Reviewer #4 (Public Review):

Summary:

In their revised manuscript "Conformational dynamics of a nicotinic receptor neurotransmitter binding site," Singh and colleagues present molecular docking and dynamics simulations to explore the initial conformational changes associated with agonist binding in the muscle nicotinic acetylcholine receptor, in context with the extensive experimental literature on this system. Their central findings are of a consistently preferred pose for agonists upon initial association with a resting channel, followed by a dramatic rotation of the ligand and contraction of a critical loop over the binding site. Principal component analysis also suggests the formation of an intermediate complex, not yet captured in structural studies. Binding free energy estimates are consistent with the evolution of a higher-affinity complex following agonist binding, with a ligand efficiency notably similar to experimental values. Snapshot comparisons provide a structural rationale for these changes on the basis of pocket volume, hydration, and rearrangement of key residues at the subunit interface.

Strengths:

Docking results are clearly presented and remarkably consistent. Simulations are produced in triplicate with each of four different agonists, providing an informative basis for internal validation. They identify an intriguing transition in ligand pose, not well documented in experimental structures, and potentially applicable to mechanistic or even pharmacological modeling of this and related receptor systems. The paper seems a notable example of integrating quantitative structure-function analysis with systematic computational modeling and simulations, likely applicable to the wider journal audience.

Weaknesses:

The response to the initial review is somewhat disappointing, declining in some places to implement suggested clarifications, and propagating apparent errors in at least one table (Fig 2-source data 1). Some legends (e.g. Fig 2-supplement 4, Fig 3, Fig 4) and figure shadings (e.g. Fig 2-supplement 2, Fig 6-supplement 2) remain unclear. Apparent convergence of agonist-docked simulations towards a desensitized state (l 184) is difficult to interpret in absence of comparative values with other states, systems, etc. In more general concerns, aside from the limited timescales (200 ns) that do not capture global rearrangements, it is not obvious that landscapes constructed on two principal components to identify endpoint and intermediate states (Fig 3) are highly robust or reproducible, nor whether they relate consistently to experimental structures.

Reviewer #3 (Public review):

Summary:

This study investigated motor system adaptation to new environments through modifications in redundant body movements. Utilizing a novel bimanual stick-manipulation task, participants controlled a virtual stick to reach targets, focusing on how tip-movement direction perturbations affected tip movement and stick-tilt adaptation. The findings revealed a consistent strategy among participants who flexibly adjusted the tilt angle of the stick in response to errors. The adaptation patterns were influenced by physical space relationships, which guided the motor system's selection of movement patterns. This study underscores the motor system's adaptability through changes in redundant body movement patterns.

Strengths:

This study introduces an innovative bimanual stick manipulation task to explore motor system adaptation to novel environments through alterations in redundant body movement patterns. It also expands the use of endpoint robots in motor control studies.

Weaknesses:

The generalizability of the findings is limited. Future work may strengthen the present study's findings by examining whether the observed relationships hold for different stick lengths (i.e., varying hand positions along the virtual stick) or when reaching targets to the left and right of the starting position, not just at varying angles along one side. Additionally, a more comprehensive review of the existing literature on redundant systems, rather than primarily focusing on the lack of redundancy in endpoint-reaching tasks, would have strengthened this study. While the novel task expands the use of endpoint robots in motor control studies, its utility in exploring broader aspects of motor control and learning may be constrained.

for - wisdom stages - 4 middle school stages and - 4 high school stages - John Churchill

for - paraphrase - Buddhist framework - 4 turnings - 4 stages of initiation - John Churchill

paraphrase - Buddhist framework - 4 turnings - 4 stages of initiation - John Churchill - The fourth stage of "soul" - interdependent origination - systems thinking - can make use the knowledge of the third stage "mind" - which in turn uses the knowledge of the second stage "emotional body" - which uses the knowledge of the first stage "body"

1. 定义和作用： 一个证明就像正确运行的代码，必须在逻辑上严谨且能被他人理解。

2. 证明的标准： 一个好的数学证明应该做到两点：

3. 正确性：每一步推理都必须符合逻辑，因为如果证明不正确，就不能称为“证明”。

4. 易于理解：在确保正确的前提下，证明应该尽可能容易理解。 证明的结构：

5. 人类阅读的特殊性： 证明是写给人类阅读的，所以允许一定的常识性和简单的推测。比如，数学家可能会使用“显然”之类的词汇，但在初学证明时，建议避免这类词，以免产生错误的假设。

6. 符号和文字的平衡： 证明既可以用符号也可以用文字表达，甚至可以两者结合。重要的是逻辑清晰，而不一定要用大量符号来显得“专业”。

Reviewer #4 (Public review):

The authors apply what I gather is a novel methodology titled "Multi-gradient Permutation Survival Analysis" to identify genes that are robustly associated with prognosis ("GEARs") using tumour expression data from 15 cancer types available in the TCGA. The resulting lists of GEARs are then interrogated for biological insights using a range of techniques including connectivity and gene enrichment analysis.

I reviewed this paper primarily from a statistical perspective. Evidently, an impressive amount of work has been conducted, and concisely summarised, and great effort has been undertaken to add layers of insight to the findings. I am no stranger to what an undertaking this would have been. My primary concern, however, is that the novel statistical procedure proposed, and applied to identify the gene lists, as far as I can tell offers no statistical error control or quantification. Consequently, we have no sense of what proportion of the highlighted GEAR genes and networks are likely to just be noise.

Major comments:

(1) The main methodology used to identify the GEAR genes, "Multi-gradient Permutation Survival Analysis" does not formally account for multiple testing and offers no formal error control. Meaning we are left with no understanding of what the family-wise (aka type 1) error rate is among the GEAR lists, nor the false discovery rate. I would generally recommend against the use of any feature selection methodology that does not provide some form of error quantification and/or control because otherwise we do not know if we are encouraging our colleagues and/or readers to put resources into lists of genes that contain more noise than not. There are numerous statistical techniques available these days that offer error control, including for lists of p-values from arbitrary sets of tests (see expansion on this and some review references below).

(2) Similarly, no formal significance measure was used to determine which of the strongest "SAS" connections to include as edges in the "Core Survival Network".

