WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Tooth Decay Promotes Senescence in Dental Pulp Stem Cells, Modifying Their Biological and Proteomic Profiles(Wiley, 2026) Durukan, Sebahat Melike; Tez, Banu Cicek; Ozcan, Servet; Simsek, Ahmet; Al-Sammarrie, Sura Hilal Ahmed; Gunaydin, Zeynep; Acar, Mustafa BurakDental caries is a prevalent oral health problem that significantly reduces an individual's quality of life; although, it can be effectively managed through restorative treatments. Even in cases where the caries does not reach the pulp, released microbial products from the lesion can still penetrate the pulp chamber, potentially inducing stress on pulp cells. In this study, we conducted a comparative analysis of the biological and proteomic profiles of dental pulp stem cells (DPSCs) isolated from clinically asymptomatic teeth with dentinal caries that had not reached the pulp and isolated from healthy teeth. Following biological evaluations, we examined proteomes of these DPSCs by conducting a shotgun proteomics approach. Our findings show that DPSCs from decayed teeth exhibit a significantly higher proportion of senescent cells. Proteomic profiling revealed upregulation of inflammatory signaling, extracellular matrix remodeling, and senescence-associated secretory phenotype (SASP) related proteins. Additionally, we observed an upregulation in the expression of proteins associated with extracellular matrix (ECM) remodeling and components of the SASP, which are hallmarks of the senescence process. The study reveals that DPSCs can be affected by stress from carious lesions, even when the pulp appears clinically intact. Senescence and inflammatory response in these affected cells may have deleterious effects on other tissues within the organism. Consequently, restorative treatments should consider targeting not only the decayed tissue but also the senescent cells within the pulp that may have been affected by the stress induced by caries.Article Optimizing Nanoclay-Enhanced Membranes for Oil Rejection Using Response Surface Methodology(Wiley, 2026) Gul, Ayse; Baris, Mesut; Boyraz, Pınar; Senol-Arslan, Dilek; Alibaz, Name NurThe efficient separation of waste oil from contaminated water is critical due to its challenges in environmental and industrial applications. This study investigated the production and optimization of polysulphone (PSF) membranes using two different types of clay (nanomer clay/CN and commercial nanoclay/NC). Response Surface Methodology (RSM) was applied to optimize the basic production parameters and nanoclay concentrations systematically to maximize oil rejection and permeability flow. The experimental results showed that NC and CN significantly increased the hydrophilicity, permeability, and fouling resistance of the membrane compared to pure PSF membranes. The contact angle significantly decreased from 64.34 degrees (pristine PSF) to 36.23 degrees (2% NC), indicating highly improved hydrophilicity. Consequently, the pure water flux increased from 177.2 L/m2 h to a maximum of 248.6 L/m2 h (1% NC). Furthermore, the modified membranes exhibited outstanding anti-fouling properties; the flux recovery ratio (FRR) improved from 88.09% to 96.20% (1% CN), while the decline ratio (DR) drastically dropped from 60.89% to 32.14%. The optimized condition for maximum removal efficiency using a modified quadratic model revealed that 2572 mg/L oil can be treated with a PSF membrane containing 2.0% CN to remove 98.271% of the oil. The model also suggests superiority of CN over NC with desirability factors of 0.978 and 0.900, respectively, while both demonstrated high efficiency. This theoretically modeled experimental comparative study highlights the importance of PSF membrane technology for efficient and sustainable oil-water separation and demonstrates the promising potential of nanoclay modifications.Article BrAIn: A Comprehensive Artificial Intelligence-Based Morphology Analysis System for Brain Organoids and Neuroscience(Wiley, 2026-03-12) Polatli, Elifsu; Guner, Huseyin; Bastanlar, Yalin; Karakulah, Gokhan; Evranos, Ali Eren; Kahveci, Burak; Guven, SinanHuman-induced pluripotent stem cells (iPSCs) offer transformative potential for biomedical research, with iPSC-derived organoids providing more physiologically relevant models than traditional 2D cell cultures. Among these, brain organoids (BO) are particularly valuable for drug screening, disease modeling, and investigations into molecular pathways. Accurate representation of brain morphology is critical, as more complex organoid structures better mimic the human brain. Deep learning (DL) and machine learning (ML) approaches have become integral to analyzing organoid morphology, yet tools for comprehensive, time-resolved assessments are scarce. Here, we introduce BrAIn, a DL-based application