İZÜ Araştırma ve Akademik Performans Sistemi
DSpace@İZÜ, İstanbul Sabahattin Zaim Üniversitesi’nin bilimsel araştırma ve akademik performansını izleme, analiz etme ve raporlama süreçlerini tek çatı altında buluşturan bütünleşik bilgi sistemidir.
İndekslere Göre Dağılım
Yıllara Göre Dağılım
Türlere Göre Dağılım
Güncel Gönderiler
Öğe Türü: Yayın , r-Subhypermodules over Krasner Hypermodules(Vasyl Stefanyk Precarpathian National University, 2025) Bolat, M.; Kaya, E.; Onar, S.; Ersoy, B. A.; Hila, K.; Kaya, ElifIn this study, we introduce the notion ofr-subhypermodule of anR-hypermodule, whereRis a commutative Krasner hyperring. A proper subhypermoduleNofMis said to be anr-subhypermodule ifa·m∈NwithannM(a) =0Mimplies thatm∈Nfor eacha∈ R,m∈M. Weinvestigate the relations between the concept of prime subhypermodules andr-subhypermodules.We also give some results aboutr-subhypermodules.Öğe Türü: Yayın , Indomethacin-Encapsulated PLGA Nanoparticles Improve Therapeutic Efficacy by Increasing Apoptosis and Reducing Motility in Glioblastoma Cells(Taylor & Francis, 2025) Bostanci, Ferhat; Sengelen, Aslihan; Aksut, Yunus; Yildirim, Eren; Ogutcu, Irem; Yucel, Oguz; Emik, Serkan; Gurdag, Gulten; Pekmez, Murat; Bostancı, FerhatGlioblastoma, with a low survival rate, is an aggressive and difficult-to-treat lethal type of brain cancer. Indomethacin (IND), a non-steroidal anti-inflammatory drug, has antitumoral activity in many cancers, including gliomas. However, its poor aqueous solubility is a critical issue. Nanomaterials are crucial tools for overcoming solubility problems and facilitating drug delivery. Herein, a polymeric nanoparticle system, poly(lactic-co-glycolic acid) (PLGA) was used to encapsulate IND. Although PLGA is an FDA-approved copolymer for drug delivery, no trials with IND-loaded PLGA-NPs have been conducted to treat brain tumors. Encapsulation success was revealed by DLS, zeta potential, TEM, and FTIR analysis; IND/PLGA-NPs had nanoscale particle size (160.6nm), narrow size distribution (0.230, PDI), and good stability (−23.9 mV). Fluorescence imaging showed that PLGA-NPs can penetrate U-87MG cells. Short-term/one-hour treatment with bound-IND increased the free-IND effect in gliomas by ⁓10 times/48h and 12.39 times/72h. Even against long-term exposure to IND, IND/PLGA-NP treatment revealed a highly marked result; the IC50 value of bound-IND (treatment-time:1h, analysis at 48h) was 200mM, IC50 value of free-IND (treatment- time:48h) was 390mM. Furthermore, IND/PLGA-NPs’ anticancer activity (100mM of IND/1h, analysis at 48h) was also supported by induced apoptosis and reduced migration/colony formation in glioma cells. All evidence suggests that IND/PLGA-NPs may be a potentially promising agent for treating gliomas.Öğe Türü: Yayın , Nature’s Solvent Solution: Harnessing Natural Deep Eutectic Solvents (NADES) For Clean, Efficient Protein Isolation(Springer, 2025) Lee, Chi-Ching; Le, Thanh-Do; Pham, Bang Phuong; Tomas, Merve; Capanoglu, Esra; Ashaolu, Tolulope Joshua; Lee, Chı-ChıngConventional protein extraction methods often face challenges such as low yields, long processing times, and environmen-tal concerns. Natural deep eutectic solvents (NADES), composed of natural hydrogen-bond donors and acceptors, offer a sustainable and efficient alternative. This review highlights traditional extraction techniques and their limitations then focuses on the advantages of NADES and explores the key factors that affect protein solubility and extraction efficiency. Various NADES components are evaluated for their roles in enhancing protein yield. NADES-extracted proteins exhibit high techno-functional properties beneficial for food systems. Life cycle analyses indicate carbon footprint reductions of 60–75% and energy savings of 40–65% relative to traditional extraction modes, while toxicological studies suggest that food-grade NADES formulations are safe. Recent advancements in applying NADES for protein recovery from oilseeds, legumes, and food by-products are also discussed. Despite their potential, issues like high viscosity and challenges in protein recovery and scalability remain. Current applications include sustainable food protein production, nutraceutical component manufacturing, and therapeutic pharmaceutical protein isolation, together with new opportunities with cellular agriculture and alternative protein technology. Future applications of work involve the computational-guided design of the NADES system, utilizing a Conductor-like Screening Model for Real Solvents (COSMO-RS) modeling to optimize continuous processing and to gain regulatory approval for applications in food-grade use. NADES technology embodies an important shift towards environ-mentally sustainable protein isolation that maximizes product quality, minimizes environmental impact, and is economically viable for multiple industries. The review concludes by outlining future research needs to improve NADES applications for green, high-performance protein extraction.