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从切片数据确定核仁多样性和细胞数量。

Determining nucleolar multiplicity and cell number from sectional data.

作者信息

Gramsbergen A, Kok L P, Poortema K, Schaafsma W

出版信息

J Microsc. 1987 Jan;145(Pt 1):69-87. doi: 10.1111/j.1365-2818.1987.tb01317.x.

DOI:10.1111/j.1365-2818.1987.tb01317.x
PMID:3573035
Abstract

The occurrence of more than one nucleolus within the cellular nucleus (polynucleolarity) is a well-known phenomenon during the proliferative cell cycle, both under normal and pathological conditions (e.g. neoplasia). It can also be observed in neuronal nuclei at early stages of their maturation. Polynucleolarity merits investigation for cytological reasons. In an histological section, the observed number of nucleoli in a nucleus may be smaller than the actual number. In order to estimate the true distribution of the number of nucleoli per nucleus from the observed distribution, the mathematical relation between these distributions is derived on the basis of rather restrictive stereological assumptions. It is indicated how these distributions can be estimated from the data available and how the statistical uncertainties involved can be expressed. This paper arose from making cell counts. Two methods may be applied: all visible nuclear profiles are counted, nuclear profiles are only included if at least one nucleolus is visible in the section. We recommended a combination of these two methods. An advantage of our theory for determining cell number is that one can often manage without the rather restrictive stereological assumptions needed hitherto. The advantage of expressing statistical uncertainties in estimated nucleolar multiplicity probabilities and cell numbers is indicated.

摘要

细胞核内出现一个以上核仁(多核仁现象)是增殖细胞周期中一种众所周知的现象,在正常和病理条件下(如肿瘤形成)均会出现。在神经元细胞核成熟的早期阶段也能观察到这种现象。出于细胞学原因,多核仁现象值得研究。在组织学切片中,观察到的细胞核内核仁数量可能小于实际数量。为了根据观察到的分布估计每个细胞核内核仁数量的真实分布,基于相当严格的体视学假设推导出了这些分布之间的数学关系。文中指出了如何根据现有数据估计这些分布,以及如何表达所涉及的统计不确定性。本文源于进行细胞计数。可应用两种方法:对所有可见的核轮廓进行计数,仅当切片中至少可见一个核仁时才纳入核轮廓。我们推荐将这两种方法结合使用。我们确定细胞数量的理论的一个优点是,通常无需迄今所需的相当严格的体视学假设。文中指出了在估计核仁多重性概率和细胞数量时表达统计不确定性的优点。

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