for analyzing the developmental progression of BOs. BrAIn tracks their evolution from embryoid bodies (EBs) and quantifies parameters including area, Feret diameter, perimeter, roundness, and circularity. It also classifies budding and abnormal morphologies of 3D organoids and detects monolayer neural rosette structures, key features of neuronal differentiation. Designed with accessibility in mind, BrAIn provides a no-code interface, enabling researchers of all technical backgrounds to conduct advanced morphological analyses with ease. Our study demonstrates the application of BrAIn to evaluate the effects of different growth conditions-static, orbital shaker, and microfluidic chip-based-on BO development. Orbital shaker cultures resulted in the largest organoids, while chip-based systems achieved more homogeneous growth. Both conditions produced organoids with greater morphological complexity compared to static culture. BrAIn emerges as a robust, user-friendly tool to quantify BO development and explore how versatile growth conditions influence their morphology and maturation.Article An Adaptation Mechanism of Model Reference Adaptive System Based on Variable Structure Control for Online Parameter Estimation of IPMSM(Wiley, 2026-01) Tekgun, Burak; Barut, Murat; Ates, ErtugrulThis study introduces stator currents-based model reference adaptive system (MRAS) estimators that employ variable structured control (VSC) in the adaptation mechanism to enable the online estimation of stator resistance and permanent magnet (PM) flux in interior permanent magnet synchronous motors (IPMSMs). These MRAS estimators estimate stator resistance and PM flux by analysing the error between the stator currents measured as the reference model and the stator currents generated by the adaptive model. The performance of the proposed estimators is assessed through simulation studies. Furthermore, the proposed approach is compared to a conventional MRAS employing a fixed-gain proportional-integral (PI) controller. Simulation results and error analyses indicate that the VSC-based MRAS algorithms outperform traditional PI-based MRAS in terms of accuracy and reliability. Additionally, the proposed method eliminates the reliance on a fixed-gain PI controller, a common component in conventional MRAS systems.Article Comparative Analysis of Modulation Shapes on Laser Diode Performance with a High-Efficiency LLC Resonant Converter Driver(Wiley, 2026-02-06) Yigit, Hayri; Rifat boynuegri, Ali; Tekgun, Burak; Rifat Boynuegri, AliHigh-power laser diodes (LDs) are key components in laser-based wireless power transfer (WPT) systems, where end-to-end efficiency is one of the most critical performance metrics. This study investigates the driving performance of an LD powered by a high-efficiency LLC resonant converter under three distinct excitation waveforms-sinusoidal, triangular, and rectified-sine-using a MATLAB/SIMULINK model and an experimental setup designed to reproduce real-world operating conditions. Each waveform is synthesized through frequency modulation of a full-bridge inverter stage and filtered at the output. The analysis examines the impact of modulation shape on output current ripple, converter efficiency, and overall LD efficiency. Experimental validation confirms the simulation trends, underscoring the trade-offs between waveform smoothness, implementation complexity, and efficiency. Beyond confirming that constant-current operation yields the highest LD efficiency, this study explicitly quantifies how low-frequency current ripple induced by different modulation waveforms propagates through the LLC resonant converter, alters RMS current stress, and translates into measurable efficiency degradation at both the driver and LD levels. By experimentally correlating waveform symmetry, ripple magnitude, and loss mechanisms, the work establishes practical design boundaries for waveform-modulated laser drivers in WPT systems.Article A Small Indole Derivative Isolated From Caper (Capparis Ovata) as an Inducer of P53-Mediated Apoptosis in Prostate Cancer: Comprehensive In Vitro and In Silico Studies(Wiley, 2025-12-31) Acar, Ozden Ozgun; Gazioglu, Isil; Oruc, Hatice; Kale, Elif; Senol, Halil; Topcu, Gulacti; Sen, AlaattinNatural products with stunning chemical diversity have been extensively researched for their anticancer potential for more than fifty years. This study aimed to determine the effect of indole derivative 1H-indole-2-hydroxy-3-carboxylic acid (IHCA), isolated as a novel alkaloid from Capparis ovata, on selected tumor suppressor, apoptotic, and cell cycle regulatory genes, which are known to be important in cancer pathophysiology, on Caco-2 and LNCaP cells in comparison with Taxol. The molecular mechanism of IHCA's anticancer activity is essentially undefined. Different concentrations of