Both linoleic and α-linolenic acid prevent insulin resistance but have divergent impacts on skeletal muscle mitochondrial bioenergetics in obese Zucker rats
Bibliographic record
Abstract
The therapeutic use of polyunsaturated fatty acids (PUFA) in preserving insulin sensitivity has gained interest in recent decades; however, the roles of linoleic acid (LA) and α-linolenic acid (ALA) remain poorly understood. We investigated the efficacy of diets enriched with either LA or ALA on attenuating the development of insulin resistance (IR) in obesity. Following a 12-wk intervention, LA and ALA both prevented the shift toward an IR phenotype and maintained muscle-specific insulin sensitivity otherwise lost in obese control animals. The beneficial effects of ALA were independent of changes in skeletal muscle mitochondrial content and oxidative capacity, as obese control and ALA-treated rats showed similar increases in these parameters. However, ALA increased the propensity for mitochondrial H2O2 emission and catalase content within whole muscle and reduced markers of oxidative stress (4-HNE and protein carbonylation). In contrast, LA prevented changes in markers of mitochondrial content, respiratory function, H2O2 emission, and oxidative stress in obese animals, thereby resembling levels seen in lean animals. Together, our data suggest that LA and ALA are efficacious in preventing IR but have divergent impacts on skeletal muscle mitochondrial content and function. Moreover, we propose that LA has value in preserving insulin sensitivity in the development of obesity, thereby challenging the classical view that n-6 PUFAs are detrimental.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".