(3) There is, as far as I could tell, no validation of any identified gene lists using an independent dataset external to the presently analysed TCGA data.

(4) There are quite a few places in the methods section where descriptions were not clear (e.g. elements of matrices referred to without defining what the columns and rows are), and I think it would be quite challenging to re-produce some aspects of the procedures as currently described (more detailed notes below).

(5) There is a general lack of statistical inference offered. For example, throughout the gene enrichment section of the results, I never saw it stated whether the pathways highlighted are enriched to a significant degree or not.

Smith Corona Typewriters 1935 - 1980 Type Alignment / Shift Motion Upper Lower Case Adjustment by [[Phoenix Typewriter]]

Duane starts out by showing the two adjustment screws for the upper and lower case motion adjustment on a 5 Series Smith-Corona portable. (This should be the same across several decades of machines and include the 4 and 6 series as well.)

Reviewer #4 (Public review):

Summary:

The authors have performed endoscopic calcium recordings of individual CeA neuron responses to food and shock, as well as to cues predicting food and shock. They claim that a majority of neurons encode valence, with a substantial minority encoding salience.

Strengths:

The use of endoscopic imaging is valuable, as it provides the ability to resolve signals from single cells, while also being able to track these cells across time. The recordings appear well-executed, and employ a sophisticated circular shifting analysis to avoid statistical errors caused by correlations between neighboring image pixels.

Weaknesses:

My main critique is that the authors didn't fully test whether neurons encode valence. While it is true that they found CeA neurons responding to stimuli that have positive or negative value, this by itself doesn't indicate that valence is the primary driver of neural activity. For example, they report that a majority of CeA neurons respond selectively to either the positive or negative US, and that this is evidence for "type I" valence encoding. However, it could also be the case that these neurons simply discriminate between motivationally relevant stimuli in a manner unrelated to valence per se. A simple test of this would be to check if neural responses generalize across more than one type of appetitive or aversive stimulus, but this was not done. The closest the authors came was to note that a small number of neurons respond to CS cues, of which some respond to the corresponding US in the same direction. This is relegated to the supplemental figures (3 and 4), and it is not noted whether the the same-direction CS-US neurons are also valence-encoding with respect to different USs. For example, are the neurons excited by CS-food and US-food also inhibited by shock? If so, that would go a long way toward classifying at least a few neurons as truly encoding valence in a generalizable way.

A second and related critique is that, although the authors correctly point out that definitions of salience and valence are sometimes confused in the existing literature, they then go on themselves to use the terms very loosely. For example, the authors define these terms in such a way that every neuron that responds to at least one stimulus is either salience or valence-encoding. This seems far too broad, as it makes essentially unfalsifiable their assertion that the CeA encodes some mixture of salience and valence. I already noted above that simply having different responses to food and shock does not qualify as valence-encoding. It also seems to me that having same-direction responses to these two stimuli similarly does not quality a neuron as encoding salience. Many authors define salience as being related to the ability of a stimulus to attract attention (which is itself a complex topic). However, the current paper does not acknowledge whether they are using this, or any other definition of salience, nor is this explicitly tested, e.g. by comparing neural response magnitudes to any measure of attention.

The impression I get from the authors' data is that CeA neurons respond to motivationally relevant stimuli, but in a way that is possibly more complex than what the authors currently imply. At the same time, they appear to have collected a large and high-quality dataset that could profitably be made available for additional analyses by themselves and/or others.

Lastly, the use of 10 daily sessions of training with 20 trials each seems rather low to me. In our hands, Pavlovian training in mice requires considerably more trials in order to effectively elicit responses to the CS. I wonder if the relatively sparse training might explain the relative lack of CS responses?

How many electoral votes does Illinois have? Cite yourr source(s).

Describe how and when industriallization took place in each country, Russia and the US.

Cite your sources.

https://www.liberatingstructures.com/1-1-2-4-all/

https://app.thebrain.com/brain/3d80058c-14d8-5361-0b61-a061f89baf87/fee4a5d8-6d7d-417a-8be2-2b2cc0e97966

DOI: 10.1038/s41467-024-51680-4

Resource: RRID:Addgene_34831

Curator: @olekpark

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What is this?

DOI: 10.1038/s41467-024-50498-4

Resource: RRID:Addgene_52961

Curator: @olekpark

SciCrunch record: RRID:Addgene_52961

What is this?

DOI: 10.1038/s41467-024-51664-4

Resource: RRID:Addgene_12456

Curator: @olekpark

SciCrunch record: RRID:Addgene_12456

What is this?

DOI: 10.1038/s41586-024-07706-4

Resource: RRID:Addgene_132778

Curator: @olekpark

SciCrunch record: RRID:Addgene_132778

What is this?

DOI: 10.1038/s41467-024-50765-4

Resource: RRID:Addgene_71237

Curator: @olekpark

SciCrunch record: RRID:Addgene_71237

What is this?

DOI: 10.1186/s13578-024-01288-4

Resource: RRID:Addgene_8453

Curator: @olekpark

SciCrunch record: RRID:Addgene_8453

What is this?

DOI: 10.1038/s41593-023-01557-4

Resource: RRID:Addgene_114472

Curator: @olekpark

SciCrunch record: RRID:Addgene_114472

What is this?

DOI: 10.1038/s41467-024-51424-4

Resource: RRID:Addgene_63800

Curator: @olekpark

SciCrunch record: RRID:Addgene_63800

What is this?

DOI: 10.1186/s12964-024-01795-4

Resource: RRID:Addgene_17360

Curator: @olekpark

SciCrunch record: RRID:Addgene_17360

What is this?

DOI: 10.1186/s12967-024-05627-4

Resource: RRID:Addgene_40973

Curator: @olekpark

SciCrunch record: RRID:Addgene_40973

What is this?

