论文标题
使用Gamma-H2AX生物标志物改善辐射剂量估计
Improving radiation dose estimation using the gamma-H2AX biomarker
论文作者
论文摘要
为了预测意外或治疗辐射暴露的健康影响，必须估计该人收到的辐射剂量。众所周知的电离辐射生物标志物，磷酸化的γ-H2AX蛋白，用于评估细胞损伤，因此适用于剂量估计过程。在本文中，我们提出了新的贝叶斯方法，这些方法与在预定的辐射后时间进行估计的方法相比，允许关于辐射暴露以来的时间的不确定性，并因此产生更精确的结果。我们还使用Laplace近似方法，该方法大大缩短了获得结果所需的时间。实际数据用于说明这些方法，分析表明模型可能是伽马 - H2AX生物标志物剂量估计过程的实际选择。
To predict the health effects of accidental or therapeutic radiation exposure, one must estimate the radiation dose that person received. A well-known ionising radiation biomarker, phosphorylated gamma-H2AX protein, is used to evaluate cell damage and is thus suitable for the dose estimation process. In this paper, we present new Bayesian methods that, in contrast to approaches where estimation is carried out at predetermined post-irradiation times, allow for uncertainty regarding the time since radiation exposure and, as a result, produce more precise results. We also use the Laplace approximation method, which drastically cuts down on the time needed to get results. Real data are used to illustrate the methods, and analyses indicate that the models might be a practical choice for the gamma-H2AX biomarker dose estimation process.
