Interaction between the apelinergic system and ACE2 in the cardiovascular system: therapeutic implications
Bibliographic record
Abstract
The apelinergic system is widely expressed and acts through autocrine and paracrine signaling to exert protective effects, including vasodilatory, metabolic, and inotropic effects on the cardiovascular (CV) system. The apelin pathway's dominant physiological role has delineated therapeutic implications for coronary artery disease, heart failure (HF), aortic aneurysm, pulmonary arterial hypertension (PAH), and transplant vasculopathy. Apelin peptides interact with the renin-angiotensin system (RAS) by promoting angiotensin converting enzyme 2 (ACE2) transcription leading to increased ACE2 protein and activity while also antagonizing the effects of angiotensin II (Ang II). Apelin modulation of the RAS by increasing ACE2 action is limited due to its rapid degradation by proteases, including ACE2, neprilysin (NEP), and kallikrein. Apelin peptides are hence tightly regulated in a negative feedback manner by ACE2. Plasma apelin levels are suppressed in pathological conditions, but its diagnostic and prognostic utility requires further clinical exploration. Enhancing the beneficial actions of apelin peptides and ACE2 axes while complementing existing pharmacological blockade of detrimental pathways is an exciting pathway for developing new therapies. In this review, we highlight the interaction between the apelin and ACE2 systems, discuss their pathophysiological roles and potential for treating a wide array of CV diseases (CVDs).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".