title: Modelling cell lifespan and proliferation: is likelihood to die or to divide independent of age?
abstract: In cell lifespan studies the exponential nature of cell survival curves is often interpreted as showing the rate of death is independent of the age of the cells within the population. Here we present an alternative model where cells that die are replaced and the age and lifespan of the population pool is monitored until a steady state is reached. In our model newly generated individual cells are given a determined lifespan drawn from a number of known distributions including the lognormal, which is frequently found in nature. For lognormal lifespans the analytic steady-state survival curve obtained can be well-fit by a single or double exponential, depending on the mean and standard deviation. Thus, experimental evidence for exponential lifespans of one and/or two populations cannot be taken as definitive evidence for time and age independence of cell survival. A related model for a dividing population in steady state is also developed. We propose that the common adoption of age-independent, constant rates of change in biological modelling may be responsible for significant errors, both of interpretation and of mathematical deduction. We suggest that additional mathematical and experimental methods must be used to resolve the relationship between time and behavioural changes by cells that are predominantly unsynchronized.
authors.affiliation: The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.
authors.forename: Mark R
authors.initials: MR
authors.lastname: Dowling
authors.forename: Dejan
authors.initials: D
authors.lastname: Milutinović
authors.forename: Philip D
authors.initials: PD
authors.lastname: Hodgkin
mesh_terms: D000818:Animals; D002455:Cell Division / Q000502:physiology*; D002468:Cell Physiological Phenomena; D049109:Cell Proliferation; D002470:Cell Survival / Q000502:physiology*; D002478:Cells, Cultured; D016922:Cellular Senescence / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008136:Longevity / Q000502:physiology*; D008954:Models, Biological