Bioengineering / Biyomühendislik

Permanent URI for this collectionhttps://hdl.handle.net/11147/4529

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  • Article
    Citation - Scopus: 3
    Development of Chrono-Spectral Gold Nanoparticle Growth Based Plasmonic Biosensor Platform
    (Elsevier, 2024) Sözmen, Alper Baran; Elveren, Beste; Erdoğan, Duygu; Mezgil, Bahadır; Baştanlar, Yalın; Yıldız, Ümit Hakan; Arslan Yıldız, Ahu
    Plasmonic sensor platforms are designed for rapid, label-free, and real-time detection and they excel as the next generation biosensors. However, current methods such as Surface Plasmon Resonance require expertise and well-equipped laboratory facilities. Simpler methods such as Localized Surface Plasmon Resonance (LSPR) overcome those limitations, though they lack sensitivity. Hence, sensitivity enhancement plays a crucial role in the future of plasmonic sensor platforms. Herein, a refractive index (RI) sensitivity enhancement methodology is reported utilizing growth of gold nanoparticles (GNPs) on solid support and it is backed up with artificial neural network (ANN) analysis. Sensor platform fabrication was initiated with GNP immobilization onto solid support; immobilized GNPs were then used as seeds for chrono-spectral growth, which was carried out using NH2OH at varied incubation times. The response to RI change of the platform was investigated with varied concentrations of sucrose and ethanol. The detection of bacteria E.coli BL21 was carried out for validation as a model microorganism and results showed that detection was possible at 102 CFU/ml. The data acquired by spectrophotometric measurements were analyzed by ANN and bacteria classification with percentage error rates near 0% was achieved. The proposed LSPR-based, label-free sensor application proved that the developed methodology promises utile sensitivity enhancement potential for similar sensor platforms. © 2024 The Author(s)
  • Conference Object
    Lots and Loop-Mediated Isothermal Amplification-Based Biosensing Using Cloud-Enabled Features
    (IEEE, 2022) Bayındır, Taha; Değirmenci, Mehmet; Ergenç, Ali Fuat; Elitaş, Meltem
    Internet-of-Things technology (IoTs) have accelerated biosensor applications in all fields. Loop-mediated isothermal amplification (LAMP)-based biosensor technologies in conjunction with smartphone detection have been adequate to cover the demands of mobile diagnostics. The ease of use, affordability, portability, high sensitivity, flexibility, and specificity demands of point-of-care detection can be achieved by low-cost electronic components, 3-dimensional printing technologies, capturing images of calorimetrically detected readouts made our system a promising approach for real-time point-of-detection in the field. In this study, we implemented a cloud service to our LAMP-based biosensor. We previously performed bacteria detection using colony-based LAMP device and now distributed the optical readouts of the assay using smartphones. We transferred the obtained image and results of the assays through cloud. Our user-friendly interface simplifies the data processing, it directly digitized the readouts and eliminates the need of data interpretation.
  • Article
    Citation - WoS: 37
    Citation - Scopus: 48
    Microfluidic-Based Virus Detection Methods for Respiratory Diseases
    (Springernature, 2021) Tarım, Ergün Alperay; Karakuzu, Betül; Öksüz, Cemre; Sarıgil, Öykü; Kızılkaya, Melike; Al-Ruweidi, Mahmoud Khatib A. A.; Yalçın, Hüseyin Çağatay; Özçivici, Engin; Tekin, Hüseyin Cumhur
    With the recent SARS-CoV-2 outbreak, the importance of rapid and direct detection of respiratory disease viruses has been well recognized. The detection of these viruses with novel technologies is vital in timely prevention and treatment strategies for epidemics and pandemics. Respiratory viruses can be detected from saliva, swab samples, nasal fluid, and blood, and collected samples can be analyzed by various techniques. Conventional methods for virus detection are based on techniques relying on cell culture, antigen-antibody interactions, and nucleic acids. However, these methods require trained personnel as well as expensive equipment. Microfluidic technologies, on the other hand, are one of the most accurate and specific methods to directly detect respiratory tract viruses. During viral infections, the production of detectable amounts of relevant antibodies takes a few days to weeks, hampering the aim of prevention. Alternatively, nucleic acid-based methods can directly detect the virus-specific RNA or DNA region, even before the immune response. There are numerous methods to detect respiratory viruses, but direct detection techniques have higher specificity and sensitivity than other techniques. This review aims to summarize the methods and technologies developed for microfluidic-based direct detection of viruses that cause respiratory infection using different detection techniques. Microfluidics enables the use of minimal sample volumes and thereby leading to a time, cost, and labor effective operation. Microfluidic-based detection technologies provide affordable, portable, rapid, and sensitive analysis of intact virus or virus genetic material, which is very important in pandemic and epidemic events to control outbreaks with an effective diagnosis.