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The early endosome containing internalized molecules matures through transformations in its location, morphology, intraluminal pH, and membrane protein composition. Together, these changes result in a more acidic late endosome that contains multiple intraluminal vesicles; therefore, the late endosome is also called a multivesicular body (MVB).
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Essential proteins such as insulin or low-density lipoprotein (LDL) and micronutrients such as iron enter a eukaryotic cell through receptor-mediated endocytosis. Subsequently, the early endosomes fuse with the vesicles containing such receptor-ligand complexes and play a vital role in sorting the incoming ligands and receptors. While the ligands are either degraded inside the vesicle or released into the cytosol, their receptors are returned to the plasma membrane for further rounds of...
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The recycling endosome, also known as the endosomal recycling compartment (ERC), is a part of the slow-recycling process of the endocytic pathway. Molecules internalized through receptor-mediated endocytosis are either degraded in the lysosomes or are recycled to the plasma membrane through the fast- or slow-recycling route.
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Visualization of Endosome Dynamics in Living Nerve Terminals with Four-dimensional Fluorescence Imaging
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Automatic Endosomal Structure Detection And Localization in Fluorescence Microscopic Images.

Dongyun Lin1, Zhiping Lin1, Ramraj Velmurugan2

  • 1School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore.

IEEE International Symposium on Circuits and Systems Proceedings. IEEE International Symposium on Circuits and Systems
|March 26, 2019
PubMed
Summary
This summary is machine-generated.

A new method called modified spatially-constrained similarity measure (mSCSM) automatically detects and localizes endosomal structures in cells. This approach achieves 79.17% accuracy in microscopic images, advancing subcellular compartment analysis.

Keywords:
bag-of-words (BoW)endosomal structureshistogram intersectionspatially-constrained similarity measure (SCSM)

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Area of Science:

  • Cell Biology
  • Image Analysis
  • Computational Biology

Background:

  • Endosomes are crucial subcellular compartments involved in various cellular processes.
  • Accurate detection and localization of endosomes are vital for understanding cell function.
  • Current methods often lack full automation or struggle with complex subcellular structures.

Purpose of the Study:

  • To introduce a novel, fully automatic method for detecting and localizing endosomal structures.
  • To adapt the spatially-constrained similarity measure (SCSM) for category-based localization of endosomes.
  • To improve upon existing techniques for subcellular compartment analysis.

Main Methods:

  • Development of a modified spatially-constrained similarity measure (mSCSM).
  • Integration of mSCSM within the bag-of-words (BoW) framework.
  • Implementation of a novel two-stage output control scheme for enhanced localization.
  • Extraction of discriminative information from query images for similarity scoring.

Main Results:

  • The proposed mSCSM method demonstrates the first fully automatic approach for endosome detection and localization.
  • mSCSM successfully addresses category-based localization, unlike the original SCSM.
  • Preliminary experiments show a 79.17% accuracy rate in detecting and localizing endosomal structures in human myeloid endothelial cells.

Conclusions:

  • The mSCSM method offers a significant advancement in the automated analysis of subcellular structures.
  • This technique provides a robust solution for the detection and localization of endosomes in biological imaging.
  • The findings highlight the potential of mSCSM for future research in cell biology and high-throughput screening.