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Abstract：
The biological mechanisms triggered by low-dose exposure still need to be explored in depth. In this study, the potential mechanisms of low-dose radiation when irradiating the BEAS-2B cell lines with a Cs-137 gamma-ray source were investigated through simulations and experiments. Monolayer cell population models were constructed for simulating and analyzing distributions of nucleus-specific energy within cell populations combined with the Monte Carlo method and microdosimetric analysis. Furthermore, the 10 × Genomics single-cell sequencing technology was employed to capture the heterogeneity of individual cell responses to low-dose radiation in the same irradiated sample. The numerical uncertainties can be found both in the specific energy distribution in microdosimetry and in differential gene expressions in radiation cytogenetics. Subsequently, the distribution of nucleus-specific energy was compared with the distribution of differential gene expressions to guide the selection of differential genes bioinformatics analysis. Dose inhomogeneity is pronounced at low doses, where an increase in dose corresponds to a decrease in the dispersion of cellular-specific energy distribution. Multiple screening of differential genes by microdosimetric features and statistical analysis indicate a number of potential pathways induced by low-dose exposure. It also provides a novel perspective on the selection of sensitive biomarkers that respond to low-dose radiation.
摘要：
低剂量暴露引发的生物学机制仍需深入探讨。在这项研究中,通过模拟和实验研究了用Cs-137γ射线源照射BEAS-2B细胞系时低剂量辐射的潜在机制。结合蒙特卡罗方法和微剂量学分析，构建了单层细胞群模型，用于模拟和分析细胞群中核比能量的分布。此外，采用10×基因组学单细胞测序技术,在同一照射样品中捕获单个细胞对低剂量辐射反应的异质性.在微剂量学中的特定能量分布和辐射细胞遗传学中的差异基因表达中都可以发现数值不确定性。随后，将核比能量的分布与差异基因表达的分布进行比较，以指导差异基因的选择生物信息学分析。剂量不均匀性在低剂量时很明显，其中剂量的增加对应于细胞比能量分布的分散的减少。通过微剂量学特征和统计分析对差异基因进行多重筛选，表明低剂量暴露诱导了许多潜在的途径。它还为选择对低剂量辐射有反应的敏感生物标志物提供了新的视角。
