 80, 99

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 94

AssayResultAssertion: Normal

Comment: See Table S3 for details; This variant was reported as c.323_235del but assumed to be c.323_325del, which corresponds to the reported protein change (p.(Gly108_Phe109delinsVal)).

AssayResult: 101, 106

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 89, 90

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 88

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 79

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 78

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 90

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 86

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 78

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 83

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 82

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 86

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 118

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 62

AssayResultAssertion: Abnormal

Comment: See Table S3 for details

AssayResult: 56, 52

AssayResultAssertion: Abnormal

Comment: See Table S3 for details

AssayResult: 61

AssayResultAssertion: Abnormal

Comment: See Table S3 for details

AssayResult: 101

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 98

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 102

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 81

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 96

AssayResultAssertion: Normal

Comment: See Table S3 for details

AssayResult: 102

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 105

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 85

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 88

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 95

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 99

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 125

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 115

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 84

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 75

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 88

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 79

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 84

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 91

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 86

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details

AssayResult: 102

AssayResultAssertion: Normal

ControlType: Normal, wild type TP53

Comment: See Table S3 for details