WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 1Citation - Scopus: 1The Impact of COVID-19 on Healthcare Utilization in Turkey(Elsevier, 2024-09) Ugur, Zeynep B.; Durak, AysenurObjectives: This study investigates the impact of the COVID-19 pandemic on healthcare utilization in Turkey. Methods: We utilized individual-level data derived from Turkish Statistical Institute 's annual surveys between 2014 and 2022 and estimated probit regression models. Results: We find that COVID-19 pandemic reduced healthcare utilization by 11.8% after taking into account a large set of background variables. Although our study finds that the elderly and those with health problems are more likely to use healthcare services under normal circumstances, the COVID-19 pandemic has caused notable drops in the healthcare utilization among the elderly (-6.5%) and those with health problems (-3.8%). Although those without health insurance had lower utilization of healthcare services before the pandemic, during the pandemic they were not particularly hit. Conclusion: We conclude that the pandemic did not lower the healthcare utilization in Turkey because of the supply constraints. Also, the evidence points to the reduced demand due to the fear of contagion rather than financial concerns.Article Citation - WoS: 27Citation - Scopus: 31Proteomic Fertility Markers in Ram Sperm(Elsevier, 2021-12) Hitit, Mustafa; Ozbek, Mehmet; Ayaz-Guner, Serife; Guner, Huseyin; Oztug, Merve; Bodu, Mustafa; Kaya, AbdullahPrecise estimation of ram fertility is important for sheep farming to sustain reproduction efficiency and profitability of production. There, however, is no conventional method to accurately predict ram fertility. The objective of this study, therefore, was to ascertain proteomic profiles of ram sperm having contrasting fertility phenotypes. Mature rams (n = 66) having greater pregnancy rates than average (89.4 +/- 7.2%) were assigned into relatively-greater fertility (GF; n = 31; 94.5 +/- 2.8%) whereas those with less-than-average pregnancy rates were assigned into a lesserfertility (LF; n = 25; 83.1 +/- 5.73%; P = 0.028) group. Sperm samples from the outlier greatestand least-fertility rams (n = 6, pregnancy rate; 98.4 +/- 1.8% and 76.1 +/- 3.9%) were used for proteomics assessments utilizing Label-free LC-MS/MS. A total of 997 proteins were identified, and among these, 840 were shared by both groups, and 57 and 93 were unique to GF and LF, respectively. Furthermore, 190 differentially abundant proteins were identified; the abundance of 124 was larger in GF while 66 was larger in LF rams. The GF ram sperm had 79 GO/pathway terms in ten major biological networks while there were 47 GO/pathway terms in six biological networks in sperm of LF rams. Accordingly, differential abundances of sperm proteins between sperm of GF and LF rams were indicative of functional implications of sperm proteome on male fertility. The results of this study emphasize there are potential protein markers for evaluation of semen quality and estimation of ram sperm fertilizing capacity.Article Citation - WoS: 3Citation - Scopus: 4Prediction of Biomechanical Properties of Ex Vivo Human Femoral Cortical Bone Using Raman Spectroscopy and Machine Learning Algorithms(Elsevier, 2025-09) Unal, Mustafa; Unlu, Ramazan; Uppuganti, Sasidhar; Nyman, Jeffry S.This study applied Raman spectroscopy (RS) to ex vivo human cadaveric femoral mid-diaphysis cortical bone specimens (n = 118 donors; age range 21-101 years) to predict fracture toughness properties via machine learning (ML) models. Spectral features, together with demographic variables (age, sex) and structural parameters (cortical porosity, volumetric bone mineral density), were fed into support vector regression (SVR), extreme tree regression (ETR), extreme gradient boosting (XGB), and ensemble models to predict fracture-toughness metrics such as crack-initiation toughness (Kinit) and energy-to-fracture (J-integral). Feature selection was based on Raman-derived mineral and organic matrix parameters, such as nu 1Phosphate (PO4)/CH2-wag, nu 1PO4/ Amide I, and others, to capture the complex composition of bone. Our results indicate that ensemble models consistently outperformed individual models, with the best performance for crack initiation toughness (Kinit) prediction being achieved using the ensemble approach. This yielded a coefficient of determination (R2) of 