Particle dispersion in morphologically-inspired computational models of alveolar capillary networks

H. Stauber, Rami Fishler, Philipp Hofemeier, D. Waisman, J. Sznitman
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引用次数: 1

Abstract

With growing evidence of the ability of inhaled nanoparticles (NP) to translocate from the lungs into the pulmonary circulation, increased concerns regarding the fate of such particles reaching body organs have risen. Until present, there is still a limited understanding on the transport dynamics of NPs following translocation into the pulmonary microcirculation. To gain initial insight into such processes, simulations of the transport and dispersion of various particle sizes are conducted in anatomically-inspired alveolar capillary networks (ACN). Our models, based on the seminal 'sheet flow' model, investigate quantitatively the influence of network porosity on particle dynamics. For fixed flow conditions, we find that the effective dispersion coefficient is sensibly enhanced with decreasing porosity levels and decreasing particle sizes. Furthermore, particle size significantly influences the characteristics of particle spreading and tortuosity. Overall, our findings represent a tangible first step in further understanding inhaled NP transport in networks representative of the alveolar capillaries.
肺泡毛细血管网络形态学启发计算模型中的粒子分散
随着越来越多的证据表明吸入的纳米颗粒(NP)能够从肺部转移到肺循环,人们越来越关注这些颗粒到达身体器官的命运。到目前为止,对NPs转运进入肺微循环后的转运动力学的了解仍然有限。为了初步了解这一过程,我们在解剖启发的肺泡毛细血管网络(ACN)中模拟了不同粒径的颗粒的运输和分散。我们的模型基于种子“薄片流”模型,定量地研究了网络孔隙度对颗粒动力学的影响。在固定流量条件下,有效分散系数随孔隙度和粒径的减小而显著增大。此外,颗粒的大小对颗粒的扩散和扭曲特性有显著影响。总的来说,我们的研究结果代表了进一步了解肺泡毛细血管网络中吸入NP转运的切实的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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