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Article Citation - WoS: 9Citation - Scopus: 10Impact of Hospital-Acquired Acute Kidney Injury on Covid-19 Outcomes in Patients With and Without Chronic Kidney Disease: a Multicenter Retrospective Cohort Study(Tubitak Scientific & Technological Research Council Turkey, 2021) Ozturk, Savas; Turgutalp, Kenan; Arıcı, Mustafa; Çetinkaya, Hakkı; Altıparmak, Mehmet Rıza; Aydın, Zeki; Ateş, Kenan; Dolarslan, Mursıde Esra; Seyahi, Nurhan; Yıldız, Alaattın; Bora, FeyzaBackground/aim: Hospital-acquired acute kidney injury (HA-AKI) may commonly develop in Covid-19 patients and is expected to have higher mortality. There is little comparative data investigating the effect of HA-AKI on mortality of chronic kidney disease (CKD) patients and a control group of general population suffering from Covid-19. Materials and methods: HA-AKI development was assessed in a group of stage 3–5 CKD patients and control group without CKD among adult patients hospitalized for Covid-19. The role of AKI development on the outcome (in-hospital mortality and admission to the intensive care unit [ICU]) of patients with and without CKD was compared. Results: Among 621 hospitalized patients (age 60 [IQR: 47–73]), women: 44.1%), AKI developed in 32.5% of the patients, as stage 1 in 84.2%, stage 2 in 8.4%, and stage 3 in 7.4%. AKI developed in 48.0 % of CKD patients, whereas it developed in 17.6% of patients without CKD. CKD patients with HA-AKI had the highest mortality rate of 41.1% compared to 14.3% of patients with HA-AKI but no CKD (p < 0.001). However, patients with AKI+non-CKD had similar rates of ICU admission, mechanical ventilation, and death rate to patients with CKD without AKI. Adjusted mortality risks of the AKI+non-CKD group (HR: 9.0, 95% CI: 1.9–44.2) and AKI+CKD group (HR: 7.9, 95% CI: 1.9–33.3) were significantly higher than that of the non-AKI+non-CKD group. Conclusion: AKI frequently develops in hospitalized patients due to Covid-19 and is associated with high mortality. HA-AKI has worse outcomes whether it develops in patients with or without CKD, but the worst outcome was seen in AKI+CKD patients.Key words: Acute kidney injury, chronic kidney disease, Covid-19, hospitalization, mortalityArticle Citation - WoS: 2Citation - Scopus: 3Predictors and Mediators of Pressure/Tension in University Students' Distance Learning During the Covid-19 Pandemic: a Self-Determination Theory Perspective(Routledge Journals, Taylor & Francis Ltd, 2024) Manuoglu, Elif; Gungor, ElisDue to the global restrictions to decrease the risk of infection in classrooms, the transition from face-to-face education to distance learning was a necessity during the Covid-19 pandemic. Grounded in Self-Determination Theory, the present research sought to explore how the pandemic affects university students during distance learning. Specifically, the study examined the predictors of pressure/tension and attempted to identify the unique and mediator roles of correlates of pressure/tension of university students. This cross-sectional study was conducted with 432 university students from different departments of different universities in Turkey. The online survey was administered between the last week of October and the second week of December 2020. Our findings revealed that there is a positive association between pressure/tension and Covid-specific worry. Also, there is a negative association between learning climate and pressure/tension and between perceived competence and pressure/tension. Further, learning climate mediated the link between Covid-specific worry and pressure/tension. The data of the present study depends on students' academic (learning climate) and also non-academic (Covid worry) experiences during the pandemic. Methodological limitations concerning the research design are discussed.Conference Object Assessment of Online Exam System Perception in Covid-19 Pandemic Era(IADIS Press, 2021) Eryılmaz,M.; Genis-Gruber,A.The swift conversion of courses to online exams has labelled the recent Covid-19 pandemic era. In educational agenda, all educators in the globe have faced the obstacles of abrupt adoption of distance education learning methods. Although distance education methods have been exercised in the past decade, the usage was not common. The pandemic has brought not only the sudden transformation of education format, but also online security issues. The online exam solution in e-learning techniques, tools and adoption has been a popular topic to research. Recent literature review shows various analyzes in the field, however the outcome of the research proves that the challenges are similiar in the globe. The aim of this research is to determine the essential problems and develop solutions based on the students perception of online exams which became compulsorily transitioned during the pandemic process. The custom-made survey was conducted on 165 students to have an insight on their approach to e-learning and online exam. Descriptive statistics method is used to describe the features of the data in the study. © 2021Article Citation - WoS: 5Citation - Scopus: 5Molecular/Antigenic Mimicry and Immunological Cross-Reactivity Explains Sars-Cov Autoimmunity(Elsevier, 2025) Adiguzel, Yekbun; Bogdanos, Dimitros P.; Shoenfeld, YehudaCOVID-19 pandemic is over, but its effects