TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Article Citation - WoS: 6Citation - Scopus: 6Sex Effect on the Correlation of Immunoglobulin G Glycosylation With Rheumatoid Arthritis Disease Activity(Tubitak Scientific & Technological Research Council Turkey, 2020-12-14) Ercan, AltanRheumatoid arthritis (RA) is a chronic autoimmune disease which affects females more than males with a presence of autoantibodies. Immunoglobulin G (IgG) produced by adaptive arm has 2 functional domains, Fc and Fab. The Fc domain binds Fc gamma receptors and C1q proteins of the innate arm. Therefore, the IgG Fc domain serves as a bridge between the innate and adaptive arms and is regulated by an evolutionarily conserved N-glycosylation with variable structures. These glycans are classified as agalactosylated G0, monogalactosylated G1, and digalactosylated G2, which are further modified by core-fucosylation (F) and bisecting N-acetylglucosamine (B) moieties such as G0F and G0FB. Interestingly, proinflammatory G0F is shown to be regulated by estrogen in vivo. Here, it is hypothesized that the regulation of G0F by estrogen contributes to sex dichotomy in RA by setting up the level of IgG-dependent inflammation and therefore, RA disease activity (Das28-CRP3). To investigate this hypothesis, IgG glycosylation was characterized in serum samples from active RA patients (n = 232) and healthy controls (n = 232) by serum N-glycan analysis using the high performance liquid chromatography. According to the results, the IgG Fc glycan phenotype originates predominantly from the structure of G0F, and both G0F and G0FB correlate with Das28-CRP3 in females, but not in males. In conclusion, IgG G0F-dependent inflammation differs in males and females, and these differences point to the differential regulation of inflammation by sex hormone estrogen via IgG glycosylation.Article Machine Learning Based Early Prediction of Type 2 Diabetes: A New Hybrid Feature Selection Approach Using Correlation Matrix With Heatmap and SFS(2022-04-30) Buyrukoglu, Selim; Akbaş, AyhanA new hybrid machine learning method for the prediction of type 2 diabetes is introduced and explained in detail. Also, outcomes are compared with similar researches. Early prediction of diabetes is crucial to take necessary measures (i.e. changing eating habits, patient weight control etc.), to defer the emergence of diabetes and to reduce the death rate to some extent and ease medical care professionals’ decision-making in preventing and managing diabetes mellitus. The purpose of this study is the creation of a new hybrid feature selection approach combination of Correlation Matrix with Heatmap and Sequential forward selection (SFS) to reveal the most effective features in the detection of diabetes. A diabetes data set with 520 instances and seven features were studied with the application of the proposed hybrid feature selection approach. The evaluation of the selected optimal features was measured by applying Support Vector Machines(SVM), Random Forest(RF), and Artificial Neural Networks(ANN) classifiers. Five evaluation metrics, namely, Accuracy, F-measure, Precision, Recall, and AUC showed the best performance with ANN (99.1%), F-measure (99.1%), Precision (99.3%), Recall (99.1%), and AUC (99.2%). Our proposed hybrid feature selection model provided a more promising performance with ANN compared to other machine learning algorithms.Article Citation - Scopus: 1Correlation of PAPP-A Values With Maternal Characteristics, Biochemical and Ultrasonographic Markers of Pregnancy(Marmara Univ, Fac Medicine, 2021-01-29) Kaymakcalan, Hande; Uzut, Ommu Gulsum; Harkonen, Juho; Bakir Gungor, Burcu; Bakir-gungor, Burcu; Söylemez, Ümmü GülsümObjective: Our aim is to investigate whether there is a correlation of pregnancy-associated plasma protein A (PAPP-A) values with other variables in pregnancy and maternal characteristics. Materials and Methods: We retrospectively analyzed the relation between the PAPP-A levels, demographics, biochemical and ultrasonographic markers of the first trimester screening of 11,842 pregnant women seen at a tertiary hospital between November 2002 and November 2008. Results: A significant difference between PAPP-A values of the diabetic and non-diabetic pregnant women were observed (p=0.0005, Mann-Whitney U test). In terms of weight, crown-rump length, Beta-hCG values, significant differences were observed between low and medium level PAPP-A subgroups and between low and high level PAPP-A subgroups. PAPP-A levels were found to differ significantly between the pregnant women of Caucasian origin and other racial origins. Conclusions: Pregnant women with different ethnic and medical backgrounds have different PAPP-A values and other markers of the aneuploidy screening. 'lb make patient specific risk predictions, understanding these interactions and differences is important. Future studies are needed to understand the pathopyhsiology behind these differences.Article Accurate Prediction of Residual Stresses in Machining of Inconel 718 Alloy through Crystal Plasticity Modelling(2023-03-01) Bal, Burak; Cetın, Barıs; Yılmaz, Okan Deniz; Kesriklioglu, Sinan; Kapçı, Mehmet Fazıl; Buyukcapar, RidvanArtık gerilmelerin belirlenmesi ve değerlendirilmesi, savunma, havacılık ve otomotiv endüstrilerinde kullanılan bileşenlerin arızalanmasını önlemede çok önemlidir. Bu çalışmanın amacı, Inconel 718'in işlenmesi sırasında oluşan artık gerilmeleri doğru bir şekilde tahmin etmek için bir malzeme modeli sunmaktır. Ortogonal talaşlı imalat testleri, çeşitli kesme ve ilerleme hızlarında gerçekleştirilerek, Inconel 718'in işlenmesinden sonraki artık gerilmeler, X-Ray ışın kırınımı ile karakterize edildi. Bu süper alaşımın mikroyapısal girdilerini ticari olarak temin edilebilen bir sonlu eleman yazılımına (Deform 2D) aktarmak için bir viskoplastik kendi içinde tutarlı kristal plastisite modeli geliştirildi. Ayrıca simülasyonlar klasik Johnson - Cook malzeme modeli ile aynı işleme parametrelerinde yapıldı. Bu çalışmada elde edilen simülasyon ve deneysel sonuçlar, kristal plastisite tabanlı çok ölçekli ve çok ölçekli malzeme modelinin, mevcut modele kıyasla Inconel 718'in işleme kaynaklı kalıntı gerilmelerinin tahmin doğruluğunu önemli ölçüde geliştirdiğini ve yüzey kusurlarını en aza indirmek için kullanılabileceğini göstermiştir. Geliştirilen bu model, kesilmesi zor malzemelerin işlenmesinde yüzey kusurlarını ve üretim denemelerinin maliyetini en aza indirmek için kullanılabilir.