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• W2891486408 abstract "With the emerging concern over the potential toxicity associated with carbon nanotube inhalation exposure, several in vitro methods have been developed to evaluate cellular responses. Since the major concern for adverse effects by carbon nanotubes is inhalation, various lung cell culture models have been established for toxicity testing, thus creating a wide variation of methodology. Limited studies have conducted side-by-side comparisons of common methods used for carbon nanotube hazard testing. The aim of this work was to use proteomics to evaluate global cellular response, including pro-inflammatory and pro-fibrotic mediators, of a 3D lung model composed of macrophages, epithelial cells, and fibroblasts which mimics the human alveolar epithelial tissue barrier. The cells were exposed to Mitsui 7 (M-7) multi-walled carbon nanotubes (MWCNT) under submerged and air-liquid interface (ALI) conditions and discovery proteomics identified 3500 proteins. The M-7 ALI exposure compared to control was found to increase expression in proteins related to oxidative stress that were not found to be enriched in submerged exposure. Comparison of MWCNT exposure methods, M-7 ALI exposure versus M-7 submerged exposure, yielded protein enrichment in pathways known to be associated with carbon nanotube exposure stress response, such as acute phase response signaling and NRF2-mediated oxidative stress response. This study demonstrates a comparison of commonly deployed carbon nanotube exposure methods. These data should be considered by the nanotoxicology community when interpreting or cross comparing in vitro exposure results." @default.
• W2891486408 created "2018-09-27" @default.
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• W2891486408 date "2019-02-01" @default.
• W2891486408 modified "2023-10-14" @default.
• W2891486408 title "Leveraging proteomics to compare submerged versus air-liquid interface carbon nanotube exposure to a 3D lung cell model" @default.
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• W2891486408 doi "https://doi.org/10.1016/j.tiv.2018.09.010" @default.
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• W2891486408 hasPublicationYear "2019" @default.
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