【摘 要】
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A key challenge to using in vitro data in risk assessment is differentiating between chemical-induced adaptive versus adverse cellular responses.To further investigate this issue, we studied the effec
【机 构】
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National Center for Computational Toxicology, Office of Research and Development, EPA.Research Trian
【出 处】
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2016(第二届)毒性测试替代方法与转化毒理学(国际)学术研讨会暨有害结局路径(AOP)与风险评估培训会议
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A key challenge to using in vitro data in risk assessment is differentiating between chemical-induced adaptive versus adverse cellular responses.To further investigate this issue, we studied the effects of hundreds of chemicals in HepG2 cells using high-content imaging (HCI).HCI measured chemical dose and time-dependent perturbations in p53, JNK, oxidative stress, cytoskeleton, mitochondria, and cell cycle progression.We developed a novel computational model to analyze these multidimensional HCI datastreams, and used this model to interpret the dynamic responses to chemicals as cell-state trajectories.By analyzing trajectories for each chemical we found three concentration-dependent trends in HepG2 cell behaviors including: (a) adaptation followed by complete recovery, (a) adaptation followed by partial recovery, and (c) adaptation without recovery leading to irreversible injury.We believe that the concentration-dependent transition from adaptation to injury is a "tipping point" for the system.Tipping points are generally observed at chemical concentrations far below cytotoxic levels.We believe that rich HCI data for chemicals can be interpreted with computational models to find tipping points, and to gain mechanistic insight into the threshold for homeostatic adaptation.With additional work, tipping points could also be used as the point of departure for risk assessment.
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