* Akademik Arşiv

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18β-Glycyrrhetinic Acid-Loaded Silver Nanoparticles Mitigate Neuroinflammation and Endoplasmic Reticulum Stress in the Brain Tissue of Diabetic Rats
(Mashhad University of Medical Sciences, 2026) Parlak, Secil Nazife; Yakut, Seda; Kara, Adem; Demir, Ozlem; Sebin, Saime Ozbek
Objective(s): Diabetes mellitus (DM) causes oxidative stress, neuroinflammation, and endoplasmic reticulum (ER) dysfunction that contribute to neurodegeneration. This study investigated the effects of 18 beta-glycyrrhetinic acid-loaded silver nanoparticles (18 beta-GA-AgNPs) on brain injury in diabetic rats. Materials and Methods: Fifty-six male Wistar rats were divided into eight groups: Sham, 18 beta-GA, AgNPs, 18 beta-GA-AgNPs, DM, DM+18 beta-GA, DM+AgNPs, and DM+18 beta-GA-AgNPs. Diabetes was induced by alloxan (120 mg/kg, IP), and treatments were administered orally for 14 days. Biochemical markers (MDA, GSH, SOD), histopathology, and expression of ER stress and apoptotic proteins (ATF6, IRE1, Caspase-3, BCL-2, CREB, TNF-alpha, and IL-1 beta) were evaluated. Results: The DM group exhibited significant increases in MDA, TNF-alpha, IL-1 beta, ATF6, and Caspase-3 with reduced GSH, SOD, and BCL-2, indicating oxidative stress, inflammation, apoptosis, and ER stress. In contrast, IRE1 levels remained unchanged in DM rats but showed a slight elevation in the AgNPs group. Treatment with 18 beta-GA-AgNPs markedly reduced MDA, TNF-alpha, IL-1 beta, ATF6, and Caspase-3, while restoring GSH, SOD, BCL-2, and CREB expression. Histopathological analysis confirmed neuronal apoptosis and perivascular and extracellular space enlargement in DM rats, whereas 18 beta-GA-AgNPs substantially attenuated these changes. Overall, 18 beta-GA-AgNPs provided synergistic neuroprotection by suppressing oxidative stress, inflammation, and ER stress while enhancing antioxidant and anti-apoptotic defenses. Conclusion: These findings suggest that 18 beta-GA-AgNPs may represent a promising therapeutic strategy against diabetes-associated neurodegeneration, although further long-term, ultrastructural, and sex-inclusive studies are warranted.
Citation - WoS: 5
Citation - Scopus: 4
3-Aminobenzamide Multifunctional Nanoparticles Enhances Anticancer Activity of Low-Dose Cisplatin Chemotherapy in Lung Adenocarcinoma
(Elsevier, 2024) Kaci, Fatma Necmiye; Daglioglu, Cenk
Chemotherapy is one of the main treatment methods for cancer patients, but its effectiveness is limited by drug resistance. Combining a chemotherapeutic agent with targeted molecular therapy may improve the curative effect of the chemotherapeutic agent. In this study, we investigate the efficacy of combining a 3-Aminobenzamide (3AB)-linked multifunctional platform with low-dose cisplatin chemotherapy aiming to modulate poly [ADP-ribose] polymerase 1 (PARP1) function in DNA repair to increase cytotoxic activity of the platinum-based cisplatin. The structure of the synthesized nanoplatforms was characterized by several physicochemical techniques, including dynamic light scattering (DLS), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and an in vitro pH-dependent release study. Cellular uptake experiments demonstrated preferentially targeted delivery of nanoparticles in lung carcinoma A549 cells, whereas the cellular uptake capacity was minimal in normal lung BEAS-2B cells. On the other hand, cytotoxicity experiments showed a reduction of cancer cell viability compared to free formulations. Furthermore, the combination treatment was examined by detecting the loss of mitochondrial membrane potential and the apoptotic cell population, confirming the treatment's functional involvement in apoptosis. Soft agar colony formation and cell invasion tests were also performed to detect the cancer cell's tumorigenic potential, confirming the synergistic effect of this combination in the reduction of tumorigenicity. Moreover, we analyzed the expression profiles of three candidate genes, which play important roles in cancer initiation, promotion and progression. Cell biology experiments indicated that this novel combination treatment possesses significant synergy between 3AB and low-dose cisplatin and is promising for development as an antitumor treatment for lung cancer.