IHCA increased the expression levels of apoptosis-related genes, including BCL-2 and TNF-alpha. In addition, the tumor suppressor genes PTEN, P53, and RB were increased in LNCaP and Caco-2 cells. KRAS, an oncogenic gene, was significantly downregulated by IHCA in LNCaP cells. Western blot results showed that the protein expression levels of P53 and PTEN in LNCaP cells were increased when treated with IHCA, whereas CDK4 and TNF-alpha were decreased. Finally, IHCA and doxorubicin significantly increased P53-driven luciferase activity compared to the control. The results strongly suggest that the novel natural compound IHCA has an anticancer effect involving the regulation of the P53 gene and its networks in vitro. The molecular docking and MD simulation analyses reveal that IHCA exhibits superior binding potential to the MDM2 protein compared to Nutlin-3a. MD simulations further confirm that IHCA maintains a more stable and consistent interaction with MDM2, as indicated by lower RMSD values and reduced ligand fluctuation. These results highlight IHCA's potential as a more effective MDM2 inhibitor, suggesting its promise as a lead compound for anticancer drug development.Clinical Trial Registration: Not applicable.Article Looking for Stability in Chaos: A Scoping Review of Relational Turbulence Theory from a Dyadic Perspective(Wiley, 2025-11-21) Lagap, Adar Cem; Gungor, DuyguThe current scoping review overviews articles that apply the relational turbulence model/theory to guide the implementation of actor-partner interdependence modeling within a structural equation modeling framework. Sixteen studies are examined in the final synthesis of the review. Research themes center on communication strategies and social connection, dispositional and situational factors, and, lastly, mental and physical health. Current work illustrates that scholars are primarily interested in sources of relational uncertainty and its intrapersonal and interpersonal consequences. Sources of partner influence and their implications for relational dynamics are also examined across the synthesized studies. Overall, more actor effects than partner effects were statistically significant. Commercial statistical programs appear preferred for analyzing dyadic data, and assessments of fit indices are reported to evaluate proposed analytic models in this body of research. Methodological and theoretical limitations are highlighted, and implications for future research are discussed.Article Citation - WoS: 1A Comprehensive Analysis of Acoustic Emission Signals To Distinguish the Different Damage Types for Fiber-Reinforced Polymers: A Review(Wiley, 2025-12-03) Yilmaz, CagatayFiber-reinforced polymers (FRP) attract the attention of key industries, such as aerospace, wind energy, and automotive, as they can reduce the weight of structural components without compromising their mechanical properties. Due to FRP's anisotropic and non-homogeneous structure, their failure under different loading conditions and the corresponding failure mechanisms must be investigated. One method that progressively monitors the failure of FRP underload is Acoustic Emission (AE). AE can register the elastic stress waves in the form of digitized waveforms, released by the discontinuous events that occur in the FRP under load. These discontinuities can be clustered and identified as transverse cracking, fiber/matrix interface debonding, delamination, and fiber failure by analyzing the AE waveforms. Recently, numerous clustering approaches using machine learning algorithms, along with the varying features of AE waveforms, have been developed and are being used. These algorithms include supervised and unsupervised clustering, deep learning algorithms, and neural network methods, among others. While supervised algorithms require a training dataset to classify AE signals, unsupervised algorithms can perform clustering without training datasets. Deep learning and neural network algorithms can train themselves to cluster data, but they may require a significant amount of computer power when the dataset is large. This review paper provides comprehensive information on the clustering algorithm, along with the AE wave features, the range of features for different damage types, and the type of reinforcer.Conference Object Bioinformatics Analysis of Antifungal Mechanisms in Serratia Fonticola: Protein-Protein Interaction with Botrytis Cinerea BAG1 and Genome-Encoded Enzyme Reportoire(Wiley, 2025) Bozkurt, E. B.; Baysal, O.; Marzec-Grzadziel, A.; Silme, R. S.; Can, A.; Belen, I. N.; Korkut, A.Conference Object The Role of X-Inactive Specific Transcript (XIST) in Neuronal Development, Neuroinflammation, Myelination, and Therapeutic Responses in Cerebral Organoids(Wiley, 2025) Pepe, N. Aktas; Acar, B.; Zararsiz, G. Erturk; Guner, S. Ayaz; Sen, A.