Bioengineering / Biyomühendislik

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

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Author: search.filters.author.Tarım, Ergün AlperayScopus Q: search.filters.scopusQuartile.Q2

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  • Review
    Citation - WoS: 23
    Citation - Scopus: 24
    Microfluidic-Based Technologies for Diagnosis, Prevention, and Treatment of Covid-19: Recent Advances and Future Directions
    (Springer, 2023) Tarım, Ergün Alperay; Anıl İnevi, Müge; Özkan, İlayda; Keçili, Seren; Bilgi, Eyüp; Başlar, Muhammet Semih; Özçivici, Engin; Öksel Karakuş, Ceyda; Tekin, Hüseyin Cumhur
    The COVID-19 pandemic has posed significant challenges to existing healthcare systems around the world. The urgent need for the development of diagnostic and therapeutic strategies for COVID-19 has boomed the demand for new technologies that can improve current healthcare approaches, moving towards more advanced, digitalized, personalized, and patient-oriented systems. Microfluidic-based technologies involve the miniaturization of large-scale devices and laboratory-based procedures, enabling complex chemical and biological operations that are conventionally performed at the macro-scale to be carried out on the microscale or less. The advantages microfluidic systems offer such as rapid, low-cost, accurate, and on-site solutions make these tools extremely useful and effective in the fight against COVID-19. In particular, microfluidic-assisted systems are of great interest in different COVID-19-related domains, varying from direct and indirect detection of COVID-19 infections to drug and vaccine discovery and their targeted delivery. Here, we review recent advances in the use of microfluidic platforms to diagnose, treat or prevent COVID-19. We start by summarizing recent microfluidic-based diagnostic solutions applicable to COVID-19. We then highlight the key roles microfluidics play in developing COVID-19 vaccines and testing how vaccine candidates perform, with a focus on RNA-delivery technologies and nano-carriers. Next, microfluidic-based efforts devoted to assessing the efficacy of potential COVID-19 drugs, either repurposed or new, and their targeted delivery to infected sites are summarized. We conclude by providing future perspectives and research directions that are critical to effectively prevent or respond to future pandemics.
  • 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.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 10
    Performance Evaluation of Webrtc-Based Online Consultation Platform
    (Türkiye Klinikleri Journal of Medical Sciences, 2019) Tarım, Ergün Alperay; Tekin, Hüseyin Cumhur
    Information technologies give patients the opportunity to communicate with medical professionals remotely. Telemedicine uses these technologies to provide advanced healthcare and medical services. We present a medical online consultation application based on Web Real-Time Communications (WebRTC) technology enabling chat, audio, and video calls. Communication architecture and protocols of the application are explained in detail. Additionally, the user interface of the application is shown via performed calls. The application is tested and evaluated on different network connections (3G, 4G, local, and DSL) and different browsers and mobile operating systems (Android, Chrome, Firefox, Internet Explorer, iOS, Opera, Safari). During calls, communication quality parameters such as round-trip time (RTT) and packet loss, obtained via the WebRTC application programming interface, are analyzed. 3G, 4G, and local connections show low packet losses (<1%). Packet losses are high (>1%) in Android, Chrome, iOS, Opera, and Safari for DSL connection, but RTT values are low (<100 ms) in all different conditions excluding iOS. In the presented application, RTT and packet loss remain lower than 100 ms and 1%, respectively, in various scenarios, indicating good communication quality. RTT and packet loss are related to total time and hang time parameters, which describe the necessary time to establish and to end a call. It is shown that communication quality of the application can simply be measured by analyzing the total time parameter. This enables predictable information for communication quality for WebRTC-based applications without continuously monitoring RTT and packet loss for the first time.