DOI: 10.1038/s41598-017-19065-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @maulamb

SciCrunch record: RRID:SCR_006457

What is this?

https://reddit.com/r/Zettelkasten/comments/1fjfl1g/highest_quality_archival_4x6_index_cards_lined/

მიუხედავად ოფიციალური ორგანოებისა და პასუხისმგებელი პირების მხრიდან ამ პრობლემის უგუვებელყოფის,აუცილებელია ქალებმა კვლავ განაგრძონ ბრძოლა საკუთარი უფლებების დასაცავად და მყარად მოიკიდონ ფეხი პლიტიკურ სფეროში,მიუცედავად არსებული წინააღმდეგობებისა,რადგან დანებება წახალისებაა იმ საზოგადოების,რომელიც შრომას ყოფს გენდერულად და არაფასებს ქალის შესაძლებლობას.

for - safe and just earth system boundaries - translations and transformations - 4 parts

earth system boundaries - translations and transformations - 4 parts - part 1 - theoretical framework - part 2 - quantification of - safe and just ESB, - which ones are transgressed - who are the victims - safe and just corridor - base - ceiling - for timeframe - present - 2050 - part 3 - translating - safe and just ESB - approaches - challenges - enabling conditions - to - cities - businesses

Your brain cannot tell whether it is real or imaginary, so imagine and think in "crazy" creative ways to get your brain to start creating something you might not have without thinking in an almost unrealistic way.

Reviewer #4 (Public Review):

Summary:

With their 'CMR-replay' model, Zhou et al. demonstrate that the use of spontaneous neural cascades in a context-maintenance and retrieval (CMR) model significantly expands the range of captured memory phenomena.

Strengths:

The proposed model compellingly outperforms its CMR predecessor and, thus, makes important strides towards understanding the empirical memory literature, as well as highlighting a cognitive function of replay.

Weaknesses:

Competing accounts of replay are acknowledged but there are no formal comparisons and only CMR-replay predictions are visualized. Indeed, other than the CMR model, only one alternative account is given serious consideration: A variant of the 'Dyna-replay' architecture, originally developed in the machine learning literature (Sutton, 1990; Moore & Atkeson, 1993) and modified by Mattar et al (2018) such that previously experienced event-sequences get replayed based on their relevance to future gain. Mattar et al acknowledged that a realistic Dyna-replay mechanism would require a learned representation of transitions between perceptual and motor events, i.e., a 'cognitive map'. While Zhou et al. note that the CMR-replay model might provide such a complementary mechanism, they emphasize that their account captures replay characteristics that Dyna-replay does not (though it is unclear to what extent the reverse is also true).

Another important consideration, however, is how CMR replay compares to alternative mechanistic accounts of cognitive maps. For example, Recurrent Neural Networks are adept at detecting spatial and temporal dependencies in sequential input; these networks are being increasingly used to capture psychological and neuroscientific data (e.g., Zhang et al, 2020; Spoerer et al, 2020), including hippocampal replay specifically (Haga & Fukai, 2018). Another relevant framework is provided by Associative Learning Theory, in which bidirectional associations between static and transient stimulus elements are commonly used to explain contextual and cue-based phenomena, including associative retrieval of absent events (McLaren et al, 1989; Harris, 2006; Kokkola et al, 2019). Without proper integration with these modeling approaches, it is difficult to gauge the innovation and significance of CMR-replay, particularly since the model is applied post hoc to the relatively narrow domain of rodent maze navigation.

Der südkoreanische Verfassungsgerichtshof hat die Regierung des Landes dazu verurteilt ein Klimschutzgesetz vorzulegen, das auch für 2031-2049 verpflichtende Ziele für die Reduktion der Emissionen vorgibt. Andernfalls würden die verfassungsmäßigen Rechte der jüngeren Generation beeinträchtigt. Das Verfahren hatte 2020 mit einer Klage der Gruppe Youth 4 Climate Action begonnen. https://www.theguardian.com/world/article/2024/aug/29/south-korea-court-climate-law-violates-rights-future-generations

Reviewer #4 (Public Review):

The authors report the role of the Piruvate Kinase M2 (PKM2) enzyme nuclear translocation as fundamental in the activation of astrocytes in a model of autoimmune encephalitis (EAE). They show that astrocytes, activated through culturing in EAE splenocytes medium, increase their nuclear PKM2 with a consequent activation of NFkB and STAT3 pathways. Prevention of PKM2 nuclear translocation decreases astrocyte counteracts this activation. The authors found that the E3 ubiquitin ligase TRIM21 interacts with PKM2 and promotes its nuclear translocation. In vivo, either silencing of TRIM21 or inhibition of PKM2 nuclear translocation ameliorates the severity of the disease in the EAE model.

Strengths

This work contributes to the knowledge of the complex action of the PKM2 enzyme in the context of an autoimmune-neurological disease, highlighting its nuclear role and a novel partner, TRIM21, promoting its nuclear translocation. In vivo amelioration of the pathological signs through inhibition of either of the two, PKM2 and TRIM21, provides a novel rationale for therapeutic targeting.

Weaknesses

I believe that the major weakness is the fact that TRIM21 is known to have per se many roles in autoimmune and immune pathways and some of the effects observed might be due to a PKM2-independent action. Some of the experiments to link the two proteins, besides their interaction, are not completely clarifying the issue. On top of that, the in vivo experiments address the role of TRIM21 and the nuclear localisation of PKM2 independently, thus leaving the matter unsolved.

In general, the conclusions of the manuscript are supported by the reported results. The points to be addressed in future are the assessment of PKM2 as substrate of TRIM21 ubiquitin ligase activity and the proof of the epistatic relationship of TRIM21 and PKM2 in astrocyte activation. However, the data surely open novel directions to follow for the understanding of multiple sclerosis and related pathologies.

Reviewer #4 (Public Review):

The manuscript examines how patterns of selection on gene expression differ between a normal field environment and a field environment with elevated salinity based on transcript abundances obtained from leaves of a diverse panel of rice germplasm. In addition, the manuscript also maps expression QTL (eQTL) that explains variation in each environment. One highlight from the mapping is that a small group of trans-mapping regulators explains some gene expression variation for large sets of transcripts in each environment. The overall scope of the datasets is impressive, combining large field studies that capture information about fecundity, gene expression, and trait variation at multiple sites. The finding related to patterns indicating increased LD among eQTLs that have cis-trans compensatory or reinforcing effects is interesting in the context of other recent work finding patterns of epistatic selection. However, other analyses in the manuscript are less compelling or do not make the most of the value of collected data. Revisions are also warranted to improve the precision with which field-specific terminology is applied and the language chosen when interpreting analytical findings.

