Department of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA.
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
Ann Biomed Eng. 2023 May;51(5):1094-1105. doi: 10.1007/s10439-023-03193-2. Epub 2023 Apr 5.
Platelet adhesion to blood vessel walls is a key initial event in thrombus formation in both vascular disease processes and prosthetic cardiovascular devices. We extended a deformable multiscale model (MSM) of flowing platelets, incorporating Dissipative Particle Dynamics (DPD) and Coarse-Grained Molecular Dynamics (CGMD) describing molecular-scale intraplatelet constituents and their interaction with surrounding flow, to predict platelet adhesion dynamics under physiological flow shear stresses. Binding of platelet glycoprotein receptor Ibα (GPIbα) to von Willebrand factor (vWF) on the blood vessel wall was modeled by a molecular-level hybrid force field and validated with in vitro microchannel experiments of flowing platelets at 30 dyne/cm. High frame rate videos of flipping platelets were analyzed with a Semi-Unsupervised Learning System (SULS) machine learning-guided imaging approach to segment platelet geometries and quantify adhesion dynamics parameters. In silico flipping dynamics followed in vitro measurements at 15 and 45 dyne/cm with high fidelity, predicting GPIbα-vWF bonding and debonding processes, distribution of bonds strength, and providing a biomechanical insight into initiation of the complex platelet adhesion process. The adhesion model and simulation framework can be further integrated with our established MSMs of platelet activation and aggregation to simulate initial mural thrombus formation on blood vessel walls.
血小板黏附于血管壁是血管疾病和心血管假体中血栓形成的初始关键事件。我们扩展了一个可变形多尺度模型（MSM），用于描述流动血小板中的耗散粒子动力学（DPD）和粗粒分子动力学（CGMD），以预测生理流动剪切应力下的血小板黏附动力学。血小板糖蛋白受体 Ibα（GPIbα）与血管壁上的血管性血友病因子（vWF）的结合通过分子水平的混合力场进行建模，并通过在 30 达因/厘米的流动血小板体外微通道实验进行验证。使用半无监督学习系统（SULS）机器学习引导的成像方法对翻转血小板的高帧率视频进行分析，以分割血小板的几何形状并量化黏附动力学参数。在计算机中，翻转动力学与 15 和 45 达因/厘米的体外测量高度吻合，预测 GPIbα-vWF 键合和去键合过程、键合强度分布，并为复杂血小板黏附过程的启动提供生物力学见解。该黏附模型和模拟框架可以进一步与我们现有的血小板激活和聚集的 MSM 集成，以模拟血管壁上初始壁血栓的形成。
