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Related Experiment Video

Updated: Nov 23, 2025

Super-Resolution Live Cell Imaging of Subcellular Structures

Super-Resolution Live Cell Imaging of Subcellular Structures

Published on: January 13, 2021

5D superresolution imaging for a live cell nucleus.

Li-An Chu¹, Shu-Wei Chang², Wei-Chun Tang²

¹Department of Biomedical Engineering and Environmental Science, National Tsing Hua University, Hsinchu, 30013, Taiwan; Brain Research Center, National Tsing Hua University, Hsinchu, 30013, Taiwan.

Current Opinion in Genetics & Development

|December 31, 2020

Summary

This summary is machine-generated.

Superresolution microscopy advances enable detailed 3D live imaging of cellular structures like the nucleus. Machine learning enhances axial resolution for better understanding of cell function and molecular interactions.

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High-resolution Imaging of Nuclear Dynamics in Live Cells under Uniaxial Tensile Strain

High-resolution Imaging of Nuclear Dynamics in Live Cells under Uniaxial Tensile Strain

Published on: June 2, 2019

Area of Science:

Cellular and Molecular Imaging
Biophysics
Microscopy Techniques

Background:

Superresolution microscopy breaks the diffraction limit, enabling visualization of subcellular structures.
Multi-dimensional (3D, live) imaging is crucial for understanding cellular dynamics and molecular interactions.
Existing 2D superresolution techniques are being expanded for 3D live imaging applications.

Purpose of the Study:

To review recent developments in superresolution microscopy for live imaging with minimal phototoxicity.
To focus on applications within the cell nucleus.
To explore the integration of machine learning for improved axial resolution.

Main Methods:

Review of current superresolution microscopy techniques for live cell imaging.
Discussion of 3D expansion of 2D superresolution methods.
Introduction of machine learning algorithms for enhancing axial resolution.

Main Results:

Superresolution microscopy provides unprecedented detail of organelles like mitochondria, cytoskeleton, and the nucleus.
3D live imaging facilitates comprehensive understanding of cellular function.
Machine learning shows promise in improving axial resolution in superresolution imaging.

Conclusions:

Superresolution microscopy is a powerful tool for dissecting cellular architecture and dynamics.
Advancements in 3D live imaging are critical for cell biology research.
Machine learning integration offers a pathway to further enhance superresolution imaging capabilities, particularly for the cell nucleus.