Toxicity Evaluation of Nanoparticles

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Bol The increasing production and application of nanomaterials inevitably release these materials into the environment, causing adverse impacts on the ecosystems and human health. Such toxicities must be reliably assessed, their mechanisms elucidated, and their risks predicted. Therefore, it is essential to develop powerful methods for evaluating nanotoxicity, such as in vitro methods (e.g., cell-based or cell-free testing), animal tests (e.g., zebra fish or rat), and computational modeling. Given this background, this Special Issue assembles high-quality original research and review papers that highlight investigations on nanotoxicity using various biological models and in-depth mechanism elucidation. This Special Issue also focuses on applications of advanced machine learning, deep learning algorithms in nanotoxicity modeling and prediction, and molecular simulation in elucidating the mechanisms for emerging nanomaterials

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The increasing production and application of nanomaterials inevitably release these materials into the environment, causing adverse impacts on the ecosystems and human health. Such toxicities must be reliably assessed, their mechanisms elucidated, and their risks predicted. Therefore, it is essential to develop powerful methods for evaluating nanotoxicity, such as in vitro methods (e.g., cell-based or cell-free testing), animal tests (e.g., zebra fish or rat), and computational modeling. Given this background, this Special Issue assembles high-quality original research and review papers that highlight investigations on nanotoxicity using various biological models and in-depth mechanism elucidation. This Special Issue also focuses on applications of advanced machine learning, deep learning algorithms in nanotoxicity modeling and prediction, and molecular simulation in elucidating the mechanisms for emerging nanomaterials

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Pages: 184, Hardcover, Mdpi AG


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  • 9783725876952
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