BMP7 counteracts TGF beta1 induced endothelial-to-mesenchymal transition in viral cardiomyopathy and its potential mechanism
Bibliographic record
Abstract
Purpose: Cardiac fibrosis is the most important histological characteristics of viral cardiomyopathy and is associated with poor prognosis and therapeutic interventions. BMP7 is a member of TGF-β superfamily and was reported to counteract the effects of TGF-β1. This study was designed to evaluate whether BMP7 administration could reduce fibrosis induced by CVB3 infection and its potential mechanism. Methods: Viral myocarditis mice model was made and BMP7 was administrated to infected mice. Fourteen days after CVB3 infection, echocardiography, Sirius Red staining and hematoxylin-eosin (HE) were performed to describe the cardiac function and histological characteristics. Colocation of endothelial markers and mesenchymal markers were identified using confocal immunofluorescence staining. Western blot was performed to evaluate the TGF-β1/smad and Wnt/β-catenin signaling pathway. Results: A mice model of CVB3 myocarditis was made and BMP7 was administrated to CVB3-infected mice. Histological data demonstrated that BMP7 administration reduced inflammatory cells accumulation and cardiac fibrosis in response to CVB3 challenge. Echo data described cardiac dysfunction was recovered after BMP7 intervention. Double labeling of endothelial and mesenchymal markers showed BMP7-treated mice had significantly reduced the double-positive cells. Western blot described that TGF-β1/smad and Wnt/β-catenin signaling pathway was involved in this pathogenesis. Conclusions: BMP7 counteracts TGF-β1 induced endothelial-to-mesenchymal transition in viral cardiomyopathy through both TGF-β1/smad and Wnt/β-catenin signaling pathway. The research is supported by grant from the Health Joint-research Program of the National Natural Science Foundation of China and Canadian Institutes of Health Research (81010007) and National Natural Science Foundation of China (31070786)
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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".