Objectives: One of the most widely used pesticides today is chlorpyrifos (CPF). Cytochrome P450 (CYP)2B6, the most prominent catalyst in CPF bioactivation, is highly polymorphic. The objective of our study was to evaluate the role of CYP2B6*6, which contains both 516G>T and 785A>G polymorphisms, in CPF toxicity, as represented by the concentration of 3,5,6-trichloro-2-pyridinol (TCPy), among vegetable farmers in Central Java, Indonesia, where CPF has been commonly used.Methods: A cross-sectional study was conducted among 132 vegetable farmers. Individual socio-demographic and occupational characteristics, as determinants of TCPy levels, were obtained using a structured interviewer-administered questionnaire and subsequently used to estimate the cumulative exposure level (CEL). TCPy levels were detected with liquid chromatography-mass spectrometry. CYP2B6*6 gene polymorphisms were analyzed using a TaqMan® SNP Genotyping Assay and Sanger sequencing. Linear regression analysis was performed to analyze the association between TCPy, as a biomarker of CPF exposure, and its determinants.Results: The prevalence of CYP2B6*6 polymorphisms was 31% for *1/*1, 51% for *1/*6, and 18% for *6/*6. TCPy concentrations were higher among participants with CYP2B6*1/*1 than among those with *1/*6 or *6/*6 genotypes. CYP2B6*6 gene polymorphisms, smoking, CEL, body mass index, and spraying time were retained in the final linear regression model as determinants of TCPy.Conclusions: The results suggest that CYP2B6*6 gene polymorphisms may play an important role in influencing susceptibility to CPF exposure. CYP2B6*6 gene polymorphisms together with CEL, smoking habits, body mass index, and spraying time were the determinants of urinary TCPy concentrations, as a biomarker of CPF toxicity.

AKNA is identified as a gene that regulates inflammation, immune response, and Epithelial–Mesenchymal Transition (EMT), which plays an important role in the progression of epithelial ovarian cancer. In this study, we analyzed the genotype and allele distribution as well as 3D modeling of one of the AKNA rs10817595 (−1372 C>A). The distribution of genotypes and alleles was analyzed using the T-ARMS PCR method on 63 ovarian cancer samples and 65 controls. AKNA mRNA expression was analyzed using qRT-PCR on 35 low-grade and 28 high-grade samples. Fifteen low-grade and 12 high-grade samples were analyzed for AKNA protein levels using immunohistochemistry. A 3D model of protein structure was constructed using AlphaFold. Significant differences in AKNA protein levels were found. However, no significant correlation was found for relative AKNA mRNA expression with protein levels. This result is thought to be related to decreased immune system response, increased inflammation, and increased EMT in epithelial ovarian cancer. AKNA gene variant (−1372 C>A) can cause a decrease in mRNA and protein levels in the low-grade and high-grade groups, so it has the potential as a genetic susceptibility factor in epithelial ovarian cancer.

Thyroid peroxidase (TPO) is a crucial enzyme in the biosynthesis of thyroid hormones, catalyzing the iodination of tyrosine residues in thyroglobulin and the coupling of iodotyrosines to form thyroxine (T4) and triiodothyronine (T3). Propylthiouracil (PTU) is an antithyroid drug commonly used to manage hyperthyroidism by inhibiting TPO. Understanding the molecular interactions between TPO and PTU can provide insights into the inhibitory mechanisms and guide the design of more effective antithyroid medications. Objective: This study aims to elucidate the binding interactions between TPO and PTU through molecular docking, providing a detailed understanding of how PTU inhibits TPO activity. Methods: The three-dimensional structure of TPO was obtained from Prosite and modelling by swissmodel and prepared for docking. The structure of PTU was optimized, and molecular docking was performed using AutoDock. The binding affinity, binding poses, and key interactions between TPO and PTU were analyzed. Visualization of the docking results was performed using PyMOL to identify critical residues involved in PTU binding. Results: The docking analysis revealed that PTU binds effectively to the active site of TPO with a binding affinity of -5.45 kcal/mol. The interaction involves coordination with the heme group and several key residues, including His239, which coordinates the heme, and Ser314, which forms hydrogen bonds with PTU. Additionally, hydrophobic interactions with residues Phe241 and Ile399 stabilize the binding of PTU in the active site. Conclusion: The docking study highlights the significant interactions between PTU and TPO, elucidating the molecular basis of TPO inhibition by PTU. The binding affinity and key interactions identified in this study provide a foundation for the design of more potent antithyroid drugs.

