Literature DB >> 24831263

Surgical animal models of neuropathic pain: Pros and Cons.

Siva Reddy Challa1.   

Abstract

One of the biggest challenges for discovering more efficacious drugs for the control of neuropathic pain has been the diversity of chronic pain states in humans. It is now acceptable that different mechanisms contribute to normal physiologic pain, pain arising from tissue damage and pain arising from injury to the nervous system. To study pain transmission, spot novel pain targets and characterize the potential analgesic profile of new chemical entities, numerous experimental animal pain models have been developed that attempt to simulate the many human pain conditions. Among the neuropathic pain models, surgical models have paramount importance in the induction of pain states. Many surgical animal models exist, like the chronic constriction injury (CCI) to the sciatic nerve, partial sciatic nerve ligation (pSNL), spinal nerve ligation (SNL), spared nerve injury (SNI), brachial plexus avulsion (BPA), sciatic nerve transaction (SNT) and sciatic nerve trisection. Most of these models induce responses similar to those found in causalgia, a syndrome of sustained burning pain often seen in the distal extremity after partial peripheral nerve injury in humans. Researchers most commonly use these surgical models in both rats and mice during drug discovery to screen new chemical entities for efficacy in the area of neuropathic pain. However, there is scant literature that provides a comparative discussion of all these surgical models. Each surgical model has its own benefits and limitations. It is very difficult for a researcher to choose a suitable surgical animal model to suit their experimental set-up. Therefore, particular attention has been given in this review to comparatively provide the pros and cons of each model of surgically induced neuropathic pain.

Entities:  

Keywords:  animal models; chronic constriction injury; neuropathic pain; partial sciatic nerve ligation; spinal nerve ligation; surgical models

Mesh:

Year:  2014        PMID: 24831263     DOI: 10.3109/00207454.2014.922559

Source DB:  PubMed          Journal:  Int J Neurosci        ISSN: 0020-7454            Impact factor:   2.292


  33 in total

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