Wang Yunji, Han Hai-Chao, Yang Jack Y, Lindsey Merry L, Jin Yufang
Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA.
BMC Syst Biol. 2010 May 28;4 Suppl 1(Suppl 1):S5. doi: 10.1186/1752-0509-4-S1-S5.
Progressive remodelling of the left ventricle (LV) following myocardial infarction (MI) is an outcome of spatial-temporal cellular interactions among different cell types that leads to heart failure for a significant number of patients. Cellular populations demonstrate temporal profiles of flux post-MI. However, little is known about the relationship between cell populations and the interaction strength among cells post-MI. The objective of this study was to establish a conceptual cellular interaction model based on a recently established graph network to describe the interaction between two types of cells.
We performed stability analysis to investigate the effects of the interaction strengths, the initial status, and the number of links between cells on the cellular population in the dynamic network. Our analysis generated a set of conditions on interaction strength, structure of the network, and initial status of the network to predict the evolutionary profiles of the network. Computer simulations of our conceptual model verified our analysis.
Our study introduces a dynamic network to model cellular interactions between two different cell types which can be used to model the cellular population changes post-MI. The results on stability analysis can be used as a tool to predict the responses of particular cell populations.
心肌梗死(MI)后左心室(LV)的进行性重塑是不同细胞类型之间时空细胞相互作用的结果,这会导致相当数量的患者发生心力衰竭。细胞群体在心肌梗死后呈现出通量的时间分布特征。然而,关于心肌梗死后细胞群体之间的关系以及细胞间相互作用强度知之甚少。本研究的目的是基于最近建立的图网络建立一个概念性细胞相互作用模型,以描述两种细胞类型之间的相互作用。
我们进行了稳定性分析,以研究相互作用强度、初始状态以及细胞间连接数量对动态网络中细胞群体的影响。我们的分析得出了一组关于相互作用强度、网络结构和网络初始状态的条件,以预测网络的进化特征。我们概念模型的计算机模拟验证了我们的分析。
我们的研究引入了一个动态网络来模拟两种不同细胞类型之间的细胞相互作用,该网络可用于模拟心肌梗死后的细胞群体变化。稳定性分析的结果可作为预测特定细胞群体反应的工具。