Horner C H, Arbuthnott E
Department of Anatomy, Trinity College, Dublin, Ireland.
J Anat. 1991 Aug;177:179-84.
Dendritic spines are small protrusions extending from the dendrites of nerve cells, which bear the majority of synapses. In the past, researchers quantified spine density as the number of visible spines per estimated micrometre of dendrite. This estimate ignores all those spines hidden from view due to their position on the dendrite. Dendrites vary in diameter and the underestimation in some will be greater than others. Estimation of dendritic length is also subjective and difficult in those which are tortuous. The Felman & Peters (1979) geometrical equation takes account of these criteria and provides a method of estimating 'true' spine numbers which does not involve slow and laborious reconstruction. This study compares ratios derived from both methods of estimation (spine density 2:1) at three loci in three experimental groups. Mean values of dendritic diameters and spine dimensions show the major cause for variation in the ratios between loci to be the shaft diameter of the dendrite. However, the greater ratio for apical as compared with basal and oblique dendrites is not as great as expected, bearing in mind that apical dendrites are approximately 2.5 times larger than oblique and basal dendrites. Therefore the spine distribution may not be the same throughout the dendritic field. Estimations of spine density based on visible spine counts are quicker, easier and sufficient for comparisons within the same locus. 'True' estimates (spine density 2) are more accurate and should be used when comparisons are being made between loci, cell types and species.
树突棘是从神经细胞的树突延伸出的小突起,大多数突触都位于其上。过去,研究人员将棘密度量化为每估计微米树突上可见棘的数量。这种估计忽略了所有因位于树突上而隐藏起来的棘。树突的直径各不相同,有些树突的低估程度会比其他树突更大。在那些曲折的树突中,树突长度的估计也是主观且困难的。费尔曼和彼得斯(1979年)的几何方程考虑了这些标准,并提供了一种估计“真实”棘数量的方法,该方法不涉及缓慢且费力的重建。本研究比较了三个实验组中三个位点的两种估计方法(棘密度2:1)得出的比率。树突直径和棘尺寸的平均值表明,位点之间比率变化的主要原因是树突的轴径。然而,考虑到顶树突比斜树突和基底树突大约大2.5倍,顶树突与基底树突和斜树突相比更大的比率并不像预期的那么大。因此,整个树突区域的棘分布可能不一样。基于可见棘计数的棘密度估计更快、更容易,并且足以在同一位点内进行比较。“真实”估计(棘密度2)更准确,在比较不同位点、细胞类型和物种时应使用。