Transgenic Restoration of Long-Chain n-3 Fatty Acids in Insulin Target Tissues Improves Resolution Capacity and Alleviates Obesity-Linked Inflammation and Insulin Resistance in High-Fat–Fed Mice
Bibliographic record
Abstract
OBJECTIVE: The catabasis of inflammation is an active process directed by n-3 derived pro-resolving lipid mediators. We aimed to determine whether high-fat (HF) diet-induced n-3 deficiency compromises the resolution capacity of obese mice and thereby contributes to obesity-linked inflammation and insulin resistance. RESEARCH DESIGN AND METHODS: We used transgenic expression of the fat-1 n-3 fatty acid desaturase from C. elegans to endogenously restore n-3 fatty acids in HF-fed mice. After 8 weeks on HF or chow diets, wild-type and fat-1 transgenic mice were subjected to insulin and glucose tolerance tests and a resolution assay was performed. Metabolic tissues were then harvested for biochemical analyses. RESULTS: We report that the n-3 docosanoid resolution mediator protectin D1 is lacking in muscle and adipose tissue of HF-fed wild-type mice. Accordingly, HF-fed wild-type mice have an impaired capacity to resolve an acute inflammatory response and display elevated adipose macrophage accrual and chemokine/cytokine expression. This is associated with insulin resistance and higher activation of iNOS and JNK in muscle and liver. These defects are reversed in HF-fed fat-1 mice, in which the biosynthesis of this important n-3 docosanoid resolution mediator is improved. Importantly, transgenic restoration of n-3 fatty acids prevented obesity-linked inflammation and insulin resistance in HF-fed mice without altering food intake, weight gain, or adiposity. CONCLUSIONS: We conclude that inefficient biosynthesis of n-3 resolution mediators in muscle and adipose tissue contributes to the maintenance of chronic inflammation in obesity and that these novel lipids offer exciting potential for the treatment of insulin resistance and diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".