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Purpose To explore the viability of used toothbrush as a source of gene expression and comparison of the same among tobacco, alcohol, diabetic and hypertensive subjects. Materials and methods Fourteen subjects with a history of type 2 diabetes mellitus (T2DM) and hypertension were allocated to Group I, 14 subjects with tobacco and alcohol habits allocated to Group II and 14 healthy subjects allocated to Group III. Genetic materials retrieved from the used toothbrush of the study subjects were assessed for genetic expression of cyclin-dependent kinase 4 (CDK4), Bcl-2-like protein 4 (BAX), cyclin-dependent kinase inhibitor 2A (CDKN2A), B-cell lymphoma 2 (BCL2), G-protein beta-3 (GNB3), and subunit gene and transcription factor 7-like 2 (TCF7L2) by polymerase chain reaction (PCR). Results BAX gene showed reduced expression in tobacco and alcohol users (p=0.0497). BCL2, CDK4, and GNB3 showed no significant difference in expression in both the groups and with control. CDKN2A was expressed at a lower level in Group I and II participants. TCF7L2 showed higher expression in Group 2 participants (p=0.001). Conclusion The study concluded that used toothbrush is a reliable source for genetic expression. There was no difference in BCL2, CDK4, and GNB3 gene expression between subjects with systemic disease, adverse habits and healthy controls. There is a downregulation of BAX and upregulation of TCF7L2 gene in subjects with adverse habits.
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http://dx.doi.org/10.7759/cureus.31391 | DOI Listing |
Alzheimers Res Ther
September 2025
Department of Neurology, Saarland University, Kirrberger Straße, 66421, Homburg/Saar, Germany.
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View Article and Find Full Text PDFEur J Med Res
September 2025
Department of Zoology, Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt.
Nuclear receptors (NRs) are a superfamily of ligand-activated transcription factors that regulate gene expression in response to metabolic, hormonal, and environmental signals. These receptors play a critical role in metabolic homeostasis, inflammation, immune function, and disease pathogenesis, positioning them as key therapeutic targets. This review explores the mechanistic roles of NRs such as PPARs, FXR, LXR, and thyroid hormone receptors (THRs) in regulating lipid and glucose metabolism, energy expenditure, cardiovascular health, and neurodegeneration.
View Article and Find Full Text PDFGenome Biol
September 2025
Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
Background: Recent advances in high-throughput sequencing technologies have enabled the collection and sharing of a massive amount of omics data, along with its associated metadata-descriptive information that contextualizes the data, including phenotypic traits and experimental design. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability and limit secondary analyses.
View Article and Find Full Text PDFDiagn Pathol
September 2025
Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Background: Gastric cancer is one of the most common cancers worldwide, with its prognosis influenced by factors such as tumor clinical stage, histological type, and the patient's overall health. Recent studies highlight the critical role of lymphatic endothelial cells (LECs) in the tumor microenvironment. Perturbations in LEC function in gastric cancer, marked by aberrant activation or damage, disrupt lymphatic fluid dynamics and impede immune cell infiltration, thereby modulating tumor progression and patient prognosis.
View Article and Find Full Text PDFGenome Biol
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Department of Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, Plön, Germany.
Background: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.
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