PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Citation - Scopus: 1Possible Drug-Drug Interactions Between Mesalamine and Tricyclic Antidepressants Through CYP2D6 Metabolism - in Silico and in Vitro Analyses(Georg Thieme Verlag, 2025-04-01) Ozen, Melek B.; Gazioğlu, Işil; Ozgun-Acar, Özden; Guner, Hüseyin; Semiz, Gürkan; Sen, Alaattin; Ozgun Acar, OzdenMesalamine (mesalazine, 5-aminosalicylic acid, 5-ASA) is an essential anti-inflammatory agent both used for therapy and as a remission control in patients with inflammatory bowel diseases (IBD) such as ulcerative colitis (UC). Tricyclic antidepressants (TCAs) are used to alleviate remaining symptoms in patients already receiving IBD therapy or with quiescent inflammation. The cytochrome P4502D6 enzyme is involved in the metabolism of TCAs. Hence, it is crucial to investigate the role of CYP2D6 in 5-ASA metabolism. Initially, in silico analysis involving the docking of 5-ASA to CYP2D6 and molecular dynamics simulations was conducted. Next, the rate of O-demethylation of a nonfluorescent probe 3-[2-(N,N-diethyl-N-methylammonium)-ethyl]-7-methoxy-4-methylcoumarin (AMMC) into a fluorescent metabolite AMHC (3-[2-(N,N-diethyl-N-methylammonium)ethyl]-7-hydroxy-4-methylcoumarin) was optimized with baculosomes co-expressing human CYP2D6 and human P450 oxidoreductase (hCPR) to monitor CYP2D6 activity in a microtiter plate assay. The apparent Km and Vmax were found to be 1.30 μM and 32.68 pmol/min/mg of protein for the O-demethylation of AMMC to AMHC, and the reaction was linear for 40 min. Then, nonselective inhibition of CYP2D6 activity with various concentrations of 5-ASA was detected. Finally, the conversion of AMMC to metabolites was analyzed by HPLC-ESI-MS/MS spectrometry, and none were identified. Thus, this study suggests that concurrent use of mesalamine with TCA may lead to adverse effects, and CYP2D6 genotyping should be routinely performed on these patients to eliminate possible threats. © 2025 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 1Measurement of Autophagic Activity in Cancer Cells With Flow Cytometric Analysis Using Cyto-Id Staining(Humana Press Inc., 2024) Şansaçar, Merve; Gencer Akçok, Emel BaşakAutophagy is an evolutionarily conserved process providing the energy that cells need to survive, especially in stress situations, through catabolic processes. Considering the dual role of autophagy in cancer cells depending on the cellular context, it is crucial to comprehend the effect of drug candidates put forward to prevent cancer through the autophagy pathway. The CYTO-ID® Autophagy Detection Kit allows a rapid, specific and quantitative measurement of autophagic activity at the cellular level using a 488 nm-excitable green fluorescent detection reagent via flow cytometer. In this chapter, we present the CYTO-ID® Autophagy Detection method with a stepwise protocol to monitor the autophagy flux after the application of any compound to suspension cancer cell lines with flow cytometric analysis. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 16Citation - Scopus: 18Genomic, Probiotic, and Metabolic Potentials of Liquorilactobacillus Nagelii AGA58, a Novel Bacteriocinogenic Motile Strain Isolated From Lactic Acid-Fermented Shalgam(Soc Bioscience Bioengineering Japan, 2023-01) Yetiman, Ahmet Evren; Ortakci, FatihThis study aimed to perform genomic, probiotic, and metabolic characterization of a novel Liquorilactobacillus nagelii AGA58 isolated from a lactic acid-fermented shalgam beverage to understand its metabolic potentials and probiotic features. AGA58 is gram-positive, motile, catalase-negative and appears as short rods under the light-microscope. The AGA58 chromosome comprises a single linear chromosome of 2,294,635 bp that is predicted to carry 2135 coding sequences, including 45 tRNA genes, 3 mRNA, and 3 rRNA operons. The genome has a GDC content of 36.9%, including 55 pseudogenes and a single intact prophage. AGA58 is micro-anaerobic due to achieving a shorter doubling time and faster growth rate than micro-aerophilic conditions. It carries flagellar biosynthesis protein-encoding genes predicting motile behavior, which was confirmed with the in vitro motility test. AGA58 is an obligatory homofermentative lactobacillus that can ferment hexose sugars such as galactose, glucose, fructose, sucrose, mannose, N-acetyl glucosamine, maltose, and trehalose to lactate through glycolysis. No acid production from pentoses implies that five-carbon sugars are being utilized for purine and pyrimidine synthesis. Putative pyruvate metabolism revealed