No abstract

Purpose: The most exposed tissue upon radon exposure is the bronchial epithelium where goblet cells serve as responsive and adaptable front-line defenders. They can rapidly produce a vast amount of mucus, and can change in number, in response to airway insults. The objective of the present study is to quantify the effects of mucus discharge and goblet cell hyperplasia on the microscopic dose consequences of macroscopic radon exposures. Methods: For this purpose, computational models of the bronchial epithelium and alpha-particle transport have been prepared and applied to quantify the hits received and doses absorbed by cell nuclei in case of different mucus thicknesses and goblet cell number. Results and conclusions: Both mucus discharge and induction of goblet cell hyperplasia reduce radiation burden at the cellular level, and as such they both can be considered as radioadaptive responses to radon exposure. As compared to basal cell hyperplasia, goblet cell hyperplasia is more effective in reducing the microscopic dose consequences of a given macroscopic exposure. Such changes in exposure geometry highlight the need for improvements in the application of biokinetic and dosimetry models for incorporated radionuclides as well as the dose and dose rate effectiveness factor.

Applying the two-stage clonal expansion model to epidemiology of lung cancer among uranium miners, it has been revealed that radon acts as a promoting agent facilitating the clonal expansion of already mutated cells. Clonal expansion rate increases non-linearly by radon concentration showing a plateau above a given exposure rate. The underlying mechanisms remain unclear. Earlier we proposed that progenitor cell hyperplasia may be induced upon chronic radon exposure. The objective of the present study is to test whether the induction of hyperplasia may provide a quantitative explanation for the plateau in clonal expansion rate. For this purpose, numerical epithelium models were prepared with different number of basal cells. Cell nucleus hits were computed by an own-developed Monte-Carlo code. Surviving fractions were estimated based on the number of cell nucleus hits. Cell division rate was computed supposing equilibrium between cell death and cell division. It was also supposed that clonal expansion rate is proportional to cell division rate, and therefore the relative increase in cell division rate and clonal expansion rate are the same functions of exposure rate. While the simulation results highly depend on model parameters with high uncertainty, a parameter set has been found resulting in a cell division rate exposure rate relationship corresponding to the plateau in clonal expansion rate. Due to the high uncertainty of the applied parameters, however, further studies are required to decide whether the induction of hyperplasia is responsible for the non-linear increase in clonal expansion rate or not. Nevertheless the present study exemplifies how computational modelling can contribute to the integration of observational and experimental radiation protection research.