Triacylglycerol accumulation in human obesity and type 2 diabetes is associated with increased rates of skeletal muscle fatty acid transport and increased sarcolemmal FAT/CD36
Bibliographic record
Abstract
We examined whether, in human obesity and type 2 diabetes, long chain fatty acid (LCFA) transport into skeletal muscle is upregulated and contributes to an excess intramuscular triacylglycerol accumulation. In giant sarcolemmal vesicles prepared from human skeletal muscle, LCFA transport rates were upregulated approximately 4-fold and were associated with an increased intramuscular triacylglycerol content in obese individuals and in type 2 diabetics. In these individuals, the increased sarcolemmal LCFA transport rate was not associated with an altered expression of FAT/CD36 or FABPpm. Instead, the increase in the LCFA transport rate was associated with an increase in sarcolemmal FAT/CD36 but not sarcolemmal FABPpm. Rates of fatty acid esterification were increased threefold in isolated human muscle strips obtained from obese subjects, while concomitantly rates of fatty acid oxidation were not altered. Thus, the increased rate of fatty acid transport may contribute to the increased rates of triacylglycerol accumulation in human skeletal muscle. The altered FAT/CD36 trafficking in muscle from obese subjects and type 2 diabetics juxtaposes the known alterations in GLUT4 trafficking, i.e., GLUT4 is known to be retained in its intracellular depots while FAT/CD36 is retained at the sarcolemma. This redistribution of FAT/CD36 to the sarcolemma may contribute to the etiology of insulin resistance in human muscle, and hence, FAT/CD36 provides another potential therapeutic target for the prevention and/or treatment of insulin resistance.
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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 | 0.001 | 0.001 |
| 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".