Weight loss induces changes in adaptive thermogenesis in female and male physique athletes
Bibliographic record
Abstract
Physique athletes lose substantial weight preparing for competitions, potentially altering systemic metabolism. We investigated sex differences in body composition, resting energy expenditure (REE), and appetite-regulating and thyroid hormone changes during a competition preparation among drug-free physique athletes. The participants were female (10 competing (COMP) and 10 nondieting controls (CTRL)) and male (13 COMP and 10 CTRL) physique athletes. COMP were tested before they started their diet 23 weeks before competing (PRE), during their diet one week before competing (MID), and 23 weeks after competing (POST), whereas CTRL were tested at similar intervals but did not diet. Measurements included body composition by dual-energy X-ray absorptiometry, muscle size, and subcutaneous fat thickness (SFA) by ultrasound, REE by indirect calorimetry, circulating ghrelin, leptin T3, and T4 hormone analysis. Fat mass (FM) and SFA decreased in both sexes ( p < 0.001), while males ( p < 0.001) lost more lean mass (LM) than females ( p < 0.05). Weight loss, decreased energy intake, and increased aerobic exercise ( p < 0.05) led to decreased LM- and FM-adjusted REE ( p < 0.05), reflecting metabolic adaptation. Absolute leptin levels decreased in both sexes ( p < 0.001) but more among females ( p < 0.001) due to higher baseline leptin levels. These changes occurred with similar decreases in T3 ( p < 0.001) and resting heart rate ( p < 0.01) in both sexes. CTRL, who were former or upcoming physique athletes, showed no systematic changes in any measured variables. In conclusion, while dieting, female and male physique athletes experience REE and hormonal changes leading to adaptive thermogenesis. However, responses seemed temporary as they returned toward baseline after the recovery phase. ClinicalTrials.gov (NCT04392752).
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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 | 0.000 |
| 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".