Selection of gene expression:<br /> One strength of the dataset is that gene expression and fecundity were measured for the same genotypes in multiple environments. However, the selection analyses are largely conducted within environments. The addition of phenotypic selection analyses that jointly analyze gene expression across environments and or selection on reaction norms would be worthwhile.

Gene expression trade-offs:<br /> The terminology and possibly methods involved in the section on gene expression trade-offs need amendment. I specifically recommend discontinuing reference to the analysis presented as an analysis of antagonistic pleiotropy (rather than more general trade-offs) because pleiotropy is defined as a property of a genotype, not a phenotype. Gene expression levels are a molecular phenotype, influenced by both genotype and the environment. By conducting analyses of selection within environments as reported, the analysis does not account for the fact that the distribution of phenotypic values, the fitness surface, or both may differ across environments. Thus, this presents a very different situation than asking whether the genotypic effect of a QTL on fitness differs across environments, which is the context in which the contrasting terms antagonistic pleiotropy and conditional neutrality have been traditionally applied. A more interesting analysis would be to examine whether the covariance of phenotype with fitness has truly changed between environments or whether the phenotypic distribution has just shifted to a different area of a static fitness surface.

Biological processes under selection / Decoherence: PCs are likely not the most ideal way to cluster genes to generate consolidated metrics for a selection gradient analysis. Because individual genes will contribute to multiple PCs, the current fractional majority-rule method applied to determine whether a PC is under direct or indirect selection for increased or decreased expression comes across as arbitrary and with the potential for double-counting genes. A gene co-expression network analysis could be more appropriate, as genes only belong to one module and one can examine how selection is acting on the eigengene of a co-expression module. Building gene co-expression modules would also provide a complementary and more concrete framework for evaluating whether salinity stress induces "decoherence" and which functional groups of genes are most impacted.

Selection of traits:<br /> Having paired organismal and molecular trait data is a strength of the manuscript, but the organismal trait data are underutilized. The manuscript as written only makes weak indirect inferences based on GO categories or assumed gene functions to connect selection at the organismal and molecular levels. Stronger connections could be made for instance by showing a selection of co-expression module eigengene values that are also correlated with traits that show similar patterns of selection, or by demonstrating that GWAS hits for trait variation co-localize to cis-mapping eQTL.

Genetic architecture of gene expression variation:<br /> The descriptive statistics of the eQTL analysis summarize counts of eQTLs observed in each environment, but these numbers are not broken down to the molecular trait level (e.g., what are the median and range of cis- and trans-eQTLs per gene). In addition, genetic architecture is a combination of the numbers and relative effect sizes of the QTLs. It would be useful to provide information about the relative distributions of phenotypic variance explained by the cis- vs. trans- eQTLs and whether those distributions vary by environment. The motivation for examining patterns of cis-trans compensation specifically for the results obtained under high salinity conditions is unclear to me. If the lines sampled have predominantly evolved under low salinity conditions and the hypothesis being evaluated relates to historical experience of stabilizing selection, then my intuition is that evaluating the eQTL patterns under normal conditions provides the more relevant test of the hypothesis.

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 45-0621-82, RRID:AB_996667)

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DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 25-0441-82, RRID:AB_469623)

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 17-0801-82, RRID:AB_469417)

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 17-0451-82, RRID:AB_469392)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 17-0451-82, RRID:AB_469392)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 17-0451-82, RRID:AB_469392)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 12-0311-82, RRID:AB_465632)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 12-0114-82, RRID:AB_465552)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 11-0081-82, RRID:AB_464915)

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Thermo Fisher Scientific Cat# 11-0081-82, RRID:AB_464915)

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Abcam Cat# ab10558, RRID:AB_442810)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Abcam Cat# ab217344, RRID:AB_2890649)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (BioLegend Cat# 861001, RRID:AB_2814585)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Cell Signaling Technology Cat# 97585, RRID:AB_2800282)

Curator: @AniH

SciCrunch record: RRID:AB_2800282

What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Cell Signaling Technology Cat# 46890, RRID:AB_2799313)

Curator: @AniH

SciCrunch record: RRID:AB_2799313

What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Cell Signaling Technology Cat# 46890, RRID:AB_2799313)

Curator: @AniH

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What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: AB2573372

Curator: @AniH

SciCrunch record: RRID:AB2573372

What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: AB_25724331

Curator: @AniH

SciCrunch record: RRID:AB_25724331

What is this?

DOI: 10.1038/s44321-024-00068-4

Resource: (Bioss Cat# bs-1444R, RRID:AB_10855240)

Curator: @AniH

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What is this?

DOI: 10.7554/eLife.82249

Resource: ZFIN_ZDB-ALT-230316-4

Curator: @olekpark

SciCrunch record: RRID:ZFIN_ZDB-ALT-230316-4

What is this?

DOI: 10.7554/eLife.91429

Resource: (ZFIN Cat# ZDB-ALT-051223-4,RRID:ZFIN_ZDB-ALT-051223-4)

Curator: @olekpark

SciCrunch record: RRID:ZFIN_ZDB-ALT-051223-4

What is this?

DOI: 10.1038/s41467-023-36644-4

Resource: RRID:BDSC_48306

Curator: @anisehay

SciCrunch record: RRID:BDSC_48306

What is this?

DOI: 10.1038/s41420-023-01642-4

Resource: RRID:BDSC_37721

Curator: @anisehay

SciCrunch record: RRID:BDSC_37721

What is this?

Reviewer #4 (Public Review):

Summary:

The authors report a novel isomorphism in which the folds of the elephant trunk are recognizably mapped onto the principal sensory trigeminal nucleus in the brainstem. Further, they identify the enlarged nucleus as being situated in this species in an unusual ventral midline position.

Strengths:

The identity of the purported trigeminal nucleus and the isomorphic mapping with the trunk folds is supported by multiple lines of evidence: enhanced staining for cytochrome oxidase, an enzyme associated with high metabolic activity; dense vascularization, consistent with high metabolic activity; prominent myelinated bundles that partition the nucleus in a 1:1 mapping of the cutaneous folds in the trunk periphery; near absence of labeling for the anti-peripherin antibody, specific for climbing fibers, which can be seen as expected in the inferior olive; and a high density of glia.

