Resveratrol supplementation does not augment performance adaptations or fibre-type–specific responses to high-intensity interval training in humans
Bibliographic record
Abstract
The present study examined the effect of concurrent exercise training and daily resveratrol (RSV) supplementation (150 mg) on training-induced adaptations following low-dose high-intensity interval training (HIIT). Sixteen recreationally active (∼22 years, ∼51 mL·kg(-1)·min(-1)) men were randomly assigned in a double-blind fashion to either the RSV or placebo group with both groups performing 4 weeks of HIIT 3 days per week. Before and after training, participants had a resting muscle biopsy taken, completed a peak oxygen uptake test, a Wingate test, and a submaximal exercise test. A main effect of training (p < 0.05) and interaction effect (p < 0.05) on peak aerobic power was observed; post hoc pairwise comparisons revealed that a significant (p < 0.05) increase occurred in the placebo group only. Main effects of training (p < 0.05) were observed for both peak oxygen uptake (placebo - pretraining: 51.3 ± 1.8, post-training: 54.5 ± 1.5 mL·kg(-1)·min(-1), effect size (ES) = 0.93; RSV - pretraining: 49.6 ± 2.2, post-training: 52.3 ± 2.5 mL·kg(-1)·min(-1), ES = 0.50) and Wingate peak power (placebo: pretraining: 747 ± 39, post-training: 809 ± 31 W, ES = 0.84; RSV - pretraining: 679 ± 39, post-training: 691 ± 43 W, ES = 0.12). Fibre-type distribution was unchanged, while a main effect of training (p < 0.05) was observed for succinate dehydrogenase activity and glycogen content, but not α-glycerophosphate dehydrogenase activity or intramuscular lipids in type I and IIA fibres. The fold change in PGC-1α, SIRT1, and SOD2 gene expression following training was significantly (p < 0.05) lower in the RSV group than placebo. These results suggest that concurrent exercise training and RSV supplementation may alter the normal training response induced by low-volume HIIT.
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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) | 0.001 | 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 | 0.000 | 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".