Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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  • Article
    Gamma Secretase Inhibitors, DAPT and MK0752, Exhibit Synergistic Anticancer Effects with Cisplatin and Docetaxel in 2D and 3D Models of Breast Cancer
    (TÜBİTAK Scientific & Technological Research Council of Turkey, 2025) Telli, Kubra; Gubat, Johannes; D'Arcy, Padraig; Ozuysal, Ozden Yalcin
    Background/aim: Breast cancer remains a major malignancy among women, and severe side effects and the development of acquired drug resistance frequently hinder current therapeutic strategies. The Notch signaling pathway, a key regulator of cell fate, is commonly dysregulated in breast cancer and associated with poor prognosis. Gamma-secretase inhibitors (GSIs) block Notch receptor activation and have shown potential anticancer efficacy. This study aimed to investigate the synergistic activity of two commonly used GSIs, DAPT and MK0752, combined with docetaxel or cisplatin in both 2D and 3D breast cancer models. Materials and methods: Triple-negative, highly metastatic MDA-MB-231 and ER+/PR+ MCF-7 breast cancer cell lines were treated with DAPT or MK0752 alone or in combination with docetaxel or cisplatin. Drug efficacy and potential synergism were evaluated in 2D monolayer cultures and 3D spheroid models. Sequential treatment strategies were also assessed, where docetaxel or cisplatin was administered prior to GSI exposure. Results: Both MDA-MB-231 and MCF-7 cell lines exhibited notable sensitivity to DAPT and MK0752 combinations with docetaxel or cisplatin in 2D and 3D cultures. Synergistic enhancement of cytotoxicity was observed, particularly in sequential treatment regimens. Pretreatment with docetaxel or cisplatin followed by GSI exposure demonstrated superior growth inhibition compared with either monotherapy or simultaneous combination treatments. Conclusion: This study highlights the therapeutic potential of combining GSIs with standard chemotherapeutics to overcome drug resistance in breast cancer. The observed synergy and sequencing effects provide a strong basis for further mechanistic and translational investigations to optimize GSI-based combinational therapy strategies.
  • Article
    Dimensionality Effects in Anisotropic Single Layers TiSe5 and TiTe5: a Comparative Study of 2D Sheets and 1D Nanochains
    (IOP Publishing Ltd, 2026) Can Dogan, Kadir; Kutay Tamdogan, Omer; Bozkurt, Yagmur; Cetin, Zebih; Yagmurcukardes, Mehmet
    In this study, we present a comprehensive first-principles investigation of the structural, vibrational, and electronic properties of titanium pentachalcogenide structures in both two-dimensional (2D) and one-dimensional (1D) nanochain (NC) forms. Total energy and geometry optimizations reveal that the 2D TiX5 (X = Se, Te) structures exhibit in-plane anisotropy arising from the trigonal prismatic TiX3 units interconnected via the chalcogenide chains. Phonon band dispersions and elastic tensor elements confirm the dynamical and mechanical stability of the 2D layers, respectively. Electronically, while TiTe5 is a metal, TiSe5 possesses direct band gap semiconducting behavior. In addition, free-standing 1D NC counterparts, which are sub-units of the 2D structures, are investigated by means of their stability. Three stable 1D NCs, namely TiTe5-NC, TiSe7-NC, and TiTe7-NC, are found to be composed of edge-sharing TiX6-like units with either five- or seven-fold coordination. The dynamically stable 1D NCs are shown to be semiconductors with relatively larger band gaps as compared to 2D layers. Predicted Raman spectra reveal clear signatures of vibrational mode evaluations as a result of quantum confinement from the 2D layer to the 1D NC. Moreover, finite-temperature ab-initio quantum molecular dynamics simulations at 300 K confirm the thermal stability of both the 2D TiX5 layers and 1D NC derivatives, showing that the Ti-based systems retain their structural integrity under ambient conditions and are feasible candidates for experimental synthesis. Our findings highlight the formation of stable semiconducting 1D NCs of Ti-pentachalcogenides from their 2D counterparts.