Weaknesses:

Despite the supporting evidence listed above, the identification of the gross anatomical bumps, conspicuous in the ventral midline, is problematic. This would be the standard location of the inferior olive, with the principal trigeminal nucleus occupying a more dorsal position. This presents an apparent contradiction which at a minimum needs further discussion. Major species-specific specializations and positional shifts are well-documented for cortical areas, but nuclear layouts in the brainstem have been considered as less malleable.

DOI: 10.1002/cne.23733

Resource: RRID:ZFIN_ZDB-GENO-100308-4

Curator: @chewbeccax

SciCrunch record: RRID:ZFIN_ZDB-GENO-100308-4

What is this?

DOI: 10.1038/s41556-023-01227-4

Resource: SCR_006457

Curator: @anisehay

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41598-021-82944-4

Resource: RRID:BDSC_7011

Curator: @olekpark

SciCrunch record: RRID:BDSC_7011

What is this?

DOI: 10.1038/s41419-021-03742-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @olekpark

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41598-020-74448-4

Resource: RRID:BDSC_32078

Curator: @anisehay

SciCrunch record: RRID:BDSC_32078

What is this?

DOI: 10.1038/s41598-021-84413-4

Resource: SCR_00645

Curator: @anisehay

SciCrunch record: RRID:SCR_00645

What is this?

DOI: 10.1038/s41598-021-88910-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @mpairish

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41559-021-01482-4

Resource: RRID:BDSC_51307

Curator: @anisehay

SciCrunch record: RRID:BDSC_51307

What is this?

DOI: 10.1038/s41598-022-09869-4

Resource: RRID:BDSC_5138

Curator: @mpairish

SciCrunch record: RRID:BDSC_5138

What is this?

DOI: 10.1038/s41467-022-30975-4

Resource: BDSC_25125

Curator: @anisehay

SciCrunch record: RRID:BDSC_25125

What is this?

DOI: 10.1186/s13064-022-00166-4

Resource: (BDSC Cat# 2376,RRID:BDSC_2376)

Curator: @anisehay

SciCrunch record: RRID:BDSC_2376

What is this?

DOI: 10.1038/s41586-022-04578-4

Resource: BDSC_50746

Curator: @mpairish

SciCrunch record: RRID:BDSC_50746

What is this?

DOI: 10.1186/s13578-021-00595-4

Resource: RRID:BDSC_67608

Curator: @bandrow

SciCrunch record: RRID:BDSC_67608

What is this?

DOI: 10.1038/s41588-020-0615-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @anisehay

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1007/s12192-020-01171-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @bpowell22

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41593-024-01678-4

Resource: (MMRRC Cat# 031796-UCD,RRID:MMRRC_031796-UCD)

Curator: @dhovakimyan1

SciCrunch record: RRID:MMRRC_031796-UCD

What is this?

DOI: 10.1186/s12964-024-01733-4

Resource: (ATCC Cat# CRL-2539, RRID:CVCL_0125)

Curator: @evieth

SciCrunch record: RRID:CVCL_0125

What is this?

DOI: 10.1038/s41422-020-0388-4

Resource: (BDSC Cat# 29455,RRID:BDSC_29455)

Curator: @bpowell22

SciCrunch record: RRID:BDSC_29455

What is this?

DOI: 10.1038/s41467-023-36474-4

Resource: RRID:BDSC_34347

Curator: @mpairish

SciCrunch record: RRID:BDSC_34347

What is this?

DOI: 10.1007/s12192-020-01074-4

Resource: (BDSC Cat# 6326,RRID:BDSC_6326)

Curator: @PeterEckmann

SciCrunch record: RRID:BDSC_6326

What is this?

DOI: 10.1038/s41467-020-14781-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @olekpark

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1007/s00359-019-01396-4

Resource: (BDSC Cat# 54203,RRID:BDSC_54203)

Curator: @bandrow

SciCrunch record: RRID:BDSC_54203

What is this?

DOI: 10.1038/s41598-019-48860-4

Resource: RRID:BDSC_30910

Curator: @bandrow

SciCrunch record: RRID:BDSC_30910

What is this?

DOI: 10.1038/s41420-023-01769-4

Resource: RRID:BDSC_549

Curator: @olekpark

SciCrunch record: RRID:BDSC_549

What is this?

DOI: 10.1038/s41467-023-38755-4

Resource: (BDSC Cat# 7415,RRID:BDSC_7415)

Curator: @mpairish

SciCrunch record: RRID:BDSC_7415

What is this?

DOI: 10.1007/s12195-024-00811-4

Resource: (NCI-DTP Cat# MCF7, RRID:CVCL_0031)

Curator: @dhovakimyan1

SciCrunch record: RRID:CVCL_0031

What is this?

DOI: 10.1038/s41559-023-02127-4

Resource: (BDSC Cat# 5905,RRID:BDSC_5905)

Curator: @mpairish

SciCrunch record: RRID:BDSC_5905

What is this?

Reviewer #4 (Public Review):

In this manuscript by Sha et al. the authors test the role of TNFa in modulating tumor regression/recurrence under therapeutic pressure from castration (or enzalutamide) in both in vitro and in vivo models of prostate cancer. Using the PTEN-null genetic mouse model, they compare the effect of a TNFα ligand trap, etanercept, at various points pre- and post-castration. Their most interesting findings from this experiment were that etanercept given 3 days prior to castration prevented tumor regression, which is a common phenotype seen in these models after castration, but etanercept given 1 day prior to castration prevented prostate cancer recurrence after castration. They go on to perform RNA sequencing on tumors isolated from either sham or castrate mice from two time points post-castration to study acute and delayed transcriptional responses to androgen deprivation. They found enrichment of gene sets containing TNF-targets which initially decrease post-castration but are elevated by 35 days, the time at which tumors recur. The authors conduct a similar set of experiments using human prostate cancer cell lines treated with the androgen receptor inhibitor enzalutamide and observe that drug treatment leads to cells with basal stem-like features that express high levels of TNF. They noticed that CCL2 levels correlate with changes in TNF levels raising the possibility that CCL2 might be a critical downstream effector for disease recurrence. To this end, they treated PTEN-null and hi-MYC castrated mice with a CCR2-antagonist (CCR2a) because CCR2 is one receptor of CCL2 and monitors tumor growth dynamics. Interestingly, upon treatment with CCR2a, tumors did not recur according to their measurements. They go on to demonstrate that the tumors pre-treated with CCR2a had reduced levels of putative TAMs and increased CTLs in the context of TNF or CCR2 inhibition providing a cellular context associated with disease regression. Lastly, they perform single-cell RNA sequencing to further characterize the tumor microenvironment post-castration and report that the ratio of CTLs to TAMs is lower in a recurrent tumor.

