Pathogenesis of Atherosclerosis and Coronary Heart Disease: Epidemiology, Diagnostic Biomarkers and Prevention by Nutraceuticals, Functional Foods, and Plant-Derived Therapies
Bibliographic record
Abstract
Atherosclerosis is characterized by hardening/narrowing of arteries and reduction of blood flow to vital organs. Animal models and human research show that endothelial dysfunction and plaque development precede the pathogenesis of atherosclerosis, and related coronary heart disease, neurological, and renal disorders. Cardiac CT-scans are used to detect atherosclerosis. Early diagnosis of atherosclerosis reduces mortality, morbidity, and healthcare expenditures. Biomarkers like C-reactive protein, IL-6, IL-8, phospholipase A2, cardiac troponin, MicroRNA, miR-21, and other endothelial inflammation biomarkers are novel targets for monitoring atherosclerosisrelated cardiovascular disorders. Anti-platelet and anti-cholesterol drugs are used in the treatment of atherogenesis and blood vessel clots. However, cholesterol-lowering drugs may cause serious adverse effects. Thus, safe and cost-effective non-pharmacological anti-atherogenic and anticoagulant therapies are urgently needed. Nutraceuticals, functional foods, plant-derived therapies, antioxidant/anti-inflammation, foods/fruits/vegetables, and lifestyle changes (e.g., physical activity, less alcohol, smoking cessation) reduce atherogenesis, diabetes mellitus, obesity, hypertension, LDL, and C-reactive protein in all age groups, especially younger people. Overwhelming evidence suggests that regular physical activity (30 min/day), cessation of cigarette smoking, and consumption of antioxidant nutraceuticals rich in flavonoids and retinoids, fresh vegetables and fruits, omega-3 PUFA, culinary spices, probiotics, Mediterranean-type diet, and “DASH DIET” lower the risk of atherogenesis and cardiovascular diseases. This review summarizes current advances in the diagnosis and management of atherosclerosis and related cardiovascular illnesses with plant-based and wholesome diets, including the Mediterranean diet, DASH DIET, and lifestyle changes. New preventative measures and alternative therapies, including dietary interventions and plant-based foods may be the most cost-effective ways to manage atherosclerosis and cardiovascular illnesses.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".