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-cells ( 8 ). Nevertheless, the exact role of m6A methylation in T2D has not been explored. In this study, bioinformatics is used to investigate the biological role and underlying mechanism of m6A methylation genes in T2D, and the INS gene was screened
Postgraduation Program in Medical Sciences: Endocrinology, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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Postgraduation Program in Medical Sciences: Endocrinology, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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Postgraduation Program in Medical Sciences: Endocrinology, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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, to further investigate which miRNAs may be used as new potential biomarkers of T1DM, we performed a systematic review of the literature on the subject. Additionally, bioinformatic analyses were performed to investigate the regulatory and functional
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prognosis and treatment of thyroid cancer. Methods RNA-seq data and bioinformatics analysis This study used data downloaded from the TCGA database ( https://portal.gdc.cancer.gov ). RNA-seq data from the TCGA–thyroid carcinoma (THCA) project was
Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, People’s Republic of China
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Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou, People’s Republic of China
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Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou, People’s Republic of China
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Background and aims
Non-alcoholic fatty liver disease (NAFLD) has become a common chronic liver disease in the world. Simple steatosis (SS) is the early phase of NAFLD. However, the molecular mechanisms underlying the development of steatosis have not yet been fully elucidated.
Methods
Two public datasets (GSE48452 and GSE89632) through the Gene Expression Omnibus (GEO) database were used to identify differentially expressed genes (DEGs) in the development of steatosis. A total of 72 participants including 38 normal histological controls and 34 SS patients were included in this study. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) network analysis were performed to explore the function of DEGs. The results were further confirmed in high-fat diet (HFD)-fed mice and oleate-treated HepG2 cells.
Results
Total 57 DEGs including 31 up- and 26 down-regulated genes between SS patients and healthy controls were determined. GO and KEGG analysis showed that most of the DEGs were enriched in the ligand–receptor signaling pathways. PPI network construction was used to identify the hub genes of the DEGs. MYC, ANXA2, GDF15, AGTR1, NAMPT, LEPR, IGFBP-2, IL1RN, MMP7, and APLNR were identified as hub genes, and IGFBP-2 expression was found to be reversely associated with hepatic steatosis, fasting insulin, HOMA-IR index, and ALT levels. In HFD-fed mice, hepatic IGFBP-2 was also downregulated and negatively associated with hepatic triglyceride (TG) levels. Moreover, overexpression of IGFBP-2 ameliorated the oleate induced accumulation of TGs in hepatocytes.
Conclusions
This study identified novel gene signatures in the hepatic steatosis and will provide new understanding and molecular clues of hepatic steatosis.
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Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
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Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina, USA
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Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina, USA
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://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108965 ). RNA-seq data processing Data analysis for placenta RNA-seq was performed by the Bioinformatics Core at the University of Virginia, on a fee for service basis as described previously ( 53 ). Fetal forebrain data analysis was conducted
Department of Surgery, The University of Melbourne, Parkville, Victoria, Australia
Department of Urology, Royal Melbourne Hospital, Parkville, Victoria, Australia
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Department of Urology, Royal Melbourne Hospital, Parkville, Victoria, Australia
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Department of Urology, Royal Melbourne Hospital, Parkville, Victoria, Australia
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Australian Prostate Cancer Research Centre Epworth, Richmond, Victoria, Australia
Ontario Institute for Cancer Research, Toronto, Canada
Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
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Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
Department of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia
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Department of Urology, Royal Melbourne Hospital, Parkville, Victoria, Australia
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Department of Urology, Royal Melbourne Hospital, Parkville, Victoria, Australia
Department of Urology, Frankston Hospital, Frankston, Victoria, Australia
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sequence data . Cambridge, UK : Babraham Bioinformatics , 2010 . (available at: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ) 26 Bolger AM Lohse M Usadel B . Trimmomatic: a flexible trimmer for Illumina sequence data . Bioinformatics
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), bioinformatics analysis and, in the clinical setting, genetic consultation (19) . Due to its well-characterized genotype–phenotype correlation and the limitations imposed by existing technologies, there is a strong argument for investigating the potential use of
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concentration for fetuin-B was 0.1 μg/mL. And the preparation and operation steps of the reagent were performed strictly in accordance with the instructions. Bioinformatics analysis Protein–protein interaction network construction The Search Tool (v
Department of Breast Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China
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Department of Surgery, Second People's Hospital of Guizhou Province, Guiyang, Guizhou, China
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the growth and invasion of tumor cells ( 20 ). Until now, the expression and function of FOXP4 in THCA have not yet been determined. In the present study, the expression and biological behavior of FOXP4 in THCA are investigated through bioinformatics
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’GGGAAACTGTGGCGTGAT3’ R: 5’GAGTGGGTGTCGCTGTTGA3’ U6(HUMAN) F: 5’AGAGAAGATTAGCATGGCCCCTG3’ F, forward. R, reverse. Cell culture and transfection The aforementioned bioinformatic analysis and RT-qPCR results suggested that the