A predictive model of the distribution of T-cell phenotype variations
Issued Date
2024-01-01
Resource Type
Scopus ID
2-s2.0-85202598586
Journal Title
INES 2024 - 28th IEEE International Conference on Intelligent Engineering Systems 2024, Proceedings
Start Page
15
End Page
19
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SCOPUS
Bibliographic Citation
INES 2024 - 28th IEEE International Conference on Intelligent Engineering Systems 2024, Proceedings (2024) , 15-19
Suggested Citation
D'Orsi L., Presti E.L., Giacopelli G., De Gaetano A. A predictive model of the distribution of T-cell phenotype variations. INES 2024 - 28th IEEE International Conference on Intelligent Engineering Systems 2024, Proceedings (2024) , 15-19. 19. doi:10.1109/INES63318.2024.10629116 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100946
Title
A predictive model of the distribution of T-cell phenotype variations
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Author's Affiliation
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Abstract
Understanding the initiation and evolution of the immune response is of fundamental importance for a rational approach to infectious and autoimmune diseases. Flow cytometry now allows the sequential study of sub-populations of T-lymphocytes, where samples of cells undergo phenotype modifications induced by initial contact with the antigen. Such phenotype changes, reflecting the transition from Naive to Effector to Memory cells, consist among others in a continuing reduction in expression of the CD27 surface antigen, accompanied by an initial reduction followed by an increment of the expression of CD45RA, also a surface antigen. The present work is the first attempt to formalize the evolution of this population of immune cells by means of a mathematical model describing the movement of clusters of T-cells over the plane defined by the (log) concentrations of CD27 and CD45RA, as measured on each cell by modern flow cytometry. Eventual estimation of the parameters of such a movement model in a given subject will help caregivers to better classify the current state and the likely progression of disease.