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[遵循冈珀茨-马克汉姆定律并与斯特勒-米尔德万相关性相关的衰老生物体理想队列的数值建模]

[Numerical modeling of ideal cohorts of aging organisms obeying the Gompertz-Makeham law in association with the Strehler-Mildwan correlation].

作者信息

Golubev A G

出版信息

Adv Gerontol. 2004;15:36-50.

Abstract

The Gompertz-Makeham law (-dn/dt x l/n(t)=C+lambdae(gammat)) so as other genuine laws of Nature is strictly applicable only to ideal objects (populations and cohorts) analogously to laws of mechanics or thermodynamics, which are exactly true only for such physical abstractions as mass points or ideal gases. Therefore, a biologically meaningful interpretation of the parameters of this law is likely to be more important for understanding the aging process than devising of alternative analytical descriptions of biodemographic processes for the sake of a better fit only. Numerical modeling of ideal cohorts of aging organisms obeying the Gompertz-Makeha law makes it possible to differentiate possible real and apparent changes in mortality patterns that occur in human history and in evolution and are observed in gerontological experiments and to demonstratively show such effects as the dependency of longevity upon population size, the evolutionarily important possibility of reciprocal changes in the mean and maximal longevity, or detection of apparent changes in negatively correlated aging rate and vitality when the Makeham term is ignored, which is usual in demography. The basic difference between the Makeham term Cand Gompertz term lambdae(gammat) is suggested to be not that the former is constant, whereas the latter is age-dependent, but that the former comprises the contributions of inherently irresistible stresses to mortality, whereas the latter comprises the contributions of resistible stresses to mortality and shows how changes in the ability to resist them is translated into changes in mortality.

摘要

冈珀茨 - 马凯姆定律(-dn/dt × 1/n(t) = C + λe^(γt))与其他真正的自然定律一样,严格来说仅适用于理想对象(种群和队列),类似于力学或热力学定律,这些定律仅对诸如质点或理想气体等物理抽象概念才完全正确。因此,对该定律参数进行生物学上有意义的解释,可能比对仅仅为了更好拟合而设计生物人口学过程的替代分析描述对于理解衰老过程更为重要。对遵循冈珀茨 - 马凯姆定律的衰老生物体理想队列进行数值建模,能够区分人类历史和进化过程中发生且在老年学实验中观察到的死亡率模式可能的真实变化和表观变化,并能直观地展示诸如寿命对种群大小的依赖性、平均寿命和最大寿命相互变化在进化上的重要可能性,或者当忽略马凯姆项(在人口统计学中通常如此)时负相关的衰老率和活力的表观变化等效应。有人认为,马凯姆项C和冈珀茨项λe^(γt)的基本区别并非前者是常数而后者随年龄变化,而是前者包含对死亡率具有内在不可抗拒的压力的贡献,而后者包含可抗拒压力对死亡率的贡献,并表明抵抗这些压力的能力变化如何转化为死亡率的变化。

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