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Fröhlich, E; Salar-Behzadi, S.
Toxicological assessment of inhaled nanoparticles: role of in vivo, ex vivo, in vitro, and in silico studies.
Int J Mol Sci. 2014; 15(3):4795-4822 Doi: 10.3390/ijms15034795 [OPEN ACCESS]
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Führende Autor*innen der Med Uni Graz
Fröhlich Eleonore
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Abstract:
The alveolar epithelium of the lung is by far the most permeable epithelial barrier of the human body. The risk for adverse effects by inhaled nanoparticles (NPs) depends on their hazard (negative action on cells and organism) and on exposure (concentration in the inhaled air and pattern of deposition in the lung). With the development of advanced in vitro models, not only in vivo, but also cellular studies can be used for toxicological testing. Advanced in vitro studies use combinations of cells cultured in the air-liquid interface. These cultures are useful for particle uptake and mechanistic studies. Whole-body, nose-only, and lung-only exposures of animals could help to determine retention of NPs in the body. Both approaches also have their limitations; cellular studies cannot mimic the entire organism and data obtained by inhalation exposure of rodents have limitations due to differences in the respiratory system from that of humans. Simulation programs for lung deposition in humans could help to determine the relevance of the biological findings. Combination of biological data generated in different biological models and in silico modeling appears suitable for a realistic estimation of potential risks by inhalation exposure to NPs.
Find related publications in this database (using NLM MeSH Indexing)
Animals -
Cell Culture Techniques - methods
Computer Simulation -
Disease Models, Animal -
Humans -
Inhalation Exposure -
Lung Diseases - diagnosis
Lung Diseases - etiology
Nanoparticles - administration & dosage
Nanoparticles - chemistry
Nanoparticles - toxicity
Reproducibility of Results -
Toxicity Tests - methods

Find related publications in this database (Keywords)
cell culture
air-liquid interface
inhalation exposure models
species differences
in silico modeling
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