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The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats
Qingfu Guanjieshu (QFGJS) is an herbal preparation for treating rheumatoid arthritis (RA). Previous studies revealed that QFGJS significantly inhibited experimental arthritis and acute inflammation, accompanied by reduction of proinflammatory cytokines and elevation of anti-inflammatory cytokines. T...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3678439/ https://www.ncbi.nlm.nih.gov/pubmed/23781264 http://dx.doi.org/10.1155/2013/582493 |
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author | Wang, Ting Yu Zhou, Hua Wong, Yuen Fan Wu, Pui Kei Hsiao, Wen-Luan Wendy Leung, Elaine Lai-Han Liu, Liang |
author_facet | Wang, Ting Yu Zhou, Hua Wong, Yuen Fan Wu, Pui Kei Hsiao, Wen-Luan Wendy Leung, Elaine Lai-Han Liu, Liang |
author_sort | Wang, Ting Yu |
collection | PubMed |
description | Qingfu Guanjieshu (QFGJS) is an herbal preparation for treating rheumatoid arthritis (RA). Previous studies revealed that QFGJS significantly inhibited experimental arthritis and acute inflammation, accompanied by reduction of proinflammatory cytokines and elevation of anti-inflammatory cytokines. This study aims to identify the targeted proteins and predict the proteomic network associated with the drug action of QFGJS by using 2D gel and MALDI-TOF-MS/MS techniques. Thirty female Wistar rats were evenly grouped as normal and vehicle- and QFGJS-treated CIA rats. The antiarthritic effect of QFGJS was examined with a 19-day treatment course, and the knee synovial tissues of animals from each group were obtained for 2D gel and MALDI-TOF-MS/MS analysis. Results showed that QFGJS significantly ameliorated collagen II-induced arthritis when administrated at 2.8 g/kg body weight for 19 days. 2D gel image analysis revealed 89 differentially expressed proteins in the synovial tissues among the normal and vehicle- and QFGJS-treated CIA rats from over 1000 proteins of which 63 proteins were identified by MALDI-TOF-MS/MS analysis, and 32 proteins were included for classification of functions using Gene Ontology (GO) method. Finally, 14 proteins were analyzed using bioinformatics, and a predicted proteomic network related to the anti-arthritic effect of QFGJS was established, and Pgk1 plays a central role. |
format | Online Article Text |
id | pubmed-3678439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-36784392013-06-18 The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats Wang, Ting Yu Zhou, Hua Wong, Yuen Fan Wu, Pui Kei Hsiao, Wen-Luan Wendy Leung, Elaine Lai-Han Liu, Liang Evid Based Complement Alternat Med Research Article Qingfu Guanjieshu (QFGJS) is an herbal preparation for treating rheumatoid arthritis (RA). Previous studies revealed that QFGJS significantly inhibited experimental arthritis and acute inflammation, accompanied by reduction of proinflammatory cytokines and elevation of anti-inflammatory cytokines. This study aims to identify the targeted proteins and predict the proteomic network associated with the drug action of QFGJS by using 2D gel and MALDI-TOF-MS/MS techniques. Thirty female Wistar rats were evenly grouped as normal and vehicle- and QFGJS-treated CIA rats. The antiarthritic effect of QFGJS was examined with a 19-day treatment course, and the knee synovial tissues of animals from each group were obtained for 2D gel and MALDI-TOF-MS/MS analysis. Results showed that QFGJS significantly ameliorated collagen II-induced arthritis when administrated at 2.8 g/kg body weight for 19 days. 2D gel image analysis revealed 89 differentially expressed proteins in the synovial tissues among the normal and vehicle- and QFGJS-treated CIA rats from over 1000 proteins of which 63 proteins were identified by MALDI-TOF-MS/MS analysis, and 32 proteins were included for classification of functions using Gene Ontology (GO) method. Finally, 14 proteins were analyzed using bioinformatics, and a predicted proteomic network related to the anti-arthritic effect of QFGJS was established, and Pgk1 plays a central role. Hindawi Publishing Corporation 2013 2013-05-27 /pmc/articles/PMC3678439/ /pubmed/23781264 http://dx.doi.org/10.1155/2013/582493 Text en Copyright © 2013 Ting Yu Wang et al. https://creativecommons.org/licenses/by/3.0/ 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 | Research Article Wang, Ting Yu Zhou, Hua Wong, Yuen Fan Wu, Pui Kei Hsiao, Wen-Luan Wendy Leung, Elaine Lai-Han Liu, Liang The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats |
title | The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats |
title_full | The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats |
title_fullStr | The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats |
title_full_unstemmed | The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats |
title_short | The Predicted Proteomic Network Associated with the Antiarthritic Action of Qingfu Guanjieshu in Collagen-II-Induced Arthritis in Rats |
title_sort | predicted proteomic network associated with the antiarthritic action of qingfu guanjieshu in collagen-ii-induced arthritis in rats |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3678439/ https://www.ncbi.nlm.nih.gov/pubmed/23781264 http://dx.doi.org/10.1155/2013/582493 |
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