Halic University
  • Istanbul, Turkey
Recent publications
Software-Defined Network (SDN) and Network Function Virtualization (NFV) are key enablers for provisioning dynamic, virtual security services on demand. This article, presents a novel Group Key Management scheme for Low-Resource Devices (GKM-LRD) with SDN aided trusted key management server as a central server to provide key management service to groups formed in Internet of Things (IoT) applications. In addition to the group key management scheme, a lightweight packet key-based communication system is proposed to make the data traffic reliable. Packet keys are short sized keys acquiring the lifetime of a packet. Even though the key is short sized, the security strength comes from its short lifetime. The proposed GKM-LRD is evaluated in terms of computation load, communication load, storage and scalability in comparison with the existing group key management schemes. The computation load, communication load and storage load is reduced by 80%, 17.25% and 20% respectively in comparison with the existing system assuring the scheme as lightweight and applicable for IoT devices. The proposed packet key-based communication scheme is compared with an existing Diffie-Hellman based packet key system. The results show the system is comparatively lightweight with computation load reduced by 74.8%. The security analysis of the proposed scheme proves that the scheme ensures forward secrecy, backward secrecy and resistance to man-in-the-middle and replay attacks.
The present study focuses on the thermo-mechanical modelling of pristine graphyne, BN-substituted graphyne, and graphyne-like BN utilizing molecular dynamics (MD) simulation. Considering the results of uniaxial tensile MD simulations, respective structures indicate outstanding mechanical properties. In particular, the pristine graphyne (note that it only consists of C–C atomic bond type) has superior mechanical properties compared to others. Besides, graphyne-like BN demonstrates the lowest mechanical properties due to consisting of only B–N bonds. MD simulations are conducted for different temperatures and strain rates varying between 1 K–1200 K and 107 s−1–109 s−1, respectively. With increasing temperature, a gradual decrease in mechanical properties is observed due to the high temperature’s weakening effect. Mechanical properties of graphyne-like BN are affected by the change in temperature more than other structures. Furthermore, findings of MD simulation show that the mechanical properties of aforementioned structures have an increasing trend with increasing strain rates. Similar to mechanical properties, pristine graphyne, BN-substituted graphyne, and graphyne-like BN have superior thermal conductivity (TC) properties. Non-equilibrium MD simulation results illustrate that the pristine graphyne containing C–C bonds exhibits the largest TC value. In contrary, the graphyne-like BN comes up with a low TC value. Temperature increase (from 200 to 900 K) affects TC values negatively owing to increase in phonon–phonon scattering. Finally, the results of this study make aforementioned structures a splendid competitor for thermo-mechanical practice of 2D-based structures.
The spectral properties of the molecules depend on the matrix in which the interactions with other molecules inside the matrix affect the vibrational and rotational modes of the molecule. In this study, an absorption-based system was designed to show how the absorbance properties of the glucose change in polyacrylamide (PAAm) hydrogel when compared with water. The measurements were performed at different wavelengths; 960 nm, 1450 nm, 1550 nm, and 1950 nm and it was observed that the system is sensitive to glucose at the wavelengths of 1450 and 1950 nm in PAAm hydrogel, whereas it is only sensitive at 1450 nm in water which is due to the high absorbance of water at 1950 nm. In PAAm hydrogel, water molecules mostly gather around the polymer chains via electrostatic interactions and the absorbance of water decreases which results in an increasing absorbance of glucose. According to the results, the responsivity of the system at 960 and 1550 nm, which are the wavelengths commonly used in LED-based systems for measuring glucose in literature, is not high enough for reliable glucose measurements when compared with 1450 and 1950 nm.
Massive, diverse, and high‐frequency Internet of Things (IoT) applications pose challenges to the operation of cluster systems that serve it. Fair and efficient multidimensional resource allocation is of great significance to the sustainable operation of these systems. However, most of the existing cluster multiresource allocation optimization researches focus too much on the fairness of resource allocation and ignore the efficiency. The unbalanced use of multidimensional system resources reduces the effective utilization of system resources, which seriously affects the service quality of IoT applications. In this paper, we define the multiresource fair and efficient sharing optimization as a fairness‐constrained efficiency optimization problem, which is from dynamics, discrete resources, and heterogeneous perspectives according to the characteristics of cluster system in practical. Moreover, we present a dynamic efficiency‐aware multiresource fair allocation algorithm, DEF, which can improve the ability of the cluster system to serve diverse IoT applications. In the algorithm, large jobs schedule to the servers that expect the least remaining resources. Simulations performed using Google cluster‐usage traces show that DEF can improve system resource utilization and guarantee the fairness of sharing among users.
