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The utility of resistance exercise training and amino acid supplementation for reversing age-associated decrements in muscle protein mass and function

2000· review· en· W2088664384 on OpenAlexaff
Gianni Parise, Kevin E. Yarasheski

Bibliographic record

VenueCurrent Opinion in Clinical Nutrition & Metabolic Care · 2000
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMcMaster University
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsSarcopeniaSkeletal muscleMedicineMuscle massMuscle powerResistance trainingMuscle proteinMuscle strengthPhysical medicine and rehabilitationPhysical therapyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Advancing age is associated with reduced skeletal muscle protein synthesis, altered expression of and chemical modifications to muscle proteins, reduced muscle strength, muscle strength per unit muscle mass and muscle power (sarcopenia). These age-associated impairments in the quantity and quality of contractile protein contribute to physical disability and frailty, a loss of independent function, the risk of falling and fractures, and escalating health-care costs. Progressive resistance exercise training is a potent, non-pharmacologic, efficacious therapy for the impairment in muscle quantity and quality in middle age and physically frail adults. Evidence is accumulating that dietary amino acid supplementation may also improve muscle protein balance in the elderly. Several potential cellular mechanisms for the loss of muscle protein and resistance exercise-induced improvements in muscle quantity and quality in elderly adults are reviewed.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.131
GPT teacher head0.420
Teacher spread0.289 · 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 designOther design
Domainnot available
GenreReview

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

Citations51
Published2000
Admission routes1
Has abstractyes

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