Citation - WoS: 28
Citation - Scopus: 31
3-D Non-Linear Stress Analysis on the Adhesively Bonded Composite Joint Under Bending Moment
(Pergamon-Elsevier Science Ltd, 2014) Akpinar, Salih; Aydin, Murat Demir
This paper presents an approach to predict the three-dimensional effects (anti-clastic, free edge and bending-twisting coupling effects) and to assess the effects of the fiber orientation angle of the laminates on the stress distributions and the failure prediction in the Single Lap Composite Joints (SLJs) subjected to a bending moment via a 3-D non-linear finite element method. In the analysis, the composite adherends (AS4/3501-6) with five different fiber orientation angles ([901 +/- 45/0](2s), [0/90](4s), [45-45](4s), [0](16) and [90](16)) were assumed to behave as linearly elastic materials while the adhesive layer (FM 73) was assumed to be nonlinear. Also, the nonlinear geometric deformations of the SLJs were also taken into account. Consequently, it is seen that the state of stress in the vicinity of the free edge of the joint is fully three dimensional which has not been taken into account in any classical theory so far and the normal and shear stress distributions are extremely sensitive to this three-dimensional effects. From this aspect, the three-dimensional finite element analysis is a necessity for understanding explicitly the stress and failure states. Also, for both the adherends and the adhesive layer, the ply stacking sequence has a significant effect on the stress distribution and the failure. (C) 2014 Elsevier Ltd. All rights reserved.
3D Skeleton-Based Sport Action Recognition System via Deep Learning
(Institute of Electrical and Electronics Engineers Inc., 2024) Dayapoglu, M.; Savirdi, E.; Akcaba, I.; Alp, S.; KüÇük, S.
In this study a system based on deep learning was developed to recognize 5 sports movements (kick, straight punch, hook, uppercut, serve). In the first stage, an application was developed for the simultaneous capture of Red Green Blue (RGB) video frames and three-dimensional (3D) skeleton data using a specialized camera. The developed system includes a user-friendly interface for data collection and video recording editing. To identify these sports movements, videos were recorded from ten different individuals, from 5 different angles, with 2 repetitions each, creating a custom dataset containing 500 samples. To characterize the temporal dependencies in the skeletal data in this dataset, 1D-CNN (One-Dimensional Convolutional Neural Network) and LSTM (Long Short-Term Memory) deep learning models were used, and the effectiveness of combining these models was investigated. The best-performing model was determined through cross-validation. Different activation functions and optimizer combinations were analyzed in detail for this model. With the best-performing model, a classification accuracy exceeding %87 was achieved for the 5 sports movements. © 2024 IEEE.
Citation - WoS: 13
Citation - Scopus: 17
Accurate Estimation of T Year Extreme Wind Speeds by Considering Different Model Selection Criterions and Different Parameter Estimation Methods
(Pergamon-Elsevier Science Ltd, 2018) Tosunoglu, Fatih
Accurate estimation of extreme wind speeds for different return periods is necessary to avoid extensive costs or large damages. To achieve this aim, the probability distribution of the wind speed data should be well defined and its parameters should be more precisely estimated. In this study, the commonly used probability distributions, including Gamma, Generalized Extreme Value, Logistic, Lognormal, Normal and Weibull, are fitted to annual maximum wind speed data in Turkey. Parameters of the fitted distributions are estimated using method of moments (MOM), method of maximum likelihood (MLM) and method of probability weighted moments (PWMs). Based on various model selection criterions (Akaike Information Criterion, Bayesian Information criterion, Anderson-Darling, Cramer-von-Mises, and Kolmogorov-Smirnov tests), the Generalized Extreme Value and Logistic, which provided the best fit for 40% and 30% of the series, respectively, were mostly found to be the most suitable distributions. Additionally, the Lognormal, Normal and Gamma distributions showed the best fit for 15%, 10% and 5% of the series, respectively. Moreover, the MLM and PWMs provided better parameter estimations for 57% and 30% the best fitted distributions, respectively. Furthermore, wind speed quantiles with the standard errors in various return periods were estimated using the best fitted distributions. (C) 2018 Elsevier Ltd. All rights reserved.
