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

T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

17.9K
T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...
17.9K

You might also read

Related Articles

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

Sort by
Same author

TabularQual: A spreadsheet-based format for annotating and curating logical models in SBML-qual.

bioRxiv : the preprint server for biology·2026
Same author

Benchmarking Dendritic Cell Enrichment Methods Reveals Subset-Specific Recovery Biases.

Immunology·2026
Same author

Spatial transcriptomics unveils immune cellular ecosystems associated with patient survival in diffuse large B-cell lymphoma.

Oncoimmunology·2026
Same author

A Multifaceted Interplay Among Hemophagocytosis, Interleukin-18, and Type I Interferon Distinguishes Still Disease From Other Autoinflammatory Diseases.

Arthritis & rheumatology (Hoboken, N.J.)·2026
Same author

Glial-to-mesenchymal transition of tumor Schwann cells drives the genetic burden in MPNSTs from neurofibromatosis type 1 mouse model.

Science advances·2025
Same author

High-dimensional spectral cytometry identifies follicular regulatory CD8<sup>+</sup> T cells in diffuse large B-cell lymphoma.

Clinical & translational immunology·2025

Related Experiment Video

Updated: Apr 17, 2026

An In Vivo Mouse Model to Measure Na&#239;ve CD4 T Cell Activation, Proliferation and Th1 Differentiation Induced by Bone Marrow-derived Dendritic Cells
08:39

An In Vivo Mouse Model to Measure Naïve CD4 T Cell Activation, Proliferation and Th1 Differentiation Induced by Bone Marrow-derived Dendritic Cells

Published on: August 22, 2018

20.8K

Model checking to assess T-helper cell plasticity.

Wassim Abou-Jaoudé1, Pedro T Monteiro2, Aurélien Naldi3

  • 1Institut de Biologie de l'Ecole Normale Supérieure , Paris , France ; UMR CNRS 8197 , Paris , France ; INSERM U1024 , Paris , France ; Laboratoire d'Informatique de l'Ecole Normale Supérieure , Paris , France.

Frontiers in Bioengineering and Biotechnology
|February 13, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a computational framework for analyzing cell plasticity by modeling T-helper cell differentiation. It uses symbolic model checking to understand how environmental cues reprogram cell states and explores strategies for cell polarization.

Keywords:
T-helper lymphocytecell differentiationcell plasticitylogical modelingmodel checkingsignaling networks

More Related Videos

Retroviral Transduction of Helper T Cells as a Genetic Approach to Study Mechanisms Controlling their Differentiation and Function
11:50

Retroviral Transduction of Helper T Cells as a Genetic Approach to Study Mechanisms Controlling their Differentiation and Function

Published on: November 4, 2016

11.7K
Mouse Na&#239;ve CD4+ T Cell Isolation and In vitro Differentiation into T Cell Subsets
07:12

Mouse Naïve CD4+ T Cell Isolation and In vitro Differentiation into T Cell Subsets

Published on: April 16, 2015

55.1K

Related Experiment Videos

Last Updated: Apr 17, 2026

An In Vivo Mouse Model to Measure Na&#239;ve CD4 T Cell Activation, Proliferation and Th1 Differentiation Induced by Bone Marrow-derived Dendritic Cells
08:39

An In Vivo Mouse Model to Measure Naïve CD4 T Cell Activation, Proliferation and Th1 Differentiation Induced by Bone Marrow-derived Dendritic Cells

Published on: August 22, 2018

20.8K
Retroviral Transduction of Helper T Cells as a Genetic Approach to Study Mechanisms Controlling their Differentiation and Function
11:50

Retroviral Transduction of Helper T Cells as a Genetic Approach to Study Mechanisms Controlling their Differentiation and Function

Published on: November 4, 2016

11.7K
Mouse Na&#239;ve CD4+ T Cell Isolation and In vitro Differentiation into T Cell Subsets
07:12

Mouse Naïve CD4+ T Cell Isolation and In vitro Differentiation into T Cell Subsets

Published on: April 16, 2015

55.1K

Area of Science:

  • Computational biology
  • Systems immunology
  • Cellular signaling

Background:

  • Logical modeling is effective for analyzing complex cellular networks, particularly signaling and transcriptional regulation.
  • Cellular plasticity, the ability to change differentiated states in response to environmental cues, is critical for immune responses.
  • T-helper (Th) cell differentiation is a key process in orchestrating immune responses, involving complex regulatory networks.

Purpose of the Study:

  • To present a multivalued logical framework and computational methods for analyzing large biological models.
  • To investigate cell plasticity and state switching in T-helper cell differentiation using symbolic model checking.
  • To develop strategies for targeted cell polarization and reprogramming.

Main Methods:

  • Development of a multivalued logical framework for computational modeling.
  • Application of symbolic model checking to analyze attractor switching upon changes in input conditions.
  • Extension of a published model of Th cell differentiation to include novel subtypes.
  • Analysis of reachability properties between Th subtypes under varying environmental cues.

Main Results:

  • A computational framework was developed for efficient analysis of large biological models.
  • Symbolic model checking was used to analyze T-helper cell differentiation plasticity and state transitions.
  • A graph representation of Th cell plasticity was constructed, connecting subtypes via input conditions.
  • Novel strategies for specific Th cell polarization and reprogramming were explored.

Conclusions:

  • The developed framework enables efficient analysis of complex cellular networks and cell plasticity.
  • Symbolic model checking provides insights into T-helper cell differentiation dynamics and environmental responses.
  • The study offers a synthetic view of cell plasticity and potential strategies for therapeutic interventions in immune responses.