Targeting vascular (endothelial) dysfunction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cardiovascular diseases are major contributors to global deaths and disability-adjusted life years, with hypertension a significant risk factor for all causes of death. The endothelium that lines the inner wall of the vasculature regulates essential haemostatic functions, such as vascular tone, circulation of blood cells, inflammation and platelet activity. Endothelial dysfunction is an early predictor of atherosclerosis and future cardiovascular events. We review the prognostic value of obtaining measurements of endothelial function, the clinical techniques for its determination, the mechanisms leading to endothelial dysfunction and the therapeutic treatment of endothelial dysfunction. Since vascular oxidative stress and inflammation are major determinants of endothelial function, we have also addressed current antioxidant and anti-inflammatory therapies. In the light of recent data that dispute the prognostic value of endothelial function in healthy human cohorts, we also discuss alternative diagnostic parameters such as vascular stiffness index and intima/media thickness ratio. We also suggest that assessing vascular function, including that of smooth muscle and even perivascular adipose tissue, may be an appropriate parameter for clinical investigations. LINKED ARTICLES: This article is part of a themed section on Redox Biology and Oxidative Stress in Health and Disease. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.12/issuetoc.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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