Sprint training reduces urinary purine loss following intense exercise in humans
Bibliographic record
Abstract
The influence of sprint training on endogenous urinary purine loss was examined in 7 active male subjects (age, 23.1 +/- 1.8 y; body mass, 76.1 +/- 3.1 kg; VO2 peak, 56.3 +/- 4.0 mL.kg-1.min-1). Each subject performed a 30 s sprint performance test (PT), before and after 7 d of sprint training. Training consisted of 15 sprints, each lasting 10 s, on an air-braked cycle ergometer performed twice each day. A rest period of 50 s separated each sprint during training. Sprint training resulted in a 20% higher muscle ATP immediately after PT, a lower IMP (57% and 89%, immediately after and 10 min after PT, respectively), and inosine accumulation (53% and 56%, immediately after and 10 min after the PT, respectively). Sprint training also attenuated the exercise-induced increases in plasma inosine, hypoxanthine (Hx), and uric acid during the first 120 min of recovery and reduced the total urinary excretion of purines (inosine + Hx + uric acid) in the 24 h recovery period following intense exercise. These results show that intermittent sprint training reduces the total urinary purine excretion after a 30 s sprint bout.
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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) | 0.000 | 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) | 0.000 | 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".