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Öğe Automatic detection of sleep spindles with the use of STFT, EMD and DWT methods(Springer London Ltd, 2018) Yucelbas, Cuneyt; Yucelbas, Sule; Ozsen, Seral; Tezel, Gulay; Kuccukturk, Serkan; Yosunkaya, SebnemSleep staging is a significant process to diagnose sleep disorders. Like other stages, several parameters are required for the determination of N-REM2 stage. Sleep spindles (SSs) are among them. In this study, a methodology was presented to automatically determine starting and ending positions of SSs. To accomplish this, short-time Fourier transform-artificial neural networks (STFT-ANN), empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods were used. Two considerable methods which were determination envelope and thresholding of the decomposed signals by EMD and DWT were also presented in this study. A database from the EEG signals of nine healthy subjects-which consisted of 100 epochs including 172 SSs in total-was prepared. According to the test results, the highest sensitivity rate was obtained as 100 and 99.42 % for EMD and DWT methods. However, the sensitivity rate for the STFT-ANN method was recorded as 55.93 %. The results indicated that the EMD method could be confidently used in the automatic determination of SSs. Thanks to this study, the sleep experts will be able to reliably find out the epochs with SSs and also know the places of SSs in these epochs, automatically. Another important point of the study was that the sleep staging process-tiring, time-consuming and high fallibility for the experts-could be performed in less time and at higher accuracy rates.Öğe Clinical Evaluation of Acute Pancreatitis Caused by SARS-CoV-2 Virus Infection(Hindawi Ltd, 2021) Vatansev, Hulya; Yildirim, Mehmet Aykut; Kuccukturk, Serkan; Karaselek, Mehmet Ali; Kadiyoran, CengizIntroduction. Coronavirus 2019 disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread to more than 200 countries worldwide. We aimed to present acute pancreatitis (AP) cases caused by SARS-CoV-2 viral infection. Methods. The study was conducted retrospectively between April 2020 and June 2020 in Necmettin Erbakan University Meram, Medical Faculty Hospital, and 150 hospitalized patients diagnosed with COVID-19 were included. The degree of acute pancreatitis was determined according to the Atlanta classification. Organ failures of the patients were evaluated in terms of respiratory, cardiovascular, and nephrology according to the modified Marshall scoring (MMS) system, and CTSI (Balthazar score) and Imrie score were determined. Modified Marshall score >= 2 was considered organ failure. Results. A total of 29 patients were diagnosed with acute pancreatitis. All 29 patients with pancreatitis had respiratory failure during hospitalization. After the diagnosis of pancreatitis, there was no change in respiratory failure. According to the Atlanta classification, 19 patients had mild AP and 10 patients had moderate AP. Patients with acute pancreatitis were scored according to the CTSI (Balthazar score), and there were no patients with >= 6 severe pancreatitis. The CTSI score of 4 patients was 3. In addition, the Imrie score of the patients was determined and 8 patients with Imrie score >= 3 were identified. Conclusion. The rate of pancreatic damage in SARS-CoV-2 infection was found to be 19% (n=29) in our study. In our study, we highlight acute pancreatitis as a complication associated with COVID-19 and the importance of pancreatic evaluation in patients with COVID-19 and abdominal pain is demonstrated.