A Generalized Kinetic Model of the T-Cell Independent Primary Immune Response.

Abstract

A generalized kinetic model has been developed which describes the T-cell independent antibody-mediated primary immune response. Immunology is a very young science and its history is important to understand the direction of investigation of those equations which remain unsolved. The immune system itself, with all the cells, cellular products, and lymph system, is very complex, second only to the nervous system for complexity in the human body. The original theoretical kinetic model was developed by Bell in 1970. However there have been many additions to the theory since then. Dintzis has proposed a novel method for specific, quantized stimulation of the immune response, known as the immunom theory. The model that was developed in this investigation is based on the clonal selection theory and Bell's overall kinetic scheme. Dintzis's theory is merged into the Bell framework and the immunon concept is developed further with an equilibrium step dependent upon antigen concentration between the two paths the immune response can follow after target cell stimulation into proliferating cells. All of the events are modeled in terms of coupled kinetic equations which are solved by standard numerical integration methods using stiff differential equation subroutines. The new model also accounts for the characteristics of the immune response: specificity, recognition, memory, and low/high dose tolerance.

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Document Details

Document Type
Technical Report
Publication Date
May 13, 1985
Accession Number
ADA158953

Entities

People

  • R. N. Hyer

Organizations

  • United States Naval Academy

Tags

DTIC Thesaurus Topics

  • Antigens
  • Blood
  • Blood Cells
  • Cells
  • Cellular Structures
  • Computers
  • Differential Equations
  • Equations
  • Fungi
  • Immune System
  • Infectious Diseases
  • Leukocytes
  • Lymphatic System
  • Lymphocytes
  • New York
  • United States
  • United States Naval Academy

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Control Systems Engineering.
  • Oncology (Cancer Research).