Bibliographic record
Abstract
Atherosclerosis is the leading cause of death in North America and within the next two decades will be the leading cause worldwide. Atherosclerosis is characterized by vascular obstruction from the deposits of plaque, resulting in reduced blood flow. Plaque rupture and the consequent thrombosis may lead to sudden blockage of the arteries and cause heart attack. High serum lipid levels, especially the elevated level of low-density lipoprotein (LDL), have been shown to be strongly related to the development of atherosclerosis. It is generally accepted that atherosclerotic lesions are initiated via an enhancement of LDL uptake by monocytes and macrophages. In the liver, uptake of plasma LDL is mediated via specific LDL receptors, but a scavenger receptor system is employed by macrophages. Plasma LDL must be modified prior to uptake by macrophages. Analysis of the lipid content in the oxidatively modified LDL from hyper lipidemic patients revealed that the level of lysophosphatidylcholine was greatly elevated, and the high level of the lysolipid was shown to impair the endothelium-dependent relaxation of the blood vessels. In a separate study, we showed that a high level of homocysteine caused the increase in cholesterol production and apolipoprotein B-100 secretion in hepatic cells. Statins have been used effectively to control the production of cholesterol in the liver, and recently, ezetimibe has been shown to supplement the efficacy of statins by inhibiting cholesterol absorption. The factor of elevated levels of triglyceride-rich lipoproteins in association with depressed high-density lipoproteins, usually in the context of insulin resistance, is an important contributor to atherosclerosis and can be effectively treated with fibric acid derivatives. In hyperhomocysteinemia, folic acid supplements may have a role in the control of cholesterol by reducing the plasma homocysteine level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".