Öğe Detection of the Electrode Disconnection in Sleep Signals(IEEE, 2015) Yucelbas, Cuneyt; Ozsen, Seral; Yucelbas, Sule; Tezel, Gulay; Dursun, Mehmet; Yosunkaya, Sebnem; Kuccukturk, SerkanSleep staging process that is performed in sleep laboratories in hospitals has an important role in diagnosing some of the sleep disorders and disturbances which are seen in sleep. And also it is an indispensable method. It is usually performed by a sleep expert through examining during the night of the patients (6-8 hours) recorded Electroencephalogram (EEG), Electrooculogram (FOG), Electromyogram (EMG), electrocardiogram (ECG) and other some signals of the patients and determining the stages of sleep in different time sections named as epochs. Manual sleep staging is preferred among the sleep experts but because it is rather tiring and time consuming task, automatic sleep stage scoring studies has come to the fore. However, none of the so far made automatic sleep staging was not accepted by the experts. The most important reason is that the results of the automated systems are not desired accuracy. There are many factors that affecting the accuracy of the systems, such as noise, the inter-channel interference, excessive body movements and disconnection of electrodes. In this study, we examined the written an algorithm to be able to determine to what extent the disconnection of electrodes in EEG signal that obtained one healthy person at the sleep laboratory of Meram Medicine Faculty of Necmettin Erbakan University. According to the obtained application results, the electrodes disconnection in EEG signal could be detected maximum of 100% and minimum of 99.12% accuracy. Accordingly, based on the success achieved in the study, this algorithm is thought to contribute positively to the researchers that the work on and will work on sleep staging problems and increase the success of automatic sleep staging systems.Öğe Effect of intensive training on immune system cells in elite female weightlifters(Assoc Medica Brasileira, 2024) Karaselek, Mehmet Ali; Kuccukturk, Serkan; Duran, TugceOBJECTIVE: This study aimed to investigate the effects of intense weightlifting training on lymphocyte and natural killer cell subgroups, which are the major cells of the immune system, in elite female weightlifters.METHODS: A total of 20 elite female weightlifters were evaluated using flow cytometry before training (pre-T), immediately after training (post-T), and after a 120-min rest period (rest-T).RESULTS: Post-T and rest-T showed significant decreases in helper T (Th) and cytotoxic T compared with pre-T (p=0.045, p<0.001 and p=0.05, p<0.001, respectively). B and natural killer cells were higher in post-T and rest-T than in pre-T. The increase in B cells was significant in pre-T/rest-T (p<0.001) but not in pre-T/post-T (p=0.122). Intense training significantly increased natural killer cells in both post-T and rest-T (p<0.001). CD56brightand CD56dim natural killer cell subgroups were significantly lower in post-T and rest-T than in pre-T (p=0.005, p=0.006 and p<0.001, p=0.004, respectively).CONCLUSION: This study shows that intense weightlifting alters peripheral lymphocyte and natural killer subgroup ratios, being the first investigation in this field.Öğe Effect of intensive training on immune system cells in elite female weightlifters(Assoc Medica Brasileira, 2024) Karaselek, Mehmet Ali; Kuccukturk, Serkan; Duran, TugceOBJECTIVE: This study aimed to investigate the effects of intense weightlifting training on lymphocyte and natural killer cell subgroups, which are the major cells of the immune system, in elite female weightlifters.METHODS: A total of 20 elite female weightlifters were evaluated using flow cytometry before training (pre-T), immediately after training (post-T), and after a 120-min rest period (rest-T).RESULTS: Post-T and rest-T showed significant decreases in helper T (Th) and cytotoxic T compared with pre-T (p=0.045, p<0.001 and p=0.05, p<0.001, respectively). B and natural killer cells were higher in post-T and rest-T than in pre-T. The increase in B cells was significant in pre-T/rest-T (p<0.001) but not in pre-T/post-T (p=0.122). Intense training significantly increased natural killer cells in both post-T and rest-T (p<0.001). CD56brightand CD56dim natural killer cell subgroups were significantly lower in post-T and rest-T than in pre-T (p=0.005, p=0.006 and p<0.001, p=0.004, respectively).CONCLUSION: This study shows that intense weightlifting alters peripheral lymphocyte and natural killer subgroup ratios, being the first investigation in this field.