AdipoQ
AdipoQ provides two ImageJ plugins for automated quantitative analysis of adipocyte morphology and function in tissue sections and in vitro cell cultures.
Key Features:
- ImageJ plugin architecture: Two plugins operate within ImageJ to perform automated quantitative analyses on microscopy images.
- Adaptability to imaging modalities: Compatible with histological staining and immunofluorescent labeling across multiple imaging modalities.
- Batch processing: Supports batch processing of large image datasets for high-throughput analysis.
- Comprehensive parameter analysis: Extracts a broad spectrum of morphological and functional parameters, including metrics distinguishing white adipocytes (large unilocular lipid droplets) and brown adipocytes (small multilocular lipid droplets).
- Integration of multiple fluorescent readouts: Analyzes multi-channel fluorescent images to combine several fluorescent markers and readouts.
Scientific Applications:
- Adipose tissue research: Quantifies adipocyte morphology and function to distinguish white and brown adipose tissue and study physiological and pathological changes.
- Clinical assessment: Provides quantitative morphological data on adipocytes that can contribute to analyses relevant to metabolic disorders and adipose tissue dysfunction.
Methodology:
Two ImageJ plugins perform automated, batch-capable analyses on labeled images from cell cultures and ex vivo tissue sections, supporting histological and immunofluorescent staining and multi-channel fluorescence readouts.
Topics
Details
- License:
- GPL-3.0
- Cost:
- Free of charge
- Tool Type:
- command-line tool, plugin
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- R
- Added:
- 2/26/2023
- Last Updated:
- 2/26/2023
Operations
Publications
Sieckmann K, Winnerling N, Huebecker M, Leyendecker P, Juliana Silva Ribeiro D, Gnad T, Pfeifer A, Wachten D, Hansen JN. AdipoQ—a simple, open-source software to quantify adipocyte morphology and function in tissues and in vitro. Molecular Biology of the Cell. 2022;33(12). doi:10.1091/mbc.e21-11-0592. PMID:35947507. PMCID:PMC9635306.