Exercise training increases branched-chain oxoacid dehydrogenase kinase content in human skeletal muscle
Bibliographic record
Abstract
The branched-chain oxoacid dehydrogenase complex (BCOAD) is rate determining for the oxidation of branched-chain amino acids (BCAAs) in skeletal muscle. Exercise training blunts the acute exercise-induced activation of BCOAD (BCOADa) in human skeletal muscle (McKenzie S, Phillips SM, Carter SL, Lowther S, Gibala MJ, Tarnopolsky MA. Am J Physiol Endocrinol Metab 278: E580-E587, 2000); however, the mechanism is unknown. We hypothesized that training would increase the muscle protein content of BCOAD kinase, the enzyme responsible for inactivation of BCOAD by phosphorylation. Twenty subjects [23 +/- 1 yr; peak oxygen uptake (.VO(2peak)) = 41 +/- 2 ml.kg(-1).min(-1)] performed 6 wk of either high-intensity interval or continuous moderate-intensity training on a cycle ergometer (n = 10/group). Before and after training, subjects performed 60 min of cycling at 65% of pretraining .VO(2peak), and needle biopsy samples (vastus lateralis) were obtained before and immediately after exercise. The effect of training was demonstrated by an increased .VO(2peak), increased citrate synthase maximal activity, and reduced muscle glycogenolysis during exercise, with no difference between groups (main effects, P < 0.05). BCOADa was lower after training (main effect, P < 0.05), and this was associated with a approximately 30% increase in BCOAD kinase protein content (main effect, P < 0.05). We conclude that the increased protein content of BCOAD kinase may be involved in the mechanism for reduced BCOADa after exercise training in human skeletal muscle. These data also highlight differences in models used to study the regulation of skeletal muscle BCAA metabolism, since exercise training was previously reported to increase BCOADa during exercise and decrease BCOAD kinase content in rats (Fujii H, Shimomura Y, Murakami T, Nakai N, Sato T, Suzuki M, Harris RA. Biochem Mol Biol Int 44: 1211-1216, 1998).
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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".