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Related Experiment Video

Updated: Nov 24, 2025

Visualizing Cytoskeleton-Dependent Trafficking of Lipid-Containing Organelles in Drosophila Embryos
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Quantifying Intracellular Particle Flows by DIC Object Tracking.

Anushree R Chaphalkar1, Yash K Jawale1, Dhruv Khatri1

  • 1Division of Biology, Indian Institute of Science Education and Research, Pune, Pashan, Pune, Maharashtra, India.

Biophysical Journal
|December 28, 2020
PubMed
Summary
This summary is machine-generated.

We developed a MATLAB tool for label-free, single-particle tracking in differential interference contrast microscopy. This method accurately quantifies intracellular dynamics and measures viscosity, advancing quantitative imaging analysis.

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Area of Science:

  • Cell Biology
  • Biophysics
  • Microscopy

Background:

  • Label-free imaging, such as differential interference contrast (DIC), enables observation of unstained biological samples.
  • Quantitative analysis of time-series microscopy data requires robust image segmentation and object tracking.
  • Existing methods for DIC image segmentation have limitations in accuracy and efficiency.

Purpose of the Study:

  • To develop and validate a computational tool for precise single-particle tracking in DIC time-series microscopy.
  • To enable quantitative analysis of intracellular dynamics and microrheology using label-free imaging.
  • To provide a user-friendly graphical user interface (GUI) for mobility analysis.

Main Methods:

  • A MATLAB-based tool integrating contrast enhancement with modified Gaussian filters.
  • Automated threshold detection for image segmentation.
  • Minimal distance-based two-dimensional single-particle tracking algorithm (DICOT).

Main Results:

  • The tool accurately tracks objects in both in vitro and in vivo DIC time-series microscopy.
  • Subcellular dynamics of Caenorhabditis elegans embryos were quantified by tracking yolk granules.
  • The method accurately measured the diffusion coefficients of beads and viscosity of glycerol solutions.

Conclusions:

  • The developed computational method provides high precision for tracking intracellular dynamics.
  • The tool is effective for both intracellular mobility studies and in vitro microrheology.
  • This approach enhances quantitative analysis capabilities for label-free microscopy.