formate, malate, oxaloacetate, acetate, acetaldehyde, acetoin, and lactate forms from pyruvate. AGA58 is predicted to encode the LuxS gene and biosynthesis of class IIa and Blp family class-II bacteriocins suggesting this bacterium's antimicrobial potential, linked to antagonism tests that AGA58 can inhibit Escherichia coli ATCC 43895, Salmonella enterica serovar Typhimurium ATCC 14028, and Klebsiella pneumonia ATCC 13883. Moreover, AGA58 is tolerant to acid and bile concentrations simulating the human gastrointestinal conditions depicting the probiotic potential of the organism as the first report in literature within the same species. (c) 2022, The Society for Biotechnology, Japan. All rights reserved.Article Evaluation of HOTAIR, HOXD8, HOXD9, HOXD11 Gene Expression Levels in Turkish Patients With Acute and Chronic Myeloid Leukemia: A Single Center Experience(Cellular and Molecular Biology Association, 2024-11-27) Saraymen, Esma; Erdem, Yakut; Akalin, Hilal Ünlü; Taşçıoğlu, Nazife; Saraymen, Berkay; Celik, Serhat; Özkul, Yusuf T.Homeobox (HOX) transcript antisense RNA (HOTAIR) and HOX genes are reported to be more expressed in various cancers in humans in recent studies. The role of HOTAIR and HOXD genes in acute myeloid leukemia (AML) and chronic myeloid leukemia (CML) is not well known. In this study, expression levels of HOXD8, HOXD9 and HOXD11 from HOXD gene family and HOTAIR were determined from peripheral blood samples of 30 AML and 30 CML patients and 20 healthy volunteers by quantitative Real Time PCR. We determined that the expression levels of HOXD9 and HOXD11 in the AML patients were significantly lower than the control group (p<0.001 and p=0.002, respectively). There was no significant difference in the expression levels of HOTAIR and HOXD8 when compared to the control group. In the CML patients there was a significant increase in the expression level of HOTAIR when compared to the control group (p=0.002). The expression levels of HOXD9 and HOXD11 were found to be significantly lower than the control group (p<0.001). Our study showed that HOTAIR may not be a biomarker in the diagnosis and is not significantly correlated with the clinicopathological prognostic characteristics of AML. Additionally; it can be said that HOTAIR is oncogenic by suppressing the expression of HOXD9 and HOXD11 but not HOXD8 in CML patients. The expression profiles of HOTAIR may be a potential biomarker in the diagnosis of CML patients in predicting and monitoring drug resistance. © 2025 Elsevier B.V., All rights reserved.Article Citation - Scopus: 4CCPred: Global and Population-Specific Colorectal Cancer Prediction and Metagenomic Biomarker Identification at Different Molecular Levels Using Machine Learning Techniques(Elsevier Ltd, 2024-11) Bakir-Güngör, Burcu; Temiz, Mustafa; Inal, Yasin; Cicekyurt, Emre; Yousef, MalikColorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the complex interplay between disease development and metagenomic data is essential for CRC diagnosis and treatment. Current computational models employ machine learning to identify metagenomic biomarkers associated with CRC, yet there is a need to improve their accuracy through a holistic biological knowledge perspective. This study aims to evaluate CRC-associated metagenomic data at species, enzymes, and pathway levels via conducting global and population-specific analyses. These analyses utilize relative abundance values from human gut microbiome sequencing data and robust classification models are built for disease prediction and biomarker identification. For global CRC prediction and biomarker identification, the features that are identified by SelectKBest (SKB), Information Gain (IG), and Extreme Gradient Boosting (XGBoost) methods are combined. Population-based analysis includes within-population, leave-one-dataset-out (LODO) and cross-population approaches. Four classification algorithms are employed for CRC classification. Random Forest achieved an AUC of 0.83 for species data, 0.78 for enzyme data and 0.76 for pathway data globally. On the global scale, potential taxonomic biomarkers include ruthenibacterium lactatiformanas; enzyme biomarkers include RNA 2′ 3′ cyclic 3′ phosphodiesterase; and pathway biomarkers include pyruvate fermentation to acetone pathway. This study underscores the potential of machine learning models trained on metagenomic data for improved disease prediction and biomarker discovery. The proposed model and associated files are available at https://github.com/TemizMus/CCPRED. © 2024 Elsevier B.V., All rights reserved.