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Article Citation - WoS: 7Citation - Scopus: 8Food Safety Awareness, Changes in Food Purchasing Behaviour and Attitudes Towards Food Waste During Covid-19 in Türkiye(Mdpi, 2023) Erol, Irfan; Mutus, Begum; Ayaz, Naim Deniz; Stowell, Julian D.; Siriken, Belgin(1) Background: The COVID-19 pandemic brought the key issues of food security, food safety, and food waste into sharp focus. Turkiye is in the enviable position of being among the top ten agricultural economies worldwide, with a wide diversity of food production. This survey was undertaken in order to gain insights into consumer behaviour and attitudes in Turkiye with respect to these issues. The objective was to highlight strengths and weaknesses, identify areas for improvement, and present strategies for the future. (2) Methods: This survey was carried out between April and May 2022 in 12 provinces throughout Turkiye. Face-to-face interviews were performed with 2400 participants representing a cross-section of ages, educational attainment, and socio-economic categories. The findings were evaluated statistically. (3) Results: The results provide an insight into attitudes and behaviours, both pre-COVID-19 and during the pandemic. In several ways, the pandemic enhanced knowledge and improved behaviour, leading to improvements in diet and reductions in food waste. However, worrying concerns about food safety persist. Specific attention has been given to understanding patterns of bread consumption, particularly in consideration of waste. (4) Conclusions: It is hoped that the results of this survey will increase dialogue between the components of the food sector, encourage education initiatives, and contribute to improving food safety and security and reducing food waste in Turkiye and beyond.Article Citation - WoS: 41Citation - Scopus: 54Impacts of Covid-19 Pandemic Period on Depression, Anxiety and Stress Levels of the Healthcare Employees in Turkey(Elsevier Ireland Ltd, 2021) Tengilimoglu, Dilaver; Zekioglu, Aysu; Tosun, Nurperihan; Isik, Oguz; Tengilimoglu, OnurThe COVID-19 pandemic has turned into a public health issue since December 2019 and has risen in all countries in the world. The healthcare employees taking part in the pandemic will eventually be affected by the process. The aim of the study is to determine the levels of the anxiety, depression, and stress of the healthcare employees during the COVID-19 pandemic in Turkey. As the data collection tool, an e-survey was used. In the first section, Depression, Anxiety and Stress Scale (DASS-21) was used. In the second section of the survey, the problems experienced by the healthcare employees during the pandemic and their working media were aimed to be defined. In the last section, the socio-demographic features of the employees were investigated. 2076 healthcare employees participated in the study. The results showed that the major cause of the anxiety or stress among healthcare employees comes from the fear to contaminate the COVID-19 virus to their families (86.9%). It was observed that the levels of depression, anxiety and stress of female employees are higher than that of male employees (p < 0.003). The highest depression, anxiety and stress levels of healthcare employees come from the pandemic, emergency, and internal services (p < 0.001). Health managers and policymakers need to make a move immediately to find solutions for the physical and psychological needs of the health employees. On the other hand, in order to minimize the risk, preparation of the work power plans beforehand and inclusion of obligatory referral chain into health services can be suggested.Article Citation - WoS: 5Citation - Scopus: 7The Problems Experienced by Employees With Chronic Disease During the Covid-19 Pandemic(Mdpi, 2022) Tengilimoglu, Dilaver; Tengilimoğlu, Dilaver; Goenuellue, Ugur; Isik, Oguz; Tosun, Nurperihan; Zekioglu, Aysu; Tengilimoglu, Onur; Younis, Mustafa; Tengilimoğlu, Dilaver; Gönüllü, Uğur; Business; BusinessChronic diseases served as a silent global epidemic before the pandemic, and individuals living with chronic disease now form one of the groups most affected by COVID-19. This study aims to determine the problems that employees with chronic disease face during the COVID-19 pandemic. As part of the study, data were collected from 952 individuals who live with chronic disease in Turkey. Of these, 76.6% of respondents worked for the public sector, a large majority of whom (67.7%) have worked full time during the COVID-19 pandemic. It was found that the COVID-19 fear level