Role of the renin–angiotensin system in the pathophysiology of coronary heart disease and heart failure: Diagnostic biomarkers and therapy with drugs and natural products
Bibliographic record
Abstract
The renin–angiotensin system (RAS) plays a pivotal role in blood pressure regulation. In some cases, this steering mechanism is affected by various deleterious factors (mainly via the overactivation of the RAS) causing cardiovascular damage, including coronary heart disease (CHD) that can ultimately lead to chronic heart failure (CHF). This not only causes cardiovascular disability and absenteeism from work but also imposes significant healthcare costs globally. The incidence of cardiovascular diseases has escalated exponentially over the years with the major outcome in the form of CHD, stroke, and CHF. The involvement of the RAS in various diseases has been extensively researched with significant limelight on CHD. The RAS may trigger a cascade of events that lead to atherosclerotic mayhem, which causes CHD and related aggravation by damaging the endothelial lining of blood vessels via various inflammatory and oxidative stress pathways. Although there are various diagnostic tests and treatments available in the market, there is a constant need for the development of procedures and therapeutic strategies that increase patient compliance and reduce the associated side effects. This review highlights the advances in the diagnostic and treatment domains for CHD, which would help in subjugating the side effects caused by conventional therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".