β-Alanine Supplementation Does Not Augment the Skeletal Muscle Adaptive Response to 6 Weeks of Sprint Interval Training
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Bibliographic record
Abstract
Sprint interval training (SIT), repeated bouts of high-intensity exercise, improves skeletal muscle oxidative capacity and exercise performance. β-alanine (β-ALA) supplementation has been shown to enhance exercise performance, which led us to hypothesize that chronic β-ALA supplementation would augment work capacity during SIT and augment training-induced adaptations in skeletal muscle and performance. Twenty-four active but untrained men (23 ± 2 yr; VO2peak = 50 ± 6 mL · kg(-1) · min(-1)) ingested 3.2 g/day of β-ALA or a placebo (PLA) for a total of 10 weeks (n = 12 per group). Following 4 weeks of baseline supplementation, participants completed a 6-week SIT intervention. Each of 3 weekly sessions consisted of 4-6 Wingate tests, i.e., 30-s bouts of maximal cycling, interspersed with 4 min of recovery. Before and after the 6-week SIT program, participants completed a 250-kJ time trial and a repeated sprint test. Biopsies (v. lateralis) revealed that skeletal muscle carnosine content increased by 33% and 52%, respectively, after 4 and 10 weeks of β-ALA supplementation, but was unchanged in PLA. Total work performed during each training session was similar across treatments. SIT increased markers of mitochondrial content, including cytochome c oxidase (40%) and β-hydroxyacyl-CoA dehydrogenase maximal activities (19%), as well as VO2peak (9%), repeated-sprint capacity (5%), and 250-kJ time trial performance (13%), but there were no differences between treatments for any measure (p < .01, main effects for time; p > .05, interaction effects). The training stimulus may have overwhelmed any potential influence of β-ALA, or the supplementation protocol was insufficient to alter the variables to a detectable extent.
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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 | 0.001 | 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) | 0.000 | 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 it