Uluslararası İndeksli Yayınlar / International Indexed Publications
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Browsing Uluslararası İndeksli Yayınlar / International Indexed Publications by Type "Review"
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Publication Effects of Pilates Exercises on Idiopathic Scoliosis: A Scoping Review of the Literature(Springer, 2023) Çolak, Tuğba Kuru; Akçay, Burçin; APTİ, ADNANPurpose Scoliosis is a deformity involving changes in three planes. These changes include lateral curvature in the frontal plane, changes in physiological thoracic kyphosis and lumbar lordosis angles in the sagittal plane, and rotation of the vertebrae in the transverse plane. The aim of this scoping review was to review and summarize the available literature to determine whether Pilates exercises are an effective treatment for scoliosis.MethodsThe Cochrane Library (reviews, protocols, trials), PubMed, Web of Science, Ovid, Scopus, PEDro, Medline, CINAHL (EBSCO), ProQuest, and Google Scholar electronic databases were used to search for published articles from inception to February 2022. All the searches included English language studies. Keywords were determined as "scoliosis and Pilates" or "idiopathic scoliosis and Pilates", "curve and Pilates", "spinal deformity and Pilates."Results Seven studies were included; one study was a meta-analysis study, three studies compared Pilates and Schroth exercises, and three applied Pilates exercises in combined therapy. The studies included in this review used outcome measurements of Cobb angle, ATR, chest expansion, SRS-22r, posture assessment, weight distribution, and psychological factors such as depression.ConclusionsThe results of this review suggest that the level of evidence regarding the effect of Pilates exercises on scoliosis-related deformity is very limited. Pilates exercises can be applied to reduce asymmetrical posture in individuals with mild scoliosis with reduced growth potential and progression risk.Publication Endoplasmic Reticulum Stress and Oncomir-Associated Chemotherapeutic Drug Resistance Mechanisms in Breast Cancer Tumors(TUBITAK - The Scientific and Technological Research Council of Turkey, 2021) Mehdizadehtapeh, Leila; YERLİKAYA, PINAR OBAKANBreast cancer, as a heterogenous malign disease among the top five leading causes of cancer death worldwide, is defined as by far the most common malignancy in women. It contributes to 25% of all cancer-associated deaths after menopause. Breast cancer is categorized based on the expression levels of cell surface and intracellular steroid receptors [estrogen, progesterone receptors, and human epidermal growth factor receptor (HER2)], and the treatment approaches frequently include antiestrogen, aromatase inhibitors, and Herceptin. However, the management and prevention strategies due to adverse side effects stress the patients. The unsuccessful treatments cause to raise the drug levels, leading to excessive toxic effects on healthy cells, and the development of multidrug-resistance (MDR) in the tumor cells against chemotherapeutic agents. MDR initially causes the tumor cells to gain a metastatic character, and subsequently, the patients do not respond adequately to treatment. Endoplasmic reticulum (ER) stress is one of the most important mechanisms supporting MDR development. ER stress-mediated chemotherapeutic resistance is very common in aggressive tumors. The in vitro and in vivo experiments on breast tumors indicate that ER stress-activated protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK)- activating transcription factor (ATF4) signal axis plays an important role in the survival of tumors and metastasis. Besides, ER stress-associated oncogenic microRNAs (miRNAs) induce chemoresistance in breast tumors. We aimed to have a look at the development of resistance mechanisms due to ER stress as well as the involvement of ER stress-associated miRNA regulation following the chemotherapeutic regimen in the human breast tumors. We also aimed to draw attention to potential molecular markers and therapeutic targets.Publication Gene Editing and RNAi Approaches for COVID-19 Diagnostics and Therapeutics(Springer Nature, 2021) Berber, Burak; Aydın, Cihan; Kocabaş, Fatih; Güney-Esken, Gülen; Yılancıoğlu, Kaan; Karadağ-Alpaslan, Medine; Çalıseki, Mehmet; Yüce, Melek; Demir, Sevda; Taştan, CihanThe novel coronavirus pneumonia (COVID-19) is a highly infectious acute respiratory disease caused by Severe Acute Respiratory Syndrome-Related Coronavirus (SARS-CoV-2) (Prec Clin Med 2020;3:9-13, Lancet 2020;395:497-506, N. Engl J Med 2020a;382:1199-207, Nature 2020;579:270-3). SARS-CoV-2 