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Record W2135546372 · doi:10.1002/mus.24906

High‐intensity resistance training attenuates dexamethasone‐induced muscle atrophy

2015· article· en· W2135546372 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMuscle & Nerve · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Waterloo
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsAtrophyResistance trainingDexamethasoneMuscle atrophyMedicineIntensity (physics)Physical medicine and rehabilitationInternal medicinePhysics

Abstract

fetched live from OpenAlex

INTRODUCTION: In this study we investigated the effects of high-intensity resistance training (RT) on dexamethasone (DEX)-induced muscle atrophy in flexor hallucis longus (FHL), tibialis anterior (TA), and soleus (SOL) muscles. METHODS: Rats underwent either high-intensity RT or were kept sedentary. In the last 10 days they received either DEX (0.5 mg/kg/day, intraperitoneally) or saline. RESULTS: DEX reduced body weight (-21%), food intake (-28%), FHL and TA muscle mass (-20% and -18%, respectively), and increased muscle-specific ring finger 1 (MuRF-1) protein level (+37% and +45.5%). RT attenuated FHL muscle atrophy through a combination of low increase in MuRF-1 protein level (-3.5%) and significant increases in mammalian target of rapamycin (mTOR) (+63%) and p70S6K (+46% and +49% for control and DEX, respectively) protein levels. CONCLUSION: RT attenuated DEX-induced muscle atrophy through a combination of increases in mTOR and p70S6K protein levels and a low increase in MuRF-1 protein 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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score1.000

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 head0.044
GPT teacher head0.259
Teacher spread0.215 · 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