| Dendritic cells (DCs) are specialized antigen presenting cells (APCs) playing key roles in initializing immune responses. Their functions have been thoroughly studied, and many applications to medicine have been derived accordingly. However, the life cycle of DCs, including cell origin, development, death and turnover, is only marginally understood. This thesis is dedicated to using computational methods to study the dynamics of the conventional DC (cDC) populations in mammalian immune systems.;Recent experimental findings of dividing DCs in peripheral lymph organs require a mathematical model to illustrate the kinetics of DC homeostasis. To this end, I build a steady-state model consisting of three linear ordinary differential equations (ODEs). Analytical solutions are derived directly from the model. And biological parameters of interest (including input rate, cell cycle length and death rate) are computed using data provided by our collaborator Dr. Kang Liu, which are consistent with other studies. In addition, stability of the model is confirmed by numerical simulations.;Furthermore, I extend the steady-state model to deal with stimulated states (equilibrium conditions altered by drugs, infections, or chemicals) by introducing the logistic growth model to cell proliferation with varying population sizes. The population of newly identified cDC precursors (pre-DCs) in spleen is included. In line with K. Liu's growth factor Flt3L-induced experiments, I conduct extensive computations to fine tune the model with regions of parameters.;Finally, I derive a systematic model for DC's dynamic life cycle, which unifies both steady- and stimulated-states. In the future, we want to apply our model to predict unforeseen changes, minor or drastic, induced by external stimulations in the DC and pre-DC populations. These computational undertakings may well facilitate immunologists to effectively design their experiments to address key questions on pathogenic mechanisms in DC-related human disorders. The whole modeling approach is applicable to other similar dynamic systems. It can be easily extended to systems of other cell types with knowledge of the developing pathways.;Keywords: APCs, cDCs, steady state, logistic growth, systematic model. |
