ESTIMATE OF THE TOTAL NUMBER OF NEURONS AND GLIAL AND ENDOTHELIAL-CELLS IN THE RAT SPINAL-CORD BY MEANS OF THE OPTICAL DISSECTOR

ESTIMATE OF THE TOTAL NUMBER OF NEURONS AND GLIAL AND ENDOTHELIAL-CELLS IN THE RAT SPINAL-CORD BY MEANS OF THE OPTICAL DISSECTOR
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DOI:
10.1002/cne.903280307
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发表时间:
1993-02-15
影响因子:
2.5
通讯作者:
GUNDERSEN, HJG
GUNDERSEN, HJG
中科院分区:
医学3区
文献类型:
--
作者:
BJUGN, R;GUNDERSEN, HJG

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用体视学方法估计了5只大鼠脊髓中神经元、胶质细胞和内皮细胞的总数。每根脊髓被分成12块等长板。从每块板上切下一块横切片和一块斜切片。然后通过点计数技术在横切面上估计每条脊髓的灰质和白质体积。通过光学检测器和系统采样,在35个mm厚的塑料斜切片上估计了不同细胞类型的数值密度。通过将数值密度乘以灰质和白质的总体积来计算总细胞数。在白质和灰质中,平均分别有1510万和210万个细胞。在灰质细胞中,640万个被判定为神经元细胞,430万个被判定为内皮细胞,1030万个被判定为胶质细胞。其中,170万个神经元位于颈椎区,250万个位于胸椎区,160万个位于腰椎区,60万个位于骶尾骨区。所使用的方法操作简单,并且可以在1天的过程中进行必要的计数,以获得对单个脊髓细胞数量的可靠估计。唯一的主要问题是可靠的标准,明确的细胞分类。
The total numbers of neurons and glial and endothelial cells in five rat spinal cords were estimated by stereological techniques.Each spinal cord was divided into 12 slabs of equal length. One transverse and one oblique slice was cut from each slab. The volumes of gray and white matter of each cord were then estimated by point-counting techniques on the transverse slices. By means of optical disectors and systematic sampling, the numerical densities of different cell types were estimated on 35 mum-thick plastic sections from the oblique slices. The total cell number was calculated by multiplying the numerical density by the total volume of gray and white matter.On average there were 15.1 and 2 1.1 million cells in white and gray matter, respectively. Of the cells in gray matter, 6.4 million were judged to be neurons, 4.3 million to be endothelial, and 10.3 million to be glial. Of the neurons, 1.7 million were located in the cervical region, 2.5 million in the thoracic, 1.6 million in the lumbar, and 0.6 million in the sacro-coccygeal region.The methods used are simple to perform, and the counting necessary to obtain a reliable estimate of cell number from one spinal cord can be carried out during the course of 1 day. The only major problem is reliable criteria for unambiguous cell classification.