Dietary α-linolenic acid supplementation alters skeletal muscle plasma membrane lipid composition, sarcolemmal FAT/CD36 abundance, and palmitate transport rates
Bibliographic record
Abstract
The cellular processes influenced by consuming polyunsaturated fatty acids remains poorly defined. Within skeletal muscle, a rate-limiting step in fatty acid oxidation is the movement of lipids across the sarcolemmal membrane, and therefore, we aimed to determine the effects of consuming flaxseed oil high in α-linolenic acid (ALA), on plasma membrane lipid composition and the capacity to transport palmitate. Rats fed a diet supplemented with ALA (10%) displayed marked increases in omega-3 polyunsaturated fatty acids (PUFAs) within whole muscle and sarcolemmal membranes (approximately five-fold), at the apparent expense of arachidonic acid (-50%). These changes coincided with increased sarcolemmal palmitate transport rates (+20%), plasma membrane fatty acid translocase (FAT/CD36; +20%) abundance, skeletal muscle triacylglycerol content (approximately twofold), and rates of whole body fat oxidation (~50%). The redistribution of FAT/CD36 to the plasma membrane could not be explained by increased phosphorylation of signaling pathways implicated in regulating FAT/CD36 trafficking events (i.e., phosphorylation of ERK1/2, CaMKII, AMPK, and Akt), suggesting the increased n-3 PUFA composition of the plasma membrane influenced FAT/CD36 accumulation. Altogether, the present data provide evidence that a diet supplemented with ALA increases the transport of lipids into resting skeletal muscle in conjunction with increased sarcolemmal n-3 PUFA and FAT/CD36 contents.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".