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A Poroelastic Model of a Fibrous-Porous Tissue Engineering Scaffold

Tissue engineering scaffolds are used in conjunction with stem cells for the treatment of various diseases. A number of factors provided by the scaffolds affect the differentiation of stem cells. Mechanical cues that are part of the natural cellular microenvironment can both accelerate the different...

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Detalles Bibliográficos
Autores principales: Yuan, Daniel, Somers, Sarah M., Grayson, Warren L., Spector, Alexander A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5864912/
https://www.ncbi.nlm.nih.gov/pubmed/29568010
http://dx.doi.org/10.1038/s41598-018-23214-8
Descripción
Sumario:Tissue engineering scaffolds are used in conjunction with stem cells for the treatment of various diseases. A number of factors provided by the scaffolds affect the differentiation of stem cells. Mechanical cues that are part of the natural cellular microenvironment can both accelerate the differentiation toward particular cell lineages or induce differentiation to an alternative cell fate. Among such factors, there are externally applied strains and mechanical (stiffness and relaxation time) properties of the extracellular matrix. Here, the mechanics of a fibrous-porous scaffold is studied by applying a coordinated modeling and experimental approach. A force relaxation experiment is used, and a poroelastic model associates the relaxation process with the fluid diffusion through the fibrous matrix. The model parameters, including the stiffness moduli in the directions along and across the fibers as well as fluid diffusion time, are estimated by fitting the experimental data. The time course of the applied force is then predicted for different rates of loading and scaffold porosities. The proposed approach can help in a reduction of the technological and experimental efforts to produce 3-D scaffolds for regenerative medicine as well as in a higher accuracy of the estimation of the local factors sensed by stem cells.