Bibliographic record
Abstract
Cardiomyocytes are excitable cells that can generate and propagate excitations; excitability is a fundamental characteristic of these cells, which is reflected by action potential; the changes of transmembrane potential as a function of time; and orchestrated by ion channels, transporters, and cellular proteins. The electrical excitation evoked in muscles must be transformed into mechanical contraction through the so-called excitation-contraction coupling mechanism, and the proper contraction of cardiac muscles then drives pumping of blood to the body circulation. Arrhythmias are electrical disturbances that can result in irregular heart beating with consequent insufficient pumping of blood. Arrhythmias are often lethal, constituting a major cause for cardiac death, particularly sudden cardiac death, in myocardial infarction and heart failure. Recent studies have led to discovery of microRNAs (miRNAs) as a new player in the cardiac excitability by fine-tuning expression of ion channels, transporters, and cellular proteins, which determines the arrhythmogenicity in many conditions. This review article will give a comprehensive summary on the data available in the literature. The basics of cardiac excitability will first be introduced, followed by a brief introduction to the basics of miRNAs. Then, studies on regulation of cardiac excitability by miRNAs will be described and analyzed. Finally, concluding remarks will be provided.
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.
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 | 0.001 | 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) | 0.001 | 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".