Leucine metabolites do not induce changes in phase angle, bioimpedance vector analysis patterns, and strength in resistance trained men
Bibliographic record
Abstract
We aimed to assess the effects of off-the-shelf leucine metabolite supplements on phase angle (PhA), bioimpedance vector analysis (BIVA) patterns and strength during an 8-week resistance training protocol. Fifty-three male participants were allocated into 4 groups: α-hydroxyisocaproic acid (n = 12, age = 30.9 ± 9.3 years), β-hydroxy-β-methylbutyrate free acid (n = 12, age = 31.0 ± 9.3 years), calcium β-hydroxy-β-methylbutyrate (n = 15, age = 32.1 ± 5.2 years) or placebo (n = 14, age = 28.9 ± 6.6 years). Bioimpedance parameters and 1-repetition maximum (1RM) for back squat and bench press were assessed at baseline and at the end of weeks 4 and 8. Additionally, fat-free mass and fat mass were evaluated by dual-energy X-ray absorptiometry. No statistically group by time interactions were found, even adjusting for age. PhA and vector did not change over the training period, while time-dependent increases were observed for 1RM back squat and 1RM bench press. A direct association was observed between PhA and 1RM bench press changes (whole sample), while PhA and strength were correlated throughout the study, even when adjusting for fat-free mass and percentage of fat mass. Leucine metabolites have no effect on PhA, BIVA patterns or strength during an 8-week resistance training program, in resistance trained subjects. The trial was registered at ClincicalTrials.gov: NCT03511092. Novelty: Supplementation with leucine metabolites is not a supplementation strategy that improves bioelectrical phase angle, cellular health, and strength after an 8-week resistance training program. When consuming a high protein diet, none of the α-hydroxyisocaproic acid, β-hydroxy-β-methylbutyrate free acid, and calcium β-hydroxy-β-methylbutyrate metabolites resulted in an ergogenic effect in resistance trained men.
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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 | 0.001 |
| 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".