Mitochondrial function and dysfunction in exercise and insulin resistanceThis paper article is one of a selection of papers published in this Special Issue, entitled 14th International Biochemistry of Exercise Conference – Muscles as Molecular and Metabolic Machines, and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
Fatty acid translocase (FAT/CD36) represents a novel flexible regulatory system, influencing rates of mitochondrial fatty acid metabolism in both human and rodent skeletal muscle. During exercise, the subcellular redistribution of FAT/CD36 provides a mechanism to increase not only plasma membrane fatty acid transport, but also mitochondrial fatty acid oxidation. This FAT/CD36-mediated coordination of long chain fatty acid (LCFA) transport and oxidation is an intriguing model in the context of insulin resistance. It was believed for almost a decade that reductions in fatty acid oxidation increased intramuscular lipids, thereby contributing to insulin resistance. A reduction in mitochondrial content may reduce the capacity of skeletal muscle LCFA oxidation; however, work from my laboratory has shown that, in some insulin-resistant muscles, mitochondrial content and fatty acid oxidation are both increased, yet these muscles accumulate lipids because of a considerably greater increase in fatty acid transport. Therefore, an alternative model is being considered, in which the balance between LCFA uptake and oxidation is a determining factor in the development of insulin resistance. A permanent redistribution of the LCFA transport protein FAT/CD36 to the sarcolemmal has been consistently found, which results in an increased rate of LCFA transport. This work suggests that the accumulation of skeletal muscle lipids, regardless of changes in mitochondria, is attributable to an increased rate of LCFA transport that exceeds the capacity for oxidation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".