Gait Assessment of Pain and Analgesics: Comparison of the DigiGait™ and CatWalk™ Gait Imaging Systems.
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ABSTRACT:
SUBMITTER: Xu Y
PROVIDER: S-EPMC6527535 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Neuropathic pain as a symptom of sensory nerve damage is a frequent side effect of chemotherapy. The most common behavioral observation in animal models of chemotherapy induced polyneuropathy is the development of mechanical allodynia, which is quantified with von Frey filaments. The data from one study, however, cannot be easily compared with other studies owing to influences of environmental factors, inter-rater variability and differences in test paradigms. To overcome these limitations, automated quantitative gait analysis was proposed as an alternative, but its usefulness for assessing animals suffering from polyneuropathy has remained unclear. In the present study, we used a novel mouse model of paclitaxel induced polyneuropathy to compare results from electrophysiology and the von Frey method to gait alterations measured with the Catwalk test. To mimic recently improved clinical treatment strategies of gynecological malignancies, we established a mouse model of dose-dense paclitaxel therapy on the common C57Bl/6 background. In this model paclitaxel treated animals developed mechanical allodynia as well as reduced caudal sensory nerve action potential amplitudes indicative of a sensory polyneuropathy. Gait analysis with the Catwalk method detected distinct alterations of gait parameters in animals suffering from sensory neuropathy, revealing a minimized contact of the hind paws with the floor. Treatment of mechanical allodynia with gabapentin improved altered dynamic gait parameters. This study establishes a novel mouse model for investigating the side effects of dose-dense paclitaxel therapy and underlines the usefulness of automated gait analysis as an additional easy-to-use objective test for evaluating painful sensory polyneuropathy.
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Project description:Motor deficits can significantly affect the completion of daily life activities and have a negative impact on quality of life. Consequently, motor function is an important behavioral endpoint to measure for in vivo pathophysiologic studies in a variety of research areas, such as toxicant exposure, drug development, disease characterization, and transgenic phenotyping. Evaluation of motor function is also critical to the interpretation of cognitive behavioral assays, as many rely on intact motor abilities to derive meaningful data. As such, gait analysis is an important component of behavioral research and can be achieved by manual or video-assisted methods. Manual gait analysis methods, however, are prone to observer bias and are unable to capture many critical parameters. In contrast, automated video-assisted gait analysis can quickly and reliably assess gait and locomotor abnormalities that were previously difficult to collect manually. Here, we describe the evaluation of gait and locomotion in rodents using the automated Noldus CatWalk XT system. We include a step-by-step guide for running an experiment using the CatWalk XT system and discuss theory and considerations when evaluating rodent gait. The protocol and discussion provided here act as a supplemental resource to the manual for this commercially available system and can assist CatWalk users in their experimental design and implementation. © 2021 Wiley Periodicals LLC.
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Project description:Characterizing gait is important in the study of movement disorders, also in clinical mouse models. Gait data are therefore necessary for the development of gait analysis methods and the study of diseases. This article presents gait data of two α-synucleinopathic transgenic mouse models and their non-transgenic littermate, backcrossed into the C57BL/6N genetic background. The animal gait was recorded using CatWalk system, which provides the information for each run about the paw positions, paw print sizes, and paw intensities as a function of time or video frame. A total of 90 run data files are provided in this article.
