Model Predicts Nanoparticle Toxicity

Model Predicts Nanoparticle Toxicity

Author: ChemistryViews

Metal oxide (MOx) nanoparticles are in high volume and frequently used for their semiconducting properties, including as catalysts for redox reactions in engineered systems and natural environments. From a biological perspective, the semiconducting properties could be responsible for generating adverse health outcomes.

Using 24 representative MOx, Andre E. Nel and colleagues, University of California, Los Angeles, USA, demonstrate that the toxicity of MOx nanoparticles closely correlates with their semiconducting property and band positions. The team predicted that six were likely to be toxic: TiO2, Ni2O3, CoO, Cr2O3, Co3O4, and Mn2O3 and correlated the overlap of conduction band energy (Ec) levels with the cellular redox potential to the ability of these nanoparticles to induce oxygen radicals, oxidative stress, and inflammation.

The team exposed human bronchial and mouse blood cells to each of the 24 nanoparticles and tested the nanoparticles’ effects on live animals’ health by forcing mice to inhale suspensions of the materials. The MOx that caused toxicity to cells also caused inflammation in the animals’ lungs. All six predicted MOx except TiO2 as well as CuO and ZnO, which dissolve in water to release toxic metal ions, were found to be toxic.

These results provide a novel platform for establishing MOx structure—activity relationships based on band energy levels and particle dissolution. The in silico hazard ranking and statistical tools can be used to establish a predictive toxicological paradigm, in which in vitro toxicological ranking can be used to predict the in vivo toxicological outcome.


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