Citation - WoS: 137
Citation - Scopus: 144
Acetylcholinesterase and Carbonic Anhydrase Inhibitory Properties of Novel Urea and Sulfamide Derivatives Incorporating Dopaminergic 2-Aminotetralin Scaffolds
(Pergamon-Elsevier Science Ltd, 2016) Ozgeris, Bunyamin; Goksu, Suleyman; Kose, Leyla Polat; Gulcin, Ilhami; Salmas, Ramin Ekhteiari; Durdagi, Serdar; Supuran, Claudiu T.
In the present study a series of urea and sulfamide compounds incorporating the tetralin scaffolds were synthesized and evaluated for their acetylcholinesterase (AChE), human carbonic anhydrase (CA, EC 4.2.1.1) isoenzyme I, and II (hCA I and hCA II) inhibitory properties. The urea and their sulfamide analogs were synthesized from the reactions of 2-aminotetralins with N,N-dimethylcarbamoyl chloride and N,N-dimethylsulfamoyl chloride, followed by conversion to the corresponding phenols via O-demethylation with BBr3. The novel urea and sulfamide derivatives were tested for inhibition of hCA I, II and AChE enzymes. These derivatives exhibited excellent inhibitory effects, in the low nanomolar range, with K-i values of 2.61-3.69 nM against hCA I, 1.64-2.80 nM against hCA II, and in the range of 0.45-1.74 nM against AChE. In silico techniques such as, atomistic molecular dynamics (MD) and molecular docking simulations, were used to understand the scenario of the inhibition mechanism upon approaching of the ligands into the active site of the target enzymes. In light of the experimental and computational results, crucial amino acids playing a role in the stabilization of the enzyme-inhibitor adducts were identified. (C) 2016 Elsevier Ltd. All rights reserved.
Citation - WoS: 10
Citation - Scopus: 11
Acgc: Adaptive Chrominance Gamma Correction for Low-Light Image Enhancement
(Academic Press Inc. Elsevier Science, 2025) Severoglu, N.; Demir, Y.; Kaplan, N. H.; Kucuk, S.
Capturing high-quality images becomes challenging in low-light conditions, often resulting in underexposed and blurry images. Only a few works can address these problems simultaneously. This paper presents a low- light image enhancement scheme based on the Y-I-Q transform and bilateral filter in least squares, named ACGC. The method involves applying a pre-correction to the input image, followed by the Y-I-Q transform. The obtained Y component is separated into its low and high-frequency layers. Local gamma correction is applied to the low-frequency layers, followed by contrast limited adaptive histogram equalization (CLAHE), and these layers are added up to produce an enhanced Y component. The remaining I and Q components are also enhanced with local gamma correction to provide images with amore natural color. Finally, the inverse Y-I-Q transform is employed to create the enhanced image. The experimental results demonstrate that the proposed approach yields superior visual quality and more natural colors compared to the state-of-the-art methods.
Citation - Scopus: 6
Adaptive Consensus-Based Formation Control of Fixed-Wing MUAVs
(Institute of Electrical and Electronics Engineers Inc., 2017) Guzey, M.