  • Article
    Importance of Zoning for Vertical Circulation Planning of Densely Populated Buildings: A Simulation Based Approach for Elevator Traffic Analyses
    (Gazi Univ, 2025) Deligoz, Dostcan; Harputlugil, Timucin
    Elevator systems are essential in multi-story buildings, affecting circulation, travel time, and user comfort. Traditional design methods, based on mathematical calculations, provide initial estimates of elevator numbers and capacities by considering basic operational criteria. However, these methods cannot fully capture dynamic passenger flows and temporal variations in demand. Dynamic simulation-based elevator traffic analysis, on the other hand, allows for more comprehensive evaluation of elevator operations and enables testing of alternative zoning scenarios. In this study, a dynamic simulation-based analysis is applied as a case study for a hospital outpatient building. Different zoning strategies are implemented for elevator groups to evaluate their effect on system performance. Performance criteria, including Average Waiting Time (AWT), Average Time To Destination (ATTD), and Interval (INT), are assessed across different zoning scenarios and compared with values commonly reported in the literature. The results highlight the potential of zoning to improve elevator performance, including passenger handling, waiting times, and travel efficiency. Especially in buildings where physical modifications are difficult, the combination of simulation-based analysis and carefully designed zoning strategies can reveal the potential for enhancing operational performance and optimizing elevator efficiency within existing physical constraints.
  • Article
    Interventions in Historic Urban Sites After Earthquake Disasters
    (MDPI, 2025) Demir, Hatice Aysegul; Turan, Mine Hamamcioglu
    Earthquakes, fires, and climate change-related hazards increasingly threaten cultural heritage. Documenting and identifying the significance of heritage sites before disasters is essential for archival purposes and for guiding post-disaster interventions such as consolidation, reconstruction, or redesign. Although various post-disaster strategies exist in the literature, they often lack consideration of pre-disaster values and authentic qualities, limiting their effectiveness in value-based regeneration. This study proposes a framework for managing post-disaster interventions grounded in pre-disaster documentation of heritage values, authenticity, and integrity. The methodology includes seven phases: case selection; site survey and documentation; thematic analysis and mapping; quantification of qualitative data; synthesis of pre-disaster analysis results to define values, problems, and potentials; post-disaster assessment using aerial and terrestrial imagery; and development of targeted intervention strategies. This study focuses on two areas in Antakya, T & uuml;rkiye: Kurtulu & scedil; Street and Kuyulu Neighborhood, affected by the 2023 earthquake (M 7.7). These areas represent different historical layers: a Hellenistic grid plan with French-style buildings, and an organic Ottoman settlement morphology, respectively. Conservation data collected in 2019 inform the analysis. Mapping techniques evaluate attributes such as spatial characteristics, typologies, and structural systems. The study concludes that traces of pre-disaster spatial patterns and building features should inform post-disaster designs, ensuring sustainable, earthquake-resistant, and value-based interventions.
  • Article
    A First Process-Oriented Characterization of Eriolobus Trilobatus (Labill. Ex Poiret) Bark From Turkey: Chemical, Morphological and Energy Properties
    (MDPI, 2025) Sen, Umut; Yucedag, Cengiz; Balci, Busra; Arici, Sefik; Kocar, Gunnur; Sat, Beyza; Pereira, Helena
    For the first time, Eriolobus trilobatus bark from Turkey has been characterized in terms of its chemical, extractive, fuel, and ash characteristics using SEM-EDS, wet chemical analysis, phenolic analysis, FT-IR, TGA, XRF, XRD, BET surface area measurement, proximate analysis, and ash fusion temperature (AFT) determination. The results showed that the bark contains 13% ash, dominated by calcium oxalate, and 15% extractives, largely composed of polar phenolic compounds with moderate radical-scavenging potential. Thermal decomposition of bark proceeds in four distinct stages, associated with the sequential degradation of extractives/hemicelluloses, cellulose, lignin/suberin, and inorganic fractions. The higher calorific value of 14.9 MJ/kg indicates moderate fuel quality compared with conventional woody biomass. Ash is mesoporous with a CaO-rich structure highly suitable for catalytic applications in biodiesel production and biomass gasification. Ash fusion analysis revealed a high flow temperature (1452 degrees C), indicating a very low slagging risk during thermochemical conversion. Overall, E. trilobatus bark is a promising material for value-added biorefinery pathways, enabling processes for the production of biochars, CaO-based catalysts, phenolic extracts, and sustainable energy. The valorization of E. trilobatus bark not only enhances the economic potential of forestry residues but also provides environmental co-benefits through carbon soil amendment and landscape applications.
