| Autor: |
Sorensen, Luke, Humenick, Adam, Poon, Sabrina S. B., Han, Myat Noe, Mahdavian, Narges S., Rowe, Matthew C., Hamnett, Ryan, Gómez-de-Mariscal, Estibaliz, Neckel, Peter H., Saito, Ayame, Mutunduwe, Keith, Glennan, Christie, Haase, Robert, McQuade, Rachel M., Foong, Jaime P. P., Brookes, Simon J. H., Kaltschmidt, Julia A., Muñoz-Barrutia, Arrate, King, Sebastian K., Veldhuis, Nicholas A. |
| Předmět: |
|
| Zdroj: |
Journal of Cell Science; Oct2024, Vol. 137 Issue 20, p1-12, 12p |
| Abstrakt: |
The enteric nervous system (ENS) consists of an extensive network of neurons and glial cells embedded within the wall of the gastrointestinal (GI) tract. Alterations in neuronal distribution and function are strongly associated with GI dysfunction. Current methods for assessing neuronal distribution suffer from undersampling, partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. We present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using two-dimensional images of GI wholemount preparations. GAT is developed in Fiji, has a user-friendly interface, and offers rapid and accurate segmentation via custom deep learning (DL)-based cell segmentation models developed using StarDist, as well as a ganglia segmentation model in deepImageJ. We apply proximal neighborbased spatial analysis to reveal differences in cellular distribution across gut regions using a public dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput, allowing rapid unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
