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Erythropoiesis is a biological phenomenon (process) of production of red blood cells by cellular differentiation. It is based on amplification steps due to an interplay between renewal and differentiation in the successive cell types from stem cells to red blood cells. We will study this mechanism with a stochastic point of view to explain unexpected fluctuations on the red blood cell numbers, as surprisingly observed by biologists and medical doctors in a rest erythropoiesis.
We consider three cell types: stem cells, progenitors and red blood cells. Each cell type is characterized by its own dynamics parameters: its division rate and by the renewal and differentiation probabilities at each division event. We model the global population dynamics by a three-dimensional stochastic decomposable branching process. We show that the amplification mechanism is given by the inverse of the small difference between the differentiation and renewal probabilities. Introducing a parameter $K$ which scales simultaneously the size of the first component, the differentiation and renewal probabilities and the red blood cell death rate, we describe the asymptotic behavior of the process for large $K$.
We show that each cell type has its own size scale and its own time scale. Focusing on the third component, we prove that the red blood cell population size, conveniently renormalized (in time and size), is expanded in an usual way inducing large fluctuations. The proofs are based on a fine study of the different scales involved in the model and on the use of different convergence and average techniques in the proofs.