Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Advances in Optical Biosensors: Technologies and Trends in Point of Care Applications(Academic Press Inc., 2025) Sözmen, A.B.; Bayraktar, A.E.; Ülker, Ö.; Arslan-Yildiz, A.A sensor detects changes in its environment and converts them into readable data using three key components: a receptor to sense changes, a transducer to generate a signal, and a detection system to output the signal. Optical sensors are devices that use a receptor and optical transducer to produce signals corresponding to an analyte, and optical biosensors combine a biological sensing element with an optical transducer to detect and quantify specific analytes. They offer easy-to-read, real-time signals, such as color changes or light emission, sometimes even detectable by the naked eye, reducing the need for external devices and providing versatile Point-of-Care (PoC) applicability. Their portability and rapid response time enable remote testing and monitoring, further improving accessibility. They allow sensitive and selective detection of various analytes, making them utile in areas like glucose monitoring, drug testing, and pathogen detection. Many of these sensors provide label-free and non-invasive detection, further enhancing patient comfort and safety. This chapter provides an overview of optical biosensors; it starts with categorizing them by biorecognition elements, transducers, and detection modes. It investigates biosensors that utilize nanomaterials, polymers, and engineered biorecognition elements are discussed, with examples from literature. Technologies such as miniaturization, multiplexing, and wearable designs, which enhance PoC feasibility, are also examined. Lastly, challenges in development and operation are addressed, and future research directions for advancing optical biosensors in PoC diagnostics are discussed. © 2025Article Citation - Scopus: 1Recent Advances in Hydrogel-Based 3D Disease Modeling and Drug Screening Platforms(2025) Bilginer-Kartal, R.; Çoban, B.; Yildirim-Semerci, Ö.; Arslan-Yildiz, A.Three-dimensional (3D) disease modeling and drug screening systems have become important in tissue engineering, drug screening, and development. The newly developed systems support cell and extracellular matrix (ECM) interactions, which are necessary for the formation of the tissue or an accurate model of a disease. Hydrogels are favorable biomaterials due to their properties: biocompatibility, high swelling capacity, tunable viscosity, mechanical properties, and their ability to biomimic the structure and function of ECM. They have been used to model various diseases such as tumors, cancer diseases, neurodegenerative diseases, cardiac diseases, and cardiovascular diseases. Additive manufacturing approaches, such as 3D printing/bioprinting, stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM), enable the design of scaffolds with high precision; thus, increasing the accuracy of the disease models. In addition, the aforementioned methodologies improve the design of the hydrogel-based scaffolds, which resemble the complicated structure and intricate microenvironment of tissues or tumors, further advancing the development of therapeutic agents and strategies. Thus, 3D hydrogel-based disease models fabricated through additive manufacturing approaches provide an enhanced 3D microenvironment that empowers personalized medicine toward targeted therapeutics, in accordance with 3D drug screening platforms. © 2025. The Author(s), under exclusive license to Springer Nature Switzerland AG.Article Citation - WoS: 1Citation - Scopus: 1Protein Quantification Via Lspr-Based Biosensor Platform Utilizing Chrono-Growth for Enhanced Sensitivity(Elsevier, 2024) Sozmen, A. B.; Arslan-Yildiz, A.In this study an enhancement methodology, which utilizes time dependent growth of immobilized gold nanoparticles (GNPs) for LSPR-based biosensor platform was developed. The chrono-growth methodology was used for protein analysis and quantification. The method consisted GNP immobilization onto well-plates, GNP chronogrowth, and antibody functionalization. Success of each step was verified by UV-Vis spectrum measurement. Afterwards, the biosensor platform was tested to determine its characteristics. Bovine Serum Albumin (BSA) was chosen to be used as a model protein and an LoD value of 0.344 mu M and a dynamic detection range of 1 to 1000 mu M was calculated. The results were acquired within 30 min. Developed platform provides simple and rapid detection of the protein.