Cargando…

Comparative Toxic Effects of Manufactured Nanoparticles and Atmospheric Particulate Matter in Human Lung Epithelial Cells

Although nanoparticles (NPs) have been used as simplified atmospheric particulate matter (PM) models, little experimental evidence is available to support such simulations. In this study, we comparatively assessed the toxic effects of PM and typical NPs (four carbonaceous NPs with different morpholo...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Yun, Wang, Mei, Luo, Shaojuan, Gu, Yunfeng, Nie, Dongyang, Xu, Zhiyang, Wu, Yue, Chen, Mindong, Ge, Xinlei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7792937/
https://www.ncbi.nlm.nih.gov/pubmed/33375152
http://dx.doi.org/10.3390/ijerph18010022
Descripción
Sumario:Although nanoparticles (NPs) have been used as simplified atmospheric particulate matter (PM) models, little experimental evidence is available to support such simulations. In this study, we comparatively assessed the toxic effects of PM and typical NPs (four carbonaceous NPs with different morphologies, metal NPs of Fe, Al, and Ti, as well as SiO(2) NPs) on human lung epithelial A549 cells. The EC50 value of PM evaluated by cell viability assay was 148.7 μg/mL, closest to that of SiO(2) NPs, between the values of carbonaceous NPs and metal NPs. All particles caused varying degrees of reactive oxygen species (ROS) generation and adenosine triphosphate (ATP) suppression. TiO(2) NPs showed similar performance with PM in inducing ROS production (p < 0.05). Small variations between two carbonaceous NPs (graphene oxides and graphenes) and PM were also observed at 50 μg/mL. Similarly, there was no significant difference in ATP inhibition between carbonaceous NPs and PM, while markedly different effects were caused by SiO(2) NP and TiO(2) NP exposure. Our results indicated that carbonaceous NPs could be served as potential surrogates for urban PM. The identification of PM model may help us further explore the specific roles and mechanisms of various components in PM.