Browsing by Author "Deniz, Kemal"

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Alantolactone ameliorates graft versus host disease in mice
(ELSEVIER, 2024) Odabas, Gul Pelin; Aslan, Kubra; Suna, Pinar Alisan; Kendirli, Perihan Kader; Erdem, Şerife; Çakır, Mustafa; Özcan, Alper; Yılmaz, Ebru; Karakukcu, Musa; Donmez-Altuntas, Hamiyet; Yay, Arzu Hanim; Deniz, Kemal; Altay, Derya; Arslan, Duran; Canatan, Halit; Eken, Ahmet; Unal, Ekrem; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü; Kendirli, Perihan Kader
The anti-inflammatory and immunosuppressive drugs which are used in the treatment of Graft-versus-Host Disease (GVHD) have limited effects in controlling the severity of the disease. In this study, we aimed to investigate the prophylactic effect of Alantolactone (ALT) in a murine model of experimental GVHD. The study included 4 BALB/c groups as hosts: Naïve (n = 7), Control GVHD (n = 16), ALT-GVHD (n = 16), and Syngeneic transplantation (n = 10). Busulfan (20 mg/kg/day) for 4 days followed by cyclophosphamide (100 mg/kg/day) were administered for conditioning. Allogeneic transplantation was performed with cells collected from mismatched female C57BL/6, and GVHD development was monitored by histological and flow cytometric assays. Additionally, liver biopsies were taken from GVHD patient volunteers between ages 2–18 (n = 4) and non-GVHD patients between ages 2–50 (n = 5) and cultured ex vivo with ALT, and the supernatants were used for ELISA. ALT significantly ameliorated histopathological scores of the GVHD and improved GVHD clinical scores. CD8+ T cells were shown to be reduced after ALT treatment. More importantly, ALT treatment skewed T cells to a more naïve phenotype (CD62L+ CD44− ). ALT did not alter Treg cell number or frequency. ALT treatment appears to suppress myeloid cell lineage (CD11c+). Consistent with reduced myeloid lineage, liver and small intestine levels of GM-CSF were reduced in ALT-treated mice. IL-6 gene expression was significantly reduced in the intestinal tissue. Ex vivo ALT-treated liver biopsy samples from GVHD patients showed a trend of decrease in proinflammatory cytokines but there was no statistical significance. Collectively, the data indicated that ALT may have immunomodulatory actions in a preclinical murine GVHD model.
Liver fibrosis staging using CT image texture analysis and soft computing
(ELSEVIER, 2014) Kayaalti, Omer; Aksebzeci, Bekir Hakan; Karahan, Ibrahim Okkes; Deniz, Kemal; Ozturk, Mehmet; Yilmaz, Bulent; Kara, Sadik; Asyali, Musa Hakan; 0000-0001-7476-8141; 0000-0003-2954-1217; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Yilmaz, Bulent; Aksebzeci, Bekir Hakan
Liver biopsy is considered to be the gold standard for analyzing chronic hepatitis and fibrosis; however, it is an invasive and expensive approach, which is also difficult to standardize. Medical imaging techniques such as ultrasonography, computed tomography (CT), and magnetic resonance imaging are non-invasive and helpful methods to interpret liver texture, and may be good alternatives to needle biopsy. Recently, instead of visual inspection of these images, computer-aided image analysis based approaches have become more popular. In this study, a non-invasive, low-cost and relatively accurate method was developed to determine liver fibrosis stage by analyzing some texture features of liver CT images. In this approach, some suitable regions of interests were selected on CT images and a comprehensive set of texture features were obtained from these regions using different methods, such as Gray Level Co-occurrence matrix (GLCM), Laws’ method, Discrete Wavelet Transform (DWT), and Gabor filters. Afterwards, sequential floating forward selection and exhaustive search methods were used in various combinations for the selection of most discriminating features. Finally, those selected texture features were classified using two methods, namely, Support Vector Machines (SVM) and k-nearest neighbors (k-NN). The mean classification accuracy in pairwise group comparisons was approximately 95% for both classification methods using only 5 features. Also, performance of our approach in classifying liver fibrosis stage of subjects in the test set into 7 possible stages was investigated. In this case, both SVM and k-NN methods have returned relatively low classification accuracies. Our pairwise group classification results showed that DWT, Gabor, GLCM, and Laws’ texture features were more successful than the others; as such features extracted from these methods were used in the feature fusion process. Fusing features from these better performing families further improved the classification performance. The results show that our approach can be used as a decision support system in especially pairwise fibrosis stage comparisons.
Staging of the liver fibrosis from CT images using texture features
(2012) Kayaalti, Ömer; Aksebzeci, Bekir Hakan; Karahan, Ibrahim Ö.; Deniz, Kemal; Öztürk, Menmet; Yilmaz, Bülent; Kara, Sadik; Asyali, Musa Hakan; 0000-0003-2954-1217; 0000-0001-7476-8141; AGÜ; Aksebzeci, Bekir Hakan; Yilmaz, Bülent; Asyali, Musa Hakan
Even though liver biopsy is critical for evaluating chronic hepatitis and fibrosis, it is an invasive, costly, and difficult to standardize approach. The developments in medical image processing and artificial intelligence methods have advanced the potential of using computer-aided diagnosis techniques in the classification of liver tissues. The aim of this study was to develop a non-invasive, cost-effective, and fast approach to specify fibrosis stage using the texture properties of computed tomography images of liver. Gray level co-occurrence matrix, discrete wavelet transform, and discrete Fourier transform were the image analysis tools in the feature extraction phase. Following dimension reduction of the texture features support vector machines and k-nearest neighbor methods were used in the classification phase of this study. Our results showed that our approach is feasible in fibrosis staging especially in pairwise stage comparisons with success rate of approximately 90%.