Fiander Maximillian Dj, Chedrawe Matthew Aj, Lamport Anna-Claire, Akay Turgay, Robertson George S
Pharmacology, Dalhousie University.
Medical Neuroscience, Dalhousie University;
J Vis Exp. 2017 Nov 4(129):56032. doi: 10.3791/56032.
Kinematic gait analysis in the sagittal plane has frequently been used to characterize motor deficits in multiple sclerosis (MS). We describe the application of these techniques to identify gait deficits in a mouse model of MS, known as experimental autoimmune encephalomyelitis (EAE). Paralysis and motor deficits in mice subjected to EAE are typically assessed using a clinical scoring scale. However, this scale yields only ordinal data that provides little information about the precise nature of the motor deficits. EAE disease severity has also been assessed by rotarod performance, which provides a measure of general motor coordination. By contrast, kinematic gait analysis of the hind limb in the sagittal plane generates highly precise information about how movement is impaired. To perform this procedure, reflective markers are placed on a hind limb to detect joint movement while a mouse is walking on a treadmill. Motion analysis software is used to measure movement of the markers during walking. Kinematic gait parameters are then derived from the resultant data. We show how these gait parameters can be used to quantify impaired movements of the hip, knee, and ankle joints in EAE. These techniques may be used to better understand disease mechanisms and identify potential treatments for MS and other neurodegenerative disorders that impair mobility.
矢状面的运动步态分析经常被用于表征多发性硬化症(MS)中的运动缺陷。我们描述了这些技术在一种名为实验性自身免疫性脑脊髓炎(EAE)的MS小鼠模型中用于识别步态缺陷的应用。通常使用临床评分量表来评估患EAE小鼠的麻痹和运动缺陷。然而,该量表仅产生序数数据,几乎没有提供关于运动缺陷确切性质的信息。EAE疾病严重程度也通过转棒试验表现来评估,该试验提供了一般运动协调性的测量。相比之下,矢状面后肢的运动步态分析产生了关于运动如何受损的高度精确信息。为了执行此程序,在小鼠在跑步机上行走时,将反光标记放置在后肢上以检测关节运动。运动分析软件用于测量行走过程中标记的运动。然后从所得数据中得出运动步态参数。我们展示了这些步态参数如何用于量化EAE中髋关节、膝关节和踝关节的受损运动。这些技术可用于更好地理解疾病机制,并识别MS和其他损害运动能力的神经退行性疾病的潜在治疗方法。