WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Identification of Turkish Extra Virgin Olive Oils Produced in Different Regions With Volatile Compounds(Innovhub SSI-Area SSOG, 2025) Sevim, Didar; Koseoglu, Oya; Ertan, Hasan; Ozdemir, Durmun; Ulan, MehmetThis study aims to characterize the composition of the volatile compounds in Turkish extra virgin olive oils (EVOOs) produced from three cultivars-Ayvalik, Gemlik, and Memecik-harvested in the South Marmara, South Aegean, and North Aegean regions during the 2014/15 and 2015/16 crop seasons. A total of 135 EVOO samples were obtained using industrial-scale 2-phase and 3-phase extraction systems. These samples were then analyzed using solid-phase microextraction (SPME) coupled with gas chromatography (GC). Among the twelve volatiles identified, trans-2-hexen-1-ol and cis-2-penten-1-ol exhibited the highest levels of abundance across all samples and seasons. Subsequently, 1-penten-3-one, hexanal, and cis-3-hexenyl acetate were identified, and it was determined that these contribute to the green and fruity sensory profile of high-quality olive oil. Two- and three-factor analyses of variance (ANOVA) revealed that volatile concentrations were significantly influenced by variety, harvest season, and extraction system. It is significant that 1-penten-3-one was found to be significantly influenced by both season and variety (p < 0.05), while 1-penten-3-ol exhibited a multifactorial dependency, with significant two-way interactions (season x variety, season x system, variety x system). Furthermore, PLS-DA-based classification successfully distinguished samples according to olive variety, indicating that volatile profiles could serve as reliable markers for authenticity and geographic origin. These findings underscore the potential of using volatile compounds as quality indicators and for geographic labelling in the olive oil industry.Article Design, Synthesis, and Biological Evaluation of Novel Water-Soluble Quinoline-Based Conjugates with Antioxidant, Antimicrobial, and DNA-Binding Activities(Society of Chemists and Technologists Madeconia, 2025) Gumus, Aysegul; Okumus, Veysi; Emrullahoglu, Mustafa; Gumus, SelcukConsidering the extremely valuable biological and pharmaceutical properties of quinolines, novel water-soluble quinoline-based conjugates were designed and synthesized. In vitro antioxidant activities, such as free radical scavenging, metal chelating, and reducing-power activities, of the newly synthesized compounds (WQ-1, WQ-2, WQ-3, WQ-4, and WQ-5) were determined. Although the highest scavenging activity (41.21 +/- 1.18%) and chelating activity (23.53 +/- 0.97%) at a concentration of 500.0 mu g/ml were observed in WQ-4, it was determined that WQ-5 had the highest reducing-power ability (0.417 +/- 0.0116). The synthesized compounds were also tested for their antimicrobial activities against two Grampositive and two Gram-negative bacteria, and it was determined that only WQ-3 showed low activity against Enterococcus hirae and Staphylococcus aureus. DNA-binding activities of the compounds were also studied using calf thymus DNA (CT-DNA). Additionally, the three-dimensional geometries and some electronic properties of the synthesized compounds were investigated with the density functional theory approach at B3LYP/6-31++G(d,p) level of theory.Article Geothermal Resources of Azerbaijan: A Comprehensive GIS-Based Remapping and Temperature Assessment Review(State Oil Company of Azerbaijan Republic, Oil Gas Scientific Research Project Institute, 2025) Isgandarov, S. M.; Uzelli, T. T.; Mukhtarov, A. N.; Baba, A. S.Azerbaijan has considerable geothermal energy potential. The resources are concentrated in regions such as the Absheron Peninsula, the Greater and Lesser Caucasus, the Kur Basin, and the Pre-Caspian-Guba region. Although the country does not have active volcanoes and geysers, geothermal energy can be extracted from deep wells, abandoned hydrocarbon fields, and natural hot springs. This study analyzes and maps Azerbaijan's geothermal resources using a Geographic Information System (GIS) to assess their potential for power generation and direct use. The main results show that wells such as Jarly-3 field thermal fluids with temperatures of up to 96 degrees C. Other promising sites include Daridagh in Nakhchivan and the Shikh field in Absheron, where geothermal water with a temperature of 68 degrees C. GIS-based interpolation techniques, including Kriging and Empirical Bayesian Kriging were applied to model the subsurface temperature distributions and identify regions with the highest geothermal potential. The study analyzed data from over 500 hot springs and geothermal wells to determine temperature variations at different depths. The results indicate that Azerbaijan's geothermal resources could support applications ranging from electricity generation to heating, agriculture, and industrial processes. Developing these resources could diversify Azerbaijan's energy sector and reduce dependence on fossil fuels. This study highlights the need for further exploration, improved drilling technologies, and investment in