WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Now showing 1 - 10 of 684
  • Conference Object
  • Conference Object
    Reagent-Free Urea Determination From Hemodialysis Fluid: Development of FT-IR Spectroscopic Strategies
    (Springer, 2025) Akyuz, Ersed; Tanrisev, Mehmet; Guler, Gunnur
  • 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, Mehmet
    This 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
    Cryofixation Strategy for Fabrication of Robust Gelatin-Polyester Conductive Biocomposites
    (Taylor & Francis Inc, 2026) Koksal, Busra; Onder, Ahmet; Yildiz, Umit Hakan
    The development of mechanically robust and electroconductive biomaterials is critical for advancing tissue engineering strategies, particularly in neural, cardiac and musculoskeletal applications. Here, we report a polycaprolactone (PCL)-gelatin conductive polymer (poly(3,4-ethylenedioxythiophene):polystyrene sulfonate, PEDOT:PSS) biocomposite with tunable mechanical and electrical properties, fabricated via the cryofixation process relying on rapid reaction between isocyanate-terminated PCL, gelatin and PEDOT:PSS. Two isocyanate sources, hexamethylene diisocyanate (HDI) or isophorone diisocyanate (IPDI) were employed to obtain reactive end-functionalized PCLHDI and PCLIPDI. The cryofixation (at -18 degrees C) of PCLHDI or PCLIPDI, gelatin and PEDOT:PSS was found to occur in unfrozen microdomains and enabled the resultant gel with an inherited network of ice, thereby increasing porosity. Electroconductivity was introduced via the incorporation of PEDOT:PSS, yielding conductive cryogels with porous morphology. The resulting scaffolds exhibited a Young's modulus of 637 Pa and electrical conductivity of 197 mu S/cm, alongside biocompatible nature of gelatin-based gels. This multifunctional platform offers significant promise for the engineering of electrically active tissues.
  • Article
    FW-S3PFCM: Feature-Weighted Safe-Semi Possibilistic Fuzzy C-Means Clustering
    (Springer, 2026) Khezri, Shirin; Aghazadeh, Nasser; Hashemzadeh, Mahdi; Golzari Oskouei, Amin
    The safe semi-supervised fuzzy c-means clustering (S3FCM) method is a well-known clustering method that can produce successful results by incorporating prior knowledge of the class distribution. Its process is fast and simple but still has two limitations. The first issue is that it gives equal weight to all data features, while in real-world applications, different features usually have different importance. Secondly, S3FCM is very sensitive to noise and outliers. This paper proposes an extension of the S3FCM, entitled FW-S3PFCM, to mitigate these shortcomings. The proposed method uses a local feature weighting scheme to consider the different feature weights in the clustering process. Additionally, a possibilistic version of the S3FCM is designed to reduce the sensitivity to noise and outliers. The effectiveness of the proposed method is comprehensively evaluated on various benchmark datasets, and its performance is compared with the state-of-the-arts methods. To practically asses the FW-S3FCM, a real-world dataset of brain MRI images and its segmentation performance are analyzed as well. The average Accuracy, F1-score, Sensitivity, and Precision measures obtained by FW-S3FCM are 0.9682, 0.9826, 0.9743, and 0.9925, respectively, which are better than the competitors' performance.
  • Article
    Interpretable Structural Modeling of MR Images Using Q-Bezier Curves: A Geometry-Aware Paradigm Beyond Deep Learning
    (Elsevier Science Inc, 2026) Ozger, Faruk; Onan, Aytug; Turhan, Nezihe; Ozger, Zeynep Odemis
    Magnetic resonance (MR) imaging plays a critical role in diagnostic workflows, yet its reliability is frequently compromised by scanner-dependent bias, contrast variability, and intensity drift. Although deep learning methods achieve high performance, they generally require extensive supervision and demonstrate limited robustness across diverse clinical settings. To address these challenges, we propose a transparent, geometry-aware framework for annotation-free MR enhancement based on q-B & eacute;zier curves. This model incorporates an adaptive deformation parameter q(x) that modulates local curvature, facilitating flexible adaptation to complex anatomical boundaries. The framework comprises three principal mechanisms: (i) adaptive q(x) for local responsiveness, (ii) monotone q-Bezier tone curves for intensity standardization, and (iii) Tikhonov-regularized optimization for smooth mapping. As a result, the operator remains interpretable, operates in linear time, and provides explicit control over smoothness. The proposed approach was validated across five public cohorts (BraTS, ACDC, PROMISE12, fastMRI, IXI), demonstrating significant improvements in image fidelity (SSIM, CNR, NIQE) and downstream segmentation accuracy (Dice, HD95) relative to variational filters and state-of-theart foundation models. Additionally, cross-vendor experiments confirm its robustness without the need for retraining. Collectively, these findings establish q-Bezier modeling as a principled, lightweight, and clinically interpretable alternative that complements deep learning by providing a geometry-aware pathway to robust MR representation.
