Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Browsing Scopus İndeksli Yayınlar Koleksiyonu by Department "AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü"

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    Master Thesis
    Centella asiatica extract containing bilayered electrospun wound dressing
    (Abdullah Gül Üniversitesi, 2019) KOÇ, NURAY
    Innovative and bioactive wound dressings prepared by electrospinning mimicking the native structure of the extracellular matrix (ECM) have gained significant interest as an alternative to conventional wound care applications. In this study, bilayered wound dressing material was produced by sequential electrospinning of quaternized poly(4- vinyl pyridine) (upper layer) on the Centella Asiatica (CA) extract containing electrospun poly(D, L-lactide-co-glycolide) (PLGA)/poly(3-hydroxybutyrate-co-3- hydroxy valerate) (PHBV) blend membrane (lower layer). Scanning electron microscopy (SEM) was utilized to show a uniform and bead-free fiber structure of electrospun membranes. The average diameter of CA extract containing electrospun PLGA/PHBV blend membrane was calculated 0.471±0.11 µm, whereas the average fiber diameter of electrospun poly(Q-VP) membranes was in the range of 0.460±0.057 µm. Chemical, thermal, mechanical properties, and adsorption capacity of electrospun membranes, as well as the cumulative release of CA from the electrospun PLGA/PHBV membrane, were investigated. Viability, adhesion, and attachment of human fibroblast cells on the electrospun membranes on pre-set days were evaluated by the colorimetric CellTiter 96® Aqueous One Solution Cell Proliferation Assay (MTS assay) and SEM. Results revealed that CA loaded bilayered electrospun wound dressing showed promoted attachment and proliferation of fibroblasts. Hence, it can be concluded that CA extract containing bilayered electrospun wound dressing prepared in this study has a promising potential for wound healing applications.
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    Conference Object
    Computer-Aided Classification of Breast Cancer Histopathological Images
    (IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017) Aksebzeci, Bekir Hakan; Kayaalti, Omer
    Nowadays, one of the most common types of cancer is breast cancer. The early and accurate diagnosis of breast cancer has great importance in the treatment of the disease. In the diagnosis of breast cancer, histopathological analysis of cell and tissue specimens taken by biopsy is considered as the gold standard. Histopathological analysis is a tedious process that is highly dependent on the knowledge and experience of the pathologists. In this study; it is aimed to develop a computer-aided system that can reduce the workload of pathologists and help them in their diagnosis. An image set containing benign and malignant tumor images of breast cancer has been studied. To perform texture analysis on tumor images; first order statistics, Gabor and gray-level co-occurrence matrix (GLCM) feature extraction methods have been applied. Then, various classifiers were applied to the obtained feature matrices and their performances were compared. The highest classification accuracy was achieved 82.06% by Random Forests classifier with feature combination of Gabor and GLCM methods. The results presented here show that computer-assisted diagnosis of breast cancer is a promising field.
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    Conference Object
    In-Silico Methods to Identify Common MicroRNAs and Pathways of Neuromuscular Diseases
    (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019) Yazici, Miray Unlu; Menges, Evrim Aksu; Ulum, Yeliz Z. Akkaya; Hayta, Burcu Balci; Bakir-Gungor, Burcu
    Neuromuscular disorders (NMD) are a heterogeneous group of diseases characterized by the loss of function of the peripheral nerves and muscles. However, there are no effective and widespread therapeutic approaches to prevent or delay the progression of these disease types. microRNAs (miRNAs) which cause significant changes in gene expression by binding to target messenger RNAs (mRNAs), are known to have an effect on disease mechanisms. In this study, by integrating different bioinformatics methods, we aim to find miRNAs, target genes and pathways related to a group of neuromuscular diseases. For this purpose, we determined 17 miRNAs that show significant expression changes between patient and healthy groups; predicted target genes of these miRNAs; and identified affected pathways using subnetwork discovery, functional enrichment based algorithms. In our study, we integrated different in-silico approaches that proceed in top-down manner or bottom-up manner. The identified candidate miRNAs, genes and pathways, which could help to explain neuromuscular disease development mechanisms, are now under investigation in wet-lab.