Evaluation of the relationship between inflammation and bone turnover by sclerostin and Dickkopf-1 (DKK-1) levels in patients with SIRS

Introduction: In intensive care units (ICU), patients remain bedridden for a long time. In addition, severe infections are frequently seen in ICUs. Both prolonged immobilization and serious infections are associated with bone tissue loss. The Wnt pathway has recently been focused on evaluating bone tissue loss. The Wnt pathway participates in both infections and the formation of bone tissue. Wnt pathway inhibitors sclerostin and Dickkopf-1 (DKK-1) inhibit bone formation and increase osteoclastic activity. In this study, we aimed to examine bone turnover by the Wnt inhibitors sclerostin and DKK-1 and their possible associations with inflammation in SIRS patients.Methods: We included 30 patients diagnosed with systemic inflammatory response syndrome (SIRS) in the study group and 16 in the control group. Serum sclerostin, DKK-1, white blood cell (WBC), and C-Reactive Protein (CRP) levels on the day of SIRS diagnosis (basal), the 7th, 14th, and 21stdays were evaluated in the study group, and the results were compared with the control group.Results: When the control group was compared with the basal SIRS, there was a significant elevation in both sclerostin (p=0.003) and DKK-1 (p=0.001). Statistical analysis showed significant decreases in sclerostin levels between basal and the 7th, 14th, and 21st days (p=0.033, p=0.003, p=0.002, respectively). Similarly, significant decreases in DKK-1 levels between basal and the 7th and 21st days (p=0.015, p=0.001, respectively) and an insignificant decrease on the 14th day (p=0.191) was observed. Sclerostin was positively and significantly correlated with WBC and CRP in basal and 7th-day measurements and WBC in 7th and 14th days. DKK-1 is positively and significantly correlated with WBC in basal and 7th-daymeasurements, while DKK-1 negatively correlates with CRP in basal-7th-day measurements.Conclusion: In this study, it was shown for the first time that the Wnt antagonists sclerostin and DKK-1 values are high in SIRS patients in ICU. Both biomarker levels decreased in parallel with the treatment. However, it could not be associated with disease severity and inflammatory marker levels. We believe that monitoring the change of Wnt antagonists will be useful in demonstrating bone turnover in patients with SIRS.Keywords: Dickkopf-1, Intensive care unit, Sclerostin, Systemic inflammatory response syndrome, Wnt signaling pathway, Bone turnove

Derin pekiştirmeli öğrenme ile kripto para portföy yönetimi

Makine Öğrenmesi, günümüzde neredeyse her alanda uygulanabilir hale geldiğinden son zamanlarda oldukça yaygınlaşmıştır. Pekiştirmeli Öğrenme ve Derin Öğrenme olarak adlandırılan Makine Öğreniminin alt alanları, bir araya geldiklerinde, Atari oyunlarında Go'da birden çok kez şampiyonu yenmek için insan düzeyindeki performansa ulaşmada veya bu performansı aşmada başarılı olan gelişmiş algoritmalar ortaya çıkardı. Makine Öğreniminin bu başarıları finans dünyasının da ilgisini çekmiş ve bu tekniklerin finansal piyasalardaki kalıpları tespit etmede de uygulanıp uygulanamayacağı sorusunu gündeme getirmiştir. Yakın zamana kadar, birçok finansal problemin çözümünde regresyon yöntemleri ve trend analizleri ön planda gelmekteydi. Ancak, Pekiştirmeli Öğrenme sayesinde, portföy yönetimi stratejilerinin geliştirilmesi ve sürecin tıpkı robotik sistemlerdekine benzer şekilde kendi kendine öğrenen bir mekanizma yardımıyla alım-satım yapılmasının önü açılmıştır. Bu tezde, Pekiştirmeli Öğrenme kullanarak Derin Öğrenme ticaret ajanının uzun vadeli servetini en üst düzeye çıkarmak için portföydeki belirli bir kripto para veri setindeki ağırlıkların en iyi şekilde nasıl dağıtılacağını araştırılmaktadır. Farklı hiper parametre testleriyle portföyün toplam getirisi hesaplanarak market dinamiğine en uygun parametreler tespit edilmeye çalışılmıştır.Machine Learning has become quite common lately, as it has become applicable in almost every field today. The subfields of Machine Learning, called Reinforcement Learning and Deep Learning, combined, revealed advanced algorithms that succeeded in achieving or exceeding human-level performance to beat the champion in Go multiple times in Atari games. These achievements of Machine Learning also attracted the attention of the financial world and raised the question of whether these techniques can be applied to identify patterns in financial markets. Until recently, regression methods and trend analysis were at the forefront in solving many financial problems. However, thanks to Reinforcement Learning, development of portfolio management strategies and trading with the help of a self-learning mechanism similar to the process in robotic systems were paved. This thesis explores how to best distribute the weights in a particular cryptocurrency dataset in the portfolio to maximize the long-term wealth of the Deep Learning trading agent using Reinforcement Learning. By calculating the total return of the portfolio with different hyper parameter tests, the most suitable parameters for market dynamics were tried to be determined