  • Article
    FTIR Spectroscopy Coupled With Chemometrics for Evaluating Functional Food Efficacy in an in Vitro Model of Iron Deficiency Anemia
    (Elsevier Science Ltd, 2026) Dalyan, Eda; Cavdaroglu, Cagri; Ozen, Banu; Gulec, Sukru
    Vibrational spectroscopy offers a rapid, cost-effective approach for studying biological systems. This study employs Fourier Transform Infrared (FTIR) spectroscopy, combined with Soft Independent Modeling of Class Analogy (SIMCA), to evaluate treatment outcomes for iron deficiency anemia (IDA). The model was built using spectra from healthy and anemic cells, then validated with cells treated with commonly used iron supplements. In calibration, 9 of 10 control and all IDA samples were correctly classified; 14 of 15 validation samples were identified as healthy. The model was applied to cells treated with protein-iron complexes. All samples treated with a 60:1 protein-iron ratio matched the healthy group, while 3 of 4 treated with a 10:1 ratio matched the IDA group. These results were further supported by iron-regulated gene expression of transferrin receptor (TFR) and (Ankyrin Repeat Domain 37) ANKRD37. FTIR coupled with chemometrics enables rapid assessment of functional effects and shows potential for screening functional ingredients in anemia-targeted food products.
  • Article
    Alterations in Secondary Lipids Are Associated with Neuroinflammation in the Brain of Neu1-Deficient Mice
    (Springer, 2026) Ada, Ebru; Seyrantepe, Volkan
    Neu1 (lysosomal sialidase 1) is essential for removing sialic acid from oligosaccharides and glycoconjugates. Neu1 deficiency impairs lysosomal digestion, leading to sialidosis and sialoglycoprotein accumulation. It also increases lipids, including gangliosides GM3, GD3, GM4, and LM1, in the kidney, liver, and spleen. Neu1-/- mice display symptoms resembling Type II sialidosis, including enlarged spleen and liver, kidney issues, neurological problems, spinal defects, and oligosaccharide buildup. The study examined secondary lipid alterations and inflammation in the cortex and cerebellum of these mice. Lipidomic, molecular, and immunohistochemical analyses of tissues from 2 and 5 M Neu1-/- mice revealed reduced levels of lipids, including PC, PE, PS, and CL, along with increased pro-inflammatory cytokines and loss of oligodendrocytes and neurons. Signs of astrogliosis and microgliosis emerged in specific brain regions. These results indicate that reduced levels of glycerophospholipids could serve as an indicator of inflammation in sialidosis mice. Future research should investigate therapies targeting these lipid changes, as modulating glycerophospholipids might slow disease progression in sialidosis patients.
  • Article
    Application of 3D Cell Culture Techniques in Nanotoxicology: How Far Are We
    (Springer, 2026) Shakeri, Raheleh; Mirjalili, Seyedeh Zohreh; Karakus, Ceyda Oksel; Safavi, Maliheh
    Investigation of toxicological profile and possible side effects of engineered nanomaterials (ENMs) is of high importance. Historically, two-dimensional (2D) cell culture was used to study the toxicity of the ENMs, but due to their inability to simulate in vivo cell behavior, three-dimensional (3D) cell culture systems have been developed. Nanotoxicity studies initiate with in vitro experiments and continue with in vivo studies, which are very challenging and sometimes accompanied by conflicting data due to the in vitro-in vivo gap. Thus, scientists are turning their attention to microfabrication techniques and engineered systems "called organ-on-a-chips", which act as an intermediate between in vivo and in vitro systems. The present account tries to review the classical study models and suitably cover the emerging 3D culture models including scaffold-free and scaffold-based 3D cell cultures, 3D co-culture with direct contact and without cell-cell contact methods as well as microfluidic-based tissue chips and organoids. Overall, this review aims to give readers a better insight about the ENMs' toxicology and fill the gaps between the knowledge and practical techniques. Hopefully, the presented information will resolve the issues of 2D in vitro cultures and display the clinically relevant responses to the concerns of therapeutic ENMs.
  • Article
    Robust Scheduling of Crude Oil Farming and Processing Under Uncertainty
    (Elsevier, 2026) Yalcin, Damla; Sildir, Hasan
    The sulphur content in crude oil has a significant impact on refinery operations, influencing the feasibility of crude blending, the distribution of product yields, and overall economic performance. Variations in sulphur content introduce uncertainty in the short-term scheduling of crude oil loading, blending, and distillation processes. This study introduces a scenario-based stochastic optimization framework in which sulphur uncertainty is treated as a central modeling element, represented through a regression-based relationship with specific gravity (SG). The approach systematically propagates uncertainty through blending decisions, crude distillation unit (CDU) feed composition, and product yields. The problem is modeled as a mixed-integer quadratically constrained programming (MIQCP) formulation within a continuous-time scheduling framework, enabling the simultaneous optimization of timing, blending, and processing strategies. The results indicate that increased sulphur uncertainty adversely affects the distribution of yields for nine end-products, resulting in profit losses. These findings underscore the importance of explicitly managing compositional uncertainty and provide insights into cost-performance trade-offs in refinery scheduling.