Zirmi

Zirmi automates quantitative image analysis to measure reactive oxygen species (ROS) levels and macrophage recruitment kinetics in vivo following tissue injury.

Key Features:

• Real-time quantitative analysis: Detects and quantifies macrophage behavior and ROS content from fluorescent probes to track recruitment kinetics after tissue injury.
• Customizable algorithm parameters: Accepts user-defined algorithm parameters for tailored quantitative measures and visualization checks of time-based changes in cellular kinetics and ROS levels.
• Integration with PhagoSight: Incorporates PhagoSight's automated keyhole cell tracking capabilities for cell tracking and trajectory analysis.
• High execution speed: Processes images up to 10 times faster than manual image-based approaches.
• Automated segmentation accuracy: Employs segmentation methods achieving a DICE Similarity coefficient greater than 0.70.

Scientific Applications:

• Macrophage kinetics after tissue injury: Quantifies time-resolved macrophage recruitment and behavior in vivo using time-lapse fluorescence imaging.
• Oxidative stress measurement: Measures ROS content from fluorescent probes to analyze in vivo oxidative stress responses.
• Zebrafish regeneration and immunology studies: Provides space- and time-based quantitative measures applicable to zebrafish models of tissue injury and regeneration.

Methodology:

Image analysis pipeline integrating user-defined parameters, automated segmentation (DICE > 0.70), use of fluorescent-probe-based ROS quantification, and incorporation of PhagoSight automated keyhole cell tracking to analyze time-based changes in cellular kinetics and ROS content; reported execution up to 10× faster than manual analysis.