on chronic illnesses remain a challenging issue. Understanding the influence of SARS-COV-2-mediated autoimmunity and overt autoimmune disease is of paramount importance, as it can provide a critical mass of information regarding both infection-mediated (and vaccination-induced) autoimmune phenomena in susceptible individuals during the disease course, and short or long-term post-disease sequelae. The high prevalence of organ and non-organ specific autoantibody positivity in patients with COVID-19 led to studies attempting to delineate the origin and the underlying mechanism responsible for their induction nature, identifying novel autoantigens, and the self-epitope sequences which could be the impetus for the initiating autoreactive responses. Herein, we provide a meticulous review of the studies reporting those mimicking sequences that have been experimentally validated, based on the assumption that molecular mimicry and immunological crossreactivity may account for autoantibody development. Most reports are based on bioinformatics approaches, and only a disproportionally small number of studies currently demonstrate immunological crossreactivity. We took the opportunity to further review and searched for the linear human epitope sequences of human, through the epitopes deposited at the Immune Epitope Database. This included an analysis of autoimmune disease as the disease data to comprehensively understand the subject matter. The critical overview of the findings underscore the urgent and immense need for further research to gain a comprehensive understanding of the mechanisms involved and the anticipated appraisal that molecular mimicry and immunological crossreactivity is indeed central to the loss of immunological tolerance during SARS-COV-2 infection.Article Citation - WoS: 11Citation - Scopus: 11Comparison of Optimization Algorithms for Selecting the Fractional Frequency in Fourier Form Unit Root Tests(Routledge Journals, Taylor & Francis Ltd, 2021) Omay, Tolga; Emirmahmutoglu, Furkan; Hussain Shahzad, Syed JawadWe compare the performance of unit root tests which include flexible Fourier trends in their testing processes. The algorithms considered are those of Broyden, Fletcher, Goldfarb and Shanno (BFGS), Berndt, Hall, Hall and Hausman (BHHH), Simplex, Genetic and grid search (GS). The simulation results indicate that derivative-free methods, such as Genetic and Simplex, have advantages over hill-climbing methods, such as BFGS and BHHH in providing accurate fractional frequencies for fractional frequency flexible Fourier form (FFFFF) unit root test. When the parameters are estimated under the alternative hypothesis of the FFFFF type of unit root test, the grid search and derivative-free methods provide unbiased and efficient estimations. We also provide the asymptotic distribution of the FFFFF unit root test. We extend the FFFFF unit root test to a panel version in order to increase the power of the test. Finally, the empirical analyses of healthcare convergence show that derivative-free methods, hill climbing and extensive grid searches can be used interchangeably. However, for big data and accurate estimation of the frequency parameters, the Simplex methodology using the bootstrap process is preferred.Article A Prediction Study About the Pandemic Era Based on Machine Learning Methods(Auricle Global Society of Education and Research, 2021) Eryılmaz,M.; Eryılmaz, Meltem; Yalçınkaya,F.; Kara, Erdi; Ertan,Ö.; Kara,E.; Eryılmaz, Meltem; Kara, Erdi; Mathematics; Computer Engineering; Mathematics; Computer EngineeringCoronavirus pandemic has been going on since late 2019, millions of people died worldwide, vaccination has recently started in many countries and new strategies are sought by countries since they are still struggling to defeat the virus. So, this research is made to predict the possible ending time of the coronavirus pandemic in Turkey using data mining and statistical studies. Data mining is a computer science study that processes large amounts of data and produces new useful information. It is especially used to support decision making in companies today. So, this project could support the decision making of authorities in developing an effective strategy against the on-going pandemic. During the research we have practiced on Turkey’s coronavirus and vaccination data between 13 January 2021 and 28 May 2021. We used Rapidminer and the Random Forest method for data mining. After all the simulations we have applied and observed during our research, it was clearly seen that vaccination parameters were decreasing the new cases. Also, the stringency index did not affect the new cases. As a conclusion of our research and observations, we think that the government should vaccinate as many people as it can in order to relax restrictions for the last time. © 2021 Authors. All rights reserved.Article Citation - WoS: 9Citation - Scopus: 7Identifying the Cycles in Covid-19 Infection: the Case of Turkey(Taylor & Francis Ltd, 2023) Akdi, Yilmaz; Karamanoglu, Yunus Emre; Unlu, Kamil Demirberk; Bas, Cem; Emre Karamanoğlu, YunusThe new coronavirus disease, called COVID-19, has spread extremely quickly to more than 200 countries since its detection in December 2019 in China. COVID-19 marks the return of a very old and familiar enemy. Throughout human history, disasters such as