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Project description:Early diagnosis of Parkinson's diseases (PD) is challenging; applying machine learning (ML) models to gait characteristics may support the classification process. Comparing performance of ML models used in various studies can be problematic due to different walking protocols and gait assessment systems. The objective of this study was to compare the impact of walking protocols and gait assessment systems on the performance of a support vector machine (SVM) and random forest (RF) for classification of PD. 93 PD and 103 controls performed two walking protocols at their normal pace: (i) four times along a 10 m walkway (intermittent walk-IW), (ii) walking for 2 minutes on a 25 m oval circuit (continuous walk-CW). 14 gait characteristics were extracted from two different systems (an instrumented walkway-GAITRite; and an accelerometer attached at the lower back-Axivity). SVM and RF were trained on normalized data (accounting for step velocity, gender, age and BMI) and evaluated using 10-fold cross validation with area under the curve (AUC). Overall performance was higher for both systems during CW compared to IW. SVM performed better than RF. With SVM, during CW Axivity significantly outperformed GAITRite (AUC: 87.83 ± 7.81% vs. 80.49 ± 9.85%); during IW systems performed similarly. These findings suggest that choice of testing protocol and sensing system may have a direct impact on ML PD classification results and highlight the need for standardization for wide scale implementation.
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Project description:Evaluation of functional outcome is widely used across species to assess the recovery process following various pathological conditions, including spinal cord injury, musculo-skeletal injury, mithochondrial disease, neuropathic cancer, Huntington's disease, chronic pain, cortical lesion, and olivocerebellar degeneration among others. The Stroke Therapy Academic Industry Roundtable (STAIR) recommends multiple endpoints for behavioral studies in pre-clinical stroke research, to demonstrate their clinical relevance. One of the more challenging tasks in experimental stroke research is measuring long-term functional outcome in mice. It is, however, becoming more important, since transgenic mice are increasingly used for modeling human neurological disorders. Using CatWalk, we characterized long-lasting gait/locomotion deficits following mouse distal middle cerebral artery occlusion (dMCAO). The post-dMCAO assessment was performed at 7, 14, 21, and 28days after experimental ischemia. When compared to sham-operated mice, dMCAO animals displayed a statistically significant decrease in Spatial parameters (such as Paw Area), while the Temporal parameters (Stand, Initial and Terminal Dual Stances) were significantly increased for three weeks after surgery. Kinetic parameters were significantly decreased in dMCAO animals at 7days after dMCAO. The Interlimb coordination group of parameters displayed the strongest deficits at 21days. While CatWalk variables were altered in all paws, the degree of change was greatest for the parameters measured from the Right Front Paw (contralateral to the lesion). All parameters measured in dMCAO and Sham-operated groups reached similar levels at four weeks after the experimental insult, which reflects a spontaneous post-ischemic recovery. Based on our investigation, we conclude that CatWalk represents a relevant and sensitive analysis, which allows long-term characterization of animal functional recovery in the dMCAO model of experimental ischemia.
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Project description:OBJECTIVE:Measuring motor function in mice is important for studying models of spinal cord injury (SCI) or other diseases. Several methods exist based on visual observation of mice moving in an open field. Though these methods require very little equipment, observers must be trained, and the possibility of human error or subjectivity cannot be eliminated. The Noldus CatWalk XT Automated Gait Analysis system assesses mouse motor function by taking high-resolution videos of the mice, with specialized software to measure several aspects of the animal's gait. This instrument reduces the possibility of human error, but it is not always clear what data is important for assessing motor function. This study used data collected during mouse SCI experiments to create a simple mathematical model that combines the data collected by the CatWalk system into a single score, the Combined CatWalk Index or CCI. RESULTS:The CCI system produces similar results to the Basso Mouse Scale or the CatWalk's Step Sequence Regularity Index. However, the CCI has a significantly smaller coefficient of variation than either other method. Additionally, CCI scoring shows slightly better correlation with impact force. The CCI system is likely to be a useful tool for SCI research.
