A Stochastic Molecular Dynamics Method for Multiscale Modeling of Blood Platlet Pheonmena

血小板现象多尺度建模的随机分子动力学方法

基本信息

  • 批准号:
    0506312
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2005
  • 资助国家:
    美国
  • 起止时间:
    2005-09-15 至 2009-08-31
  • 项目状态:
    已结题

项目摘要

It is now well established that platelet aggregation is not only important for primary hemostasis but, when exaggerated, can also lead to the formation of occlusive thrombi, which form at sites of atherosclerotic plaque rupture, resulting in a heart attack, stroke or sudden death. Platelets are micron-size cells - smaller than red blood cells - and when activated they become adhesive for other activated platelets and they adhere to the vessel wall. Their strong interaction with nano-size proteins at the sub-endothelium matrix activates and reshapes them from passively traveling discoids to active spiny spheres. The length and time scales characterizing such interactions as well as platelet-blood flow interactions span several orders of magnitude.We propose a multiscale modeling methodology with focus on flow-modulated phenomena such as platelet adhesion and aggregation at the micron-scale, and including nanoscale effects representing the main protein interactions. We will develop an integrated approach by coupling multiscale representations of blood flow, ranging from a quasi 1D transient flow in compliant vessels at the largest scale, to unsteady 3D flows in curved and flexing vessels at the mm range, to multi micron-scale thrombus formation at a fissure in the lumen of such a vessel with an atherosclerotic plaque, to changes over short times (seconds and minutes) in the behavior of platelet structure, receptors and bonds in a developing thrombus-wall interaction. To this end, we will develop a new mesoscopic numerical method that bridges the gap between atomistic phenomena and large-scale phenomena to seamlessly connect length scales from 10 nm to a few mm. The new simulation approach will be validated systematically against experiments of varying biological and computational complexity.We also propose to establish a virtual center for multiscale modeling in order to provide modelers and experimentalists with quantitative information about molecular and cellullar processes that can be incorporated into simplified models. To this end, we plan to organize a workshop on multiscale modeling of biological processes during the second year of the proposed project. In our outreach program, we plan to engage pre-college women from the Providence area in computer and computational sciences. This will involve lectures by our medical collaborators as well as interactive learning at Brown's virtual immersive visualization facility.The potential impact of this work is great as it provides a new simulation capability for studying biomolecular interactions in blood vessels, organs and the entire arterial tree in a few hours instead of days or even weeks on a supercomputer. This, in turn, will allow fundamental studies at the molecular and cellular level and interaction with macroscales not currently possible with existing methodologies.
现在已经确定,血小板聚集不仅对主要止血很重要,而且当过度时,还可导致闭塞性血栓的形成,其在动脉粥样硬化斑块破裂部位形成,导致心脏病发作、中风或猝死。血小板是微米大小的细胞-比红细胞小-当活化时,它们成为其他活化血小板的粘合剂,并粘附在血管壁上。它们与内皮下基质中纳米大小的蛋白质的强烈相互作用激活并重塑它们,使其从被动移动的盘状体变为主动的多刺球体。这种相互作用以及血小板-血流相互作用的特征的长度和时间尺度跨越几个数量级,我们提出了一个多尺度建模方法,专注于流动调制的现象,如血小板粘附和聚集在微米级,包括纳米级的影响,代表主要的蛋白质相互作用。我们将通过耦合血流的多尺度表示来开发一种综合方法,范围从最大尺度下顺应性血管中的准1D瞬态流到mm范围内弯曲和挠曲血管中的不稳定3D流,再到具有动脉粥样硬化斑块的此类血管的管腔中的裂缝处的多微米尺度血栓形成,血小板结构、受体和键在血栓-壁相互作用中的行为在短时间内(秒和分钟)发生变化。为此目的,我们将发展一种新的介观数值方法,弥合原子现象和大尺度现象之间的差距,新的模拟方法将在不同生物学和计算复杂性的实验中得到系统的验证。我们还建议建立一个多尺度建模的虚拟中心,以便为建模者和实验者提供有关分子和细胞过程的定量信息,可以纳入简化模型。为此,我们计划在拟议项目的第二年组织一个关于生物过程多尺度建模的研讨会。在我们的推广计划中,我们计划让来自普罗维登斯地区的大学前妇女参与计算机和计算科学。这项工作的潜在影响是巨大的,因为它提供了一种新的模拟能力,可以在几个小时内研究血管、器官和整个动脉树中的生物分子相互作用,而不是在超级计算机上进行几天甚至几周的研究。这反过来将允许在分子和细胞水平上进行基础研究,并与目前用现有方法无法实现的宏观尺度相互作用。

项目成果

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George Karniadakis其他文献

Correction to: A computational mechanics special issue on: data-driven modeling and simulation—theory, methods, and applications
  • DOI:
    10.1007/s00466-019-01747-7
  • 发表时间:
    2019-06-28
  • 期刊:
  • 影响因子:
    3.800
  • 作者:
    Wing Kam Liu;George Karniadakis;Shaoqiang Tang;Julien Yvonnet
  • 通讯作者:
    Julien Yvonnet
Physics-Informed Learning Machines for Partial Differential Equations: Gaussian Processes Versus Neural Networks
用于偏微分方程的物理学习机:高斯过程与神经网络
Simulating and visualizing the human arterial system on the TeraGrid
  • DOI:
    10.1016/j.future.2006.03.019
  • 发表时间:
    2006-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Suchuan Dong;Joseph Insley;Nicholas T. Karonis;Michael E. Papka;Justin Binns;George Karniadakis
  • 通讯作者:
    George Karniadakis
En-DeepONet: An enrichment approach for enhancing the expressivity of neural operators with applications to seismology
  • DOI:
    10.1016/j.cma.2023.116681
  • 发表时间:
    2024-02-15
  • 期刊:
  • 影响因子:
  • 作者:
    Ehsan Haghighat;Umair bin Waheed;George Karniadakis
  • 通讯作者:
    George Karniadakis
CMINNs: Compartment model informed neural networks — Unlocking drug dynamics
  • DOI:
    10.1016/j.compbiomed.2024.109392
  • 发表时间:
    2025-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Nazanin Ahmadi Daryakenari;Shupeng Wang;George Karniadakis
  • 通讯作者:
    George Karniadakis

George Karniadakis的其他文献

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{{ truncateString('George Karniadakis', 18)}}的其他基金

Collaborative Research: AMPS: Multi-Fidelity Modeling via Machine Learning for Real-time Prediction of Power System Behavior
合作研究:AMPS:通过机器学习进行多保真度建模,实时预测电力系统行为
  • 批准号:
    1736088
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
MANNA 2017: Modeling, Analysis, and Numerics for Nonlocal Applications
MANNA 2017:非局部应用的建模、分析和数值
  • 批准号:
    1747867
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
New evolution equations of the joint response-excitation PDF for stochastic modeling: Theory and numerical methods
用于随机建模的联合响应激励 PDF 的新演化方程:理论和数值方法
  • 批准号:
    1216437
  • 财政年份:
    2012
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
Collaborative Research: Scalable Multiscale Models for the Cerebrovasculature: Algorithms, Software and Petaflop Simulations
合作研究:可扩展的脑血管多尺度模型:算法、软件和千万亿次模拟
  • 批准号:
    0904288
  • 财政年份:
    2009
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Multiscale Modeling of Flow over Functionalized Surfaces: Algorithms and Applications
功能化表面流动的多尺度建模:算法和应用
  • 批准号:
    0852948
  • 财政年份:
    2009
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Overcoming the Bottlenecks in Polynomial Chaos: Algorithms and Applications to Systems Biology and Fluid Mechanics
克服多项式混沌的瓶颈:系统生物学和流体力学的算法和应用
  • 批准号:
    0915077
  • 财政年份:
    2009
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Multiscale Models and Petaflops Simulations on the Human Brain Vascular Network
人脑血管网络的多尺度模型和千万亿次模拟
  • 批准号:
    0845449
  • 财政年份:
    2008
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
International Conference on Spectral and High-Order Methods 2009 - ICOSAHOM'09; June 2009, Trondheim, Norway
2009 年光谱和高阶方法国际会议 - ICOSAHOM09;
  • 批准号:
    0839866
  • 财政年份:
    2008
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
CI-TEAM Implementation Project: Collaborative Research: Training Simulation Scientists in Advanced Cyberinfrastructure Tools and Concepts
CI-TEAM 实施项目:协作研究:培训模拟科学家掌握先进的网络基础设施工具和概念
  • 批准号:
    0636336
  • 财政年份:
    2006
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
AMC-SS: A Multi-Element Generalized Polynomial Chaos Method for Modeling Uncertainty in Flow Simulations
AMC-SS:一种用于流体仿真中不确定性建模的多元素广义多项式混沌方法
  • 批准号:
    0510799
  • 财政年份:
    2005
  • 资助金额:
    --
  • 项目类别:
    Standard Grant

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