Öğe The effect of intermittent diet and/or physical therapy in patients with chronic low back pain: A single-blinded randomized controlled trial(Elsevier Science Inc, 2022) Torlak, Mustafa S.; Bagcaci, Sinan; Akpinar, Elif; Okutan, Ozerk; Nazli, Merve S.; Kuccukturk, SerkanBackground and purpose: This study aimed to investigate the effect of intermittent diet and/or physical therapy in patients with chronic low back pain. Materials and methods: Sixty sedentary volunteers with chronic low back pain participated in the study. Body weight and body mass index (BMI) were measured. Pain severity was assessed using Visual Analogue Scale (VAS) and Leeds Assessment of Neuropathic Symptoms and Signs (LANSS), while assessment of disability was done using Barthel Index (BI). Results: The weight and BMI were reduced after treatment with diet only and diet plus physical therapy (p < 0.001). The pain severity was reduced in all the treated groups (p < 0.001), while BI was increased in the group treated with only physical therapy (p < 0.001). Conclusion: The present study indicated that intermittent diet and/or physical therapy are beneficial to patients with chronic low back pain in terms of pain sensation and daily activities. (c) 2020 Elsevier Inc. All rights reserved.Öğe Effective anticancer agents based-on two Pillar[5]arene derivatives for pancreas cancer cell lines: synthesis, apoptotic effect, caspase pathway(Springer, 2023) Karaselek, Mehmet Ali; Kuccukturk, Serkan; Duran, Tugce; Kursunlu, Ahmed Nuri; Ozmen, Mustafa; Bozdag, Ceren; Alkan, SelmanThis study aimed to evaluate the possible anticancer effects of two different pillar[5]arene derivatives (5Q-[P5] and 10Q-P[5]) on two different pancreatic cancer cell lines in vitro. For this purpose, changes in the expression of major genes that play a role in apoptosis and caspase pathways were investigated. Panc-1 and BxPC-3 cell lines were used in the study and the cytotoxic dose of pillar[5]arenes was determined by the MTT method. Changes in gene expression after pillar[5]arenes treatment were evaluated by real-time polymerase chain reaction (qPCR). Apoptosis was studied by flow cytometry. As a result of analysis, it was determined that proapoptotic genes and genes involved in major caspase activation were upregulated and antiapoptotic genes were down-regulated in Panc-1 cell line treated with pillar[5]arenes. Flow cytometric apoptosis analysis also showed an increased apoptosis rate in this cell line. On the contrary, although MTT analysis showed cytotoxic effect in BxPC-3 cell line treated with two pillar[5]arene derivatives, the apoptosis pathway was not active. This suggested that it may activate different death pathways for BxPC-3 cell line. Thus, it was first determined that the pillar[5]arene derivatives reduced cancer cell proliferation on pancreatic cancer cells.Öğe Elimination of EMG Artifacts From EEG Signal in Sleep Staging(IEEE, 2016) Ozsen, Seral; Yucelbas, Cuneyt; Yucelbas, Sule; Tezel, Gulay; Yosunkaya, Sebnem; Kuccukturk, SerkanSleep staging is a tiring and time-consuming process for the experts. Thus, attention given to automatic sleep staging studies is increasing gradually. Many factors such as effects of EOG and EKG signals to EEG result in contaminated signals rather than clear recorded signals. EMG contamination to EEG is among that kind of factors. In this study, some filters and Discrete Wavelet Transform based EMG artifact elimination process were evaluated on the performance of sleep staging process. Features were extracted from cleaned EEG signals and subjected to a classifier to conduct sleep staging. By using test classification accuracy as a measure of performance, the method giving highest accuracy was tried to be found. Artificial Neural Networks was used in the applications and Discrete Wavelet Transform was found to be the method giving the highest accuracy.