Collaborative Research: Transport of model-virus through the lung liquid lining

合作研究：模型病毒通过肺液层的运输

• 批准号: 2204081
• 负责人: Amir Hirsa
• 金额: $ 28.55万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2204081&HistoricalAwards=false
• 关键词: Collaborative; Research; Transport; model; virus

The novel coronavirus SARS-CoV-2, responsible for the COVID-19 pandemic, is similar to other respiratory coronaviruses, such as SARS-CoV (2002) and MERS-CoV (2012). All these viruses cause dangerous respiratory disorders with high mortality and grave impacts on society. This virus destroys the cells that produce lung surfactants which, among other things, keep the alveoli air-sacks from collapsing, and eventually the lungs fill with liquid. The two primary functions of lung surfactants are regulating the interfacial tension and surface viscosities of the liquid lining of the alveoli, and providing a first line of immune defense against airborne pathogens. The fluid dynamic interactions between the liquid lining of the lung, the lung surfactants, and the respiratory virus are presently not well understood. This project addresses this gap by conducting experiments and numerical modeling to capture the essential fluid dynamics of a model virus interacting with the primary insoluble component of lung surfactant. The expansion and contraction of the alveoli will be modeled using an open cavity with oscillatory sidewalls that expand and compress the liquid layer. The numerical models will then be used to simulate physiologically relevant scales, not accessible experimentally. Aside from the flow in the lung liquid lining, the present knowledge gap in predictive modeling of interfacial dilation and compression is hampering developments in other areas, such as in water waves, which are of utmost importance in modeling of carbon dioxide gas exchange between the atmosphere and the oceans.Predictive models for the transport of small particles in a surfactant-covered liquid layer will be developed. A key advancement in the proposed modeling of surface elasticity is to measure the equation-of-state of the monolayer in a state corresponding to that found when it has been subjected to a large number of dilation/compression cycles. The usual approach of determining properties of a recently spread monolayer undergoing slow compression is inappropriate for modeling monolayer hydrodynamics coupled to an oscillatory bulk flow, as the monolayer is in a different state with very different interfacial properties. The role of interfacial dilatational viscosity and its significance relative to surface elasticity remains poorly understood and presents a major impediment to the predictive modeling of free-surface flows. The PIs have a proven track record of productive multidisciplinary collaboration, and will continue to provide a unique educational opportunity for the graduate and undergraduate students.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

导致COVID-19大流行的新型冠状病毒SARS-CoV-2与其他呼吸道冠状病毒相似，如SARS-CoV（2002）和MERS-CoV（2012）。所有这些病毒都会引起危险的呼吸系统疾病，死亡率很高，对社会造成严重影响。这种病毒会破坏产生肺表面活性物质的细胞，这些表面活性物质可以防止肺泡气囊塌陷，最终使肺充满液体。肺表面活性剂的两个主要功能是调节肺泡液体衬里的界面张力和表面粘度，并提供针对空气传播病原体的第一道免疫防御。 肺的液体衬里、肺表面活性剂和呼吸道病毒之间的流体动力学相互作用目前还不清楚。该项目通过进行实验和数值模拟来捕捉模型病毒与肺表面活性物质的主要不溶性成分相互作用的基本流体动力学，从而解决了这一差距。肺泡的膨胀和收缩将使用具有膨胀和压缩液体层的振荡侧壁的开放腔来建模。然后，将使用数值模型来模拟生理相关的尺度，实验无法访问。 除了肺液体衬里的流动，目前在界面扩张和压缩的预测建模方面的知识差距阻碍了其他领域的发展，例如在水波方面，这对大气和海洋之间的二氧化碳气体交换建模至关重要。在所提出的表面弹性建模的一个关键的进步是测量状态方程的单层在对应的状态下发现，当它已经受到了大量的扩张/压缩循环。通常的方法来确定最近蔓延的单层经历缓慢的压缩性能是不合适的单层流体动力学耦合到振荡的整体流建模，因为单层是在一个不同的状态，非常不同的界面特性。界面粘性的作用及其相对于表面弹性的意义仍然知之甚少，并提出了一个主要的障碍，自由表面流动的预测建模。PI在多学科合作方面有着良好的记录，并将继续为研究生和本科生提供独特的教育机会。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。