Öğe Türü: Yayın , Enhancing QR code security: Exploiting hidden message mechanisms and machine learning classification(Sage Publications, 2025) Yesiltepe, Mirsat; Kurulay, Muhammet; Bennour, Akram; Rasheed, Jawad; Alsubai, Shtwai; Rasheed, Jawad;The degree of utilization of Quick Response (QR) codes is sharply increasing due to the wide availability of smart devices. The primary purpose of the QR code is to ensure that an extensive message is fully transferred in a compact data format. Like any environment, security is an essential issue where QR codes are utilized. Such problems include the lack of signing information in a QR. This study aims to exploit the QR code hiding mechanism without spoiling the value of the code in the QR code while determining it using several machine learning algorithms. Consequently, several new QR image datasets are generated with varying sizes and variations to examine the classification of the proposed message-hiding scheme. This study used state-of-the-art models (VGG16, Xception) and a CNN-based model for QR code classification but only achieved 50% accuracy across four QR code dataset variants. Unsatisfied with these results, the study then employed the histogram feature density technique with various machine-learning (Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF)) and deep learning (DL) models. The experimental results reveal that adapting the histogram density method in the proposed scheme for feature creation achieved an overall success rate of approximately 99.98%. Moreover, the study further aims to simulate single-layer QR codes from hackers’ perspective that pretends to look like two-layer QR code systems. As a result of this simulation study, the performance was tested using different classification algorithms. In most cases, except for one, the DL model performed better by attaining a success rate above 90%.Öğe Türü: Yayın , Minimization of Protein Allergenicity in Food Products Through Conventional and Novel Processes: A Comprehensive Review on Mechanisms, Detection, and Applications(Taylor & Francis, 2025) Tarhan, Ozgur; Venerando, Andrea; Falsafi, Reza; Rostamabadi, Hadis; Rashidinejad, Ali; Capanoglu, Esra; Tomas, Merve; Karaca, Asli Can; Lee, Chi-Ching; Pourjafar, Hadi; Jafari, Seid Mahdi; Lee, Chı-ChıngFood proteins can cause life-threatening anaphylactic responses due to their allergenic properties when absorbed via the gastrointestinal system. Reduction or elimination of protein allergenicity is possibly achieved by the masking and destruction or alteration of allergenic epitopes in the molecular structure of relevant proteins via various food treatments capable of desta-bilizing, unfolding, digesting, fragmenting, denaturing, modifying, and aggregating proteins. Since the common food allergens are found in milk, wheat, meat, and nuts to be further processed into various products, efforts are increasingly proceeding to develop fast and accurate allergen detection methods, and processing approaches to mitigate the allergenic potential of the relevant proteins in the end products. This review aims to present the current status of food proteins treatments and processing techniques, both conventional and novel, whether individually or in combination, to either reduce, eliminate, or detect allergenicity. Proteomic studies, immunological assays, and polymerase chain reaction (PCR) based analyses are imperative for the effective profiling of protein allergenicity. Finally, a significant chal-lenge that must be addressed in the context of safety guidelines is the lack of a predictive and validated method for assessing allergenicity in relation to novel proteins or foods that have been recently introduced to the market.
