Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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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: 16Citation - Scopus: 15Role of AHR, NF-kB and CYP1A1 Crosstalk With the X Protein of Hepatitis B Virus in Hepatocellular Carcinoma Cells(Elsevier, 2023-02) Celik-Turgut, Gurbet; Olmez, Nazmiye; Koc, Tugba; Ozgun-Acar, Ozden; Semiz, Asli; Dodurga, Yavuz; Sen, AlaattinIn this study, it was aimed to elucidate the interaction between aryl hydrocarbon receptor (AHR), nuclear factor -kappa B (NF-kB), and cytochrome P4501A1 (CYP1A1) with hepatitis B virus X protein (HBX) in a human liver cancer cell line (HepG2) transfected with HBX. First, AHR, NF-kB, and CYP1A1 genes were cloned into the appropriate region of the CheckMate mammalian two-hybrid recipient plasmids using a flexi vector system. Renilla and firefly luciferases were quantified using the dual-luciferase reporter assay system to measure the interactions. Secondly, transient transfections of CYP1A1 and NF-kB (RelA) were performed into HBX-positive and HBX-negative HepG2 cells. The mRNA expression of CYP1A1 and NF-kB genes were confirmed with RT-PCR, and cell viability was measured by WST-1. Further verification was assessed by measuring the activity and protein level of CYP1A1. Additionally, CYP1A1/HBX protein-protein interactions were performed with co-immunoprecipitation, which demonstrated no interaction. These results have clearly shown that the NF-kB and AHR genes interact with HBX without involving CYP1A1 and HBX protein-protein interactions. The present study confirms that AHR and NF-kB interaction plays a role in the HBV mechanism mediated via HBX and coordinating the carcinogenic or inflammatory responses; still, the CYP1A1 gene has no effect on this interaction.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: 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: 1Magnus Series Expansion Method for Solving Nonhomogeneous Stiff Systems of Ordinary Differential Equations(Elsevier, 2016) Atay, Mehmet T.; Eryilmaz, Aytekin; Komez, Sure; Köme, SureIn this paper, Magnus Series Expansion Method, which is based on Lie Groups and Lie algebras is proposed with different orders to solve nonhomogeneous stiff systems of ordinary differential equations. Using multivariate Gaussian quadrature, fourth (MG4) and sixth (MG6) order method are presented. Then, it is applied to nonhomogeneous stiff systems using different step sizes and stiffness ratios. In addition, approximate and exact solutions are demonstrated with figures in detail. Moreover, absolute errors are illustrated with detailed tables.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 - WoS: 3Citation - Scopus: 3Designed Optimization of Photoluminescence Emission for Carbon Dots With Bright Blue Emission at 416 NM and Mono-Exponential Decay Lifetime(Elsevier, 2025-09) Ruwaih, Mohammed Abbas; Soheyli, Ehsan; Naji, Jalil; Mutlugun, Evren; Kikhavani, Tavan; Sahraei, Reza; Abbas Ruwaih, MohammedThe presented study introduces optimized blue-emissive carbon dots (CDs) with high photoluminescence efficiency up to 65 % at 416 nm, large Stokes shift (69 nm), and full-width at half maximum (FWHM) of 73 nm. Xray photoelectron spectroscopy confirmed the formation of carbon-based bonds as the main component of CDs, with reliable amounts of O, S, and N as dopant components. These features, along with single-exponential time-decay profile at long average lifetime of 10.05 ns, supported the significant role of uniformly distributed mid-gap energy levels in the recombination process. The simplicity, low-cost, non-toxicity, and short reaction time of CDs, along with their excellent emission properties in the deep-blue region, make them suitable for use in environmental monitoring and high-contrast bioimaging.Data Paper Citation - WoS: 34Citation - Scopus: 41Big Data Acquired by Internet of Things-Enabled Industrial Multichannel Wireless Sensors Networks for Active Monitoring and Control in the Smart Grid Industry 4.0(Elsevier, 2021-04) Faheem, Muhammad; Fizza, Ghulam; Ashraf, Muhammad Waqar; Butt, Rizwan Aslam; Ngadi, Md. Asri; Gungor, Vehbi CagriSmart Grid Industry 4.0 (SGI4.0) defines a new paradigm to provide high-quality electricity at a low cost by reacting quickly and effectively to changing energy demands in the highly volatile global markets. However, in SGI4.0, the reliable and efficient gathering and transmission of the observed information from the Internet of Things (IoT)-enabled Cyberphysical systems, such as sensors located in remote places to the control center is the biggest challenge for the Industrial Multichannel Wireless Sensors Networks (IMWSNs). This is due to the harsh nature of the smart grid environment that causes high noise, signal fading, multipath effects, heat, and electromagnetic interference, which reduces the transmission quality and trigger errors in the IMWSNs. Thus, an efficient monitoring and real-time control of unexpected changes in the power generation and distribution processes is essential to guarantee the quality of service (QoS) re-quirements in the smart grid. In this context, this paper de-scribes the dataset contains measurements acquired by the IMWSNs during events monitoring and control in the smart grid. This work provides an updated detail comparison of our proposed work, including channel detection, channel assign-ment, and packets forwarding algorithms, collectively called CARP [1] with existing G-RPL [2] and EQSHC [3] schemes in the smart grid. The experimental outcomes show that the dataset and is useful for the design, development, testing, and validation of algorithms for real-time events monitoring and control applications in the smart grid. (C) 2021 The Authors. Published by Elsevier Inc.Data Paper Citation - WoS: 26Citation - Scopus: 33Big Datasets of Optical-Wireless Cyber-Physical Systems for Optimizing Manufacturing Services in the Internet of Things-Enabled Industry 4.0(Elsevier, 2022-06) Faheem, Muhammad; Butt, Rizwan AslamThe Industry 4.0 revolution is aimed to optimize the product design according to the customers' demand, quality requirements and economic feasibility. Industry 4.0 employs advanced two-way communication technologies for optimizing the manufacturing process to increase the sales of the products and revenues to cope the existing global economy issues. In Industry 4.0, big data obtained from the Internet of Things (IoT)-enabled industrial Cyber-Physical Systems (CPS) plays an important role in enhancing the system service performance to boost the productivity with enhanced quality of customer experience. This paper presents the big datasets obtained from the Internet of things (IoT)-enabled Optical Wireless Sensor Networks (OWSNs) for optimizing service systems' performance in the electronics manufacturing Industry 4.0. The updated raw and analyzed big datasets of our published work [3] contain five values namely, data delivery, latency, congestion, throughput, and packet error rate in OWSNs. The obtained dataset are useful for optimizing the service system performance in the electronics manufacturing Industry 4.0. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)