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.