Department of Histology and Embryology, Ondokuz Mayis University School of Medicine, Samsun, Turkey.
J Neurosci Methods. 2010 Mar 15;187(1):90-9. doi: 10.1016/j.jneumeth.2010.01.001. Epub 2010 Jan 12.
Several sources of variability can affect stereological estimates. Here we measured the impact of potential sources of variability on numerical stereological estimates of myelinated axons in the adult rat sciatic nerve. Besides biological variation, parameters tested included two variations of stereological methods (unbiased counting frame versus 2D-disector), two sampling schemes (few large versus frequent small sampling boxes), and workstations with varying degrees of sophistication. All estimates were validated against exhaustive counts of the same nerve cross sections to obtain calibrated true numbers of myelinated axons (gold standard). In addition, we quantified errors in particle identification by comparing light microscopic and electron microscopic images of selected consecutive sections. Biological variation was 15.6%. There was no significant difference between the two stereological approaches or workstations used, but sampling schemes with few large samples yielded larger differences (20.7+/-3.7% SEM) of estimates from true values, while frequent small samples showed significantly smaller differences (12.7+/-1.9% SEM). Particle identification was accurate in 94% of cases (range: 89-98%). The most common identification error was due to profiles of Schwann cell nuclei mimicking profiles of small myelinated nerve fibers. We recommend sampling frequent small rather than few large areas, and conclude that workstations with basic stereological equipment are sufficient to obtain accurate estimates. Electron microscopic verification showed that particle misidentification had a surprisingly variable and large impact of up to 11%, corresponding to 2/3 of the biological variation (15.6%). Thus, errors in particle identification require further attention, and we provide a simple nerve fiber recognition test to assist investigators with self-testing and training.
多种变异性来源可能会影响体视学估计。在这里，我们测量了潜在变异性来源对成年大鼠坐骨神经髓鞘轴突数量体视学估计的影响。除了生物学变异性之外，还测试了两个体视学方法（无偏计数框与 2D 切割器）、两种采样方案（少数大样本与频繁小样本箱）以及具有不同复杂程度的工作站的变化对数值估计的影响。所有估计均通过对同一神经横切样本进行详尽计数进行验证，以获得校准的真实髓鞘轴突数量（黄金标准）。此外，我们通过比较选定连续切片的光镜和电镜图像，量化了粒子识别中的误差。生物学变异性为 15.6%。两种体视学方法或使用的工作站之间没有显著差异，但采用少数大样本的采样方案会导致估计值与真实值之间的差异更大（20.7+/-3.7% SEM），而频繁小样本的差异则明显更小（12.7+/-1.9% SEM）。94%的情况下粒子识别是准确的（范围：89-98%）。最常见的识别错误是由于施万细胞核的轮廓类似于小髓鞘神经纤维的轮廓。我们建议频繁地从小样本中采样，而不是少数大区域，并且得出结论，具有基本体视学设备的工作站足以获得准确的估计值。电子显微镜验证表明，粒子误识别具有惊人的可变且较大的影响，高达 11%，相当于生物学变异性的 2/3（15.6%）。因此，粒子识别中的误差需要进一步关注，我们提供了一个简单的神经纤维识别测试，以帮助研究人员进行自我测试和培训。
