Bone Remodelling in BioShape

Many biological phenomena are inherently multiscale, i.e. they are characterised by interactions involving different scales at the same time. This is the case of bone remodelling, where macroscopic behaviour (at organ and tissue scale) and microstructure (at cell scale) strongly influence each other. Consequently, several approaches have been defined to model such a process at different spatial and temporal levels and, in particular, in terms of continuum properties, abstracting in this way from a realistic - and more complex - cellular scenario. While a large amount of information is available to validate such models separately, more work is needed to integrate all levels fully in a faithful multiscale model. In this scenario, we propose the use of BioShape, a 3D particle-based, scale-independent, geometry and space oriented simulator. It is used to define and integrate a cell and tissue scale model for bone remodelling in terms of shapes equipped with perception, interaction and movement capabilities. Their in-silico simulation allows for tuning continuum-based tissutal and cellular models, as well as for better understanding - both in qualitative and in quantitative terms - the blurry synergy between mechanical and metabolic factors triggering bone remodelling.

[1]  Michel Dumontier,et al.  GridCell: a stochastic particle-based biological system simulator , 2008, BMC Systems Biology.

[2]  S. Cowin,et al.  Bone remodeling I: theory of adaptive elasticity , 1976 .

[3]  S. Plimpton,et al.  Microbial cell modeling via reacting diffusive particles , 2005 .

[4]  D. Bray,et al.  Stochastic simulation of chemical reactions with spatial resolution and single molecule detail , 2004, Physical biology.

[5]  P. Koumoutsakos MULTISCALE FLOW SIMULATIONS USING PARTICLES , 2005 .

[6]  R H Smallwood,et al.  The application of multiscale modelling to the process of development and prevention of stenosis in a stented coronary artery , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[7]  T M Keaveny,et al.  Osteoblasts respond to pulsatile fluid flow with short-term increases in PGE(2) but no change in mineralization. , 2001, Journal of applied physiology.

[8]  Gregory A Voth,et al.  Multiscale modeling of biomolecular systems: in serial and in parallel. , 2007, Current opinion in structural biology.

[9]  Erik De Schutter,et al.  Computational neuroscience : realistic modeling for experimentalists , 2000 .

[10]  Emanuela Merelli,et al.  Hermes: Agent-Based Middleware for Mobile Computing , 2005, SFM.

[11]  Walter Herzog,et al.  Modeling bone resorption using Mixture Theory with chemical reactions , 2007 .

[12]  T. Bartol,et al.  Monte Carlo Methods for Simulating Realistic Synaptic Microphysiology Using MCell , 2000 .

[13]  H. Frost Skeletal structural adaptations to mechanical usage (SATMU): 2. Redefining Wolff's Law: The remodeling problem , 1990, The Anatomical record.

[14]  Corrado Priami,et al.  BlenX4Bio - BlenX for Biologists , 2009, CMSB.

[15]  S. Cowin,et al.  Candidates for the mechanosensory system in bone. , 1991, Journal of biomechanical engineering.

[16]  Ezio Bartocci,et al.  Shape Calculus A spatial calculus for 3D colliding shapes , 2009 .

[17]  Adam Duguid,et al.  The Bio-PEPA Tool Suite , 2009, 2009 Sixth International Conference on the Quantitative Evaluation of Systems.

[18]  Peter J. Hunter,et al.  Multiscale modeling: physiome project standards, tools, and databases , 2006, Computer.

[19]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[20]  J. Klein-Nulend,et al.  MECHANOTRANSDUCTION IN BONE : ROLE OF THE LACUNOCANALICULAR NETWORK , 1999 .

[21]  Gideon A. Rodan,et al.  Control of osteoblast function and regulation of bone mass , 2003, Nature.

[22]  C. H. Turner,et al.  Toward a Mathematical Description of Bone Biology: The Principle of Cellular Accommodation , 1999, Calcified Tissue International.

[23]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[24]  David L. Lacey,et al.  Osteoclast differentiation and activation , 2003, Nature.

[25]  Stephen C. Cowin,et al.  Bone remodeling II: small strain adaptive elasticity , 1976 .

[26]  P. Koumoutsakos MULTISCALE FLOW SIMULATIONS USING PARTICLES , 2005 .

[27]  H. Frost,et al.  Skeletal structural adaptations to mechanical usage (SATMU): 1. Redefining Wolff's Law: The bone modeling problem , 1990, The Anatomical record.

[28]  Emanuela Merelli,et al.  BioShape: a spatial shape-based scale-independent simulation environment for biological systems , 2010, ICCS.

[29]  Zhenjun Hu,et al.  Towards zoomable multidimensional maps of the cell , 2007, Nature Biotechnology.

[30]  Rik Huiskes,et al.  Effects of mechanical forces on maintenance and adaptation of form in trabecular bone , 2000, Nature.

[31]  Fabio Baruffaldi,et al.  Multiscale investigation of the functional properties of the human femur , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[32]  A. van der Plas,et al.  Sensitivity of osteocytes to biomechanical stress in vitro , 1995, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[33]  Peter M. A. Sloot,et al.  Multi-scale modelling in computational biomedicine , 2010, Briefings Bioinform..

[34]  D. van der Spoel,et al.  GROMACS: A message-passing parallel molecular dynamics implementation , 1995 .