Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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  • Article
    Developing a Label Propagation Approach for Cancer Subtype Classification Problem
    (TUBITAK, 2021) Güner, P.; Bakir-Güngör, B.; Coşkun, M.; Şahan, Pınar Güner
    Cancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, treatment methods need to be customized. The identification of distinct cancer subtypes is an important problem in bioinformatics, since it can guide future precision medicine applications. In order to design targeted treatments, bioinformatics methods attempt to discover common molecular pathology of different cancer subtypes. Along this line, several computational methods have been proposed to discover cancer subtypes or to stratify cancer into informative subtypes. However, existing works do not consider the sparseness of data (genes having low degrees) and result in an ill-conditioned solution. To address this shortcoming, in this paper, we propose an alternative unsupervised method to stratify cancer patients into subtypes using applied numerical algebra techniques. More specifically, we applied a label propagation-based approach to stratify somatic mutation profiles of colon, head and neck, uterine, bladder, and breast tumors. We evaluated the performance of our method by comparing it to the baseline methods. Extensive experiments demonstrate that our approach highly renders tumor classification tasks by largely outperforming the state-of-the-art unsupervised and supervised approaches. © 2022 Elsevier B.V., All rights reserved.
  • Editorial
    Editors' Introduction: Fall 2025
    (Cambridge Univ Press, 2025-10-28) Dincer, Evren M.; Yukseker, Deniz; Kolluoglu, Biray
  • Article
    Fuzzy Logic-Enhanced PMC Index for Assessing Policies for Decarbonization in Higher Education: Evidence from a Public University
    (MDPI, 2025-10-09) Fidan, Fatma Sener; Şener Fidan, Fatma
    Higher education institutions play a critical role in the transition to a low-carbon future due to their research capacity and societal influence. Accordingly, the calculation of greenhouse gas (GHG) emissions and the prioritization of mitigation strategies are of particular importance. In this study, a comprehensive campus-level GHG inventory was prepared for a public university in T & uuml;rkiye in alignment with the ISO 14064-1:2018 standard, and mitigation strategies were evaluated. To prioritize these strategies, both the classical Policy Modeling Consistency (PMC) index and, for the first time in the literature, a fuzzy extension of the PMC model was applied. The results reveal that the total GHG emissions for 2023 amounted to 4888.63 tCO2e (1.19 tCO2e per capita), with the largest shares originating from investments (31%) and purchased electricity (28.38%). While the classical PMC identified only two high-priority actions, the fuzzy PMC reduced score dispersion, resolved ranking ties, and expanded the number of high-priority actions to seven. The top strategies include awareness programs, energy-efficiency measures, virtual meeting practices, advanced electricity monitoring, and improved data management systems. By comparing the classical and fuzzy approaches, the study demonstrates that integrating fuzzy logic enhances the transparency, reproducibility, and robustness of strategy prioritization, thereby offering a practical roadmap for campus decarbonization and sustainability policy in higher education institutions.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Evaluating the Effects of Design and Manufacturing Parameters on Friction at the Surrogate Skin-3D Textile Interface
    (Sage Publications Ltd, 2025-10-30) Temel-Cicek, Mevra; Cicek, Umur I.; Lloyd, Alex B.; Johnson, Andrew A.
    Additive manufacturing (AM) is increasingly employed in the development of 3D-printed wearables, including medical wrist supports, textiles, and protective garments. While the general tribological behavior of 3D-printed components has been widely studied, limited research has focused on the friction behavior of 3D-printed wearables when in contact with human skin, which is a crucial factor for improving wearer comfort by minimizing local skin friction. This study, therefore, investigates the influence of material type, manufacturing technology, and print parameters of 3D-printed textiles on frictional behavior against skin. Specimens were fabricated using three AM technologies: material extrusion (MEX), vat photopolymerization (VATP), and powder bed fusion (PBF). Each technology employed various materials and print parameters, specifically layer thickness (ranging from 0.05 to 0.3 mm) and print orientations (horizontal and vertical). Friction was measured using a custom-built handheld device at the interface between 3D-printed specimens and two surrogate skin models: lorica (representing the dorsal forearm) and silicone (representing the chest). The results revealed that friction was significantly influenced by both layer thickness and print orientation. For MEX specimens, acrylonitrile butadiene styrene, acrylonitrile styrene acrylate, and polycarbonate showed the highest friction, while for VATP, durable resin resulted in the highest friction coefficient. In contrast, PBF specimens exhibited very similar frictional behavior. Regarding layer thickness, higher values consistently resulted in the highest friction coefficients, regardless of manufacturing method or material type. These findings provide valuable insights for designers and engineers seeking to optimize the comfort of 3D-printed wearables, guiding the selection of suitable AM processes and parameters for products intended for direct skin contact.