Neural Network-based adaptive consensus control is designed in this paper for a team of fixed-wing unmanned aerial vehicles. The group of unmanned aerial vehicles moving at fixed altitudes are controlled through a novel adaptive formation controller to drive them to a pre-defined formation shape. The theoretical conjecture is verified by simulation results. © 2017 IEEE.
Citation - WoS: 1
Citation - Scopus: 1
Adaptive Event Triggered Control of Nonholonomic Mobile Robots
(Springer International Publishing AG, 2021) Guzey, Mehmet
In this paper, the design of adaptive regulation control of mobile robots in the presence of uncertain robot dynamics and with event-based feedback is presented. Two-layer neural networks (NN) are utilized to represent the uncertain nonlinear dynamics of the mobile robots, which is subsequently employed to generate the control torque with event-sampled measurement update. Relaxing the perfect velocity tracking assumption, control torque is designed to minimize the velocity tracking error, by explicitly taking into account the dynamics of the robot. The Lyapunov's stability method is utilized to develop an event-sampling condition and to demonstrate the regulation performance of the mobile robot. Finally, simulation results are presented to verify theoretical claims and to demonstrate the reduction in the computations with event-sampled control execution.
Citation - Scopus: 1
Adaptive Event-Triggered Regulation Control of Nonholonomic Mobile Robots
(Springer, 2020) Guzey, M.
In this chapter, the design of adaptive-regulation control of mobile robots (MR) in the presence of uncertain MR dynamics with event-based feedback is provided. Two layer neural-networks (NN) are utilized to represent the uncertain dynamics of the MR which is subsequently employed to generate the control torque with event-sampled measurement update. By relaxing the perfect velocity tracking assumption, control torque is developed to minimize the velocity tracking errors, by explicitly taking into account the dynamics of the MR. The Lyapunov’s method is utilized to develop an event-sampling condition and to demonstrate the regulation error performance of the MR. At the end of the chapter, simulation results are given to verify our theoretical claims. © Springer Nature Singapore Pte Ltd. 2020.
Additive Manufacturing of Amorphous Soft Magnetic Materials
(Elsevier, 2025) Özden, M.G.
Amorphous alloys intended for soft-magnetic applications are commonly produced through the rapid solidification of the molten metal. Typically, these alloys are prepared by incorporating metalloids (such as Si, B, Al, C, and P) into Fe-based and Co-based alloys, constituting approximately 20% of the composition. In amorphous magnetic alloys, the microstructure is characterized by the absence of atomic long-range order, showcasing only short-range order. This short-range order stems from the essentially random atomic arrangement during the solidification of the liquid melt at a cooling rate ranging from 105 to 106 K/s. Consequently, the absence of crystallite-related defects, such as grain boundaries and dislocations, contributes to a reduction in coercivity. Numerous studies have explored Fe-and Co-based magnetic materials produced through additive manufacturing (AM), given their broad applicability in the energy sector. While certain soft-magnetic amorphous/nanocrystalline alloys, such as the commercially available FeSiBCuNb alloys (FINEMET), show excellent soft-magnetic properties, AM has not yet introduced commercially available amorphous or nanocrystalline alloys. These materials are still at the research stage. Notably, the significant challenges lie in substantial crystallization and the segregation of alloying elements in AM, particularly when dealing with conventional alloying systems that exhibit low glass-forming ability (GFA). An innovative scanning strategy enabled the successful achievement of nearly 90% amorphous content in the laser additive manufactured FeSiBCrC alloy, which initially had low GFA. Despite the low bulk density (94%), stress-relief annealing resulted in relatively low coercivity (238A/m) in the as-printed samples. Recently, a “record-large” amorphous rotor with intricate 3D geometry was successfully manufactured through the laser AM process, employing the same alloy system (FeSiBCrC). This rotor possesses good soft-magnetic properties (saturation magnetization: 1.29T, coercivity: 510A/m, magnetic susceptibility: 9.17), high hardness (877 HV), and electrical resistivity (178.2 μΩ.cm). Moreover, the amorphization degree was moderate (70%). Consequently, AM presents a promising future technology for the production of large-scale amorphous soft-magnetic components. This chapter focuses on the AM of amorphous Fe-based and Co-based soft-magnetic materials. Among the various AM techniques, powder-bed fusion and direct energy deposition have been applied for this specific purpose. Within this section, an in-depth examination is conducted on these AM processes for amorphous magnetic materials. The chapter also includes an analysis of the research conducted in this field, along with a comprehensive exploration of the advantages and disadvantages associated with each method. © 2025 Elsevier Ltd. All rights reserved.