geothermal infrastructure to unlock the full potential of Azerbaijan's geothermal reserves.Article Seismic Risk Prioritization of Stone Masonry Building Stock in Urla Peninsula Based on Rapid Assessment Techniques(Turkish Chamber of Civil Engineers, 2026) Karavin, Y.S.; Akdag, N.; Demir, U.This study aims to investigate seismic risk of stone masonry buildings in the Urla Peninsula, a region of historical and architectural significance within İzmir, Türkiye. A total of 100 stone masonry buildings were surveyed and documented with a focus on their architectural characteristics, including construction techniques, material types, structural configurations, and age. Data on the properties of all surveyed buildings are provided in an open-access database. Based on the survey, multiple rapid seismic performance assessment methods were applied to evaluate the vulnerability of these structures. These included: i) FEMA P-154 Rapid Visual Screening, ii) Provisions for the Seismic Risk Evaluation of Existing Buildings under Urban Renewal Law (RBTE-2019), iii) Seismic Vulnerability Index for Vernacular Architecture (SVIVA), and iv) the Masonry Quality Index (MQI). The comparative use of different methods is intended to investigate the relative influence of parameters shaping the seismic performance of the masonry building stock rather than to align their scores. The outcomes of this research are expected to contribute to the current risk mitigation efforts for stone masonry buildings in İzmir, thereby supporting regional seismic resilience planning. © 2026, Turkish Chamber of Civil Engineers. All rights reserved.Article Dissecting the Metabolic Landscape of Breast Cancer Subtypes via Elastic Net Modeling and Examining Its Immune Correlates(Walter de Gruyter GmbH, 2026) Kus, M.E.; Ekiz, H.A.Objectives: Breast cancer is a heterogeneous disease, and the estrogen receptor (ER) status is a key factor in disease classification and treatment planning. While metabolomic profiling has revealed subtype-specific differences, cross-study comparisons have been limited, posing challenges for data extrapolation. This study aims to investigate metabolites that differentiate ER-positive and ER-negative tumors via integrative analyses of multi-omics data. Methods: We jointly analyzed two untargeted metabolomics datasets via elastic net modeling using consistent analysis pipelines tuned for low sample sizes, namely multiple bootstrapping and stability selection. Significant metabolite predictors from two studies were cross-examined to reveal distinctions and commonalities. We also performed differential gene expression analysis using RNA sequencing data from matching samples to link metabolic patterns with transcriptomic signatures and intratumoral immune cell signatures. Results: This study identified unique metabolite signatures in distinct datasets and a limited overlap of discriminating metabolites that can be broadly generalizable for subtyping. Nevertheless, several glycolysis and fatty acid metabolism intermediates exhibited variation depending on the tumor ER status. Consistently, genes related to fatty acid metabolism and glycolysis were enriched in ER-positive and ER-negative tumors respectively. Furthermore, we used multiple immune cell deconvolution algorithms to correlate various immune cell types with the metabolite levels within the tumor microenvironment. Conclusions: Together, these findings highlight the metabolic and immunological diversity of breast cancer and establish a reproducible machine-learning framework for integrating multi-omics data to interrogate tumor complexity. © 2025 the author(s), published by De Gruyter, Berlin/Boston.Article N-Formylation of Amines Over a Protonic Zeolite Socony Mobil (H-Zsm-5) and Ion-Exchanged Zeolite: Catalytic Performance and Reusability(Sciendo, 2025) Mekkas, Nadia; Azizi, Soulef; Yilmaz, Selahattin; Benbouzid, Mohammed; Dizoglu, Gunsev; Taib, Hana; Gherraf, NoureddineAn efficient and sustainable method was developed for the N-formylation of primary and secondary amines using formic acid in dichloromethane at room temperature over zeolite H-ZSM-5 and ion-exchanged forms (Zn-ZSM-5, Cu-ZSM-5, Ag-ZSM-5, and Cd-ZSM-5). The catalysts were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area, ammonia temperature-programmed desorption (NH3-TPD), and inductively coupled plasma-optical emission spectrometry (ICP-OES) analyses, revealing a regular hexagonal plate-like morphology and high surface area. H-ZSM-5 exhibited the largest surface area (248.2 m2/g) and total acidity (0.109 mmol NH3/g), while ion exchange slightly modified these properties. The catalytic system achieved excellent yields (up to 99 %) for various amines, demonstrating high efficiency and reusability. This study highlights the potential of zeolite-based catalysts as effective, recyclable materials for N-formylation processes.Article The Relation of Geogenic and Antrophogenic Factors with Blood and Hair Lead and Arsenic Levels in Women Living in Can and Bayramic Districts of Canakkale Province(Nobel Ilac, 2019) Baba, Alper; Gunduz, Orhan; Bakar, Coskun; Sulun, Serdar; Save, DilsadObjective: