CatWalk步态分析系统分析大鼠大脑中动脉阻塞模型的行为学特征

目的 探讨以CatWalk步态分析系统对大鼠暂时性大脑中动脉阻塞(MCAO)模型进行行为学评价的可行性.方法 30只SD雄性大鼠按随机数字表法分为MCAO模型组和对照组,其中模型组以线栓法制作成暂时性MCAO模型.分别于模型制作后第1、3、7、14、28天应用传统的18分制mNSS评分以及CatWalk步态分析系统对2组大鼠进行行为学特征分析.结果 CatWalk结果 显示MCAO模型组大鼠的四肢压强、接触面积和运行速度均比对照组大鼠减小减慢；在协调性方面,模型组大鼠造模后第3天时同为后侧的左后肢→右后肢的时间较对照组明显缩短,且其同为左侧的左前肢→左后肢的时间亦较对照组明显缩短,这一变化在第28天时仍然存在；在造模后第3天模型组出现了在对照组中并未见到的Ra型(1.5％)和Rb型(2.3％)步序；但步调、站立时间、抬爪时间和规律指数等参数在2组间差别不明显.结论 CatWalk步态分析系统在压强、速度、接触面积、步态以及协调性等方面可反映脑缺血造成的损伤及其随时间变化的过程,可用于动物模型的多种行为学特征的综合分析.

Catwalk-assisted behavioral analysis of rat models of middle cerebral artery occlusion

Objective To investigate the feasibility of Catwalk-assisted system in analyzing the behavioral features of rat models of middle cerebral artery occlusion(MCAO).Methods Thirty male SD rats were randomly assigned to experimental group and control group.Suture-occluded method was used to establish the focal cerebral ischemia/reperfusion models in the experimental group.Traditional modified neurological severity scale(mNSS),vibrissae-evoked forelimb placing test and cylinder test were employed to analyze the behavioral characteristics of the SD rats 1,3,7,14 and 28 dafter establishment of rat models.Besides that,Catwalk-assisted gait analysis system was employed at the same time points.Results Catwalk-assisted gait analysis results suggest rats from experimental group had smaller intensity,print area and slower walk speed than rats from control group.Besides that,interlimb coordination also changed on the 3rd d of operation and existed until the 28th d of operation.Rotate step patterns like Ra(1.5％)and Rb(2.3％)were detected in experimental group but never seen in control group.Parameters as cadence,stance,swing and other regularity index had no significant changes between the 2 groups.Conclusion Catwalk analysis system,by analyzing such movement parameters of MCAO rats as intensity,speed,print area,step pattern and interlimb coordination,can commendably reflect the damage of brain ischemia and its changes crossing time,which can comprehensively analyze many behavioral features of the models.