Suppr超能文献

细胞培养中少突胶质细胞生成的随机建模:用延时数据进行模型验证

Stochastic modeling of oligodendrocyte generation in cell culture: model validation with time-lapse data.

作者信息

Hyrien Ollivier, Ambeskovic Ibro, Mayer-Proschel Margot, Noble Mark, Yakovlev Andrei

机构信息

Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA.

出版信息

Theor Biol Med Model. 2006 May 17;3:21. doi: 10.1186/1742-4682-3-21.

Abstract

BACKGROUND

The purpose of this paper is two-fold. The first objective is to validate the assumptions behind a stochastic model developed earlier by these authors to describe oligodendrocyte generation in cell culture. The second is to generate time-lapse data that may help biomathematicians to build stochastic models of cell proliferation and differentiation under other experimental scenarios.

RESULTS

Using time-lapse video recording it is possible to follow the individual evolutions of different cells within each clone. This experimental technique is very laborious and cannot replace model-based quantitative inference from clonal data. However, it is unrivalled in validating the structure of a stochastic model intended to describe cell proliferation and differentiation at the clonal level. In this paper, such data are reported and analyzed for oligodendrocyte precursor cells cultured in vitro.

CONCLUSION

The results strongly support the validity of the most basic assumptions underpinning the previously proposed model of oligodendrocyte development in cell culture. However, there are some discrepancies; the most important is that the contribution of progenitor cell death to cell kinetics in this experimental system has been underestimated.

摘要

背景

本文目的有两个。第一个目标是验证这些作者之前开发的用于描述细胞培养中少突胶质细胞生成的随机模型背后的假设。第二个目标是生成延时数据,这可能有助于生物数学家构建其他实验场景下细胞增殖和分化的随机模型。

结果

使用延时视频记录可以追踪每个克隆内不同细胞的个体演变。这种实验技术非常费力,无法替代基于克隆数据的基于模型的定量推断。然而,在验证旨在描述克隆水平上细胞增殖和分化的随机模型结构方面,它是无与伦比的。本文报告并分析了体外培养的少突胶质前体细胞的此类数据。

结论

结果有力地支持了先前提出的细胞培养中少突胶质细胞发育模型的最基本假设的有效性。然而,存在一些差异;最重要的是,在该实验系统中祖细胞死亡对细胞动力学的贡献被低估了。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebf0/1481529/444e289e98da/1742-4682-3-21-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验