Mechanism of Hypercholesterolemia-Induced Atherosclerosis
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Bibliographic record
Abstract
Hypercholesterolemia is involved in the development of atherosclerosis and is a risk factor for coronary artery disease, stroke, and peripheral vascular disease. This paper deals with the mechanism of development of hypercholesterolemic atherosclerosis. Hypercholesterolemia increases the formation of numerous atherogenic biomolecules including reactive oxygen species (ROS), proinflammatory cytokines [interleukin (IL)-1, IL-2, IL-6, IL-8, tumor necrosis factor-alpha (TNF-α)], expression of intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), E-selectin, monocyte chemoattractant protein-1 (MCP-1), granulocyte macrophage-colony stimulating factor (GM-CSF) and numerous growth factors [insulin-like growth factor-1 (IGF-1), platelet-derived growth factor-1 (PDGF-1) and transforming growth factor-beta (TGF-β)]. ROS mildly oxidizes low-density lipoprotein-cholesterol (LDL-C) to form minimally modified LDL (MM-LDL) which is further oxidized to form oxidized LDL (OX-LDL). Hypercholesterolemia also activates nuclear factor-kappa-B (NF-κB). The above atherogenic biomolecules are involved in the development of atherosclerosis which has been described in detail. Hypercholesterolemia also assists in the development of atherosclerosis through AGE (advanced glycation end-products)-RAGE (receptor for AGE) axis and C-reactive protein (CRP). Hypercholesterolemia is associated with increases in AGE, oxidative stress [AGE/sRAGE (soluble receptor for AGE)] and C-reactive protein, and decreases in the sRAGE, which are known to be implicated in the development of atherosclerosis. In conclusion, hypercholesterolemia induces atherosclerosis through increases in atherogenic biomolecules, AGE-RAGE axis and CRP.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it