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A Murine Pancreatic Islet Cell-based Screening for Diabetogenic Environmental Chemicals
Published on: June 25, 2018
Literature-based discovery of diabetes- and ROS-related targets.
Junguk Hur1, Kelli A Sullivan, Adam D Schuyler
1Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA.
This study identifies genes linked to reactive oxygen species (ROS) and diabetes using text mining. Key ROS-diabetes genes were found to be differentially expressed in mouse models of diabetic neuropathy.
Area of Science:
- Biomedical Informatics
- Molecular Biology
- Genetics
Background:
- Reactive oxygen species (ROS) are implicated in cellular damage in diseases like diabetes.
- A comprehensive database for ROS-associated genes is lacking.
- Understanding these genes is crucial for addressing diabetic complications.
Purpose of the Study:
- To identify and compile genes related to both ROS and diabetes.
- To evaluate the biological relevance of these identified genes in diabetic neuropathy.
- To establish a foundation for a ROS-diabetes gene database.
Main Methods:
- Utilized text mining technology (SciMiner) on 1,154 PubMed-indexed papers on ROS and diabetes.
- Identified 1,026 ROS- and diabetes-related targets.
- Compared target frequency against random literature to find over-represented genes.
- Measured expression levels of nine selected genes in mouse dorsal root ganglia (DRG).
Main Results:
- Identified 1,026 ROS- and diabetes-related targets.
- Found 53 significantly over-represented targets, including catalase, NADPH oxidase, and superoxide dismutase families.
- Eight of nine tested genes showed differential expression in diabetic mice.
- Six genes' expression changes correlated with increased oxidative stress in the DRG.
Conclusions:
- Literature mining effectively compiled ROS-diabetes related targets.
- Selected targets demonstrated biological relevance in the pathogenesis of diabetic neuropathy.
- This work provides a basis for further research into ROS-mediated diabetic complications.
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