AxonQuant: A Microfluidic Chamber Culture-Coupled Algorithm That Allows High-Throughput Quantification of Axonal Damage.

ABSTRACT: Published methods for imaging and quantitatively analyzing morphological changes in neuronal axons have serious limitations because of their small sample sizes, and their time-consuming and nonobjective nature. Here we present an improved microfluidic chamber design suitable for fast and high-throughput imaging of neuronal axons. We developed the AxonQuant algorithm, which is suitable for automatic processing of axonal imaging data. This microfluidic chamber-coupled algorithm allows calculation of an 'axonal continuity index' that quantitatively measures axonal health status in a manner independent of neuronal or axonal density. This method allows quantitative analysis of axonal morphology in an automatic and nonbiased manner. Our method will facilitate large-scale high-throughput screenin

SUBMITTER: Li Y 

PROVIDER: S-EPMC4148468 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature