Aspirin enhances protective effect of fish oil against thrombosis and injury‐induced vascular remodelling
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although aspirin (acetylsalicylic acid) is commonly used to prevent ischaemic events in patients with coronary artery disease, many patients fail to respond to aspirin treatment. Dietary fish oil (FO), containing ω3 polyunsaturated fatty acids (PUFAs), has anti-inflammatory and cardio-protective properties, such as lowering cholesterol and modulating platelet activity. The objective of the present study was to investigate the potential additional effects of aspirin and FO on platelet activity and vascular response to injury. EXPERIMENTAL APPROACH: Femoral arterial remodelling was induced by wire injury in mice. Platelet aggregation, and photochemical- and ferric chloride-induced carotid artery thrombosis were employed to evaluate platelet function. KEY RESULTS: FO treatment increased membrane ω3 PUFA incorporation, lowered plasma triglyceride and cholesterol levels, and reduced systolic BP in mice. FO or aspirin alone inhibited platelet aggregation; however, when combined, they exhibited synergistic suppression of platelet activity in mice, independent of COX-1 inhibition. FO alone, but not aspirin, attenuated arterial neointimal growth in response to injury. Strikingly, a combination of FO and aspirin synergistically inhibited injury-induced neointimal hyperplasia and reduced perivascular inflammatory reactions. Moreover, co-administration of FO and aspirin decreased the expression of pro-inflammatory cytokines and adhesion molecules in inflammatory cells. Consistently, a pro-resolution lipid mediator-Resolvin E1, was significantly elevated in plasma in FO/aspirin-treated mice. CONCLUSIONS AND IMPLICATIONS: Co-administration of FO and low-dose aspirin may act synergistically to protect against thrombosis and injury-induced vascular remodelling in mice. Our results support further investigation of adjuvant FO supplementation for patients with stable coronary artery disease.
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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 | 0.000 | 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 | 0.000 |
| 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".