of employees living with chronic disease was higher than moderate (21.061 +/- 7.607). When the variables affecting the COVID-19 fear level are listed in order of relative significance, eating problems, residing in the Mediterranean region, having asthma, and working as a female employee made the greatest impact, respectively. Necessary conditions of work should be provided to those living with chronic disease who could adapt themselves to working flexibly or working from home, so that they would not feel isolated from business life. This group should be provided with essential protective equipment, their working conditions must be reviewed and vaccination priority could be given to them.Review Citation - WoS: 6Citation - Scopus: 6Shared Pathogenicity Features and Sequences Between Ebv, Sars-Cov and Hla Class I Molecule-Binding Motifs With a Potential Role in Autoimmunity(Humana Press inc, 2023) Adiguzel, Yekbun; Mahroum, Naim; Muller, Sylviane; Blank, Miri; Halpert, Gilad; Shoenfeld, YehudaEpstein-Barr virus (EBV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are extraordinary in their ability to activate autoimmunity as well as to induce diverse autoimmune diseases. Here we reviewed the current knowledge on their relation. Further, we suggested that molecular mimicry could be a possible common mechanism of autoimmunity induction in the susceptible individuals infected with SARS-CoV-2. Molecular mimicry between SARS-CoV-2 and human proteins, and EBV and human proteins, are present. Besides, relation of the pathogenicity associated with both coronavirus diseases and EBV supports the notion. As a proof-of-the-concept, we investigated 8mer sequences with shared 5mers of SARS-CoV-2, EBV, and human proteins, which were predicted as epitopes binding to the same human leukocyte antigen (HLA) supertype representatives. We identified significant number of human peptide sequences with predicted-affinities to the HLA-A*02:01 allele. Rest of the peptide sequences had predicted-affinities to the HLA-A*02:01, HLA-B*40:01, HLA-B*27:05, HLA-A*01:01, and HLA-B*39:01 alleles. Carriers of these serotypes can be under a higher risk of autoimmune response induction upon getting infected, through molecular mimicry-based mechanisms common to SARS-CoV-2 and EBV infections. We additionally reviewed established associations of the identified proteins with the EBV-related pathogenicity and with the autoimmune diseases.Article Citation - WoS: 17Pulmonary Rehabilitation Principles in Sars-Cov Infection (covid-19): the Revised Guideline for the Acute, Subacute, and Post-Covid Rehabilitation(Baycinar Medical Publ-baycinar Tibbi Yayincilik, 2021) Aytur, Yesim Kurtais; Koseoglu, Belma Fusun; Taskiran, Ozden Ozyemisci; Ordu-Gokkaya, Nilufer Kutay; Delialioglu, Sibel Unsal; Tur, Birkan Sonel; Tikiz, CananCoronavirus disease 2019 (COVID-19) is a contagious infection disease, which may cause respiratory, physical, psychological, and generalized systemic dysfunction. The severity of disease ranges from an asymptomatic infection or mild illness to mild or severe pneumonia with respiratory failure and/or death. COVID-19 dramatically affects the pulmonary system. This clinical practice guideline includes pulmonary rehabilitation (PR) recommendations for adult COVID-19 patients and has been developed in the light of the guidelines on the diagnosis and treatment of COVID-19 provided by the World Health Organization and Republic of Turkey, Ministry of Health, recently published scientific literature, and PR recommendations for COVID-19 regarding basic principles of PR. This national guideline provides suggestions regarding the PR methods during the clinical stages of COVID-19 and post-COVID-19 with its possible benefits, contraindications, and disadvantages.Article Citation - WoS: 173Mortality Analysis of Covid-19 Infection in Chronic Kidney Disease, Haemodialysis and Renal Transplant Patients Compared With Patients Without Kidney Disease: a Nationwide Analysis From Turkey(Oxford Univ Press, 2020) Ozturk, Savas; Turgutalp, Kenan; Arici, Mustafa; Odabas, Ali Riza; Altiparmak, Mehmet Riza; Aydin, Zeki; Ates, KenanBackground. Chronic kidney disease (CKD) and immunosuppression, such as in renal transplantation (RT), stand as one of the established potential risk factors for severe coronavirus disease 2019 (COVID-19). Case morbidity and mortality rates for any type of infection have always been much higher in CKD, haemodialysis (HD) and RT patients than in the general population. A large study comparing COVID-19 outcome in moderate to advanced CKD (Stages 3-5), HD and