0.623, root-mean squared error (RMSE) of 1.320, mean absolute error (MAE) of 1.015, and mean percentage absolute error (MAPE) of 0.134. For prediction of the overall energy to propagate a crack (J-integral), the XGB model achieved an R2 of 0.737, RMSE of 2.634, MAE of 2.283, and MAPE of 0.240. This study highlights the importance of incorporating mineral quality properties (MP) and organic matrix properties (OMP) for enhanced prediction accuracy. This work represents the first-ever study combining Raman spectroscopy with other clinical and structural features to predict fracture toughness of human cortical bone, demonstrating the potential of artificial intelligence (AI) and ML in advancing bone research. Future studies could focus on larger datasets and more advanced modeling techniques to further improve predictive capabilities.Article Citation - WoS: 4Citation - Scopus: 5Novel Insights Into Bacillus Thuringiensis: Beyond Its Role as a Bioinsecticide(Elsevier, 2025-03) Jouzani, Gholamreza Salehi; Sharafi, Reza; Argentel-Martinez, Leandris; Penuelas-Rubio, Ofelda; Ozkan, Ceyda; Incegul, Bengisu; Azizoglu, Ugur; Salehi Jouzani, GholamrezaThis review explores the diverse applications of Bacillus thuringiensis (Bt) beyond its traditional role as a bioinsecticide. Bt produces a variety of compounds with distinct chemical structures and biological activities. These include antimicrobial agents effective against plant pathogens and bioactive compounds that promote plant growth through the production of siderophores, hormones, and enzymes. Additionally, Bt's industrial potential is highlighted, encompassing biofuel production, bioplastics, nanoparticle synthesis, food preservation, anticancer therapies, and heavy metal bioremediation. This critical analysis emphasizes recent advancements and applications, providing insights into Bt's role in sustainable agriculture, biotechnology, and environmental management.Article Citation - WoS: 2Citation - Scopus: 3Multi Fragment Melting Analysis System (MFMAS) for One-Step Identification of Lactobacilli(Elsevier, 2020-10) Kesmen, Zulal; Kilic, Ozge; Gormez, Yasin; Celik, Mete; Bakir-Gungor, BurcuThe accurate identification of lactobacilli is essential for the effective management of industrial practices associated with lactobacilli strains, such as the production of fermented foods or probiotic supplements. For this reason, in this study, we proposed the Multi Fragment Melting Analysis System (MFMAS)-lactobacilli based on high resolution melting (HRM) analysis of multiple DNA regions that have high interspecies heterogeneity for fast and reliable identification and characterization of lactobacilli. The MFMAS-lactobacilli is a new and customized version of the MFMAS, which was developed by our research group. MFMAS-lactobacilli is a combined system that consists of i) a ready-to-use plate, which is designed for multiple HRM analysis, and ii) a data analysis software, which is used to characterize lactobacilli species via incorporating machine learning techniques. Simultaneous HRM analysis of multiple DNA fragments yields a fingerprint for each tested strain and the identification is performed by comparing the fingerprints of unknown strains with those of known lactobacilli species registered in the MFMAS. In this study, a total of 254 isolates, which were recovered from fermented foods and probiotic supplements, were subjected to MFMAS analysis, and the results were confirmed by a combination of different molecular techniques. All of the analyzed isolates were exactly differentiated and accurately identified by applying the single-step procedure of MFMAS, and it was determined that all of the tested isolates belonged to 18 different lactobacilli species. The individual analysis of each target DNA region provided identification with an accuracy range from 59% to 90% for all tested isolates. However, when each target DNA region was analyzed simultaneously, perfect discrimination and 100% accurate identification were obtained even in closely related species. As a result, it was concluded that MFMAS-lactobacilli is a multi-purpose method that can be used to differentiate, classify, and identify lactobacilli species. Hence, our proposed system could be a potential alternative to overcome the inconsistencies and difficulties of the current methods.Article Citation - WoS: 2Citation - Scopus: 2Membrane Binding and Lipid-Protein