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Modelling cell deformations in bioprinting process using a multicompartment-smooth particle hydrodynamics approach

光滑粒子流体力学 3D生物打印 材料科学 过程(计算) 挤压 纳米技术 生物医学工程 组织工程 机械 复合材料 计算机科学 工程类 物理 操作系统
作者
Samir Das,Amit Roy Chowdhury,Pallab Datta
出处
期刊:Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine [SAGE]
卷期号:236 (6): 867-881 被引量:1
标识
DOI:10.1177/09544119221089720
摘要

Bioprinting using cell-laden bioink is a rapidly emerging additive manufacturing method to fabricate engineered tissue constructs and in vitro models of disease biology. Amongst different bioprinting modalities, extrusion-based bioprinting is the most conveniently adopted technique due to its affordability. Bioinks consisting of living cells are suspended in hydrogels and extruded through syringe-needle assemblies, which subsequently undergo gelation at the collector plate. During the process, pressure is exerted on living cells which may cause cell deaths. Thus, for selected combination of cell and hydrogel, exerted pressure and the extrusion play key roles in determining the cell viability. Experimental evaluation to characterise stresses experienced by the cells in a bioink during bioprinting is a tedious exercise. Herein, computational modelling can be applied efficiently for rapid screening of bioinks. In the present study, a smoothed particle hydrodynamics model is developed for the analysis of stresses exerted on the cells during bioprinting process. Cells are modelled by assigning different mechanical properties to nucleus, cytoskeleton and cell membrane regions of the cell to get a more realistic understanding of cell deformation. The cytoplasm and nucleus are modelled as finite element meshes and a spring model of the cell membrane is coupled to the finite element model to develop a three-compartment model of the cell. Cell deformation is taken as a potential indicator of cell death. Effect of different process parameters such as flow rate, syringe-nozzle geometry and cell density are investigated. A submodeling approach is further introduced to predict deformation with higher resolution in a unit volume containing 104 to 108 cells. Results suggest that the generated bioink flow dynamic model can be a useful tool for the computational study of fluid flow involving cell suspensions during a bioprinting process.
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