Modeling In Vivo Interactions of Engineered Nanoparticles in the Pulmonary Alveolar Lining Fluid

Nanomaterials

Dwaipayan Mukherjee¹  Alexandra Porter³  Mary Ryan³  Stephan Schwander⁵  Kian Fan Chung²  Teresa Tetley²  Junfeng Zhang⁴  Panos Georgopoulos¹ 

[1] Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University, 170 Frelinghuysen Road, Piscataway, NJ 08854, USA; E-Mail:;National Heart and Lung Institute, Imperial College London, Dovehouse Street, London SW3 6LY, UK; E-Mails:;Department of Materials and London Centre of Nanotechnology, Imperial College London, Exhibition Road, London SW7 2AZ, UK; E-Mails:;Nicholas School of the Environment and Duke Global Health Institute, Duke University, 9 Circuit Drive, Durham, NC 27708, USA; E-Mail:;Department of Environmental and Occupational Health, School of Public Health, Rutgers University, 683 Hoes Lane West, Piscataway, NJ 08854, USA; E-Mail:

关键词: nanoparticles;    surfactant;    agglomeration;    adsorption;    lipid vesicles;    surfactant proteins;    Monte Carlo;   

DOI  :  10.3390/nano5031223

来源: mdpi

【 摘 要 】

Increasing use of engineered nanomaterials (ENMs) in consumer products may result in widespread human inhalation exposures. Due to their high surface area per unit mass, inhaled ENMs interact with multiple components of the pulmonary system, and these interactions affect their ultimate fate in the body. Modeling of ENM transport and clearance in vivo has traditionally treated tissues as well-mixed compartments, without consideration of nanoscale interaction and transformation mechanisms. ENM agglomeration, dissolution and transport, along with adsorption of biomolecules, such as surfactant lipids and proteins, cause irreversible changes to ENM morphology and surface properties. The model presented in this article quantifies ENM transformation and transport in the alveolar air to liquid interface and estimates eventual alveolar cell dosimetry. This formulation brings together established concepts from colloidal and surface science, physics, and biochemistry to provide a stochastic framework capable of capturing essential in vivo processes in the pulmonary alveolar lining layer. The model has been implemented for in vitro solutions with parameters estimated from relevant published in vitro measurements and has been extended here to in vivo systems simulating human inhalation exposures. Applications are presented for four different ENMs, and relevant kinetic rates are estimated, demonstrating an approach for improving human in vivo pulmonary dosimetry.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.