earthquakes, volcanic eruptions and even wars have not caused more human losses than lethal diseases, which are caused by viruses, bacteria and parasites. The first COVID-19 case was detected in Turkey on 12 March 2020 and researchers have since then attempted to examine periodicity in the number of daily new cases. One of the most curious questions in the pandemic process that affects the whole world is whether there will be a second wave. Such questions can be answered by examining any periodicities in the series of daily cases. Periodic series are frequently seen in many disciplines. An important method based on harmonic regression is the focus of the study. The main aim of this study is to identify the hidden periodic structure of the daily infected cases. Infected case of Turkey is analyzed by using periodogram-based methodology. Our results revealed that there are 4, 5 and 62 days cycles in the daily new cases of Turkey.Article Citation - WoS: 1The Socio-Economic Impact of the Covid-19 Pandemic on Syrian Refugees in Turkey(Uluslararasi Iliskiler Konseyi dernegi, 2024) Memisoglu, Fulya; Ozkil, Altan; Kilinc, TunaBuilding upon empirical research, this study examines the socio-economic impact of the Covid-19 pandemic on Syrian refugees in Turkey by analyzing its implications on employment, livelihood opportunities, and social cohesion. More specifically, it focuses on the experiences of Syrian refugees to examine the ways in which they exert their agency to cope with the structural constraints when faced with 'multiple crises' in host countries, intersecting with the dynamics of a 'normalized refugee crisis'. Our findings from fieldwork conducted in the top six refugee-hosting cities reveal that loss of jobs, limited access to decent work, increased dependency on external financial assistance, and social exclusion have been some of the most acute effects of the pandemic on refugees. Meanwhile, the perceived effects that refugees have on the host community's welfare trigger problems that impede social cohesion. All in all, the study intends to highlight the far-reaching effects of the pandemic beyond its direct health implications by addressing the structural vulnerability of refugees and the importance of providing an enabling environment for socio-economic self-reliance.Article Citation - WoS: 3Citation - Scopus: 4Predicted Sars-Cov Mirnas Associated With Epigenetic Viral Pathoge-Nesis and the Detection of New Possible Drugs for Covid-19(Bentham Science Publ Ltd, 2021) Cetin, Zafer; Bayrak, Tuncay; Ogul, Hasan; Saygili, Eyup Ilker; Akkol, Esra KupeliObjective: The outbreak of COVID-19 caused by SARS-CoV-2 has promptly spread worldwide. This study aimed to predict mature miRNA sequences in the SARS-CoV-2 genome, their effects on protein-protein interactions in the affected cells, and gene-drug relationships to detect possible drug candidates. Methods: Viral hairpin structure prediction, classification of hairpins, mutational examination of precursor miRNA candidate sequences, Minimum Free Energy (MFE) and regional entropy analysis, mature miRNA sequences, target gene prediction, gene ontology enrichment, and Protein-Protein Interaction (PPI) analysis, and gene-drug interactions were performed. Results: A total of 62 candidate hairpins were detected by VMir analysis. Three hairpin structures were classified as true precursor miRNAs by miRBoost. Five different mutations were detected in precursor miRNA sequences in 100 SARS-CoV-2 viral genomes. Mutations slightly elevated MFE values and entropy in precursor miRNAs. Gene ontology terms associated with fibrotic pathways and immune system were found to be enriched in PANTHER, KEGG and Wiki pathway analysis. PPI analysis showed a network between 60 genes. CytoHubba analysis showed SMAD1 as a hub gene in the network. The targets of the predicted miRNAs, FAM214A, PPM1E, NUFIP2 and FAT4, were downregulated in SARS-CoV-2 infected A549 cells. Conclusion: miRNAs in the SARS-CoV-2 virus genome may contribute to the emergence of the Covid-19 infection by activating pathways associated with fibrosis in the cells infected by the virus and modulating the innate immune system. The hub protein between these pathways may be the SMAD1, which has an effective role in TGF signal transduction.Article Deep Learning Based Covid-19 Detection Using Computed Tomography Images(Prof.Dr. İskender AKKURT, 2024) Yılmaz, A.A.; Sevinç, Ö.The infectious coronavirus disease (COVID-19), seen in Wuhan city of China in December 2019, led to a global pandemic, resulting in countless deaths. The healthcare sector has become extensively use of deep learning (DL), a method that is currently quite popular. The aim of this study is to identify the best and most successful deep learning model and optimizer approach combination for COVID-19 diagnosis. For this reason, several DL methods and optimizer techniques are tested on two comprehensive public data set to select the best DL model with optimizer technique. A variety of performance evaluation metrics, including f-score, precision, specificity, and accuracy, were used to assess the models' effectiveness. The experimental results show that the most suitable and effective architecture is DenseNet-201 in the network comparison, which achieved a 98% accuracy rate using the AdaGrad optimizer and 200 iterations. © IJCESEN.
