Bibliographic record
Abstract
Endothelial dysfunction defined as the impaired ability of vascular endothelium to stimulate vasodilation plays a key role in the development of atherosclerosis and in various pathological conditions which predispose to atherosclerosis, such as hypercholesterolemia, hypertension, type 2 diabetes, hyperhomocyst (e) inemia and chronic renal failure. The major cause of the endothelial dysfunction is decreased bioavailability of nitric oxide (NO), a potent biological vasodilator produced in vascular endothelium from L-arginine by the endothelial NO synthase (eNOS). In vascular diseases, the bioavailability of NO can be impaired by various mechanisms, including decreased NO production by eNOS, and/or enhanced NO breakdown due to increased oxidative stress. The deactivation of eNOS is often associated with elevated plasma levels of its endogenous inhibitor, N(G) N(G)-dimethyl-L-arginine (ADMA). In hypercholesterolemia, a systemic deficit of NO may also increase the levels of low density lipoproteins (LDL) by modulating its synthesis and metabolism by the liver, as suggested by recent in vivo and in vitro studies using organic NO donors. Therapeutic strategies aiming to reduce the risk of vascular diseases by increasing bioavailability of NO continue to be developed. Cholesterol-lowering drugs, statins, have been shown to improve endothelial function in patients with hypercholesterolemia and atherosclerosis. Promising results were also obtained in some, but not all, vascular diseases after treatment with antioxidant vitamins (C and E) and after administration of eNOS substrate, L-arginine, or its cofactor, tetrahydrobiopterin (BH(4)). Novel strategies, which may produce beneficial changes in the vascular endothelium, include the use of natural extracts from plant foods rich in phytochemicals.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".