Three Weeks Daily Intake of Matcha Green Tea Powder Affects Substrate Oxidation during Moderate-Intensity Exercise in Females
Bibliographic record
Abstract
Artificial green tea extracts may enhance exercise-induced fat oxidation. Natural Matcha green tea consumption involves the ingestion of the powdered green tea leaves. We examined the effects of three weeks daily intake of Matcha green tea powder on substrate oxidation during moderate-intensity exercise in females. Females with a regular menstrual cycle (n = 12, age: 28 ± 10 yr, body mass: 69 ± 17 kg, height: 163 ± 6 cm) volunteered to complete an incremental walking test to determine the individual moderate exercise intensity (four metabolic equivalent) for the subsequent 30-min treadmill walk. The study had a randomized placebo-controlled cross-over design with participants tested between day 9 and 11 of the menstrual cycle (follicular phase). Participants consumed 3x1 gram capsules of Matcha premium grade, (OMGTea Ltd, UK) per day for three weeks, with the final dose (1 gram) two hours before the 30-min walk (walking speed: 5.8 ± 0.4 km·h−1). Matcha had no effect on physiological responses (e.g. heart rate, placebo: 127 ± 14; Matcha: 124 ± 14 beats·min−1, p = 0.154), but resulted in lower respiratory exchange ratio (placebo: 0.872 ± 0.040; Matcha: 0.839 ± 0.035) (p = 0.033), higher fat oxidation by 35 ± 47% (placebo: 0.21 ± 0.08; Matcha: 0.26 ± 0.06 g·min−1) (p = 0.034), and lower carbohydrate oxidation (placebo: 0.75 ± 0.21; Matcha: 0.60 ± 0.18 g·min−1) (p = 0.048) during the 30-min moderate-intensity walk. Energy expenditure was similar for both conditions. There was no significant correlation between body fat % and the absolute or relative change in Matcha-induced fat oxidation during exercise. Continuous intake of Matcha green tea effects exercise-induced metabolic responses by enhancing fat oxidation during moderate-intensity exercise in adult females, seemingly independent of body composition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".