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干细胞的综合实验与理论研究

Integrated Experimental and Theoretical Studies of Stem Cells.

作者信息

Sladitschek Hanna L, Neveu Pierre A

机构信息

Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany.

出版信息

Curr Stem Cell Rep. 2017;3(3):248-252. doi: 10.1007/s40778-017-0096-2. Epub 2017 Jul 10.

Abstract

PURPOSE OF REVIEW

Stem cells have to balance self-renewal and differentiation. The dynamic nature of these fate decisions has made stem cell study by traditional methods particularly challenging. Here we highlight recent advances in the field that draw on combining quantitative experiments and modeling to illuminate the biology of stem cells both in vitro and in vivo.

RECENT FINDINGS

Recent studies have shown that seemingly complex processes such as the fate decision-making of stem cells or the self-organization of developing tissues obey remarkably simple mathematical models. Negative feedback loops appear to stabilize cellular states hereby ensuring robust fate decision-making and reproducible outcomes. Stochastic fate decisions can account for the great variability observed in biological systems.

SUMMARY

The study of stem cells is hampered by the necessity to track the fate of a cell's progeny over time. Confronting experiments with simple predictive models has allowed to circumvent this problem and gain insights from stem cell heterogeneity in vitro to organ morphogenesis.

摘要

综述目的

干细胞必须在自我更新和分化之间取得平衡。这些命运决定的动态性质使得用传统方法研究干细胞极具挑战性。在此,我们重点介绍该领域的最新进展,这些进展利用定量实验与建模相结合的方法,来阐明体外和体内干细胞的生物学特性。

最新发现

最近的研究表明,诸如干细胞的命运决定或发育中组织的自我组织等看似复杂的过程,遵循着非常简单的数学模型。负反馈回路似乎能稳定细胞状态,从而确保可靠的命运决定和可重复的结果。随机命运决定可以解释生物系统中观察到的巨大变异性。

总结

追踪细胞后代随时间的命运这一必要性阻碍了干细胞研究。将实验与简单的预测模型相结合,使得能够规避这一问题,并从体外干细胞异质性到器官形态发生中获得见解。

相似文献

1
Integrated Experimental and Theoretical Studies of Stem Cells.干细胞的综合实验与理论研究
Curr Stem Cell Rep. 2017;3(3):248-252. doi: 10.1007/s40778-017-0096-2. Epub 2017 Jul 10.
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Stem cell biology meets systems biology.干细胞生物学与系统生物学相遇。
Development. 2009 Nov;136(21):3525-30. doi: 10.1242/dev.040758.

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Inferring epigenetic dynamics from kin correlations.从亲属相关性推断表观遗传动力学。
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