Vitamin and mineral supplementation effect on muscular activity and cycling efficiency in master athletes
Bibliographic record
Abstract
The influence of vitamin and mineral complex supplementation on muscular activity and cycling efficiency was examined in elderly endurance-trained master athletes during a heavy cycling trial. Master athletes were randomly assigned in a double-blind process to 1 of 2 treatment groups: antioxidant supplementation (n = 8: As group) or placebo (n = 8: Pl group) for 21 days. After that time, each subject had to perform a 10-min session of cycling on a cycloergometer at a heavy constant intensity. Twenty-four to 48 h after this session, subjects performed an isometric maximal voluntary contraction before and immediately after a fatiguing strength training (leg press exercise) and the same 10-min cycling test after fatigue. Isometric maximal voluntary force (MVF) of knee extensors was assessed before and after fatigue. Electromyographic (EMG) activity of the vastus medialis, the vastus lateralis (VL), and the biceps femoris was recorded with surface EMG. The knee-extensors MVF after the fatiguing exercise was reduced in similar proportions for both groups (As, -10.9%; Pl, -11.3%, p < 0.05). This MVF loss was associated with a significant reduction in EMG frequency parameters for both groups, with a lower decrease for the As group. Muscular activity and cycling efficiency during the cycling bouts were affected by the treatment. Cycling efficiency decreased significantly and the oxygen uptake slow component was higher after the fatiguing exercise for both groups. Furthermore, a decrease in cycling efficiency was associated with an increase in VL activity. However, these changes were significantly lower for the As group. The results of the present study indicate an overall positive effect of vitamin and mineral complex supplementation on cycling efficiency after fatigue, in the endurance-trained elderly.
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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 | 0.000 | 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".