In our study, we aimed to investigate the relationship between microRNA (miRNA) expression levels and serum iron (Fe), copper (Cu), and zinc (Zn) levels in Multiple sclerosis (MS) patients. Total RNA was isolated from peripheral venous blood containing ethylenediaminetetraacetic acid (EDTA) of MS patients and controls. Total RNA was labeled with Cy3-CTP fluorescent dye. Hybridization of samples was performed on microarray slides and arrays were scanned. Data argument and bioinformatics analysis were performed. Atomic absorption spectrophotometer method was used to measure serum Fe, Cu, and Zn levels. In our study, in bioinformatics analysis, although differently expressed miRNAs were not detected between 16 MS patients and 16 controls, hsa-miR-744-5p upregulation was detected between 4 MS patients and 4 controls. This may be stem from the patient group consisting of MS patients who have never had an attack for 1 year. Serum iron levels were detected significantly higher in the 16 MS patients compared to the 16 controls. This may be stem from the increase in iron accumulation based on inflammation in MS disease. According to the findings in our study, hsa-miR-744-5p upregulation has been determined as an early diagnostic biomarker for the development together of insulin resistance, diabetes mellitus associated with insulin signaling, and Alzheimer’s diseases. Therefore, hsa-miR-744-5p is recommended as an important biomarker for the development together of diabetes mellitus, Alzheimer’s disease, and MS disease. In addition, increased serum Fe levels may be suggested as an important biomarker for neurodegenerative diseases such as Parkinson’s disease, Alzheimer’s disease, and MS disease.
Cyber security encompasses a variety of financial, political, and social aspects with significant implications for the safety of individuals and organisations. Hospitals are among the least secure and most vulnerable organisations in terms of cybersecurity. Protecting medical records from cyberattacks is critical for protecting personal and financial records of those involved in medical institutions. Attack graphs, like in other systems, can be used to protect medical and hospital records from cyberattacks. In the current study, a total of 352 real-life cyberattacks on healthcare institutions using common vulnerability scoring system (CVSS) data were statistically examined to determine important trends and specifications in regard to those attacks. Following that, several machine learning techniques and an artificial neural network model were used to model industrial control systems (ICS) vulnerability data of those attacks. The average vulnerability score for attacks on healthcare IT systems was found to be very high. Moreover, this score was found to be higher in healthcare institutions which have experienced cyberattacks in the past and no mitigation actions were implemented. Using Python programming software, the most successful model that can be used in modelling cyberattacks on IT systems of healthcare institutions was found to be the K-nearest neighbours (KNN) algorithm. The model was then enhanced further and then it was tried to make predictions for future cyberattacks on IT systems of healthcare institutions. Results indicate that the overall score is critical indicating that medical records are, in general, at high risk and that there is a high risk of cyberattacks on medical records in healthcare institutions. It is recommended, therefore, that those institutions should take urgent precautionary measures to mitigate such a high risk of cyberattacks and to make them more secure, reliable, and robust.
Background The aim of our study is to investigate the roles of IL-8 (+ 781 C/T) and MMP-2 (-735 C/T) gene variations in early diagnosis and progression of BCA. Methods Polymerase chain reaction (PCR) followed by restriction fragment length polymorphism (RFLP) methods were used to determine the genotype distributions of IL-8 (+ 781 C/T) and MMP-2 (-735 C/T) gene variations. Results In our study, the genotype distributions of IL-8 (+ 781 C/T) and MMP-2 (-735 C/T) gene variations were not found to be significantly different between the patient and control groups. In addition, C and T allele frequencies for these gene variations were not different from the Hardy-Weinberg distribution in patient and control groups. However, when the combined genotype analyzes for these gene variations were evaluated, CC-CC and CT-CC combined genotypes for + 781 C/T / -735 C/T gene variations were observed significantly more in the patient group compared to other genotypes. Conclusion Although IL-8 (+ 781 C/T) and MMP-2 (-735 C/T) gene variations were not found to be genetic risk factors in the Thrace population in our study, CC-CC and CT-CC combined genotypes were determined as genetic risk factors for BCA susceptibility. The combined genotypes obtained as a result of the combined genotype analysis of these genetic variations that are effective in tumor progression may be considered to be important biomarkers for the early diagnosis and progression of BCA.
