The priming dose effect, called also the Raper–Yonezawa effect or simply the Yonezawa effect, is a special case of the radiation adaptive response phenomenon (radioadaptation), which refers to: (a) faster repair of direct DNA lesions (damage), and (b) DNA mutation frequency reduction after irradiation, by applying a small priming (conditioning) dose prior to the high detrimental (challenging) one. This effect is observed in many (but not all) radiobiological experiments which present the reduction of lesion, mutation or even mortality frequency of the irradiated cells or species. Additionally, the multi-parameter model created by Dr. Yonezawa and collaborators tried to explain it theoretically based on experimental data on the mortality of mice with chronic internal irradiation. The presented paper proposes a new theoretical approach to understanding and explaining the priming dose effect: it starts from the radiation adaptive response theory and moves to the three-parameter model, separately for two previously mentioned situations: creation of fast (lesions) and delayed damage (mutations). The proposed biophysical model was applied to experimental data—lesions in human lymphocytes and chromosomal inversions in mice—and was shown to be able to predict the Yonezawa effect for future investigations. It was also found that the strongest radioadaptation is correlated with the weakest cellular radiosensitivity. Additional discussions were focussed on more general situations where many small priming doses are used.

Without any available physical measurements, absorbed doses of radiation can be assessed through the use of biological methods, of which the most common is cytogenetic biodosimetry. Evaluating the absorbed dose of mixed radiation requires determining the separate doses of each component. This paper aims to test the effectiveness of the Monte Carlo method as an alternate statistical approach for assessing absorbed doses of mixed neutron-γ fields. It combines the iterative method with Bayesian statistics, allowing for evaluation both when the γ to total absorbed dose ratio is known as well as when it is not. Additionally, this paper demonstrates a few of the statistical tests made possible by the Monte Carlo technique, including the distribution of damages among cells.