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• W2923266813 abstract "Abstract Cell viability and cytotoxicity assays are highly important for drug screening and cytotoxicity tests of antineoplastic or other therapeutic drugs. Even though biochemical-based tests are very helpful to obtain preliminary preview, their results should be confirmed by methods based on direct cell death assessment. In this study, time-dependent changes in quantitative phase-based parameters during cell death were determined and methodology useable for rapid and label-free assessment of direct cell death was introduced. Our method utilizes Quantitative Phase Imaging (QPI) which enables the time-lapse observation of subtle changes in cell mass distribution. According to our results, morphological and dynamical features extracted from QPI micrographs are suitable for cell death detection (76% accuracy in comparison with manual annotation). Furthermore, based on QPI data alone and machine learning, we were able to classify typical dynamical changes of cell morphology during both caspase 3,7-dependent and independent cell death subroutines. The main parameters used for label-free detection of these cell death modalities were cell density (pg/pixel) and average intensity change of cell pixels further designated as Cell Dynamic Score (CDS). To the best of our knowledge, this is the first study introducing CDS and cell density as a parameter typical for individual cell death subroutines with prediction accuracy 75.4 % for caspase 3,7-dependent and -independent cell death." @default.
• W2923266813 created "2019-04-01" @default.
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• W2923266813 date "2019-03-27" @default.
• W2923266813 modified "2023-09-25" @default.
• W2923266813 title "Detection and characterization of apoptotic and necrotic cell death by time-lapse quantitative phase image analysis" @default.
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• W2923266813 doi "https://doi.org/10.1101/589697" @default.
• W2923266813 hasPublicationYear "2019" @default.
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