  • Article
    Burg-Aided 2D MIMO Array Extrapolation for Improved Spatial Resolution
    (MDPI, 2025-10-12) Bekar, Muge; Bekar, Ali; Pirkani, Anum; Baker, Christopher John; Gashinova, Marina
    In this paper, the extrapolation of a 2D multiple-input multiple-output (MIMO) array is proposed using the Burg algorithm to achieve higher angular resolution beyond that of the corresponding 2D MIMO virtual array. The main advantage of such an approach is that it allows us to dramatically decrease both the physical size and the number of antenna elements of the MIMO array. The performance and limitations of the Burg algorithm are examined through both simulation and experimentation at 77 GHz. The experimental methodology used to acquire 3D data of range, azimuth and elevation information with the 1D MIMO off-the-shelf radar is described. Using this method, the performance of the proposed array can be tested experimentally, especially at frequencies where it is desired to assess the antenna response prior to fabricating the antenna.
  • Article
    Contributions Toward Net-Zero Carbon in the Water Sector: Application to a Case Study
    (IWA Publishing, 2025-09-01) Ramos, Helena M.; Perez-Sanchez, Modesto; Correia, Tiago; Bekci, E.; Besharat, M.; Kuriqi, Alban; Coronado-Hernandez, Oscar E.
    This study presents an integrated smart water-energy nexus framework combining IoT-based water monitoring, hybrid renewables (hydropower/solar/wind), and AI-driven optimization. Real-time sensor data enables automated grid management, while AI analytics optimize operations and predict maintenance needs through a closed-loop system. The solution achieves bidirectional energy exchange, with the full hybrid system (G + H + PV + W) reducing costs by 41.5% (<euro>831K) and LCOE by 57.2% (<euro>0.0475/kWh). Financial analysis confirms viability with 26.4% IRR and 3.8-year payback, while achieving negative CO2 emissions (-160,476 kg/year). Progressive renewable integration enhances all key performance indicators (KPIs), cutting OPEX by 89.9% (<euro>7,156/year) through optimized operations. Dual water-energy performance metrics (leakage, pressure, % renewable share) ensure balanced and sustainable grid management. Key innovations include IoT-energy synergy, AI-driven predictive maintenance, and circular resource efficiency. The framework demonstrates how smart water grids can achieve both economic and environmental benefits through renewable energy integration and advanced digital solutions.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Effect of Yttrium/Lanthanum-Doped Ultrasonically Assisted Nano-Hydroxyapatite on Remineralization and Bracket Bond Strength in Artificial Enamel Lesions
    (BMC, 2025-09-29) Ozturk, Taner; Mammadov, Elshan; Bulduk Karakaya, Humeyra; Yagci, Filiz; Dayan, Serkan; Yagci, Ahmet
    Background This in vitro study aimed to evaluate the remineralization efficacy of ultrasonically assisted yttrium fluoride-doped (Ult-YF3-nHAP) and lanthanum fluoride-doped (Ult-LaF3-nHAP) nano-hydroxyapatite (nHAP) on artificially induced enamel lesions (aWSLs), and to compare their performance with acidulated phosphate fluoride (APF) gel, fluoride varnish, casein phosphopeptide-amorphous calcium phosphate (CPP-ACP), and resin infiltrant (ICON). Methods This in vitro study followed a four-phase design: enamel lesion creation, application of remineralization agents, a 14-day treatment protocol, and post-treatment analyses using QLF, Micro-CT, SEM-EDX, and SBS testing. This study included 168 extracted human premolars, divided into eight experimental groups (n = 21 per group): (1) Demineralized control (no remineralization treatment), (2) Acidulated phosphate fluoride (APF) gel, (3) Fluoride varnish, (4) Casein phosphopeptide-amorphous calcium phosphate (CPP-ACP), (5) Ultrasonically assisted nHAP (Control nHAP), (6) Ult-YF3-nHAP, (7) Ult-LaF3-nHAP, and (8) Resin infiltrant (ICON). The aWSLs were created under laboratory conditions. Brackets were bonded to the teeth with composite material, and aWSLs were created under laboratory conditions. After lesion formation and at the end of the experimental process, micro-computed tomography (Micro-CT) and laser-assisted quantitative light fluorescence (QLF) analysis were performed to assess lesion progression and remineralization. Additionally, scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) and shear bond strength (SBS) tests were conducted at the end of the study. Statistical analysis was performed using one-way ANOVA, Kruskal-Wallis, and Mann-Whitney U tests, with a significance level of p < 0.05. Results The bracket bond strength test data showed no significant differences between the groups (p = 0.156). Significant differences were found among groups for QLF fluorescence recovery (Delta F, p < 0.001), with the Ult-YF3-nHAP group showing the greatest increase (median: +0.5, IQR: -1.4 to + 0.7), while the control group showed the greatest decrease (median: -12.1, IQR: -12.4 to -10.2). Micro-CT analysis also revealed significant differences between groups (p = 0.008). The APF Gel group showed values comparable to those of all other experimental groups. The highest remineralization values were recorded in the Ult-YF3-nHAP group (6.87 +/- 3.03 mm(3)), whereas the lowest values were found in the Varnish group. The demineralized control group had significantly higher values than the Varnish group, but lower than the Ult-LaF3-nHAP group. SEM-EDX analysis revealed that fluoride weight was significantly lower in the Tooth Mousse and Varnish groups compared to the other experimental groups (p < 0.001). Ca/P ratio was significantly lower in the demineralized control, Varnish, and Ult-YF3-nHAP groups than in other experimental groups (p = 0.002). Conclusion Ult-YF3-nHAP showed higher efficacy in remineralization of aWSLs compared to fluoride-based treatments, CPP-ACP, and resin infiltrant. The highest remineralization was detected in the Ult-YF3-nHAP group by micro-CT and QLF analysis, while fluoride varnish gave the lowest result.
