使用自动化方法量化挫伤、脱位和牵张性脊髓损伤后存活的神经元

Jingchao Wang, Meiyan Zhang, Yue-sheng Guo, Hai Hu, Kinon Chen
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引用次数: 6

摘要

本研究提出并验证了一种自动计数脊髓损伤(SCI)神经元的方法,然后用它来检查和比较常见类型脊髓损伤机制中的存活细胞。Sprague-Dawley雄性大鼠(n = 每种损伤类型6个)。他们的脊髓被切除了8根 损伤后数周,用5只正常体重匹配的大鼠。切断脊髓,用抗NeuN抗体和荧光Nissl染色,并在距震中不同距离的背角和腹角成像。使用一种算法自动计数图像中的神经元,该算法旨在根据形态学特征(大小、坚固性、圆形图案)过滤非躯体状物体,并检查剩余物体的细胞核/细胞体双重染色特征(亮度变化、亮度分布、颜色)。为了验证自动化方法,随机选择一些图像进行手动计数。发现算法自动测量的存活细胞数与2名观察者手动测量的值相关(P  .05)。SCIs后,背角和腹角神经元减少(P < .05)。错位和分心对腹角神经元的损伤最为严重,尤其是在震中附近,对背角神经元的损害最为广泛和均匀(P < .05)。我们的方法被证明是可靠的,适用于研究不同类型的SCI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantification of surviving neurons after contusion, dislocation, and distraction spinal cord injuries using automated methods
This study proposes and validates an automated method for counting neurons in spinal cord injury (SCI) and then uses it to examine and compare the surviving cells in common types of SCI mechanisms. Moderate contusion, dislocation, and distraction SCIs were surgically induced in Sprague Dawley male rats (n = 6 for each type of injury). Their spinal cords were harvested 8 weeks post injury with 5 normal weight-matched rats. The spinal cords were cut, stained with anti-NeuN antibody and fluorescent Nissl, and imaged in the dorsal and ventral horns at various distances to the epicenter. Neurons in the images were automatically counted using an algorithm that was designed to filter non-soma-like objects based on morphological characteristics (size, solidity, circular pattern) and check the remaining objects for the double-stained nucleus/cell body features (brightness variation, brightness distribution, color). To validate the automated method, some of the images were randomly selected for manual counting. The number of surviving cells that were automatically measured by the algorithm was found to be correlated with the values that were manually measured by 2 observers (P < .001) with similar differences (P > .05). Neurons in the dorsal and ventral horns were reduced after the SCIs (P < .05). Dislocation and distraction, respectively, caused the most severe damage to the ventral horn neurons especially near the epicenter and the most extensive and uniform damage to the dorsal horn neurons (P < .05). Our method was proved to be reliable, which is suitable for studying different types of SCI.
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