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首页> 外文期刊>Biotechnology and Bioengineering >Adventures in Time and Space: Non linearity and Complexity of Cytokine Effects on Stem Cell Fate Decisions
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Adventures in Time and Space: Non linearity and Complexity of Cytokine Effects on Stem Cell Fate Decisions

机译：时空历险：细胞因子对干细胞命运决定的非线性和复杂性

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Cytokines are central factors in the control of stem cell fate decisions and, as such, they are invaluable to those interested in the manipulation of stem and progenitor cells for clinical or research purposes. In their in vivo niches or in optimized cultures, stem cells are exposed to multiple cytokines, matrix proteins and other cell types that provide individual and combinatorial signals that influence their self-renewal, proliferation and differentiation. Although the individual effects of cytokines are well-characterized in terms of increases or decreases in stern cell expansion or in the production of specific cell lineages, their interactions are often overlooked. Factorial design experiments in association with multiple linear regression is a powerful multivariate approach to derive response-surface models and to obtain a quantitative understanding of cytokine dose and interactions effects. On the other hand, cytokine interactions detected in stem cell processes can be difficult to interpret clue to the fact that the cell populations examined are often heterogeneous, that cytokines can exhibit pleiotropy and redundancy and that they can also be endogenously produced. This perspective piece presents a list of possible biological mechanisms that can give rise to positive and negative two-way factor interactions in the context of in vivo and in vitro stem cell-based processes. These interpretations are based on insights provided by recent studies examining intra- and extra-cellular signaling pathways in adult and embryonic stem cells. Cytokine interactions have been classified according to four main types of molecular and cellular mechanisms: (i) interactions due to co-signaling; (ii) interactions due to sequential actions; (iii) interactions due to high-dose saturation and inhibition; and (iv) interactions due to intercellular signaling networks. For each mechanism, possible patterns of regression coefficients corresponding to the cytokine main effects, quadratic effects and two-way interactions effects are provided. Finally, directions for future mechanistic studies are presented. Biotechnol. Bioeng. 2010;106: 173-182.
机译：细胞因子是控制干细胞命运决定的关键因素，因此，对于那些出于临床或研究目的而对干细胞和祖细胞进行操作感兴趣的人而言，它们是无价的。在干细胞体内或优化培养中，干细胞会暴露于多种细胞因子，基质蛋白和其他细胞类型，这些细胞因子会提供影响其自我更新，增殖和分化的个体和组合信号。尽管就细胞因子的增加或减少，或在特定细胞谱系的产生方面而言，细胞因子的个别作用已被很好地表征，但它们之间的相互作用常常被忽略。与多重线性回归关联的析因设计实验是一种强大的多元方法，可用于推导响应表面模型并获得对细胞因子剂量和相互作用影响的定量了解。另一方面，在干细胞过程中检测到的细胞因子相互作用可能难以解释，这是由于以下事实的事实：所检查的细胞群通常是异质的，细胞因子可以表现出多效性和冗余性，并且它们也可以内源产生。该观点介绍了一系列可能的生物学机制，这些机制可能在体内和体外基于干细胞的过程中引起正负两种双向相互作用。这些解释基于最新研究提供的见解，这些研究检查了成体和胚胎干细胞中的细胞内和细胞外信号通路。细胞因子的相互作用已根据分子和细胞机制的四种主要类型进行了分类：（i）由于共信号作用引起的相互作用; （ii）依序采取行动的互动; （iii）高剂量饱和和抑制作用引起的相互作用; （iv）由于细胞间信号网络的相互作用。对于每种机制，都提供了与细胞因子主效应，二次效应和双向相互作用效应相对应的回归系数的可能模式。最后，提出了未来力学研究的方向。生物技术。生恩2010; 106：173-182。

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