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Related Concept Videos

T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

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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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Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
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Related Experiment Video

Updated: Jun 18, 2025

A TIRF Microscopy Technique for Real-time, Simultaneous Imaging of the TCR and its Associated Signaling Proteins
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Mathematical models of TCR initial triggering.

Jiawei Shi1,2, Weiwei Yin1,3, Wei Chen1,2,4,5

  • 1Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

Frontiers in Immunology
|August 2, 2024
PubMed
Summary
This summary is machine-generated.

Mathematical models help understand T cell receptor (TCR) signaling networks. This review compares kinetic proofreading (KPR) models to identify key regulators for improved T cell responses and therapies.

Keywords:
T cell receptor (TCR)TCR modelsTCR triggeringkinetic proofreading modelmathematical model

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Area of Science:

  • Immunology
  • Computational Biology
  • Systems Biology

Background:

  • T cell receptors (TCRs) are critical for adaptive immunity, mediating antigen recognition.
  • TCR signaling involves complex molecular interactions and regulatory networks.
  • Understanding these networks is essential for immune response modulation.

Purpose of the Study:

  • To review and compare mathematical models of initial T cell receptor (TCR) triggering.
  • To focus on kinetic proofreading (KPR) models with various structural modifications.
  • To identify key regulators within TCR signaling networks.

Main Methods:

  • Introduction and discussion of relevant mathematical models for TCR triggering.
  • Comparative analysis of different modified kinetic proofreading (KPR) model structures.
  • Evaluation of model topology, biological assumptions, parameterization, and simulation performance.

Main Results:

  • Comparison of advantages and limitations of various TCR kinetic proofreading (KPR) models.
  • Summary of structural and functional differences among reviewed models.
  • Identification of key parameters and network components influencing TCR signaling.

Conclusions:

  • Mathematical modeling provides insights into complex TCR signaling pathways.
  • Optimizing TCR model design is crucial for balancing specificity and sensitivity.
  • Advancements in TCR modeling can inform the development of novel therapeutic strategies.