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Related Concept Videos

Super-resolution Fluorescence Microscopy01:37

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Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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Born Normalization for Fluorescence Optical Projection Tomography for Whole Heart Imaging
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ProDiVis: a method to normalize fluorescence signal localization in 3D specimens.

Kyle T Nguyen1, Alexandre R Sathler1, Alvaro G Estevez1,2,3

  • 1Department of Biochemistry and Biophysics, Oregon State University, Corvallis, OR, United States.

Frontiers in Cell and Developmental Biology
|October 8, 2024
PubMed
Summary

Confocal microscopy struggles with signal loss in 3D specimens. We developed ProDiVis, a free program to normalize fluorescence signals, improving 3D image interpretation and protein localization accuracy.

Keywords:
3D specimenconfocal microscopyfluorescence microscopyheatmapimage analysisimagingprotein distributionsignal normalization

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Area of Science:

  • Cell Biology
  • Microscopy
  • Bioimaging

Background:

  • Confocal microscopy faces signal attenuation in 3D specimens, impacting fluorescence intensity and depth-dependent signal detection.
  • This signal loss hinders accurate interpretation of protein distribution within complex 3D cellular structures.
  • Accurate visualization of fluorophore signals is crucial for understanding cellular processes.

Purpose of the Study:

  • To develop a computational tool for correcting depth-dependent fluorescence signal loss in confocal microscopy.
  • To improve the visualization and interpretation of differential protein localization in 3D cell clusters.
  • To provide an accessible and unbiased method for analyzing fluorescence microscopy data.

Main Methods:

  • Developed ProDiVis, a visualization program that normalizes fluorescent signals against a reference signal at each focal plane.
  • Utilized widely used fluorophores (COXI, P2X7R, β-Actin, Ki-67, DAPI) for labeling glioblastoma cell clusters.
  • Acquired Z-stack images using a laser scanning confocal microscope.

Main Results:

  • Observed significant fluorescence signal loss (up to ~70%) with increasing depth in Z-stacks.
  • ProDiVis effectively normalized apparent fluorescent signals, compensating for depth-dependent attenuation.
  • The program facilitates more accurate representation of signal location within 3D structures.

Conclusions:

  • ProDiVis addresses the challenge of signal loss in 3D confocal microscopy, enhancing image interpretation.
  • The software provides a free, accessible, and unbiased tool for analyzing fluorescence microscopy data.
  • Improved visualization aids in understanding protein disposition and cellular architecture in 3D specimens.