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
Correction to: The prognostic impact of Her2 status in early triple negative breast cancer: a Turkish Oncology Group (TOG) study (Scientific Reports, (2024), 14, 1, (23556), 10.1038/s41598-024-75293-5)
(Nature Research, 2025) Özyurt, Neslihan; Alkan, Ali; Gülbağcı, Burcu; Seyyar, Mustafa; Aşık, Esra; Şahbazlar, Mustafa; Aydın, Esra; Doğan, Mutlu
Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-024-75293-5, published online 09 October 2024 The original version of this Article contained an error in the spelling of the author Esra Aşık which was incorrectly given as Esra Aydın. The original Article has been corrected.
Comparison of methods for detecting mandibular lingula and can antilingula be used in lingula mandibula detection?
(BioMed Central Ltd, 2025) Balaban, Emre; Köse, Taha Emre; Günaçar, Dilara Nil; Naralan, Muhammed Enes; Gonca, Merve
Objective: The aim of this study is to evaluate the relationship between anatomical reference points used during orthognathic surgery and to minimize the risks of iatrogenic neurovascular damage. Materials and methods: This retrospective study included cone-beam computed tomography (CBCT) images involving the mandible from patients who visited Recep Tayyip Erdoğan University Faculty of Dentistry between January 2018 and September 2023. The age range of the included individuals was set between 18 and 80 years. Horizontal and vertical distances between mandibular anatomical structures, such as the lingula mandibula (LM), mandibular foramen (MF), antilingula (AL), and surrounding structures were measured using CBCT software. Individuals with intraosseous pathology, insufficient image quality, or a history of surgical/orthodontic treatment were excluded from the study. Results: A total of 240 hemimandibles from 120 patients were analyzed (55.83% female, 44.17% male; mean age: 46.78 ± 15.30 years). Significant differences were identified in LM positions according to different AL types. The LM was found to be more inferior and posterior relative to hill and ridge type ALs, while it was more anterior relative to plateau type ALs. In 26.25% of mandibular rami, AL was not detected. Conclusion: The position of the AL can serve as a guide in determining the osteotomy line during inferior vertical ramus osteotomy (IVRO). However, relying solely on AL as a reference point may increase the risk of inferior alveolar nerve (IAN) injury. Preoperative tomographic evaluations to determine the relationships among LM, MF, and AL can provide a safer approach in surgical planning, reduce complications, and help protect neurovascular structures.
High precision banana variety identification using vision transformer based feature extraction and support vector machine
(Nature Research, 2025) Ergün, Ebru
Bananas, renowned for their delightful flavor, exceptional nutritional value, and digestibility, are among the most widely consumed fruits globally. The advent of advanced image processing, computer vision, and deep learning (DL) techniques has revolutionized agricultural diagnostics, offering innovative and automated solutions for detecting and classifying fruit varieties. Despite significant progress in DL, the accurate classification of banana varieties remains challenging, particularly due to the difficulty in identifying subtle features at early developmental stages. To address these challenges, this study presents a novel hybrid framework that integrates the Vision Transformer (ViT) model for global semantic feature representation with the robust classification capabilities of Support Vector Machines. The proposed framework was rigorously evaluated on two datasets: the four-class BananaImageBD and the six-class BananaSet. To mitigate data imbalance issues, a robust evaluation strategy was employed, resulting in a remarkable classification accuracy rate (CAR) of 99.86%0.099 for BananaSet and 99.70%0.17 for BananaImageBD, surpassing traditional methods by a margin of 1.77%. The ViT model, leveraging self-supervised and semi-supervised learning mechanisms, demonstrated exceptional promise in extracting nuanced features critical for agricultural applications. By combining ViT features with cutting-edge machine learning classifiers, the proposed system establishes a new benchmark in precision and reliability for the automated detection and classification of banana varieties. These findings underscore the potential of hybrid DL frameworks in advancing agricultural diagnostics and pave the way for future innovations in the domain.
Recent results on elastic scattering and single-neutron stripping reaction in the18O+48Ti collision at 275 MeV
(National Documentation Centre, 2024) Sgouros, O.; Brischetto, G.A.; Cappuzzello, F.; Cavallaro, M.; Carbone, D.; Agodi, C.; Hacısalihoğlu, Aylin; Close Zagatto V.A.B.
A global study of the18O+48Ti collision at 275 MeV was carried out within the NUMEN and NURE experimental campaigns by measuring the complete net of nuclear reactions which may be involved in the48Ti→48Ca double charge exchange transition. The relevant experiment was visualized at the INFN-LNS in Catania, where angular distribution measurements for a plethora of reaction channels were performed by means of the MAGNEX large acceptance magnetic spectrometer. The present work provides an overview of the analyses of the elastic scattering and one-neutron transfer reaction channels.
Periostin and fibronectin in nasal lesions: Key players in polyps and inverted papillomas
(Facultad de Salud de la Universidad del Valle, 2025) Birinci, Mehmet; Okçu, Oğuzhan; Yemiş, Tuğba; Gül, Oğuz; Terzi, Suat; Çeliker, Metin; Erdivanlı, Özlem Çelebi; Mercantepe, Tolga; Erdivanlı, Başar; Dursun, Engin
Background Sinonasal lesions are common benign masses with overlapping cli nical and histopathological features. Extracellular matrix proteins such as periostin, fibronectin, and tenascin-C play key roles in tissue remodeling and inflammation, yet their distinct expression profiles in these lesions remain poorly defined. Aim This study aimed to compare the immunohistochemical staining patterns of periostin, fibronectin, and tenascin-C in sinonasal lesions to elucidate their roles in pathogenesis and enhance differential diagnosis. Methods In this retrospective study, pathological specimens from 70 patients who underwent surgery for sinonasal polyps were analyzed. Immunohistochemical expression of periostin, fibronectin, and tenascin-C was assessed separately in epithelial and stromal compartments using a semi-quantitative scoring system. Associations between staining patterns and lesion types were evaluated using multinomial logistic regression. Results The cohort had a male-to-female ratio of 5:2 with a mean age of approximately 40 years. Nasal polyps demonstrated significantly higher stromal periostin staining compared to both antrochoanal polyps and inverted papillomas. Conversely, antrochoanal polyps exhibited significantly elevated epithelial periostin expression relative to inverted papillomas. Fibronectin expression was markedly increased in nasal polyps, especially in the stroma, supporting its role in inflammatory tissue remodeling. Tenascin-C expression did not differ significantly among the lesion types. Conclusions Differential expression of periostin and fibronectin suggests distinct pathogenic mechanisms in sinonasal lesions. The compartment-specific staining patterns of periostin, along with the prominent fibronectin expression in nasal polyps, suggest these biomarkers could serve as valuable diagnostic tools and potential therapeutic targets. Further research is needed to explore these pathways in sinonasal disease management.