RT patients with a control group of patients is still lacking. Methods. We conducted a multicentre, retrospective, observational study, involving hospitalized adult patients with COVID-19 from 47 centres in Turkey. Patients with CKD Stages 3-5, chronic HD and RT were compared with patients who had COVID-19 but no kidney disease. Demographics, comorbidities, medications, laboratory tests, COVID-19 treatments and outcome [in-hospital mortality and combined in-hospital outcome mortality or admission to the intensive care unit (ICU)] were compared. Results. A total of 1210 patients were included [median age, 61 (quartile 1-quartile 3 48-71) years, female 551 (45.5%)] composed of four groups: control (n = 450), HD (n = 390), RT (n = 81) and CKD (n = 289). The ICU admission rate was 266/1210 (22.0%). A total of 172/1210 (14.2%) patients died. The ICU admission and in-hospital mortality rates in the CKD group [114/289 (39.4%); 95% confidence interval (CI) 33.9-45.2; and 82/289 (28.4%); 95% CI 23.9-34.5)] were significantly higher than the other groups: HD = 99/390 (25.4%; 95% CI 21.3-29.9; P < 0.001) and 63/390 (16.2%; 95% CI 13.0-20.4; P < 0.001); RT = 17/81 (21.0%; 95% CI 13.2-30.8; P = 0.002) and 9/81 (11.1%; 95% CI 5.7-19.5; P = 0.001); and control = 36/450 (8.0%; 95% CI 5.8-10.8; P < 0.001) and 18/450 (4%; 95% CI 2.5-6.2; P < 0.001). Adjusted mortality and adjusted combined outcomes in CKD group and HD groups were significantly higher than the control group [hazard ratio (HR) (95% CI) CKD: 2.88 (1.52-5.44); P = 0.001; 2.44 (1.35-4.40); P = 0.003; HD: 2.32 (1.21-4.46); P = 0.011; 2.25 (1.23-4.12); P = 0.008), respectively], but these were not significantly different in the RT from in the control group [HR (95% CI) 1.89 (0.76-4.72); P = 0.169; 1.87 (0.81-4.28); P = 0.138, respectively]. Conclusions. Hospitalized COVID-19 patients with CKDs, including Stages 3-5 CKD, HD and RT, have significantly higher mortality than patients without kidney disease. Stages 3-5 CKD patients have an in-hospital mortality rate as much as HD patients, which may be in part because of similar age and comorbidity burden. We were unable to assess if RT patients were or were not at increased risk for in-hospital mortality because of the relatively small sample size of the RT patients in this study.Editorial Citation - Scopus: 1Safety and Feasibility of Surgery for Oropharyngeal Cancers During the Sars-Cov(Frontiers Media Sa, 2021) Gorphe, Philippe; Grandbastien, Bruno; Dietz, Andreas; Duvvuri, Umamaheswar; Ferris, Robert L.; Golusinski, Wojciech; Simon, Christian[No Abstract Available]Review Citation - WoS: 7Citation - Scopus: 9A Survey of Covid-19 Diagnosis Using Routine Blood Tests With the Aid of Artificial Intelligence Techniques(Mdpi, 2023) Habashi, Soheila Abbasi; Koyuncu, Murat; Alizadehsani, Roohallah; Abbasi Habashi, SoheilaSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causing a disease called COVID-19, is a class of acute respiratory syndrome that has considerably affected the global economy and healthcare system. This virus is diagnosed using a traditional technique known as the Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. However, RT-PCR customarily outputs a lot of false-negative and incorrect results. Current works indicate that COVID-19 can also be diagnosed using imaging resolutions, including CT scans, X-rays, and blood tests. Nevertheless, X-rays and CT scans cannot always be used for patient screening because of high costs, radiation doses, and an insufficient number of devices. Therefore, there is a requirement for a less expensive and faster diagnostic model to recognize the positive and negative cases of COVID-19. Blood tests are easily performed and cost less than RT-PCR and imaging tests. Since biochemical parameters in routine blood tests vary during the COVID-19 infection, they may supply physicians with exact information about the diagnosis of COVID-19. This study reviewed some newly emerging artificial intelligence (AI)-based methods to diagnose COVID-19 using routine blood tests. We gathered information about research resources and inspected 92 articles that were carefully chosen from a variety of publishers, such as IEEE, Springer, Elsevier, and MDPI. Then, these 92 studies are classified into two tables which contain articles that use machine Learning and deep Learning models to diagnose COVID-19 while using routine blood test datasets. In these studies, for diagnosing COVID-19, Random Forest and logistic regression are the most widely used machine learning methods and the most widely used performance metrics are