气溶剂量测量的多尺度模型的自动双向合:通过对象特定的沉积数据进行验证
A P Kuprat1, O Price2, B Asgharian2
1Pacific Northwest National Laboratory, Richland, WA, USA.
这项研究改进了in silico肺模型,以准确预测吸入颗粒沉积. 经过验证的模型增强了对呼吸系统中气溶行为的理解,用于药物输送和毒性评估.
科学领域:
- 呼吸系统科学 呼吸系统科学
- 计算生物学 计算生物学
- 气溶科学 气溶科学
背景情况:
- 精确估计吸入物质在呼吸系统中的沉积对于评估空气中的颗粒物毒性和吸入药物的有效性至关重要.
- 在 silico (计算) 方法提供了宝贵的见解,在复杂的呼吸道内的特定地点的气溶沉积.
- 以前的3D/1D模型模拟了气溶的运输和沉积,但需要进一步细化,以进行全肺,多呼吸的预测.
研究的目的:
- 增强先前开发的3D/1D模型,以模拟整个呼吸系统的气溶运输和沉积在多个呼吸周期内.
- 通过将其预测与健康男性受试者在各种呼吸条件和颗粒大小下的实验数据进行比较来验证改进的模型.
主要方法:
- 为上呼吸道 (口腔到大支气管) 开发了集成计算流体粒子动力学 (CFPD) 的专用多尺度肺模型.
- 双向将3D CFPD模型与改进的多路径粒子剂量计 (MPPD) 模型相结合,覆盖整个呼吸道.
- 在缓慢 (~300毫升/秒) 和快速 (~750毫升/秒) 的呼吸速率 (1升潮体积) 中,模拟了1微米和2.9微米颗粒的气溶沉积.
主要成果:
- 在模型准确地预测了气溶保留分数,显示了与实验数据对粒子大小和呼吸速率的良好一致.
- 预测1μm颗粒的保留分数为0.31 (缓慢) 和0.29 (快速),与实验值 (0.31±0.01和0.27±0.01) 非常接近.
- 预测2.9微米颗粒的保留分数为0.66 (缓慢) 和0.62 (快速),也与实验值 (0.63±0.03和0.68±0.02) 有很好的一致性.
结论:
- 增强的3D/1D合模型为预测整个呼吸道的气溶沉积提供了有效和可靠的方法.
- 该模型的准确性,与实验数据进行验证,支持其在涉及吸入物质的研究中的实用性.
- 这种精细的计算工具可以推进吸入药物的疗效和空气中微粒的毒理影响的评估.
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