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Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system

Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally dissemina...

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Autores principales: Pappalardo, Francesco, Russo, Giulia, Corsini, Emanuela, Paini, Alicia, Worth, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035946/
https://www.ncbi.nlm.nih.gov/pubmed/35495116
http://dx.doi.org/10.1016/j.csbj.2022.03.024
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author Pappalardo, Francesco
Russo, Giulia
Corsini, Emanuela
Paini, Alicia
Worth, Andrew
author_facet Pappalardo, Francesco
Russo, Giulia
Corsini, Emanuela
Paini, Alicia
Worth, Andrew
author_sort Pappalardo, Francesco
collection PubMed
description Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally disseminated environmental contaminants known to be immunotoxic. Elevated PFAS exposure is associated with lower antibody responses to vaccinations in children and in adults. In addition, some studies have reported a correlation between PFAS levels in the body and lower resistance to disease, in other words an increased risk of infections or cancers. In this context, modelling and simulation platforms could be used to simulate the human immune system with the aim to evaluate the adverse effects that immunotoxicants may have. Here, we show the conditions under which a mathematical model developed for one purpose and application (e.g., in the pharmaceutical domain) can be successfully translated and transferred to another (e.g., in the chemicals domain) without undergoing significant adaptation. In particular, we demonstrate that the Universal Immune System Simulator was able to simulate the effects of PFAS on the immune system, introducing entities and new interactions that are biologically involved in the phenomenon. This also revealed a potentially exploitable pathway for assessing immunotoxicity through a computational model.
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spelling pubmed-90359462022-04-28 Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system Pappalardo, Francesco Russo, Giulia Corsini, Emanuela Paini, Alicia Worth, Andrew Comput Struct Biotechnol J Method Article Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally disseminated environmental contaminants known to be immunotoxic. Elevated PFAS exposure is associated with lower antibody responses to vaccinations in children and in adults. In addition, some studies have reported a correlation between PFAS levels in the body and lower resistance to disease, in other words an increased risk of infections or cancers. In this context, modelling and simulation platforms could be used to simulate the human immune system with the aim to evaluate the adverse effects that immunotoxicants may have. Here, we show the conditions under which a mathematical model developed for one purpose and application (e.g., in the pharmaceutical domain) can be successfully translated and transferred to another (e.g., in the chemicals domain) without undergoing significant adaptation. In particular, we demonstrate that the Universal Immune System Simulator was able to simulate the effects of PFAS on the immune system, introducing entities and new interactions that are biologically involved in the phenomenon. This also revealed a potentially exploitable pathway for assessing immunotoxicity through a computational model. Research Network of Computational and Structural Biotechnology 2022-03-26 /pmc/articles/PMC9035946/ /pubmed/35495116 http://dx.doi.org/10.1016/j.csbj.2022.03.024 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Pappalardo, Francesco
Russo, Giulia
Corsini, Emanuela
Paini, Alicia
Worth, Andrew
Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system
title Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system
title_full Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system
title_fullStr Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system
title_full_unstemmed Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system
title_short Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system
title_sort translatability and transferability of in silico models: context of use switching to predict the effects of environmental chemicals on the immune system
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035946/
https://www.ncbi.nlm.nih.gov/pubmed/35495116
http://dx.doi.org/10.1016/j.csbj.2022.03.024
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