Öğe Evaluation of coagulation with TEG in patients diagnosed COVID-19(Tubitak Scientific & Technological Research Council Turkey, 2022) Vatansev, Hulya; Karaselek, Mehmet Ali; Yilmaz, Resul; Kuccukturk, Serkan; Topal, Ahmet; Yosunkaya, Sebnem; Kucuk, AdemBackground and aim: A high D-dimer level may indicate the risk of coagulopathy and mortality in COVID-19 patients. Thromboelastography (TEG) is a test that evaluates clot formation and fibrinolysis in real-time, unlike routine coagulation tests. The study aimed to investigate the coagulation process with TEG in patients diagnosed with COVID-19. Materials and Methods: The study was performed at our university hospital, chest diseases outpatient clinic as a cross-section study. A total of 51 patients with 23 high D-dimer levels group (HDG) and 28 low D-dimers group (LDG) were included in the study. TEG analysis was performed at the pretreatment evaluation in these two groups. Results: D-dimer and fibrinogen levels of the HDG were higher than those of the LDG (550 vs. 90 ng/mL, p < 0.001; 521 vs. 269 mg/ dL, p < 0.001, respectively). In TEG analysis, HDG's R and K values were lower than LDG, and HDG's Angle, MA, and CI values were higher than LDG (p = 0.037; p < 0.001; p < 0.001; p < 0.001; p < 0.001, respectively). ROC curve analysis suggested that the optimum TEG parameters cut-off points for thrombosis risk were as below: for K was <_2.1 min, for R was <_6.1 min, for Angle was >62 degrees, MA was 60.4 mm. Conclusion: Our study showed that the risk of thrombosis might increase in COVID-19 patients who are not hospitalized in the intensive care unit. Thrombosis risk should be investigated with TEG analysis and laboratory tests in every patient diagnosed with COVID-19, and treatment should be started for risky patients.Öğe Impacts of potential anticancer agents based on pillar[5]arene for head and neck squamous cell carcinoma cells(Springer, 2023) Kuccukturk, Serkan; Karaselek, Mehmet Ali; Duran, Tugce; Kursunlu, Ahmed Nuri; Ozmen, MustafaPurposeThis study was conducted to investigate impacts of potential anticancer (associated with apoptosis and caspase pathways) of two newly synthesized derivatives of pillar[5]arene, named as d-Q-P5 and p-Q-P5, on Squamous cell carcinomas of the head and neck (HNSCC) cells.Materials and methodsThe MTT method was used to determine the IC50 doses of the derivatives on HNSCC cells, and the changes in gene expression were analyzed by real-time polymerase chain reaction (qPCR). The apoptosis change was confirmed by flow cytometry analysis.ResultsThe results showed that the d-Q-P5 and p-Q-P5 effectively inhibited the proliferation of the cells by upregulating proapoptotic genes (Bax, Bad, p53, Bak, and Apaf-1) and genes involved in the caspase pathway (Casp2, Casp3, and Casp9), while downregulating the antiapoptotic gene (Bcl-2).ConclusionsThis study is the first to demonstrate the potential anticancer effects of these two agents on HNSCC cells by positively regulating apoptosis gene expression.Öğe Is Hypnosis Innocent? Physiopathological Evaluation of Effect on Vital Findings(Wiley, 2018) Sunar, Fusun; Kuccukturk, Serkan[Abstract Not Availabe]Öğe A new approach to eliminating EOG artifacts from the sleep EEG signals for the automatic sleep stage classification(Springer, 2017) Dursun, Mehmet; Ozsen, Seral; Yucelbas, Cuneyt; Yucelbas, Sule; Tezel, Gulay; Kuccukturk, Serkan; Yosunkaya, SebnemInterference between EEG and EOG signals has been studied heavily in clinical EEG signal processing applications. But, in automatic sleep stage classification studies these effects are generally ignored. Thus, the objective of this study was to eliminate EOG artifacts from the EEG signals and to see the effects of this process. We proposed a new scheme in which EOG artifacts are separated from electrode or other line artifacts by a correlation and discrete wavelet transform-based rule. Also, to discriminate the situation of EEG contamination to EOG from EOG contamination to EEG, we introduced another rule and integrated this rule to our proposed method. The proposed method was also evaluated under two different circumstances: EOG-EEG elimination along the whole 0.3-35 Hz power spectrum and EOG-EEG elimination with discrete wavelet transform in 0-4 Hz frequency range. To see the consequences of EOG-EEG elimination in these circumstances, we classified pure EEG and artifact-eliminated EEG signals for each situation with artificial neural networks. The results on 11 subjects showed that pure EEG signals gave a mean classification accuracy of 60.12 %. The proposed EOG elimination process performed in 0-35 Hz frequency range resulted in a classification accuracy of 63.75 %. Furthermore, conducting EOG elimination process by using 0-4 Hz DWT detail coefficients caused this accuracy to be raised to 68.15 %. By comparing the results obtained from all applications, we concluded that an improvement about 8.03 % in classification accuracy with regard to the uncleaned EEG signals was achieved.