Computational modeling of cardiac fibroblasts and fibrosis
| Autor: | William J. Richardson, Angela C. Zeigler, Jeffrey W. Holmes, Jeffrey J. Saucerman |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Systems biology 030204 cardiovascular system & hematology Biology Fibroblast growth factor Models Biological Article Extracellular matrix 03 medical and health sciences 0302 clinical medicine Fibrosis medicine Animals Humans Computer Simulation Myocytes Cardiac Epithelial–mesenchymal transition Fibroblast Molecular Biology Myocardium Arrhythmias Cardiac Fibroblasts medicine.disease Phenotype Extracellular Matrix Cell biology 030104 developmental biology medicine.anatomical_structure Immunology Signal transduction Cardiology and Cardiovascular Medicine Signal Transduction |
| Zdroj: | Journal of Molecular and Cellular Cardiology. 93:73-83 |
| ISSN: | 0022-2828 |
| DOI: | 10.1016/j.yjmcc.2015.11.020 |
| Popis: | Altered fibroblast behavior can lead to pathologic changes in the heart such as arrhythmia, diastolic dysfunction, and systolic dysfunction. Computational models are increasingly used as a tool to identify potential mechanisms driving a phenotype or potential therapeutic targets against an unwanted phenotype. Here we review how computational models incorporating cardiac fibroblasts have clarified the role for these cells in electrical conduction and tissue remodeling in the heart. Models of fibroblast signaling networks have primarily focused on fibroblast cell lines or fibroblasts from other tissues rather than cardiac fibroblasts, specifically, but they are useful for understanding how fundamental signaling pathways control fibroblast phenotype. In the future, modeling cardiac fibroblast signaling, incorporating -omics and drug-interaction data into signaling network models, and utilizing multi-scale models will improve the ability of in silico studies to predict potential therapeutic targets against adverse cardiac fibroblast activity. |
| Databáze: | OpenAIRE |
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