Activation of mTOR signalling in young and old human skeletal muscle in response to combined resistance exercise and whey protein ingestion
Bibliographic record
Abstract
PURPOSE: To investigate the impact of whey protein ingestion and resistance exercise training on the phosphorylation of mRNA translational signalling proteins in the skeletal muscle of young and old men. METHODS: Sixteen healthy young (aged 18-25 years) and 15 healthy older men (aged 60-75 years) completed 12 weeks of resistance exercise and were randomly assigned to consume a whey protein (WPI) or placebo drink after each session. Muscle biopsies were collected before and 2 h after an acute exercise bout at the beginning and the end of training. RESULTS: All subjects significantly increased strength after following strength training. Phosphorylation of mTOR was significantly greater in the WPI groups compared with placebo for both younger and older subjects. Phosphorylation of p70(S6K), eIF4G, and 4EBP1 was greater for older subjects consuming WPI. Phosphorylation of rpS6, eIF4G, and 4EBP1 tended to increase in the younger subjects that had consumed WPI. Post-training, younger subjects demonstrated a similar pattern of mTOR phosphorylation as seen pre-training. In contrast, the initial heightened phosphorylation of mTOR, p70(S6K), rpS6, and eIF4G in older muscle to combined resistance exercise and WPI ingestion became less pronounced after repeated training sessions. CONCLUSIONS: In the untrained state, resistance exercise coupled with WPI increases the phosphorylation of proteins involved in mRNA translation compared with exercise alone. Post-training, WPI- and exercise-induced protein phosphorylation was reduced in older men, but not in younger men. Thus, strategies to induce hypertrophy should utilize protein and resistance training concurrently. Further investigations should delineate interventions that will maintain sensitivity to anabolic stimuli in older populations.
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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".