Citation - WoS: 107
Citation - Scopus: 114
Additive Manufacturing of Multiple Layered Materials (Ti6Al4V/316L) and Improving Their Tribological Properties with Glow Discharge Surface Modification
(Pergamon-Elsevier Science Ltd, 2021) Tekdir, H.; Yetim, A. F.
Selective Laser Melting (SLM), which is a kind of laser powder bed fusion additive manufacturing technology, is commonly used in the manufacturing of AISI 316L stainless steel components. This study aims to enhance the mechanical and tribological properties of 316L manufactured by using SLM and plasma oxidation treatment in a glow discharge atmosphere. For that reason, Ti6Al4V layers were formed on 316L stainless steel samples by selective laser melting. Samples with a duplex structure (316L substrate and Ti6Al4V layer) were oxidized at 650 degrees C and 750 degrees C for 1 h and 4 h in the plasma atmosphere. The characterization of the formed Ti6Al4V and oxide layers is determined by the Vickers micro-hardness tester, scanning electric microscope, 3D profilometer, Energy dispersive X-ray spectrometer, and X-ray diffractometer. Wear tests were performed against Al2O3 balls under a load of 10 N, dry sliding ambient air conditions by a pin-on-disk tribometer. It was observed that the hardness and wear resistance of Ti6Al4V layered and plasma-oxidized samples were better than the uncoated 316L samples due to the formation of titanium oxide phases and diffusion zone depth. The best wear resistance is obtained in the sample with the highest hardness value.
Citation - Scopus: 4
Additive Manufacturing of Non-Ferrous Metals
(Springer Nature, 2024) Varol, T.; Güler, O.; Yıldız, F.; Suresh Kumar, S.
Non-ferrous metals such as titanium (Ti), nickel (Ni), cobalt (Co), aluminum (Al), copper (Cu) and their alloys have many advantages compared to ferrous metals due to their low density, high corrosion resistance and high strength. Ti and its alloys are mostly used in engine applications such as rotors, compressor blades, and hydraulic systems. Ni and its alloys are frequently preferred in areas such as transmission shafts and turbine blades due to corrosion resistance and magnetic properties. Although cobalt and its alloys are used in cutting and piercing equipment, especially due to their high hardness, they have also used in the fabrication of biomaterials, hard permanent magnets due to biocompatible and their magnetic properties. The excellent corrosion resistance, thermal conductivity and lightness of Al and its alloys compared to ferrous metals make it usable in almost all industrial areas. Copper and copper alloys are one of the main materials used in the fabrication of conductive materials and heat exchangers. For this reason, efforts to produce more qualified and cheaper non-ferrous metals are gaining importance day by day. Traditional methods such as casting, powder metallurgy and injection molding have been used in the fabrication of metal parts. These methods need too many secondary processes such as cutting, machining, grinding, sintering, etc. after production. Moreover, some difficulties are encountered in these processes of non-ferrous metals such as titanium. Additive manufacturing (AM) methods have been developed to overcome these and many challenges. These methods eliminate the disadvantages of methods such as casting methods where scrap loss is experienced and powder metallurgy and / or injection molding methods, where the production of complex and large parts is difficult and combining their advantages in a single method. In this method, engineering parts are made by layering on the layer and