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

Chemical Agents for Microbial Control01:27

Chemical Agents for Microbial Control

162
Chemicals play important roles in controlling microbial growth by targeting microbial structures and functions as sanitizers, antiseptics, disinfectants, and sterilants.Alcohols are commonly used sanitizers, effectively disrupting lipid membranes, which compromises cell integrity. They are also used as antiseptics and disinfectants due to their rapid action and versatility.Phenols and their derivatives phenolics , known for denaturing proteins and disrupting cell membranes, are particularly...
162
Antimicrobial Effectiveness01:28

Antimicrobial Effectiveness

128
The effectiveness of antimicrobial agents depends on various factors influencing their ability to eliminate microbial populations. Larger microbial populations require more time for complete eradication, emphasizing the importance of population size analysis when evaluating antimicrobial efficacy.Microbial resistance to antimicrobial agents varies significantly. Highly resilient microorganisms include endospores, gram-negative bacteria, and non-enveloped viruses, while prions are exceptionally...
128
Biological Methods for Microbial Control01:28

Biological Methods for Microbial Control

167
Biological agents offer an effective means of controlling microbial growth by leveraging natural processes like predation, competition, and the secretion of antimicrobial substances.Predatory bacteria such as Bdellovibrio species target and kill pathogens like Salmonella and E. coli. They are widely used in poultry farms to control infections. Myxococcus species help combat plant-pathogenic fungi. These naturally occurring predators serve as eco-friendly alternatives to chemical pesticides and...
167
Methods for Controlling Microbial Growth01:29

Methods for Controlling Microbial Growth

291
Microbial growth control refers to various methods employed to inhibit, reduce, or eliminate microorganisms to ensure safety and hygiene across different settings. These methods are categorized based on the target environment and the level of microbial control required.Biocides are versatile agents designed to control microorganisms by either inhibiting their growth or outright killing them. These agents work through various physical, chemical, mechanical, or biological mechanisms. The...
291
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

855
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
855
Surface Membrane Barriers01:18

Surface Membrane Barriers

1.3K
The skin and mucous membranes serve as the primary line of defense against pathogens by providing both physical and chemical protection. These barriers are essential in preventing the entry and establishment of microbes, thereby maintaining the integrity of the host.
The outer layer of the skin, the epidermis, is a robust barrier comprising layers of closely packed keratinized cells. This dense arrangement prevents microbes from penetrating the body. The periodic shedding of epidermal cells...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Path entropy-driven design of solid-state electrolytes.

Nature communications·2026
Same author

Supramolecular Assembly of Fused Macrocycle-Cage Molecules for Fast Lithium-Ion Transport.

Journal of the American Chemical Society·2024
Same author

Bioinspired Genetic and Chemical Engineering of Protein Hydrogels for Programable Multi-Responsive Actuation.

Advanced healthcare materials·2024
Same author

A Pseudo-Surfactant Chemical Permeation Enhancer to Treat Otitis Media via Sustained Transtympanic Delivery of Antibiotics.

Advanced healthcare materials·2024
Same author

Elucidating Interfacial Dynamics of Ti-Al Systems Using Molecular Dynamics Simulation and Markov State Modeling.

ACS applied materials & interfaces·2023
Same author

Controlling biofilm transport with porous metamaterials designed with Bayesian learning.

Journal of the mechanical behavior of biomedical materials·2023

Related Experiment Video

Updated: Aug 16, 2025

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection
10:50

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

Published on: September 27, 2016

9.8K

Computational Design of Antimicrobial Active Surfaces via Automated Bayesian Optimization.

Hanfeng Zhai1, Jingjie Yeo1

  • 1Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York14850, United States.

ACS Biomaterials Science & Engineering
|December 20, 2022
PubMed
Summary

Designing nanosurfaces with specific topographies can effectively control biofilms. This study used computational modeling to optimize surface designs for biofilm removal via shear and vibration, finding optimal geometries for different conditions.

Keywords:
Bayesian optimizationbiofilmsbiomaterialsindividual-based modelingmachine learningmicrostructure

More Related Videos

Antimicrobial Characterization of Advanced Materials for Bioengineering Applications
08:08

Antimicrobial Characterization of Advanced Materials for Bioengineering Applications

Published on: August 4, 2018

22.2K
High-throughput Identification of Bacteria Repellent Polymers for Medical Devices
10:43

High-throughput Identification of Bacteria Repellent Polymers for Medical Devices

Published on: November 5, 2016

9.2K

Related Experiment Videos

Last Updated: Aug 16, 2025

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection
10:50

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

Published on: September 27, 2016

9.8K
Antimicrobial Characterization of Advanced Materials for Bioengineering Applications
08:08

Antimicrobial Characterization of Advanced Materials for Bioengineering Applications

Published on: August 4, 2018

22.2K
High-throughput Identification of Bacteria Repellent Polymers for Medical Devices
10:43

High-throughput Identification of Bacteria Repellent Polymers for Medical Devices

Published on: November 5, 2016

9.2K

Area of Science:

  • Materials Science
  • Biotechnology
  • Surface Engineering

Background:

  • Biofilms present significant challenges across marine science, bioenergy, and biomedicine.
  • Effective biofilm control relies heavily on understanding adhesion and surface mechanics.
  • Current methods for biofilm removal and control are often insufficient for long-term applications.

Purpose of the Study:

  • To develop a computational framework for rapidly designing customized nanosurfaces for enhanced biofilm removal.
  • To identify optimal surface topologies and mechanical stimuli for preventing and removing biofilms.
  • To provide insights for engineering applications requiring surface-mediated biofilm control.

Main Methods:

  • Utilized individual-based modeling and Bayesian optimization to automate nanosurface design.
  • Simulated biofilm interactions with various surface topographies under different mechanical stresses (shear and vibration).
  • Optimized surface geometries and vibrational parameters for maximum biofilm removal efficiency.

Main Results:

  • Identified optimal nanosurface topographies for biofilm control under different conditions.
  • Densely packed short pillars are optimal for preventing biofilm formation.
  • Sparsely distributed tall, slim pillars are optimal for shear-induced removal.
  • Thick trapezoidal cones are optimal for vibration-induced removal, with low magnitude and frequency vibrations being most efficient.

Conclusions:

  • Computational design frameworks can accelerate the development of effective anti-biofilm surfaces.
  • Tailoring nanosurface topography and applying mechanical stimuli are key strategies for biofilm control.
  • The findings offer practical guidance for diverse engineering fields and general materials design.