Reith A, Mayhew T M
Gegenbaurs Morphol Jahrb. 1980;126(2):206-15.
In seeking to draw comparisons between surface density Sv estimates of various organelle membranes, it becomes apparent that main classes of data may be recognised. In the 1st (class A) there is a relatively good agreement between the uncorrected Sv values obtained in different research laboratories, e.g. the boundary membranes of mitochondria, lysosomes and nuclei. In the 2nd class (class B) fall estimates for organelles or organelle sub-compartments whose membrane boundardies cannot be everywhere reliably predicted when they form but vague images on the micrograph, e.g. cristae and membranes of the rough and smooth ER, i.e. class B membranes do not fulfil the assumption for morphometric counting that the identification on section is unambiguous (WEIBEL). For these class B membranes Sv estimates are often more widely discrepant for 2 main reasons. The 1st is connected with the difficulties in finding suitable correction factors which correct either for underestimation of membranes (due to membranes oriented obliquely to the axis of the electron beam) or overestimation due to the Holmes effect. The 2nd equally important reason lies in the subjectivity of the analyser who has to decide to count or not to count vague membrane images. In order to show the insecurities of class B membrane Sv estimates when presenting data it is proposed to abandon the 2nd and 3rd decimal. 2 proposals are made to tackle the problems connected with Sv estimates of class B membranes: Firstly a new method of obtaining a correction factor is presented and secondly, a rigorous standardisation of the criteria used for defining membrane profile intersections. Examples of the latter are shown.
在试图比较各种细胞器膜的表面密度Sv估计值时,很明显可以识别出主要的数据类别。在第一类(A类)中,不同研究实验室获得的未校正Sv值之间有相对较好的一致性,例如线粒体、溶酶体和细胞核的边界膜。第二类(B类)包括细胞器或细胞器亚区室的估计值,其膜边界在形成时不能在各处可靠预测,在显微照片上形成模糊图像,例如嵴以及粗面和滑面内质网的膜,即B类膜不符合形态计量计数的假设,即切片上的识别是明确的(韦贝尔)。对于这些B类膜,Sv估计值往往因两个主要原因而差异更大。第一个原因与找到合适的校正因子的困难有关,这些校正因子用于校正膜的低估(由于膜与电子束轴倾斜)或由于霍姆斯效应导致的高估。第二个同样重要的原因在于分析人员的主观性,分析人员必须决定是否对模糊的膜图像进行计数。为了在呈现数据时显示B类膜Sv估计值的不安全性,建议舍弃小数点后第二位和第三位。针对与B类膜Sv估计相关的问题提出了两项建议:首先,提出了一种获得校正因子的新方法;其次,对用于定义膜轮廓交叉点的标准进行严格标准化。并给出了后者的示例。