Stochastic simulation of structured skin cell population dynamics

Abstract

The epidermis is the outmost skin tissue. It operates as a first defense system to process inflammatory signals and responds by producing inflammatory mediators that promote the recruitment of immune cells. Various skin diseases such as atopic dermatitis occur as a result of the defect of proper skin barrier function and successive impaired inflammatory responses. The onset of such a skin disease links to the disturbed epidermal homeostasis regulated by appropriate self-renewal and differentiation of epidermal stem cells. The theory of physiologically structured population models provides a versatile framework to formulate mathematical models which describe the growth dynamics of a cell population such as the epidermis. In this paper, we develop an algorithm to implement stochastic simulation for a class of physiologically structured population models. We demonstrate that the developed algorithm is applicable to several cell population models and typical age-structured population models. On the basis of the developed algorithm, we investigate stochastic dynamics of skin cell populations and spread of inflammation. It is revealed that demographic stochasticity can bring considerable impact on the outcome of inflammation spread at the tissue level.

An Attempt to Predict the Preferential Cellular Orientation in Any Complex Mechanical Environment

“…It is likely that the reported results cannot be extended to the case of confluent cells, as cell-cell communication should affect the cellular preferential direction [ 7 , 10 ]. In the case of confluent cells, different approaches (stochastic simulations [ 36 ], reaction-diffusion equations [ 37 ], or other mathematical methods [ 38 ]) are used to model cell population dynamics. Moreover, it has been clearly observed that the cellular orientation also depends on the substrate curvature (this phenomenon has been modelled recently [ 39 ]), or on the micro- or nano-structured surfaces [ 40 ].…”

Stochastic dynamics in a time-delayed model for autoimmunity

“…Including different cytokines can provide a better insight into the dynamics of immune response, as has been recently shown in a detailed model of immune response to hepatitis B [108]. A number of papers have considered time-delayed stochastic models of cellular processes that also explicitly include cell division, but from a perspective of direct stochastic simulation [109,110,111,112]. While in the current model, the dynamics of uninfected cells is described by logistic growth, it would be interesting to explore how one could include cell division as an alternative and more realistic representation for the dynamics of cell populations within the framework of SDDEs.…”

Kinetics of the maintenance of the epidermis

“…After the completion of our work, a three-variable model operating with the population of stem cells in the basal layer, the population of differentiated cells in other layers, and the concentration of a growth factor controlling the division of stem cells was recently proposed in Ref. [30] (Eqs. (3.3)).…”

“…In light of this complexity, existing kinetic models related to the epidermis are focused primarily on proliferation and differentiation of stem cells in the basal layer (Refs. [9][10][11] and [21]- [30]). There is limited consideration of cell-cell communication, and as a rule neither feedback between the basal layer and the upper layers nor spatial constraints are taken into account.…”