Effects of Post-Exercise Whey Protein Consumption on Recovery Indices in Adolescent Swimmers
Bibliographic record
Abstract
Purpose: This study examined the effect of whey protein consumption following high-intensity interval swimming (HIIS) on muscle damage, inflammatory cytokines and performance in adolescent swimmers. Methods: Fifty-four swimmers (11–17 years-old) were stratified by age, sex and body mass to a whey protein (PRO), isoenergetic carbohydrate (CHO) or a water/placebo (H2O) group. Following baseline blood samples (06:00 h) and a standardised breakfast, participants performed a maximal 200 m swim, followed by HIIS. A total of two post-exercise boluses were consumed following HIIS and ~5 h post-baseline. Blood and 200 m performance measurements were repeated at 5 h, 8 h and 24 h from baseline. Muscle soreness was assessed at 24 h. Creatine kinase (CK), interleukin-6 (IL-6), interleukin-10 (IL-10) and tumor necrosis factor-alpha (TNF-α) were measured in plasma. Results: No difference in 200 m swim performance was observed between groups. CK activity was elevated at 5 h compared to baseline and 24 h and at 8 h compared to all other timepoints, with no differences between groups. Muscle soreness was lower in PRO compared to H2O (p = 0.04). Anti-inflammatory IL-10 increased at 8 h in PRO, while it decreased in CHO and H2O. Conclusions: Post-exercise consumption of whey protein appears to have no additional benefit on recovery indices following HIIS compared to isoenergetic amounts of carbohydrate in adolescent swimmers. However, it may assist with the acute-inflammatory response.
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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".