article = {IJRGM-2018-2-106}
title = {Realistic Murine Model for Streptozotocin-induced Diabetic Peripheral Neuropathy}
journal = {International Journal of Regenerative Medicine}
year = {2018}
issn = {2613-5914}
doi = {http://dx.doi.org/10.31487/j.RGM.2018.02.006}
url = {https://www.sciencerepository.org/realistic-murine-model-for-streptozotocin-induced-diabetic-peripheral-neuropathy_RGM-2-106 
author = { Beverly L.  Roeder, Ryan  Lavering,Ryan Wood, Whitney  Harris,Alonzo D.  Cook,Bryan Witt,Greggory  Boatright II,Jeffrey  Brown,Kyril  Cole,Lincoln  Kartchner,Marissa  Campbell,Michael Bradshaw,Ysabella Del  Rosario,}
keywords = {Diabetes, neuropathy, streptozotocin, STZ, insulin}
abstract ={Diabetic peripheral neuropathy (DPN) is a side effect of diabetes that affects ~4% of the world population.
Such a high prevalence mandates appropriate models for studying potential treatments for DPN. This study
used a streptozotocin (STZ) induced DPN model in Wistar rats in conjunction with a precise insulin
treatment to create a realistic environment for the development and testing of DPN. Four sensory tests: Von
Frey force, Von Frey time, Hargreaves method, and digit spread were used to measure neuropathy.
Neuropathy was effectively measured with the Hargreaves method, the Von Frey force, and Von Frey time
(p < 0.05). Digit spread produced insignificant results.
The study described herein is a realistic model for accurately testing DPN in rats treated with insulin. STZinduced diabetic rats may be used to successfully model the progression of diabetic neuropathy in
individuals treating their condition with insulin. Three methods traditionally only used in studies mimicking
the symptoms of neuropathy were also effective in measuring neuropathy resulting from diabetes.}