Cardiac Fibroblast Glycogen Synthase Kinase-3β Regulates Ventricular Remodeling and Dysfunction in Ischemic Heart
Bibliographic record
Abstract
BACKGROUND: Myocardial infarction-induced remodeling includes chamber dilatation, contractile dysfunction, and fibrosis. Of these, fibrosis is the least understood. After myocardial infarction, activated cardiac fibroblasts deposit extracellular matrix. Current therapies to prevent fibrosis are inadequate, and new molecular targets are needed. METHODS AND RESULTS: Herein we report that glycogen synthase kinase-3β (GSK-3β) is phosphorylated (inhibited) in fibrotic tissues from ischemic human and mouse heart. Using 2 fibroblast-specific GSK-3β knockout mouse models, we show that deletion of GSK-3β in cardiac fibroblasts leads to fibrogenesis, left ventricular dysfunction, and excessive scarring in the ischemic heart. Deletion of GSK-3β induces a profibrotic myofibroblast phenotype in isolated cardiac fibroblasts, in post-myocardial infarction hearts, and in mouse embryonic fibroblasts deleted for GSK-3β. Mechanistically, GSK-3β inhibits profibrotic transforming growth factor-β1/SMAD-3 signaling via interactions with SMAD-3. Moreover, deletion of GSK-3β resulted in the significant increase of SMAD-3 transcriptional activity. This pathway is central to the pathology because a small-molecule inhibitor of SMAD-3 largely prevented fibrosis and limited left ventricular remodeling. CONCLUSIONS: These studies support targeting GSK-3β in myocardial fibrotic disorders and establish critical roles of cardiac fibroblasts in remodeling and ventricular dysfunction.
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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 | 0.000 |
| 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".