Published on: Oct 18, 2012
A Numerical Framework for Modeling Electrotaxis in Bone Cell Cultures
JC Vanegas-Acosta, V. Lancellotti, APM Zwamborn
Department of Electrical Engineering, Eindhoven University of Technology.
5612AZ, Eindhoven, The Netherlands
The exposure of cell cultures to electromagnetic fields (EMF) induces interactions that could change the behavior and response of the cells. Such effects are mediated by both the electrical (and magnetic) properties of the cells and the nature of the EMF stimulus. Although thermal effects are clearly understood and acknowledged as such, a vast number of results show the presence of other than thermal effects. In these cases, the exact biological mechanisms influenced during EMF exposure are still a matter of research and debate. Moreover, some of these effects have been reported as possible causes for sickness. We can mention as examples the noise over power transmission lines, which is believed to induce hyper-electro-sensitivity in exposed populations, and the electromagnetic radiation coming from conventional electronic appliances such as mobile phones, suspected by some people to induce brain cancer.
Most of the available knowledge on the EMF effects on the human body follows from experimental research. However, as sometimes experimental results are inconclusive and even contradictory, and clear pathways explaining the EMF interaction with cells are lacking, numerical models have gained popularity as useful tools to provide additional research paths that may lead to evidence better understanding of the EMF effects. By combining our knowledge on computational biology and computational electromagnetics, we aim at developing a numerical framework to identify possible explanations to the EMF interaction mechanisms, based on the physics involved in both the EMF stimulus and the cells response.
A first step toward this goal has been the numerical modeling of cell electrotaxis. Electrotaxis is the cell migration in the presence of an electric field, which induces cell movement parallel to the electric field lines. This effect is modeled by describing the biological component (cell migration, proliferation and death) by means of a set of reaction-diffusion equations. The electrical component, which is the external electrical stimulus plus the electrical response of the cells, is modeled by considering the cells as dielectric spheres and computing the equivalent dipole moments induced by the polarization effect. These dipole moments are used to obtain the electric field outside the cells, which is then coupled with the biological component to model electrotaxis.
Using this simple description we are able to numerically reproduce results on cell migration in agreement with experiments. We have also found that the intercellular electric field of a migrating cell is enhanced by the contribution of the dipole moments induced in the surrounding cells, which also depends on the number and position of the cells. With a similar approach, we are dealing with applications to wound healing and tissue growth. For instance, the wound healing process around dental implants has been numerically analyzed by mathematically describing both the biological process leading to bone formation, and the increased biological activity found during electrostimulation. Numerical results compare favorably with the increased bone formation and reduced healing times observed at the implant site, and allow an exploration of the influence of the electrical stimulus during blood coagulation, tissue formation and tissue replacement, among others.
Further work will be soon started on an application to bone growth around hip implants. We are also interested in combining both biological and electromagnetic models with computational mechanics to deal with a more complex and detailed model for tissue formation. At the same time, we are focusing our efforts on more detailed physical descriptions able to deal with time-harmonic electric and magnetic fields. Such descriptions will allow us to explore the EMF distributions in the cell membrane, cytoplasm and nucleus, and may provide additional information on the interaction mechanisms among a large number of cells.
This research is performed by biologists, physicists and engineers working in an interdisciplinary environment. While our ideas and results are discussed with scientists working on the experimental side, we are focused on the computer implementation of mathematical formulations. Therefore, since numerical models should always describe practical applications, we would be glad to cooperate with researchers who could provide experimental data to support and validate our numerical findings.