High Levels of Avenanthramides in Oat-Based Diet Further Suppress High Fat Diet-Induced Atherosclerosis in Ldlr<sup>–/–</sup> Mice
Bibliographic record
Abstract
Oats, in addition to cholesterol-lowering properties, contain unique antioxidants called avenanthramides (Avns), which inhibit both inflammatory cytokines and adhesion molecules in endothelial cells in culture. This study evaluated the effects of Avns of oats on atherosclerosis in Ldlr –/– mice, one of the most commonly used atherosclerosis mouse models with their similar cholesterol distributions to humans. The Ldlr –/– mice were fed a low fat, high fat, high fat containing regular oat brans with low levels of Avns (HFLA), or high fat containing regular oat brans with high levels of Avns (HFHA) diet. After 16 weeks of intervention, blood cholesterol and extent of aortic lesions were evaluated. We found that both oat-based diets reduced high fat diet-induced atheroma lesions in the aortic valve ( p < 0.01). Furthermore, the effects of oat-based diets are more profound in HFHA mice than mice fed HFLA. Total plasma cholesterol levels were similarly reduced in both oat-supplemented mice. We concluded that oat bran diets reduce atheroma lesions and higher levels of Avns further reduce aortic lesions compared to regular oat bran. These preliminary in vivo data indicate that consumption of oats bran, with high Avns, has demonstrable beneficial effects on prevention of cardiovascular 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".