Interaction of the C2 Domain From Coagulation Factor V(Elsevier, 2024) Ohkubo, Y. Zenmei; Radulovic, Peter W.; Kahira, Albert N.; Madsen, Jesper J.Anchoring of coagulation factors to anionic regions of the membrane involves the C2 domain as a key player. The rate of enzymatic reactions of the coagulation factors is increased by several orders of magnitude upon membrane binding. However, the precise mechanisms behind the rate acceleration remain unclear, primarily because of a lack of understanding of the conformational dynamics of the C2-containing factors and corresponding complexes. We elucidate the membrane-bound form of the C2 domain from human coagulation factor V (FV-C2) by characterizing its membrane binding the specific lipid -protein interactions. Employing all-atom molecular dynamics simulations and leveraging the highly mobile membrane-mimetic (HMMM) model, we observed spontaneous binding of FV-C2 to a phosphatidylserine (PS)-containing membrane within 2-25 ns across twelve independent simulations. FV-C2 interacted with the membrane through three loops (spikes 1-3), achieving a converged, stable orientation. Multiple HMMM trajectories of the spontaneous membrane binding provided extensive sampling and ample data to examine the membrane-induced effects on the conformational dynamics of C2 as well as specific lipid -protein interactions. Despite existing crystal structures representing presumed "open" and "closed" states of FV-C2, our results revealed a continuous distribution of structures between these states, with the most populated structures differing from both "open" and "closed" states observed in crystal environments. Lastly, we characterized a putative PS-specific binding site formed by K23, Q48, and S78 located in the groove enclosed by spikes 1-3 (PS-specificity pocket), suggesting a different orientation of a bound headgroup moiety compared to previous proposals based upon analysis of static crystal structures.Article Citation - WoS: 18Citation - Scopus: 19Infrared Multiple Photon Dissociation Spectroscopy of Protonated Histidine and 4-Phenylmidazole(Elsevier, 2012-12) Citir, Murat; Hinton, Christopher S.; Oomens, Jos; Steill, Jeffrey D.; Armentrout, P. B.The gas-phase structures of protonated histidine (His) and the side-chain model, protonated 4-phenyl imidazole (PhIm), are examined by infrared multiple photon dissociation (IRMPD) action spectroscopy utilizing light generated by the free electron laser FELIX. To identify the structures present in the experimental studies, the measured IRMPD spectra are compared to spectra calculated at a B3LYP/6-311+G(d,p) level of theory. Relative energies of various conformers are provided by single point energy calculations carried out at the B3LYP, B3P86, and MP2(full) levels using the 6-311+G(2d,2p) basis set. On the basis of these experiments and calculations, the IRMPD action spectrum for H+(His) is characterized by a mixture of [N-pi,N-alpha] and [N-pi,CO] conformers, with the former dominating. These conformers have the protonated nitrogen atom of imidazole adjacent to the side-chain (N-pi) hydrogen bonding to the backbone amino nitrogen (N-alpha) and to the backbone carbonyl oxygen, respectively. Comparison of the present results to recent IRMPD studies of protonated histamine, the radical His(center dot+) cation, H+(HisArg), H-2(2+)(HisArg), and M+(His), where M+ = Li+, Na+, K+, Rb+, and Cs+, allows evaluation of the vibrational motions associated with the observed bands. (c) 2012 Elsevier B.V. All rights reserved.Article Citation - Scopus: 2CompreCity: Accelerating the Traveling Salesman Problem on GPU With Data Compression(Elsevier, 2025-05) Yalcin, Salih; Usul, Hamdi Burak; Yalcin, GulayTraveling Salesman Problem (TSP) is one of the significant problems in computer science which tries to find the shortest path for a salesman who needs to visit a set of cities and it is involved in many computing problems such as networks, genome analysis, logistics etc. Using parallel executing paradigms, especially GPUs, is appealing in order to reduce the problem solving time of TSP. One of the main issues in GPUs is to have limited GPU memory which would not be enough for the entire data. Therefore, transferring data from the host device would reduce the performance in execution time. In this study, we applied three data compression methodologies to represent cities in the TSP such as (1) Using Greatest