Mathematical analysis of canine atrial action potentials: rate, regional factors, and electrical remodeling
Bibliographic record
Abstract
Dogs have been used extensively to study atrial arrhythmias, but there are no published mathematical models of the canine atrial action potential (AP). To obtain insights into the ionic mechanisms governing canine atrial AP properties, we incorporated formulations of K(+), Na(+), Ca(2+), and Cl(-) currents, based on measurements in canine atrial myocytes, into a mathematical model of the AP. The rate-dependent behavior of model APs corresponded to experimental measurements and pointed to a central role for L-type Ca(2+) current inactivation in rate adaptation. Incorporating previously described regional ionic current variations into the model largely reproduced AP forms characteristic of the corresponding right atrial regions (appendage, pectinate muscle, crista terminalis, and atrioventricular ring). When ionic alterations induced by tachycardia-dependent remodeling were incorporated, the model reproduced qualitatively the AP features constituting the cellular substrate for atrial fibrillation. We conclude that this ionic model of the canine atrial AP agrees well with experimental measurements and gives potential insights into mechanisms underlying functionally important electrophysiological phenomena in canine atrium.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".