Bioengineering / Biyomühendislik
Permanent URI for this collectionhttps://hdl.handle.net/11147/4529
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Conference Object Electromechanical Lab-On Platform for Creatinine Analysis Using Automated Elisa Protocols(Chemical and Biological Microsystems Society, 2020) Karakuzu, Betül; Tarım, Ergün Alperay; Öksüz, Cemre; Tekin, Hüseyin CumhurWe present an electromechanical lab-on-a-chip (LOC) platform for the automated serum creatinine detection applying enzyme-linked immunosorbent assay (ELISA) principle. In the platform, antibody covered bar selectively captures the creatinine in the sample and the electromechanical system allows automatic movement between the designed reservoirs containing assay solutions. At the end of the protocol, the absorbance value of the appeared color is measured to determine creatinine concentration in the sample. Since this system allows measuring automatically creatinine levels with minimum time and cost, it can be utilized for point-of-care monitoring of chronic kidney diseases (CKD) for the future. © 2020 CBMS-0001Conference Object Citation - WoS: 3Citation - Scopus: 3Active Mixing Strategy With Electromechanical Platform for Lab-On Applications(Institute of Electrical and Electronics Engineers Inc., 2019) Karakuzu, Betül; Özçivici, Engin; Tekin, Hüseyin Cumhur; Tarım, E. AlperayThe main purpose of this study is to present a new active mixing strategy that can be used for lab-on-A-chip applications to shorten analysis time. An electromechanical platform composed of stepper and DC motors is designed and manufactured. This platform allows rapid mixing in microwells of a polydimethylsiloxane chip for analysis. Mixing in microwells is performed with a stirring bar spun automatically using the electromechanical platform. Mixing experiments performed at different spinning speeds and different time intervals on the platform. It was observed that mixing was achieved only in 300 ms inside 100 ?L microwell using 4300 revolutions per minute (rpm) spinning speeds. Hence, the proposed mixing strategy showed 200-fold faster mixing than pure diffusion-based mixing. © 2019 IEEE.
