Aerosol physicochemical determinants of carbon black and ozone inhalation co-exposure induced pulmonary toxicity

Toxicological Sciences(2022)

引用 3|浏览11
暂无评分
摘要
Abstract Air pollution accounts for more than 7 million premature deaths worldwide. Using ultrafine carbon black (CB) and ozone (O3) as a model for an environmental co-exposure scenario, the dose response relationships in acute pulmonary injury and inflammation were determined by generating, characterizing, and comparing stable concentrations of CB aerosols (2.5, 5.0, 10.0 mg/m3), O3 (0.5, 1.0, 2.0 ppm) with mixture CB+O3 (2.5 + 0.5, 5.0 + 1.0, 10.0 + 2.0). C57BL6 male mice were exposed for 3 hours by whole body inhalation and acute toxicity determined after 24 h. CB itself did not cause any alteration, however, a dose response in pulmonary injury/inflammation was observed with O3 and CB+O3. This increase in response with mixtures was not dependent on the uptake but due to enhanced reactivity of the particles. Benchmark dose modeling showed several-fold increase in potency with CB+O3 compared to CB or O3 alone. Principal component analysis provided insight into response relationships between various doses and treatments. There was a significant correlation in lung responses with charge-based size distribution, total/alveolar deposition, oxidant generation and antioxidant depletion potential. Lung tissue gene/protein response demonstrated distinct patterns that are better predicted by either particle dose/aerosol responses (IL-1β, KC, TGF-β) or particle reactivity (TSLP, IL13, IL-6). Hierarchical clustering showed a distinct signature with high dose and a similarity in mRNA expression pattern of low and medium doses of CB+O3. In conclusion, we demonstrate that the biological outcomes from CB+O3 co-exposure are significantly greater than individual exposures over a range of aerosol concentrations and aerosol characteristics can predict biological outcome.
更多
查看译文
关键词
ozone,ultrafine carbon black,physicochemical properties,inhalation,co-exposure,inflammation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要