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FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking.

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This study introduces FilamentSensor 2.0 (FS2.0), an automated tool for analyzing cytoskeletal dynamics. FS2.0 quantifies fibrous structures and tracks their movement in live cells, aiding biological research.

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Area of Science:

  • Cell Biology
  • Biophysics
  • Bioimaging

Background:

  • Cytoskeletal dynamics are crucial for cellular functions and homeostasis.
  • Quantitative analysis of cytoskeletal structures and dynamics provides critical insights.
  • Current methods lack robust, automated workflows for detailed cytoskeletal analysis.

Purpose of the Study:

  • To develop an automated, quantitative analysis workflow for cytoskeletal structures and dynamics.
  • To enhance existing fiber detection algorithms for improved performance.
  • To enable real-time tracking and cell event monitoring of fibrous elements.

Main Methods:

  • Upgraded and expanded the FilamentSensor (FS) algorithm to FilamentSensor 2.0 (FS2.0).
  • Implemented automatic detection and segmentation of fibrous structures.
  • Developed real-time data extraction (center of mass, length, width, orientation, curvature) and object tracking.

Main Results:

  • FS2.0 provides an unbiased, quantitative, and robust analysis workflow.
  • The toolbox allows for automatic segmentation and characterization of cytoskeletal fibers.
  • Enables frame-to-frame tracking of fibrous structures and monitoring of cellular events.

Conclusions:

  • FS2.0 offers a highly automated solution for analyzing cytoskeletal dynamics.
  • This tool facilitates detailed studies of cellular homeostasis and pathology.
  • FS2.0 advances high-content live cell imaging analysis for cytoskeletal research.