Mouth rinsing with a sweet solution increases energy expenditure and decreases appetite during 60 min of self-regulated walking exercise
Bibliographic record
Abstract
Carbohydrate mouth rinsing can improve endurance exercise performance and is most ergogenic when exercise is completed in the fasted state. This strategy may also be beneficial to increase exercise capacity and the energy deficit achieved during moderate-intensity exercise relevant to weight control when performed after an overnight fast. Eighteen healthy men (mean (SD); age, 23 (4) years; body mass index, 23.1 (2.4) kg·m−2) completed a familiarisation trial and 3 experimental trials. After an overnight fast, participants performed 60 min of treadmill walking at a speed that equated to a rating of perceived exertion of 13 (“fairly hard”). Participants manually adjusted the treadmill speed to maintain this exertion. Mouth rinses for the experimental trials contained either a 6.4% maltodextrin solution with sweetener (CHO), a taste-matched placebo (PLA), or water (WAT). Appetite ratings were collected using visual analogue scales and exercise energy expenditure and substrate oxidation were calculated from online gas analysis. Increased walking distance during CHO and PLA induced greater energy expenditure compared with WAT (mean difference (90% confidence interval); 79 (60) kJ, P = 0.035, d = 0.24; and 90 (63) kJ, P = 0.024, d = 0.27, respectively). Appetite area under the curve was lower in CHO and PLA than WAT (8 (6) mm, P = 0.042, d = 0.43; and 6 (8) mm, P = 0.201, d = 0.32, respectively). Carbohydrate oxidation was higher in CHO than PLA and WAT (7.3 (6.7) g, P = 0.078, d = 0.47; and 10.1 (6.5) g, P = 0.015, d = 0.81, respectively). This study provides novel evidence that mouth rinsing with a sweetened solution may promote a greater energy deficit during moderate-exertion walking exercise by increasing energy expenditure and decreasing appetite. A placebo effect may have contributed to these benefits.
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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) | 0.001 | 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) | 0.002 | 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".