Energy distribution systems and cyber-physical systems brought together information technology, electrical and mechanical engineering in an integrated manner. This cybernetic–mechatronics development has drawn the attention of both cybercriminals and cybersecurity researchers by expanding the attacks in critical infrastructures. With the development of information communication technology, supervisory control and data acquisition (SCADA) systems will turn into cloud-based systems that can communicate with IoT devices in the future. In addition, SCADA systems can be utilized in hospitals for various aspects and in IoT healthcare environments. However, SCADA protocols communicate on text and do not have a generalized security structure. Intrusion detection systems are structures developed against cyber-attacks that may cause serious damage. These systems try to provide the highest level of security, including both software and hardware structures. In this work, attack detection based on artificial intelligence and machine learning techniques is performed for the classification of attack threats in cyber-physical systems. Intrusion detection based on artificial intelligence and machine learning techniques is performed for the detection and classification of threats against cyber-physical systems. In this context, attack type classification is performed using machine learning algorithms. At the same time, performance evaluation realized by using computational metrics on machine learning algorithms. Attack type determination and performance analysis were carried out in the test environment and the results were discussed.
This study explores the machine learning-based assessment of predisposition to colorectal cancer based on single nucleotide polymorphisms (SNP). Such a computational approach may be used as a risk indicator and an auxiliary diagnosis method that complements the traditional methods such as biopsy and CT scan. Moreover, it may be used to develop a low-cost screening test for the early detection of colorectal cancers to improve public health. We employ several supervised classification algorithms. Besides, we apply data imputation to fill in the missing genotype values. The employed dataset includes SNPs observed in particular colorectal cancer-associated genomic loci that are located within DNA regions of 11 selected genes obtained from 115 individuals. We make the following observations: (i) random forest-based classifier using one-hot encoding and K-nearest neighbor (KNN)-based imputation performs the best among the studied classifiers with an F1 score of 89% and area under the curve (AUC) score of 0.96. (ii) One-hot encoding together with K-nearest neighbor-based data imputation increases the F1 scores by around 26% in comparison to the baseline approach which does not employ them. (iii) The proposed model outperforms a commonly employed state-of-the-art approach, ColonFlag, under all evaluated settings by up to 24% in terms of the AUC score. Based on the high accuracy of the constructed predictive models, the studied 11 genes may be considered a gene panel candidate for colon cancer risk screening.
Background: Cardiorespiratory system involvement and early fatigue observed in stroke patients complicate the rehabilitation process and affect their ability to perform daily activities and functional independence. Aim: It was aimed to determine the relationship between respiratory functions and respiratory muscle strength with trunk control, functional capacity, and functional independence in hemiplegic patients after stroke. Materials and methods: Twenty-five volunteers who were diagnosed with post-stroke hemiplegia were included in the study. Sociodemographic and physical characteristics were recorded. Pulmonary function test (PFT), respiratory muscle strength, Trunk Impairment Scale (TIS), Timed-Up and Go Test (TUG), and Barthel Index (BI) were applied. Results: There was a moderate negative correlation between TUG scores and PFT results (r = 0.413-0.502; p = 0.011-0.04), except for PEF (%) and FEV1/FVC. Also, there were statistically significant correlation between TIS scores and FEV1(%) (r = 0.505; p = 0.012), FVC(%) (r = 0.449; p = 0.024). On the other hand, there was no statistically significant relationship between BI results and any parameter of the PFT (p > 0.05). There was no statistically significant correlation between respiratory muscle strength and TUG, TIS, BI (p > 0.05). Conclusion: It has been shown that respiratory functions are associated with functional capacity and trunk control. However, it was found that there was no relationship between respiratory muscle strength and functional capacity, trunk control, and functional independence. It is thought that considering these parameters in the assessment of patients will contribute to the creation of individual and effective rehabilitation programs. The respiratory system should be systematically assessed in stroke rehabilitation and considered as part of a holistic approach. Clinical trial registration: NCT05290649 (retrospectively registered) (clinicaltrials.gov).
