Mass Transfer Phenomena in the Lymphatic System

本研究项目的主要目的是量化淋巴肌肉细胞（LMCs）在舒张直径和跨壁压力范围内的多种尺度的收缩性。这一目标的动机是由于收缩力在淋巴推进中的重要性以及淋巴阀功能所需的压力差的产生。从这项研究中获得的知识将被纳入基于集总参数和计算质量传递方法的淋巴系统流动的多尺度模型中。这将使用实验和计算方法来完成，主要实验由合作者进行，然后作为研究项目的一部分开发理论模型。将进行实验以获得确定作为上游和下游压力函数的收缩力所需的数据。将进行两个系列的实验，第一个系列将包括管状淋巴管，改变压力和测量内外血管直径。第二个系列的实验将使用钢丝肌图来确定孤立淋巴管的长度-张力关系。这个项目将使用计算方法来处理实验结果，因为lmc的收缩性只能间接测量。从实验结果中确定收缩力应以平衡圆周力为基础。第一组实验的几何数据和淋巴管内压力的测量结果将结合起来计算收缩力。第二系列实验的分析将根据力传感器的测量值和平均壁厚计算收缩张力，并将结果与五个或更多淋巴管的有限元模型进行比较。在目前的平滑肌细胞模型的基础上进一步建模，将需要将收缩性纳入淋巴流模型。这项研究将是原创的，因为目前还没有单一的平滑肌模型可以应用于所有系统，淋巴系统的平滑肌与研究重点系统的平滑肌有很大的不同。因此，这项研究将是第一个在生理范围内量化和模拟lmc收缩性的研究。该项目还将包括参与研究小组的其他研究目标，这些目标是描述淋巴阀的阻力和迟滞，并开发淋巴结中流体流动和白细胞行为的模型。这些目标的结果也将被纳入淋巴系统运输现象的多尺度模型。淋巴阀的表征将涉及阀门的实验表征和所涉及的固体和流体力学的计算模型，这将最终结合在一个流固耦合模型中。淋巴结的建模将涉及通过淋巴结的淋巴流动的计算流体动力学，以及淋巴结中细胞的基于agent的建模。计算流体动力学和基于主体的模型将最终结合起来，提供一个更全面的淋巴结模型。

The primary aim of this research project is to quantify the contractility of lymphatic muscle cells (LMCs) across multiple scales for a range of diastolic diameters and transmural pressures. This aim is motivated by the importance of contractile force in lymph propulsion and the generation of pressure differences required for the function of lymphatic valves. The knowledge gained from this research will be incorporated into multi-scale models of flow in the lymphatic system, which are based on lumped parameter and computational mass transport approaches. This is to be done using both experimental and computational methods, with the main experiments being performed by collaborators and theoretical models then being developed as part of the research project. The experiments will be performed to obtain data required for determining contractile force as a function of the upstream and downstream pressures. Two series of experiments will be performed, the first series will consist of cannulating lymphatic vessels, varying the pressure and measuring both the internal and external vessel diameters. The second series of experiments will use a wire myograph to determine the length-tension relationship of isolated lymphatic vessels. This project will then use computational methods required to process the experimental results because the contractility of the LMCs can only be measured indirectly. The determination of contractility from experimental results is to be based on balancing the circumferential forces. Geometrical data and measurements of the pressure within the lymphangion from the first series of experiments will be combined for the calculation of contractile force. Analysis of the second series of experiments will calculate the contractile tension from measurements of the force transducer and average wall thickness, and the results will be compared with a finite element model of five or more lymphangions. Further modelling based on current models of smooth muscle cells will be required for incorporation of the contractility into the lymphatic flow models. This research will be original as there is currently no single model of smooth muscle that can be applied to all systems and the smooth muscle in lymphatics is significantly different from that in the systems which have been the focus of research. This research will therefore be the first to quantify and model the contractility of LMCs over the physiologic range.The project will also include involvement in the other research aims of the research group, which are to characterize the resistance and hysteresis of lymphatic valves, and to develop models of fluid flow and leukocyte behaviour in lymph nodes. The results from these aims will also be incorporated into multi-scale models of the transport phenomena of the lymphatic system. Characterization of the lymphatic valves will involve experimental characterization of valves and computational models of the solid and fluid mechanics involved, which will ultimately be combined in a fluid-structure interaction model. Modelling the lymph nodes will involve computational fluid dynamics of lymph flow through the node, and agent-based modelling of the cells in lymph nodes. The computational fluid dynamics and agent-based models will ultimately be coupled to provide a more comprehensive model of lymph nodes.