Toward a standardized urine proteome analysis methodology

2011 ◽  
Vol 5 (9-10) ◽  
pp. 547-547 ◽  
Author(s):  
Magali Court ◽  
Nathalie Selevsek ◽  
Mariette Matondo ◽  
Yves Allory ◽  
Jerome Garin ◽  
...  
Keyword(s):  
Proteome Analysis ◽  
Urine Proteome ◽  
Analysis Methodology

Toward a standardized urine proteome analysis methodology

PROTEOMICS ◽  
2011 ◽  
Vol 11 (6) ◽  
pp. 1160-1171 ◽  
Author(s):  
Magali Court ◽  
Nathalie Selevsek ◽  
Mariette Matondo ◽  
Yves Allory ◽  
Jerome Garin ◽  
...  
Keyword(s):  
Proteome Analysis ◽  
Urine Proteome ◽  
Analysis Methodology

Reconstruction of associative protein networks connected with processes of sodium exchange regulation and sodium deposition in healthy volunteers based on urine proteome analysis

2012 ◽  
Vol 38 (3) ◽  
pp. 316-323 ◽  
Author(s):  
I. M. Larina ◽  
N. A. Kolchanov ◽  
I. V. Dobrokhotov ◽  
V. A. Ivanisenko ◽  
P. S. Demenkov ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Proteome Analysis ◽  
Protein Networks ◽  
Urine Proteome ◽  
Sodium Exchange

Accurate mass tag retention time database for urine proteome analysis by chromatography-mass spectrometry

2010 ◽  
Vol 75 (5) ◽  
pp. 636-641 ◽  
Author(s):  
I. A. Agron ◽  
D. M. Avtonomov ◽  
A. S. Kononikhin ◽  
I. A. Popov ◽  
S. A. Moshkovskii ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Retention Time ◽  
Proteome Analysis ◽  
Accurate Mass ◽  
Urine Proteome ◽  
Tag Retention ◽  
Chromatography Mass Spectrometry ◽  
Mass Tag

Urine proteome analysis in Dent's disease shows high selective changes potentially involved in chronic renal damage

2016 ◽  
Vol 130 ◽  
pp. 26-32 ◽  
Author(s):  
Laura Santucci ◽  
Giovanni Candiano ◽  
Franca Anglani ◽  
Maurizio Bruschi ◽  
Enrica Tosetto ◽  
...  
Keyword(s):  
Renal Damage ◽  
Proteome Analysis ◽  
Dent’S Disease ◽  
Urine Proteome ◽  
Dent's Disease

Human urine proteome analysis by three separation approaches

PROTEOMICS ◽  
2005 ◽  
Vol 5 (18) ◽  
pp. 4994-5001 ◽  
Author(s):  
Wei Sun ◽  
Fuxin Li ◽  
Shuzhen Wu ◽  
Xiaorong Wang ◽  
Dexian Zheng ◽  
...  
Keyword(s):  
Human Urine ◽  
Proteome Analysis ◽  
Urine Proteome

Toward a standardized saliva proteome analysis methodology

2012 ◽  
Vol 75 (17) ◽  
pp. 5140-5165 ◽  
Author(s):  
Rui Vitorino ◽  
Sofia Guedes ◽  
Bruno Manadas ◽  
Rita Ferreira ◽  
Francisco Amado
Keyword(s):  
Proteome Analysis ◽  
Analysis Methodology

Urine proteome analysis to evaluate protein biomarkers in children with autism

2015 ◽  
Vol 450 ◽  
pp. 210-219 ◽  
Author(s):  
Vijayashankar Suganya ◽  
Arumugam Geetha ◽  
Sridharan Sujatha
Keyword(s):  
Proteome Analysis ◽  
Children With Autism ◽  
Protein Biomarkers ◽  
Urine Proteome

scholarly journals Urine Proteome Analysis May Allow Noninvasive Differential Diagnosis of Diabetic Nephropathy

Diabetes Care ◽  
2010 ◽  
Vol 33 (11) ◽  
pp. 2409-2415 ◽  
Author(s):  
M. Papale ◽  
S. Di Paolo ◽  
R. Magistroni ◽  
O. Lamacchia ◽  
A. M. Di Palma ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Diabetic Nephropathy ◽  
Proteome Analysis ◽  
Urine Proteome

scholarly journals Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Sanja Kiprijanovska ◽  
Sotir Stavridis ◽  
Oliver Stankov ◽  
Selim Komina ◽  
Gordana Petrusevska ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
System Development ◽  
Proteome Analysis ◽  
Cellular Growth ◽  
Specific Information ◽  
Urogenital System ◽  
Urine Proteome ◽  
2D Page ◽  
Protein Components ◽  
Normal Urine

Proteome analysis of the urine has shown that urine contains disease-specific information for a variety of urogenital system disorders, including prostate cancer (PCa). The aim of this study was to determine the protein components of urine from PCa patients. Urine from 8 patients with clinically and histologically confirmed PCa was analyzed by conventional 2D PAGE. The MS identification of the most prominent 125 spots from the urine map revealed 45 distinct proteins. According to Gene Ontology, the identified proteins are involved in a variety of biological processes, majority of them are secreted (71%), and half of them are enzymes or transporters. Comparison with the normal urine proteome revealed 11 proteins distinctive for PCa. Using Ingenuity Pathways Analysis, we have found 3 proteins (E3 ubiquitin-protein ligase rififylin, tumor protein D52, and thymidine phosphorylase) associated with cellular growth and proliferation (p=8.35×10-4-3.41×10-2). The top network of functional associations between 11 proteins was Cell Death and Survival, Cell-To-Cell Signaling and Interaction, and System Development and Function (p=10-30). In summary, we have created an initial proteomic map of PCa patient’s urine. The results from this study provide some leads to understand the molecular bases of prostate cancer.

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