TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Research Project Kolon Polipleri için Kolonoskopi ve Histopatoloji Görüntülerinden Yapay Zekâ Destekli Prognostik Belirteç Tespiti(2023) Doğan, Serkan; Doğan, Refika Sultan; Aydın, Zafer; Akay, Ebru; Güzel, Ömer Faruk; Yilmaz, Bulent; Taşdemir, Sena Büşra YengeçKolon kanseri vakalarının çoğu kolon mukozasında anormal hücre çoğalmasından kaynaklanan poliplerle başlar. Bu projede Kayseri Şehir Hastanesi gastroenteroloji kliniğine gelen 201 hastada tespit edilen poliplere dair kolonoskopi video ve görüntülerinden ve biyopsi örneklerinden elde edilen patoloji raporu ve immunohistokimyasal (İHK) gen ve protein analizi sonuçlarını içeren kapsamlı bir veri seti oluşturulmuştur. Bu projede, elde ettiğimiz veri setinde yer alan görüntülerden kolon poliplerinin evresini/patolojisini tahmin etmek için yenilikçi derin öğrenme ve makine öğrenmesi yöntemlerini temel alan çevrim içi veya dışı kullanılabilen kapsamlı bir yapay zekâ destekli bilgisayarlı görü sistemi geliştirilmiştir. Bu proje kapsamında; kolonoskopi videolarından gerçek zamanlı polip lokalizasyonu, videolardan görüntülerin elde edilmesi, polip görüntülerinden hiperplastik ve tübüler polip ayrımının otomatik yapılması ve hekim performansıyla karşılaştırılması, bu görüntüler üzerinde ayırt edici özniteliklerin tespit edilmesi, farklı büyütmelerde alınan histopatoloji görüntülerinden adenomatöz olan ve olmayan poliplerin ve poliplerin alt tiplerinin yenilikçi derin öğrenme yöntemleriyle tespiti, Ki-67, p53, VEGF, PDL-lenfosit ve PDL-epitel, BRAF ve cd34 isimli gen ve proteinlerin İHK analizlerinin sonuçlarının polip tipleri ve alt tipleri için yorumlanması ve poliplerin bu bilgilere göre etiketlenmesi gerçekleştirilmiştir.Research Project Artificial Intelligence Assisted Prognostic Marker Determination from Colonoscopy and Histopathology Images for Colon Polyps(2023) Doğan, Serkan; Doğan, Refika Sultan; Aydın, Zafer; Akay, Ebru; Güzel, Ömer Faruk; Yilmaz, Bulent; Taşdemir, Sena Büşra YengeçIn this project our goal is to develop a computer vision and artificial intelligence-based system to be used in the real-time or offline differentiation (and characterization) of colon polyps that are known to be the precursors of colon cancer. The system will use image/video processing, machine learning and deep learning approaches. It is expected to provide a real-time optical biopsy opportunity to the endoscopists to examine the polyps in terms of type, phase, malignancy potential, etc. during the colonoscopy procedure without a need to send the extracted tissue to the pathology clinic. The system will allow to make sense of the molecular level of the tissues from the colonoscopy and histopathology images.Article Thermosensitive Pluronic® F127-Based in Situ Gel Formulation Containing Nanoparticles for the Sustained Delivery of Paclitaxel(2023) Unal, Sedat; Aktas, Yesim; Doğan, Osman; Tekeli, Merve CelikBone metastasis is one of the most encountered complications among cancer patients and majority of cancer types has led to bone metastasis. Paclitaxel (PCX) is an anticancer agent commonly used in cancer treatment. However, its clinical use is restricted owing to poor water solubility. PCL NPs were investigated to cope with solubility problem of PCX. The size, polydispersity index and zeta potential of PCL were 383.8±2.4 nm, 0.253±0.122 and +51.3±6.1 mV, respectively. The PCX encapsulation efficiency was 77.2±2.1%. Subsequently, in situ gellling system was prepared by using different Pluronic F-127 concentration in order to determine the optimum ratio. İn situ gel formulation containing 20% Pluronic F-127 was selected as the optimum formulation and subjected to characterization tests. The viscosity of in situ gelling system with CS/PCX-PCL NPs at room temperature (25 °C±0.1) and at body temperature (37 °C±0.1) were found 137.00 ±3.05 cP and 890.30 ±89.61 cP at 100 rpm, respectively. According to the release results, in situ gel provided prolonged release profile compared to PCL NPs alone. Consequently, in situ gel containing CS/PCX-PCL NP elucidated in detail is a promising approach for locally applicable injectable systems.Article Citation - WoS: 1Citation - Scopus: 1Enlightening the Molecular Mechanisms of Type 2 Diabetes With a Novel Pathway Clustering and Pathway Subnetwork Approach(Tubitak Scientific & Technological Research Council Turkey, 2022-01-01) Bakir-Gungor, Burcu; Yazici, Miray Unlu; Goy, Gokhan; Temiz, Mustafa; Ünlü Yazici, MirayType 2 diabetes mellitus (T2D) constitutes 90% of the diabetes cases, and it is a complex multifactorial disease. In the last decade, genome-wide association studies (GWASs) for T2D successfully pinpointed the genetic variants (typically single nucleotide polymorphisms, SNPs) that associate with disease risk. In order to diminish the burden of multiple testing in GWAS, researchers attempted to evaluate the collective effects of interesting variants. In this regard, pathway-based analyses of GWAS became popular to discover novel multigenic functional associations. Still, to reveal the unaccounted 85 to 90% of T2D variation, which lies hidden in GWAS datasets, new post-GWAS strategies need to be developed. In this respect, here we reanalyze three metaanalysis data of GWAS in T2D, using the methodology that we have developed to identify disease-associated pathways by combining nominally significant evidence of genetic association with the known biochemical pathways, protein-protein interaction (PPI) networks, and the functional information of selected SNPs. In this research effort, to enlighten the molecular mechanisms underlying T2D development and progress, we integrated different in silico approaches that proceed in top-down manner and bottom-up manner, and presented a comprehensive analysis at protein subnetwork, pathway, and pathway subnetwork levels. Using the mutual information based on the shared genes, the identified protein subnetworks and the affected pathways of each dataset were compared. While most of the identified pathways recapitulate the pathophysiology of T2D, our results show that incorporating SNP functional properties, PPI networks into GWAS can dissect leading molecular pathways, and it could offer improvement over traditional enrichment strategies.