JAK-STAT signalling and the atrial fibrillation promoting fibrotic substrate
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Left-atrial (LA) fibrosis is an important feature of many atrial fibrillation (AF) substrates. The JAK-STAT system contributes to cardiac remodelling, but its role in AF is unknown. Here we investigated JAK-STAT changes in an AF-model and their potential contributions to LA-fibrosis. METHODS AND RESULTS: LA-remodelling was studied in dogs with heart failure (HF) induced by ventricular tachypacing (VTP, 240 bpm), and in mice with left-ventricular (LV) dysfunction due to myocardial infarction (MI). The selective STAT-3 inhibitor S3I-201 was administered to fibroblasts in vitro or mice in vivo (10 mg/kg/d, osmotic mini-pump). HF-dogs developed LA-selective fibrosis and AF-susceptibility at 1-week VTP. The mRNA-expression of platelet-derived growth factor (PDGF, a JAK-STAT activator) isoforms A, C and D, as well as JAK2, increased in LA fibroblasts from 1-week VTP. HF upregulated protein-expression of PDGF-receptor-β and phosphorylated (activated) signal transducer and activator of transcription 3 (STAT3) in LA. PDGF-AB stimulation of LA fibroblasts increased PDGFR-α, STAT3 and phosphorylated-STAT3 expression, as well as collagen-1 and fibronectin-1 protein secretion (by 1.6- to 20-fold), with smaller changes in LV fibroblasts. Phosphorylated-STAT3 and collagen upregulation were suppressed by the JAK2 inhibitor AG-490, PDGF receptor inhibitor AG1296 and STAT3-inhibitor SI3-201. In vivo S3I-201 treatment of MI-mice attenuated LA-fibrosis, LA-dilation and P-wave duration changes versus vehicle-control. CONCLUSIONS: HF activates the LA JAK-STAT system and enhances PDGF-signalling. JAK-STAT inhibition reduces the profibrotic effects of PDGF stimulation on canine fibroblasts in vitro while attenuating in vivo LA-fibrosis and remodelling in post-MI mice, suggesting that the JAK/STAT pathway contributes to LA-fibrogenesis and might be a potential target for LA-fibrosis prevention.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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