Ultrastructural quantitative stereology on 'mixed' cell populations: problems and possibilities.

Microscopica acta Pub Date : 1980-11-01
R S Fritsch, R Stracke
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引用次数: 0

Abstract

Contrary to homogeneous tissues, "mixed" tissues or cell suspensions are composed of different cell individuals. They have been characterized as heterogeneous cell populations (composed of cells of different cytogenetical source) and heteromorphous or inhomogeneous cell populations (of cells of the same type but of different individual functional state). Certain problems may arise during ultrastructural morphometrical investigations of heteromorphous populations. Because of the different size of planes of sectioning of individual cells, morphometrical results should be treated by means of modifications of the t-test [4]. Furthermore, the unambiguous classification of individual cell profiles necessitates a conscious selection of cell profiles containing a nuclear profile. This non-random sampling approach leads to systematic errors of computed parameters for the whole cell as the nuclear volume fraction and the specific cell surface area which should be corrected. Besides correction procedures derived from regular geometrical models we have presented correction methods for cells with non-spherical nucleus and a cell surface with marked surface projections [13, 21]. On the other hand, on heteromorphous cell populations, more detailed information about functional events can be gained, in comparison the customary stereological mean values, by means of frequency distributions of morphometrical data of individual cell profiles as well as by correlation of data of different cell organelles.

“混合”细胞群的超微结构定量立体学:问题和可能性。
与同质组织相反,“混合”组织或细胞悬浮液由不同的细胞个体组成。它们的特点是异质细胞群(由不同细胞遗传来源的细胞组成)和异型或非均质细胞群(由相同类型的细胞组成,但个体功能状态不同)。异型群体的超微结构形态学研究可能会出现一些问题。由于单个细胞的切片平面大小不同,形态计量学结果应通过修改t检验来处理[4]。此外,对单个细胞轮廓的明确分类需要有意识地选择包含核轮廓的细胞轮廓。这种非随机抽样方法导致整个细胞计算参数的系统误差,如核体积分数和细胞比表面积,应予以纠正。除了来自规则几何模型的校正程序外,我们还提出了非球形核细胞和具有标记表面投影的细胞表面的校正方法[13,21]。另一方面,在异型细胞群体中,通过单个细胞剖面形态测量数据的频率分布以及不同细胞器数据的相关性,可以获得关于功能事件的更详细的信息,与习惯的体视平均值进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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