Investigating Learning Technology By Design Approach in Pre-Service Language Teacher Education: Collaborative and Reflective Experiences

The study aims to present how technology integration can be fulfilled into Language Teacher Education (LTE) contexts by tracking the development of Technological Pedagogical Content Knowledge (TPACK) of the pre-service English Language teachers through Learning Technology By Design approach. A total of 100 senior student teachers (STs) of English at a large state university in Turkey participated in the study. The STs were required totrain their peers about one digital tool and prepare digital materials to be used in language classrooms. The data were collected through three instruments quantitatively and qualitatively: the TPACK-EFL survey, peer reflective discussion forms and focus-group interviews. The findings revealed that the TPACK-EFL knowledge of the STs has improved significantly in all domains after the research intervention, and the STs reported considerably positive perceptions about the digital tools such as increasing motivation and positive atmosphere, more attractive and content-rich materials and more practical and found the experience of peer teaching very effective. The study suggests implications for a variety of digital tools to be used in language classrooms and aneffective technology training in LTE contexts

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Ankara : İhsan Doğramacı Bilkent Üniversitesi İktisadi, İdari ve Sosyal Bilimler Fakültesi, Tarih Bölümü, 2016.This work is a student project of the The Department of History, Faculty of Economics, Administrative and Social Sciences, İhsan Doğramacı Bilkent University.by Özer, Abdurrahim

Cardiac Masses: Pathological and Surgical Features - A Multicenter Study

Introduction: This study aimed to review the surgical excision results and pathological diagnostic features of rarely observed intracardiac masses in the light of the literature. Diagnosis and treatment approaches and complications were evaluated. Methods: Forty patients (26 females, mean age 52.1 +/- 18.1 years, and 14 males, mean age 48.1 +/- 20.5 years), who had undergone surgery for intracardiac mass between January 2008 and December 2018, were included in this study. The patients' data were analyzed retrospectively from the medical records of both centers. Results: When the pathological diagnoses were examined, 85.8% of the masses (n=35) were observed to be benign (benign tumor + hydatid cyst) and 14.2% (n=5) were malignant tumors. The masses were most commonly located in the left atrium (75%, n=30), and this was followed by the right ventricle (12.5%, n=5), right atrium (7.5%, n=3), and left ventricle (5%, n=2). Of the patients, 7.5% (n=3) died during the early postoperative period, while the remaining 92.5% (n=37) were discharged with healing. In the histopathological diagnosis of the patients, in whom in-hospital major adverse cardiovascular events were observed, there was malignancy in two cases. Conclusion: Intracardiac masses, which have pathological features, are severe life-threatening problems. In-hospital mortality is frequent, especially in malignant tumors