  • Article
    Contrastive Retrieval Methodology for Turkish Metaphor Detection and Identification
    (Assoc Computing Machinery, 2025) Inan, Emrah
    Metaphorical expressions, as a form of figurative language, are individually limited in their use. However, whenboth literal and non-literal meanings are considered, they are frequently used in web content. Hence, producinga balanced dataset to learn superior representations is a challenging task, and metaphor detection suffers froma limited training dataset. To alleviate this problem, we present a retrieval-based contrastive learning approachwhich first identifies candidate metaphors in the input text and then detects metaphorical expressions as aclaim verification task in the inherently unbalanced setting of this study. Furthermore, we adapt contrastivelearning to make it easier to distinguish between the literal and figurative meanings of the same expression.For the experimental setup, we extract non-literal and literal expressions along with their meanings andsample sentences from a Turkish dictionary. In the metaphor detection subtask, performance evaluation shows that sparse and dense search variations using the Turkish-e5-Large model achieve a Recall@10 (R@10) scoreof 0.614. Moreover, the SimCSE-TR-Contr-Sample-Meaning model achieves the highest Recall@10 (R@10)of 0.9739 on the generated test dataset for the metaphor identification subtask. In the real-world scenario,it achieves a competitive R@10 score of 0.8684, and these results clearly demonstrate that our model cangeneralise to this real-world scenario
  • Article
    A Machine Learning Model for Predicting Oligoclonal Band Positivity Using Routine Cerebrospinal Fluid and Serum Biochemical Markers
    (Oxford University Press Inc, 2025) Gözgöz, Hazar; Orhan, Oğuzhan; Akan Konuk, Başak; Akan, Pınar
    OBJECTIVE: To develop and validate a machine learning model for predicting oligoclonal band (OCB) positivity using routine cerebrospinal fluid (CSF) and serum biochemical markers to improve the diagnostic accuracy and efficiency of assessing intrathecal immunoglobulin G (IgG) synthesis. METHODS: In this retrospective study (n = 1709), an ensemble model was developed using 8 refined CSF and serum parameters. Combining optimized CatBoost, XGBoost, and LightGBM classifiers, the model was trained and evaluated using a 2-phase workflow, including 5-fold cross-validation and validation on independent internal (n = 342) and external (n = 49) cohorts. RESULTS: The developed ensemble model achieved a receiver operating characteristic-area under the curve (ROC-AUC) of 0.902 on the internal test set, significantly outperforming the conventional IgG index (ROC-AUC, 0.795). At its optimal threshold, the model demonstrated an accuracy of 0.830, with a sensitivity of 0.714 and a specificity of 0.916. On the external validation cohort, it achieved 90% accuracy and 96% sensitivity. CONCLUSIONS: A novel machine learning ensemble model accurately predicts OCB positivity using routine laboratory data and demonstrates superior performance compared with the IgG index. This approach represents a significant step in applying artificial intelligence in laboratory medicine, with the potential to enhance diagnostic efficiency. Prospective, multicenter validation is essential for broader clinical implementation. © The Author(s) 2025.
