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Annals of biomedical engineering
May, 2023;51 (5): 1094-1105.

A Multiscale Model for Shear-Mediated Platelet Adhesion Dynamics: Correlating In Silico with In Vitro Results.

Peineng Wang, Jawaad Sheriff, Peng Zhang, Yuefan Deng, Danny Bluestein
Author Information
  1. Peineng Wang: Department of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA.
  2. Jawaad Sheriff: Department of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA.
  3. Peng Zhang: Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
  4. Yuefan Deng: Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
  5. Danny Bluestein: Department of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA. danny.bluestein@stonybrook.edu. ORCID
PMID: 37020171 DOI: 10.1007/s10439-023-03193-2

Abstract

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.

Keywords

Dissipative particle dynamics GPIbα-vWF bond Machine learning Molecular dynamics Platelet kinematics

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Grants

  1. U01 HL131052/NHLBI NIH HHS
  2. R01 HL131052/NHLBI NIH HHS

MeSH Term

Humans
von Willebrand Factor
Protein Binding
Platelet Adhesiveness
Blood Platelets
Molecular Dynamics Simulation
Thrombosis

Chemicals

von Willebrand Factor
Journal Article

Word Cloud

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