Jove
Visualize
Contact Us

Related Concept Videos

Viral Recombination00:57

Viral Recombination

24.0K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
24.0K
Immunological Memory01:23

Immunological Memory

10.6K
Immunological memory, a pivotal pillar of the adaptive immune system, is responsible for the body's ability to remember and respond more swiftly and effectively to previously encountered pathogens. This remarkable feature is what makes vaccines so effective in preventing diseases.
What is Immunological Memory?
Immunological memory is an integral function of the immune system that allows it to recognize and react more rapidly and effectively to pathogens previously encountered. This feature...
10.6K
Cross-reactivity00:42

Cross-reactivity

31.8K
Overview
31.8K
Cell-mediated Immune Responses01:40

Cell-mediated Immune Responses

76.1K
Overview
76.1K
Immune Response Against Viral Pathogens01:29

Immune Response Against Viral Pathogens

1.1K
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...
1.1K
Development of Immunocompetence01:22

Development of Immunocompetence

516
The initiation of cell-mediated immunity can be observed as early as the third month of fetal growth, with active antibody-mediated immunity following approximately one month later.
The initial cells that migrate from the fetal thymus settle within the skin and epithelial tissues lining the mouth, digestive tract, and in females, the uterus and vagina. These cells, including skin-based dendritic cells, serve as antigen-presenting cells, playing a key role in T cell activation.
Subsequent T...
516

You might also read

Related Articles

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

Sort by
Same author

Genome wide association study of vaginal microbiota genetic diversity in French women.

Open research Europe·2026
Same author

Resource landscape shapes the composition and stability of the human vaginal microbiota.

PLoS biology·2026
Same author

SARS-CoV-2 epidemiology, kinetics, and evolution: A narrative review.

Virulence·2025
Same author

Factors shaping vaginal microbiota long-term community dynamics in young adult women.

Peer community journal·2025
Same author

Viral and immune dynamics of genital human papillomavirus infections in young women with high temporal resolution.

PLoS biology·2025
Same author

Resource landscape shapes the composition and stability of the human vaginal microbiota.

bioRxiv : the preprint server for biology·2024
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 Experiment Video

Updated: Oct 20, 2025

Contact-Free Co-Culture Model for the Study of Innate Immune Cell Activation During Respiratory Virus Infection
07:36

Contact-Free Co-Culture Model for the Study of Innate Immune Cell Activation During Respiratory Virus Infection

Published on: February 28, 2021

3.1K

Reconstructing contact network structure and cross-immunity patterns from multiple infection histories.

Christian Selinger1, Samuel Alizon1

  • 1MIVEGEC, Univ. Montpellier, CNRS, IRD, Montpellier, France.

Plos Computational Biology
|September 15, 2021
PubMed
Summary

Understanding disease spread requires knowing contact patterns, which are hard to track. This study shows how analyzing multiple infections in individuals over time can reveal population networks and pathogen interactions.

More Related Videos

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays
06:03

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays

Published on: September 20, 2024

1.5K
Ex Vivo Infection of Human Lymphoid Tissue and Female Genital Mucosa with Human Immunodeficiency Virus 1 and Histoculture
11:14

Ex Vivo Infection of Human Lymphoid Tissue and Female Genital Mucosa with Human Immunodeficiency Virus 1 and Histoculture

Published on: October 12, 2018

9.3K

Related Experiment Videos

Last Updated: Oct 20, 2025

Contact-Free Co-Culture Model for the Study of Innate Immune Cell Activation During Respiratory Virus Infection
07:36

Contact-Free Co-Culture Model for the Study of Innate Immune Cell Activation During Respiratory Virus Infection

Published on: February 28, 2021

3.1K
Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays
06:03

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays

Published on: September 20, 2024

1.5K
Ex Vivo Infection of Human Lymphoid Tissue and Female Genital Mucosa with Human Immunodeficiency Virus 1 and Histoculture
11:14

Ex Vivo Infection of Human Lymphoid Tissue and Female Genital Mucosa with Human Immunodeficiency Virus 1 and Histoculture

Published on: October 12, 2018

9.3K

Area of Science:

  • Epidemiology
  • Network Science
  • Computational Biology

Background:

  • Contact patterns are crucial for infectious disease spread but challenging to measure directly.
  • Longitudinal data on multiple infections within individuals offer a potential indirect method to study these patterns.

Purpose of the Study:

  • To develop and validate a method for inferring population contact networks and pathogen interactions from multiple infection histories.
  • To assess the feasibility of using simulation and analysis of individual infection time series to understand disease transmission dynamics.

Main Methods:

  • Developed an agent-based epidemic simulator incorporating multiple infections on networks.
  • Introduced similarity metrics based on host multiple infection histories to analyze individual infection time series.
  • Analyzed simulation outputs to correlate infection patterns with network properties and immunological interference.

Main Results:

  • Multiple infection summary statistics can successfully recover network properties like degree distribution, depending on infection multiplicity and sampling.
  • Identified patterns in multiple infections that indicate immunological interference between pathogens.
  • Demonstrated the link between past infections and future infection probabilities in hosts.

Conclusions:

  • Inferring transmission networks and immunological interference from longitudinal cohort data is feasible using individual-based simulations and multiple infection history analysis.
  • This approach offers a promising new avenue for understanding infectious disease dynamics and host-pathogen interactions.
  • Highlights the value of detailed longitudinal infection data in epidemiological research.