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Record W2577671479 · doi:10.7554/elife.19837

The RFamide receptor DMSR-1 regulates stress-induced sleep in C. elegans

2017· article· en· W2577671479 on OpenAlexaff
Michael J. Iannacone, Isabel Beets, Lindsey E. Lopes, Matthew A. Churgin, Christopher Fang‐Yen, Matthew D. Nelson, Liliane Schoofs, David M. Raizen

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsCanadian Sleep & Circadian Network
FundersNational Institute of Environmental Health SciencesNational Institute of Neurological Disorders and StrokeNational Institutes of HealthEuropean Research CouncilFonds Wetenschappelijk Onderzoek
KeywordsBiologyCell biologyHeterotrimeric G proteinNeuropeptideCaenorhabditis elegansG protein-coupled receptorReceptorMutantNeuroscienceHEK 293 cellsSignal transductionGeneticsGeneG protein

Abstract

fetched live from OpenAlex

In response to environments that cause cellular stress, animals engage in sleep behavior that facilitates recovery from the stress. In Caenorhabditis elegans, stress-induced sleep(SIS) is regulated by cytokine activation of the ALA neuron, which releases FLP-13 neuropeptides characterized by an amidated arginine-phenylalanine (RFamide) C-terminus motif. By performing an unbiased genetic screen for mutants that impair the somnogenic effects of FLP-13 neuropeptides, we identified the gene dmsr-1, which encodes a G-protein coupled receptor similar to an insect RFamide receptor. DMSR-1 is activated by FLP-13 peptides in cell culture, is required for SIS in vivo, is expressed non-synaptically in several wake-promoting neurons, and likely couples to a Gi/o heterotrimeric G-protein. Our data expand our understanding of how a single neuroendocrine cell coordinates an organism-wide behavioral response, and suggest that similar signaling principles may function in other organisms to regulate sleep during sickness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.253
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations78
Published2017
Admission routes1
Has abstractyes

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