Molecular basis of selective atrial fibrosis due to overexpression of transforming growth factor-β1
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Bibliographic record
Abstract
AIMS: Animal studies show that transforming growth factor-β1 (TGF-β1) is an important mediator of atrial fibrosis and atrial fibrillation (AF). This study investigated the role of TGF-β1 in human AF and the mechanism of atrial-selective fibrosis. METHODS AND RESULTS: Atrial specimens from 17 open heart surgery patients and left atrial and ventricular specimens from 17 explanted hearts were collected to assess the relationship between TGF-β1, AF, and differential atrial vs. ventricular TGF-β1 levels. A transgenic mouse model overexpressing active TGF-β1 was used to study the mechanisms underlying the resultant atrial-selective fibrosis. Higher right atrial total TGF-β1 levels (2.58 ± 0.16-fold, P < 0.0001) and active TGF-β1 (3.7 ± 0.7-fold, P = 0.013) were observed in those that developed post-operative AF. Although no ventricular differences were observed, 11 explanted heart failure hearts exhibited higher atrial TGF-β1 levels than 6 non-failing hearts (2.30 ± 0.87 fold higher, P < 0.001). In the transgenic mouse, TGF-β1 receptor-1 kinase blockade resulted in decreased atrial expression of fibrosis-related genes. By RNA microarray analyses in that model, 80 genes in the atria and only 2 genes in the ventricle were differentially expressed. Although these mice atria, but not the ventricles, exhibited increased expression of fibrosis-related genes and phosphorylation of Smad2, there were no differences in TGF-β1 receptor levels or Smads in the atria compared with the ventricles. CONCLUSIONS: TGF-β1 mediates selective atrial fibrosis in AF that occurs via TGF-β Receptor 1/2 and the classical Smad pathway. The differential atrial vs. ventricular fibrotic response occurs at the level of TGF-β1 receptor binding or phosphorylation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it