Green Tea Extract Ingestion Decreases Respiratory Exchange Ratio During Recovery From High-intensity Interval Exercise.
Bibliographic record
Abstract
Green tea extract (GTE) ingestion has been shown to increase energy expenditure and reduce respiratory exchange ratio (RER) at rest. The high concentration of catechins in green tea is hypothesized to inhibit catechol-O-methyltransferase (COMT), an enzyme that regulates catecholamine degradation, and thus could enhance sympathetic stimulation. Data are equivocal regarding the effects of GTE ingestion on metabolism during exercise and no studies have examined the effect on fuel utilization during recovery from exercise. PURPOSE: To examine the effect of a single dose of GTE ingestion on substrate utilization during recovery from an acute bout of high-intensity interval exercise. METHODS: Active men and women (n=10 each; 26±1 and 25±1 y, respectively) were matched for initial fitness based on VO2peak per fat-free mass (56±2 and 60±2 ml/kg fat free mass/min, respectively; p > 0.05). Subjects ingested a single dose of GTE (700 mg) or placebo (PLA) 1.5 h prior to exercise in a double-blind, crossover design. Exercise involved 10 x 1 min cycling efforts at ∼70% of peak power output (PPO) elicited during a ramp VO2peak test, interspersed with 1 min of unloaded cycling for recovery. Following exercise subjects rested supine in a dark and quiet room for 70 min while respiratory gases were collected via a ventilated hood. RESULTS: Exercise workload was 236±8 and 186±5 W for men and women, respectively, which corresponded to a relative work intensity of 69% of PPO in both groups. RER during recovery from exercise was lower after GTE ingestion compared to PLA (0.76 ± 0.01 vs. 0.79 ± 0.02; P < 0.05, main effect for treatment), with no difference between sexes. CONCLUSION: A single dose of GTE reduced RER during recovery from an acute bout of high-intensity interval exercise. These data suggest GTE alters post-exercise fuel utilization, potentially mediated through enhanced sympathetic stimulation, however determination of precise mechanisms is warranted. Supported by NSERC, Canada.
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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 | 0.000 |
| 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 | 0.001 |
| 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".