While the concepts behind the study have merit, the data are incomplete and do not fully support the authors' conclusions. The author's definition of recurrence is subjective given that the amount of disease regression after castration is both variable (Figure 8) and relatively limited, particularly in the PTEN loss model. Critical controls are missing. For example, both drug experiments were completed without treating non-castrate plus drug controls which raises the question of how specific these findings are to castration resistance. No validation was performed to ensure that either the TNF ligand trap or the CCR2 agonist was acting on target. The single-cell sequencing experiments were done without replicates which raises concern about its interpretation. At a conceptual level, the authors say that a major cause of disease recurrence in the immunosuppressive TME, but provide little functional data that macrophages and T cells are directly responsible for this phenotype. Statistical analyses were performed on only select experiments. In summary, further work is recommended to support the conclusions of this story.

DOI: 10.1038/s41467-024-47465-4

Resource: RRID:BDSC_93857

Curator: @bandrow

SciCrunch record: RRID:BDSC_93857

What is this?

DOI: 10.1038/s41598-019-53508-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @bpowell22

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41598-024-56343-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @anisehay

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41598-024-56343-4

Resource: BDSC_27387

Curator: @anisehay

SciCrunch record: RRID:BDSC_27387

What is this?

DOI: 10.1186/s13008-023-00097-4

Resource: BDSC_55626

Curator: @mpairish

SciCrunch record: RRID:BDSC_55626

What is this?

DOI: 10.1038/s41586-024-07463-4

Resource: RRID:BDSC_66795

Curator: @bandrow

SciCrunch record: RRID:BDSC_66795

What is this?

DOI: 10.1038/s41593-024-01589-4

Resource: (BDSC Cat# 9146,RRID:BDSC_9146)

Curator: @mpairish

SciCrunch record: RRID:BDSC_9146

What is this?

DOI: 10.1038/s41598-024-65172-4

Resource: (BDSC Cat# 458,RRID:BDSC_458)

Curator: @bandrow

SciCrunch record: RRID:BDSC_458

What is this?

DOI: 10.1038/s42003-023-05427-4

Resource: BDSC_4361

Curator: @maulamb

SciCrunch record: RRID:BDSC_4361

What is this?

DOI: 10.1038/s41597-023-02389-4

Resource: BICCN (RRID:SCR_015820)

Curator: @evieth

SciCrunch record: RRID:SCR_015820

What is this?

Reviewer #4 (Public Review):

Summary:

This manuscript claims to provide a new null hypothesis for testing the effects of biodiversity on ecosystem functioning. It reports that the strength of biodiversity effects changes when this different null hypothesis is used. This main result is rather inevitable. That is, one expects a different answer when using a different approach. The question then becomes whether the manuscript's null hypothesis is both new and an improvement on the null hypothesis that has been in use in recent decades.

Strengths:

In general, I appreciate studies like this that question whether we have been doing it all wrong and I encourage consideration of new approaches.

Weaknesses:

Despite many sweeping critiques of previous studies and bold claims of novelty made throughout the manuscript, I was unable to find new insights. The manuscript fails to place the study in the context of the long history of literature on competition and biodiversity and ecosystem functioning. The Introduction claims the new approach will address deficiencies of previous approaches, but after reading further I see no evidence that it addresses the limitations of previous approaches noted in the Introduction. Furthermore, the manuscript does not reproducibly describe the methods used to produce the results (e.g., in Table 1) and relies on simulations, claiming experimental data are not available when many experiments have already tested these ideas and not found support for them. Finally, it is unclear to me whether rejecting the 'new' null hypothesis presented in the manuscript would be of interest to ecologists, agronomists, conservationists, or others. I will elaborate on each of these points below.

The critiques of biodiversity experiments and existing additive partitioning methods are overstated, as is the extent to which this new approach addresses its limitations. For example, the critique that current biodiversity experiments cannot reveal the effects of species interactions (e.g., lines 37-39) isn't generally true, but it could be true if stated more specifically. That is, this statement is incorrect as written because comparisons of mixtures, where there are interspecific and intraspecific interactions, with monocultures, where there are only intraspecific interactions, certainly provide information about the effects of species interactions (interspecific interactions). These biodiversity experiments and existing additive partitioning approaches have limits, of course, for identifying the specific types of interactions (e.g., whether mediated by exploitative resource competition, apparent competition, or other types of interactions). However, the approach proposed in this manuscript gets no closer to identifying these specific mechanisms of species interactions. It has no ability to distinguish between resource and apparent competition, for example. Thus, the motivation and framing of the manuscript do not match what it provides. I believe the entire Introduction would need to be rewritten to clarify what gap in knowledge this proposed approach is addressing and what would be gained by filling this knowledge gap.

I recommend that the Introduction instead clarify how this study builds on and goes beyond many decades of literature considering how competition and biodiversity effects depend on density. This large literature is insufficiently addressed in this manuscript. This fails to give credit to previous studies considering these ideas and makes it unclear how this manuscript goes beyond the many previous related studies. For example, see papers and books written by de Wit, Harper, Vandermeer, Connolly, Schmid, and many others. Also, note that many biodiversity experiments have crossed diversity treatments with a density treatment and found no significant effects of density or interactions between density and diversity (e.g., Finn et al. 2013 Journal of Applied Ecology). Thus, claiming that these considerations of density are novel, without giving credit to the enormous number of previous studies considering this, is insufficient.

Replacement series designs emerged as a consensus for biodiversity experiments because they directly test a relevant null hypothesis. This is not to say that there are no other interesting null hypotheses or study designs, but one must acknowledge that many designs and analyses of biodiversity experiments have already been considered. For example, Schmid et al. reviewed these designs and analyses two decades ago (2002, chapter 6 in Loreau et al. 2002 OUP book) and the overwhelming consensus in recent decades has been to use a replacement series and test the corresponding null hypothesis.

