Loss of muscle PDH induces lactic acidosis and adaptive anaplerotic compensation via pyruvate-alanine cycling and glutaminolysis
Bibliographic record
Abstract
Pyruvate dehydrogenase (PDH) is the rate-limiting enzyme for glucose oxidation that links glycolysis-derived pyruvate with the tricarboxylic acid (TCA) cycle. Although skeletal muscle is a significant site for glucose oxidation and is closely linked with metabolic flexibility, the importance of muscle PDH during rest and exercise has yet to be fully elucidated. Here, we demonstrate that mice with muscle-specific deletion of PDH exhibit rapid weight loss and suffer from severe lactic acidosis, ultimately leading to early mortality under low-fat diet provision. Furthermore, loss of muscle PDH induces adaptive anaplerotic compensation by increasing pyruvate-alanine cycling and glutaminolysis. Interestingly, high-fat diet supplementation effectively abolishes early mortality and rescues the overt metabolic phenotype induced by muscle PDH deficiency. Despite increased reliance on fatty acid oxidation during high-fat diet provision, loss of muscle PDH worsens exercise performance and induces lactic acidosis. These observations illustrate the importance of muscle PDH in maintaining metabolic flexibility and preventing the development of metabolic disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".