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Mathematical modeling of the immune system recognition to mammary carcinoma antigen

The definition of artificial immunity, realized through vaccinations, is nowadays a practice widely developed in order to eliminate cancer disease. The present paper deals with an improved version of a mathematical model recently analyzed and related to the competition between immune system cells an...

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Detalles Bibliográficos
Autores principales: Bianca, Carlo, Chiacchio, Ferdinando, Pappalardo, Francesco, Pennisi, Marzio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521211/
https://www.ncbi.nlm.nih.gov/pubmed/23281916
http://dx.doi.org/10.1186/1471-2105-13-S17-S21
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author Bianca, Carlo
Chiacchio, Ferdinando
Pappalardo, Francesco
Pennisi, Marzio
author_facet Bianca, Carlo
Chiacchio, Ferdinando
Pappalardo, Francesco
Pennisi, Marzio
author_sort Bianca, Carlo
collection PubMed
description The definition of artificial immunity, realized through vaccinations, is nowadays a practice widely developed in order to eliminate cancer disease. The present paper deals with an improved version of a mathematical model recently analyzed and related to the competition between immune system cells and mammary carcinoma cells under the action of a vaccine (Triplex). The model describes in detail both the humoral and cellular response of the immune system to the tumor associate antigen and the recognition process between B cells, T cells and antigen presenting cells. The control of the tumor cells growth occurs through the definition of different vaccine protocols. The performed numerical simulations of the model are in agreement with in vivo experiments on transgenic mice.
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spelling pubmed-35212112012-12-14 Mathematical modeling of the immune system recognition to mammary carcinoma antigen Bianca, Carlo Chiacchio, Ferdinando Pappalardo, Francesco Pennisi, Marzio BMC Bioinformatics Proceedings The definition of artificial immunity, realized through vaccinations, is nowadays a practice widely developed in order to eliminate cancer disease. The present paper deals with an improved version of a mathematical model recently analyzed and related to the competition between immune system cells and mammary carcinoma cells under the action of a vaccine (Triplex). The model describes in detail both the humoral and cellular response of the immune system to the tumor associate antigen and the recognition process between B cells, T cells and antigen presenting cells. The control of the tumor cells growth occurs through the definition of different vaccine protocols. The performed numerical simulations of the model are in agreement with in vivo experiments on transgenic mice. BioMed Central 2012-12-07 /pmc/articles/PMC3521211/ /pubmed/23281916 http://dx.doi.org/10.1186/1471-2105-13-S17-S21 Text en Copyright ©2012 Bianca et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Bianca, Carlo
Chiacchio, Ferdinando
Pappalardo, Francesco
Pennisi, Marzio
Mathematical modeling of the immune system recognition to mammary carcinoma antigen
title Mathematical modeling of the immune system recognition to mammary carcinoma antigen
title_full Mathematical modeling of the immune system recognition to mammary carcinoma antigen
title_fullStr Mathematical modeling of the immune system recognition to mammary carcinoma antigen
title_full_unstemmed Mathematical modeling of the immune system recognition to mammary carcinoma antigen
title_short Mathematical modeling of the immune system recognition to mammary carcinoma antigen
title_sort mathematical modeling of the immune system recognition to mammary carcinoma antigen
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521211/
https://www.ncbi.nlm.nih.gov/pubmed/23281916
http://dx.doi.org/10.1186/1471-2105-13-S17-S21
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