Skeletal muscle pyruvate dehydrogenase phosphatase: effects of obesity and endurance training
Bibliographic record
Abstract
Pyruvate dehydrogenase (PDH) plays an important role in regulating carbohydrate metabolism in skeletal muscle. PDH is activated by PDH phosphatase (PDP) and deactivated by PDH kinase (PDK). It has been well documented that there is altered skeletal muscle PDH activity with obesity and endurance training. A majority of this literature has focused on the relative importance of PDK, with little information available on PDP. To determine the relative role of PDP in regulating skeletal muscle PDH activity with obesity and endurance training, obese (O) and lean (L) Zucker rats remained sedentary (S) or were endurance trained (TR; 1 hour per day, 5 days a week) for a period of 7 weeks. Slow oxidative (soleus, SOL), fast oxidative glycolytic (red gastrocnemius, RG), and fast glycolytic (white gastrocnemius, WG) muscles were sampled after the training period. Obesity decreased PDP activity in RG (LS, 0.56 ± 0.07; OS, 0.30 ± 0.07 nmol/min/mg mitochondrial protein). TR restored PDP activity in obese and had no effect on lean RG (OTR, 0.59 ± 0.15; LTR, 0.54 ± 0.07 nmol/min/mg mitochondrial protein). Obesity and TR had no effect on SOL (LS, 0.62 ± 0.07; LTR, 0.59 ± 0.16; OS, 0.46 ± 0.11; OTR, 0.51 ± 0.07 nmol/min/mg mitochondrial protein) and WG (LS, 0.60 ± 0.10; LTR, 0.75 ± 0.16; OS, 0.42 ± 0.15; OTR, 0.71 ± 0.20 nmol/min/mg mitochondrial protein) PDP activity. These results suggest that decreased PDP activity in a fast oxidative glycolytic fiber (RG) may play a role in the impairment of carbohydrate metabolism in obese rats, which is reversible with endurance training. Supported by NSERC (SJP, BDR & PJL).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".