The efficacy of protein supplementation during recovery from muscle-damaging concurrent exercise
Bibliographic record
Abstract
This study investigated the effect of protein supplementation on recovery following muscle-damaging exercise, which was induced with a concurrent exercise design. Twenty-four well-trained male cyclists were randomised to 3 independent groups receiving 20 g protein hydrolysate, iso-caloric carbohydrate, or low-calorific placebo supplementation, per serve. Supplement serves were provided twice daily, from the onset of the muscle-damaging exercise, for a total of 4 days and in addition to a controlled diet (6 g·kg−1·day−1 carbohydrate, 1.2 g·kg−1·day−1 protein, remainder from fat). Following the concurrent exercise session at time-point 0 h, comprising a simulated high-intensity road cycling trial and 100 drop-jumps, recovery of outcome measures was assessed at 24, 48, and 72 h. The concurrent exercise protocol was deemed to have caused exercise-induced muscle damage (EIMD), owing to time effects (p < 0.001), confirming decrements in maximal voluntary contraction (peaking at 15% ± 10%) and countermovement jump performance (peaking at 8% ± 7%), along with increased muscle soreness, creatine kinase, and C-reactive protein concentrations. No group or interaction effects (p > 0.05) were observed for any of the outcome measures. The present results indicate that protein supplementation does not attenuate any of the indirect indices of EIMD imposed by concurrent exercise, when employing great rigour around the provision of a quality habitual diet and the provision of appropriate supplemental controls.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".