Contrasting Gene Expression Profiles in Two Canine Models of Atrial Fibrillation
Bibliographic record
Abstract
Gene-expression changes in atrial fibrillation patients reflect both underlying heart-disease substrates and changes because of atrial fibrillation-induced atrial-tachycardia remodeling. These are difficult to separate in clinical investigations. This study assessed time-dependent mRNA expression-changes in canine models of atrial-tachycardia remodeling and congestive heart failure. Five experimental groups (5 dogs/group) were submitted to atrial (ATP, 400 bpm x 24 hours, 1 or 6 weeks) or ventricular (VTP, 240 bpm x 24 hours or 2 weeks) tachypacing. The expression of approximately 21,700 transcripts was analyzed by microarray in isolated left-atrial cardiomyocytes and (for 18 genes) by real-time RT-PCR. Protein-expression changes were assessed by Western blot. In VTP, a large number of significant mRNA-expression changes occurred after both 24 hours (2209) and 2 weeks (2720). In ATP, fewer changes occurred at 24 hours (242) and fewer still (87) at 1 week, with no statistically-significant alterations at 6 weeks. Expression changes in VTP varied over time in complex ways. Extracellular matrix-related transcripts were strongly upregulated by VTP consistent with its pathophysiology, with 8 collagen-genes upregulated >10-fold, fibrillin-1 8-fold and MMP2 4.5-fold at 2 weeks (time of fibrosis) but unchanged at 24 hours. Other extracellular matrix genes (eg, fibronectin, lysine oxidase-like 2) increased at both time-points ( approximately 10, approximately 5-fold respectively). In ATP, mRNA-changes almost exclusively represented downregulation and were quantitatively smaller. This study shows that VTP-induced congestive heart failure and ATP produce qualitatively different temporally-evolving patterns of gene-expression change, and that specific transcriptomal responses associated with atrial fibrillation versus underlying heart disease substrates must be considered in assessing gene-expression changes in man.
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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 | 0.000 | 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".