Dietary patterns and endothelium dysfunction: a literature review
Bibliographic record
Abstract
The integrity of the vascular endothelium is fundamental to regulating cardio-metabolic and neurological functions. Endothelial dysfunction (ED) is a key driver of atherosclerosis and is strongly linked to the pathogenesis of heart disease, peripheral arterial disease, and stroke. This review describes the relationship between dietary patterns and endothelial health, focusing on observational and experimental studies that investigate the protective effects of healthy dietary patterns in the maintenance of endothelial integrity and prevention of ED. Plant-based diets, including Mediterranean and Dietary Approaches to Stop Hypertension (DASH) dietary patterns, have been linked to improvement of endothelial function through multiple mechanisms such as increased nitric oxide bioavailability, reduced oxidative stress and inflammation, and fostering a healthy gut microbiome. Traditional Japanese, Nordic, and Palaeolithic dietary patterns also show potential cardiovascular benefits through improved vascular biomarkers and significant anti-inflammatory effects, though evidence on effects on endothelial function remains less established. The consequences of poor endothelial health extend to all systems, and the brain is one of the organs crucially affected by ED. ED has been increasingly recognised as a critical contributor to cognitive decline, dementia, and stroke, largely accounted and explained by mechanisms impairing cerebral blood flow, neuronal metabolism, neuro-vascular coupling and compromised integrity of the blood-brain barrier. This review highlights the importance of maintaining endothelial health as a protective strategy for cognitive function and reduction of dementia risk. Adherence to dietary patterns with protective effects on endothelial integrity may represent an effective strategy to promote lifelong health for both the heart and brain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".