Withaferin-A Reduces Type I Collagen Expression In Vitro and Inhibits Development of Myocardial Fibrosis In Vivo
Bibliographic record
Abstract
Type I collagen is the most abundant protein in the human body. Its excessive synthesis results in fibrosis of various organs. Fibrosis is a major medical problem without an existing cure. Excessive synthesis of type I collagen in fibrosis is primarily due to stabilization of collagen mRNAs. We recently reported that intermediate filaments composed of vimentin regulate collagen synthesis by stabilizing collagen mRNAs. Vimentin is a primary target of Withaferin-A (WF-A). Therefore, we hypothesized that WF-A may reduce type I collagen production by disrupting vimentin filaments and decreasing the stability of collagen mRNAs. This study is to determine if WF-A exhibits anti-fibrotic properties in vitro and in vivo and to elucidate the molecular mechanisms of its action. In lung, skin and heart fibroblasts WF-A disrupted vimentin filaments at concentrations of 0.5-1.5 µM and reduced 3 fold the half-lives of collagen α1(I) and α2(I) mRNAs and protein expression. In addition, WF-A inhibited TGF-β1 induced phosphorylation of TGF-β1 receptor I, Smad3 phosphorylation and transcription of collagen genes. WF-A also inhibited in vitro activation of primary hepatic stellate cells and decreased their type I collagen expression. In mice, administration of 4 mg/kg WF-A daily for 2 weeks reduced isoproterenol-induced myocardial fibrosis by 50%. Our findings provide strong evidence that Withaferin-A could act as an anti-fibrotic compound against fibroproliferative diseases, including, but not limited to, cardiac interstitial fibrosis.
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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".