by Keyword: Mechanobiology

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Ladoux, B., Mège, R. M., Trepat, X., (2016). Front-rear polarization by mechanical cues: From single cells to tissues Trends in Cell Biology , 26, (6), 420-433

Directed cell migration is a complex process that involves front-rear polarization, characterized by cell adhesion and cytoskeleton-based protrusion, retraction, and contraction of either a single cell or a cell collective. Single cell polarization depends on a variety of mechanochemical signals including external adhesive cues, substrate stiffness, and confinement. In cell ensembles, coordinated polarization of migrating tissues results not only from the application of traction forces on the extracellular matrix but also from the transmission of mechanical stress through intercellular junctions. We focus here on the impact of mechanical cues on the establishment and maintenance of front-rear polarization from single cell to collective cell behaviors through local or large-scale mechanisms.

Keywords: Cell forces, Cell polarity, Collective cell migration, Mechanobiology, Micropatterning, Substrate stiffness

Malandrino, Andrea, Lacroix, Damien, Hellmich, Christian, Ito, Keita, Ferguson, Stephen J., Noailly, J., (2014). The role of endplate poromechanical properties on the nutrient availability in the intervertebral disc Osteoarthritis and Cartilage , 22, (7), 1053-1060

Objective To investigate the relevance of the human vertebral endplate poromechanics on the fluid and metabolic transport from and to the intervertebral disc (IVD) based on educated estimations of the poromechanical parameter values of the bony endplate (BEP). Methods 50 micro-models of different BEP samples were generated from μCTs of lumbar vertebrae and allowed direct determination of porosity values. Permeability values were calculated by using the micro-models, through the simulation of permeation via computational fluid dynamics. These educated ranges of porosity and permeability values were used as inputs for mechano-transport simulations to assess their effect on both the distributions of metabolites within an IVD model and the poromechanical calculations within the cartilaginous part of the endplate i.e., the cartilage endplate (CEP). Results BEP effective permeability was highly correlated to local variations of porosity (R2 ≈ 0.88). Universal patterns between bone volume fraction and permeability arose from these results and from other experimental data in the literature. These variations in BEP permeability and porosity had negligible effects on the distributions of metabolites within the disc. In the CEP, the variability of the poromechanical properties of the BEP did not affect the predicted consolidation but induced higher fluid velocities. Conclusions The present paper provides the first sets of thoroughly identified BEP parameter values that can be further used in patient-specific poromechanical studies. Representing BEP structural changes through variations in poromechanical properties did not affect the diffusion of metabolites. However, attention might be paid to alterations in fluid velocities and cell mechano-sensing within the CEP.

Keywords: Bony endplate, Spine mechanobiology, Intervertebral disc metabolites, Hydraulic Permeability, Bone Porosity, Poromechanics

Noailly, J., Malandrino, A., Galbusera, F., Jin, Zhongmin, (2014). Computational modelling of spinal implants Computational Modelling of Biomechanics and Biotribology in the Musculoskeletal System (ed. Jin, Z.), Woodhead Publishing (Cambridge, UK) Biomaterials and Tissues, 447-484

This chapter focuses on the use of the finite element method in the design and exploration of spinal implants. Following an introduction to biomechanical alterations of the spine in disease and to spine finite element modelling, focus is placed on different models developed for spine treatment simulations. Despite the hindrance of working thorough representations of in vivo situations, predictions of load transfer within both the implants and the tissues simulated allow improved interpretations of known clinical outcomes, and permit the educated design of new implants. The potential of probabilistic modelling is also discussed in relation to model validation and patient-specific analyses. Finally, the latest developments in the multiphysical modelling of intervertebral discs are presented, revealing a strong potential for the study of implant-based strategies that aim to restore the functional biophysics of the spine.

Keywords: Spinal implant, Finite element modelling, Spine surgery, Spine biomechanics, Tissue mechanobiology

Prendergast, P. J., Checa, S., Lacroix, D., (2010). Computational models of tissue differentiation Computational Modeling in Biomechanics (ed. Suvranu De, Farshid Guilak, Mohammad R. K. Mofrad), Springer-Verlag Berlin (Berlin) 3, 353-372

Readers of this chapter will learn about our approach to computer simulation of tissue differentiation in response to mechanical forces. It involves defining algorithms for mechanoregulation of each of following cell activities: proliferation, apoptosis, migration, and differentiation using a stimulus based on a combination of strain and fluid flow (Prendergast et al., J. Biomech., 1997) - algorithms are based on a lattice-modelling which also facilitates building algorithms for complex processes such as angiogenesis. The algorithms are designed to be collaboratable individually. They can be combined to create a computational simulation method for tissue differentiation, using finite element analysis to compute the mechanical stimuli in even quite complex biomechanical environments. Examples are presented of the simulation method in use.

Keywords: Mechanobiology, Lattice modeling, Differentiation, Tissue engineering, Finite element modeling, Scaffolds