The apelin receptor: physiology, pathology, cell signalling, and ligand modulation of a peptide-activated class A GPCR
Bibliographic record
Abstract
The apelin receptor (AR or APJ) is a class A (rhodopsin-like) G-protein-coupled receptor with wide distribution throughout the human body. Activation of the AR by its cognate peptide ligand, apelin, induces diverse physiological effects including vasoconstriction and dilation, strengthening of heart muscle contractility, angiogenesis, and regulation of energy metabolism and fluid homeostasis. Recently, another endogenous peptidic activator of the AR, Toddler/ELABELA, was identified as having a crucial role in zebrafish (Danio rerio) embryonic development. The AR is also implicated in pathologies including cardiovascular disease, diabetes, obesity, and cancer, making it a promising therapeutic target. Despite its established importance, the precise roles of AR signalling remain poorly understood. Moreover, little is known about the mechanisms of peptide-AR activation. Additional complexity arises from modulation of the AR by 2 endogenous peptide ligands, both with multiple bioactive isoforms of variable length and distribution. The various apelin and Toddler/ELABELA isoforms may also produce distinct cellular effects. Further complexity arises through formation of functionally distinct heterodimers between the AR and other G-protein-coupled receptors. This minireview outlines key (patho)physiological actions of the AR, addresses what is known about signal transduction downstream of AR activation, and concludes by discussing unique properties of the endogenous peptidic ligands of the AR.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.002 |
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".