PDH activation during in vitro muscle contractions in PDH kinase 2 knockout mice: effect of PDH kinase 1 compensation
Bibliographic record
Abstract
Pyruvate dehydrogenase (PDH) plays an important role in regulating carbohydrate oxidation in skeletal muscle. PDH is deactivated by a set of PDH kinases (PDK1, PDK2, PDK3, PDK4), with PDK2 and PDK4 being the most predominant isoforms in skeletal muscle. Although PDK2 is the most abundant isoform, few studies have examined its physiological role. The role of PDK2 on PDH activation (PDHa) at rest and during muscle stimulation at 10 and 40 Hz (eliciting low- and moderate-intensity muscle contractions, respectively) in isolated extensor digitorum longus muscles was studied in PDK2 knockout (PDK2KO) and wild-type (WT) mice (n = 5 per group). PDHa activity was unexpectedly 35 and 77% lower in PDK2KO than WT muscle (P = 0.043), while total PDK activity was nearly fourfold lower in PDK2KO muscle (P = 0.006). During 40-Hz contractions, initial force was lower in PDK2KO than WT muscle (P < 0.001) but fatigued similarly to ∼75% of initial force by 3 min. There were no differences in initial force or rate of fatigue during 10-Hz contractions. PDK1 compensated for the lack of PDK2 and was 1.8-fold higher in PDK2KO than WT muscle (P = 0.019). This likely contributed to ensuring that resting PDHa activity was similar between the groups and accounts for the lower PDH activation during muscle contraction, as PDK1 is a very potent inhibitor of the PDH complex. Increased PDK1 expression appears to be regulated by hypoxia inducible factor-1α, which was 3.5-fold higher in PDK2KO muscle. It is clear that PDK2 activity is essential, even at rest, in regulation of carbohydrate oxidation and production of reducing equivalents for the electron transport chain. In addition, these results underscore the importance of the overall kinetics of the PDK isoform population, rather than total PDK activity, in determining transformation of the PDH complex and PDHa activity during muscle contraction.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".