It is unclear to me whether rejecting the 'new' null hypothesis presented in the manuscript would be of interest to ecologists, agronomists, conservationists, or others. Most biodiversity experiments and additive partitions have tested and quantified diversity effects against the null hypothesis that there is no difference between intraspecific and interspecific interactions. If there was no less competition and no more facilitation in mixtures than in monocultures, then there would be no positive diversity effects. Rejecting this null hypothesis is relevant when considering coexistence in ecology, overyielding in agronomy, and the consequences of biodiversity loss in conservation (e.g., Vandermeer 1981 Bioscience, Loreau 2010 Princeton Monograph). This manuscript proposes a different null hypothesis and it is not yet clear to me how it would be relevant to any of these ongoing discussions of changes in biodiversity.

The claim that all previous methods 'are not capable of quantifying changes in ecosystem productivity by species interactions and species or community level' is incorrect. As noted above, all approaches that compare mixtures, where there are interspecific interactions, to monocultures, where there are no species interactions, do this to some extent. By overstating the limitations of previous approaches, the manuscript fails to clearly identify what unique contribution it is offering, and how this builds on and goes beyond previous work.

The manuscript relies on simulations because it claims that current experiments are unable to test this, given that they have replacement series designs (lines 128-131). There are, however, dozens of experiments where the replacement series was repeated at multiple densities, which would allow a direct test of these ideas. In fact, these ideas have already been tested in these experiments and density effects were found to be nonsignificant (e.g., Finn et al. 2013).

It seems that the authors are primarily interested in trees planted at a fixed density, with no opportunity for changes in density, and thus only changes in the size of individuals (e.g., Fig. 1). In natural and experimental systems, realized density differs from the initial planted density, and survivorship of seedlings can depend on both intraspecific and interspecific interactions. Thus, the constrained conditions under which these ideas are explored in this manuscript seem narrow and far from the more complex reality where density is not fixed.

Additional detailed comments:

It is unclear to me which 'effects' are referred to on line 36. For example, are these diversity effects or just effects of competition? What is the response variable?

The usefulness of the approach is overstated on line 52. All partitioning approaches, including the new one proposed here, give the net result of many types of species interactions and thus cannot 'disentangle underlying mechanisms of species interactions.'

The weaknesses of previous approaches are overstated throughout the manuscript, including in lines 60-61. All approaches provide some, but not all insights. Sweeping statements that previous approaches are not effective, without clarifying what they can and can't do, is unhelpful and incorrect. Also, these statements imply that the approach proposed here addresses the limitations of these previous approaches. I don't yet see how it does so.

The definitions given for the CE and SE on line 71 are incorrect. Competition affects both terms and CE can be negative or have nothing to do with positive interactions, as noted in many of the papers cited.

The proposed approach does not address the limitations noted on lines 73 and 74.

The definition of positive interactions in lines 77 and 78 seems inconsistent with much of the literature, which instead focuses on facilitation or mutualism, rather than competition when describing positive interactions.

Throughout the manuscript, competition is often used interchangeably with resource competition (e.g., line 82) and complementarity is often attributed to resource partitioning (e.g., line 77). This ignores apparent competition and partitioning enemy-free niche space, which has been found to contribute to biodiversity effects in many studies.

In what sense are competitive interactions positive for competitive species (lines 82-83)? By definition, competition is an interaction that has a negative effect. Do you mean that interspecific competition is less than intraspecific competition? I am having a very difficult time following the logic.

Results are asserted on lines 93-95, but I cannot find the methods that produced these results. I am unable to evaluate the work without a repeatable description of the methods.

The description of the null hypothesis in the common additive partitioning approach on lines 145-146 is incorrect. In the null case, it does not assume that there are no interspecific interactions, but rather that interspecific and intraspecific interactions are equivalent.

Reviewer #4 (Public Review):

Summary:

The authors report a novel isomorphism in which the folds of the elephant trunk are recognizably mapped onto the principal sensory trigeminal nucleus in the brainstem. Further, they identifiy the enlarged nucleus as being situated in this species in an unusual ventral midline position.

Strengths:

The identity of the purported trigeminal nucleus and the isomorphic mapping with the trunk folds is supported by multiple lines of evidence: enhanced staining for cytochrome oxidase, an enzyme associated with high metabolic activity; dense vascularization, consistent with high metabolic activity; prominent myelinated bundles that partition the nucleus in a 1:1 mapping of the cutaneous folds in the trunk periphery; near absence of labeling for the anti-peripherin antibody, specific for climbing fibers, which can be seen as expected in the inferior olive; and a high density of glia.

Weaknesses:

Despite the supporting evidence listed above, the identification of the gross anatomical bumps, conspicuous in the ventral midline, is problematic. This would be the standard location of the inferior olive, with the principal trigeminal nucleus occupying a more dorsal position. This presents an apparent contradiction which at a minimum needs further discussion. Major species-specific specializations and positional shifts are well-documented for cortical areas, but nuclear layouts in the brainstem have been considered as less malleable.

for - AI - inside industry predictions to 2034 - Leopold Aschenbrenner - inside information on disruptive Generative AI to 2034

document description - Situational Awareness - The Decade Ahead - author - Leopold Aschenbrenner

summary - Leopold Aschenbrenner is an ex-employee of OpenAI and reveals the insider information of the disruptive plans for AI in the next decade, that pose an existential threat to create a truly dystopian world if we continue going down our BAU trajectory. - The A.I. arms race can end in disaster. The mason threat of A.I. is that humans are fallible and even one bad actor with access to support intelligent A.I. can post an existential threat to everyone - A.I. threat is amplifier by allowing itt to control important processes - and when it is exploited by the military industrial complex, the threat escalates significantly

• to - YouTube - 4 hour in-depth interview with Leopold Aschenbrenner on the disruptive and existential impacts of A.I. super-intelligence
  • https://hyp.is/zk8hdjEoEe-EIHtdo3U81w/www.youtube.com/watch?v=zdbVtZIn9IM

DOI: 10.7554/eLife.95980

Resource: RRID:ZFIN_ZDB-ALT-191219-4

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-191219-4

What is this?