In this study, the characteristics of the Covid-19 pandemic in Turkey are examined in terms of the number of cases and deaths, and a characteristic prediction is made with an approach that employs artificial intelligence. The number of cases and deaths are estimated using the number of tests, the numbers of seriously ill and recovered patients as parameters. The machine learning methods used are linear regression, polynomial regression, support vector regression with different kernel functions, decision tree and artificial neural networks. The obtained results are compared by calculating the coefficient of determination (R²), and the mean absolute percentage error (MAPE) values. When R² and MAPE values are compared, it is seen that the optimal results for cases in Turkey are obtained with the decision tree, for deaths with polynomial regression method. The results reached for the United States of America and Russia are similar and the optimal results are obtained by polynomial regression. However, while the optimal results are obtained by neural networks in the Indian data, linear regression for the cases in the Brazilian data, neural network for the deaths, decision tree for the cases in France, polynomial regression for the deaths, neural network for the cases in the UK data and decision tree for the deaths are the methods that produced the optimal results. These results also give an idea about the similarities and differences of country characteristics.
The human neck is a resilient biological structure connecting the head to the body. It hosts different kinds of tissues including bones, muscles, skin, vertebra, discs, nerves and the spinal cord. These structures work together as one unit to provide stability and facilitate functionality to the head. However, accident or sport-related dynamic striking to the head is resisted entirely by the neck structure. Based on Machine Learning principles, the purpose of this paper is to attempt to derive a workable biomechanical–machine learning formula of the neck stiffness as represented by a single spring. Such a formula would help in developing applications in head and neck healthcare applications. Findings of this derivation demonstrate that stiffness of the neck as one unit depends on the maximum voluntary contraction its muscles can exert in a specific direction. Healthcare implications of the findings are discussed at the end.
Objective: The aim of this study was to determine the effect of online breastfeeding counseling after cesarean section on breastfeeding success and anthropometric measurements of the baby in the first 6 months. Methods: The study was conducted with single-blind randomized controlled experimental research design and performed with 151 primiparous women as intervention (n=76) and control (n=75) groups. The mothers were given training in the first 24 h postpartum by applying the "Data Collection Form," "Breastfeeding and Infant Follow-up Form," and "Breastfeeding Self-Efficacy Scale - Short Form," who followed up at the first and sixth months, and further again for 6 months. Results: Although there was no difference and homogeneity at the beginning of study among the participants in the intervention group compared with the control group, it was observed that the breastfeeding rates at the first and sixth months were higher and significant. When the anthropometric measurements of the participants in both the groups were compared, it was found that there was a significant difference between the measurements of height and weight at discharge, first, and sixth months. Breastfeeding self-efficacy scores in the intervention group were significantly higher at discharge, 4 weeks postpartum, and 6 months postpartum than those in the control group (p<0.05). Conclusions: Breastfeeding training and online counseling given to mothers who give birth by cesarean section during the early postpartum period increased breastfeeding rates and self-sufficiency, and the anthropometric measurements of babies were found to be higher at healthy limits.
Objective: We aimed to examine the predictive and prognostic value of plasma zonulin for gestational diabetes mellitus (GDM) in women at 24-28 weeks of gestation. Methods: This retrospective study was carried out with pregnant women with GDM (n=98) and normal glucose tolerance (control group) (n=132). GDM was diagnosed according to American Diabetes Association (ADA) criteria with a one-step 75-g OGTT at 24-28 gestational weeks. Their serum zonulin levels measured during one-step 75-g OGTT and perinatal outcomes were compared, and the cut-off value of plasma zonulin for the prediction of GDM was calculated with receiver operating characteristic curve analysis. Results: Plasma zonulin level was significantly higher in women with GDM compared to controls (28.8±24.9 and 7.3±11.3 ng/mL, respectively). According to logistic regression analysis, plasma zonulin levels and GDM were statistically significant. The plasma zonulin cut-off value was>45.2 ng/mL. The rate of cesarean section, the rate of meconium in the amniotic fluid, and the need for admission to the neonatal intensive care unit significantly differed between women with GDM and controls. Conclusion: In pregnant women with GDM, plasma zonulin increases, and with the cut-off level of>45.2 ng/mL, it can predict GDM with values of sensitivity and specificity levels significantly higher in pregnant women with GDM, suggesting that it can be used as a tool for its screening and early diagnosis.
