English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 847589      Online Users : 310
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/13960


    Title: Shotgun proteomic analysis using human serum from type 2 diabetes mellitus patients
    Authors: Li, RN;Shen, PT;Lin, HYH;Liang, SS
    Contributors: Core Instrument Center
    Abstract: Background: Type 2 diabetes mellitus (T2DM), also known as adult-onset diabetes or noninsulin-dependent diabetes mellitus, is characterized by hyperglycemia and insulin resistance. Protein biomarker screening plays an essential role in different diseases. Proteomic methods such as MALDI-TOF based peptide mass fingerprinting, LC-MS/MS based peptide sequencing, and multidimensional liquid phase chromatography (MDLC) coupled with tandem mass spectrometry (MS) shotgun proteomics are used to identify biomarkers. Methods: In this study, we used a MDLC coupled with tandem MS shotgun proteomic method to demonstrate protein quantitation results by comparing human serum samples from T2DM patients with those of healthy subjects. We utilized quantitative techniques, dimethyl labeling, MDLC by hydrophilic interaction liquid chromatography separated column, and reverse-phase high-performance liquid chromatography coupled with tandem MS to identify proteins with high potential to be T2DM biomarker candidates. Results: Identified candidates included vitamin D–binding protein, apolipoprotein B-100, apolipoprotein A2, apolipoprotein A1, transthyretin, Ig heavy-chain V–III region BRO, antithrombin-3, fibrinogen gamma chains, fibrinogen alpha chains, and alpha-1-antitrypsin. In addition, we also generated relative protein networks using STRING bioinformatic software. Conclusion: These potential biomarker candidates might be verified by further experiments such as an ELISA assay or multiple reaction monitoring MS screening.
    Date: 2022-01-30
    Relation: International Journal of Diabetes in Developing Countries. 2022 Jan 30;43:145-154.
    Link to: http://dx.doi.org/10.1007/s13410-021-01038-z
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0973-3930&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000749161700001
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85123871437
    Appears in Collections:[其他] 期刊論文

    Files in This Item:

    File Description SizeFormat
    SCP85123871437.pdf1456KbAdobe PDF254View/Open


    All items in NHRI are protected by copyright, with all rights reserved.

    Related Items in TAIR

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback