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

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

888
Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
888
Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

2.0K
Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
2.0K
Modeling with Differential Equations01:25

Modeling with Differential Equations

137
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
137
Teeth01:15

Teeth

2.0K
The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
2.0K
Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

468
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
468
Exponential Equations for Modeling Growth02:33

Exponential Equations for Modeling Growth

300
Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is...
300

You might also read

Related Articles

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

Sort by
Same author

Iron burden and endocrine complications in transfusion-dependent thalassemia patients In Sarawak, Malaysia: a retrospective study.

The Medical journal of Malaysia·2024
Same author

MEMO1 Is Required for Ameloblast Maturation and Functional Enamel Formation.

Journal of dental research·2023
Same author

Solubility of <i>β</i>-Ca<sub>3</sub>(PO<sub>4</sub>)<sub>2</sub> in the System Ca(OH)<sub>2</sub>-H<sub>3</sub>PO<sub>4</sub>-H<sub>2</sub>O at 5, 15, 25, and 37 °C.

Journal of research of the National Bureau of Standards. Section A, Physics and chemistry·2020
Same author

Solubility of CaHPO<sub>4</sub> · 2H<sub>2</sub>O in the Quaternary System Ca(OH)<sub>2</sub> - H<sub>3</sub>PO<sub>4</sub> - NaCl - H<sub>2</sub>O at 25 °C.

Journal of research of the National Bureau of Standards. Section A, Physics and chemistry·2020
Same author

Calculation of Diffusion Coefficients in Ternary Systems from Diaphragm Cell Experiments.

Journal of research of the National Bureau of Standards. Section A, Physics and chemistry·2020
Same author

Preparation and Solubility of Hydroxyapatite.

Journal of research of the National Bureau of Standards. Section A, Physics and chemistry·2019
Same journal

Precise Numerical Differentiation of Thermodynamic Functions with Multicomplex Variables.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

Characterization of 3-Dimensional Printing and Casting Materials for use in Computed Tomography and X-ray Imaging Phantoms.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

On The Quotient of a Centralized and a Non-centralized Complex Gaussian Random Variable.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

Fast Methods for Finding Multiple Effective Influencers in Real Networks.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

Disinfection of Respirators with Ultraviolet Radiation.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

DNA Origami Design: A How-To Tutorial.

Journal of research of the National Institute of Standards and Technology·2024
See all related articles

Related Experiment Video

Updated: Mar 7, 2026

Systematic Approach to Identify Novel Antimicrobial and Antibiofilm Molecules from Plants' Extracts and Fractions to Prevent Dental Caries
08:20

Systematic Approach to Identify Novel Antimicrobial and Antibiofilm Molecules from Plants' Extracts and Fractions to Prevent Dental Caries

Published on: March 31, 2021

7.0K

A Mathematical Model for Dental Caries: A Coupled Dissolution-Diffusion Process.

T M Gregory1, L C Chow1, C M Carey1

  • 1American Dental Association Health Foundation, Paffenbarger Research Center, National Institute of Standards and Technology, Gaithersburg, MD 20899.

Journal of Research of the National Institute of Standards and Technology
|February 11, 2017
PubMed
Summary
This summary is machine-generated.

A computer model simulating tooth demineralization shows that membrane permselectivity significantly impacts caries progression. Cation-selective membranes accelerate demineralization, while anion-selective membranes slow it down.

Keywords:
Ca fluxP fluxcomputer simulationcoupled dissolution-diffusiondental carieshydroxyapatitepermselective diffusion

More Related Videos

Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation
08:45

Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation

Published on: July 21, 2014

14.1K
Ratiometric Imaging of Extracellular pH in Dental Biofilms
13:05

Ratiometric Imaging of Extracellular pH in Dental Biofilms

Published on: March 9, 2016

10.8K

Related Experiment Videos

Last Updated: Mar 7, 2026

Systematic Approach to Identify Novel Antimicrobial and Antibiofilm Molecules from Plants' Extracts and Fractions to Prevent Dental Caries
08:20

Systematic Approach to Identify Novel Antimicrobial and Antibiofilm Molecules from Plants' Extracts and Fractions to Prevent Dental Caries

Published on: March 31, 2021

7.0K
Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation
08:45

Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation

Published on: July 21, 2014

14.1K
Ratiometric Imaging of Extracellular pH in Dental Biofilms
13:05

Ratiometric Imaging of Extracellular pH in Dental Biofilms

Published on: March 9, 2016

10.8K

Area of Science:

  • Biomineralization
  • Dental Caries Research
  • Computational Modeling

Background:

  • Dental caries involves demineralization of tooth mineral.
  • Understanding ion diffusion and dissolution is crucial for caries management.
  • Previous models did not fully account for membrane permselectivity effects.

Purpose of the Study:

  • To investigate the role of diffusion barrier permselectivity in tooth demineralization using a computer model.
  • To simulate the dynamic changes in calcium and phosphate fluxes during caries progression.
  • To determine the effect of different membrane selectivities on the rate of demineralization.

Main Methods:

  • Developed a two-compartment computer model simulating diffusion-controlled dissolution of tooth mineral.
  • Modeled an acidic plaque compartment and an inner lesion compartment with a permselective barrier.
  • Varied the cation and anion permeability of the barrier to examine its effects on ion flux and dissolution.

Main Results:

  • The model reached a steady state where calcium to phosphate flux ratio approached the mineral's ratio (5/3).
  • Lesion fluid composition significantly changed due to unequal calcium and phosphate losses.
  • Demineralization rates varied with membrane type: highest for cation-selective and lowest for anion-selective membranes at a given plaque pH.

Conclusions:

  • Membrane permselectivity is a critical factor influencing the rate of tooth demineralization.
  • The findings highlight the importance of considering ion transport dynamics in caries models.
  • Simulation results align with experimental data, validating the model's predictive capability.