CNN vs. LSTM for Turkish text classification

In this paper, the efficiency of two states of the art text classification techniques, i.e., Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) for supporting the Turkish text classification has been investigated. In addition, the effect of the main preprocessing steps such as Tokenization, Stop Word Elimination, Stemming, etc. has also been studied. Several experiments using "TTC-3600"dataset were performed, and it has been observed that both CNN and LSTM can efficiently support the Turkish language and can achieve quite good performance. Related to data preprocessing, results indicated that such a process improves the performance, however, for the Turkish language, it is preferred to exclude stemming. Also, by comparing the performance of feature extraction techniques for processing Turkish language, Word2Vec outperforms TF-IDF. © 2021 IEEE

CD4(+) T cells of myasthenia gravis patients are characterized by ıncreased IL-21, IL-4, and IL-17A productions and higher presence of PD-1 and ICOS

Myasthenia gravis (MG) is an autoimmune disease mediated by autoantibodies predominantly against the acetylcholine receptor (AChR). Specific T cell subsets are required for long-term antibody responses, and cytokines secreted mainly from CD4(+) T cells regulate B cell antibody production. The aim of this study was to assess the differences in the cytokine expressions of CD4(+) T cells in MG patients with AChR antibodies (AChR-MG) and the effect of immunosuppressive (IS) therapy on cytokine activity and to test these findings also in MG patients without detectable antibodies (SN-MG). Clinically diagnosed AChR-MG and SN-MG patients were included. The AChR-MG patients were grouped as IS-positive and -negative and compared with age- and sex-matched healthy controls. Peripheral blood mononuclear cells were used for ex vivo intracellular cytokine production, and subsets of CD4(+) T cells and circulating follicular helper T (cTfh) cells were detected phenotypically by the expression of the chemokine and the costimulatory receptors. Thymocytes obtained from patients who had thymectomy were also analyzed. IL-21, IL-4, IL-10, and IL-17A productions in CD4(+) T cells were increased in AChR-MG compared to those in healthy controls. IS treatment enhanced IL-10 and reduced IFN-gamma production in AChR-MG patients compared to those in IS-negative patients. Increased IL-21 and IL-4 productions were also demonstrated in SN-MG patients. Among CD4(+) T cells, Th17 cells were increased in both disease subgroups. Treatment induced higher proportions of Th2 cells in AChR-MG patients. Both CXCR5(+) and CXCR5(-) CD4(+) T cells expressed higher programmed cell death protein 1 (PD-1) and inducible costimulatory (ICOS) in AChR-MG and SN-MG groups, mostly irrespective of the treatment. Based on chemokine receptors on CXCR5(+)PD-1(+) in CD4(+) T (cTfh) cells, in AChR-MG patients without treatment, the proportions of Tfh17 cells were higher than those in the treated group, whereas the Tfh1 cells were decreased compared with those in the controls. The relevance of CXCR5 and PD-1 in the pathogenesis of AChR-MG was also suggested by the increased presence of these molecules on mature CD4 single-positive thymocytes from the thymic samples. The study provides further evidence for the importance of IL-21, IL-17A, IL-4, and IL-10 in AChR-MG. Disease-related CD4(+)T cells are identified mainly as PD-1(+) or ICOS+ with or without CXCR5, resembling cTfh cells in the circulation or probably in the thymus. AChR-MG and SN-MG seem to have some similar characteristics. IS treatment has distinctive effects on cytokine expression.Istanbul Universit

Rna-seq verilerinin sınıflandırılmasında derin öğrenme yöntemlerinin entegrasyonu

Rahim ağzı kanseri, serviks adı verilen rahmin alt kısmındaki hücreleri etkileyen bir jinekolojik kanser türüdür. Gen mutasyonlarının bir sonucu olarak hücreler anormal hale gelir ve kontrolsüz bölünme kanserin birincil nedenidir. Öte yandan, Alzheimer hastalığı, esas olarak insanlar yaşlandıkça beyin hücresi ölümünün bir sonucu olarak hafıza kaybına ve bunamaya neden olan geri dönüşü olmayan bir nörolojik hastalıktır. Beynin düşünme, öğrenme ve hafızayı kontrol eden kısımları yaralanmış veya tahrip olmuş ve semptomlara neden olmuştur. Rahim ağzı kanseri ve Alzheimer hastalığı her ikisi de genetik bozukluklardır. Birçok genin bilgisi RNA-Seq verilerinde tutulur. Bu yaklaşımı hızlandırmak ve klinisyenlere tanı sürecinde yardımcı olmak için ilişkisiz gen sayısı azaltılarak sınıflandırma algoritmaları kullanılarak metodolojiler oluşturulabilir. Bu önerinin amacı, gerçek örneklerden elde edilen genlerle oluşturulmuş RNA-Seq veri kümelerini kullanarak Rahim Ağzı Kanseri ve Alzheimer Hastalığını incelemek için istatistiksel ve derin öğrenme yaklaşımlarını kullanmaktır. RNA-Seq veri setinin boyutunu küçültmek için iki veri seti için tüm genler arasında %5, %10 ve %30 olacak şekilde gen seçilim yapılır ve gen ekspresyon verileri her bir gen için genlerin önem düzeyine göre oluşturulmuştur. Bu üç senaryoda, seçilen genler kategorizasyon sürecinde eğitilir ve test edilir. Sınıflandırma için Derin Sinir Ağları (DNN), Evrişimli sinir ağları (CNN) ve uzun kısa süreli bellek (LSTM) yaklaşımları uygulanmaktadır. Bu araştırmanın ardından Alzheimer Hastalığı ve Rahim Ağzı Kanseri sınıflandırmalarında hangi yaklaşımların en iyi sonuç verdiği değerlendirilecektir.Cervical cancer is a type of gynecological cancer that affects the cells in the lower section of the uterus called the cervix. Cells become abnormal as a result of gene mutations, and uncontrolled division is the primary cause of cancer. On the other hand, Alzheimer's disease is an irreversible neurological disease that causes memory loss and dementia, primarily as a result of brain cell death as people age. The parts of the brain that control thinking, learning, and memory have been injured or destroyed, causing symptoms. Cervical cancer and Alzheimer's disease are both genetic disorders. As a matter of fact, gene expression is significant in the diagnosis and classification of Cervical Cancer and Alzheimer's disease. Many genes' information is kept in RNA-Seq data. To accelerate this approach and assist clinicians in the diagnosis process, methodologies can be constructed using classification algorithms with decreasing the number of irrelevant genes. The objective of this thesis is to use statistical and deep learning approaches to examine Cervical Cancer and Alzheimer's Disease utilizing RNA-Seq datasets built with genes obtained from real samples. To lower the size of the RNA-Seq data set, gene selection is done by 5%, 10%, and 30% among all genes for both datasets, and the gene expression data were generated for each gene according to the importance level of the genes. In three scenarios, the selected genes are trained and tested in the categorization process. Deep Neural networks, convolutional neural networks, and long short-term memory approaches are implemented for classification. Following this research, it will be evaluated which approaches work best in the classifications of Alzheimer's Disease and Cervical Cancer

