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
Cross-Species Generalization and Comparative Performance Analysis of Deep Neural Network Architectures in Histological Image Classification
(2026) Çelen, Kaan; Oltulu, Fatih; Çağlar, Buse; Buhur, Aylin; Kılıçarslan, Burak; Çolak, Burhan Berk; Yavaşoğlu, Altuğ
Histological image classification plays a critical role in biomedical research and diagnostic processes. Advances in the field of deep learning present significant opportunities for enhancing diagnostic accuracy and developing automated decision support systems. This study aims to comparatively evaluate the out-of-distribution generalization and cross-domain classification performance of different deep neural network encoders. In this study, models were trained on an internal dataset of 4307 hematoxylin and eosin (H&E) stained images of male rat lung, cerebellum, and adipose tissues, obtained under ethical committee approval (Ege University, HADYEK 2026-06). To evaluate genuine generalization, testing was conducted on a separate, diverse external cohort of 600 mixed human-and-animal images. Nine different deep learning architectures-MobileNetV3-S, MobileNetV3-L, DenseNet121, DenseNet201, ConvNeXt-S, ConvNeXt-B, DINOv3 ViT-S, DINOv3 ViT-H+, and the pathology foundation model UNI2-h-were evaluated using frozen feature extraction combined with a linear probe. For performance evaluation, accuracy, sensitivity, specificity, F1 score, Cohen's κ, and ROC-AUC metrics were analyzed along with per-image inference times. While all models achieved near-perfect results during internal cross-validation, their performance diverged significantly on the external dataset, confirming that the observed differences reflect genuine cross-domain generalization capabilities rather than under-fitting. All competitive models demonstrated high performance in classifying adipose and cerebellum tissues, achieving an F1 score of 95% or higher for these tissues. In distinguishing the lung tissue, which has the most diverse structure and is the most difficult to classify, the UNI2-h model emerged as the most successful, achieving an F1 score of 97.4% and a recall of 95.0%. When evaluated in terms of computational efficiency, the MobileNetV3-Small model stood out as having the lowest processing time among all scenarios, demonstrating an inferenc
Trends, Analyses and Future Forecasts for Sports Media Investments
(2026) Kuyucu, Mihalis Michael; Korkmaz, Murat; Yücel, Ali Serdar; Abay, Perihan; Aytaç, Ayhan
The main objective of this study is to analyze the trends in sports media investments in Türkiye between 2011 and 2024 and to make forecasts for the future. Using data from the Association of Advertisers and Deloitte, investment figures for television, press, outdoor, radio, cinema and digital media were analyzed. The study was tested at 5% significance level by performing basic statistical analysis with Eviews 8.0 software. The results show that digital media investments are gradually increasing their dominance in the sports media ecosystem. While digital media advertising investments have increased 14 times in the last 8 years, TV media investments have increased by 194%, press by 40%, outdoor by 446%, radio by 348% and cinema by 218%. By 2023, digital media accounts for 72.6% of total media investments, reaching TL 86.50 billion, an increase of 136.9%. The annual rate of increase in total media investments was found to be 1,097 million TL. These analyses show that media investments will continue to increase in the future, but the balance between traditional and digital media will change.
Zafirlukast Exacerbates Behavioral Seizure Activity and Blood–Brain Barrier Disruption Despite Modestly Reducing Neuronal Injury Markers in a PTZ‑Induced Early Epileptogenesis Mouse Model
(Springer, 2026) Görgülü, Volkan; Tomruk, Cansın Şirin; Ergün, Pelin; Özdil, Berrin; Sancı, Ebru; Buhur, Aylin; Sözmen, Eser Y.; Köse, Timur; Yavaşoğlu, Nefise Ülkü Karabay; Yavaşoğlu, Altay
Epilepsy is one of the most prevalent neurological disorders worldwide, and approximately 25% of patients remain refractory to pharmacological treatment. Blood–brain barrier (BBB) disruption and reactive gliosis are key mechanisms implicated in early epileptogenesis. This study investigated the effects of zafirlukast, a leukotriene receptor antagonist, on BBB permeability, reactive gliosis, and behavioral seizure activity in a pentylenetetrazol (PTZ)-induced early epileptogenesis model in C57BL/6 mice. Zafirlukast was administered twice daily at a dose of 10 mg/kg. Seizure activity was evaluated by behavioral observation in terms of seizure severity, latency, duration, and frequency. BBB permeability was assessed using the Evans Blue assay, and brain tissues were analyzed by biochemical and immunohistochemical methods. The PTZ + ZAFIR group exhibited more severe seizures, characterized by increased seizure frequency and duration, shorter latency, and a higher kindling rate (80% vs. 27%). BBB permeability was also increased, whereas MMP-9 levels remained, suggesting disruption may be linked to direct mechanical effects of recurrent seizures rather than inflammation. Clues suggest that zafirlukast may exert paradoxical effects on two prominent cell types involved in reactive gliosis. While increased GFAP and TGF-β1 expression may reflect enhanced astrocyte activation, changes in IL-1β and Iba1 expression suggest suppression of microglial activation. Notably, pro-inflammatory and oxidative stress markers remained unchanged despite the increase in seizure severity. The observed reduction in neurodegeneration may be attributable to the suppressive effects of zafirlukast on microglial activation and the subsequent reduction in pro-inflammatory cytokine release. These findings indicate a complex role for leukotriene signaling during early epileptogenesis. Further studies using different doses, vehicles, and experimental models are warranted to clarify the effects of zafirlukast on the mechanisms underlying early epileptogenesis. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026.
