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Related Concept Videos

Diffusion01:12

Diffusion

Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
Diffusion01:21

Diffusion

Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this principle...
Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting their diffusion into...
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...

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Related Experiment Video

Updated: May 18, 2026

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)
12:19

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)

Published on: May 27, 2012

Locating the source of diffusion in large-scale networks.

Pedro C Pinto1, Patrick Thiran, Martin Vetterli

  • 1École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland.

Physical Review Letters
|September 26, 2012
PubMed
Summary

This study demonstrates that pinpointing diffusion sources in large networks is possible using limited observer data. An optimal strategy for trees maximizes localization accuracy, with efficient algorithms applicable to complex graphs.

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Last Updated: May 18, 2026

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)
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Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
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Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

Area of Science:

  • Network Science
  • Information Diffusion
  • Complex Systems Analysis

Background:

  • Real-world networks (e.g., internet, social graphs) are often too large to monitor all nodes.
  • Identifying the origin of diffusion processes is crucial for understanding and controlling phenomena like information spread or disease outbreaks.

Purpose of the Study:

  • To determine if diffusion source localization is fundamentally possible with sparse measurements.
  • To develop an optimal strategy for accurate source localization in complex networks.
  • To analyze the impact of network structure and observer density on localization accuracy.

Main Methods:

  • Developed a novel strategy for source localization in arbitrary trees and graphs.
  • Analyzed the computational complexity of proposed algorithms (O(N(α))).
  • Conducted case studies to evaluate localization accuracy under varying system parameters.

Main Results:

  • Demonstrated the fundamental possibility of estimating diffusion source location from sparse observations.
  • Achieved optimal localization probability for arbitrary trees.
  • Identified key system parameters influencing localization accuracy, including network topology, observer density, and cascade data.

Conclusions:

  • Sparse observation is sufficient for effective diffusion source localization in complex networks.
  • The proposed strategy offers an efficient and accurate method for identifying diffusion origins.
  • Understanding parameter influences is key to optimizing localization in real-world applications.