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Mathematical Modeling for Dendritic ...

Liu, Xiangtao.

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Mathematical Modeling for Dendritic Cells in the Immune System.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Mathematical Modeling for Dendritic Cells in the Immune System./
作者:	Liu, Xiangtao.
面頁冊數:	139 p.
附註:	Source: Dissertation Abstracts International, Volume: 72-03, Section: B, page: .
Contained By:	Dissertation Abstracts International72-03B.
標題:	Applied Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3440598
ISBN:	9781124424538

Mathematical Modeling for Dendritic Cells in the Immune System.
Liu, Xiangtao.

Mathematical Modeling for Dendritic Cells in the Immune System. - 139 p.

Source: Dissertation Abstracts International, Volume: 72-03, Section: B, page: .

Thesis (Ph.D.)--Yale University, 2010.

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.

ISBN: 9781124424538Subjects--Topical Terms:

1669109
Applied Mathematics.

Mathematical Modeling for Dendritic Cells in the Immune System.
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245 1 0 $a Mathematical Modeling for Dendritic Cells in the Immune System.
300 $a 139 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-03, Section: B, page: .
500 $a Adviser: Josephine Hoh.
502 $a Thesis (Ph.D.)--Yale University, 2010.
520 $a 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.
520 $a 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.
520 $a 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.
520 $a 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.
520 $a Keywords: APCs, cDCs, steady state, logistic growth, systematic model.
590 $a School code: 0265.
650 4 $a Applied Mathematics. $3 1669109
650 4 $a Health Sciences, Immunology. $3 1017716
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790 1 0 $a Hoh, Josephine, $e advisor
790 $a 0265
791 $a Ph.D.
792 $a 2010
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