We have located links that may give you full text access.
iTRAQ-based quantitative analysis of alveolar bone resorption in rats with experimental periodontitis.
Archives of Oral Biology 2017 October
OBJECTIVE: Periapical periodontitis results in alveolar bone resorption around the root apex. During the progression of inflammation, host cells release various inflammatory mediators and pro-inflammatory cytokines through immune responses. However, the pathological mechanisms associated with periapical bone destruction remain unclear. This study was objected to identify differentially regulated proteins in periapical periodontitis via a quantitative proteomics approach using isobaric tags for relative and absolute quantification (iTRAQ) labelling of peptides.
METHODS: A model of periapical periodontitis by sealing LPS into the pulp chambers of rats was established. iTRAQ was employed to screen differentially expressed proteins in alveolar bone between periapical lesions and healthy controls. These proteins were further analysed by bioinformatics. And four proteins were validated by western bolt.
RESULTS: We identified 4398 proteins, of which 7 were up-regulated and 151 were down-regulated in periapical periodontitis compared to normal tissue. Using bioinformatics tools such as GO and KEGG pathway analysis, we found that our proteomics strategy could identify and quantify differentially expressed proteins that were not described in previous studies examining periapical periodontitis; these proteins included hexokinase, legumain and members of the keratin family.
CONCLUSION: In summary, our results represent potential biomarkers for the detection of periapical periodontitis and demonstrate that quantitative proteomics is a robust discovery tool for the identification of differentially regulated proteins in periapical periodontitis.
METHODS: A model of periapical periodontitis by sealing LPS into the pulp chambers of rats was established. iTRAQ was employed to screen differentially expressed proteins in alveolar bone between periapical lesions and healthy controls. These proteins were further analysed by bioinformatics. And four proteins were validated by western bolt.
RESULTS: We identified 4398 proteins, of which 7 were up-regulated and 151 were down-regulated in periapical periodontitis compared to normal tissue. Using bioinformatics tools such as GO and KEGG pathway analysis, we found that our proteomics strategy could identify and quantify differentially expressed proteins that were not described in previous studies examining periapical periodontitis; these proteins included hexokinase, legumain and members of the keratin family.
CONCLUSION: In summary, our results represent potential biomarkers for the detection of periapical periodontitis and demonstrate that quantitative proteomics is a robust discovery tool for the identification of differentially regulated proteins in periapical periodontitis.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app