Literature DB >> 19514073

Corroboration of mechanobiological simulations of tissue differentiation in an in vivo bone chamber using a lattice-modeling approach.

Hanifeh Khayyeri1, Sara Checa, Magnus Tägil, Patrick J Prendergast.   

Abstract

It is well established that the mechanical environment modulates tissue differentiation, and a number of mechanoregulatory theories for describing the process have been proposed. In this study, simulations of an in vivo bone chamber experiment were performed that allowed direct comparison with experimental data. A mechanoregulation theory for mesenchymal stem cell differentiation based on a combination of fluid flow and shear strain (computed using finite element analysis) was implemented to predict tissue differentiation inside mechanically controlled bone chambers inserted into rat tibae. To simulate cell activity, a lattice approach with stochastic cell migration, proliferation, and selected differentiation was adopted; because of its stochastic nature, each run of the simulation gave a somewhat different result. Simulations predicted the load-dependency of the tissue differentiation inside the chamber and a qualitative agreement with histological data; however, the full variability found between specimens in the experiment could not be predicted by the mechanoregulation algorithm. This result raises the question whether tissue differentiation predictions can be linked to genetic variability in animal populations.

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Year:  2009        PMID: 19514073     DOI: 10.1002/jor.20926

Source DB:  PubMed          Journal:  J Orthop Res        ISSN: 0736-0266            Impact factor:   3.494


  15 in total

1.  Tissue differentiation in an in vivo bioreactor: in silico investigations of scaffold stiffness.

Authors:  Hanifeh Khayyeri; Sara Checa; Magnus Tägil; Fergal J O'Brien; Patrick J Prendergast
Journal:  J Mater Sci Mater Med       Date:  2010-08       Impact factor: 3.896

2.  Computational simulation methodologies for mechanobiological modelling: a cell-centred approach to neointima development in stents.

Authors:  C J Boyle; A B Lennon; M Early; D J Kelly; C Lally; P J Prendergast
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2010-06-28       Impact factor: 4.226

Review 3.  Mechanical regulation of skeletal development.

Authors:  Rebecca Rolfe; Karen Roddy; Paula Murphy
Journal:  Curr Osteoporos Rep       Date:  2013-06       Impact factor: 5.096

Review 4.  Role of mathematical modeling in bone fracture healing.

Authors:  Peter Pivonka; Colin R Dunstan
Journal:  Bonekey Rep       Date:  2012-11-14

Review 5.  Finite element method (FEM), mechanobiology and biomimetic scaffolds in bone tissue engineering.

Authors:  A Boccaccio; A Ballini; C Pappalettere; D Tullo; S Cantore; A Desiate
Journal:  Int J Biol Sci       Date:  2011-01-26       Impact factor: 6.580

Review 6.  Cell-biomaterial mechanical interaction in the framework of tissue engineering: insights, computational modeling and perspectives.

Authors:  Jose A Sanz-Herrera; Esther Reina-Romo
Journal:  Int J Mol Sci       Date:  2011-11-21       Impact factor: 5.923

7.  A Mechanobiology-based Algorithm to Optimize the Microstructure Geometry of Bone Tissue Scaffolds.

Authors:  Antonio Boccaccio; Antonio Emmanuele Uva; Michele Fiorentino; Luciano Lamberti; Giuseppe Monno
Journal:  Int J Biol Sci       Date:  2016-01-01       Impact factor: 6.580

Review 8.  Mechanical regulation of bone regeneration: theories, models, and experiments.

Authors:  Duncan Colin Betts; Ralph Müller
Journal:  Front Endocrinol (Lausanne)       Date:  2014-12-10       Impact factor: 5.555

Review 9.  In silico bone mechanobiology: modeling a multifaceted biological system.

Authors:  Mario Giorgi; Stefaan W Verbruggen; Damien Lacroix
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2016-09-07

10.  Substrate stiffness and oxygen as regulators of stem cell differentiation during skeletal tissue regeneration: a mechanobiological model.

Authors:  Darren Paul Burke; Daniel John Kelly
Journal:  PLoS One       Date:  2012-07-24       Impact factor: 3.240

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