İstanbul Galata Üniversitesi Kurumsal Akademik Arşivi
DSpace@Galata, İstanbul Galata Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Smart Contracts, Blockchain, and Health Policies: Past, Present, and Future
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Kurt, Kenan Kaan; Timurtaş, Meral; Ozaydin, Fatih; Türkeli, Serkan
The integration of blockchain technology into healthcare systems has emerged as a technical solution for enhancing data security, protecting privacy, and improving interoperability. Blockchain-based smart contracts offer reliability, transparency, and efficiency in healthcare services, making them a focal point of many studies. However, challenges such as scalability, regulatory compliance, and interoperability continue to limit their widespread adoption. This study conducts a comprehensive literature review to assess blockchain-driven health data management, focusing on the classification of blockchain-based smart contracts in health policy and the health protocols and standards applicable to blockchain-based smart contracts. This review includes 80 core studies published between 2019 and 2025, identified through searches in PubMed, Scopus, and Web of Science using the PRISMA method. Risk of bias and methodological quality were assessed using the Joanna Briggs Institute tool. The findings highlight the potential of blockchain-enabled smart contracts in health policy management, emphasizing their advantages, limitations, and implementation challenges. Additionally, the research underscores their transformative impact on digital health policies in ensuring data integrity, enhancing patient autonomy, and fostering a more resilient healthcare ecosystem. Recent advancements in quantum technologies are also considered as they present both novel opportunities and emerging threats to the future security and design of healthcare blockchain systems.
Machine learning–assisted classification of lung cancer: the role of sarcopenia, inflammatory biomarkers, and PET/CT anatomical-metabolic parameters
(Springer Science and Business Media Deutschland GmbH, 2025) Tanyildizi-Kokkulunk, Handan; Alcin, Goksel; Cavdar, Iffet; Akyel, Resit; Ciftci-Kusbeci, Tuba; Caliskan, Gonul
Accurate differentiation between non-cancerous, benign, and malignant lung cancer remains a diagnostic challenge due to overlapping clinical and imaging characteristics. This study proposes a multimodal machine learning (ML) framework integrating positron emission tomography/computed tomography (PET/CT) anatomic-metabolic parameters, sarcopenia markers, and inflammatory biomarkers to enhance classification performance in lung cancer. A retrospective dataset of 222 patients was analyzed, including demographic variables, functional and morphometric sarcopenia indices, hematological inflammation markers, and PET/CT derived parameters such as maximum and mean standardized uptake value (SUVmax, SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG). Five ML algorithms—Logistic Regression, Multi-Layer Perceptron, Support Vector Machine, Extreme Gradient Boosting, and Random Forest—were evaluated using standardized performance metrics. Synthetic Minority Oversampling Technique was applied to balance class distributions. Feature importance analysis was conducted using the optimal model, and classification was repeated using the top 15 features. Among the models, Random Forest demonstrated superior predictive performance with a test accuracy of 96%, precision, recall, and F1-score of 0.96, and an average AUC of 0.99. Feature importance analysis revealed SUVmax, SUVmean, total lesion glycolysis, and skeletal muscle index as leading predictors. A secondary classification using only the top 15 features yielded even higher test accuracy (97%). These findings underscore the potential of integrating metabolic imaging, physical function, and biochemical inflammation markers in a non-invasive ML-based diagnostic pipeline. The proposed framework demonstrates high accuracy and generalizability and may serve as an effective clinical decision support tool in early lung cancer diagnosis and risk stratification.
Comparison of University Students' Awareness of Radiation Protection before and after Hospital Internship
(The Korean Association for Radiation Protection, 2025) Colak, Gülcihan
This study aims to compare the pre-and post-application results of university students' knowledge regarding radiation protection. Materials and Methods: The study was conducted on 116 students enrolled in the medical imaging and radiotherapy program. These students were administered a two-stage, 33-item radiation protection knowledge scale via Google Forms before and after the application course. The application results were analyzed as pre-test and post-test. Results and Discussion: A total of 116 students participated in the study. According to the study results, there was a difference in the students' awareness of the radiation protection sub-factor before and after the application. The primary reason for this is that observing the use of protective equipment during the application has increased their awareness. The importance of protective equipment for both worker health and patient safety has been understood. Conclusion: This study demonstrated the necessity of recording and monitoring radiation exposure during diagnosis and treatment procedures. The need to implement safety protocols to minimize the potential consequences of radiation hazards has also been recognized.
