Resistance exercise enhances myofibrillar protein synthesis with graded intakes of whey protein in older men
Bibliographic record
Abstract
Feeding stimulates robust increases in muscle protein synthesis (MPS); however, ageing may alter the anabolic response to protein ingestion and the subsequent aminoacidaemia. With this as background, we aimed to determine in the present study the dose-response of MPS with the ingestion of isolated whey protein, with and without prior resistance exercise, in the elderly. For the purpose of this study, thirty-seven elderly men (age 71 (sd 4) years) completed a bout of unilateral leg-based resistance exercise before ingesting 0, 10, 20 or 40 g of whey protein isolate (W0-W40, respectively). Infusion of l-[1-13C]leucine and l-[ring-13C6]phenylalanine with bilateral vastus lateralis muscle biopsies were used to ascertain whole-body leucine oxidation and 4 h post-protein consumption of MPS in the fed-state of non-exercised and exercised leg muscles. It was determined that whole-body leucine oxidation increased in a stepwise, dose-dependent manner. MPS increased above basal, fasting values by approximately 65 and 90 % for W20 and W40, respectively (P < 0·05), but not with lower doses of whey. While resistance exercise was generally effective at stimulating MPS, W20 and W40 ingestion post-exercise increased MPS above W0 and W10 exercised values (P < 0·05) and W40 was greater than W20 (P < 0·05). Based on the study, the following conclusions were drawn. At rest, the optimal whey protein dose for non-frail older adults to consume, to increase myofibrillar MPS above fasting rates, was 20 g. Resistance exercise increases MPS in the elderly at all protein doses, but to a greater extent with 40 g of whey ingestion. These data suggest that, in contrast to younger adults, in whom post-exercise rates of MPS are saturated with 20 g of protein, exercised muscles of older adults respond to higher protein doses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".