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

Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

1.9K
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...
1.9K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.4K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.4K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

6.3K
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...
6.3K
Diffusion01:12

Diffusion

232.0K
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...
232.0K
Diffusion01:21

Diffusion

7.4K
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...
7.4K
Poisson's And Laplace's Equation01:25

Poisson's And Laplace's Equation

4.6K
The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
4.6K

You might also read

Related Articles

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

Sort by
Same author

Time-lapse in vivo dynamics of human corneal immune cells reveals a density-diffusivity relationship.

The ocular surface·2026
Same author

Optimal experiment design for practical parameter identifiability and model discrimination.

Mathematical biosciences·2026
Same author

Likelihood-free parameter inference for spatiotemporal stochastic biological models using neural posterior estimation.

Journal of theoretical biology·2026
Same author

Modeling Collective Cell Migration in a Data-Rich Age: Challenges and Opportunities for Data-Driven Modeling.

Cold Spring Harbor perspectives in biology·2026
Same author

A likelihood-based Bayesian inference framework for the calibration of and selection between stochastic velocity-jump models.

Journal of the Royal Society, Interface·2026
Same author

Continuum models describing probabilistic motion of tagged agents in exclusion processes.

Physical review. E·2026
Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
See all related articles

Related Experiment Video

Updated: Apr 12, 2026

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

9.2K

Survival probability for a diffusive process on a growing domain.

Matthew J Simpson1,2, Jesse A Sharp1, Ruth E Baker3

  • 1School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 15, 2015
PubMed
Summary
This summary is machine-generated.

Domain growth enables diffusive populations to survive, unlike in non-growing scenarios. This study provides tools to distinguish survival based on population movement and boundary interaction in developmental biology.

More Related Videos

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

8.6K
Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy
12:06

Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy

Published on: February 1, 2017

11.7K

Related Experiment Videos

Last Updated: Apr 12, 2026

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

9.2K
Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

8.6K
Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy
12:06

Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy

Published on: February 1, 2017

11.7K

Area of Science:

  • Mathematical Biology
  • Developmental Biology
  • Population Dynamics

Background:

  • Diffusive populations on growing domains are relevant to developmental biology.
  • Understanding population survival probability is crucial for these scenarios.

Purpose of the Study:

  • To analyze the motion of a diffusive population on a growing domain.
  • To derive an exact solution for population density and survival probability.
  • To distinguish between population survival and extinction based on domain growth.

Main Methods:

  • Solving a partial differential equation for population density.
  • Deriving an exact expression for survival probability.
  • Implementing a discrete stochastic model for verification.

Main Results:

  • An exact solution for population density and survival probability was obtained.
  • Domain growth can lead to a positive survival probability, unlike in non-growing domains.
  • Theoretical tools were developed to differentiate between population survival and extinction.

Conclusions:

  • Domain growth significantly impacts population survival.
  • The derived methods can predict whether a diffusive population will reach a moving boundary.
  • This research has implications for understanding biological development, such as the enteric nervous system.