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Quantification of surviving neurons after contusion dislocation and distraction spinal cord injuries using automated methods

机译: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

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摘要

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.
机译:这项研究提出并验证了一种用于计数脊髓损伤(SCI)中神经元的自动化方法,然后使用它来检查和比较常见类型SCI机制中的存活细胞。在Sprague Dawley雄性大鼠中,通过手术诱发了中度挫伤,脱位和分心SCI(每种伤害类型,n = 6)。在损伤后8周,收集5只正常体重匹配的大鼠的脊髓。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。使用一种算法对图像中的神经元进行自动计数,该算法旨在根据形态特征(大小,坚固性,圆形图案)过滤非类索马物体,并检查其余物体的双核/细胞体特征(亮度)变化,亮度分布,颜色)。为了验证自动方法,随机选择了一些图像进行手动计数。发现通过算法自动测量的存活细胞数与由两名观察员手动测量的值相关(P <0.001),具有相似的差异(P> 0.05)。脊髓损伤后,背角和腹角神经元减少(P <0.05)。脱位和分散注意力分别对腹角神经元造成最严重的损害,尤其是在震中附近,对背角神经元造成最广泛,最均匀的损害(P <0.05)。我们的方法被证明是可靠的,适用于研究不同类型的SCI。

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