Mining areas and associated industrial activities carry considerable risks for human health due to multi-pathway exposure of heavy metals such as arsenic and lead. The objective of this study was to compare arsenic and lead levels it human blood and hair samples in all industrial mining area in northwestern Turkey with that of non-exposed group demonstrating similar sociocultural characteristics. Material and Method: The population of the study consisted of 674 nonsmoker women over the age of 40 who were selected on random basis from mine region and control area. Venous blood samples were taken and analyzed fur blood lead and arsenic levels in all participants. Hair samples were later collected from 108 women with high levels in blood samples. Results: The results showed that the highest prevalence of occurrences was found in district centers whereas relatively lower values were observed in the villages. Hail arsenic and lead levels were comparably higher in the industrialized area (can Region) where low-quality coal combustion used in power generation and residential heating were dominant. Conclusion: Although high correlations were not found, blood and hair arsenic and lead levels in individuals living in industrial in agricultural areas were found to he high at levels influencing the human health On the other hand, these results should be further supported and verified with advanced and long duration monitoring activities.Article Determining Area Affected by Corona in Lung Computed Tomography Images by Three-Phase Level Set and Shearlet Transform(Wolters Kluwer Medknow Publications, 2025) Aghazadeh, Nasser; Noras, Parisa; Moghaddasighamchi, SevdaBackground:The COVID-19 pandemic has created a critical global situation, causing widespread challenges and numerous fatalities due to severe respiratory complications. Since lung involvement is a key factor in COVID-19 diagnosis and treatment, accurate identification of infected regions in lung images is essential.Methods:We propose a multiphase segmentation method based on the level set framework to determine lunginvolved areas. The shearlet transform, a high-precision directional multiresolution transform, is employed to guide the gradient flow in the level set formulation. Additionally, the phase stretch transform (PST) is applied to enhance the contrast between infected and healthy regions, improving convergence speed during segmentation.Results:The proposed algorithm was tested on 500 lung images. The method accurately identified infected areas, enabling precise calculation of the percentage of lung involvement. The use of the shearlet transform also allowed clear delineation of ground-glass opacity boundaries.Conclusion:The proposed multiphase level set method, enhanced with shearlet and phase stretch transforms, effectively segments COVID-19-infected lung regions. This approach improves segmentation accuracy and computational efficiency, offering a reliable tool for quantitative lung involvement assessment.Editorial A Thin Film Micro-Extraction Based Salivary Metabolomics and Chemometric Strategy for Rapid Lung Cancer Diagnosis(Galenos Publ House, 2025) Pelit, Levent; Basbinar, Yasemin; Goksel, Ozlem; Goksel, Tuncay; Erbas, İlknur; Pelit, Fusun; Ozdemir, DurmusINTRODUCTION: Lung cancer (LC) remains one of the leading causes of cancer-related mortality worldwide, largely due to the lack of reliable biomarkers for early detection.1 Despite advances in di-agnostic imaging and targeted therapies, the five-year survival rate remains low because most cases are diagnosed at advanced stages. Consequently, the development of sensitive, non-invasive, and cost-effective diagnostic approaches is a major clinical priority. Metabolomics, the comprehensive profiling of small-molecule metabolites, has emerged as a powerful tool for uncovering cancer-associated metabolic alterations, providing insights into tumor biology and facilitating the discovery of novel biomarkers for accurate diagnosis and disease monitoring. Among biological matrices, saliva is a promising diagnostic biofluid because it can be collected non-invasively, is simple to obtain, and reflects systemic and local metabolic changes. Recent studies have demonstrated its potential for detecting various cancers, including lung cancer, highlighting its value for biomarker-based early di-agnosis.2,3 In this study, a novel thin-film microextraction (TFME) technique integrated with liquid chromatography-tandem mass spectrometry (LC-MS/MS) is introduced for the rapid, selective, and reproducible extraction of salivary metabolites. The developed TFME approach offers high throughput, reduced solvent consumption, and enhanced analytical performance, enabling the identification and quantification of key metabolic biomarkers associated with lung cancer. The objective of this workflow is to advance saliva-based metabolomics toward clinical translation, offering a promising avenue for the early and non-invasive diagnosis of lung cancer. MATERIAL AND METHODS: Synthesis of SiO2 Nanoparticles and TFME blade Preparation: SiO2 nanoparticles were synthesized using the Stöber