HYPOTHESES ON LONGEVITY HORMESIS 13
ity hormesis appears to be such a response; its reversibility serves to keep it
economical.
Hypothesis X: When, through exposure to nonessential, exogenous agents
or stimuli, longevity hormesis is elicited in homogeneous laboratory popula
tions of eutherian mammals housed under uniform, good laboratory condi
tions and kept free of preventable disease, toxicity, if also induced, is most
likely to be of the irreversible kind.
In searching the literature for mortality data in laboratory populations,
the most frequently located data come from studies in which exogenous
agents are administered at a constant rate. When toxicity is observed, with
or without concomitant longevity hormesis, it most frequently is the irre
versible kind; longevity hormesis, by definition, is reversible. Assuming
both irreversible toxicity and reversible hormesis are deposited onto the
linear Gompertz function at a zero-order rate, and further assuming longev
ity hormesis dissipates at a first-order rate, one obtains the following Gom
pertz function:1824’25
where 7 X represents the irreversible accumulation of toxicity injury and the
far right term reflects the reversible longevity hormetic effect.
Obviously both 7 and X will be dependent on the dose of exogenous
agent. Neafsey et al.24 25 empirically found that the logarithmic-logistic
function,64-74 also known as the sigmoid Emax model, generalized hyperbolic
function, and Hill equation, characterized the dose-response relationships
remarkably well. This is not to imply that toxicity and longevity hormesis
processes obey the underlying assumptions inherent in this equation, but
rather that the large number of parameters in the logarithmic-logistic equa
tion provide superior flexibility in curve-fitting equations to data. It is
therefore not surprising that in the examples cited below, Equation 12 (or a
“collapsed” version) is most frequently employed.
In generalized nomenclature, the logarithmic-logistic equation may be
expressed as follows:
(13)
( 14 )
where R = response
Rm = maximum response
D = dose