Carbohydrate metabolism during prolonged exercise and recovery: interactions between pyruvate dehydrogenase, fatty acids, and amino acids
Bibliographic record
Abstract
During prolonged exercise, carbohydrate oxidation may result from decreased pyruvate production and increased fatty acid supply and ultimately lead to reduced pyruvate dehydrogenase (PDH) activity. Pyruvate also interacts with the amino acids alanine, glutamine, and glutamate, whereby the decline in pyruvate production could affect tricarboxycylic acid cycle flux as well as gluconeogenesis. To enhance our understanding of these interactions, we studied the time course of changes in substrate utilization in six men who cycled at 44+/-1% peak oxygen consumption (mean+/-SE) until exhaustion (exhaustion at 3 h 23 min+/-11 min). Femoral arterial and venous blood, blood flow measurements, and muscle samples were obtained hourly during exercise and recovery (3 h). Carbohydrate oxidation peaked at 30 min of exercise and subsequently decreased for the remainder of the exercise bout (P<0.05). PDH activity peaked at 2 h of exercise, whereas pyruvate production peaked at 1 h of exercise and was reduced (approximately 30%) thereafter, suggesting that pyruvate availability primarily accounted for reduced carbohydrate oxidation. Increased free fatty acid uptake (P<0.05) was also associated with decreasing PDH activity (P<0.05) and increased PDH kinase 4 mRNA (P<0.05) during exercise and recovery. At 1 h of exercise, pyruvate production was greatest and was closely linked to glutamate, which was the predominant amino acid taken up during exercise and recovery. Alanine and glutamine were also associated with pyruvate metabolism, and they comprised approximately 68% of total amino-acid release during exercise and recovery. Thus reduced pyruvate production was primarily associated with reduced carbohydrate oxidation, whereas the greatest production of pyruvate was related to glutamate, glutamine, and alanine metabolism in early exercise.
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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".