Effects of β-hydroxybutyrate treatment on glycogen repletion and its related signaling cascades in epitrochlearis muscle during 120 min of postexercise recovery
Bibliographic record
Abstract
We investigated the effects of β-hydroxybutyrate (β-HB), the most abundant type of ketone body in mammals, on postexercise glycogen recovery in skeletal muscle by using an in vitro experimental model. Male ICR mice swam for 60 min and then their epitrochlearis muscles were removed and incubated with either physiological levels of glucose (8 mmol/L) and insulin (60 μU/mL) or glucose and insulin plus 1, 2, or 4 mmol/L of sodium β-HB. Four millimoles per liter β-HB had a significant positive effect on glycogen repletion in epitrochlearis muscle at 120 min after exercise (p < 0.01), while 2 mmol/L of β-HB showed a tendency to increase the glycogen level (p < 0.09), and 1 mmol/L of β-HB had no significant effect. We further investigated the effect of 4 mmol/L β-HB treatment on the signaling cascade related to glycogen repletion in the epitrochlearis muscles throughout a 120-min recovery period. After incubating the muscles in 4 mmol/L of β-HB for 15 min postexercise, the Akt substrate of 160 kDa Thr642 (p < 0.05) and Akt Thr308 (p < 0.05) phosphorylations were significantly increased compared with the control treatment. At the same time point, 5′-AMP–activated protein kinase and acetyl-coenzyme A carboxylase phosphorylations were significantly lower (p < 0.05) in the epitrochlearis muscle incubated with 4 mmol/L of β-HB than in the control muscle. Our results demonstrate that postexercise 4 mmol/L β-HB administration enhanced glycogen repletion in epitrochlearis muscle. Four millimoles per liter β-HB treatment was associated with alternation of the phosphorylated status of several proteins involved in glucose uptake and metabolic/energy homeostasis at the early stage of postexercise.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".