The Effect of Electrical Conductivity on Pore Resistance and Electroporation

Electroporation refers to the permeabilization of the cell membrane with one or multiple electric pulses. The reversible form of electroporation is widely applied for drug delivery, gene and cancer therapy, and stem cell research, among others; the irreversible form of electroporation is being explored for cancer treatment in a drug-free manner. In this work, an electroporation model is developed with particular focus on the prediction of pore resistance. The resulting formulation computes pore resistance as a function of pore size, and intracellular and extracellular conductivities, and avoids empirical or ad hoc specification of the conductivity of the pore-filling solution as practiced in previous works. Such a model is coupled at the whole cell level to investigate the effect of conductivity ratio on membrane permeabilization. The results reveal that the membrane achieves the maximum degree of permeabilization when the extracellular-to-intracellular conductivity ratio is around 0.5.

Numerical Simulations of Fractionated Electrograms and Pathological Cardiac Action Potential

The aim of this work is twofold. First we focus on the complex phenomenon of electrogram fractionation, due to the presence of discontinuities in the conduction properties of the cardiac tissue in a bidomain model. Numerical simulations of paced activation may help to understand the role of the membrane ionic currents and of the changes in cellular coupling in the formation of conduction blocks and fractionation of the electrogram waveform. In particular, we show that fractionation is independent ofINAalterations and that it can be described by the bidomain model of cardiac tissue. Moreover, some deflections in fractionated electrograms may give nonlocal information about the shape of damaged areas, also revealing the presence of inhomogeneities in the intracellular conductivity of the medium at a distance.The second point of interest is the analysis of the effects of space–time discretization on numerical results, especially during slow conduction in damaged cardiac tissue. Indeed, large discretization steps can induce numerical artifacts such as slowing down of conduction velocity, alteration in extracellular and transmembrane potential waveforms or conduction blocks, which are not predicted by the continuous bidomain model. Several possible numerical and physiological explanations of these effects are given. Essentially, the discrete system obtained at the end of the approximation process may be interpreted as a discrete model of the cardiac tissue made up of isopotential cells where the effective intracellular conductivity tensor depends on the space discretization steps; the increase of these steps results in an increase of the effective intracellular resistance and can induce conduction blocks if a certain critical value is exceeded.