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

Vaccinations01:51

Vaccinations

53.0K
Overview
53.0K
Infection01:20

Infection

13.5K
When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
13.5K
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

76
Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
76
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

58
PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure...
58
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

65
The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
65
Immune Response Against Viral Pathogens01:29

Immune Response Against Viral Pathogens

2.3K
The immune system's response to viral infections is a complex and coordinated process involving natural killer (NK) cells, T cell-mediated responses, and antibody-mediated responses.
NK Cells
NK cells are a crucial part of our innate immune system, acting as the first line of defense against viral infections. These cells can recognize and kill infected cells without prior exposure to the virus, effectively slowing down the spread of infection. Additionally, NK cells produce proinflammatory...
2.3K

You might also read

Related Articles

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

Sort by
Same author

Insight Into the Heterogeneous Risks of Epidemic Burden After Relaxing Interventions by a Multi-Regional, Age-Stratified Mathematical Model.

Risk analysis : an official publication of the Society for Risk Analysis·2025
Same author

Risk aggregation considering probabilistic and consequential interactions: A general formulation with computational cost handling.

Risk analysis : an official publication of the Society for Risk Analysis·2023
Same author

Treating SARS-CoV-2 Omicron variant infection by molnupiravir for pandemic mitigation and living with the virus: a mathematical modeling study.

Scientific reports·2023
Same author

Disparities in transmission dynamics of the 2022 mpox outbreaks between Europe and Americas.

New microbes and new infections·2023
Same author

Probability of Mpox importation during the FIFA World Cup 2022 in Qatar.

Journal of infection and public health·2023
Same author

Projecting the global spread of the 2022 monkeypox outbreak considering population mobility.

Travel medicine and infectious disease·2022

Related Experiment Video

Updated: Mar 10, 2026

Generating a Reproducible Model of Mid-Gestational Maternal Immune Activation using PolyI:C to Study Susceptibility and Resilience in Offspring
09:09

Generating a Reproducible Model of Mid-Gestational Maternal Immune Activation using PolyI:C to Study Susceptibility and Resilience in Offspring

Published on: August 17, 2022

2.4K

Toward Systemic Immunization: Modeling Disinformation Propagation Dynamics With Intervention and Network-Driven Risk

Chunbing Bao1, Haoqian Xie1, Wenting Chen1

  • 1School of Management, Shandong University, Jinan, Shandong, China.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|March 9, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new model for disinformation spread on social media, accounting for individual behavior and network structure. It offers tools to combat fake news and enhance digital society resilience.

Keywords:
disinformation interventionnetwork‐driven risk managementpropagation dynamicssystem equilibrium

More Related Videos

Murine Model of Epicutaneously-Induced Immunomodulation
09:07

Murine Model of Epicutaneously-Induced Immunomodulation

Published on: June 24, 2025

608
Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination
11:07

Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination

Published on: April 29, 2015

13.8K

Related Experiment Videos

Last Updated: Mar 10, 2026

Generating a Reproducible Model of Mid-Gestational Maternal Immune Activation using PolyI:C to Study Susceptibility and Resilience in Offspring
09:09

Generating a Reproducible Model of Mid-Gestational Maternal Immune Activation using PolyI:C to Study Susceptibility and Resilience in Offspring

Published on: August 17, 2022

2.4K
Murine Model of Epicutaneously-Induced Immunomodulation
09:07

Murine Model of Epicutaneously-Induced Immunomodulation

Published on: June 24, 2025

608
Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination
11:07

Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination

Published on: April 29, 2015

13.8K

Area of Science:

  • Computational Social Science
  • Network Science
  • Behavioral Economics

Background:

  • Disinformation on social media threatens digital societies, causing cognitive distortion and public crises.
  • Existing models fail to capture individual heterogeneity, complete rationality assumptions, or cross-scale risk coupling.

Purpose of the Study:

  • To propose a novel disinformation propagation model integrating individual dynamics, network topology, and intervention analytics.
  • To develop a theoretical framework for a disinformation immune system and provide quantifiable decision-making tools for digital governance.

Main Methods:

  • Constructed a network propagation model incorporating risk perception, decision sensitivity, and cognitive inertia.
  • Developed a dual-index system for identifying superspreaders based on risk exposure and vulnerability.
  • Formulated an intervention model combining cognitive correction and propagation suppression, analyzing equilibrium and convergence.

Main Results:

  • Proved equilibrium existence in the nonintervention model and derived conditions for unique convergence under interventions.
  • Established the bounded intervention efficacy theorem and derived lower bounds on convergence time.
  • Quantified the joint modulation of systemic risks by individual heterogeneity and intervention intensity.

Conclusions:

  • The proposed model offers a comprehensive framework for understanding and mitigating disinformation propagation.
  • Findings provide quantifiable tools for digital governance, enhancing resilience against systemic risks posed by fake news.