Vanfleteren J R, De Vreese A, Braeckman B P
Department of Biology, University of Gent, Belgium.
J Gerontol A Biol Sci Med Sci. 1998 Nov;53(6):B393-403; discussion B404-8. doi: 10.1093/gerona/53a.6.b393.
We have fitted Gompertz, Weibull, and two- and three-parameter logistic equations to survival data obtained from 77 cohorts of Caenorhabditis elegans in axenic culture. Statistical analysis showed that the fitting ability was in the order: three-parameter logistic > two-parameter logistic = Weibull > Gompertz. Pooled data were better fit by the logistic equations, which tended to perform equally well as population size increased, suggesting that the third parameter is likely to be biologically irrelevant. Considering restraints imposed by the small population sizes used, we simply conclude that the two-parameter logistic and Weibull mortality models for axenically grown C. elegans generally provided good fits to the data, whereas the Gompertz model was inappropriate in many cases. The survival curves of several short- and long-lived mutant strains could be predicted by adjusting only the logistic curve parameter that defines mean life span. We conclude that life expectancy is genetically determined; the life span-altering mutations reported in this study define a novel mean life span, but do not appear to fundamentally alter the aging process.
我们已将冈珀茨方程、威布尔方程以及双参数和三参数逻辑方程拟合到从77个秀丽隐杆线虫无菌培养群体获得的生存数据上。统计分析表明,拟合能力顺序为:三参数逻辑方程>双参数逻辑方程 = 威布尔方程>冈珀茨方程。合并数据用逻辑方程拟合效果更好,随着群体规模增大,这些方程往往表现得同样出色,这表明第三个参数可能在生物学上不相关。考虑到所使用的小群体规模带来的限制,我们简单得出结论,对于无菌培养的秀丽隐杆线虫,双参数逻辑方程和威布尔死亡率模型通常能很好地拟合数据,而冈珀茨模型在许多情况下并不适用。通过仅调整定义平均寿命的逻辑曲线参数,就可以预测几种短寿命和长寿命突变株的生存曲线。我们得出结论,预期寿命是由基因决定的;本研究中报道的改变寿命的突变定义了一个新的平均寿命,但似乎并未从根本上改变衰老过程。