Juçara (<i>Euterpe edulis</i> Martius) improves time-to-exhaustion cycling performance and increased reduced glutathione: a randomized, placebo-controlled, crossover, and triple-blind study
Bibliographic record
Abstract
To examine the effects of 7-days juçara powder (JP) intake on oxidative stress biomarkers and endurance and sprint cycling performances. In a randomized, placebo-controlled, crossover, and triple-blind study, 20 male trained cyclists were assigned to intake 10 g of JP (240 mg anthocyanins) or placebo (PLA) for 7 days and performed a cycling time-to-exhaustion (TTE). A 5 s cycling sprint was performed before and after the cycling TTE. Blood oxidative stress biomarkers and lactate concentration where evaluated 1 h before (T-1), immediately after (T0), and 1 h after (T1) the cycling TTE. The mean duration time for the cycling TTE was 8.4 ± 6.0% (63 ± 17 s) longer in the JP condition (JP: 751 ± 283 s) compared to PLA (688 ± 266 s) ( P < 0.019). Two-way repeated measures Analysis of variance showed an increase in the JP condition for reduced glutathione (GSH) ( P = 0.049) at T0 ( P = 0.039) and T1 ( P = 0.029) compared to PLA with a moderate effect size at T0 ( d = 0.61) and T1 ( d = 0.57). Blood lactate levels increased over time in both conditions ( P ≤ 0.001). No differences were observed for the post-TTE sprint fatigue index, total phenols, protein carbonyls, and glutathione peroxidase activity. Seven-day intake of JP improved cycling endurance performance and increased GSH levels but had no effect on lactate and cycling sprint-induced fatigue.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".