Öğe A novel system for automatic detection of K-complexes in sleep EEG(Springer London Ltd, 2018) Yucelbas, Cuneyt; Yucelbas, Sule; Ozsen, Seral; Tezel, Gulay; Kuccukturk, Serkan; Yosunkaya, SebnemSleep staging process is applied to diagnose sleep-related disorders by sleep experts through analyzing sleep signals such as electroencephalogram (EEG), electrooculogram and electromyogram of subjects and determining the stages in 30-s-length time parts of sleep named as epochs. Subjects enter several stages during the sleep, and N-REM2 is one of them which has also the highest duration among the other stages. Approximately half of the sleep consists of N-REM2. One of the important parameters in determining N-REM2 stage is K-complex (Kc). In this study, some time and frequency analysis methods were used to determine the locations of Kcs, automatically. These are singular value decomposition (SVD), variational mode decomposition and discrete wavelet transform. The performance of them in detecting Kcs was compared. Furthermore, systems with combinations of these methods were presented with logic AND operations. The EEG recordings of seven subjects were obtained from the Sleep Research Laboratory of Necmettin Erbakan University. A database with total 359 Kcs in 320 epochs was prepared from the recordings. According to the results, the highest average recognition rate was found as 92.29% for the SVD method. Thanks to this study, the sleep experts can find out whether there were Kcs in related epochs and also know their locations in these epochs, automatically. Also, it will help automatic sleep stage classification systems.Öğe Pre-determination of OSA degree using morphological features of the ECG signal(Pergamon-Elsevier Science Ltd, 2017) Yucelbas, Sule; Yucelbas, Cuneyt; Tezel, Gulay; Ozsen, Seral; Kuccukturk, Serkan; Yosunkaya, SebnemObstructive sleep apnea (OSA) is a very common, but a difficult sleep disorder to diagnose. Recurrent obstructions form in the airway during sleep, such that OSA can threaten a breathing capacity of patients. Clinically, continuous positive airway pressure (CPAP) is the most specific and effective treatment for this. In addition, these patients must be separated according to its degree, with CPAP treatment applied as a result. In this study, 30 OSA patients from two different databases were automatically classified using electrocardiogram (ECG) data, identified as mild, moderate, and severe. One of the databases was original recordings which had 9 OSA patients with 8303 epochs and the other one was Physionet benchmark database which had 21 patients with 20,824 epochs. Fifteen morphological features could be identified when apnea was seen, both before and after it presented. Five data groups in total for first dataset and second dataset were prepared with these features and 10-fold cross validation was used to effectively determine the test data. Then, sequential backward feature selection (SBFS) algorithm was applied to understand the more effective features. The prepared data groups were evaluated with artificial neural networks (ANN) to obtain optimum classification performance. All processes were repeated for ten times and error deviation was calculated for the accuracy. Furthermore, different classifiers which are frequently used in the literature were tested with selected features. The degree of OSA was estimated from three epochs in pre-apnea data, yielding the success rates of 97.20 +/- 2.15% and 90.18 +/- 8.11% with the SBFS algorithm for the first and second datasets, respectively. Also, SVM classifier followed ANN system in the success rates of 96.23 +/- 3.48% and 88.75 +/- 8.52% for used datasets. (C) 2017 Elsevier Ltd. All rights reserved.
