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Related Concept Videos

T Cell Types and Functions01:24

T Cell Types and Functions

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When T cells with CD4 markers are activated, they give rise to two types of effector cells: helper T cells and regulatory T cells. Meanwhile, T cells with CD8 markers differentiate into effector cytotoxic T cells. The differentiation of CD4 T cells into helper T cell subsets, such as Th1, Th2, and Th17 cells, is dependent on the antigen type, antigen-presenting cell, and regulatory cytokines.
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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.
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Immune Response Against Viral Pathogens01:29

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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.
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Related Experiment Video

Updated: Aug 13, 2025

Isolation and Th17 Differentiation of Na&#239;ve CD4 T Lymphocytes
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CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe

Mariana Esther Martinez-Sánchez1, José Alberto Choreño-Parra2, Elena R Álvarez-Buylla3,4

  • 1Laboratory of Computational Biology, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City CP 14080, Mexico.

Pathogens (Basel, Switzerland)
|January 21, 2023
PubMed
Summary
This summary is machine-generated.

This study models COVID-19 immune responses, revealing decreased Th1 cells and increased regulatory/exhausted T cells with disease severity. Inhibiting SOCS1 shows promise for restoring antiviral immunity with minimal side effects.

Keywords:
Boolean modelCD4+ T cellCOVID-19Th1Th17Tregcytokinesimmune responseregulatory modelsimulation study

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Area of Science:

  • Immunology
  • Computational Biology
  • Systems Biology

Background:

  • COVID-19 is associated with lymphopenia and altered CD4+ T cell subset balance.
  • Cytokine microenvironments significantly influence T cell differentiation and function in viral infections.

Purpose of the Study:

  • To mechanistically explain COVID-19-induced lymphopenia and CD4+ T cell dysregulation using a dynamic Boolean regulatory network.
  • To identify potential therapeutic targets for restoring antiviral immunity in severe COVID-19.

Main Methods:

  • Simulated cytokine microenvironments of mild, moderate, and severe COVID-19 using a multistable Boolean regulatory network model.
  • Analyzed the impact of regulatory cytokines (TGF-β, IL-10) on T cell subset stability.
  • Identified therapeutic interventions by targeting specific pathways (IFN-γ, TGF-β, IL-10, SOCS1).

Main Results:

  • Increased disease severity correlates with decreased Th1 cells and increased Th1-like regulatory and exhausted cells.
  • Regulatory cytokines TGF-β and IL-10 destabilize Th1 cells, favoring Th17 and regulatory subsets.
  • Inhibition of SOCS1 protein emerged as a promising therapeutic strategy with fewer predicted collateral effects.

Conclusions:

  • The model provides a mechanistic basis for CD4+ T cell subset dysregulation in COVID-19.
  • Targeting SOCS1 offers a potential therapeutic avenue to enhance Th1 responses in severe COVID-19.
  • A simulation tool is available for predicting CD4+ T cell subset responses to cytokine environments and interventions.