Resistance to chemotherapy presents a significant challenge in the treatment of ovarian cancer, particularly among patients receiving platinum-based therapies like cisplatin. Understanding the molecular mechanisms underlying this resistance is crucial for improving treatment effectiveness. This study utilized a combination of computational and experimental methods to identify genes associated with chemoresistance in ovarian cancer. We downloaded transcriptomic datasets GSE73935 and GSE51683 from the Gene Expression Omnibus (GEO) database and analyzed them for differentially expressed genes (DEGs). We selected common DEGs across both datasets and performed functional enrichment analysis on them. To validate key gene candidates, we conducted quantitative real-time PCR (qRT-PCR) on cisplatin-resistant and non-resistant A2780 ovarian cancer cell lines. Several genes exhibited consistent changes in expression across both datasets. Specifically, ABCB1 and TOP2A were significantly upregulated, while CDH1 was noticeably downregulated, suggesting their involvement in drug transport, cell proliferation, and epithelial–mesenchymal transition (EMT). We also identified additional genes unique to each dataset, such as BCL2, MMP9, BIRC5, and CDKN1A, which are linked to apoptosis and cell cycle regulation. Enrichment analyses connected these genes to mechanisms of platinum resistance and the p53 signaling pathway. qRT-PCR results confirmed substantial increases in ABCB1 and TOP2A expression in resistant cell lines. These findings provide potential predictive biomarkers and therapeutic targets for overcoming chemoresistance in ovarian cancer, and may inform the development of personalized treatment strategies in clinical practice.

Graves' disease is an autoimmune disorder in which the CD40-CD154 interaction plays a critical role in T-cell activation. In this study, in silico methods were employed to analyze the binding interactions of quinoline-benzoic acid derivatives (NSB, FSB, and NQB) with the CD40 receptor and to investigate the implications of specific CD40 mutations for drug efficacy. In this reseach conducted by molecular simulation approach with molecular docking Results Mutation analysis of CD40 identified alterations in key residues, such as R203C, which may impact ligand-independent activation and downstream TRAF binding, crucial for signal transduction. These findings highlight the therapeutic potential of quinoline-benzoic acid derivatives for targeting CD40 in Graves' disease, particularly in the context of receptor mutations. The integration of molecular docking, mutation analysis, and pharmacokinetic profiling provides a comprehensive framework for designing effective CD40-targeted therapies.

This study explores the molecular landscape of cervical cancer through the identification and analysis of differentially expressed genes (DEGs) from the GSE63514 dataset. A high-confidence protein–protein interaction (PPI) network was constructed using the STRING database (v11.5) and visualized via Cytoscape, identifying 178 nodes and 1,052 edges. Using the CytoHubba plugin, the top 10 hub genes—TOP2A, MKI67, CDK1, BUB1, CCNB1, CCNA2, AURKA, CDC20, PLK1, and RFC4—were highlighted based on degree centrality. These genes are predominantly associated with cell cycle regulation, DNA replication, and mitotic division, and are potentially valuable as biomarkers or therapeutic targets for cervical cancer. Functional enrichment using DAVID and Enrichr tools revealed significant involvement of DEGs in ATP binding, spindle microtubule formation, and protein kinase activity, particularly within the chromosome centromeric region and nucleoplasm. KEGG pathway analysis identified key associations with the cell cycle, DNA replication, p53 signaling, and complement and coagulation cascades. Further heatmap analysis of treatment responders versus non-responders demonstrated distinct gene expression profiles, particularly of immune-related genes like C1QA, C3, and SERPING1, and proliferative markers such as TOP2A and MKI67. These findings underscore the dual role of immune and proliferative pathways in cervical cancer progression and suggest their utility in developing predictive biomarkers and personalized treatment strategies.