X-ray Imaging Center, Department of Materials Science and Engineering, Pohang University of Science and Technology , San 31, Hyoja-dong, Pohang, 790-784, Korea.
Sci Rep. 2011;1:104. doi: 10.1038/srep00104. Epub 2011 Sep 28.
Living systems inevitably undergo a progressive deterioration of physiological function with age and an increase of vulnerability to disease and death. To maintain health and survival, living systems should optimize survival strategies with adaptive interactions among molecules, cells, organs, individuals, and environments, which arises plasticity in survival curves of living systems. In general, survival dynamics in a population is mathematically depicted by a survival rate, which monotonically changes from 1 to 0 with age. It would be then useful to find an adequate function to describe complicated survival dynamics. Here we describe a flexible survival function, derived from the stretched exponential function by adopting an age-dependent shaping exponent. We note that the exponent is associated with the fractal-like scaling in cumulative mortality rate. The survival function well depicts general features in survival curves; healthy populations exhibit plasticity and evolve towards rectangular-like survival curves, as examples in humans or laboratory animals.
生命系统不可避免地会随着年龄的增长而导致生理功能逐渐恶化,并增加对疾病和死亡的脆弱性。为了保持健康和生存,生命系统应该通过分子、细胞、器官、个体和环境之间的适应性相互作用来优化生存策略,这就产生了生命系统生存曲线的可塑性。一般来说,种群的生存动态在数学上可以用存活率来描述,存活率随着年龄的增长从 1 单调地变化到 0。因此,找到一个合适的函数来描述复杂的生存动态是很有用的。在这里,我们描述了一个灵活的生存函数,它是通过采用与年龄相关的形状指数从扩展指数函数中推导出来的。我们注意到,该指数与累积死亡率的分形样标度有关。该生存函数很好地描述了生存曲线的一般特征;健康人群表现出可塑性,并朝着类似于矩形的生存曲线进化,例如人类或实验室动物。