Stimulation of muscle anabolism by resistance exercise and ingestion of leucine plus protein
Bibliographic record
Abstract
Leucine is known to stimulate muscle protein synthesis and anabolism. However, evidence for the efficacy of additional leucine to enhance the response of muscle anabolism to resistance exercise and protein ingestion is unclear. Thus, we investigated the response of net muscle protein balance to ingestion of additional leucine with protein in association with resistance exercise. Two groups of untrained subjects performed an intense bout of leg resistance exercise following ingestion of 1 of 2 drinks: flavored water (PL); or 16.6 g of whey protein + 3.4 g of leucine (W+L). Arteriovenous amino acid balance across the leg was measured to assess the anabolic response of muscle in each group. Arterial amino acid concentrations increased in response to ingestion of W+L. Amino acid concentrations peaked between 60 and 120 min after ingestion, and then declined to baseline values. Valine concentration decreased to levels significantly lower than baseline. Net balance of leucine, threonine, and phenylalanine did not change following PL ingestion, but increased and remained elevated above baseline for 90-120 min following W+L ingestion. Leucine (138 +/- 37 and -23 +/- 23 mg), phenylalanine (58 +/- 28 and -38 +/- 14 mg), and threonine (138 +/- 37 and -23 +/- 23 mg) uptake was greater for W+L than for PL over the 5.5 h following drink ingestion. Our results indicate that the whey protein plus leucine in healthy young volunteers results in an anabolic response in muscle that is not greater than the previously reported response to whey protein alone.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".