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Salivary Biomarkers in Systemic Sclerosis Disease
Scleroderma or systemic sclerosis (SSc) is frequently detected at an advanced stage due to diagnosis difficulties. Salivary biomarkers, if existing, could be used for predictive diagnosis of this disease. Human saliva contains a large number of proteins that can be used for diagnosis and are of grea...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5867662/ https://www.ncbi.nlm.nih.gov/pubmed/29721505 http://dx.doi.org/10.1155/2018/3921247 |
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author | Zian, Zeineb Bakkach, Joaira Barakat, Amina Ghailani Nourouti, Naima Bennani Mechita, Mohcine |
author_facet | Zian, Zeineb Bakkach, Joaira Barakat, Amina Ghailani Nourouti, Naima Bennani Mechita, Mohcine |
author_sort | Zian, Zeineb |
collection | PubMed |
description | Scleroderma or systemic sclerosis (SSc) is frequently detected at an advanced stage due to diagnosis difficulties. Salivary biomarkers, if existing, could be used for predictive diagnosis of this disease. Human saliva contains a large number of proteins that can be used for diagnosis and are of great potential in clinical research. The use of proteomic analysis to characterize whole saliva (WS) in SSc has gained an increasing attention in the last years and the identification of salivary proteins specific for SSc could lead to early diagnosis or new therapeutic targets. This review will present an overview about the use of WS in SSc studies. The proteomic technologies currently used for global identification of salivary proteins in SSc, as well as the advantages and limitations for the use of WS as a diagnostic tool, will be presented. |
format | Online Article Text |
id | pubmed-5867662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-58676622018-05-02 Salivary Biomarkers in Systemic Sclerosis Disease Zian, Zeineb Bakkach, Joaira Barakat, Amina Ghailani Nourouti, Naima Bennani Mechita, Mohcine Biomed Res Int Review Article Scleroderma or systemic sclerosis (SSc) is frequently detected at an advanced stage due to diagnosis difficulties. Salivary biomarkers, if existing, could be used for predictive diagnosis of this disease. Human saliva contains a large number of proteins that can be used for diagnosis and are of great potential in clinical research. The use of proteomic analysis to characterize whole saliva (WS) in SSc has gained an increasing attention in the last years and the identification of salivary proteins specific for SSc could lead to early diagnosis or new therapeutic targets. This review will present an overview about the use of WS in SSc studies. The proteomic technologies currently used for global identification of salivary proteins in SSc, as well as the advantages and limitations for the use of WS as a diagnostic tool, will be presented. Hindawi 2018-03-12 /pmc/articles/PMC5867662/ /pubmed/29721505 http://dx.doi.org/10.1155/2018/3921247 Text en Copyright © 2018 Zeineb Zian et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Zian, Zeineb Bakkach, Joaira Barakat, Amina Ghailani Nourouti, Naima Bennani Mechita, Mohcine Salivary Biomarkers in Systemic Sclerosis Disease |
title | Salivary Biomarkers in Systemic Sclerosis Disease |
title_full | Salivary Biomarkers in Systemic Sclerosis Disease |
title_fullStr | Salivary Biomarkers in Systemic Sclerosis Disease |
title_full_unstemmed | Salivary Biomarkers in Systemic Sclerosis Disease |
title_short | Salivary Biomarkers in Systemic Sclerosis Disease |
title_sort | salivary biomarkers in systemic sclerosis disease |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5867662/ https://www.ncbi.nlm.nih.gov/pubmed/29721505 http://dx.doi.org/10.1155/2018/3921247 |
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