Cardiac tissue engineering: state-of-the-art methods and outlook

Anh H Nguyen; Paul Marsh; Lauren Schmiess-Heine; Peter J Burke; Abraham Lee; Juhyun Lee; Hung Cao

doi:10.1186/s13036-019-0185-0

Cardiac tissue engineering: state-of-the-art methods and outlook

J Biol Eng. 2019 Jun 28:13:57. doi: 10.1186/s13036-019-0185-0. eCollection 2019.

Authors

Anh H Nguyen^#^{1

2}, Paul Marsh^#², Lauren Schmiess-Heine², Peter J Burke^{2

3

4}, Abraham Lee^{3

5}, Juhyun Lee⁶, Hung Cao^{2

3

7}

Affiliations

¹ 1Electrical and Computer Engineering Department, University of Alberta, Edmonton, Alberta Canada.
² 2Electrical Engineering and Computer Science Department, University of California Irvine, Irvine, CA USA.
³ 3Biomedical Engineering Department, University of California Irvine, Irvine, CA USA.
⁴ 4Chemical Engineering and Materials Science Department, University of California Irvine, Irvine, CA USA.
⁵ 5Mechanical and Aerospace Engineering Department, University of California Irvine, Irvine, CA USA.
⁶ 6Bioengineering Department, University of Texas at Arlington, Arlington, TX USA.
⁷ 7Henry Samueli School of Engineering, University of California, Irvine, USA.

^# Contributed equally.

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.

Keywords: 3D scaffolds; CRISPR/Cas9 systems; Cardiac tissue engineering; Machine learning.

Publication types

Review

Grants and funding

R41 OD024874/OD/NIH HHS/United States