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A Biomathematical Modeling Approach to Explain the Phenomenon of Radiation Hormesis
This study presents an improved version of a published biomathematical model, the Random Coincidence Model-Radiation Adapted (RCM-RA). That model describes how cancer mortality increases as dose rate increases in the high-dose rate range, as well as how mortality decreases as dose rate increases in...
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Published in: | Human and ecological risk assessment 2001-08, Vol.7 (4), p.867-890 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | This study presents an improved version of a published biomathematical model, the Random Coincidence Model-Radiation Adapted (RCM-RA). That model describes how cancer mortality increases as dose rate increases in the high-dose rate range, as well as how mortality decreases as dose rate increases in the low-dose rate range. It was assumed that low-dose rates of ionizing radiation induce cellular defense mechanisms that also prevent or repair endogenous DNA damage caused by natural cell metabolism. The model presented describes the development of cancer by a phase of initiation that consists of a series of DNA lesions in the critical regions of tumor-associated genes such as proto-oncogenes or tumor-suppressor genes. Initiated cells can divide and form a clone of initiated cells. This clonal growth is called promotion and leads to premalignant cells. Premalignant clones can sustain further genomic damage that may lead to a malignant cell and ultimately a malignant tumor. The model thereby shares structural features with Moolgavkar's two-stage clonal expansion model. It was tested on published, U-shaped data of radon exposure in U.S. homes. The model correctly reflects the ratio of endogenous DNA damage to radiation-induced damage. |
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ISSN: | 1080-7039 1549-7860 |
DOI: | 10.1080/20018091094709 |