Work

Automated high-throughput, high-content imaging of intact pancreatic islets

Year: 2023

Type: article

Abstract: Herein, we describe an improved 384-well method for automated high-content fluorescence imaging of multiple intact murine islets per-well with single-cell resolution and an analysis pipeline for image cytometric detection of nascent/proliferating beta-cells. Technological advancements in high-content imaging hardware allow for two-pass imaging involving low-magnification islet identification followed by high-resolution imaging of each individual islet. This two-pass imaging method coupled with serial 2D maximum intensity projection (MIP) imaging reduces the number of images needed per islet, reduces data size, speeds acquisition/analysis, and alleviates the need for true 3D image analysis that remains a technological barrier for most screening centers. By retaining the 3D structure, we are able to extract the cell populations and their spatial organization within each islet.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.7864551

Authors: McCarty, Sean, Sexton, Jonathan

Institution: University of Michigan

Language: English

Topic: Pancreatic function and diabetes

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institutes of Health