surveillance is essential to controlling widespread transmission. However, there are several challenges associated with the diagnostic of the COVID-19 during the current outbreak (Liu and Li (2019), Nature 2020;579:265-9, N. Engl J Med 2020;382:727-33). Firstly, the high number of cases overwhelms diagnostic test capacity and proposes the need for a rapid solution for sample processing (Science 2018;360:444-8). Secondly, SARS-CoV-2 is closely related to other important coronavirus species and subspecies, so detection assays can give false-positive results if they are not efficiently specific to SARS-CoV-2. Thirdly, patients with suspected SARS-CoV-2 infection sometimes have a different respiratory viral infection or co-infections with SARS-CoV-2 and other respiratory viruses (MedRxiv 2020a;1-18). Confirmation of the COVID-19 is performed mainly by virus isolation followed by RT-PCR and sequencing (N. Engl J Med 2020;382:727-33, MedRxiv 2020a, Turkish J Biol 2020;44:192-202). The emergence and outbreak of the novel coronavirus highlighted the urgent need for new therapeutic technologies that are fast, precise, stable, easy to manufacture, and target-specific for surveillance and treatment. Molecular biology tools that include gene-editing approaches such as CRISPR-Cas12/13-based SHERLOCK, DETECTR, CARVER and PAC-MAN, antisense oligonucleotides, antisense peptide nucleic acids, ribozymes, aptamers, and RNAi silencing approaches produced with cutting-edge scientific advances compared to conventional diagnostic or treatment methods could be vital in COVID-19 and other future outbreaks. Thus, in this review, we will discuss potent the molecular biology approaches that can revolutionize diagnostic of viral infections and therapies to fight COVID-19 in a highly specific, stable, and efficient way.Publication Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review(MDPI, 2022) JORAYEVA, MANZURA; AKBULUT, AKHAN; Çatal, Çağatay; Mishra, AlokSoftware defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be allocated to fault-prone modules effectively. While a few software defect prediction models have been developed for mobile applications, a systematic overview of these studies is still missing. Therefore, we carried out a Systematic Literature Review (SLR) study to evaluate how machine learning has been applied to predict faults in mobile applications. This study defined nine research questions, and 47 relevant studies were selected from scientific databases to respond to these research questions. Results show that most studies focused on Android applications (i.e., 48%), supervised machine learning has been applied in most studies (i.e., 92%), and object-oriented metrics were mainly preferred. The top five most preferred machine learning algorithms are Naive Bayes, Support Vector Machines, Logistic Regression, Artificial Neural Networks, and Decision Trees. Researchers mostly preferred Object-Oriented metrics. Only a few studies applied deep learning algorithms including Long Short-Term Memory (LSTM), Deep Belief Networks (DBN), and Deep Neural Networks (DNN). This is the first study that systematically reviews software defect prediction research focused on mobile applications. It will pave the way for further research in mobile software fault prediction and help both researchers and practitioners in this field.Publication The Tumor Microenvironment of Pancreatic Adenocarcinoma and Immune Checkpoint Inhibitor Resistance: A Perplex Relationship(OAE Publishing Inc., 2020) Şahin, İrem; TÜREN, SEVDA; Santapuram, Pranav; Şahin, İbrahim HalilPancreatic cancer is one of the most aggressive cancers with a high mortality rate even among patients with early-stage disease. Although recent studies with novel therapeutic approaches have led to modest improvement in survival outcomes, limited progress is achieved for the use of immunotherapeutics in this challenging cancer. Immune checkpoint inhibitors, thus far, single-agent or in combination, have not yielded significant improvement in survival outcomes except in mismatch repair-deficient pancreatic cancer. The tumor microenvironment of pancreatic cancer has been considered as an attractive target for over a decade based on preclinical studies that suggested it may adversely affect drug delivery and antitumor immunity. In this review article, we elaborate on the biology of pancreatic cancer microenvironment, its highly complicated interaction with cancer cells, and the immune system. We also discuss plausible explanations that led to the failure of immune checkpoint inhibitors as therapeutic agents and the potential impacts of pancreatic cancer stroma on these negative studies.