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

Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

4.3K
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...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Laterally Distorted 1,2-Dibora-4-gallatacyclopentane Anion.

Inorganic chemistry·2025
Same author

Combining Inflammation and Tissue Turnover in the Modeling of Atherosclerosis Development Following the Outside-In Disease Approach.

International journal for numerical methods in biomedical engineering·2025
Same author

In Situ X-Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C-SiC Composites Fabricated by Liquid Silicon Infiltration.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

Biofilm development of <i>Porphyromonas gingivalis</i> on titanium surfaces in response to 1,4-dihydroxy-2-naphthoic acid-a hybrid <i>in vitro</i>-<i>in silico</i> approach.

Microbiology spectrum·2025
Same author

A diffusion-driven phase-field model for simulation of glioma growth.

Computer methods in biomechanics and biomedical engineering·2025
Same author

Characterization and modeling of additively manufactured Ti-6Al-4V alloy with modified surfaces for medical applications.

Frontiers in bioengineering and biotechnology·2025

Related Experiment Video

Updated: Jun 11, 2025

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity
09:21

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity

Published on: March 11, 2015

10.0K

A Hamilton principle-based model for diffusion-driven biofilm growth.

Felix Klempt1, Meisam Soleimani2, Peter Wriggers2

  • 1Institue of Continuum Mechanics, Leibniz University Hannover, An der Universität 1, 30823, Garbsen, Lower Saxony, Germany. klempt@ikm.uni-hannover.de.

Biomechanics and Modeling in Mechanobiology
|September 30, 2024
PubMed
Summary

This study introduces a new in silico model for simulating bacterial biofilm growth by combining volumetric and density-based approaches. This innovative method accurately captures biofilm stresses and mass changes, offering a more comprehensive understanding of these complex microbial communities.

Keywords:
BiofilmFinite Element SimulationGrowthHamilton principleMulti-physics

More Related Videos

Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales
12:32

Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales

Published on: November 25, 2020

6.4K
A Microfluidic Platform to Study Bioclogging in Porous Media
05:10

A Microfluidic Platform to Study Bioclogging in Porous Media

Published on: October 13, 2022

1.9K

Related Experiment Videos

Last Updated: Jun 11, 2025

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity
09:21

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity

Published on: March 11, 2015

10.0K
Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales
12:32

Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales

Published on: November 25, 2020

6.4K
A Microfluidic Platform to Study Bioclogging in Porous Media
05:10

A Microfluidic Platform to Study Bioclogging in Porous Media

Published on: October 13, 2022

1.9K

Area of Science:

  • Microbiology and Computational Biology
  • Biophysics and Mathematical Modeling

Background:

  • Bacterial biofilms are ubiquitous, playing crucial roles both beneficially and harmfully in human health and the environment.
  • Understanding biofilm dynamics is vital, but experimental methods (in vitro/in vivo) are often time-consuming and costly.
  • Existing in silico models, such as volumetric and density-based approaches, have limitations in fully capturing biofilm behavior.

Purpose of the Study:

  • To develop and present a novel in silico model for simulating bacterial biofilm growth.
  • To combine the strengths of volumetric and density-based modeling approaches.
  • To create a model that inherently satisfies thermodynamic laws and accurately represents biofilm stresses and mass addition.

Main Methods:

  • A new in silico model was derived based on Hamilton's principle, integrating volumetric and density-based simulation strategies.
  • The model was validated through selected numerical experiments to assess its behavior and predictive capabilities.
  • Thermodynamic consistency (first and second laws) was automatically ensured by the model's derivation.

Main Results:

  • The proposed model successfully captures internal stresses within biofilms while accounting for mass addition during growth.
  • Numerical experiments demonstrated good phenomenological agreement with expected biofilm growth patterns.
  • The model exhibited stable numerical behavior, enabling the solution of complex boundary value problems and adaptability to various biofilm types via parameter adjustments.

Conclusions:

  • The combined in silico model offers a robust and thermodynamically consistent approach to simulating bacterial biofilm growth.
  • This new model overcomes limitations of previous methods, providing a more accurate and versatile tool for biofilm research.
  • The model's reactivity to input parameters allows for the simulation of diverse biofilm behaviors without altering the core model structure.