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The abuse of anabolic substances in animal husbandry is forbidden within the EU and well controlled by detecting substance residues in different matrices. The application of newly designed drugs or substance cocktails represents big problems. Therefore developing sensitive test methods is important. The analysis of physiological changes caused by the use of anabolic agents on the molecular level, for example, by quantifying gene expression response, is a new approach to develop such screening methods. A novel technology for holistic gene expression analysis is RNA sequencing. In this study, the potential of this high-throughput method for the identification of biomarkers was evaluated. The effect of trenbolone acetate plus estradiol on gene expression in liver from Nguni heifers was analyzed with RNA sequencing. The expression of 40 selected candidate genes was verified via RT-qPCR, whereby 20 of these genes were significantly regulated. To extract the intended information from these regulated genes, biostatistical tools for pattern recognition were applied and resulted in a clear separation of the treatment groups. Those candidate genes could be verified in boars and in calves treated with anabolic substances. These results show the potential of RNA sequencing to screen for biomarker candidates to detect the abuse of anabolics. The verification of these biomarkers in boars and calves leads to the assumption that gene expression biomarkers are independent of breed or even species and that biomarkers, identified in farm animals could also act as potential biomarker candidates to detect the abuse of anabolic substances in human sports.
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http://dx.doi.org/10.1021/ac301433d | DOI Listing |
Dig Dis Sci
September 2025
Department of Gastroenterology and Hepatology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
Background And Aims: Liver metastasis significantly contributes to poor survival in patients with colorectal cancer (CRC), posing therapeutic challenges due to limited understanding of its mechanisms. We aimed to identify a potential target critical for CRC liver metastasis.
Methods: We analyzed the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases and identified EphrinA3 (EFNA3) as a potential clinically relevant target.
Med Oncol
September 2025
Division of Hematology and Blood Bank, Department of Medical Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
Acute Myeloid Leukemia (AML) patient-derived Mesenchymal Stem Cells (MSCs) behave differently than normal ones, creating a more protective environment for leukemia cells, making relapse harder to prevent. This study aimed to identify prognostic biomarkers and elucidate relevant biological pathways in AML by leveraging microarray data and advanced bioinformatics techniques. We retrieved the GSE122917 dataset from the NCBI Gene Expression Omnibus and performed differential expression analysis (DEA) within R Studio to identify differentially expressed genes (DEGs) among healthy donors, newly diagnosed AML patients, and relapsed AML patients.
View Article and Find Full Text PDFAppl Biochem Biotechnol
September 2025
Operating Room, Shanghai Tianyou Hospital, No.528, Zhennan Road, Putuo District, Shanghai, 200331, China.
Gastric cancer (GC) is a malignant tumor originating from the epithelial cells of the gastric mucosa. The 5-methylcytosine (mC) modification refers to the addition of a methyl group to the fifth carbon atom of cytosine in RNA molecules. This study aimed to investigate the role of NOL1/NOP2/SUN domain (NSUN)6 in GC and its underlying molecular mechanisms.
View Article and Find Full Text PDFActa Diabetol
September 2025
Department of Endocrinology & Metabolism, Medical College & Hospital, Kolkata, 88, College St. College Square, Kolkata, West Bengal, 700073, India.
Background And Aims: Gestational diabetes mellitus (GDM) is defined as glucose intolerance first identified during pregnancy that does not meet the criteria for overt diabetes. Its pathophysiology shares key features with type 2 diabetes mellitus (T2D), including insulin resistance and inflammation. Emerging evidence suggests that long non-coding RNAs (lncRNAs) are implicated in T2D.
View Article and Find Full Text PDFPlant Cell Rep
September 2025
Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, 225009, China.
Plasma membrane Gγ protein MGG4, the candidate for maize yield QTL, positively regulates seed size mainly through affecting kernel width.
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