Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Book Part Rebuilding the British Seamen's Hospital at Smyrna in the Wake of Smallpox and Cholera Epidemics, 1892(Intellect Ltd., 2021) Gün, I.T.S.; Erten, E.Article Citation - Scopus: 13Her2-Targeted, Degradable Core Cross-Linked Micelles for Specific and Dual Ph-Sensitive Dox Release(John Wiley and Sons Inc, 2022) Bayram, N.N.; Ulu, G.T.; Topuzoğulları, M.; Baran, Y.; Dinçer, İşoğlu, S.Here, a targeted, dual-pH responsive, and stable micelle nanocarrier is designed, which specifically selects an HER2 receptor on breast cancer cells. Intracellularly degradable and stabilized micelles are prepared by core cross-linking via reversible addition−fragmentation chain-transfer (RAFT) polymerization with an acid-sensitive cross-linker followed by the conjugation of maleimide–doxorubicin to the pyridyl disulfide-modified micelles. Multifunctional nanocarriers are obtained by coupling HER2-specific peptide. Formation of micelles, addition of peptide and doxorubicin (DOX) are confirmed structurally by spectroscopical techniques. Size and morphological characterization are performed by Zetasizer and transmission electron microscope (TEM). For the physicochemical verification of the synergistic acid-triggered degradation induced by acetal and hydrazone bond degradation, Infrared spectroscopy and particle size measurements are used. Drug release studies show that DOX release is accelerated at acidic pH. DOX-conjugated HER2-specific peptide-carrying nanocarriers significantly enhance cytotoxicity toward SKBR-3 cells. More importantly, no selectivity toward MCF-10A cells is observed compared to HER2(+) SKBR-3 cells. Formulations cause apoptosis depending on Bax and Caspase-3 and cell cycle arrest in G2 phase. This study shows a novel system for HER2-targeted therapy of breast cancer with a multifunctional nanocarrier, which has higher stability, dual pH-sensitivity, selectivity, and it can be an efficient way of targeted anticancer drug delivery. © 2021 Wiley-VCH GmbHConference Object Citation - WoS: 2Citation - Scopus: 4A Comparison of Feature Selection Algorithms for Cancer Classification Through Gene Expression Data: Leukemia Case(Institute of Electrical and Electronics Engineers Inc., 2018) Taşçı, Aslı; İnce, Türker; Güzeliş, CüneytIn this study, three different feature selection algorithms are compared using Support Vector Machines as classifier for cancer classification through gene expression data. The ability of feature selection algorithms to select an optimal gene subset for a cancer type is evaluated by the classification ability of selected genes. A publicly available micro array dataset is employed for gene expression values. Selected gene subsets were able to classify subtypes of the considered cancer type with high accuracies and showed that these feature selection methods were applicable for bio-marker gene selection.