Training of ANFIS with simulated annealing algorithm on flexural buckling load prediction of aluminium alloy columns

In this study, we propose a simulated annealing algorithm (SA) to train an adaptive neurofuzzy inference system (ANFIS). We performed different types of optimization algorithms such as genetic algorithm (GA), SA and artificial bee colony algorithm on two different problem types. Then, we measured the performance of these algorithms. First, we applied optimization algorithms on eight numerical benchmark functions which are sphere, axis parallel hyper-ellipsoid, Rosenbrock, Rastrigin, Schwefel, Griewank, sum of different powers and Ackley functions. After that, the training of ANFIS is carried out by mentioned optimization algorithms to predict the strength of heat-treated fine-drawn aluminium composite columns defeated by flexural bending. In summary, the accuracy of the proposed soft computing model was compared with the accuracy of the results of existing methods in the literature. It is seen that the training of ANFIS with the SA has more accuracy.</p

CD4+ T Cells of Myasthenia Gravis Patients Are Characterized by Increased IL-21, IL-4, and IL-17A Productions and Higher Presence of PD-1 and ICOS

© Copyright © 2020 Çebi, Durmus, Aysal, Özkan, Gül, Çakar, Hocaoglu, Mercan, Yentür, Tütüncü, Yayla, Akan, Dogan, Parman and Saruhan-Direskeneli.Myasthenia gravis (MG) is an autoimmune disease mediated by autoantibodies predominantly against the acetylcholine receptor (AChR). Specific T cell subsets are required for long-term antibody responses, and cytokines secreted mainly from CD4+ T cells regulate B cell antibody production. The aim of this study was to assess the differences in the cytokine expressions of CD4+ T cells in MG patients with AChR antibodies (AChR-MG) and the effect of immunosuppressive (IS) therapy on cytokine activity and to test these findings also in MG patients without detectable antibodies (SN-MG). Clinically diagnosed AChR-MG and SN-MG patients were included. The AChR-MG patients were grouped as IS-positive and -negative and compared with age- and sex-matched healthy controls. Peripheral blood mononuclear cells were used for ex vivo intracellular cytokine production, and subsets of CD4+ T cells and circulating follicular helper T (cTfh) cells were detected phenotypically by the expression of the chemokine and the costimulatory receptors. Thymocytes obtained from patients who had thymectomy were also analyzed. IL-21, IL-4, IL-10, and IL-17A productions in CD4+ T cells were increased in AChR-MG compared to those in healthy controls. IS treatment enhanced IL-10 and reduced IFN-γ production in AChR-MG patients compared to those in IS-negative patients. Increased IL-21 and IL-4 productions were also demonstrated in SN-MG patients. Among CD4+ T cells, Th17 cells were increased in both disease subgroups. Treatment induced higher proportions of Th2 cells in AChR-MG patients. Both CXCR5+ and CXCR5− CD4+ T cells expressed higher programmed cell death protein 1 (PD-1) and inducible costimulatory (ICOS) in AChR-MG and SN-MG groups, mostly irrespective of the treatment. Based on chemokine receptors on CXCR5+PD-1+ in CD4+ T (cTfh) cells, in AChR-MG patients without treatment, the proportions of Tfh17 cells were higher than those in the treated group, whereas the Tfh1 cells were decreased compared with those in the controls. The relevance of CXCR5 and PD-1 in the pathogenesis of AChR-MG was also suggested by the increased presence of these molecules on mature CD4 single-positive thymocytes from the thymic samples. The study provides further evidence for the importance of IL-21, IL-17A, IL-4, and IL-10 in AChR-MG. Disease-related CD4+T cells are identified mainly as PD-1+ or ICOS+ with or without CXCR5, resembling cTfh cells in the circulation or probably in the thymus. AChR-MG and SN-MG seem to have some similar characteristics. IS treatment has distinctive effects on cytokine expression