Endogenously Generated Omega‐3 Fatty Acids Attenuate Vascular Inflammation and Neointimal Hyperplasia by Interaction With Free Fatty Acid Receptor 4 in Mice
Bibliographic record
Abstract
BACKGROUND: Omega-3 polyunsaturated fatty acids (ω3 PUFAs) suppress inflammation through activation of free fatty acid receptor 4 (FFAR4), but this pathway has not been explored in the context of cardiovascular disease. We aimed to elucidate the involvement of FFAR4 activation by ω3 PUFAs in the process of vascular inflammation and neointimal hyperplasia in mice. METHODS AND RESULTS: We used mice with disruption of FFAR4 (Ffar4(-/-)), along with a strain that synthesizes high levels of ω3 PUFAs (fat-1) and a group of crossed mice (Ffar4(-/-)/fat-1), to elucidate the role of FFAR4 in vascular dysfunction using acute and chronic thrombosis/vascular remodeling models. The presence of FFAR4 in vascular-associated cells including perivascular adipocytes and macrophages, but not platelets, was demonstrated. ω3 PUFAs endogenously generated in fat-1 mice (n=9), but not in compound Ffar4(-/-)/fat-1 mice (n=9), attenuated femoral arterial thrombosis induced by FeCl3. Neointimal hyperplasia and vascular inflammation in the common carotid artery were significantly curtailed 4 weeks after FeCl3 injury in fat-1 mice (n=6). This included greater luminal diameter and enhanced blood flow, reduced intima:media ratio, and diminished macrophage infiltration in the vasculature and perivascular adipose tissue compared with control mice. These effects were attenuated in the Ffar4(-/-)/fat-1 mice. CONCLUSIONS: These results indicate that ω3 PUFAs mitigate vascular inflammation, arterial thrombus formation, and neointimal hyperplasia by interaction with FFAR4 in mice. Moreover, the ω3 PUFA-FFAR4 pathway decreases inflammatory responses with dampened macrophage transmigration and infiltration.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".