  • Article
    Chemical Composition and Reactivity of Quercus Pubescens Bark and Bark Fractions for Thermochemical Biorefinery Applications
    (MDPI, 2025) Sen, Umut; Balci, Busra; Arici, Sefik; Sat, Beyza; Miranda, Isabel; Pereira, Helena
    Advancing circular bioeconomy in thermochemical biorefineries requires species-specific data that link biomass composition and thermochemical performance. Here, we provide the first integrated thermochemical dataset for Quercus pubescens bark combining FT-IR, XRD, XRF, TGA, and measured ash fusion temperatures (AFT). The results reveal that bark is enriched in phenolic extractives (21.2%) and inorganics (15%), with calcium oxalate monohydrate (COM) dominating the inorganic fraction, as confirmed by FT-IR and XRD. Thermal decomposition occurs between 150 degrees C and 690 degrees C. Pyrolysis follows diffusion-controlled kinetics, with apparent activation energies for bark and its fractions ranging between 70 and 103 kJ mol-1. Extraction increases the activation energy of bark. The ash exhibits a high AFT (softening: 1421 degrees C, flow: 1467 degrees C), placing this feedstock within the low-slagging, moderate-fouling range compared to other lignocellulosics. The observed COM-to-CaCO3/CaO transformation upon heating contributes to the elevated AFT. Reactivity analyses of bark fractions support thermochemical biorefinery routing of fractions: extracted bark (EB) and desuberinised bark (DB) are highly reactive and well-suited to combustion/gasification, whereas raw bark (B) and Klason lignin (KL) exhibit higher thermal stability and yield more persistent char, favoring slow pyrolysis for biochar production. Such routing strategies optimize energy recovery and also enable co-products with environmental co-benefits.
  • Article
    One-Pot, Light-Induced, Liquid Crystal-Templated Synthesis of Nanoporous Silver Films at Room Temperature
    (TÜBİTAK, 2025) Mert-Balci, F.
    Nanoporous silver (NPS) films, characterized by a 3-dimensional bicontinuous structure of interconnected nanopores and ligaments, have found widespread use in spectroscopy, plasmonics, solar cells, catalysis, and chemical sensing. Traditionally, NPS films are fabricated via chemical dealloying, where a less noble metal (e.g., Cu or Al) is selectively removed through harsh chemical etching. However, residual traces of these metals can adversely affect the performance of NPS thin films in applications such as plasmonics and catalysis. This paper reports a one-pot, liquid crystal-templated method for synthesizing ultrapure NPS thin films at room temperature for the first time. The process begins with the preparation of an LLC composed of a nonionic surfactant and AgNO<inf>3</inf> that is then coated onto solid substrates. Exposure of the LLC film to ultraviolet light facilitates the in situ synthesis of Ag nanoparticles within the liquid crystal film. Subsequent solvent washing removes the surfactant molecules and any unreacted metal ions, yielding NPS films comprised of densely packed Ag nanoparticles on glass substrates. The resulting NPS films feature a 3-dimensional structure with uniformly distributed, interconnected nanopores. Synthesized under ambient conditions and scalable over large areas, these ultrapure NPS films present a highly promising platform for advanced applications in catalysis, spectroscopy, plasmonics, and biosensing. © TÜBİTAK.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Synthesis of Pristine Chitosan Foams with Enhanced Pore Structure, Surface Area, and Mechanical Strength for Tissue Engineering Applications
    (Iop Publishing Ltd, 2025) Polat, M.; Cropper, Chelsea; Ozdamar, A. B.; Polat, H.
    With its excellent biocompatibility, biodegradability, and antimicrobial activity, chitosan is a promising scaffold material for hard-tissue engineering. Yet, pristine chitosan foams typically lack the strength and porosity required for such use. Here we present a simple emulsion-templating approach to fabricate pristine chitosan foams with optimized strength and porosity. Sodium dodecyl sulfate (SDS), a widely used biocompatible anionic surfactant, was employed at trace levels to aid polymerization. The foams display a dual-scale pore morphology. Cavities of 150-300 mu m are separated by around 50 mu m thick chitosan walls containing large interconnecting openings. The walls are further populated with meso- and macropores of 50-500 nm. This architecture should support cell attachment and growth, facilitate proliferation, and enhance nutrient transport and metabolic exchange. The structure yields high surface area (up to 10 m2 g-1). Mechanically, the thick-walled cavities impart both elastic recovery and high compressive resistance (255 kPa at 40% strain from foams polymerized with 4% chitosan). A preliminary drug-release study using vancomycin confirmed excellent loading and sustained release.