Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 35Citation - Scopus: 44Current Trends and Challenges in Point-Of Urinalysis of Biomarkers in Trace Amounts(Elsevier, 2022) Yeasmin, Sanjida; Ammanath, Gopal; Yıldız, Ümit Hakan; Yan, Evelias; Yıldız, Ümit Hakan; Palaniappan, Alagappan; Liedberg, Bo; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyUrinalysis enables non-invasive point-of-care (POC) testing of numerous biomarkers at their physiological and elevated levels, obviating the need for sophisticated equipment or trained personnel. POC urinalysis is used to identify biomarkers that are rich in urine (greater than 1 μM), such as lactate, uric acid, glucose, ions, and adenosine. Urine also contains biomarkers such as small molecules, nucleic acids, neurotransmitters, and drugs in trace amounts (less than 1 μM). These biomarkers are of significant importance for health care monitoring, diagnosis of various disorders (cancer, metabolic diseases, etc.) and illicit drug control (cocaine, steroids, etc.). While POC detection of urinary biomarkers at higher concentration (μM to mM) levels is feasible, direct assaying of biomarkers in nM to fM levels is challenging, as assay responses are typically masked by interferences from the urine sample matrix. This report is a consolidated review of emerging trends and challenges in the POC urinalysis for detecting biomarkers that are less abundant in urine. The sensing mechanisms, analytical device fabrication, discrete and integrated sample pre-treatment procedures for POC assaying of urinary markers in trace amounts are elaborated. Subsequently, the utilization of smart data analytics for facilitating personalized urinalysis is presented. A comprehensive outlook on associated challenges in POC urinalysis of biomarkers in trace amounts is further provided, which would facilitate the advancement of POC urinalysis for a wide range of healthcare applications.Conference Object Citation - Scopus: 2Label-Free Detection of Rare Cancer Cells Using Deep Learning and Magnetic Levitation Principle(SPIE, 2021) Delikoyun, Kerem; Tekin, Hüseyin Cumhur; Demir, Ali Aslan; Delikoyun, Kerem; Tekin, Hüseyin Cumhur; 03.01. Department of Bioengineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyMagnetic levitation is an effective tool for separating target cells within a heterogeneous solution by utilizing density differences among cell lines. However, magnetic levitation cannot be used to identify target cells which have similar density profile as the other cells in the solution. Therefore, accuracy of cell identification can dramatically reduce. In this study, we introduce, for the first time, the use of deep learning-based object detection approach for label-free identification of rare cancer cells within levitated cells. As a result, our novel and hybrid detection strategy could be used to identify circulating tumor cells for diagnosis and prognosis of cancer. © 2021 SPIE.Conference Object Citation - Scopus: 2Magnetic Levitation-Based Protein Detection Using Lensless Digital Inline Holographic Microscopy(The Chemical and Biological Microsystems Society (CBMS), 2019) Yaman, Sena; Tekin, Hüseyin Cumhur; Delikoyun, Kerem; Delikoyun, Kerem; Tekin, Hüseyin Cumhur; Yaman, Sena; 03.01. Department of Bioengineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyWe present a portable protein detection platform based on magnetic levitation principle integrated with a lensless imaging system. In the platform, polymer microspheres are used to capture selectively target proteins and magnetic nanoparticle labels. The imaging system monitors the levitation height change of polymer microspheres with respect to the presence of target protein on their surfaces. This system enables the detection of target proteins down to ng/mL levels in a short time. © 2019 CBMS-0001.