accuracy, sensitivity, specificity, and AUC. Finally, we conclude by discussing and analyzing these studies which use machine learning and deep learning models and routine blood test datasets for COVID-19 detection. This survey can be the starting point for a novice-/beginner-level researcher to perform on COVID-19 classification.Article Citation - WoS: 5Citation - Scopus: 8A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification(Mdpi, 2024) Kadhim, Yezi Ali; Guzel, Mehmet Serdar; Mishra, AlokMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep learning techniques, which were based on a convolutional neural network (CNN) or autoencoder, to extract features and combine them with the next step of the meta-heuristic algorithm in order to select optimal features using the particle swarm optimization (PSO) algorithm. This combination sought to reduce the dimensionality of the datasets while maintaining the original performance of the data. This is considered an innovative method and ensures highly accurate classification results across various medical datasets. Several classifiers were employed to predict the diseases. The COVID-19 dataset found that the highest accuracy was 99.76% using the combination of CNN-PSO-SVM. In comparison, the brain tumor dataset obtained 99.51% accuracy, the highest accuracy derived using the combination method of autoencoder-PSO-KNN.Article Investigation of Sars-Cov Antibody Levels After Covid-19 Vaccine in Chronic Hepatitis B Patients(Aepress Sro, 2024) Kinikli, Sami; Afsar, Fatma Elcin; Dursun, Ali Dogan; Aksoy, Altan; Karahan, Gizem; Cesur, Salih; Urtimur, UfukAIM: The aim was to compare SARS-CoV-2 IgG antibody levels in chronic hepatitis B patients and healthcare personnel selected as the control group and to determine factors such as age, gender, vaccine type, and number of vaccines that may affect the antibody levels. MATERIALS AND METHODS: 87 chronic hepatitis B (CHB) patients followed in Ankara Training and Research Hospital Infectious Diseases Clinic and Mamak State Hospital Infectious Diseases outpatient clinic and 89 healthcare personnel selected as the control group were included in the study. SARS-CoV-2 IgG antibody levels in the serum samples of patients and healthcare personnel who received the COVID-19 vaccine were studied with the ELISA method in the Microbiology Laboratory of Ankara Training and Research Hospital, using a commercial ELISA kit (Abbott, USA) in line with the recommendations of the manufacturer. In the study, SARS-CoV-2 IgG levels were compared in CHB patients and healthcare personnel. In addition, the relationship between SARS-CoV-2 antibody level, gender, average age, natural history of the disease, number of vaccinations, vaccine type (Coronavac TM vaccine alone, BNT162b2 vaccine alone or Coronavac TM and BNT162b2 vaccine (heterologous vaccination)), treatment duration of CHB was investigated. Statistical analyses were made in the SPSS program. A value of p <= 0.05 was considered statistically significant. FINDINGS: A total of 167 people, including 87 CKD patients and 80 healthcare personnel as the control group, were included in the study. SARS-CoV-2 IgG antibody levels were detected above the cut-off level in the entire study group, regardless of the vaccine type. No difference was detected in SARS-CoV-2 IgG titers after COVID-19 vaccination between CHB patients and healthcare personnel. There was a statistically significant difference in SARS-CoV-2 IgG antibody levels among individuals participating in the study according to vaccine types. Compared to those who received Coronavac TM vaccine alone, the average SARS-CoV-2 IgG level was found to be statistically significantly higher in those who received BNT162b2 vaccine alone or heterologous vaccination with Coronavac TM + BNT162b2 vaccine. There was no difference between the groups in terms of age, gender, number of vaccinations, natural transmission of the disease, and duration of antiviral therapy in the CHD patient group. CONCLUSION: As a result, SARS-CoV-2 IgG antibody levels above the cut-off value were achieved with Coronavac TM and BNT162b2 vaccines in both CHD patients and healthy control groups. however, both CHD patients and healthcare personnel had higher antibody levels than those who received BNT162b2 alone or those who received heterologous vaccination had higher antibody levels than those with Coronavac TM alone. Therefore, if there are no contraindications, BNT162b2 vaccine may be preferred in CHB and health personnel (Tab. 2, Ref. 14) .
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