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使用CFSE分布数据对标记结构细胞群体生长进行数值建模。

Numerical modelling of label-structured cell population growth using CFSE distribution data.

作者信息

Luzyanina Tatyana, Roose Dirk, Schenkel Tim, Sester Martina, Ehl Stephan, Meyerhans Andreas, Bocharov Gennady

机构信息

Institute of Numerical Mathematics, RAS, Moscow, Russia.

出版信息

Theor Biol Med Model. 2007 Jul 24;4:26. doi: 10.1186/1742-4682-4-26.

DOI:10.1186/1742-4682-4-26
PMID:17650320
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1950697/
Abstract

BACKGROUND

The flow cytometry analysis of CFSE-labelled cells is currently one of the most informative experimental techniques for studying cell proliferation in immunology. The quantitative interpretation and understanding of such heterogenous cell population data requires the development of distributed parameter mathematical models and computational techniques for data assimilation.

METHODS AND RESULTS

The mathematical modelling of label-structured cell population dynamics leads to a hyperbolic partial differential equation in one space variable. The model contains fundamental parameters of cell turnover and label dilution that need to be estimated from the flow cytometry data on the kinetics of the CFSE label distribution. To this end a maximum likelihood approach is used. The Lax-Wendroff method is used to solve the corresponding initial-boundary value problem for the model equation. By fitting two original experimental data sets with the model we show its biological consistency and potential for quantitative characterization of the cell division and death rates, treated as continuous functions of the CFSE expression level.

CONCLUSION

Once the initial distribution of the proliferating cell population with respect to the CFSE intensity is given, the distributed parameter modelling allows one to work directly with the histograms of the CFSE fluorescence without the need to specify the marker ranges. The label-structured model and the elaborated computational approach establish a quantitative basis for more informative interpretation of the flow cytometry CFSE systems.

摘要

背景

目前，对CFSE标记细胞进行流式细胞术分析是免疫学中研究细胞增殖最具信息量的实验技术之一。对这种异质细胞群体数据进行定量解释和理解需要开发分布式参数数学模型和数据同化计算技术。

方法与结果

标记结构细胞群体动力学的数学建模导致一个单空间变量的双曲型偏微分方程。该模型包含细胞更新和标记稀释的基本参数，需要根据CFSE标记分布动力学的流式细胞术数据进行估计。为此，采用了最大似然法。使用Lax-Wendroff方法求解模型方程的相应初边值问题。通过将两个原始实验数据集与模型拟合，我们展示了其生物学一致性以及对细胞分裂和死亡率进行定量表征的潜力，将其视为CFSE表达水平的连续函数。

结论

一旦给出增殖细胞群体相对于CFSE强度的初始分布，分布式参数建模允许直接处理CFSE荧光直方图，而无需指定标记范围。标记结构模型和详细的计算方法为更有信息量地解释流式细胞术CFSE系统建立了定量基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cd0/1950697/6fdd4ce12aef/1742-4682-4-26-10.jpg
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2
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BMC Bioinformatics. 2007 Jun 12;8:196. doi: 10.1186/1471-2105-8-196.
3
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4
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PLoS Comput Biol. 2019 Nov 6;15(11):e1007401. doi: 10.1371/journal.pcbi.1007401. eCollection 2019 Nov.
5
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7
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8
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4
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