Common Divisor (2) Shift Cities to the Origin (3) Splitting Surface to Grids. Therefore, we include more cities in GPU memory and reduce the number of data transfers from the host device. We implement our methodology in Iterated Local Search (ILS) algorithm with 2-opt and The Lin-Kernighan-Helsgaun (LKH) Algorithm. We show that our implementation presents more than 25% performance improvement for both algorithms.Article Citation - WoS: 4Citation - Scopus: 5Beyond Visual Cues: Emotion Recognition in Images With Text-Aware Fusion(Elsevier, 2025-04) Sungur, Kerim Serdar; Bakal, GokhanSentiment analysis is a widely studied problem for understanding human emotions and potential outcomes. As it can be performed over textual data, working on visual data elements is also critically substantial to examining the current emotional status. In this effort, the aim is to investigate any potential enhancements in sentiment analysis predictions through visual instances by integrating textual data as additional knowledge reflecting the contextual information of the images. Thus, two separate models have been developed as image-processing and text-processing models in which both models were trained on distinct datasets comprising the same five human emotions. Following, the outputs of the individual models' last dense layers are combined to construct the hybrid multimodel empowered by visual and textual components. The fundamental focus is to evaluate the performance of the hybrid model in which the textual knowledge is concatenated with visual data. Essentially, the hybrid model achieved nearly a 3% F1-score improvement compared to the plain image classification model utilizing convolutional neural network architecture. In essence, this research underscores the potency of fusing textual context with visual information to refine sentiment analysis predictions. The findings not only emphasize the potential of a multi-modal approach but also spotlight a promising avenue for future advancements in emotion analysis and understanding.Article A Novel Germline Pregnane X Receptor (PXR) Variant Predisposing to Hodgkin Lymphoma in Two Siblings(Elsevier, 2024-12) Khodzhaev, Khusan; Sudutan, Tugce; Erbilgin, Yucel; Saritas, Merve; Yegen, Gulcin; Bozkurt, Ceyhun; Kebudi, RejinHodgkin's lymphoma (HL) is the most common cancer in adolescents and young adults. A family history of HL increases the risk of developing HL in other family members. Identification of genetic predisposition variants in HL is important for understanding disease aetiology, prognosis, and response to treatment. Aberrant activation of the NF-kappa B pathway is a hallmark feature of HL, contributing to the survival and proliferation of the malignant cells' characteristic of HL. The family with multiple consanguineous marriages with siblings of diagnosed HL was examined by whole-exome sequencing. We found a germline homozygous variation in the PXR ligand binding domain (NM_003889.3:c.811G>A, p.(Asp271Asn)), which was classified as pathogenic by prediction tools and segregated in HL cases. Increased PXR expression was found in homozygous variant carriers compared to heterozygous carriers by quantitative real time PCR (qRT-PCR) and immunofluorescence staining of patients' formalin-fixed paraffin-embedded tissues showed upregulation of PXR, particularly in Hodgkin Reed/Sternberg (HRS) cells. Patients with homozygous PXR variant showed significantly high expression compared to PXR wild-type HL, heterozygous and controls (p = 0.0001, p = 0.0004 and p = 0.0001, respectively). PXR homozygous HRS cells had significantly higher PXR expression compared to PXR wild-type HRS cells (p < 0.0001, 3.27-fold change). Albeit PXR's prominent expression in cytoplasm of HRS cells, homozygous PXR HRS cells showed increased PXR expression in nucleus (p < 0.001). PXR is a member of the nuclear receptor superfamily and previous studies have demonstrated a pleiotropic effect of PXR on malignant transformation. Expression analysis showed that cell proliferation, apoptosis and inflammation related genes were deregulated, in homozygous PXR HL cases. This study provided clinical evidence to previously reported Sxr(-/-) mice model that develop multifocal lymphomas, had an aberrantly increased NF-kappa B expression and consistent inflammation. Further functional studies are needed to elucidate the exact mechanisms of action of PXR in HL pathogenesis.