Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

119
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
119
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

4.4K
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...
4.4K
Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

562
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...
562
Diffusion01:12

Diffusion

194.1K
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...
194.1K
Three-Compartment Open Model01:06

Three-Compartment Open Model

294
The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
294
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

5.7K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
5.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Increase maximum economic yield in a patchy environment.

Journal of mathematical biology·2024
Same journal

Discrete-time exploitative competition model of different stage-specific predators.

Journal of mathematical biology·2026
Same journal

Spatiotemporal SEIQR Epidemic Modeling with Optimal Control for Vaccination, Treatment, and Social Measures.

Journal of mathematical biology·2026
Same journal

Phenotypic plasticity trade-offs in an age-structured model of bacterial growth under stress.

Journal of mathematical biology·2026
Same journal

Intraspecific interactions facilitate mutualism across multilayer networks under weak selection.

Journal of mathematical biology·2026
Same journal

A two-species competition model on a compact metric graph for the invasion and competition of Aedes Aegypti and Aedes Albopictus mosquitoes in Florida.

Journal of mathematical biology·2026
Same journal

Superinfection and the hypnozoite reservoir for Plasmodium vivax: a multitype branching process approximation.

Journal of mathematical biology·2026
See all related articles

Related Experiment Video

Updated: Jul 27, 2025

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

8.8K

Nonlinear diffusion in multi-patch logistic model.

Bilel Elbetch1, Ali Moussaoui2

  • 1Department of Mathematics, University Dr. Moulay Tahar of Saida, Saida, Algeria.

Journal of Mathematical Biology
|June 6, 2023
PubMed
Summary
This summary is machine-generated.

This study analyzes population dynamics in a multi-patch model with nonlinear migration. It reveals how migration influences carrying capacity and total population size, impacting ecological strategies.

Keywords:
Logistic equationNonlinear diffusionPerfect mixingPopulation dynamicsSlow-fast systemsTikhonov’s theorem

More Related Videos

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
00:10

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.3K
The Diffusion of Passive Tracers in Laminar Shear Flow
08:01

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

8.6K

Related Experiment Videos

Last Updated: Jul 27, 2025

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

8.8K
Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
00:10

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.3K
The Diffusion of Passive Tracers in Laminar Shear Flow
08:01

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

8.6K

Area of Science:

  • Mathematical Biology
  • Theoretical Ecology
  • Population Dynamics

Background:

  • Investigating population dynamics in spatially structured environments is crucial for understanding ecological processes.
  • Nonlinear migration patterns can significantly alter population distribution and stability.
  • Logistic growth is a fundamental model for population self-limitation.

Purpose of the Study:

  • To analyze a multi-patch population model with nonlinear asymmetrical migration.
  • To determine the global stability of the proposed ecological model.
  • To understand how migration and fragmentation affect total population size and carrying capacity.

Main Methods:

  • Utilizing the theory of cooperative differential systems.
  • Analyzing a multi-patch model with logistic growth on each patch.
  • Investigating limiting cases of perfect mixing (infinite migration rates).

Main Results:

  • The global stability of the multi-patch model was proven.
  • In perfect mixing, total population follows a logistic law with a modified carrying capacity.
  • Conditions were established for fragmentation and nonlinear migration to increase or decrease total population size relative to the sum of carrying capacities.

Conclusions:

  • Nonlinear asymmetrical migration significantly impacts population dynamics and carrying capacity.
  • Fragmentation and migration can be manipulated to alter total population size.
  • For two-patch systems, nonlinear dispersal's benefit or detriment to carrying capacity can be classified based on model parameters.