Craig Henreiquez, Duke University

This project is an extension of a current collaboration with Dr. Henriquez and Duke University. The collaboration explores the feasibility of creating discrete bidomain models at a cellular level in order to study the effects of tissue structure on the propagation of action potentials in cardiac tissue. The most commonly used models for this type of study employ continuous bidomain models (averaging out the intra- and extracellular spaces to form continuous interleaved volumes separated by a membrane). This type of model, however, does not account for the shape and location of the actual membrane or that cells are discrete entities. In order to further analyze the effect of averaging, and more specifically to tie the averaged properties to the underlying tissue pathology, the project aims at using discrete geometric and computational models at a cellular scale to perform simulations of the propagation of the depolarization front in cardiac tissue.

A similar framework can be applied to questions at the tissue scale other than propagation in cardiac tissue. We are extending the ongoing collaboration to assist Dr. Henriquez in the study of electroporation and field mediated DNA transport. In electroporation, the integrity of the plasma membrane is affected by the presence of a large electric field, which causes breakdown of the membrane in certain locations and forms pores wide enough for large molecules to enter the cell. The latter is an effect scientists are eager to take advantage of in the search for an efficient way of delivering DNA to a cell for gene therapy. For electroporation to be effective, one needs to know how many pores are formed by the strong electric field that is applied externally. Hence the central goal is to find an optimal way of creating an external field that transfects enough cells with DNA, but does not damage the integrity of the tissue. Simulations offer many advantages in trying to first understand the nature of electroporation and DNA transport and then optimize the technique for eventual clinical use.