Quantitative Assessment of Pancreatic Islets Using Laser Scanning Cytometry
Insulin-dependent (type II) diabetes is characterized by an inability to metabolize glucose, resulting from insufficient insulin function for glucose transport from the blood to tissues. One cause of insufficiency is malfunction of the insulin-producing beta cells within the pancreatic islets. Various compounds to stimulate and restore normal islet function are under development. Zucker diabetic fatty (ZDF) rat animal models are used to measure efficacy of drug candidates, as they show clinical effects similar to those in diabetic patients. Drug effects are evaluated by removing the pancreas from ZDF rats, processing the tissue with paraffin and sectioning it, and then analyzing the sections utilizing antibodies against targeted proteins to quantify morphology and metabolic activity. This protocol describes quantitative analysis of insulin, glucagon, mitochondria (all on a per-islet basis), and insulin-positive proliferating cells in ZDF and lean rat pancreatic tissue sections using the iCyte Imaging Cytometer. Curr. Protoc. Cytom. 56:6.32.1-6.32.17. © 2011 by John Wiley & Sons, Inc.
Keywords: imaging cytometry; laser scanning cytometry; multi-parameter tissue analysis; pancreatic islets biomarkers
Table of Contents
- Basic Protocol: Automated Multi-Parameter Staining of Beta and Alpha Islet Cells for Quantitative Analysis
- Support Protocol 1: Image Acquisition
- Support Protocol 2: Image Analysis
- Support Protocol 3: Data Analysis
- Literature Cited
Basic Protocol: Automated Multi-Parameter Staining of Beta and Alpha Islet Cells for Quantitative Analysis
Figure 6.32.1 Structure of the pancreas (http://www.nanotechgalaxy.com).
Figure 6.32.2 Four-laser iCyte Automated Imaging Cytometer.
Figure 6.32.3 LSC scan system and representative images.
Figure 6.32.4 Combination of high-resolution images into CompuColor mosaic images.
Figure 6.32.5 Low- and high-resolution images.
Figure 6.32.6 DAPI and AF532 compensated out of the green PMT.
Figure 6.32.7 Four different event-based components for identifying different cell types.
Figure 6.32.8 Peripheral contours allow measurement of expression outside the event contour.
Figure 6.32.9 Random sampling elements for extracting quantitative data from the samples independent of event-based segmentation.
Figure 6.32.12 Relating gated subpopulations to the image data.
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