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CatWalk gait analysis in a rat model of multiple sclerosis

Overview of attention for article published in BMC Neuroscience, November 2016
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Title
CatWalk gait analysis in a rat model of multiple sclerosis
Published in
BMC Neuroscience, November 2016
DOI 10.1186/s12868-016-0317-0
Pubmed ID
Authors

Sabine Herold, Prateek Kumar, Klaus Jung, Irina Graf, Henrike Menkhoff, Xenia Schulz, Mathias Bähr, Katharina Hein

Abstract

Myelin oligodendrocyte glycoprotein (MOG)-induced experimental autoimmune encephalomyelitis (EAE) is a widely used animal model for multiple sclerosis. The characteristic feature of the MOG-EAE model in Brown Norway rats is consistent involvement of the spinal cord resulting in limb paresis. The aim of the study was to investigate whether early subclinical gait abnormalities are present in this animal model and can be detected by CatWalk XT, a fully automated gait analysis system. Furthermore, we investigated the usability of CatWalk system for treatment studies. Our gait analysis showed no preclinical abnormalities in MOG-EAE animals. Nevertheless, we characterized a combination of gait parameters that display a high predictive capacity in regard to disease onset. Our detailed histopathological analysis of the spinal cord revealed that lesion formation starts in the lumbar region and propagates toward the cervical part of the spinal cord during the disease course. In the treatment study, the stabilization of gait parameters under the treatment with methylprednisolone was detected in CatWalk as well as in traditional EAE-scoring system. The results from CatWalk test indicate no benefit of lab-intensive automated gait system in EAE-model with chronic-progressive disease course as well as in therapeutic studies with pronounced effect on the severity of clinical symptoms. However, due to its quantitative and objective nature this system may display a refined test to detect small but functional relevant changes in regeneration-orientated studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 94 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 17%
Student > Bachelor 13 14%
Student > Doctoral Student 12 13%
Student > Master 12 13%
Researcher 9 10%
Other 10 11%
Unknown 22 23%
Readers by discipline Count As %
Medicine and Dentistry 13 14%
Neuroscience 13 14%
Nursing and Health Professions 10 11%
Agricultural and Biological Sciences 8 9%
Biochemistry, Genetics and Molecular Biology 5 5%
Other 17 18%
Unknown 28 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 August 2017.
All research outputs
#20,440,241
of 22,994,508 outputs
Outputs from BMC Neuroscience
#1,060
of 1,250 outputs
Outputs of similar age
#350,872
of 416,806 outputs
Outputs of similar age from BMC Neuroscience
#22
of 32 outputs
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