Abstract 11879: Control of Fibroblast Function by Adrenergic/EPAC System and Potential Role in Atrial Remodeling
Bibliographic record
Abstract
Introduction: Heart failure (HF) produces left atrial (LA)-selective fibrosis and atrial fibrillation. HF also causes adrenergic activation, which contributes to remodeling via a variety of pathways mediated by altered signaling molecules, including the exchange protein activated by cAMP (Epac). Hypothesis: To evaluate the effects of adrenergic receptor (AR) and Epac1 signaling on LA fibroblast (FB) function and its potential role in HF-induced atrial remodeling. Methods: HF was induced in dogs by ventricular tachypacing (VTP, 240 bpm) for various periods. mRNA and protein expression were measured in freshly isolated LA FBs by qPCR and immunoblot, respectively. Results: Epac1 expression decreased in LA FBs within 12 hrs (-3.9 fold) of VTP onset (Fig. A). The selective Epac activator, 8-pCPT (33 μM) reduced, whereas the Epac blocker ESI-09 (1 μM) enhanced, LA FB collagen expression (Fig. B). Norepinephrine (NE, 1 μM) decreased Epac1 expression, an effect blocked by prazosin, and increased FB collagen protein production (Fig. C). Isoproterenol (ISO) increased Epac1 expression (Fig. D), an effect antagonized by ICI (β2-AR antagonist, 2 μM), but not CGP (β1-AR antagonist, 2 μM). β2-AR activation with ISO decreased collagen expression (Fig. E), an effect mimicked by salbutamol (10 μM) and blocked by ICI but not CGP. Transforming growth factor (TGF) β1 (10 ng/ml), known to be activated in HF, suppressed Epac1 expression, an effect blocked by the Smad3 inhibitor SIS3 (Fig. F). Conclusions: AR activation has complex effects on FBs, with NE/α-AR-activation suppressing Epac1 and increasing collagen expression, and β2-ARs having opposite effects. HF reduces LA FB Epac1 expression, likely via increased NE release from adrenergic nerve endings, along with TGF β1 activation. Epac1 signaling reduces FB collagen expression, so Epac1 downregulation in HF contributes to the atrial profibrotic milieu and may be a novel target for prevention of profibrillatory atrial remodeling.
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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) | 0.005 | 0.001 |
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".