DOI: 10.1038/s41586-022-05485-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @DavidDeutsch

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1016/j.isci.2024.110078

Resource: ZFIN_ZDB-ALT-150916-4

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-150916-4

What is this?

Reviewer #4 (Public Review):

This is a very interesting study, where the authors discovered two neuroendocrine signaling circuits with opposite effects on organismal longevity elicited by motor neurons at different ages.

Interestingly, both systems employ the same neurotransmitter (that is, acetylcholine) and signal the intestine. However, one has effects on early life to shorten lifespan whereas the other system is activated in mid-life to extend lifespan. At the mechanistic level, this bidirectional regulation is possible through the recruitment of two different ACh receptors in the gut: ACR-6 and GAR-3. The authors found that ACR-6 expression in the intestine is restricted to early life, whereas GAR-3 expression in the gut is confined to mid-late life. Interestingly, ACR-6 modulates the transcription factor DAF-16, but GAR-3 regulates HSF-1.

The study combines different approaches, including inducible systems (AID) which are critical for the conclusions of the paper. The conclusions are well supported by the experiments and results. The data provide a potential mechanism for the temporal control of lifespan and shed light on the complex role of the nervous system in organismal aging. These results can have important implications for understanding how organismal aging is regulated in a temporal manner by cell non-autonomous mechanisms. I didn't observe significant weaknesses in the study, but I have several comments that I hope the authors will address.

Reviewer #4 (Public Review):

Summary:

The authors report the role of the Pyruvate Kinase M2 (PKM2) enzyme nuclear translocation as fundamental in the activation of astrocytes in a model of autoimmune encephalitis (EAE). They show that astrocytes, activated through culturing in EAE splenocytes medium, increase their nuclear PKM2 with consequent activation of NFkB and STAT3 pathways. Prevention of PKM2 nuclear translocation decreases astrocyte counteracts this activation. The authors found that the E3 ubiquitin ligase TRIM21 interacts with PKM2 and promotes its nuclear translocation. In vivo, either silencing of TRIM21 or inhibition of PKM2 nuclear translocation ameliorates the severity of the disease in the EAE model.

Strengths:

This work contributes to the knowledge of the complex action of the PKM2 enzyme in the context of an autoimmune-neurological disease, highlighting its nuclear role and a novel partner, TRIM21, and thus adding a novel rationale for therapeutic targeting.

Weaknesses:

Despite the relevance of the work and its goals, some of the conclusions drawn would require more thorough proof:

I believe that the major weakness is the fact that TRIM21 is known to have per se many roles in autoimmune and immune pathways and some of the effects observed might be due to a PKM2-independent action. Some of the experiments to link the two proteins, besides their interaction, do not completely clarify the issue. On top of that, the in vivo experiments address the role of TRIM21 and the nuclear localisation of PKM2 independently, thus leaving the matter unsolved.

Some experimental settings are not described to a level that is necessary to fully understand the data, especially for a non-expert audience: e.g. the EAE model and MOG treatment; action and reference of the different nuclear import inhibitors; use of splenocyte culture medium and the possible effect of non-EAE splenocytes.

The statement that PKM2 is a substrate of TRIM21 ubiquitin ligase activity is an overinterpretation. There is no evidence that this interaction results in ubiquitin modification of PKM2; the ubiquitination experiment is minimal and is not performed in conditions that would allow us to see ubiquitination of PKM2 (e.g. denaturing conditions, reciprocal pull-down, catalytically inactive TRIM21, etc.).

DOI: 10.1038/s41467-022-35527-4

Resource: BDSC_3506

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_3506

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: (BDSC Cat# 4776,RRID:BDSC_4776)

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_4776

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: RRID:BDSC_44633

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_44633

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: RRID:BDSC_52215

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_52215

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: RRID:BDSC_32489

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_32489

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: (BDSC Cat# 7017,RRID:BDSC_7017)

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_7017

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: RRID:BDSC_67493

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_67493

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: (BDSC Cat# 57669,RRID:BDSC_57669)

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_57669

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: RRID:BDSC_91368

Curator: @DavidDeutsch

SciCrunch record: RRID:BDSC_91368

What is this?

DOI: 10.1038/s41467-022-35527-4

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @DavidDeutsch

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1038/s41577-023-00985-4

Resource: Network for Pancreatic Organ Donors with Diabetes (RRID:SCR_014641)

Curator: @bandrow

SciCrunch record: RRID:SCR_014641

What is this?

DOI: 10.7554/eLife.89516

Resource: (ZFIN Cat# ZDB-GENO-130815-4,RRID:ZFIN_ZDB-GENO-130815-4)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-GENO-130815-4

What is this?

DOI: 10.17912/micropub.biology.001219

Resource: ZFIN_ZDB-ALT-220225-4

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-220225-4

What is this?

DOI: 10.1038/s42003-024-06320-4

Resource: (Abcam Cat# ab25251, RRID:AB_448738)

Curator: @bandrow

SciCrunch record: RRID:AB_448738

What is this?

DOI: 10.1007/s40618-023-02248-4

Resource: CVCL_0582

Curator: @bandrow

SciCrunch record: RRID:CVCL_0582

What is this?

DOI: 10.1186/s12864-023-09562-4

Resource: (Torrey Pines Biolabs Cat# TP401, RRID:AB_2313770)

Curator: @abever99

SciCrunch record: RRID:AB_2313770

What is this?

DOI: 10.1186/s12864-023-09562-4

Resource: (Molecular Probes Cat# A-11122, RRID:AB_221569)

Curator: @abever99

SciCrunch record: RRID:AB_221569

What is this?

DOI: 10.1186/s12974-023-03004-4

Resource: Illumina (RRID:SCR_010233)

Curator: @abever99

SciCrunch record: RRID:SCR_010233

What is this?

DOI: 10.1186/s12974-023-03004-4

Resource: (IMSR Cat# JAX_003010,RRID:IMSR_JAX:003010)

Curator: @bandrow

SciCrunch record: RRID:IMSR_JAX:003010

What is this?

DOI: 10.1186/s12974-023-03004-4

Resource: (MMRRC Cat# 034845-JAX,RRID:MMRRC_034845-JAX)

Curator: @bandrow

SciCrunch record: RRID:MMRRC_034845-JAX

What is this?