Chapter title |
Fabrication of a myocardial patch with cells differentiated from human-induced pluripotent stem cells.
|
---|---|
Chapter number | 8 |
Book title |
Cardiomyocytes
|
Published in |
Methods in molecular biology, January 2015
|
DOI | 10.1007/978-1-4939-2572-8_8 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2571-1, 978-1-4939-2572-8
|
Authors |
Ye, Lei, Basu, Joydeep, Zhang, Jianyi, Lei Ye, Joydeep Basu, Jianyi Zhang |
Abstract |
The incidence of cardiovascular disease represents a significant and growing health-care challenge to the developed and developing world. The ability of native heart muscle to regenerate in response to myocardial infarct is minimal. Tissue engineering and regenerative medicine approaches represent one promising response to this difficulty. Here, we present methods for the construction of a cell-seeded cardiac patch with the potential to promote regenerative outcomes in heart muscle with damage secondary to myocardial infarct. This method leverages iPS cells and a fibrin-based scaffold to create a simple and commercially viable tissue-engineered cardiac patch. Human-induced pluripotent stem cells (hiPSCs) can, in principle, be differentiated into cells of any lineage. However, most of the protocols used to generate hiPSC-derived endothelial cells (ECs) and cardiomyocytes (CMs) are unsatisfactory because the yield and phenotypic stability of the hiPSC-ECs are low, and the hiPSC-CMs are often purified via selection for expression of a promoter-reporter construct. In this chapter, we describe an hiPSC-EC differentiation protocol that generates large numbers of stable ECs and an hiPSC-CM differentiation protocol that does not require genetic manipulation, single-cell selection, or sorting with fluorescent dyes or other reagents. We also provide a simple but effective method that can be used to combine hiPSC-ECs and hiPSC-CMs with hiPSC-derived smooth muscle cells to engineer a contracting patch of cardiac cells. |
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Mendeley readers
Geographical breakdown
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Unknown | 21 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 6 | 29% |
Student > Postgraduate | 4 | 19% |
Student > Bachelor | 3 | 14% |
Other | 2 | 10% |
Student > Ph. D. Student | 1 | 5% |
Other | 2 | 10% |
Unknown | 3 | 14% |
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Agricultural and Biological Sciences | 5 | 24% |
Medicine and Dentistry | 4 | 19% |
Engineering | 2 | 10% |
Materials Science | 1 | 5% |
Other | 1 | 5% |
Unknown | 3 | 14% |