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Project description:PurposeIn this study, we evaluated the analgesic potential of demethylating drugs on oral cancer pain. Although demethylating drugs could affect expression of many genes, we focused on the mu-opioid receptor (OPRM1) gene pathway, because of its role in pain processing. We determined the antinociceptive effect of OPRM1 re-expression in a mouse oral cancer model.Experimental designUsing a mouse oral cancer model, we determined whether demethylating drugs produced antinociception through re-expression of OPRM1. We then re-expressed OPRM1 with adenoviral transduction and determined if, and by what mechanism, OPRM1 re-expression produced antinociception. To determine the clinical significance of OPRM1 on cancer pain, we quantified OPRM1 methylation in painful cancer tissues and nonpainful contralateral normal tissues of patients with oral cancer, and nonpainful dysplastic tissues of patients with oral dysplasia.ResultsWe demonstrated that OPRM1 was methylated in cancer tissue, but not normal tissue, of patients with oral cancer, and not in dysplastic tissues from patients with oral dysplasia. Treatment with demethylating drugs resulted in mechanical and thermal antinociception in the mouse cancer model. This behavioral change correlated with OPRM1 re-expression in the cancer and associated neurons. Similarly, adenoviral-mediated OPRM1 re-expression on cancer cells resulted in naloxone-reversible antinociception. OPRM1 re-expression on oral cancer cells in vitro increased β-endorphin secretion from the cancer, and decreased activation of neurons that were treated with cancer supernatant.ConclusionOur study establishes the regulatory role of methylation in cancer pain. OPRM1 re-expression in cancer cells produces antinociception through cancer-mediated endogenous opioid secretion. Demethylating drugs have an analgesic effect that involves OPRM1.
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Project description:AimsTo investigate the use of an enriched study design on the estimates of treatment effect in analgesic trials for chronic musculoskeletal pain.MethodsDatabase searches were conducted from 2004 to 2014. We included randomized placebo-controlled trials evaluating pain medications for chronic musculoskeletal pain. Methodological quality was assessed using the PEDro scale. The estimates of treatment effect on pain and adverse events were compared between enriched and nonenriched designs. Metaregression was used to assess the association between the effect size estimate and the study design controlling for analgesic dose and methodological quality.ResultsWe included 108 trials, of which 99 were included in the meta-analysis (n = 44?171). There were no overall differences in effect sizes between enriched and nonenriched designs for pain intensity. There was a significant difference for a reduction in any adverse events favouring enriched designs for opioids, but not for other analgesics or the outcome serious adverse events. There was an association between effect size and methodological quality, with failure to blind the outcome assessor and failure to use intention-to-treat analysis being associated with larger effect sizes.ConclusionsThere is no evidence that the use of an enriched study design changes the treatment effect size estimate for pain. There is some evidence that clinical trials that employ enriched designs report a reduced risk of adverse events in trials for chronic musculoskeletal pain, but it is unclear whether enriched designs influence estimates of serious adverse events. Features of trial design and study quality were associated with treatment effect estimates.
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Project description:Arthritic disorders have become one of the main contributors to the global burden of disease. Today, they are one of the leading causes of chronic pain and disability worldwide. Current therapies are incapable of treating pain sufficiently and preventing disease progression. The lack of understanding basic mechanisms underlying the initiation, maintenance and progression of arthritic disorders and related symptoms represent the major obstacle in the search for adequate treatments. For a long time, histological evaluation of joint pathology was the predominant outcome parameter in preclinical arthritis models. Nevertheless, quantification of pain and functional limitations analogs to arthritis related symptoms in humans is essential to enable bench to bedside translation and to evaluate the effectiveness of new treatment strategies. As the experience of pain and functional deficits are often associated with altered gait behavior, in the last decades, automated gait analysis has become a well-established tool for the quantitative evaluation of the sequalae of arthritic disorders in animal models. The purpose of this review is to provide a detailed overview on the current literature on the use of the CatWalk gait analysis system in rodent models of arthritic disorders, e.g., Osteoarthritis, Monoarthritis and Rheumatoid Arthritis. Special focus is put on the assessment and monitoring of pain-related behavior during the course of the disease. The capability of evaluating the effect of distinct treatment strategies and the future potential for the application of the CatWalk in rodent models of arthritic disorders is also addressed in this review. Finally, we discuss important consideration and provide recommendations on the use of the CatWalk in preclinical models of arthritic diseases.
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