A formulation of cell surviving fraction after radiation exposure.

Local energy transfer from electrons generated in biotissues that are exposed to ionizing radiation is fundamental to cell damage. Our aim in this investigation was to quantify the probability of cell mortality associated with the damage by electrons and the repair processes in the cell nucleus, envisaging a new interpretation of the cell surviving fraction (SF). We introduced a SF formula for cells exposed to X-rays, which is given as a linear combination of the Poisson distributions about the number of long-lived lesions per nucleus and their "non-lethal probabilities", to show the non-linearity of log SF as a function of dose. The model selection was rated by a statistical index, Akaike's information criterion (AIC). It was shown that the new formula is suitable for describing cell survival and explicitly takes account of the non-lethality in damage-processing pathways of the cells.

A simulation study of the radiation-induced bystander effect: modeling with stochastically defined signal reemission.

The radiation-induced bystander effect (RIBE) has been experimentally observed for different types of radiation, cell types, and cell culture conditions. However, the behavior of signal transmission between unirradiated and irradiated cells is not well known. In this study, we have developed a new model for RIBE based on the diffusion of soluble factors in cell cultures using a Monte Carlo technique. The model involves the signal emission probability from bystander cells following Poisson statistics. Simulations with this model show that the spatial configuration of the bystander cells agrees well with that of corresponding experiments, where the optimal emission probability is estimated through a large number of simulation runs. It was suggested that the most likely probability falls within 0.63-0.92 for mean number of the emission signals ranging from 1.0 to 2.5.