Adaptation of skeletal muscle pyruvate dehydrogenase kinase in response to starvation in mitochondrial subpopulations
Bibliographic record
Abstract
Pyruvate dehydrogenase (PDH) catalyses decarboxylation of pyruvate, to form acetyl‐CoA. PDH activity is down‐regulated by intrinsic PDH kinases (predominantly PDK2 and PDK4 isoforms), but the understanding of the PDK isoform distribution and adaptation to nutritional stresses has been restricted to mixed mitochondrial populations, and not delineated between subsarcolemmal (SS) and intermyofibrillar (IMF) sub‐populations. SS and IMF exhibit distinct morphological and biochemical properties; however the functional differences are not well understood. This study investigated the effect of fed (FED) versus 48 h food restriction (FR) on adaptive changes in rat red gastrocnemius muscle PDK2 and 4 isoform content in SS and IMF mitochondria. PDK4 content was 2–4 fold higher in SS mitochondria compared to IMF (p=0.003), and increased with FR ~10‐ fold in both sub‐populations (p<0.001). PDK2 was ~3–4 fold higher in SS mitochondria compared to IMF (p=0.017), but PDK2 was unaltered with FR. These results demonstrate that there is a markedly higher content of both PDK isoforms in SS compared to IMF mitochondria. Although PDK2 does not increase in either sub‐population in response to FR, PDK4 increases to a similar extent in both SS and IMF after 48 h food restriction Supported by NSERC (SJP, BDR & PJL) and CIHR (LLM).
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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".