Erciyes University - AVESIS
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Bitki Büyümeyi Teşvik Edici Rizobakteri (PGPR) Uygulamalarının Kısıtlı Sulama Şartlarında Patlıcanda Bitki Gelişimi, Fizyolojisi, Biyokimyasal İçeriği ile Gen Ekspresyonu Üzerine Etkisinin Araştırılması
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65 YAŞ ÜSTÜ BİREYLERDE İMMÜN KONTROL NOKTALARI VE KEMOKİN İMZASININ FRAİL, PRE-FRAİL, NON-FRAİL DURUMLARINA GÖRE İNCELENMESİ
No full textBu çalışma, ileri yaş bireylerde bağışıklık sisteminde meydana gelen değişimlerin moleküler düzeyde anlaşılmasına katkı sağlamayı amaçlamaktadır. Özellikle immün sistemin düzenleyici molekülleri olan İmmün Kontrol Noktaları ve kemokinler üzerine odaklanarak, yaşlanma süreciyle ilişkili bağışıklık dinamiklerinin ortaya konması hedeflenmektedir.Çalışmada; belirli yaş gruplarındaki bireylerin biyolojik örnekleri çeşitli moleküler ve hücresel analiz yöntemleriyle değerlendirilecek, elde edilen veriler istatistiksel olarak analiz edilerek bağışıklık profilleri arasındaki farklılıklar ortaya konacaktır. Kullanılan yöntemler sayesinde hem gen düzeyinde hem de protein düzeyinde kapsamlı bir değerlendirme yapılması planlanmaktadır.Bu araştırmadan elde edilecek bulguların, yaşla ilişkili immün değişiklikleri daha derinlemesine anlamaya katkı sunmasının yanı sıra, yaşlı bireylerde bağışıklık sistemine yönelik yenilikçi tedavi ve izlem stratejilerinin geliştirilmesine zemin hazırlaması beklenmektedir.This study aims to contribute to the understanding of age-related alterations in the immune system at a molecular level in elderly individuals. Specifically, it focuses on immune checkpoint molecules and chemokine signatures, which are key regulators of immune responses, to elucidate the immunological dynamics associated with the aging process.Within the scope of the research, biological samples obtained from individuals in distinct age groups will be analyzed using various molecular and cellular techniques. The data collected will be subjected to statistical analyses in order to identify significant immunological differences across the age spectrum. The combination of gene and protein expression profiling is expected to provide a comprehensive view of the aging immune landscape.Findings from this study are anticipated to enhance our understanding of immunosenescence and support the development of novel therapeutic and monitoring strategies targeting the immune system in elderly populations.</p
Phenotypic and Genotypic Characterization of Silent Antibiotic Resistance Genes and Their Activation Under Antibiotic Stress in Clinical Escherichia coli and Klebsiella pneumoniae Isolates
No full textThe simulation of diatomic molecule of spin-3/2 Blume–Capel model with full antiferromagnetic interactions: Exacts recursion relations approach
No full textIn this work, we investigate the magnetic and critical properties of a diatomic molecular model in which each molecule is composed of two atoms with spin = ′ = 3∕2. The system is simulated on the Bethe lattice (BL) with coordination number = 3 using the Exacts Recursion Relations (ERR) method. To explore antiferromagnetic (AFM) behavior, all exchange interactions are chosen to be negative ( = ′ = = −1). The thermal variations of the sublattice magnetizations reveal the existence of several ordered phases, including five antiferromagnetic, one ferrimagnetic, and one mixed (partially ordered) phase. These phases are separated by both first- and second-order phase transition lines, giving rise to different types of critical points such as tricritical points (TCP), critical end points (CEP), and quadruple points (QP). The corresponding phase diagrams in the (,) and (,) planes exhibit rich topological structures resulting from the competition between the exchange interactions, the crystal field , and the external magnetic field . The results obtained provide a deeper understanding of the </p
Kamu Binalarında Su ve Enerji Verimliliği Analizi: Nevşehir Hacı Bektaş Veli Üniversitesi Diş Hekimliği Fakültesi ve Uygulama Hastanesi Örneği
No full textHow the history of pharmacy improves pharmaceutical science, education, and practice
No full textThe history of pharmacy is more than heritage; it offers usable methods that inform drug discovery, strengthen pharmacy education, and support trustworthy practice. Read with today’s tools, historical sources provide practical insight across the pharmacy spectrum—from community practice to industry, academia, and regulation—and for pharmacy students alike.</p
Modeling Earthquake Activities from 1915 to 2023 in Turkey Using Machine Learning Methods
No full textAccurately predicting seismic events is crucial for enhancing safety measures and informing strategic infrastructure development. By leveraging data from past earthquakes, we can effectively allocate resources to mitigate potential disaster impacts. Given Turkey's active fault lines and geological position, the region is highly vulnerable to earthquakes. This research aims to conduct a comprehensive analysis of earthquake activities in Turkey and develop models using machine learning algorithms that can predict earthquake intensity. Earthquake data from the Kandilli Observatory and Earthquake Research Institute for the years 1915–2023 have been analyzed using statistical and visualization techniques. The models evaluated in this study include KNN Model (K-Nearest Neighbors), Decision Tree Model, SVM Model (Support Vector Machine), Neural Network Regression (Deep Neural Network), Bagging Model, and AdaBoost Model. As a result of the analysis, the (Deep) Neural Network Regression model was found to provide good results with an accuracy of approximately 95%. These efforts will contribute to a better understanding of earthquake risks in Turkey and improve preparedness for future seismic events