A Metabolically Stable Apelin-13 Analog Acting as a Potent ITo Potassium Current Blocker with Potential Benefits for Brugada Syndrome
Bibliographic record
Abstract
Apelin serves as the endogenous ligand for the APJ receptor and enhances cardiac contractility without significantly affecting potassium currents. However, its short in vivo half-life limits clinical application, prompting the development of metabolically stable APJ receptor agonists. This study employed the patch-clamp technique to investigate the effects of the C-terminally modified apelin-13-2Nal derivative (2Nal) on action potential dynamics, rapid sodium (INa), and transient potassium (ITO) currents in rat cardiomyocytes. We discovered that 2Nal prolongs ventricular action potential duration by selectively blocking ITo. Dose-response analysis indicated that 2Nal acts as a partial antagonist of ITO, achieving a maximum blockade of 47%, with an apparent EC50 of 0.3 nM, while not affecting INa. Our lab previously found that an imbalance between ITo and INa currents contributes to the development of cardiac arrhythmias in conditions like Brugada syndrome. Currently, few therapeutic options exist to safely address this imbalance, as sodium channel openers cannot restore it, and most ITo blockers are cardiotoxic. The selective blockade of ITo by 2Nal that we describe here helps restore the balance of electrical currents between ITo and INa. Our study presents a novel, safe partial antagonist of ITo that may help prevent arrhythmias associated with Brugada syndrome.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Pharmacology study of an apelin-13 analog as a potassium current blocker for Brugada syndrome.
It studies a potential cardiac drug analog for Brugada syndrome, not research practice.
Patch-clamp pharmacology of an apelin analog on cardiac currents; biomedical physiology.
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) | 0.000 | 0.000 |
| 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 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".