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Mathematical Model to Predict Polyclonal T-Cell-Dependent Antibody Synthesis Responses

Author

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  • Jagdish S. Thakur

    (Cellular Immunotherapy and Bone Marrow Transplant Programs, Department of Medicine, Division of Hematology/Oncology, University of Virginia, Charlottesville, VA 22903, USA)

  • Archana Thakur

    (Cellular Immunotherapy and Bone Marrow Transplant Programs, Department of Medicine, Division of Hematology/Oncology, University of Virginia, Charlottesville, VA 22903, USA)

  • Lawrence G. Lum

    (Cellular Immunotherapy and Bone Marrow Transplant Programs, Department of Medicine, Division of Hematology/Oncology, University of Virginia, Charlottesville, VA 22903, USA)

Abstract

Mathematical models are becoming indispensable tools to explore the complexities of biological systems at cellular levels. We present a model to explore the baseline immune cell interactions for in vitro polyclonal antibody synthesis via B-cells regulated by helper and regulatory T-cells. The model incorporates interactions of antigen-presenting cells, T-cells, regulatory T-cells, and B-cells with each other and predicts time-dependent trajectories of these cells and antibody synthesis stimulated by pokeweed mitogen. We used an ordinary differential equation-based approach to simulate the dynamic changes in the cells and cytokines numbers due to the cellular and humoral response to pokeweed mitogen stimulation. The parameters of the ordinary differential equations model are determined to yield a normal immune response as observed in the pokeweed mitogen-stimulated in vitro antibody synthesis via normal T, B, and antigen-presenting cells. The dose effects of antigen load and basal values of regulatory T-cells on the profiles of various immune response variables are also evaluated.

Suggested Citation

  • Jagdish S. Thakur & Archana Thakur & Lawrence G. Lum, 2023. "Mathematical Model to Predict Polyclonal T-Cell-Dependent Antibody Synthesis Responses," Mathematics, MDPI, vol. 11(18), pages 1-19, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:4017-:d:1244984
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    References listed on IDEAS

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    1. Hongwei Shao & Tao Peng & Zhiwei Ji & Jing Su & Xiaobo Zhou, 2013. "Systematically Studying Kinase Inhibitor Induced Signaling Network Signatures by Integrating Both Therapeutic and Side Effects," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-16, December.
    2. Yang, Xuehua & Wu, Lijiao & Zhang, Haixiang, 2023. "A space-time spectral order sinc-collocation method for the fourth-order nonlocal heat model arising in viscoelasticity," Applied Mathematics and Computation, Elsevier, vol. 457(C).
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