Low- and high-load resistance training exercise to volitional fatigue generate exercise-induced appetite suppression
Bibliographic record
Abstract
Research on exercise-induced appetite suppression often does not include resistance training (RT) exercise and only compared matched volumes. To compare the effects of low-load and high-load RT exercise completed to volitional fatigue on appetite-regulation. 11 resistance-trained males (24 ± 2 y) completed 3 sessions in a crossover experimental design: 1) control (CTRL); 2) RT exercise at 30% 1-repetition maximum (RM); and 3) RT exercise at 90% 1-RM. RT sessions consisted of 3 sets of 5 exercises completed to volitional fatigue. Acylated ghrelin, active glucagon-like peptide-1 (GLP-1), active peptide tyrosine (PYY), lactate, and subjective appetite perceptions were measured pre-exercise, 0-, 60-, and 120-min post-exercise. Energy intake was recorded the day before, of, and after each session. Lactate was elevated following both 30% (0-, 60-, 120-min post-exercise) and 90% (0-, 60-min post-exercise; P < 0.001, d > 3.92) versus CTRL, with 30% greater than 90% (0-min post-exercise; P = 0.011, d = 1.14). Acylated ghrelin was suppressed by 30% (P < 0.007, d > 1.22) and 90% (P < 0.028, d > 0.096) post-exercise versus CTRL, and 30% suppressed concentrations versus 90% (60-min post-exercise; P = 0.032, d = 0.95). There was no effect on PYY (P > 0.171, ηp2 <0.149) though GLP-1 was greater at 60-min post-exercise in 90% (P = 0.052, d = 0.86) versus CTRL. Overall appetite was suppressed 0-min post-exercise following 30% and 90% versus CTRL (P < 0.013, d > 1.10) with no other differences (P > 0.279, d < 0.56). There were no differences in energy intake (P > 0.101, ηp2 <0.319). RT at low- and high-loads to volitional fatigue induced appetite suppression coinciding with changes in acylated ghrelin though limited effects on anorexigenic hormones or free-living energy intake were present.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".