Original research paperEstablishing a reliable gait evaluation method for rodent studies☆
Introduction
Peripheral nerve injury is a major burden to healthcare systems worldwide, affects 1.4 million patients, and costs over $150 billion dollars every year (Jia et al., 2014, Jiang et al., 2017, Jones et al., 2016, Taylor et al., 2008). Preclinical rodent studies are particularly valuable due to low cost and high translational potential (Kizilay et al., 2016, Wang et al., 2016), however, researchers must rely on postmortem pathological evaluation with only limited ways to evaluate functional recovery (Bervar, 2000, de Medinaceli et al., 1982). CatWalk has become a popular tool in rodent preclinical studies for evaluating functional recovery due to its ability to acquire a wide variety of gait parameters with its automatic “Auto Classify” function, and it is now widely used in mainstream research protocols in a wide variety of fields including peripheral nerve injury (Bozkurt et al., 2008, Deumens et al., 2007, Deumens et al., 2014, Johnson and Jia, 2016), spinal cord injury (Kjell et al., 2015, Salewski et al., 2015), traumatic brain injury (Kizilay et al., 2016), neurodegenerative diseases (Neckel, 2015) etc. Google Scholar generated 1520 search results with the search term “CatWalk Gait” and 490 results with “CatWalk Sciatic” since 2006.
While CatWalk is now a widely used tool, it has significant drawbacks. Researchers often choose from wide variety of gait parameters to report their findings without justification of selection preference (Freria et al., 2016, Fujimaki et al., 2016, Hausner et al., 2014, Huang et al., 2012), and there are conflicting interpretations of results across different injury models (Bozkurt et al., 2008, Hamers et al., 2006). The lack of a standard set of parameters and interpretations may be due to common but seldom mentioned problems following rat sciatic nerve injury such as preferential heel walking (Deumens et al., 2007, Deumens et al., 2014) and poor compliance (Neckel, 2015). While these problems significantly impair the ability of CatWalk to reliably automatically collect and analyze data, current literature has yet to propose any strategies on how to address them. Therefore, a standard method that effectively addresses these problems must first be established in order to properly identify a standard set of reliable CatWalk gait parameters.
The goal of this study is to establish a standard data processing method to account for and address inherent problems such as heel walking and poor compliance, and to identify a set of CatWalk parameters that is capable of consistently evaluating injury and recovery. Current literature evaluating CatWalk only employ a single injury group and a sham group, so to emulate current research practices, we employed three experimental groups, each receiving nerve resection injury followed by different interventions leading to different levels of recovery: one with an autologous nerve graft (clinical gold standard) to serve as positive control, one with an empty nerve conduit to serve as negative control, and one with human neural crest stem cell (NCSC) implantation to serve as the study target (Bozkurt et al., 2008), which leads to improvements in recovery that is superior to empty nerve conduits but not as effective as autologous nerve grafts (Georgiou et al., 2015, Ni et al., 2013, Wang et al., 2015).
Section snippets
Animals
All animals were maintained according to NIH guidelines, and experimental protocols were approved by the IACUC of the University of Maryland School of Medicine. Every attempt was made to minimize the total number of animals used and their discomfort and pain. In this study, 36 athymic nude rats were used. Rats were individually housed in a controlled temperature (21 ± 1 °C) and humidity (50 ± 15%) throughout this study with a 12:12 h light/dark cycle to reduce stress. All rats had free access to food
Histomorphometric analysis and gastrocnemius muscle weight showed differentiated recovery across experimental groups over time
Overall, there was a significant difference in cell count per 100 um2 when considering all groups and time points (p < 0.001 for all). See Fig. 1.
At 6 weeks, the cell count per 100 um2 was statistically significantly greater for the autograft group (57.17 ± 9.84) than the conduit group (4.00 ± 1.67, p < 0.001) and the NCSC group (8.33 ± 1.76, p < 0.001). The NCSC group showed no significant difference with the conduit only group. Similarly, the cell count was statistically significantly greater for the
Discussion
CatWalk is a very popular tool for evaluating functional recovery following sciatic nerve injuries in rats, however, due to inherent problems such as heel walking and poor compliance, CatWalk is prone to error and fails to generate consistent and trustable results without extensive manual intervention. We tested and established a manual classification process that overcomes the limitations of CatWalk to address inherent problems, and were able to reliably model injury and recovery following
Conclusion
CatWalk is a popular system able to automatically detect many parameters of gait, however, it has many inherent problems that needed to be addressed. Though the automation feature of the software is convenient for researchers, it should not be trusted and relied upon. Further manual processing is a necessary step to improve the usability of results and generate meaningful data. We successfully established a manual processing method that yields reliable dynamic parameters of gait, namely Stand
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2022, Journal of Integrative MedicineCitation Excerpt :The nerve conduction velocity (NCV; in m/s) was calculated as follows [32]: the distance between two stimulation electrodes (in mm) divided by the difference between the action potential latency of the two stimulation points (in ms). On the 28th day after surgery, the gastrocnemius muscles were excised bilaterally, and the wet weights were measured using a high-precision electronic balance [33]. The wet weight ratio (%) of the gastrocnemius was calculated as the wet weight of the muscle on the injured side divided by the wet weight of the muscle on the contralateral side × 100%.
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Supported by Maryland Stem Cell Research Fund (2013-MSCRFE-146-00) (to XJ), and R01HL118084 from NIH (to XJ).