Effect of strength training combined with antioxidant supplementation on muscular performance
Bibliographic record
Abstract
This was a placebo-controlled randomized study that aimed to investigate the effects of strength training (ST) combined with antioxidant supplementation on muscle performance and thickness. Forty-two women (age, 23.8 ± 2.7 years; body mass, 58.7 ± 11.0 kg; height, 1.63 ± 0.1 m) were allocated into 3 groups: vitamins (n = 15), placebo (n = 12), or control (n = 15). The vitamins and placebo groups underwent an ST program, twice a week, for 10 weeks. The vitamins group was supplemented with vitamins C (1 g/day) and E (400 IU/day) during the ST period. Before and after training, peak torque (PT) and total work (TW) were measured on an isokinetic dynamometer, and quadriceps muscle thickness (MT) was assessed by ultrasound. Mixed-factor ANOVA was used to analyze data and showed a significant group × time interaction for PT and TW. Both the vitamins (37.2 ± 5.4 to 40.3 ± 5.6 mm) and placebo (39.7 ± 5.2 to 42.5 ± 5.6 mm) groups increased MT after the intervention (P < 0.05) with no difference between them. The vitamins (146.0 ± 29.1 to 170.1 ± 30.3 N·m) and placebo (158.9 ± 22.4 to 182.7 ± 23.2 N·m) groups increased PT after training (P < 0.05) and PT was higher in the placebo compared with the control group (P = 0.01). The vitamins (2068.3 ± 401.2 to 2295.5 ± 426.8 J) and placebo (2165.1 ± 369.5 to 2480.8 ± 241.3 J) groups increased TW after training (P < 0.05) and TW was higher in the placebo compared with the control group (P = 0.01). Thus, chronic antioxidant supplementation may attenuate peak torque and total work improvement in young women after 10 weeks of ST.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".