Dataset Information

DM

ABSTRACT: Diabetic mellitus (DM) is a disease that affects glucose homeostasis and has cause of complications, such as diabetic nephropathy (DN). For diagnose of the early DN, microalbuminuria is one of the mostly used biomarker currently. However, more early diagnostic biomarkers are desired rather than microalbuminuria.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Tadashi Yamamoto

PROVIDER: PXD008683 | JPOST Repository | Thu May 31 00:00:00 BST 2018

REPOSITORIES: jPOST

ACCESS DATA

Publications

Proteome Profiling of Diabetic Mellitus Patient Urine for Discovery of Biomarkers by Comprehensive MS-Based Proteomics.

Hirao Yoshitoshi Y Saito Suguru S Fujinaka Hidehiko H Miyazaki Shigeru S Xu Bo B Quadery Ali F AF Elguoshy Amr A Yamamoto Keiko K Yamamoto Tadashi T

Proteomes 20180206 1

Diabetic mellitus (DM) is a disease that affects glucose homeostasis and causes complications, such as diabetic nephropathy (DN). For early diagnosis of DN, microalbuminuria is currently one of the most frequently used biomarkers. However, more early diagnostic biomarkers are desired in addition to microalbuminuria. In this study, we performed comprehensive proteomics analysis of urine proteomes of diabetic mellitus patients without microalbuminuria and healthy volunteers to compare the protein ...[more]

PMID: 29415455

Similar Datasets

Project description:The paper describes a model on the detection of cancer based on cancer and immune biomarkers. Created by COPASI 4.25 (Build 207) This model is described in the article: Improving cancer detection through combinations of cancer and immune biomarkers: a modelling approach Raluca Eftimie and and Esraa Hassanein J Transl Med (2018) 16:73 Abstract: Background: Early cancer diagnosis is one of the most important challenges of cancer research, since in many can- cers it can lead to cure for patients with early stage diseases. For epithelial ovarian cancer (which is the leading cause of death among gynaecologic malignancies) the classical detection approach is based on measurements of CA-125 biomarker. However, the poor sensitivity and specificity of this biomarker impacts the detection of early-stage cancers. Methods: Here we use a computational approach to investigate the effect of combining multiple biomarkers for ovarian cancer (e.g., CA-125 and IL-7), to improve early cancer detection. Results: We show that this combined biomarkers approach could lead indeed to earlier cancer detection. However, the immune response (which influences the level of secreted IL-7 biomarker) plays an important role in improving and/or delaying cancer detection. Moreover, the detection level of IL-7 immune biomarker could be in a range that would not allow to distinguish between a healthy state and a cancerous state. In this case, the construction of solu- tion diagrams in the space generated by the IL-7 and CA-125 biomarkers could allow us predict the long-term evolu- tion of cancer biomarkers, thus allowing us to make predictions on cancer detection times. Conclusions: Combining cancer and immune biomarkers could improve cancer detection times, and any predic- tions that could be made (at least through the use of CA-125/IL-7 biomarkers) are patient specific. Keywords: Ovarian cancer, Mathematical model, CA-125 biomarker, IL-7 biomarker, Cancer detection times This model is hosted on BioModels Database and identified by: MODEL1907050002. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

DM

Publications

Proteome Profiling of Diabetic Mellitus Patient Urine for Discovery of Biomarkers by Comprehensive MS-Based Proteomics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure