Role of atrial tissue remodeling on rotor dynamics: an in vitro study
Bibliographic record
Abstract
The objective of this article is to present an in vitro model of atrial cardiac tissue that could serve to study the mechanisms of remodeling related to atrial fibrillation (AF). We analyze the modification on gene expression and modifications on rotor dynamics following tissue remodeling. Atrial murine cells (HL-1 myocytes) were maintained in culture after the spontaneous initiation of AF and analyzed at two time points: 3.1 ± 1.3 and 9.7 ± 0.5 days after AF initiation. The degree of electrophysiological remodeling (i.e., relative gene expression of key ion channels) and structural inhomogeneity was compared between early and late cell culture times both in nonfibrillating and fibrillating cell cultures. In addition, the electrophysiological characteristics of in vitro fibrillation [e.g., density of phase singularities (PS/cm(2)), dominant frequency, and rotor meandering] analyzed by means of optical mapping were compared with the degree of electrophysiological remodeling. Fibrillating cell cultures showed a differential ion channel gene expression associated with atrial tissue remodeling (i.e., decreased SCN5A, CACN1C, KCND3, and GJA1 and increased KCNJ2) not present in nonfibrillating cell cultures. Also, fibrillatory complexity was increased in late- vs. early stage cultures (1.12 ± 0.14 vs. 0.43 ± 0.19 PS/cm(2), P < 0.01), which was associated with changes in the electrical reentrant patterns (i.e., decrease in rotor tip meandering and increase in wavefront curvature). HL-1 cells can reproduce AF features such as electrophysiological remodeling and an increased complexity of the electrophysiological behavior associated with the fibrillation time that resembles those occurring in patients with chronic AF.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".