| Autor: |
Golbamaki A; a Department of Environmental Health Sciences , Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri , Milan , Italy., Golbamaki N; a Department of Environmental Health Sciences , Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri , Milan , Italy., Sizochenko N; b Interdisciplinary Center for Nanotoxicity , Jackson State University , Jackson , MS , USA.; c Department of Computer Science , Dartmouth College, Sudikoff Lab , Hanover , NH , USA., Rasulev B; b Interdisciplinary Center for Nanotoxicity , Jackson State University , Jackson , MS , USA.; d Department of Coatings and Polymeric Materials , North Dakota State University , Fargo , ND , USA., Leszczynski J; b Interdisciplinary Center for Nanotoxicity , Jackson State University , Jackson , MS , USA., Benfenati E; a Department of Environmental Health Sciences , Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri , Milan , Italy. |
| Abstrakt: |
The genetic toxicology of nanomaterials is a crucial toxicology issue and one of the least investigated topics. Substantially, the genotoxicity of metal oxide nanomaterials' data is resulting from in vitro comet assay. Current contributions to the genotoxicity data assessed by the comet assay provide a case-by-case evaluation of different types of metal oxides. The existing inconsistency in the literature regarding the genotoxicity testing data requires intelligent assessment strategies, such as weight of evidence evaluation. Two main tasks were performed in the present study. First, the genotoxicity data from comet assay for 16 noncoated metal oxide nanomaterials with different core composition were collected. An evaluation criterion was applied to establish which of these individual lines of evidence were of sufficient quality and what weight could have been given to them in inferring genotoxic results. The collected data were surveyed on (1) minimum necessary characterization points for nanomaterials and (2) principals of correct comet assay testing for nanomaterials. Second, in this study the genotoxicity effect of metal oxide nanomaterials was investigated by quantitative nanostructure-activity relationship approach. A set of quantum-chemical descriptors was developed for all investigated metal oxide nanomaterials. A classification model based on decision tree was developed for the investigated dataset. Thus, three descriptors were identified as the most responsible factors for genotoxicity effect: heat of formation, molecular weight, and surface area of the oxide cluster based on the conductor-like screening model. Conclusively, the proposed genotoxicity assessment strategy is useful to prioritize the study of the nanomaterials for further risk assessment evaluations. |