Background This study aims compare the pregnancy and live birth rates between the oocytes retrieved without follicular flushing FF(-) in the oocyte pick-up (OPU) procedure performed in women with diminished ovarian reserve (DOR) and those retrieved by follicular flushing FF(+). Results The study was conducted among patients diagnosed with DOR according to Bologna criteria and applied to the clinic for IVF between 2017–2020. A total of 358 infertile women with follicles three and below on the hCG day, between the ages of 21 and 42, without severe male factor, without uterine anomaly, without uterine surgery, and who did not undergo PGD were included in the study. Each follicle was aspirated once in the OPU procedure, and if a follicle was retrieved, it was moved to the other follicle. If the follicle could not be retrieved, the oocyte was tried to be retrieved by flushing a maximum of 3 times. The number of oocytes retrieved, clinical pregnancy rate, and live birth rate were compared. Since all the oocytes retrieved in 143 patients were retrieved directly without the need for FF, it was named FF(-) group. Since at least one oocyte of the remaining 215 patients was retrieved by performing FF, it was named FF(+) group. Since some of the oocytes retrieved from 112 patients in the FF(+) group were retrieved with FF and some without FF, they were excluded from the study, and the remaining 103 cases formed the FF(+) group a total of 246 patients were compared. The mean number of MII oocytes ,the pregnancy rates, rates of live births and the abortion rates between two groups did not show any statistical difference. Conclusion FF applied during oocyte retrieval in DOR did not positively affect the number of retrieved oocytes, clinical pregnancy, and live birth rates even doing this may decrease the pregnancy rate because of the probable low quality egg but we should not forget that if we did not do flushing after once we aspirated the follicle we would not be able to obtain any pregnancy at all in this patients.
Transcranial direct current stimulation (tDCS) studies in healthy volunteers have shown conflicting results in terms of modulation in pain thresholds. The aim of this study was to investigate how single session anodal tDCS and modulated tDCS (mtDCS) of distinct cortical areas affected pain and perception thresholds in healthy participants. Five different stimulation conditions were applied at different cortical sites to 20 healthy volunteers to investigate the effects of tDCS and mtDCS (20 Hz) on pain and perception thresholds. TDCS over the motor cortex (M1), mtDCS over the motor cortex, tDCS over the dorsolateral prefrontal cortex (DLPFC), mtDCS of the DLPFC, and mtDCS over the occipital cortex were the stimulation conditions. All of the stimulations were anodal. The stimulations were given in a randomized order at 20-minute intervals. For comparison, electrical pain and perception thresholds were obtained from the right middle finger before and during the tDCS. After each measurement, participants were asked to give a score to their pain. In repeated measures analysis of variance (RM-ANOVA) test, the Condition × Time interaction showed no significant influence on changes in pain, perception thresholds, and pain scores ( p = .48, p = .89, and p = .50, respectively). However, regardless of the condition types, there was a significant difference in pain and perceptual thresholds during tDCS ( p = .01, p = .025, respectively). Our findings did not support difference in pain and perception modulation by a single session anodal tDCS over M1 and DLPFC compared to the occipital cortex in healthy volunteers. The increase in all thresholds during tDCS, irrespective of conditions, and peripheral sensations, including an active control group, taken together, suggest a placebo effect of active tDCS. Future studies about pain and perception in healthy subjects should consider the level of experimental pain and a strong placebo effect.
The aim of this study is to determine the roles of eNOS gene variations in BCA development. Our study included 91 patients diagnosed with BCA and 91 healthy controls. eNOS 4VNTR (4a/b), T786C and G894T gene variations genotype distributions were determined by PCR and RFLP methods. The significant difference was determined between these groups in terms of eNOS T786C and eNOS G894T gene variations genotype distributions (p < 0.05). TT genotype for G894T gene variation and CC genotype for T786C gene variation were detected higher in patients. The CC genotype of T786C gene variation was detected significantly higher in male patients than in male controls (p < 0.05). In addition, aa-TT, ab-TT, bb-TT haplotypes of 4VNTR (4a/b)-G894T gene variations, aa-CC, ab-CC, bb-CC haplotypes of 4VNTR (4a/b)-T786C gene variations and TT-TT, TT-CC, TT-CT, GG-CC, GT-CC haplotypes of G894T-T786C gene variations were observed in patient group more than control group. The significant difference was detected between these groups in terms of eNOS (G894T-T786C) haplotypes (p < 0.05). In our study, eNOS T786C and eNOS G894T gene variations were determined important genetic risk factor in the Thrace population of Turkey.