Assessing Metabolic and Reproductive Consequences of Prenatal Paracetamol Exposure in Female CD1 Mice
(Wiley, 2026) Entezari, Bita; Bozdağ, Deniz; İnce-Ergüç, Elif; Buhur, Aylin; Tomruk, Cansın Şirin; Sabuncuoğlu, Suna; Yavaşoğlu, Altuğ; Gürer, Orhan Hande
Paracetamol is a widely used analgesic during pregnancy; however, emerging evidence suggests it may act as an endocrine/ metabolism disrupting compound. Using an F1 female CD1 mouse model, this study scrutinized the long-term metabolic and reproductive consequences linked to intrauterine paracetamol exposure. Pregnant dams were administered paracetamol at three dose levels (Cmax/10, Cmax, and Cmax×10) during a critical window of organogenesis (gestational days 7.5–16.5). Offspring were monitored until 17weeks of age to assess growth, glucose homeostasis, lipidomic profiles, and ovarian histology. Prenatal exposure did not significantly affect total body weight but induced a dose-dependent increase in peritoneal adipose tissue mass, particularly in the Cmax×10 group. Metabolic assessments revealed impaired glucose tolerance in the Cmax/10 group and increased insulin sensitivity across all dose groups. Adipose tissue gene expression analysis demonstrated upregulation of adipogenic markers (Pparγ, Lpl, Fasn), while untargeted lipidomics revealed consistent dysregulation of lipid species, including lysophosphatidylcholines (LPCs), phosphatidylcholines (PCs), sphingomyelins (SMs), and triacylglycerols (TGs), indicating altered lipid storage and inflammatory signaling. Histological evaluation showed a marked reduction in total follicle number and increased follicular atresia following paracetamol exposure. Degenerative changes in oocytes and granulosa cells were observed, and multi-oocyte follicles (MOFs) were detected exclusively in the Cmax/10. Collectively, these findings demonstrate that intrauterine paracetamol exposure induces persistent developmental reprogramming in female offspring, characterized by visceral adiposity, disrupted lipid homeostasis, and depletion of the ovarian reserve. Notably, several endpoints exhibited non-monotonic dose–response relationships, underscoring the sensitivity of developing systems to even subtherapeutic paracetamol exposure.
The use of artificial intelligence (AI) in tourism employment: employees’ perceptions and business strategies
(Emerald Group Publishing, 2026) Kızıldemir. Özgür; Şengel, Ümit; Çakmak, Muzaffer; İbiş, Salim; İnan, Ramazan
Purpose – The study aims to focus on the challenges that artificial intelligence (AI) brings to career decisions among tourism employees, while on the other hand, it focuses on how tourism employees’ AI risk perceptions affect their career decisions. In addition, another aim of the study is to reveal problem-solving strategies and future vision from a sector-based and managerial perspective for possible employment problems. Design/methodology/approach – In the first stage of my study, which used a mixed-method approach, data was obtained from 423 tourism employees (accommodation, food and beverage and travel) in Istanbul through a survey, while in the second stage, data was obtained from 25 managers (accommodation, food and beverage and travel) working in tourism establishments in Istanbul through interview forms. Findings – The results of the study revealed that AI risk perceptions affect tourism employees’ career decisions, while the professional motivation and anxiety levels of employees significantly mediated this effect. For the potential employment problems that these results will reveal, sub-sectors in tourism are trying to produce solutions with strategies such as technology investments and employee adaptation. Originality/value – This study fills an important gap in the literature by revealing that AI, which has the potential to increase service delivery and operational efficiency, affects employees’ career decisions and that businesses act with the mission of producing solutions with this awareness.
