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Cell Seeding Process Experiment and Simulation on Three-Dimensional Polyhedron and Cross-Link Design Scaffolds

Cell attachment to a scaffold is a significant step toward successful tissue engineering. Cell seeding is the first stage of cell attachment, and its efficiency and distribution can affect the final biological performance of the scaffold. One of the contributing factors to maximize cell seeding effi...

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Detalles Bibliográficos
Autores principales: Liu, Ziyu, Tamaddon, Maryam, Gu, Yingying, Yu, Jianshu, Xu, Nan, Gang, Fangli, Sun, Xiaodan, Liu, Chaozong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064471/
https://www.ncbi.nlm.nih.gov/pubmed/32195229
http://dx.doi.org/10.3389/fbioe.2020.00104
Descripción
Sumario:Cell attachment to a scaffold is a significant step toward successful tissue engineering. Cell seeding is the first stage of cell attachment, and its efficiency and distribution can affect the final biological performance of the scaffold. One of the contributing factors to maximize cell seeding efficiency and consequently cell attachment is the design of the scaffold. In this study, we investigated the optimum scaffold structure using two designs – truncated octahedron (TO) structure and cubic structure – for cell attachment. A simulation approach, by ANSYS Fluent coupling the volume of fluid (VOF) model, discrete phase model (DPM), and cell impingement model (CIM), was developed for cell seeding process in scaffold, and the results were validated with in vitro cell culture assays. Our observations suggest that both designs showed a gradual lateral variation of attached cells, and live cell movements are extremely slow by diffusion only while dead cells cannot move without external force. The simulation approaches supply a more accurate model to simulate cell adhesion for three-dimensional structures. As the initial stages of cell attachment in vivo are hard to observe, this novel method provides an opportunity to predict cell distribution, thereby helping to optimize scaffold structures. As tissue formation is highly related to cell distribution, this model may help researchers predict the effect of applied scaffold and reduce the number of animal testing.