Background This study aims compare the pregnancy and live birth rates between the oocytes retrieved without follicular flushing FF(-) in the oocyte pick-up (OPU) procedure performed in women with diminished ovarian reserve (DOR) and those retrieved by follicular flushing FF(+). Results The study was conducted among patients diagnosed with DOR according to Bologna criteria and applied to the clinic for IVF between 2017–2020. A total of 358 infertile women with follicles three and below on the hCG day, between the ages of 21 and 42, without severe male factor, without uterine anomaly, without uterine surgery, and who did not undergo PGD were included in the study. Each follicle was aspirated once in the OPU procedure, and if a follicle was retrieved, it was moved to the other follicle. If the follicle could not be retrieved, the oocyte was tried to be retrieved by flushing a maximum of 3 times. The number of oocytes retrieved, clinical pregnancy rate, and live birth rate were compared. Since all the oocytes retrieved in 143 patients were retrieved directly without the need for FF, it was named FF(-) group. Since at least one oocyte of the remaining 215 patients was retrieved by performing FF, it was named FF(+) group. Since some of the oocytes retrieved from 112 patients in the FF(+) group were retrieved with FF and some without FF, they were excluded from the study, and the remaining 103 cases formed the FF(+) group a total of 246 patients were compared. The mean number of MII oocytes ,the pregnancy rates, rates of live births and the abortion rates between two groups did not show any statistical difference. Conclusion FF applied during oocyte retrieval in DOR did not positively affect the number of retrieved oocytes, clinical pregnancy, and live birth rates even doing this may decrease the pregnancy rate because of the probable low quality egg but we should not forget that if we did not do flushing after once we aspirated the follicle we would not be able to obtain any pregnancy at all in this patients.
Objective: To evaluate the relationship between calciferol (vitamin D), cobalamin (vitamin-B12), and Stromelysin-1 (MMP-3) circulating levels in patients with diabetic peripheral neuropathy (DPN), patients with DM type 2 (T2DM) without neuropathy, and healthy control groups. Study design: Cross-sectional descriptive study. Place and duration of study: Department of Internal Medicine, Namik Kemal University of Medicine, Tekirdag, Turkey, between November 2020 and February 2022. Methodology: Healthy, age, and gender matched volunteers who were admitted to the hospital for a check-up with no health problem constituted the control group (n=30). Cases diagnosed with T2DM (n=30) and those with DPN (n=30) comprised the experimental group. Stromelysin-1, calciferol, and cobalamin levels were analysed from blood samples from all groups using enzyme-linked immunosorbent assay (ELISA) with a commercial kit. Tukey's Honest Significant Difference (HSD) test was performed after one-way analysis of variance (ANOVA) for intergroup comparisons. Alpha significance level was accepted as.
Background: Diabetes mellitus leads to endothelial dysfunction and accumulation of oxygen radicals. Sulfasalazine-induced Nrf2 activation reduces oxidative stress in vessels. Thus, in the present study, we investigated the effects of sulfasalazine on endothelial dysfunction induced by high glucose. We also ascribed the underlying mechanism involved in glucose-induced endothelial dysfunction. Methods: For this experiment we used 80 Wistar Albino rats thoracic aorta to calculate the dose response curve of noradrenaline and acetylcholine. Vessels were incubated in normal and high glucose for 2 h. To investigate glucose and sulfasalazine effects the vessels of the high glucose group were pre-treated with sulfasalazine (300 mM), JNK inhibitor (SP600125), and ERK inhibitor (U0126) for 30 min. The dose response curve was calculated through organ bath. The eNOS, TAS, TOS, and HO-1 levels were estimated by commercially available ELISA kits. Results: In the high glucose group, the E max for contraction was significantly higher ( p < 0.001), and E max for relaxation was lower than that of control. These functional changes were parallel with the low levels of eNOS ( p < 0.05). High glucose vessel treated with sulfasalazine showed low E max value for contraction ( p < 0.001) however, the E max for relaxation was significantly high ( p < 0.001) when compared to high glucose group. In the JNK group, E max for contraction and relaxation was inhibited ( p < 0.001) compared to sulfasalazine treated vessels. HO—1 enzyme levels were significantly low ( p < 0.01) with sulfasalazine but higher with ERK inhibitor ( p < 0.05). Conclusion: High glucose induced endothelial dysfunction and sulfasalazine reduced damage in high glucose vessels by activating eNOS, antioxidant effect through HO-1 enzymes and particularly inducing Nrf2 via the ERK and JNK pathways.
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Salaheddine Bendak
  • Department of Industrial Engineering
Tahsin Beyzadeoglu
  • School of Health Sciences
Zafer Utlu
  • Department of Mechanical Engineering
Nuri Gökhan Torlak
  • Department of Business Administration
Alireza Souri
  • Department of Software Engineering
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