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    In silico cytotoxicity assessment on cultured rat intestinal cells deduced from cellular impedance measurements (2017)

    Art
    Zeitschriftenartikel / wissenschaftlicher Beitrag
    Autoren
    Gupta, P
    Gramatke, A
    Einspanier, R (WE 3)
    Schütte, C
    von Kleist, M
    Sharbati, J (WE 3)
    Quelle
    Toxicology in vitro; 41 — S. 179–188
    ISSN: 0887-2333
    Sprache
    Englisch
    Verweise
    DOI: 10.1016/j.tiv.2017.02.021
    Pubmed: 28263893
    Kontakt
    Institut für Veterinär-Biochemie

    Oertzenweg 19 b
    14163 Berlin
    +49 30 838 62225
    biochemie@vetmed.fu-berlin.de

    Abstract / Zusammenfassung

    Early and reliable identification of chemical toxicity is of utmost importance. At the same time, reduction of animal testing is paramount. Therefore, methods that improve the interpretability and usability of in vitro assays are essential. xCELLigence's real-time cell analyzer (RTCA) provides a novel, fast and cost effective in vitro method to probe compound toxicity. We developed a simple mathematical framework for the qualitative and quantitative assessment of toxicity for RTCA measurements. Compound toxicity, in terms of its 50% inhibitory concentration IC50 on cell growth, and parameters related to cell turnover were estimated on cultured IEC-6 cells exposed to 10 chemicals at varying concentrations. Our method estimated IC50 values of 113.05, 7.16, 28.69 and 725.15 μM for the apparently toxic compounds 2-acetylamino-fluorene, aflatoxin B1, benzo-[a]-pyrene and chloramphenicol in the tested cell line, in agreement with literature knowledge. IC50 values of all apparent in vivo non-toxic compounds were estimated to be non-toxic by our method. Corresponding estimates from RTCA's in-built model gave false positive (toxicity) predictions in 5/10 cases. Taken together, our proposed method reduces false positive predictions and reliably identifies chemical toxicity based on impedance measurements. The source code for the developed method including instructions is available at https://git.zib.de/bzfgupta/toxfit/tree/master.