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Record W4402990627 · doi:10.1093/genetics/iyae141

Neuropeptide signaling network of <i>Caenorhabditis elegans</i>: from structure to behavior

2024· review· en· W4402990627 on OpenAlexfundno aff
Jan Watteyne, Aleksandra Chudinova, Lidia Ripoll-Sánchez, William R Schafer, Isabel Beets

Bibliographic record

VenueGenetics · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersMedical Research CouncilVlaamse regeringEuropean Research CouncilMedical Research Council CanadaFonds Wetenschappelijk Onderzoek
KeywordsCaenorhabditis elegansBiologyNeuropeptideNeuroscienceNervous systemCaenorhabditisSignal transductionG protein-coupled receptorCell signalingNeuropeptide Y receptorCell biologyComputational biologyReceptorGeneticsGene

Abstract

fetched live from OpenAlex

Neuropeptides are abundant signaling molecules that control neuronal activity and behavior in all animals. Owing in part to its well-defined and compact nervous system, Caenorhabditis elegans has been one of the primary model organisms used to investigate how neuropeptide signaling networks are organized and how these neurochemicals regulate behavior. We here review recent work that has expanded our understanding of the neuropeptidergic signaling network in C. elegans by mapping the evolutionary conservation, the molecular expression, the receptor-ligand interactions, and the system-wide organization of neuropeptide pathways in the C. elegans nervous system. We also describe general insights into neuropeptidergic circuit motifs and the spatiotemporal range of peptidergic transmission that have emerged from in vivo studies on neuropeptide signaling. With efforts ongoing to chart peptide signaling networks in other organisms, the C. elegans neuropeptidergic connectome can serve as a prototype to further understand the organization and the signaling dynamics of these networks at organismal level.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.021
GPT teacher head0.289
Teacher spread0.268 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2024
Admission routes1
Has abstractyes

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