期刊
RADIATION AND ENVIRONMENTAL BIOPHYSICS
卷 60, 期 1, 页码 49-60出版社
SPRINGER
DOI: 10.1007/s00411-020-00880-9
关键词
Low-dose; Acute myeloid leukemia; CBA mice; Mathematical modeling; Ionizing radiation exposure; LDEF
The study examined the impact of low-dose ionizing radiation on leukemia incidence, investigated the mechanisms of radiation-induced acute myeloid leukemia using an animal model, and performed simulations through a mathematical model. The findings indicated a proportional relationship between low-dose leukemia incidence and the number of cells with specific gene deletions, as well as discussed the impact of different data transformation methods on the results.
The effect of low-dose ionizing radiation exposure on leukemia incidence remains poorly understood. Possible dose-response curves for various forms of leukemia are largely based on cohorts of atomic bomb survivors. Animal studies can contribute to an improved understanding of radiation-induced acute myeloid leukemia (rAML) in humans. In male CBA/H mice, incidence of rAML can be described by a two-hit model involving a radiation-induced deletion with Sfpi1 gene copy loss and a point mutation in the remaining Sfpi1 allele. In the present study (historical) mouse data were used and these processes were translated into a mathematical model to study photon-induced low-dose AML incidence in male CBA/H mice following acute exposure. Numerical model solutions for low-dose rAML incidence and diagnosis times could respectively be approximated with a model linear-quadratic in radiation dose and a normal cumulative distribution function. Interestingly, the low-dose incidence was found to be proportional to the modeled number of cells carrying the Sfpi1 deletion present per mouse following exposure. After making only model-derived high-dose rAML estimates available to extrapolate from, the linear-quadratic model could be used to approximate low-dose rAML incidence calculated with our mouse model. The accuracy in estimating low-dose rAML incidence when extrapolating from a linear model using a low-dose effectiveness factor was found to depend on whether a data transformation was used in the curve fitting procedure.
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