| Literature DB >> 32755615 |
Johannes Heinzel1, Gregor Längle2, Viola Oberhauser2, Thomas Hausner2, Jonas Kolbenschlag3, Cosima Prahm3, Johannes Grillari4, David Hercher5.
Abstract
Injuries of the peripheral nervous system are common among the population affecting around 3% of all trauma patients. This high clinical need in the field of peripheral nerve injury and regeneration has been steadily driving experimental and epidemiological research. Thereby, it is crucial to determine the exact degree of recovery of end-organ function. Regeneration after nerve injuries is assessed by a wide variety of techniques and pre-clinical model systems, where rodent models are among the most widely used. However, results from rodents are difficult to translate to human patients in general, and reproducible and comparable assessment of functional recovery is of highest importance. Computerized gait analysis allows comprehensive acquisition of locomotor function. As the animals cross the recording device voluntarily, functional recovery is assessable with a minimum degree of human interference on their behavior. This article aims to give a detailed overview on the existing literature on CatWalk gait analysis in rodent models of peripheral nerve injuries of upper and lower extremities, e.g. axonotmesis, neurotmesis or fibrosis, with special emphasis on differences between models. Researchers interested in assessment of locomotor function in such models will especially benefit from this work as it will provide them with an overview of the various experimental setups and expected outcomes. This work also addresses potential pitfalls and hurdles in order to promote well designed, comparable studies allowing for accelerated development of therapeutic strategies in peripheral repair and regeneration.Entities:
Keywords: Automated gait analysis; CatWalk™ XT; Fibrosis; Functional recovery; Mice; Nerve injury; Nerve regeneration; Peripheral nerve; Rats; Rodents
Mesh:
Year: 2020 PMID: 32755615 DOI: 10.1016/j.jneumeth.2020.108889
Source DB: PubMed Journal: J Neurosci Methods ISSN: 0165-0270 Impact factor: 2.390