2Paleontological Institute of Russian Academy of Sciences, 117997 Moscow, Russia
3Lomonosov Moscow State University, Economics Faculty, 119991 Moscow, Russia; E-mail: email@example.com
* To whom correspondence should be addressed.
Received April 10, 2016
The dynamics of aging is often described by survival curves that show the proportion of individuals surviving to a given age. The shape of the survival curve reflects the dependence of mortality on age, and it varies greatly for different organisms. In a recently published paper, Stroustrup and coauthors ((2016) Nature, 530, 103-107) showed that many factors affecting the lifespan of Caenorhabditis elegans do not change the shape of the survival curve, but only stretch or compress it in time. Apparently, this means that aging is a programmed process whose trajectory is difficult to change, although it is possible to speed it up or slow it down. More research is needed to clarify whether the “rule of temporal scaling” is applicable to other organisms. A good indicator of temporal scaling is the coefficient of lifespan variation: similar values of this coefficient for two samples indicate similar shape of the survival curves. Preliminary results of experiments on adaptation of Drosophila melanogaster to unfavorable food show that temporal scalability of survival curves is sometimes present in more complex organisms, although this is not a universal rule. Both evolutionary and environmental changes sometimes affect only the average lifespan without changing the coefficient of variation (in this case, temporal scaling is present), but often both parameters (i.e. both scale and shape of the survival curve) change simultaneously. In addition to the relative stability of the coefficient of variation, another possible argument in favor of genetic determination of the aging process is relatively low variability of the time of death, which is sometimes of the same order of magnitude as the variability of timing of other ontogenetic events, such as the onset of sexual maturation.
KEY WORDS: aging, survival curves, mortality, stability, temporal scaling