Cells that are directly exposed to low doses of ionizing radiation may experience DNA damage. Cells which happen to be in the vicinity of the exposed cells, but have not received any radiation dose at all, can also be affected. These neighborhood cells can be referred to as "bystander cells" and the indirect radiation effect as "bystander effect". Therefore, in order to assess the risks associated with low doses of radiation, one has to take into account not only the cells that receive radiation directly, but also those unfortunate cells that are also damaged because they happen to be their neighbors. On the other hand there is some evidence that "bystander effects" could act as a defense mechanism whereby radiation risk is reduced. The mechanisms for bystander effects need to be understood for the following reasons: (1) to understand the extent and the number of neighboring cells affected and (2) to evaluate whether the bystander effect causes more or less cells to be at risk for damage and disease.

Project Goals:

Understand the cellular mechanisms associated with bystander effects.

Experimental Approach:

Our approach is to develop a computational theory, or algorithm, which will model bystander effects on all 46 chromosome in the nucleus of a human cell. To validate this computer algorithm, specific information from other experiments will be necessary to test the assumptions that have been used for the model. Some of these experiments have already been designed and are being actively pursued at present. Our computational modeling effort begins with the following assumptions:

1. In a given tissue, cells communicate with each other via "gap junctions". It may be that the irradiated cells send a distress message to the neighboring cells via the diffusion of molecules through "gap junctions". When this molecule reaches the vicinity of the DNA molecules in the bystander cells, damages are induced.
   
2. When cells are irradiated they secrete certain types of soluble proteins into the medium. These proteins can attach to the surfaces of bystander cells and send a biochemical signal, which can also damage DNA.

The software is being developed simultaneously, as if the assumptions are true. If, in the future, it turns out that the experimental data do not support the various assumptions made, then we will modify our assumptions accordingly and hence the software. These assumed mechanisms are now being incorporated into the computer code for a more quantitative understanding of bystander effects.

Expected Outcomes:

A more quantitative understanding of bystander effects and it's role in radiation risk.