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Related Concept Videos

Membrane Fluidity01:26

Membrane Fluidity

Membrane fluidity is explained by the fluid mosaic model of the cell membrane, which describes the plasma membrane structure as a mosaic of components—including phospholipids, cholesterol, proteins, and carbohydrates—that gives the membrane a fluid character.
Mosaic nature of the membrane
The mosaic characteristic of the membrane helps the plasma membrane remain fluid. The integral proteins and lipids exist as separate but loosely-attached molecules in the membrane. The membrane is a relatively...
Membrane Fluidity01:23

Membrane Fluidity

Cell membranes are composed of phospholipids, proteins, and carbohydrates loosely attached to one another through chemical interactions. Molecules are generally able to move about in the plane of the membrane, giving the membrane its flexible nature called fluidity. Two other features of the membrane contribute to membrane fluidity: the chemical structure of the phospholipids and the presence of cholesterol in the membrane.Fatty acids tails of phospholipids can be either saturated or...

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Related Experiment Video

Updated: Jun 18, 2026

Neutron Spin Echo Spectroscopy as a Unique Probe for Lipid Membrane Dynamics and Membrane-Protein Interactions
10:02

Neutron Spin Echo Spectroscopy as a Unique Probe for Lipid Membrane Dynamics and Membrane-Protein Interactions

Published on: May 27, 2021

Image correlation spectroscopy to define membrane dynamics.

Jeremy Bonor1, Anja Nohe

  • 1Department of Biological Sciences, University of Delaware, Newark, DE, USA.

Methods in Molecular Biology (Clifton, N.J.)
|December 4, 2009
PubMed
Summary
This summary is machine-generated.

Image correlation spectroscopy techniques visualize protein dynamics and aggregation on cell membranes. These methods, including image correlation spectroscopy, image cross-correlation spectroscopy, and dynamic image correlation spectroscopy, offer insights into cellular communication.

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Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)
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Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)

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Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics
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Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

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Related Experiment Videos

Last Updated: Jun 18, 2026

Neutron Spin Echo Spectroscopy as a Unique Probe for Lipid Membrane Dynamics and Membrane-Protein Interactions
10:02

Neutron Spin Echo Spectroscopy as a Unique Probe for Lipid Membrane Dynamics and Membrane-Protein Interactions

Published on: May 27, 2021

Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)
10:59

Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)

Published on: April 6, 2012

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics
13:30

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

Published on: February 18, 2022

Area of Science:

  • Cell Biology
  • Biophysics
  • Microscopy

Background:

  • Fluorescent imaging is crucial for studying protein dynamics and membrane domains.
  • Caveolae and clathrin-coated pits are vital for cell communication and signaling.
  • Image correlation spectroscopy (FICS) methods analyze protein aggregation and dynamics on the plasma membrane.

Purpose of the Study:

  • To detail the applications of image correlation spectroscopy (FICS) techniques.
  • To explain how FICS methods analyze protein aggregation, clustering, and dynamics.
  • To highlight the utility of FICS in studying cellular structures like caveolae and clathrin-coated pits.

Main Methods:

  • Focus on image correlation spectroscopy (ICS), image cross-correlation spectroscopy (ICCS), and dynamic image correlation spectroscopy (DICS).
  • ICS quantifies cluster density and protein aggregation degree.
  • ICCS measures protein colocalization.
  • DICS analyzes protein aggregate dynamics during live-cell imaging.

Main Results:

  • ICS provides data on the average number of clusters per unit area.
  • ICCS effectively measures the colocalization of specific proteins.
  • DICS enables the analysis of protein aggregate dynamics in real-time (milliseconds to seconds).

Conclusions:

  • FICS techniques are powerful tools for investigating protein behavior at the plasma membrane.
  • These methods enhance the understanding of cellular communication and signaling pathways.
  • FICS provides quantitative insights into protein aggregation, colocalization, and dynamics.