Literature DB >> 21851323

Noninvasive evaluation of contractile behavior of cardiomyocyte monolayers based on motion vector analysis.

Tomohiro Hayakawa1, Takeshi Kunihiro, Suguru Dowaki, Hatsume Uno, Eriko Matsui, Masashi Uchida, Seiji Kobayashi, Akio Yasuda, Tatsuya Shimizu, Teruo Okano.   

Abstract

A noninvasive method for the characterization of cardiomyocyte contractile behavior is presented. Light microscopic video images of cardiomyocytes were captured with a high-speed camera, and motion vectors (which have a velocity dimension) were calculated with a high spatiotemporal resolution using a block-matching algorithm. This method could extract contraction and relaxation motions of cardiomyocytes separately and evaluate characteristics such as the beating rate, orientation of contraction, beating cooperativity/homogeneity in the monolayer, and wave propagation of impulses. Simultaneous phase-contrast imaging and calcium (Ca2+) fluorescence measurements confirmed that the timing of the maximum shortening velocity of cardiomyocytes correlated well with intracellular Ca2+ transients. Based on our analysis, gap junction inhibitors, 1-heptanol (2 mM) or 18-β-glycyrrhetinic acid (30 μM), resulted in clear changes in beating cooperativity and the propagation pattern of impulses in the cardiomyocyte monolayer. Additionally, the time dependence of the motion vector length indicated a prolonged relaxation process in the presence of potassium (K+) channel blockers, dl-sotalol (1 μM), E-4031 (100 nM), or terfenadine (100 nM), reflecting the prolonged QT (Q wave and T wave) interval of cardiomyocytes. Effects of autonomic agents (acetylcholine or epinephrine [EPI]) or EPI and propranolol on cardiomyocytes were clearly detected by the alterations of beating rate and the motion vector length in contraction and relaxation processes. This method was noninvasive and could sensitively evaluate the contractile behavior of cardiomyocytes; therefore, it may be used to study and/or monitor cardiomyocyte tissue during prolonged culture periods and in screens for drugs that may alter the contraction of cardiomyocytes.

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Year:  2011        PMID: 21851323     DOI: 10.1089/ten.TEC.2011.0273

Source DB:  PubMed          Journal:  Tissue Eng Part C Methods        ISSN: 1937-3384            Impact factor:   3.056


  18 in total

1.  Modeling Secondary Iron Overload Cardiomyopathy with Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes.

Authors:  June-Wha Rhee; Hyoju Yi; Dilip Thomas; Chi Keung Lam; Nadjet Belbachir; Lei Tian; Xulei Qin; Jessica Malisa; Edward Lau; David T Paik; Youngkyun Kim; Beatrice SeungHye Choi; Nazish Sayed; Karim Sallam; Ronglih Liao; Joseph C Wu
Journal:  Cell Rep       Date:  2020-07-14       Impact factor: 9.423

2.  Reflective lens-free imaging on high-density silicon microelectrode arrays for monitoring and evaluation of in vitro cardiac contractility.

Authors:  Thomas Pauwelyn; Richard Stahl; Lakyn Mayo; Xuan Zheng; Andy Lambrechts; Stefan Janssens; Liesbet Lagae; Veerle Reumers; Dries Braeken
Journal:  Biomed Opt Express       Date:  2018-03-22       Impact factor: 3.732

3.  iPSC-derived functional human neuromuscular junctions model the pathophysiology of neuromuscular diseases.

Authors:  Chuang-Yu Lin; Michiko Yoshida; Li-Tzu Li; Akihiro Ikenaka; Shiori Oshima; Kazuhiro Nakagawa; Hidetoshi Sakurai; Eriko Matsui; Tatsutoshi Nakahata; Megumu K Saito
Journal:  JCI Insight       Date:  2019-09-19

4.  Automated Video-Based Analysis of Contractility and Calcium Flux in Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes Cultured over Different Spatial Scales.

Authors:  Nathaniel Huebsch; Peter Loskill; Mohammad A Mandegar; Natalie C Marks; Alice S Sheehan; Zhen Ma; Anurag Mathur; Trieu N Nguyen; Jennie C Yoo; Luke M Judge; C Ian Spencer; Anand C Chukka; Caitlin R Russell; Po-Lin So; Bruce R Conklin; Kevin E Healy
Journal:  Tissue Eng Part C Methods       Date:  2015-01-14       Impact factor: 3.056

5.  Integrated platform for functional monitoring of biomimetic heart sheets derived from human pluripotent stem cells.

Authors:  Aaron Chen; Eugene Lee; Roger Tu; Kevin Santiago; Anna Grosberg; Charless Fowlkes; Michelle Khine
Journal:  Biomaterials       Date:  2013-10-18       Impact factor: 15.304

6.  Machine learning plus optical flow: a simple and sensitive method to detect cardioactive drugs.

Authors:  Eugene K Lee; Yosuke K Kurokawa; Robin Tu; Steven C George; Michelle Khine
Journal:  Sci Rep       Date:  2015-07-03       Impact factor: 4.379

7.  Endothelin-1 induces myofibrillar disarray and contractile vector variability in hypertrophic cardiomyopathy-induced pluripotent stem cell-derived cardiomyocytes.

Authors:  Atsushi Tanaka; Shinsuke Yuasa; Giulia Mearini; Toru Egashira; Tomohisa Seki; Masaki Kodaira; Dai Kusumoto; Yusuke Kuroda; Shinichiro Okata; Tomoyuki Suzuki; Taku Inohara; Takuro Arimura; Shinji Makino; Kensuke Kimura; Akinori Kimura; Tetsushi Furukawa; Lucie Carrier; Koichi Node; Keiichi Fukuda
Journal:  J Am Heart Assoc       Date:  2014-11-11       Impact factor: 5.501

8.  Evolution of the fish heart by sub/neofunctionalization of an elastin gene.

Authors:  Yuuta Moriyama; Fumihiro Ito; Hiroyuki Takeda; Tohru Yano; Masataka Okabe; Shigehiro Kuraku; Fred W Keeley; Kazuko Koshiba-Takeuchi
Journal:  Nat Commun       Date:  2016-01-19       Impact factor: 14.919

9.  Machine Learning Techniques to Classify Healthy and Diseased Cardiomyocytes by Contractility Profile.

Authors:  Diogo Teles; Youngbin Kim; Kacey Ronaldson-Bouchard; Gordana Vunjak-Novakovic
Journal:  ACS Biomater Sci Eng       Date:  2021-06-21

10.  Video image-based analysis of single human induced pluripotent stem cell derived cardiomyocyte beating dynamics using digital image correlation.

Authors:  Antti Ahola; Anna L Kiviaho; Kim Larsson; Markus Honkanen; Katriina Aalto-Setälä; Jari Hyttinen
Journal:  Biomed Eng Online       Date:  2014-04-07       Impact factor: 2.819

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