Nutritional regulation of muscle protein synthesis with resistance exercise: strategies to enhance anabolism
Bibliographic record
Abstract
Provision of dietary amino acids increases skeletal muscle protein synthesis (MPS), an effect that is enhanced by prior resistance exercise. As a fundamentally necessary process in the enhancement of muscle mass, strategies to enhance rates of MPS would be beneficial in the development of interventions aimed at increasing skeletal muscle mass particularly when combined with chronic resistance exercise. The purpose of this review article is to provide an update on current findings regarding the nutritional regulation of MPS and highlight nutrition based strategies that may serve to maximize skeletal muscle protein anabolism with resistance exercise. Such factors include timing of protein intake, dietary protein type, the role of leucine as a key anabolic amino acid, and the impact of other macronutrients (i.e. carbohydrate) on the regulation of MPS after resistance exercise. We contend that nutritional strategies that serve to maximally stimulate MPS may be useful in the development of nutrition and exercise based interventions aimed at enhancing skeletal muscle mass which may be of interest to elderly populations and to athletes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".