  • Correction
    Correction: Engineering Novel Features for Diabetes Complication Prediction Using Synthetic Electronic Health Records
    (Frontiers Media S.A., 2025-08-29) Voskergian, Daniel; Bakir-Gungor, Burcu; Yousef, Malik
  • Article
    Tuning Mechanical Performance of PCL Scaffolds: Influence of 3D Bioprinting Parameters, Polymer Concentration, and Solvent Selection
    (IOP Publishing Ltd, 2025-09-01) Ceylan, Saniye Aylin; Baltacioglu, Mehmet Furkan; Bal, Burak; Bayram, Ferdi Caner; Isoglu, Ismail Alper
    The mechanical performance of three-dimensional (3D) bioprinted scaffolds is susceptible to printing parameters and material formulation. In this study, poly (epsilon-caprolactone) (PCL) scaffolds were fabricated using four different polymer concentrations (10%, 25%, 50%, and 75% w/v) to investigate how these variations, along with process parameters, influence mechanical behavior. Maintaining the structural integrity of bioprinted constructs requires careful optimization of polymer concentration and precise control over parameters such as printing speed, pressure, and infill density. Tensile tests were conducted to evaluate the effects of these variables. Among the tested conditions, a 50% (w/v) concentration allowed for a broader operational window, enabling fabrication across a range of printing speeds and pressures. At a printing speed of 5 mm s-1, PCL-DCM exhibited a Young's modulus of 39.0 MPa, while PCL-CF samples printed at 10 mm s-1 achieved the highest modulus of 32.0 MPa. Notably, when the printing speed was kept constant, applying higher pressures led to an increase in Young's modulus, suggesting that pressure plays a key role in enhancing scaffold stiffness. When comparing the 50% and 75% (w/v) polymer concentrations, the 50% (w/v) formulation stood out by offering both higher elongation and greater stiffness, which makes it particularly suitable for load-bearing applications. These findings provide a quantitative framework for optimizing extrusion-based bioprinting of PCL scaffolds, with implications for customized biomedical implants and regenerative medicine.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Antifungal Efficacy of 3D-Cultured Palatal Mesenchymal Stem Cells and Their Secreted Factors Against Candida albicans
    (American Chemical Society, 2025-09-19) Bicer, M.; Öztürk, E.; Sener, F.; Hakki, S.S.; Fidan, O.
    Candida albicans is among the life-threatening fungal species and the primary contributor to hospital-acquired systemic infections, accounting for nearly 70% of all fungal infections worldwide. The current treatment primarily relies on azoles, pyrimidine analogs, polyenes, and echinocandins. However, growing antifungal resistance highlights the urgent need for the development of alternative treatments against C. albicans. Mesenchymal stem cells (MSCs) offer huge therapeutic potential for the treatment of C. albicans-associated diseases. In this study, palatal adipose tissue-derived MSCs (PAT-MSCs) and PAT-MSCs cultured in 3D biomaterial using nanofibrillar cellulose were tested against C. albicans strains ATCC 10231 and ATCC MYA 2876 using an in vitro antifungal activity assay. In addition, the conditioned medium from both PAT-MSCs and PAT-MSCs cultured in 3D hydrogel biomaterial (CM-PAT-MSCs-3D) were evaluated for their antifungal activities. The combined effect of PAT-MSCs and their secreted factors was also investigated. The expression of five antimicrobial peptide (AMP)-encoding genes was analyzed by quantitative real-time PCR. The expression of antimicrobial peptides was further confirmed via immunocytochemical staining. PAT-MSCs significantly inhibited the growth of C. albicans strains at varying inoculum concentrations (500 and 2000 CFU). Similarly, a comparable antifungal effect was observed when Candida strains were treated with PAT-MSC secreted factors alone. Statistical analysis revealed significant differences between the antifungal activities of PAT-MSCs and CM-PAT-MSCs. Lastly, the combination of PAT-MSCs and CM-PAT-MSC-3D led to a marked reduction in fungal growth, with inhibition rates of 99.75% and 99.91% for C. albicans ATCC 10231 and ATCC MYA-2876, respectively, at 500 CFU inocula. At 2000 CFU inocula, inhibition rates were 99.54% and 99.91%, respectively (****P ≤ 0.0001). These antifungal activities were further confirmed by using RT-PCR and immunocytochemical analysis. Our findings underscore a perspective on the potent antifungal activity of secreted factors from PAT-MSCs cultured within a 3D hydrogel matrix, specifically against various strains of C. albicans. Particularly, the combination of PAT-MSCs with their secreted factors represents a promising therapeutic platform, potentially offering a safer and more effective alternative to conventional antifungal treatments. © 2025 Elsevier B.V., All rights reserved.