Literature DB >> 18068201

Interactions of blood cell constituents: experimental investigation and computational modeling by discrete particle dynamics algorithm.

N Filipovic1, D Ravnic, M Kojic, S J Mentzer, S Haber, A Tsuda.   

Abstract

When the size of individual blood constituents [e.g., red blood cells (RBCs), white blood cells, platelets] becomes comparable to the size of blood vessels, the interactions among blood constituents in determining the blood behavior can no longer be ignored. In this paper, we have developed a comprehensive computational model to simulate the motion of an individual platelet in the plasma medium and its binding to the microvessel wall. The model is based on a Discrete Particle Dynamics (DPD) algorithm, in which blood plasma, platelets and the vessel walls are treated as a group of discretized mesoscopic size particles interacting through conservative, dissipative and random forces. Deposition (i.e., binding) of platelets is modeled by considering attractive forces at the vessel wall, which is characterized by the values of the effective spring constant for platelet adhesion. To test this model, we simulated platelet deposition in a perfusion chamber. By matching the simulation results to experimental data, the effective platelet spring constants were determined and were found to be approximately 50 N/m, which is within a physiologically relevant range. It is demonstrated that the DPD analysis offers the capability of simulating the time-dependent binding of platelets. We conclude that this model provides a new approach for studying the interaction among blood constituents.

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Year:  2007        PMID: 18068201     DOI: 10.1016/j.mvr.2007.09.007

Source DB:  PubMed          Journal:  Microvasc Res        ISSN: 0026-2862            Impact factor:   3.514


  14 in total

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2.  A mesoscopic bridging scale method for fluids and coupling dissipative particle dynamics with continuum finite element method.

Authors:  Milos Kojic; Nenad Filipovic; Akira Tsuda
Journal:  Comput Methods Appl Mech Eng       Date:  2013-01-15       Impact factor: 6.756

3.  A density-dependent FEM-FCT algorithm with application to modeling platelet aggregation.

Authors:  Nicholas A Danes; Karin Leiderman
Journal:  Int J Numer Method Biomed Eng       Date:  2019-07-09       Impact factor: 2.747

4.  A multiscale biomechanical model of platelets: Correlating with in-vitro results.

Authors:  Peng Zhang; Li Zhang; Marvin J Slepian; Yuefan Deng; Danny Bluestein
Journal:  J Biomech       Date:  2016-11-11       Impact factor: 2.712

5.  Tortuosity triggers platelet activation and thrombus formation in microvessels.

Authors:  Jennifer K W Chesnutt; Hai-Chao Han
Journal:  J Biomech Eng       Date:  2011-12       Impact factor: 2.097

6.  Simulation of the microscopic process during initiation of stent thrombosis.

Authors:  Jennifer K W Chesnutt; Hai-Chao Han
Journal:  Comput Biol Med       Date:  2014-11-15       Impact factor: 4.589

Review 7.  Computational Fluid Dynamics Assessment Associated with Transcatheter Heart Valve Prostheses: A Position Paper of the ISO Working Group.

Authors:  Zhenglun Alan Wei; Simon Johannes Sonntag; Milan Toma; Shelly Singh-Gryzbon; Wei Sun
Journal:  Cardiovasc Eng Technol       Date:  2018-04-19       Impact factor: 2.495

8.  Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics.

Authors:  Peng Zhang; Chao Gao; Na Zhang; Marvin J Slepian; Yuefan Deng; Danny Bluestein
Journal:  Cell Mol Bioeng       Date:  2014-12-01       Impact factor: 2.321

9.  Computational flow dynamics in a geometric model of intussusceptive angiogenesis.

Authors:  Nenad Filipovic; Akira Tsuda; Grace S Lee; Lino F Miele; Miao Lin; Moritz A Konerding; Steven J Mentzer
Journal:  Microvasc Res       Date:  2009-08-26       Impact factor: 3.514

10.  Modelling thrombosis using dissipative particle dynamics method.

Authors:  N Filipovic; M Kojic; A Tsuda
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2008-09-28       Impact factor: 4.226

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