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Vascular dementia (VD) is one of the most common types of dementia, accounting for about 20% of all dementia cases ( Hugo and Ganguli, 2014 O'Brien and Thomas, 2015). According to the World Alzheimer Report 2015, the number was expected to increase to 75.6 million by 2030 and more than 130 million by 2050 ( Prina et al., 2015).

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Then, nine unique proteins and two composite markers (CM) (A0A5C2GRG5+U2AF2 and U2AF2+C6) were confirmed by a ROC curve method.Ĭonclusion: This study provided an insight into the potential pathogenesis of DVD and elucidated a method for early detection.ĭementia, a disabling condition with functional impairment in language, memory, and execution functions, currently affects nearly 50 million people worldwide ( World Health Organization, 2017). NC, T2DM, and VD, respectively, including 481 overlapped common DEPs. Results: The proteomic findings showed quantitative changes in patients with DVD compared to patients with NC, T2DM, and VD groups among 4,744 identified urine proteins, 1,222, 1,152, and 1,180 proteins displayed quantitative changes unique to DVD vs. Combining bioinformatics analysis using Gene Ontology (GO), pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), protein–protein interaction (PPI) network analysis using STRING, and literature searching, the differentially expressed proteins (DEPs) of DVD can be comprehensively judged and were further quantified by receiver operating characteristic (ROC) curve methods.

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Searching the MS data by Proteome Discoverer software (ThermoFisher Scientific Waltham, MA, USA), protein abundances were analyzed qualitatively and quantitatively and compared between these groups. Methods: Label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis was applied to urine samples from four groups, including 14 patients with vascular dementia (VD), 22 patients with type 2 diabetes mellitus (T2DM), 12 patients with DVD, and 21 normal controls (NCs). Objective: This study aimed to identify potential diagnostic biomarkers of diabetic vascular dementia (DVD) and unravel the underlying mechanisms using mass spectrometry (MS).

  • 4Department of Neurology, Second Xiangya Hospital, Central South University, Changsha, China.
  • 3State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
  • 2Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.
  • 1Department of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, China.
  • Ruijuan Chen 1, Yuanjing Yi 1, Wenbiao Xiao 2, Bowen Zhong 3, Yi Shu 4, Le Zhang 2 and Yi Zeng 1 * "Mnova MS - Process, analyze and report Mass Analysis Data".
  • ^ "HPLC Software - ChromNAV 2.0 Chromatography Data System | JASCO".
  • ^ "LabSolutions : SHIMADZU (Shimadzu Corporation)".
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  • ^ "Mass Frontier on Archived from the original on.
  • ^ "Dionex Chromeleon™ 7.2 Chromatography Data System".
  • Vendor independent data analysis software Web app, supports High Throughput Analysis

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    The following is a list of software and the (unexplained) tools that each provides: Īpplications are also available for simulation of chromatography, for example for teaching, demonstration, or for method development &/or optimization. Areas are computed between two valleys, a signal, and a baseline. The most common tool is "integration": It computes simple areas to delimit peaks by adding valleys automatically or not. They also provide different tools to analyze this data. Many chromatography software packages are provided by manufacturers, and many of them only provide a simple interface to acquire data. Chromatography software is software that collects and analyzes chromatographic results delivered by chromatography detectors.






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