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Record W2097125189 · doi:10.1242/dev.02300

FGF negatively regulates muscle membrane extension in<i>Caenorhabditis elegans</i>

2006· article· en· W2097125189 on OpenAlexaff
Scott J. Dixon, Mariam P. Alexander, Raynah Fernandes, Nicole Ricker, Peter J. Roy

Bibliographic record

VenueDevelopment · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyCell biologyCaenorhabditis elegansMyocyteNeuromuscular junctionLamininPhenotypeFibroblast growth factorAnatomyGeneBiochemistryReceptorNeuroscienceExtracellular matrix

Abstract

fetched live from OpenAlex

Striated muscles from Drosophila and several vertebrates extend plasma membrane to facilitate the formation of the neuromuscular junction (NMJ) during development. However, the regulation of these membrane extensions is poorly understood. In C. elegans, the body wall muscles (BWMs) also have plasma membrane extensions called muscle arms that are guided to the motor axons where they form the postsynaptic element of the NMJ. To investigate the regulation of muscle membrane extension, we screened 871 genes by RNAi for ectopic muscle membrane extensions (EMEs) in C. elegans. We discovered that an FGF pathway, including let-756(FGF), egl-15(FGF receptor), sem-5(GRB2) and other genes negatively regulates plasma membrane extension from muscles. Although compromised FGF pathway activity results in EMEs, hyperactivity of the pathway disrupts larval muscle arm extension, a phenotype we call muscle arm extension defective or MAD. We show that expression of egl-15 and sem-5 in the BWMs are each necessary and sufficient to prevent EMEs. Furthermore, we demonstrate that let-756 expression from any one of several tissues can rescue the EMEs of let-756 mutants, suggesting that LET-756 does not guide muscle membrane extensions. Our screen also revealed that loss-of-function in laminin and integrin components results in both MADs and EMEs, the latter of which are suppressed by hyperactive FGF signaling. Our data are consistent with a model in which integrins and laminins are needed for directed muscle arm extension to the nerve cords, while FGF signaling provides a general mechanism to regulate muscle membrane extension.

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 score0.297
Threshold uncertainty score0.882

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 science0.0000.000
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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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

Citations31
Published2006
Admission routes1
Has abstractyes

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