Predicting the in vivo pulmonary toxicity induced by acute exposure to poorly soluble nanomaterials by using advanced in vitro methods

使用先进的体外方法预测急性暴露于难溶性纳米材料引起的体内肺毒性

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作者:Thomas Loret, Françoise Rogerieux, Bénédicte Trouiller, Anne Braun, Christophe Egles, Ghislaine Lacroix

Background

Animal models remain at that time a reference tool to predict potential pulmonary adverse effects of nanomaterials in humans. However, in a context of reduction of the number of animals used in experimentation, there is a need for reliable alternatives. In vitro models using lung cells represent relevant alternatives to assess potential nanomaterial acute toxicity by inhalation, particularly since advanced in vitro

Conclusions

We showed that advanced methods could be used to enhance in vitro experiments ability to predict potential acute pulmonary toxicity in vivo. Moreover, we showed that the timing of the dose delivery could be controlled to enhance the predictivity. Further studies should be necessary to assess if air-liquid interface provide more reliable ranking of nanomaterials than submerged methods.

Results

For each dose metric used (mass/alveolar surface or mass/macrophage), we observed that the most realistic in vitro exposure method, the air-liquid interface method, was the most predictive of in vivo effects regarding biological activation levels. We also noted less differences between in vivo and in vitro results when doses were normalized by the number of macrophages rather than by the alveolar surface. Lastly, although we observed similarities in the nanomaterial ranking using in vivo and in vitro approaches, the quality of the data-set was insufficient to provide clear ranking comparisons. Conclusions: We showed that advanced methods could be used to enhance in vitro experiments ability to predict potential acute pulmonary toxicity in vivo. Moreover, we showed that the timing of the dose delivery could be controlled to enhance the predictivity. Further studies should be necessary to assess if air-liquid interface provide more reliable ranking of nanomaterials than submerged methods.

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