Quantification of Neurite Degeneration with Enhanced Accuracy and Efficiency in an Model of Parkinson's Disease.

Neurite degeneration is associated with early stages of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease (PD), and amyotrophic lateral sclerosis. One method that is commonly used to analyze neurite degeneration involves calculation of a Degeneration Index (DI) following utilization of the Analyze Particles tool of ImageJ to detect neurite fragments in micrographs of cultured cells. However, DI analyses are prone to several types of measurement error, can be time consuming to perform, and are limited in application. Here, we describe an improved method for performing DI analyses. Accuracy of measurements was enhanced through modification of selection criteria for detecting neurite fragments, removal of image artifacts and non-neurite materials from images, and optimization of image contrast. Such enhancements were implemented into an ImageJ macro that enables rapid and fully automated DI analysis of multiple images. The macro features operations for automated removal of cell bodies from micrographs, thus expanding the application of DI analyses to use in experiments involving dissociated cultures. We present experimental findings supporting that, compared with the conventional method, the enhanced analysis method yields measurements with increased accuracy and requires significantly less time to perform. Furthermore, we demonstrate the utility of the method to investigate neurite degeneration in a cell culture model of PD by conducting an experiment revealing the effects of c-Jun N-terminal kinase (JNK) on neurite degeneration induced by oxidative stress in human mesencephalic cells. This improved analysis method may be used to gain novel insight into factors underlying neurite degeneration and the progression of neurodegenerative disorders.