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Record W3200315391 · doi:10.1007/s40279-021-01510-0

Protein Requirements for Master Athletes: Just Older Versions of Their Younger Selves

2021· review· en· W3200315391 on OpenAlexaff
Daniel R. Moore

Bibliographic record

VenueSports Medicine · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Toronto
FundersGran Sasso Science InstitutePepsiCo
KeywordsAthletesAnabolismSports medicineMedicineSarcopeniaPhysical therapyMuscle massPopulationExercise physiologyPhysiologyGerontologyPhysical medicine and rehabilitationEndocrinology

Abstract

fetched live from OpenAlex

It is established that protein requirements are elevated in athletes to support their training and post-exercise recovery and adaptation, especially within skeletal muscle. However, research on the requirements for this macronutrient has been performed almost exclusively in younger athletes, which may complicate their translation to the growing population of Master athletes (i.e. > 35 years old). In contrast to older (> 65 years) untrained adults who typically demonstrate anabolic resistance to dietary protein as a primary mediator of the 'normal' age-related loss of muscle mass and strength, Master athletes are generally considered successful models of aging as evidenced by possessing similar body composition, muscle mass, and aerobic fitness as untrained adults more than half their age. The primary physiology changes considered to underpin the anabolic resistance of aging are precipitated or exacerbated by physical inactivity, which has led to higher protein recommendations to stimulate muscle protein synthesis in older untrained compared to younger untrained adults. This review puts forth the argument that Master athletes have similar muscle characteristics, physiological responses to exercise, and protein metabolism as young athletes and, therefore, are unlikely to have protein requirements that are different from their young contemporaries. Recommendations for protein amount, type, and pattern will be discussed for Master athletes to enhance their recovery from and adaptation to resistance and endurance training.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.070
GPT teacher head0.335
Teacher spread0.264 · 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 designNot applicable
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

Citations25
Published2021
Admission routes1
Has abstractyes

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