layers are formed by the use of powder or wire selectively melted by a laser source followed by cooling. In this regard, in this book chapter, the manufacturability of non-ferrous metals consisting of Ti, Ni, Co, Al, Cu and their alloys, which are frequently used in the industry by AM methods, the application areas of such non-ferrous metals produced by AM methods and the advantages of the products obtained by these methods will be discussed in detail. Moreover, the challenges encountered in the fabrication of the specified non-ferrous metals with AM methods and the procedures that can be done to overcome these difficulties will also be highlighted. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
Citation - WoS: 18
Citation - Scopus: 19
Adhesion and Multipass Scratch Characterization of Ti:Ta-DLC Composite Coatings
(Elsevier Science Sa, 2018) Cicek, Hikmet; Keles, Aysenur; Totik, Yasar; Efeoglu, Ihsan
DLC (diamond like carbon) is one of the most studied coatings due to its excellent mechanical and tribological properties, desirable chemical inertness and high corrosion resistance hence it has been widely used in industrial applications for a long time. However, low adhesion and low fatigue resistance are disadvantages of this coating. In this study, we deposited Ti:Ta doped DLC graded-composite coatings on Ti6Al4V and M2 substrates and adhesion and multipass scratch behaviors were characterized. SEM, EDAX and XRD were used to determine the structural properties. Adhesion and fatigue-like behaviors were obtained by scratch tests. The results showed that the critical loads and fatigue resistance of the coatings were affected by the target currents and the hardness of the coatings and substrate.
Citation - WoS: 7
Citation - Scopus: 9
Advanced Mini Solar Still Design: Spiral Heating, Triangular Prism Condensation, and Comprehensive Energy-Exergy Analysis
(Elsevier, 2025) Afshari, Faraz; Kose, Murat; Akyurek, Eda Feyza; Mandev, Emre
Improving solar distillation systems is crucial in addressing water scarcity by providing a sustainable solution for clean water production, while also harnessing renewable energy to reduce environmental impact and reliance on conventional power sources. In solar still systems, salt water is typically contained in a basin, where it is heated by solar energy to produce distilled water through evaporation and condensation procedure. However, traditional systems do not allow for precise control over the temperature of the saltwater. This study introduces a novel approach by integrating a spiral type solar heater for salt water heating, which elevates the saltwater temperature to higher levels. To implement the proposed set up, the integration of a spiral-type solar heater, cotton-based materials, and a perforated pipe for delivering heated saltwater should be adopted, along with intermittent water pump operation to optimize heat absorption and evaporation efficiency. This enhancement enables more efficient condensation, which is achieved using a long triangular prism condensation unit. From the obtained results, it was revealed that the proposed mini solar still system can be modified by using cotton base materials and dripping salt water from a perforated pipe can enhance the distilled water by 138.46%. Comparing the energy efficiency results shows a significant 128.57 % efficiency improvement, highlighting the need to optimize strategies and modifications for better solar distillation performance. Comparing the optimal experiment with the reference experiment revealed a substantial 152.63 % increase in exergy efficiency.
Citation - WoS: 1
Citation - Scopus: 1
Advancing Pulmonary Embolism Detection with Integrated Deep Learning Architectures
(Springer, 2025) Biret, Can Berk; Gurbuz, Sukru; Akbal, Erhan; Baygin, Mehmet; Ekingen, Evren; Derya, Serdar; Tuncer, Turker
The main aim of this study is to introduce a new hybrid deep learning model for biomedical image classification. We propose a novel convolutional neural network (CNN), named HybridNeXt, for detecting pulmonary embolism (PE) from computed tomography (CT) images. To evaluate the HybridNeXt model, we created a new dataset consisting of two classes: (1) PE and (2) control. The HybridNeXt architecture combines different advanced CNN blocks, including MobileNet, ResNet, ConvNeXt, and Swin Transformer. We specifically designed this model to combine the strengths of these well-known CNNs. The architecture also includes stem, downsampling, and output stages. By adjusting the parameters, we developed a lightweight version of HybridNeXt, suitable for clinical use. To further improve the classification performance and demonstrate transfer learning capability, we proposed a deep feature engineering (DFE) method using a multilevel discrete wavelet transform (MDWT). This DFE model has three main phases: (i) feature extraction from raw images and wavelet bands, (ii) feature selection using iterative neighborhood component analysis (INCA), and (iii) classification using a k-nearest neighbors (kNN) classifier. We first trained HybridNeXt on the training images, creating a pretrained HybridNeXt model. Then, using this pretrained model, we extracted features and applied the proposed DFE method for classification. The HybridNeXt model achieved a test accuracy of 90.14%, while our DFE model improved accuracy to 96.35%. Overall, the results confirm that our HybridNeXt architecture is highly accurate and effective for biomedical image classification. The presented HybridNeXt and HybridNeXt-based DFE methods can potentially be applied to other image classification tasks.
Citation - Scopus: 3
Advantages of Using Halotolerant/Halophilic Bacteria in Agriculture
(Elsevier, 2022) Orhan, F.; Efe, D.; Gormez, A.
Soil salinization, one of the major restrictive problems in agricultural production, is increasing in arid and semiarid regions day by day. Rainfall in arid and semiarid regions is insufficient and cannot leach the excess salts from the plant root zones. This significantly affects the water uptake and ion homeostasis, photosynthesis, respiration, nutrient assimilation, and hormonal imbalance of plants. Soil salinity can be ameliorated using chemical and biological approaches. The application of halophytes including salt-tolerant plants and microorganisms is more preferable as it is an environment-friendly approach, given that the already salt-affected soil cannot be further contaminated with additional chemicals/matter. Yet, halophytes have limitations as they constitute an extremely small part of the total flora (around 1%); thus, the only environment-friendly approach in the amelioration of saline soils is the use of halophilic/halotolerant plant growth-promoting (PGP) bacteria. Recent research studies have indicated that the utilization of halotolerant/halophilic (PGP) bacteria in barren and deconstructed soils affected by salinity is a promising method to remediate these soils and increase soil fertility. © 2023 Elsevier Inc. All rights reserved.
Citation - WoS: 41
Citation - Scopus: 43
Aerobic Exercise Increases Irisin Serum Levels and Improves Depression and Fatigue in Patients with Relapsing Remitting Multiple Sclerosis: A Randomized Controlled Trial
(Elsevier Sci Ltd, 2022) Bilek, Furkan; Cetisli-Korkmaz, Nilufer; Ercan, Zubeyde; Deniz, Gulnihal; Demir, Caner Feyzi
Background: Multiple sclerosis (MS) is a chronic progressive neurodegenerative disease of the central nervous system. Although there is increasing evidence that aerobic exercise has a positive effect on both cognitive and psychological functioning, there is limited evidence for Relapsing-Remitting MS (RRMS) patients. Moreover, it is unclear at what exercise modality and intensity the irisin, the cleaved and circulating form of the exerciseassociated membrane protein Fibronectin Type III Domain Containing 5, is induced in patients with MS. This study aimed to investigate the effect of a regular aerobic exercise program on irisin serum level, depression, fatigue, and cognitive performance in patients with MS. Methods: Thirty-two individuals with RRMS were randomized into 2 groups as control and study groups (mean EDSS score 1.69 and 1.97, respectively). While the Study Group received a combined exercise training consisting of three sessions of aerobic exercise and Frenkel Coordination Exercises per week for 6 weeks, the Control Group received only Frenkel Coordination Exercise training. Before and after the study, the cognitive performance of the participants were evaluated with the Paced Auditory Serial Addition Test with 3-second stimulus (PASAT-3), their maximum aerobic capacity with the Fitmate Pro (R) (VO2max), their fatigue status with the Fatigue Impact Scale (FIS), and their depression status with the Beck Depression Inventory (BDI). Irisin serum levels were analyzed with Enzyme-Linked ImmunoSorbent Assay (ELISA) test from the serum samples of individuals. Results: Our results revealed that the irisin serum level significantly increased in the Study Group. Significant improvement in aerobic capacity, PASAT-3, FIS, and BDI values was observed in the Study Group compared to the Control Group. When the Delta Irisin, Delta VO2max, Delta FIS, and Delta BDI values between the groups were compared, a significant difference was found in favor of the study group. Conclusion: The aerobic exercise revealed significant changes in depression, fatigue and irisin serum levels in MS patients. We think that this study, in which a significant increase in irisin serum level, significant improvement in depression, cognitive performance and fatigue states were obtained in the Study Group, will be a pioneering study for the future studies aiming to investigate the effects of irisin serum level on these symptoms in detail.
