Publications by authors named "U L Demir"

This study aims to investigate the diagnostic values of fine needle aspiration cytology (FNAC) and frozen section (FS) in evaluating parotid gland masses subjected to parotidectomy. A retrospective analysis of data from 274 patients who underwent parotidectomy for parotid gland masses was performed at the Department of Otolaryngology of the University Hospital between 2013 and 2019. We compared the preoperative FNAC and intraoperative FS records with the definitive histopathological diagnoses obtained from the surgical resection specimens.

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Article Synopsis
  • Meckel's diverticulum (MD) is the most common congenital gastrointestinal anomaly, found in about 2% of people, and is rarely symptomatic in adults.
  • This case highlights a 46-year-old male who experienced abdominal pain due to Meckel's diverticulitis, which had formed a fistula with the abdominal wall, and was also found to have a benign inflammatory myofibroblastic tumor (IMT) on imaging.
  • After surgery for the diverticulitis and complications like an anastomotic leak, the patient ultimately recovered, and this case emphasizes the importance of thorough diagnostic work to uncover incidental findings that can impact treatment.
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Objective: This study aimed to evaluate anti-cancer potential of a novel glutaminase (GLS) inhibitor IN-3 in prostate cancer cells.

Methods: The cell viability upon IN-3 treatment was examined using crystal violet staining and IC values were calculated for cancer cell lines PC-3 and LNCaP and normal fibroblasts CCD1072sk. The expression levels of GLS isoforms were determined by real-time polymerase chain reaction after IN-3 treatment.

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Background: Colonoscopy difficulty and procedure time can vary between cases, posing challenges for daily scheduling in endoscopy units. In the literature, cecal intubation time (CIT) is commonly used to assess colonoscopy difficulty, yet there is debate regarding the factors influencing CIT. This prospective observational study aimed to evaluate the factors influencing CIT.

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Domain generalization (DG) approaches intend to extract domain invariant features that can lead to a more robust deep learning model. In this regard, style augmentation is a strong DG method taking advantage of instance-specific feature statistics containing informative style characteristics to synthetic novel domains. While it is one of the state-of-the-art methods, prior works on style augmentation have either disregarded the interdependence amongst distinct feature channels or have solely constrained style augmentation to linear interpolation.

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