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A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation
Clinical investigations prove that blue light irradiation reduces the severity of psoriasis vulgaris. Nevertheless, the mechanisms involved in the management of this condition remain poorly defined. Despite the encouraging results of the clinical studies, no clear guidelines are specified in the lit...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5266737/ https://www.ncbi.nlm.nih.gov/pubmed/28184200 http://dx.doi.org/10.3389/fphys.2017.00028 |
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author | Félix Garza, Zandra C. Liebmann, Joerg Born, Matthias Hilbers, Peter A. J. van Riel, Natal A. W. |
author_facet | Félix Garza, Zandra C. Liebmann, Joerg Born, Matthias Hilbers, Peter A. J. van Riel, Natal A. W. |
author_sort | Félix Garza, Zandra C. |
collection | PubMed |
description | Clinical investigations prove that blue light irradiation reduces the severity of psoriasis vulgaris. Nevertheless, the mechanisms involved in the management of this condition remain poorly defined. Despite the encouraging results of the clinical studies, no clear guidelines are specified in the literature for the irradiation scheme regime of blue light-based therapy for psoriasis. We investigated the underlying mechanism of blue light irradiation of psoriatic skin, and tested the hypothesis that regulation of proliferation is a key process. We implemented a mechanistic model of cellular epidermal dynamics to analyze whether a temporary decrease of keratinocytes hyper-proliferation can explain the outcome of phototherapy with blue light. Our results suggest that the main effect of blue light on keratinocytes impacts the proliferative cells. They show that the decrease in the keratinocytes proliferative capacity is sufficient to induce a transient decrease in the severity of psoriasis. To study the impact of the therapeutic regime on the efficacy of psoriasis treatment, we performed simulations for different combinations of the treatment parameters, i.e., length of treatment, fluence (also referred to as dose), and intensity. These simulations indicate that high efficacy is achieved by regimes with long duration and high fluence levels, regardless of the chosen intensity. Our modeling approach constitutes a framework for testing diverse hypotheses on the underlying mechanism of blue light-based phototherapy, and for designing effective strategies for the treatment of psoriasis. |
format | Online Article Text |
id | pubmed-5266737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52667372017-02-09 A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation Félix Garza, Zandra C. Liebmann, Joerg Born, Matthias Hilbers, Peter A. J. van Riel, Natal A. W. Front Physiol Physiology Clinical investigations prove that blue light irradiation reduces the severity of psoriasis vulgaris. Nevertheless, the mechanisms involved in the management of this condition remain poorly defined. Despite the encouraging results of the clinical studies, no clear guidelines are specified in the literature for the irradiation scheme regime of blue light-based therapy for psoriasis. We investigated the underlying mechanism of blue light irradiation of psoriatic skin, and tested the hypothesis that regulation of proliferation is a key process. We implemented a mechanistic model of cellular epidermal dynamics to analyze whether a temporary decrease of keratinocytes hyper-proliferation can explain the outcome of phototherapy with blue light. Our results suggest that the main effect of blue light on keratinocytes impacts the proliferative cells. They show that the decrease in the keratinocytes proliferative capacity is sufficient to induce a transient decrease in the severity of psoriasis. To study the impact of the therapeutic regime on the efficacy of psoriasis treatment, we performed simulations for different combinations of the treatment parameters, i.e., length of treatment, fluence (also referred to as dose), and intensity. These simulations indicate that high efficacy is achieved by regimes with long duration and high fluence levels, regardless of the chosen intensity. Our modeling approach constitutes a framework for testing diverse hypotheses on the underlying mechanism of blue light-based phototherapy, and for designing effective strategies for the treatment of psoriasis. Frontiers Media S.A. 2017-01-26 /pmc/articles/PMC5266737/ /pubmed/28184200 http://dx.doi.org/10.3389/fphys.2017.00028 Text en Copyright © 2017 Félix Garza, Liebmann, Born, Hilbers and van Riel. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Félix Garza, Zandra C. Liebmann, Joerg Born, Matthias Hilbers, Peter A. J. van Riel, Natal A. W. A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation |
title | A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation |
title_full | A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation |
title_fullStr | A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation |
title_full_unstemmed | A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation |
title_short | A Dynamic Model for Prediction of Psoriasis Management by Blue Light Irradiation |
title_sort | dynamic model for prediction of psoriasis management by blue light irradiation |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5266737/ https://www.ncbi.nlm.nih.gov/pubmed/28184200 http://dx.doi.org/10.3389/fphys.2017.00028 |
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