Cardiac tissue engineering: state-of-the-art methods and outlook
Abstract The purpose of this review is to assess the state-of-the-art fabrication methods, advances in genome editing, and the use of machine learning to shape the prospective growth in cardiac tissue engineering. Those interdisciplinary emerging innovations would move forward basic research in this...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-06-01
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| Series: | Journal of Biological Engineering |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13036-019-0185-0 |
| _version_ | 1818418170602455040 |
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| author | Anh H. Nguyen Paul Marsh Lauren Schmiess-Heine Peter J. Burke Abraham Lee Juhyun Lee Hung Cao |
| author_facet | Anh H. Nguyen Paul Marsh Lauren Schmiess-Heine Peter J. Burke Abraham Lee Juhyun Lee Hung Cao |
| author_sort | Anh H. Nguyen |
| collection | DOAJ |
| description | Abstract The purpose of this review is to assess the state-of-the-art fabrication methods, advances in genome editing, and the use of machine learning to shape the prospective growth in cardiac tissue engineering. Those interdisciplinary emerging innovations would move forward basic research in this field and their clinical applications. The long-entrenched challenges in this field could be addressed by novel 3-dimensional (3D) scaffold substrates for cardiomyocyte (CM) growth and maturation. Stem cell-based therapy through genome editing techniques can repair gene mutation, control better maturation of CMs or even reveal its molecular clock. Finally, machine learning and precision control for improvements of the construct fabrication process and optimization in tissue-specific clonal selections with an outlook of cardiac tissue engineering are also presented. |
| first_indexed | 2024-12-14T12:18:25Z |
| format | Article |
| id | doaj.art-1fc9343e088f41378e74079e6e13ca82 |
| institution | Directory Open Access Journal |
| issn | 1754-1611 |
| language | English |
| last_indexed | 2024-12-14T12:18:25Z |
| publishDate | 2019-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biological Engineering |
| spelling | doaj.art-1fc9343e088f41378e74079e6e13ca822022-12-21T23:01:34ZengBMCJournal of Biological Engineering1754-16112019-06-0113112110.1186/s13036-019-0185-0Cardiac tissue engineering: state-of-the-art methods and outlookAnh H. Nguyen0Paul Marsh1Lauren Schmiess-Heine2Peter J. Burke3Abraham Lee4Juhyun Lee5Hung Cao6Electrical and Computer Engineering Department, University of AlbertaElectrical Engineering and Computer Science Department, University of California IrvineElectrical Engineering and Computer Science Department, University of California IrvineElectrical Engineering and Computer Science Department, University of California IrvineBiomedical Engineering Department, University of California IrvineBioengineering Department, University of Texas at ArlingtonElectrical Engineering and Computer Science Department, University of California IrvineAbstract The purpose of this review is to assess the state-of-the-art fabrication methods, advances in genome editing, and the use of machine learning to shape the prospective growth in cardiac tissue engineering. Those interdisciplinary emerging innovations would move forward basic research in this field and their clinical applications. The long-entrenched challenges in this field could be addressed by novel 3-dimensional (3D) scaffold substrates for cardiomyocyte (CM) growth and maturation. Stem cell-based therapy through genome editing techniques can repair gene mutation, control better maturation of CMs or even reveal its molecular clock. Finally, machine learning and precision control for improvements of the construct fabrication process and optimization in tissue-specific clonal selections with an outlook of cardiac tissue engineering are also presented.http://link.springer.com/article/10.1186/s13036-019-0185-0Cardiac tissue engineeringCRISPR/Cas9 systems3D scaffoldsMachine learning |
| spellingShingle | Anh H. Nguyen Paul Marsh Lauren Schmiess-Heine Peter J. Burke Abraham Lee Juhyun Lee Hung Cao Cardiac tissue engineering: state-of-the-art methods and outlook Journal of Biological Engineering Cardiac tissue engineering CRISPR/Cas9 systems 3D scaffolds Machine learning |
| title | Cardiac tissue engineering: state-of-the-art methods and outlook |
| title_full | Cardiac tissue engineering: state-of-the-art methods and outlook |
| title_fullStr | Cardiac tissue engineering: state-of-the-art methods and outlook |
| title_full_unstemmed | Cardiac tissue engineering: state-of-the-art methods and outlook |
| title_short | Cardiac tissue engineering: state-of-the-art methods and outlook |
| title_sort | cardiac tissue engineering state of the art methods and outlook |
| topic | Cardiac tissue engineering CRISPR/Cas9 systems 3D scaffolds Machine learning |
| url | http://link.springer.com/article/10.1186/s13036-019-0185-0 |
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