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Record W7067609376

Morphological and functional remodelling of the neuromuscular junction by skeletal muscle PGC-1 alpha

2023· article· en· W7067609376 on OpenAlexfundno aff

Bibliographic record

VenueidUS (Universidad de Sevilla) · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsnot available
FundersNeuromuscular Research Association BaselMinisterio de Ciencia e InnovaciónSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMcGill UniversityTerry Fox FoundationUniversität BaselStiftung für die Erforschung der MuskelkrankheitenMuscular Dystrophy AssociationCanadian Institutes of Health ResearchUnited Mitochondrial Disease FoundationNational Science Foundation
KeywordsSkeletal muscleNeuromuscular junctionGenetically modified mousePlasticityMyocyteTransgeneReceptorAlpha (finance)Muscle contraction
DOInot available

Abstract

fetched live from OpenAlex

The neuromuscular junction (NMJ) exhibits high morphological and functional plasticity. In
\nthe mature muscle, the relative levels of physical activity are the major determinants of NMJ
\nfunction. Classically, motor neuron-mediated activation patterns of skeletal muscle have been
\nthought of as the major drivers of NMJ plasticity and the ensuing fibre-type determination in
\nmuscle. Here we use muscle-specific transgenic animals for the peroxisome proliferatoractivated receptor g co-activator 1a (PGC-1a) as a genetic model for trained mice to elucidate
\nthe contribution of skeletal muscle to activity-induced adaptation of the NMJ. We find that
\nmuscle-specific expression of PGC-1a promotes a remodelling of the NMJ, even in the
\nabsence of increased physical activity. Importantly, these plastic changes are not restricted to
\npost-synaptic structures, but extended to modulation of presynaptic cell morphology and
\nfunction. Therefore, our data indicate that skeletal muscle significantly contributes to the
\nadaptation of the NMJ subsequent to physical activity

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.268

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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