Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Tekin, H. CumhurInstitution Author: search.filters.institutionAuthor.…

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  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Investigating Influences of Intravenous Fluids on Huvec and U937 Monocyte Cell Lines Using the Magnetic Levitation Method
    (ROYAL SOC CHEMISTRY, 2023) Keçili, Seren; Kaymaz, Sumeyra Vural; Özoğul, Beyzanur; Tekin, H. Cumhur; Elitaş, Meltem
    Intravenous fluids are being widely used in patients of all ages for preventing or treating dehydration in the intensive care units, surgeries in the operation rooms, or administering chemotherapeutic drugs at hospitals. Dextrose, Ringer, and NaCl solutions are widely received as intravenous fluids by hospitalized patients. Despite their widespread administration for over 100 years, studies on their influences on different cell types have been very limited. Increasing evidence suggests that treatment outcomes might be altered by the choice of the administered intravenous fluids. In this study, we investigated the influences of intravenous fluids on human endothelial (HUVEC) and monocyte (U937) cell lines using the magnetic levitation technique. Our magnetic levitation platform provides label-free manipulation of single cells without altering their phenotypic or genetic properties. It allows for monitoring and quantifying behavior of single cells by measuring their levitation heights, deformation indices, and areas. Our results indicate that HUVEC and U937 cell lines respond differently to different intravenous fluids. Dextrose solution decreased the viability of both cell lines while increasing the heterogeneity of areas, deformation, and levitation heights of HUVEC cells. We strongly believe that improved outcomes can be achieved when the influences of intravenous fluids on different cell types are revealed using robust, label-free, and efficient methods. Label-free analysis of cells exposed to intravenous fluids can be achieved through magnetic levitation technology coupled with cell-morphology characterization.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 12
    A Wearable Device Integrated With Deep Learning-Based Algorithms for the Analysis of Breath Patterns
    (Wiley, 2023) Tarım, Ergün Alperay; Erimez, Büşra; Değirmenci, Mehmet; Tekin, H. Cumhur
    Sleep problems are serious issues that make life difficult for all people, including sleep apnea. Sleep apnea, which causes breathlessness for more than 10 s, is linked to severe health problems due to the serious damage it can induce. To mitigate the risk of these disorders, the monitoring of patients has become increasingly challenging. Wearable technologies offer an effective healthcare solution for remote patient monitoring and diagnosis. A novel wearable system based on Arduino technology is introduced, specifically designed to monitor the breath patterns of patients. The analysis of breath data from patients holds great importance for the diagnosis and continuous monitoring of sleep apnea. To address this need, an advanced image processing system based on deep learning techniques is presented. This system automatically detects respiratory patterns, including inhalation, exhalation, and breathlessness. The device has an average of 97.6% sensitivity, 79.7% specificity, and 96% accuracy in identifying breath patterns. The designed device can offer patients and healthcare institutions a simple, inexpensive, noninvasive, and ergonomic system for the analysis of breath patterns that can be further extended for sleep apnea diagnosis.