X-Message-Number: 29481
Subject: Re: Gavrilov has a better understanding aging
References: <>
From: "Perry E. Metzger" <>
Date: Wed, 02 May 2007 19:41:06 -0400

> From: "Basie" <>
>
> It is clear that Hayflick never read or understand : Gavrilov L.A., 
> Gavrilova Journal of Theoretical Biology, 2001, 213(4): 527-545. According 
> Gavrilov all animals are born with a certain number of defective cells that 
> self destruct. Hence the different rates of aging.

The paper makes no claims about "defective cells that self destruct"
or anything similar. If you think it does, well, I'm sorry, but you
didn't understand it at all. Indeed, the paper makes no reference to
specific biological parts like cells or specific aging mechanisms --
it is a theoretical paper about which statistical models fit death
rates best.

Those that want to look for themselves can find the paper here:

http://www.ingentaconnect.com/content/ap/jt/2001/00000213/00000004/art02430

I was moved to write after seeing your second, rather odd posting in
connection with long lived species, and noting that no one had
bothered to correct you.

The paper claims that human death rates follow the standard
statistical models for equipment failure in devices with multiple
redundant parts. Perhaps you were confused about the fact that the
model requires the "tweak" that one starts with a certain number of
parts that are not working at the beginning.  "Parts" in the Gavrilov
model are not, however, "cells" or anything else. They're a
mathematical abstraction at best. (This modification from the usual
models of equipment failure is there to explain the early part of the
curve -- presumably phenomena like death from "natural causes" in
childhood and such. Without such a tweak, one would expect a power law
curve. The important part is not the "parts not working at start"
portion but that death rates follow the general model they propose
very well.)

Part of the evidence for this that the paper cites is the fact that,
past a particular point, death rates stop increasing much. If you're
100, your odds of making it to 101 aren't very high, but the odds of
making it to 102 from 101 are not significantly worse. For the reason
why this is true, read the paper, but the simple summary is that after
a certain point you've lost all remaining redundancy so the death rate
converges on the steady state part failure rate.

What makes the paper interesting is that it is yet more confirmation
of the "we aren't built to age, it is just that we're not built well
enough not to" hypothesis -- i.e. the statistical model fits the
assumption that you accumulate unrepairable damage until you lose your
last backup of some critical subsystem and die.


Perry

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