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Metal Oxide Nanomaterial QNAR Models: Available Structural Descriptors and Understanding of Toxicity Mechanisms.
Ying, Jiali; Zhang, Ting; Tang, Meng.
Affiliation
  • Ying J; Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China. yingjiali1020@163.com.
  • Zhang T; Jiangsu key Laboratory for Biomaterials and Devices, Southeast University, Nanjing 210009, China. yingjiali1020@163.com.
  • Tang M; Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China. zhangting@seu.edu.cn.
Nanomaterials (Basel) ; 5(4): 1620-1637, 2015 Oct 12.
Article in En | MEDLINE | ID: mdl-28347085
ABSTRACT
Metal oxide nanomaterials are widely used in various areas; however, the divergent published toxicology data makes it difficult to determine whether there is a risk associated with exposure to metal oxide nanomaterials. The application of quantitative structure activity relationship (QSAR) modeling in metal oxide nanomaterials toxicity studies can reduce the need for time-consuming and resource-intensive nanotoxicity tests. The nanostructure and inorganic composition of metal oxide nanomaterials makes this approach different from classical QSAR study; this review lists and classifies some structural descriptors, such as size, cation charge, and band gap energy, in recent metal oxide nanomaterials quantitative nanostructure activity relationship (QNAR) studies and discusses the mechanism of metal oxide nanomaterials toxicity based on these descriptors and traditional nanotoxicity tests.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Nanomaterials (Basel) Year: 2015 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Nanomaterials (Basel) Year: 2015 Document type: Article Affiliation country: China