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Department: search.filters.department.Department of Computer EngineeringSubject: search.filters.subject.Medicine

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    A simplified grid method of camera-captured images may be a practical alternative if validated ai-assisted counting is inaccessible
    (Elsevier Science Inc, 2023) Adsay, David; Eren, Ozgur; Basturk, Olca; Department of Computer Engineering; Esmer, Rohat; Armutlu, Ayşe; Taşkın, Orhun Çığ; Koç, Soner; Tezcan, Nuray; Aktaş, Berk Kaan; Kulaç, İbrahim; Kapran, Yersu; Demir, Çiğdem Gündüz; Saka, Burcu; Department of Computer Engineering; School of Medicine; Graduate School of Sciences and Engineering; College of Engineering
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    An evaluation of DNA methylation levels and sleep in relation to hot flashes: a cross-sectional study
    (MDPI, 2024) Ozcivit Erkan, Ipek Betul; Seyisoglu, Hasan Hakan; Senel, Gulcin Benbir; Karadeniz, Derya; Ozdemir, Filiz; Kalayci, Aysel; Seven, Mehmet; Department of Computer Engineering; İnan, Neslihan Gökmen; Department of Computer Engineering; College of Engineering
    Objectives: We aimed to evaluate the DNA methylation levels in perimenopausal and postmenopausal women, measured through Long Interspersed Element-1 (LINE-1) and Alu, and the sleep parameters in relation to the presence of hot flashes (HFs). Methods: This cross-sectional study included 30 peri- or postmenopausal women aged between 45 and 55. The menopausal status was determined according to STRAW + 10 criteria and all participants had a low cardiovascular disease (CVD) risk profile determined by Framingham risk score. The sample was divided into two groups based on the presence or absence of HFs documented in their medical history during their initial visit: Group 1 (n = 15) with HFs present and Group 2 (n = 15) with HFs absent. The patients had polysomnography test and HFs were recorded both by sternal skin conductance and self-report overnight. Genomic DNA was extracted from the women's blood and methylation status was analyzed by fluorescence-based real-time quantitative PCR. The quantified value of DNA methylation of a target gene was normalized by beta-actin. The primary outcome was the variation in methylation levels of LINE-1 and Alu and sleep parameters according to the presence of HFs. Results: LINE-1 and Alu methylation levels were higher in Group 1 (HFs present), although statistically non-significant. LINE-1 methylation levels were negatively correlated with age. Sleep efficiency was statistically significantly lower for women in Group 1 (HFs present) (74.66% +/- 11.16% vs. 82.63% +/- 7.31%;p = 0.03). The ratio of duration of awakening to total sleep time was statistically significantly higher in Group 1 (HFs present) (22.38% +/- 9.99% vs. 15.07% +/- 6.93, p = 0.03). Objectively recorded hot flashes were significantly higher in Group 1 (4.00 +/- 3.21 vs. 1.47 +/- 1.46, p = 0.03). None of the cases in Group 2 self-reported HF despite objectively recorded HFs during the polysomnography. The rate of hot flash associated with awakening was 41.4% in the whole sample. Conclusions: Women with a history of hot flashes exhibited lower sleep efficiency and higher awakening rates. Although a history of experiencing hot flashes was associated with higher LINE-1 and Alu methylation levels, no statistical significance was found. Further studies are needed to clarify this association. This study was funded by the Scientific Research Projects Coordination Unit of Istanbul University-Cerrahpasa. Project number: TTU-2021-35629.
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    PublicationOpen Access
    Identification of interconnected markers for T-cell acute lymphoblastic leukemia
    (Hindawi, 2013) Ng, Özden Hatırnaz; Department of Chemical and Biological Engineering; Department of Computer Engineering; Maiorov, Emine Güven; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; N/A; 26605; 8745
    T-cell acute lymphoblastic leukemia (T-ALL) is a complex disease, resulting from proliferation of differentially arrested immature T cells. The molecular mechanisms and the genes involved in the generation of T-ALL remain largely undefined. In this study, we propose a set of genes to differentiate individuals with T-ALL from the nonleukemia/healthy ones and genes that are not differential themselves but interconnected with highly differentially expressed ones. We provide new suggestions for pathways involved in the cause of T-ALL and show that network-based classification techniques produce fewer genes with more meaningful and successful results than expression-based approaches. We have identified 19 significant subnetworks, containing 102 genes. The classification/prediction accuracies of subnetworks are considerably high, as high as 98%. Subnetworks contain 6 nondifferentially expressed genes, which could potentially participate in pathogenesis of T-ALL. Although these genes are not differential, they may serve as biomarkers if their loss/gain of function contributes to generation of T-ALL via SNPs. We conclude that transcription factors, zinc-ion-binding proteins, and tyrosine kinases are the important protein families to trigger T-ALL. These potential disease-causing genes in our subnetworks may serve as biomarkers, alternative to the traditional ones used for the diagnosis of T-ALL, and help understand the pathogenesis of the disease.