Role of the Immune System in Hypertension: Modulation by Dietary Antioxidants
Bibliographic record
Abstract
Hypertension is a major health problem worldwide. Individuals with hypertension are at an increased risk for stroke, heart disease, and kidney failure. Although the etiology of essential hypertension has a genetic component, lifestyle factors such as diet play an important role. Insulin resistance is a common feature of hypertension in both humans and animal models affecting glucose and lipid metabolism producing excess aldehydes including methylglyoxal. These aldehydes react with proteins to form conjugates called advanced glycation end products (AGEs). This alters protein structure and function and can affect vascular and immune cells leading to their activation and secretion of inflammatory cytokines. AGEs also act via receptors for advanced glycation end products on these cells altering the function of antioxidant and metabolic enzymes, and ion channels. This results in an increase in cytosolic free calcium, decrease in nitric oxide, endothelial dysfunction, oxidative stress, peripheral vascular resistance, and infiltration of vascular and kidney tissue with inflammatory cells leading to hypertension. Supplementation with dietary antioxidants including vitamins C, E, or B(6), thiols such as cysteine and lipoic acid, have been shown to lower blood pressure and plasma inflammatory cytokines in animal models and humans with essential hypertension. A well-balanced diet rich in antioxidants that includes vegetables, fruits, low fat dairy products, low salt, and includes whole grains, poultry, fish and nuts, lowers blood pressure and vascular inflammation. These antioxidants may achieve their antihypertensive and anti-inflammatory/immunomodulatory effects by reducing AGEs and improving insulin resistance and associated alterations. Dietary supplementation with antioxidants may be a beneficial, inexpensive, front-line alterative treatment modality for hypertension.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".