Could Plugging the Oxidation-Mediated Ca <sup>2+</sup> Leak Stem the Tide of the Atrial Fibrillation Epidemic?
Bibliographic record
Abstract
A s the most common sustained arrhythmia, atrial fibril- lation (AF) afflicts Ͼ2 million patients in the United States alone, and this number is predicted to double by the year 2050. 1 Although AF is not life-threatening, it is linked to a 2-fold increase in mortality when present as a comorbidity in heart disease patients. 2,3AF can have devastating consequences, such as stroke, impaired cardiac performance, and promotion of cardiomyopathy.The treatment of AF can also produce life-threatening side effects, such as ventricular arrhythmias and hemorrhage.AF patients are generally classified as paroxysmal (episodes lasting Ͻ7 days), persistent (lasting Ͼ7 days but treated to restore sinus rhythm), or permanent (no attempt to restore sinus rhythm). 2,3AF is usually secondary to other conditions such as hypertension, heart failure, valvular disease, sleep apnea, hyperthyroidism, and diabetes.Most of these AF-inducing conditions are associated with elevated atrial pressure and atrial stretch, as well as increased oxidative stress and inflammation, which lead to structural and electric changes (remodeling) that create a substrate for supporting AF induction and maintenance. 4,
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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.024 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".