A novel statistical signal processing method to estimate effects of compounds on contractility of cardiomyocytes using impedance assays

Abstract : Label free methods such as cell impedance assays are in vitro tests increasingly used in drug development and producing large and high-content data files. Since the current commercial software are not suited for fully automated analysis , there is a need to develop validated and rapid solutions to extract relevant information for biologists. This need is particularly obvious in the case of impedance signals analysis from cardiomyocytes. The proposed solution is based on three main steps. The first one consists in calculating five indices informing about the time variations of frequency (F), amplitude (A), shape (S) of beatings, trends (T) of the cardiomyocyte dependent on spreading, viability and attachment as well as irregularity (I) of the contractility. In a second phase, two summary statistics are proposed to test the concentration effect of drugs on the five FASTI indices. Results of the statistical tests are finally aggregated in a cardio-effect grade to compare the tested molecules in a cardio-impact scale graduated from 0 (no influence) to 10 (highly disturbed effects in cardiomy-ocytes). This innovative approach was tested using in vitro data obtained from cell impedance analysis of three known molecules (2 cardiotoxic and 1 non-cardiotoxic compounds). Results have clearly shown the ability of the proposed approach to identify significant effects on the contractility of cardiomyocytes. This solution speeds up the analysis of cardiomyocyte impedance data, takes into account all the kinetic data generated and is now available for biologists on a web-platform: i-Cardio TM developed by CYBERnano TM .
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Lévy Batista, Thierry Bastogne, Annie Delaunois, Jean-Pierre Valentin, Franck Atienzar. A novel statistical signal processing method to estimate effects of compounds on contractility of cardiomyocytes using impedance assays. Biomedical Signal Processing and Control, Elsevier, 2018, 45, pp.202-212. ⟨10.1016/j.bspc.2018.05.038⟩. ⟨hal-01621227⟩

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