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Record W2136485284 · doi:10.1002/mus.24698

Hyperactive mTORC1 signaling is unaffected by metformin treatment in aged skeletal muscle

2015· article· en· W2136485284 on OpenAlexaff
Cory M. Dungan, Zhuyun Li, David C. Wright, David L. Williamson

Bibliographic record

VenueMuscle & Nerve · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsmTORC1MetforminP70-S6 Kinase 1EndocrinologySkeletal muscleInternal medicineSignal transductionPhosphorylationBiologyMedicineCell biologyPI3K/AKT/mTOR pathwayDiabetes mellitus

Abstract

fetched live from OpenAlex

INTRODUCTION: Appropriate activation of growth signaling pathways, specifically mammalian target of rapamycin complex 1 (mTORC1), is central to muscle mass and metabolism. The goal of these studies was to examine the effects of metformin on mTORC1 signaling in aged skeletal muscle in an attempt to normalize growth signaling. METHODS: Aged (23m) and young (3m) male mice were fed a low fat diet without or with 0.5% metformin for up to 8 weeks, then mTORC1-related signaling was examined in the plantar flexor complex. RESULTS: Metformin had no significant effect on lowering body weight or muscle mass in aged animals, nor altered p70 S6 Kinase 1 (S6K1) and 4E-binding protein 1 (4E-BP1) phosphorylation. However, it significantly (P < 0.05) reduced body weight and lowered S6K1 and rpS6 phosphorylation in the young. CONCLUSIONS: Collectively, these data suggest metformin is ineffective at normalizing growth signaling in aged skeletal muscle.

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 score0.470
Threshold uncertainty score0.905

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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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