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Biotechnology and bioengineering v.115 no.8, 2018년, pp.1958 - 1970   SCI SCIE
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

Quantitatively characterizing drug‐induced arrhythmic contractile motions of human stem cell‐derived cardiomyocytes

Hoang, Plansky (Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York ) ; Huebsch, Nathaniel (Department of Bioengineering, University of California, Berkeley, California ) ; Bang, Shin Hyuk (Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York ) ; Siemons, Brian A. (Department of Bioengineering, University of California, Berkeley, California ) ; Conklin, Bruce R. (Glastone Institute of Cardiovascular Diseases, San Francisco, California ) ; Healy, Kevin E. (Department of Bioengineering, University of California, Berkeley, California ) ; Ma, Zhen (Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York ) ; Jacquir, Sabir (Laboratoire LE2I UMR CNRS 6306, Université ) ;
  • 초록  

    Abstract Quantification of abnormal contractile motions of cardiac tissue has been a noteworthy challenge and significant limitation in assessing and classifying the drug‐induced arrhythmias (i.e., Torsades de pointes). To overcome these challenges, researchers have taken advantage of computational image processing tools to measure contractile motion from cardiomyocytes derived from human induced pluripotent stem cells (hiPSC‐CMs). However, the amplitude and frequency analysis of contractile motion waveforms does not produce sufficient information to objectively classify the degree of variations between two or more sets of cardiac contractile motions. In this paper, we generated contractile motion data from beating hiPSC‐CMs using motion tracking software based on optical flow analysis, and then implemented a computational algorithm, phase space reconstruction (PSR), to derive parameters (embedding, regularity, and fractal dimensions) to further characterize the dynamic nature of the cardiac contractile motions. Application of drugs known to cause cardiac arrhythmia induced significant changes to these resultant dimensional parameters calculated from PSR analysis. Integrating this new computational algorithm with the existing analytical toolbox of cardiac contractile motions will allow us to expand current assessments of cardiac tissue physiology into an automated, high‐throughput, and quantifiable manner which will allow more objective assessments of drug‐induced proarrhythmias.


  • 주제어

    arrhythmia .   biosignal processing .   cardiac motion .   phase space reconstruction .   optical flow.  

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