University of Lyon, University of Claude Bernard Lyon 1, CNRS/IN2P3, IP2I Lyon, F-69622, Villeurbanne, France.
Radiat Res. 2020 Apr;193(4):331-340. doi: 10.1667/RR15463.1. Epub 2020 Feb 4.
NanOx is a biophysical model recently developed in the context of hadrontherapy to predict the cell survival probability from ionizing radiation. It postulates that this may be factorized into two independent terms describing the cell response to two classes of biological events that occur in the sequence of an irradiation: the local lethal events that occur at nanometric scale and can by themselves induce cell death, and the non-local lethal events that lead to cell death by an effect of accumulation and/or interaction at a larger scale. Here we address how local lethal events are modeled in terms of the inactivation of undifferentiated nanometric targets via an "effective local lethal function ", which characterizes the response of each cell line to the spectra of "restricted specific energy". is initially determined as a linear combination of basis functions. Then, a parametric expression is used to reproduce the function's main features, a threshold and a saturation, while at the same time reducing the number of free parameters. This strategy was applied to three cell lines in response to ions of different type and energy, which allows for benchmarking of the α(LET) curves predicted with both effective local lethal functions against the experimental data.
NanOx 是一种生物物理模型，最近在粒子治疗学的背景下发展起来，用于预测电离辐射的细胞存活率。它假设这可以分解为两个独立的项，描述细胞对两类生物事件的反应，这些事件按照射的顺序发生：发生在纳米尺度的局部致死事件，本身就可以诱导细胞死亡，以及非局部致死事件，通过在较大尺度上的累积和/或相互作用导致细胞死亡。在这里，我们将讨论如何根据未分化纳米级靶标的失活来建模局部致死事件，方法是通过“有效局部致死函数”，该函数描述了每个细胞系对“受限特定能量”谱的反应。 最初被确定为基函数的线性组合。然后，使用参数表达式来再现函数的主要特征，即阈值和饱和度，同时减少自由参数的数量。该策略应用于三种细胞系对不同类型和能量的离子的反应，允许针对两种有效局部致死函数预测的 α(LET)曲线与实验数据进行基准测试。
