Publications by authors named "M S Celik"

Despite the variety of proposed solutions, anastomotic leakage is still a critical complication after colorectal surgery, which causes increased clinical mortality and morbidity. By enhancing microcirculation in the colonic mucosa, the use of Iloprost (Ilo) has shown promising results for the healing of anastomosis. The purpose of this study is to examine the performance of Ilo-impregnated Polycaprolactone:Gelatin electrospun membranes (PCL/Gel/Ilo) on anastomosis repair and intra-abdominal adhesion behavior in the Rat colon.

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Objective: Childhood cancer treatment disrupts vaccination schedules and weakens or eliminates vaccine-induced immunity. In addition, post-treatment vaccine responses vary. This study aimed to assess post-treatment serum antibody levels and vaccine responses in children.

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Objectives: Fournier's gangrene is an aggressive, rapidly progressing, and life-threatening necrotizing fasciitis of the perineal and genital regions. Various scoring systems have been developed for predicting survival and prognosis in Fournier's gangrene. This retrospective study aimed to evaluate the effectiveness of the newly developed Fournier's gangrene mortality index (FGMI) in predicting mortality associated with Fournier's gangrene.

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Mitochondrial dysfunction is increasingly recognized as a key factor in Alzheimer's disease (AD) pathogenesis, but the precise relationship between mitochondrial dynamics and proteinopathies in AD remains unclear. This study investigates the role of mitochondrial dynamics and function in the hippocampal tissue and peripheral blood mononuclear cells (PBMCs) of 5xFAD transgenic mice, as a model of AD. The levels of mitochondrial fusion proteins OPA1 and MFN2 and fission proteins DRP1 and phospho-DRP1 (S616) at 3, 6, and 9 months of age were assessed.

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Objectives: Deep learning has revolutionized image analysis for dentistry. Automated segmentation of dental radiographs is of great importance towards digital dentistry. The performance of deep learning models heavily relies on the quality and diversity of the training data.

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