The Effect of Acute Taurine Ingestion on Endurance Performance and Metabolism in Well-Trained Cyclists
Bibliographic record
Abstract
This study examined whether acute taurine (T) ingestion before prolonged cycling would improve time-trial (TT) performance and alter whole-body fuel utilization compared with a control (CON) trial and a placebo (PL) trial in which participants were told they received taurine but did not. Eleven endurance-trained male cyclists (27.2 ± 1.5 yr, 74.3 ± 2.3 kg, 59.9 ± 2.3 ml · kg⁻¹ · min⁻¹; M ± SEM) completed 3 trials in a randomized, crossover, blinded design in which they consumed a noncaloric sweetened beverage with either 1.66 g of T or nothing added (CON, PL) 1 hr before exercise. Participants then cycled at 66.5% ± 1.9% VO(2max) for 90 min followed immediately by a TT (doing 5 kJ of work/kg body mass as fast as possible). Data on fluid administration, expired gas, heart rate, and ratings of perceived exertion were collected at 15-min intervals during the 90-min cycling ride, but there were no differences recorded between trials. There was no difference in TT performance between any of the 3 trials (1,500 ± 87 s). Average carbohydrate (T 2.73 ± 0.21, CON 2.88 ± 0.19, PL 2.89 ± 0.20 g/min) and fat (T 0.45 ± 0.05, CON 0.39 ± 0.04, PL 0.39 ± 0.05 g/min) oxidation rates were unaffected by T supplementation. T ingestion resulted in a 16% increase (5 g, ~84 kJ; p < .05) in total fat oxidation over the 90-min exercise period compared with CON and PL. The acute ingestion of 1.66 g of T before exercise did not enhance TT performance but did result in a small but significant increase in fat oxidation during submaximal cycling in endurance-trained cyclists.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".