Multiscale Modeling and Parallel Simulations of Blood Flow in Cerebral Malaria an

项目简介/摘要本项目旨在为两种严重血液系统疾病：庆典疟疾（CM）和镰状细胞性贫血（SS）开发一种统一且有效的多尺度建模方法。这两种疾病的共同临床症状是微循环阻塞，主要由红细胞变形性丧失和细胞粘附性增加引起。这两种疾病都具有多尺度现象的特征，在长度尺度上跨越至少四个数量级，在时间尺度上存在相应的差异。此外，CM和SS发生的局部血管闭塞也强烈影响全身器官范围内的血流和氧运输。基于最近在红细胞光谱水平和细胞聚集过程建模方面的进展，并利用现有的千万亿次级计算资源，我们提出了一种并行的多尺度方法来模拟CM和SS，并将其用作定量评估这些疾病严重程度的预测工具。这将形成一个通用的模拟平台，以便在未来的研究中进一步增加复杂性，例如纳入更多的生化细节或研究其他溶血疾病。多尺度模型的可预测性需要量化不确定性，为此，我们将采用多项式混沌方法在多尺度系统中建模和传播参数不确定性。此外，为了验证新方法，将使用微流体实验，光学镊子测量和3D相显微镜来测试不同条件下概念和数值建模的不同方面。本项目的具体贡献包括：(1)利用分子动力学（MD）、偏微分方程（PDEs）和平均场理论，在CM（细胞骨架动力学）和SS（氧运输和聚合）中建立了细粒度和粗粒度RBC模型。(2)利用光学无创方法对不同发育阶段的感染红细胞和镰状细胞进行表征。(3)小血管内流动和流变的建模。流动建模将基于“三层”1——我们为无缝连接MD、介观动力学和Navier-Stokes方程而开发的一种新算法。对于介观动力学，我们将采用耗散粒子动力学（DPD）方法，这是一种特别有效的复杂流体模拟方法。我们计划传播我们的模型和软件工具，包括通用的三层算法，通过基于网络的存储库，现有的公共开放软件站点，暑期学校，以及通过MSM联盟。1 http://www.cfm.brown.edu/crunch/IMAG/FedosovK08.pdf

DESCRIPTION (provided by applicant): Project Summary/Abstract The objective of this project is to develop a unified and validated multiscale modeling methodology for two diseases with serious hematological disorders: celebral malaria (CM) and sickle-cell (SS) anemia. The common clinical symptom of both diseases is obstruction in the microcirculation caused primarily by loss of deformability of red blood cells (RBCs) and increased cytoadhesion. Both diseases are characterized by multiscale phenomena, spanning at least four orders of magnitude in length scale with corresponding disparity in the temporal scale. Moreover, the local vaso-oclusions occurring in CM and SS strongly affect blood flow and oxygen transport at the global organ scale as well. Building on recent progress in modeling RBCs at the spectrin level and cell-aggregation processes and taking advantage of available petaflop-level computing resources, we propose a parallel multiscale methodology to model CM and SS and use it as a predictive tool for quantitatively assessing the severity of these diseases. This will form a general simulation platform for adding further complexity in future studies, e.g., incorporating more biochemical details or studying other hemolytic disorders. Predictability of multiscale models requires quantifying uncertainty, and, to this end, we will incorporate polynomial chaos methods to model and propagate parametric uncertainties through the multiscale system. In addition, to validate the new methodology, microfluidic experiments, optical tweezers measurements and 3D phase microscopy will be used to test different aspects of the conceptual and numerical modeling under different conditions. The specific contributions of this project include: (1) Development of fine- and coarse-grained RBC models in CM (cytoskeleton dynamics) and SS (oxygen transport and polymerization) using molecular dynamics (MD), partial differential equations (PDEs), and mean-field theory. (2) Characterization of infected RBCs and sickle cells at different developmental stages using optical non-invasive means. (3) Modeling of flow and rheology in small vessels. Flow modeling will be based on the "triple-decker"1 - a new algorithm that we have developed for interfacing seamlessly MD, mesoscopic dynamics, and the Navier-Stokes equations. For mesoscopic dynamics we will employ the dissipative particle dynamics (DPD) method, a particularly effective simulation approach for complex fluids. We plan to disseminate our models and software tools, including the general-purpose triple-decker algorithm, via web-based repositories, existing public openware sites, summer schools, and through the MSM consortium. 1 http://www.cfm.brown.edu/crunch/IMAG/FedosovK08.pdf PUBLIC HEALTH RELEVANCE: We propose to develop a unified multiscale modeling methodology for two diseases with serious hematological disorders: celebral malaria (CM) and sickle-cell (SS) anemia. We will model the increase in stiffness of the deformable red blood cells and the adhesion processes involved and correspondingly blood flow in capillaries and arterioles, modeling multiscale phenomena across more than four orders of magnitude in spatio-temporal scales.