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Record W2970087283 · doi:10.1152/ajpcell.00209.2019

Molecular regulation of human skeletal muscle protein synthesis in response to exercise and nutrients: a compass for overcoming age-related anabolic resistance

2019· review· en· W2970087283 on OpenAlexaff
Nathan Hodson, Daniel W. D. West, Andrew Philp, Nicholas A. Burd, Daniel R. Moore

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAnabolismmTORC1Skeletal muscleSarcopeniaBiologyAnabolic AgentsAdaptive responseBioinformaticsEndocrinologyCell biologyPI3K/AKT/mTOR pathwayGeneticsSignal transduction

Abstract

fetched live from OpenAlex

Skeletal muscle mass, a strong predictor of longevity and health in humans, is determined by the balance of two cellular processes, muscle protein synthesis (MPS) and muscle protein breakdown. MPS seems to be particularly sensitive to changes in mechanical load and/or nutritional status; therefore, much research has focused on understanding the molecular mechanisms that underpin this cellular process. Furthermore, older individuals display an attenuated MPS response to anabolic stimuli, termed anabolic resistance, which has a negative impact on muscle mass and function, as well as quality of life. Therefore, an understanding of which, if any, molecular mechanisms contribute to anabolic resistance of MPS is of vital importance in formulation of therapeutic interventions for such populations. This review summarizes the current knowledge of the mechanisms that underpin MPS, which are broadly divided into mechanistic target of rapamycin complex 1 (mTORC1)-dependent, mTORC1-independent, and ribosomal biogenesis-related, and describes the evidence that shows how they are regulated by anabolic stimuli (exercise and/or nutrition) in healthy human skeletal muscle. This review also summarizes evidence regarding which of these mechanisms may be implicated in age-related skeletal muscle anabolic resistance and provides recommendations for future avenues of research that can expand our knowledge of this area.

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)0.001
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 score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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.

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

Citations71
Published2019
Admission routes1
Has abstractyes

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