method, followed by post-coating with tetraethyl orthosilicate, centrifugation, wash-ing with ethanol, and drying. The nanoparticles were incorporated into a polyacrylonitrile (PAN) matrix and coated onto steel TFME blades via a controlled dip-coating process to ensure uniform film thick-ness. Participants and Sample Collection: Saliva samples were collected from 40 histopathologically con-firmed lung cancer patients and 38 healthy volunteers following an overnight fast and an oral rinse. Ethical approval and informed consent were obtained (Ege University Ethics Committee, protocol: 15-11.1/46). Saliva samples were centrifuged, diluted (1:2), and stored at -80 °C until analysis. TFME Sampling and Analysis: A 96-well plate system equipped with PAN/SiO2-coated TFME blades was used for metabolite extraction (Figure 1). Blades were immersed in diluted saliva samples and rotated at 850 rpm for 150 minutes to allow analyte adsorption, followed by desorption of analytes in 0.1% formic acid for 30 minutes. Desorbed solutions were spiked with 0.5 µg/mL ornidazole as an internal standard prior to LC-MS/MS analysis. RESULTS: The TFME method was optimized to detect 18 metabolites in pre-treatment saliva samples from lung cancer patients. Chromatographic evaluation demonstrated that the Inertsil 100 column, employing isocratic elution with ornidazole as the internal standard, provided optimal separation effi-ciency and reproducibility. Extraction parameters, including desorption solution type and pH, were optimized; desorption solution type 2 at pH 8-9 yielding the highest metabolite recovery. Analytical validation indicated robust linearity (R2: 0.9841-0.9975), sensitivity (limit of detection: 0.014-0.97 μg/mL; limit of quantification: 0.046-3.20 μg/mL), precision (%relative standard deviation <20%), and accuracy (85-125% for most metabolites). Pathway analysis revealed significant alterations in the me-tabolism of phenylalanine, purine, tyrosine, histidine, and methionine. The Heatmap visualization showed increased levels of proline, hypoxanthine, phenylalanine, and tyrosine in lung cancer pa-tients. receiver operating characteristic curve analysis highlighted these metabolites as potential bi-omarkers, with proline exhibiting the highest diagnostic performance [area under the curve (AUC): 0.946], followed by hypoxanthine (AUC: 0.933) and phenylalanine (AUC: 0.905) CONCLUSION: The findings of this study demonstrate that the TFME approach is a reliable and effi-cient platform for metabolomic profiling in lung cancer. Using pre-treatment saliva samples, the method achieved a sensitivity exceeding 90% for detecting newly diagnosed histopathologically con-firmed patients. Among the metabolites analyzed, proline, hypoxanthine, and phenylalanine showed strong diagnostic potential, consistent with the pathway analyses implicating purine and phenylala-nine metabolism. These results underscore the potential of salivary metabolomics as a non-invasive screening alternative in the absence of validated early lung cancer biomarkers. Additionally, TFME’s high-throughput capacity, cost-effectiveness, and environmental sustainability support its feasibility for routine clinical application.Article Improving Doppler Radar Performance through Optically-Reconfigurable Unequal Power Division with Semi-Analytical Approach(Taylor & Francis Ltd, 2025) Karatay, Anil; Atac, Enes; Dinleyici, Mehmet Salih; Yaman, FatihThe improvement of the signal-to-noise ratio (SNR) of Doppler radar systems, enabling the detection of targets at greater ranges even with limited power, has been a longstanding focus of research. However, while key limitations such as low target reflectivity and environmental interference are often addressed, the impact of efficient use of the input power remains an overlooked, yet crucial factor in overall sensitivity. Additionally, the power allocation needs to be examined from an analytical perspective for further enhancement. In this study, we present a novel measurement approach, utilizing both semi-analytical analysis and experimental methods, to improve the performance of a dual-antenna CW Doppler radar through the use of an optically reconfigurable unequal microwave power divider which provides well-directed power utilization. Comprehensive grid searches, supported by an analytical approach and considering various loss and noise scenarios, demonstrate the capability of the proposed reconfiguration method. In the Doppler radar experiments where the pendulum and servo motor were used as targets, an SNR increase of 3.04 and 2.11 dB in the radar signal was observed with the proposed method, respectively. This noticeable improvement in the SNR of the time-frequency plots indicates an enhancement in the measurement performance. The unequal power allocation enabled continuous detection of target motion with minimal signal loss, lowering the minimum detectable power level by more than 2 dB compared to the equal power division case. The experimental results show that integrating an optically reconfigurable microwave power divider into the Doppler radar system increases precision in velocity measurements.