論文

査読有り 国際誌
2020年4月4日

Machine-learning-based quality control of contractility of cultured human-induced pluripotent stem-cell-derived cardiomyocytes.

Biochemical and Biophysical Research Communications
  • Ken Orita
  • ,
  • Kohei Sawada
  • ,
  • Nobuyoshi Matsumoto
  • ,
  • Yuji Ikegaya

記述言語
英語
掲載種別
DOI
10.1016/j.bbrc.2020.03.141

The precise and early assessment of cardiotoxicity is fundamental to bring forward novel drug candidates to the pharmaceutical market and to avoid their withdrawal from the market. Recent preclinical studies have attempted to use human-induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs) to predict clinical cardiotoxicity, but the heterogeneity and inconsistency in the functional qualities of the spontaneous contractility of hiPSC-CMs across cell culture wells and product lots still matter. To rapidly assess the functional qualities of hiPSC-CMs without histological labeling, we optically detected the contractility of confluently cultured hiPSC-CMs using bright-field microscopy. Using a method that consisted of data preprocessing, data augmentation, dimensionality reduction, and supervised learning, we succeeded in precisely discriminating between functionally normal and abnormal contractions of hiPSC-CMs.

リンク情報
DOI
https://doi.org/10.1016/j.bbrc.2020.03.141
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/32265031
ID情報
  • DOI : 10.1016/j.bbrc.2020.03.141
  • PubMed ID : 32265031

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