Resistance exercise enhances mTOR and MAPK signalling in human muscle over that seen at rest after bolus protein ingestion
Bibliographic record
Abstract
AIM: Feeding protein after resistance exercise enhances the magnitude and duration of myofibrillar protein synthesis (MPS) over that induced by feeding alone. We hypothesized that the underlying mechanism for this would be a greater and prolonged phosphorylation of signalling involved in protein translation. METHODS: Seven healthy young males performed unilateral resistance exercise followed immediately by the ingestion of 25 g of whey protein to maximally stimulate MPS in a rested and exercised leg. RESULTS: Phosphorylation of p70 ribosomal protein S6 kinase (p70S6K) was elevated (P<0.05) above fasted at 1 h at rest whereas it was elevated at 1, 3 and 5 h after exercise with protein ingestion and displayed a similar post-exercise time course to that shown by MPS. Extracellular regulated kinase1/2 (ERK1/2) and p90 ribosomal S6 kinase (p90RSK) phosphorylation were unaltered after protein ingestion at rest but were elevated (P < 0.05) above fasted early in recovery (1 h) and were greater for the exercised-fed leg than feeding alone (main effect; P < 0.01). Eukaryotic elongation factor 2 (eEF2) phosphorylation was also less (main effect; P<0.05) in the exercised-fed leg than in the rested leg suggesting greater activity after exercise. Eukaryotic initiation 4E binding protein-1 (4EBP-1) phosphorylation was increased (P<0.05) above fasted to the same extent in both conditions. CONCLUSION: Our data suggest that resistance exercise followed by protein feeding stimulates MPS over that induced by feeding alone in part by enhancing the phosphorylation of select proteins within the mammalian target of rapamycin (p70S6K, eEF2) and by activating proteins within the mitogen-activated protein kinase (ERK1/2, p90RSK) signalling.
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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) | 0.002 | 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".