Pyruvate dehydrogenase kinase-4 contributes to the recirculation of gluconeogenic precursors during postexercise glycogen recovery
Bibliographic record
Abstract
During recovery from glycogen-depleting exercise, there is a shift from carbohydrate oxidation to glycogen resynthesis. The activity of the pyruvate dehydrogenase (PDH) complex may decrease to reduce oxidation of carbohydrates in favor of increasing gluconeogenic recycling of carbohydrate-derived substrates for this process. The precise mechanism behind this has yet to be elucidated; however, research examining mRNA content has suggested that the less-abundant pyruvate dehydrogenase kinase-4 (PDK4) may reduce PDH activation during exercise recovery. To investigate this, skeletal muscle and liver of wild-type (WT) and PDK4-knockout (PDK4-KO) mice were analyzed at rest (Rest), after exercise to exhaustion (Exh), and after 2 h of recovery with ad libitum feeding (Rec). Although there were no differences in exercise tolerance between genotypes, caloric consumption was doubled by PDK4-KO mice during Rec. Because of this, PDK4-KO mice at Rec supercompensated muscle glycogen to 120% of resting stores. Therefore, an extra group of PDK4-KO mice were pair-fed (PF) with WT mice during Rec for comparison. PF mice fully replenished muscle glycogen but recovered only 50% of liver glycogen stores. Concentrations of muscle lactate and alanine were also lower in PF than in WT mice, indicating that this decrease may lead to a potential reduction of recycled gluconeogenic substrates, due to oxidation of their carbohydrate precursors in skeletal muscle, leading to observed reductions in hepatic glucose and glycogen concentrations. Because of the impairments seen in PF PDK4-KO mice, these results suggest a role for PDK4 in regulating the PDH complex in muscle and promoting gluconeogenic precursor recirculation during recovery from exhaustive 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".