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Here are some excerpts from the a new interview, which is just published by the scientific journal Rejuvenation Research:
Rejuvenation Research, 2009, 12(5): 371-374.
The excerpts are provided in their original, non-edited form, as they were initially presented before the publication.
Any comments and suggestions are welcome!
Please feel free to post your comments and suggestions below by clicking here.
-- Leonid Gavrilov
-- Leonid Gavrilov, Ph.D. , GSA Fellow
Center on Aging, NORC/University of Chicago
Our books: http://longevity-science.org/Books.html
Excerpts from Interview
3. You have spearheaded the application of reliability theory to the modeling of aging and mortality. Reliability theory is designed to describe the behavior of man-made machines, which differ from living organisms in that they do not incorporate significant in-built self-repair machinery. To what extent do you feel that this difference diminishes the applicability of reliability theory to living organisms?
Thank you for your kind comment on our 'spearheading' . Yes, we first started to apply reliability theory to the problem of biological aging more than 30 years ago, as early as in 1978 [1, 2], and since that time the reliability theory of aging and longevity has become well known in scientific literature [3 - 9]. To answer your question on applicability of reliability theory to living organisms, it is useful to consider separately two different topics: (1) applicability of reliability theory as a general concept; and (2) applicability of our particular mathematical models based on reliability theory.
Discussing the first topic, it is important to note that reliability theory is a general theory about systems failure. It allows researchers to predict the age-related failure kinetics for a system of given architecture (reliability structure) and given reliability of its components. Although historically it was initially applied to describe the behavior of man-made machines, nothing in this general mathematical theory prevents us from taking into account the in-built self-repair machinery, if this is needed. Therefore, there are no fundamental problems with applicability of reliability theory to living organisms, as there are no problems in applicability of mathematics in general to living organisms.
Discussing the second topic, it was our initial intent to find the most simple explanation for the major facts about aging and mortality (the very origin of aging, the Gompertz law of mortality, the compensation law of mortality, and the late-life mortality deceleration). We were interested in understanding the first principles and fundamental explanations of aging, before trying to create a comprehensive model, which takes into account all the complexities of living organisms. Therefore, in our models we were focused on accumulation of un-repaired damage as the final outcome of the damage-vs-repair process, leading to age-related decrease in systems redundancy (e.g. decrease in numbers of functional cells).
Now, when these intentionally simplified models with minimum number of assumptions gave us some general understanding of the nature of aging process and mortality laws, the way is opened to build upon them a more detailed and complex model of aging. This work is opened to everyone who can find a protected time to do it.
Another interesting feature of biological systems is that they are formed in evolution during a severe struggle for survival, and biological arms race with numerous infections and predators. Therefore they have many potentially harmful defense mechanisms, which may be useful for short-term survival in hostile wild environment, but not conductive for longevity in a protected environment (like the inflammation response).
So the analogy between living organisms and man-made machines is more appropriate for a man-made military machines, overloaded by weaponry and ammunition at the expense of their durability. Such machines could last much longer in protected environment if many dangerous fighting devices are removed from them.
The same is true for living organisms -- loss of some functions through introduced mutations or other interventions often leads to increased species longevity in a protected environment. Sometimes this observation is interpreted as a proof that aging is a programmed process, while in fact it simply means that organisms were selected by Nature for survival in the wild hostile environment, rather than for longevity in protected laboratory conditions.
1. Gavrilov, L.A. A mathematical model of the aging of animals. Proc. Acad. Sci. USSR [Doklady Akademii Nauk SSSR], 1978, 238(2): 490-492. English translation by Plenum Publ Corp: pp.53-55. PMID 624242
2. Gavrilov, L.A., Gavrilova, N.S., Yaguzhinsky, L.S. The main regularities of animal aging and death viewed in terms of reliability theory. J. General Biology [Zhurnal Obschey Biologii], 1978, 39(5): 734-742. PMID 716614
3. Gavrilov LA, Gavrilova NS. Reliability Theory of Aging and Longevity. In: Masoro E.J. & Austad S.N.. (eds.): Handbook of the Biology of Aging, Sixth Edition. Academic Press. San Diego, CA, USA, 2006, 3-42. ISBN 0-12-088387-2
4. Gavrilov LA, Gavrilova NS. Models of Systems Failure in Aging. In: P Michael Conn (Editor): Handbook of Models for Human Aging, Burlington, MA : Elsevier Academic Press, 2006. 45-68. ISBN 0-12-369391-8.
5. Gavrilov LA, Gavrilova NS. Why We Fall Apart. Engineering's Reliability Theory Explains Human Aging. IEEE Spectrum, 2004, 41(9): 30-35.
6. Gavrilov LA, Gavrilova NS. The Reliability-Engineering Approach to the Problem of Biological Aging. Annals of the New York Academy of Sciences, 2004, 1019: 509-512. PMID 15247076
7. Gavrilov L.A., Gavrilova N.S. The quest for a general theory of aging and longevity. Science's SAGE KE (Science of Aging Knowledge Environment) for 16 July 2003; Vol. 2003, No. 28, 1-10. http://sageke.sciencemag.org , PMID 12867663
8. Gavrilov L.A., Gavrilova N.S. The reliability theory of aging and longevity. Journal of Theoretical Biology, 2001, 213(4): 527-545. PMID 11742523
9. Gavrilov L.A., Gavrilova N.S (1991), The Biology of Life Span: A Quantitative Approach. New York: Harwood Academic Publisher, ISBN 3-7186-4983-7
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