Salvia argentea L. extract inhibits the production of NO, and pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), alleviates the inflammatory response of LPS-induced macrophages cells, and reduces the CRP level on carrageenan-induced paw edema
(Springer Science and Business Media Deutschland GmbH, 2025) Alhamedi, Almonther; Demiroz Akbulut, Tugce; Baykan, Sura; Gümüştaş, Barış; Sanci, Ebru; Alsakini, Karrar Ali Mohammed Hasan; Nalbantsoy, Ayşe; Yavasoğlu, Altuğ; Karabay Yavasoğlu, N. Ülkü
Salvia argentea L. (Lamiaceae) is a medicinal plant originating from the Mediterranean region and has been used since ancient times for the treatment of various diseases. This study aimed to determine the phytochemical composition of S. argentea L. ethanol extract and to evaluate its in vitro and in vivo anti-inflammatory activity and its acute oral toxicity. The chemical constituents of the ethanol extract prepared from the aerial parts of the plant were identified using HPLC. The in vitro anti-inflammatory activity of the extract was evaluated in LPS-stimulated murine macrophage RAW 264.7 cells and the human monocytic cell line THP-1 by measuring the levels of nitric oxide (NO), pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α). Acute toxicity of the extract was assessed in accordance with OECD guideline no 423. In vivo anti-inflammatory activity was evaluated based on the inhibition of 1% carrageenan-induced paw edema in rats. Serum CRP levels as an inflammatory marker, were measured via ELISA. Histological and immunohistochemical assessments were performed to identify tissue changes in the paw. HPLC profiling revealed that the extract contained rosmarinic acid (11.334 µg/mg dry extract), and salvigenin (2.74 µg/mg of dry extract) as major compounds. The extract significantly inhibited the production of NO, IL-1β, IL-6, and TNF-α without affecting cell viability. In vivo, the extract treatment exhibited a dose-dependent reduction in paw edema and serum CRP levels, along with notable histological improvements. Administration of the extract resulted in dose-dependent decreases of NF-κB expressions in the paw tissues. No signs of acute toxicity were observed (oral LD₅₀ > 2000 mg/kg). These findings suggest that S. argentea L. ethanol extract possesses significant anti-inflammatory potential supporting its possible development as a natural therapeutic agent for inflammatory disorders.
From unmet childhood needs to parenting attitudes: breaking the cycle
(Taylor and Francis, 2025)
Objective: Rooted in Schema Therapy, this research posits that unmet physiological, social, and psychological needs during early life contribute to the development of enduring cognitive frameworks, termed early maladaptive schemas (EMS), which influence affect, behaviour, and cognition across the lifespan. Accordingly, the objective was to examine whether EMSs are systematically associated with specific parenting attitudes (PAs). Method: This correlational study employed a concurrent design. Participants included 246 volunteer parents of preschool-aged children residing in a cosmopolitan district of Istanbul. Data were collected online using validated measures of EMS and PA, along with additional items assessing potential confounding variables. Results: Correlational analyses revealed moderate positive associations between EMS and authoritarian parenting attitudes and moderate negative associations with democratic parenting attitudes. Hierarchical regression analyses showed that EMS accounted for over 20% of the variance in parenting attitudes, with socioeconomic status and education emerging as significant moderators. Discussion: EMSs significantly predict parenting attitudes, increasing authoritarian attitudes, and reducing democratic ones. Early identification of EMS, combined with schema-focused interventions and evidence-based parent education programs may help disrupt maladaptive parenting cycles and promote healthier parent–child dynamics.
