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Record W2291867385 · doi:10.1152/ajpcell.00285.2015

Muscle RANK is a key regulator of Ca<sup>2+</sup> storage, SERCA activity, and function of fast-twitch skeletal muscles

2016· article· en· W2291867385 on OpenAlexafffund
Sébastien S. Dufresne, Nicolas A. Dumont, Antoine Boulanger‐Piette, Val A. Fajardo, Daniel Gamu, Sandrine-Aurélie Kake-Guena, Rares Ovidiu David, Patrice Bouchard, Éliane Lavergne, Josef Penninger, Paul C. Pape, A. Russell Tupling, Jérôme Frenette

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2016
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversité LavalUniversity of WaterlooCentre hospitalier de l'Université LavalUniversité de SherbrookeCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health Research
KeywordsSERCARegulatorSkeletal muscleRank (graph theory)Function (biology)Key (lock)ChemistryInternal medicineAnatomyCell biologyBiologyMathematicsBiochemistryMedicineCombinatoricsGene

Abstract

fetched live from OpenAlex

Receptor-activator of nuclear factor-κB (RANK), its ligand RANKL, and the soluble decoy receptor osteoprotegerin are the key regulators of osteoclast differentiation and bone remodeling. Here we show that RANK is also expressed in fully differentiated myotubes and skeletal muscle. Muscle RANK deletion has inotropic effects in denervated, but not in sham, extensor digitorum longus (EDL) muscles preventing the loss of maximum specific force while promoting muscle atrophy, fatigability, and increased proportion of fast-twitch fibers. In denervated EDL muscles, RANK deletion markedly increased stromal interaction molecule 1 content, a Ca(2+)sensor, and altered activity of the sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA) modulating Ca(2+)storage. Muscle RANK deletion had no significant effects on the sham or denervated slow-twitch soleus muscles. These data identify a novel role for RANK as a key regulator of Ca(2+)storage and SERCA activity, ultimately affecting denervated skeletal muscle function.

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 score0.669
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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

Citations76
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Physiology-Cell PhysiologySame topicAdipose Tissue and MetabolismFrench-language works237,207