Among the advantages of an electrowetting-on-dielectric (EWOD) chip are its uncomplicated fabrication and low cost; one of its greatest strengths that might be applied in the field of biomedical technology is that it can accurately control volume and reduces the amount of samples and reagents. We present an EWOD for the biochemical identification of microorganisms, which is required to confirm the source of microbial contamination or quality inspection of product-added bacteria, etc. The traditional kit we used existed in the market; the detection results are judged by the pattern of color change after incubation. After a preliminary study, we confirmed that an image-processing tool (ImageJ) provides a suitable method of analysis, and that, when the concentration of the sugar reagent is 38 µg/µL, the best operating parameters for the EWOD chip in silicone oil are 40 V and 1.5 kHz. Additionally, we completed the biochemical identification of five bacterial species on the EWOD chip at the required concentration of the kit. Next, we found a decreased duration of reaction and that the least number of bacteria that were identifiable on the chip lies between 100 and 1000 CFU per droplet. Because the number of bacteria required on the chip is much smaller than for the kit, we tested whether a single colony can be used for identification, which provided a positive result. Finally, we designed an experimental flow to simulate an actual sample in an unclean environment, in which we divided the various processed samples into four groups to conduct experiments on the chip.
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http://dx.doi.org/10.3390/mi13020189 | DOI Listing |
Lab Chip
December 2024
Department of Nanoscience and Engineering, Center for Nano Manufacturing, Inje University, Gimhae, 50834, Republic of Korea.
Droplets are essential in a wide range of microfluidic applications, but traditional passive droplet generation methods suffer from slow response speed and the need for precise flow rate adjustment. Here, we present an active droplet generation method through electrowetting-on-dielectric (EWOD). Electrowetting is a technique that uses an electric field to change the wettability of a surface.
View Article and Find Full Text PDFLab Chip
December 2024
Microsystems, Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.
Using sweat instead of blood for monitoring chemical biomarker concentrations of hospitalised patients offers several advantages for both the patients and healthcare workers. Unlike blood, sweat can be noninvasively and continuously sampled without direct involvement of a professional, and sweat contains a rich composition of biomarkers. However, patients in resting state have extremely low sweat rates and they produce correspondingly small sweat volumes, which makes sweat sensing of hospitalised patients highly challenging.
View Article and Find Full Text PDFTalanta
January 2025
DTU Bioengineering, Technical University of Denmark, Kongens Lyngby, Denmark. Electronic address:
Soft Matter
October 2024
NanoEngineering Group, Department of Mechanical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel.
Electrowetting on dielectric (EWOD) involves actuating droplets through electrical stimulus while the droplets lie on a dielectric layer that covers the electrode. In order to activate the droplet, a higher threshold voltage is required due to electrowetting hysteresis. The effect of a deformable dielectric layer and its thickness on electrowetting hysteresis has not been studied.
View Article and Find Full Text PDFMicrosyst Nanoeng
September 2024
CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu Province, 215163, PR China.
An active-matrix electrowetting-on-dielectric (AM-EWOD) system integrates hundreds of thousands of active electrodes for sample droplet manipulation, which can enable simultaneous, automatic, and parallel on-chip biochemical reactions. A smart detection system is essential for ensuring a fully automatic workflow and online programming for the subsequent experimental steps. In this work, we demonstrated an artificial intelligence (AI)-enabled multipurpose smart detection method in an AM-EWOD system for different tasks.
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