Citation - WoS: 6
Citation - Scopus: 10
Affective States Classification Performance of Audio-Visual Stimuli from EEG Signals with Multiple-Instance Learning
(TÜBİTAK Scientific & Technological Research Council Turkey, 2022) Dasdemir, Yaar; Ozakar, Rustem
Throughout various disciplines, emotion recognition continues to be an essential subject of study. With the advancement of machine learning methods, accurate emotion recognition from different data modalities (facial images, brain EEG signals) has become possible. Success of EEG-based emotion recognition systems depends on efficient feature extraction and pre/postprocessing of signals. Main objective of this study is to analyze the efficacy of multiple-instance learning (MIL) on postprocessing features of EEG signals using three different domains (time, frequency, time-frequency) for human emotion classification. Methods and results are presented for single-trial classification of valence (V), arousal (A), and dominance (D) ratings from EEG signals obtained with audio (A), video (V), and audio-video (AV) stimulus using alpha, beta and gamma bands. High accuracy was observed with both binary and multiclass classification of the AV stimulus. Findings in this study suggest that MIL applied on frequency features yields efficient results on EEG emotion recognition.
Citation - WoS: 11
Citation - Scopus: 13
Affinity-Based and In a Single Step Purification of Recombinant Horseradish Peroxidase A2a Isoenzyme Produced by Pichia Pastoris
(Springer, 2023) Acar, Melek; Abul, Nurgul; Yildiz, Seyda; Taskesenligil, Ezgi Dag; Gerni, Serpil; Unver, Yagmur; Ozdemir, Hasan
Horseradish peroxidase (HRP) is an oxidoreductase enzyme and oxidizes various inorganic and organic compounds. It has wide application areas such as immunological tests, probe-based test techniques, removal of phenolic pollutants from wastewater and organic synthesis. HRP is found in the root of the horseradish plant as a mixture of different isoenzymes, and it is very difficult to separate these enzymes from each other. In this regard, recombinant production is a very advantageous method in terms of producing the desired isoenzyme. This study was performed to produce HRP A2A isoenzyme extracellularly in Pichia pastoris and to purify this enzyme in a single step using a 3-amino-4-chloro benzohydrazide affinity column. First, codon-optimized HRP A2A gene was amplified and inserted into pPICZ alpha C. So, obtained pPICZ alpha C-HRPA2A was cloned in E. coli cells. Then, P. pastoris X-33 cells were transformed with linearized recombinant DNA and a yeast clone was cultivated for extracellular recombinant HRP A2A (rHRP A2A) enzyme production. Then, the purification of this enzyme was performed in a single step by affinity chromatography. The molecular mass of purified rHRP A2A enzyme was found to be about 40 kDa. According to characterization studies of the purified enzyme, the optimum pH and ionic strength for the rHRP A2A isoenzyme were determined to be 6.0 and 0.04 M, respectively, and o-dianisidine had the highest specificity with the lowest Km and Vmax values. Thus, this is an economical procedure to purify HRP A2A isoenzyme without time-consuming and laborious isolation from an isoenzyme mixture.

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