Role of Advanced Glycation End Products and Its Receptors in the Pathogenesis of Cigarette Smoke-Induced Cardiovascular Disease
Bibliographic record
Abstract
The interaction of advanced glycation end products (AGEs) with its cell-bound receptor RAGE increases gene expression and release of proinflammatory cytokines and increase generation of reactive oxygen species (ROS). Circulating receptors, soluble RAGE (sRAGE), and endosecretory RAGE (esRAGE) by binding with RAGE ligands have protective effects against AGE-RAGE interaction. Cigarette smoking is a risk factor for coronary artery disease, stroke, and peripheral vascular disease. This article reviews; if the AGE-RAGE axis is involved in the cigarette smoke-induced cardiovascular diseases. There are various sources of AGEs in smokers including, gas/tar of cigarette, activation of macrophages and polymorphonuclear leukocytes, uncoupling of endothelial isoform of nitric oxide synthase (eNOS) and xanthine oxidase. The levels of AGEs are elevated in smokers. Serum levels of sRAGE have been reported to be reduced, elevated, or unchanged in smokers. Mostly the levels are reduced. There is one article which shows an elevation of levels of sRAGE in smokers. Serum levels of esRAGE are unaltered in smokers. Mechanism of AGE-RAGE-induced atherosclerosis has been discussed. Atherosclerosis leads to the cardiovascular diseases. It has been suggested that ratio of AGE/sRAGE or AGE/esRAGE is useful in determining the deleterious effects of AGE-RAGE interaction in smokers. sRAGE alone is not a good marker for smoke-induced cardiovascular disease. In conclusion cigarette smoke induces formation of AGEs and reduces sRAGE resulting in the development of atherosclerosis and related coronary heart disease, stroke, and peripheral vascular disease. Ratio of AGEs/sRAGE is a better marker for cardiovascular disease than AGEs or sRAGE alone in smokers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".