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 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) | 0.001 | 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".