Detecting ALS and Parkinson's disease in rats through locomotion analysis

被引：1

作者：

Tang W. ^{[1
]}

Yarowsky P. ^{[2
]}

Tasch U. ^{[1
]}

机构：

[1] Department of Mechanical Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD

[2] Department of Pharmacology and Experimental Therapeutics, University of Maryland School of Medicine and the Veterans Administration, Baltimore, MD

来源：

Network Modeling Analysis in Health Informatics and Bioinformatics | 2012年 / 1卷 / 1-2期

关键词：

ALS; Locomotion analysis; Logistic regression model; PD; Rats;

D O I：

10.1007/s13721-012-0004-8

中图分类号：

学科分类号：

摘要：

We describe a method that detects locomotion deficiencies due to amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) in laboratory rats. The locomotion deficiencies are recognized by performing three different comparisons: (1) comparing the locomotion of an ALS model, G93A mutation of SOD1 with control rats, (2) comparing the locomotion of a PD model, 6-OHDA lesioned with control rats, and (3) comparing the locomotion of G93A/SOD1 and 6-OHDA lesioned rats. Each comparison resulted in different set of locomotion parameters for ALS and PD that characterized the locomotion deficiencies and resulted in the best logistic regression model that classifies the rats into diseased/healthy groups with minimum error. The sensitivity and the specificity of the classification for comparisons (1), (2), and (3) were above 90%. © 2012 Springer-Verlag.

引用

页码：63 / 68

页数：5

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