Recep Tayyip Erdoğan Üniversitesi Kurumsal Akademik Arşivi
DSpace@RTEÜ, Recep Tayyip Erdoğan 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 yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Integrative machine learning model for overall survival prediction in breast cancer using clinical and transcriptomic data
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Kıvrak, Mehmet; Nalkıran, Hatice Sevim; Kesen, Oğuzhan; Nalkıran, İhsan
Breast cancer is the most common malignancy in women, with the Luminal A subtype generally associated with favorable survival. However, age and menopausal status may influence tumor biology and prognosis. To improve prediction beyond conventional models, we analyzed transcriptomic and clinical data from the METABRIC cohort. Patients with Luminal A breast cancer were stratified into premenopausal, postmenopausal-nongeriatric, and geriatric (>= 70 years) groups. Differentially expressed genes (DEGs) were identified, and Boruta feature selection revealed 27 clinical and genomic variables. Random Forest, Logistic Regression, Multilayer Perceptron, and ensemble XGBoost models were trained with stratified 5-fold cross-validation, using SMOTE to correct class imbalance. Principal component analysis showed distinct clustering across age groups, while DEG analysis revealed 41 genes associated with age and survival. Key predictors included clinical variables (age, tumor size, NPI, radiotherapy) and molecular markers (ATM, HERC2, AKT2, FOXO3, CYP3A43). Among ML models, XGBoost demonstrated the highest performance (accuracy 98%, sensitivity 98%, specificity 97%, F1-score 0.99, AUC 0.86), outperforming other algorithms. These findings indicate that age-related transcriptomic changes impact survival in Luminal A breast cancer and that an ML-based integrative approach combining clinical and molecular variables provides superior prognostic accuracy, supporting its potential for clinical application.
Agronomic potential and limitations of factory-derived tea waste in kale cultivation under drought stress
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Oğuz, Alparslan; Boyacı, Hatice Filiz
Plant-derived wastes are increasingly explored as organic matter sources for sustainable agriculture. Tea waste, a by-product of industrial tea processing, is often regarded as an environmental pollutant, yet its potential for agricultural use remains conditional and requires careful evaluation. This study examined the effects of factory-derived tea waste on kale (Brassica oleracea var. acephala) under drought stress. Plants were grown in soils amended with 5% or 10% tea waste and subjected to mild (75% field capacity) and moderate (50% field capacity) water deficits, compared with full irrigation (100% field capacity). Fifteen morphological and physiological parameters were assessed, and data were analyzed using principal component analysis (PCA) and correlation heatmaps to identify trait associations and stress markers. Drought stress significantly reduced all growth and yield traits, with stronger effects under more severe water deficit. Tea waste generally exacerbated stress impacts, increasing damage indices, reducing plant height, and lowering chlorophyll values. However, 10% tea waste under non-stress conditions increased plant and root dry weights without negatively affecting other traits, suggesting a partial nutrient contribution. In contrast, 5% tea waste aggravated stress effects, likely due to phenolic and caffeine toxicity. Overall, raw tea waste was found to be unsuitable for kale production under drought conditions. To harness its potential, bioactive compounds must be degraded or removed, and the material stabilized through composting or biochar conversion for safe integration into drought-resilient systems.
Treatment outcomes in allergic rhinitis: nasal obstruction symptom evaluation scale-based analysis
(2025) Yemiş, Tuğba; Birinci, Mehmet; Erdivanlı, Başar; Güneser, Yunus; Çeliker, Metin; Erdivanlı, Özlem Çelebi
Objective: This study aimed to assess the impact of oral antihistamines (OAH), intranasal corticosteroids (INC), and their combination on Nasal Obstruction Symptom Evaluation (NOSE) scores in individuals diagnosed with mild persistent allergic rhinitis. Materials and Methods: This retrospective study analyzed medical records of 86 patients with mild persistent allergic rhinitis. Patients had been treated with OAH, INC, or combination of both, and symptom severity was assessed using the NOSE scale - an instrument specifically measuring nasal obstruction - before treatment and at one month post-treatment. Results: A total of 86 patients were included, with similar distributions of age (33 [18-79]) and gender (48% female) among the treatment groups. Patients treated with INC exhibited a more pronounced reduction in nasal obstruction symptoms. Multiple linear regression analysis indicated that the baseline NOSE score was the only significant predictor of post-treatment outcomes (beta=0.434, p<0.0001), whereas age, gender, and treatment type did not demonstrate statistical significance. Conclusion: These findings indicate that adding OAHs to INC therapy does not enhance the relief of nasal obstruction in patients with mild persistent allergic rhinitis. Given their proven efficacy and safety, INCs alone may be sufficient and should be considered the firstline treatment for managing nasal obstruction in this patient cohort. However, given the multisystemic symptoms of allergic rhinitis, and the limits of NOSE scale to evaluate symptoms other than nasal airway obstruction, the results of this study should be interpreted carefully. Future studies utilizing multisystem scoring systems are required to capture the broader clinical effects of treatment.
Diplomacy meets paradiplomacy: unpacking central government responses through evidence from turkey's paradiplomacy
(Uluslararası İlişkiler Konseyi Derneği, 2025) Erdoğan, Seven; Atar
This study examines the central government's response to the paradiplomacy of sub-state actors through an analysis of the Turkish case, using a qualitative approach. As part of this research, a total of twelve face-to-face or virtual interviews were conducted with the representatives from the Turkish Ministry of Foreign Affairs, the Marmara Municipalities Union, and academics between June 2023 and November 2023. It views paradiplomacy as an outcome of the ongoing trend to localize diplomacy and aims to identify varying central government responses to paradiplomacy. These responses are analyzed using a three-fold categorization: positive, negative and mixed. The characteristics of each category explored in the context of the Turkish case. The study suggests that, despite the central government's opportunistic approach to paradiplomacy, its response has shown a cyclical tendency. The central government's stance on paradiplomacy is therefore complex and politically driven. It fluctuates along a broad spectrum, ranging from direct support to outright exclusion. This reflects the shifting political dynamics in Turkey.
Revisiting the institutional quality-environmental pollution nexus in developing countries
(SAGE Publications, 2025) Yaman, İlker; Çetin, Mümin Atalay
Global environmental pollution disproportionately burdens developing countries through multiple channels. Prior research identifies institutional quality as one of a key determinant of environmental outcomes in these settings. Exploring how six different aspects of institutional quality uniquely influence environmental quality over the long term in developing countries. Dynamic heterogeneous panel data estimators that account for cross-country heterogeneity and persistence have been employed to identify long-run relationships. The analysis is based on a panel of 94 developing countries over the period 2002 to 2019. Environmental quality is proxied by carbon dioxide (CO2) emissions, while institutional quality is measured using six widely recognized dimensions: Control of Corruption, Rule of Law, Voice and Accountability, Government Effectiveness, Regulatory Quality, and Political Stability and Absence of Violence. All six institutional dimensions exhibit statistically significant long-term effects on CO2 emissions. Specifically, improvements in Control of Corruption, Rule of Law, and Voice and Accountability are associated with reductions in emissions. Conversely, enhancements in Government Effectiveness, Regulatory Quality, and Political Stability and Absence of Violence are linked to increased emissions. The magnitude and direction of institutional quality effects vary across dimensions. Institutional quality plays a crucial role in shaping environmental outcomes in developing countries; however, its impact varies significantly across dimensions. Effective policy design must take these divergent pathways into account to effectively support the achievement of sustainable development goals.
