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Open-source tool for real-time and automated analysis of droplet-based microfluidic.
- Source :
-
Lab on a Chip . 7/21/2023, Vol. 23 Issue 14, p3238-3244. 7p. - Publication Year :
- 2023
-
Abstract
- Droplet-based microfluidic technology is a powerful tool for generating large numbers of monodispersed nanoliter-sized droplets for ultra-high throughput screening of molecules or single cells. Yet further progress in the development of methods for the real-time detection and measurement of passing droplets is needed for achieving fully automated systems and ultimately scalability. Existing droplet monitoring technologies are either difficult to implement by non-experts or require complex experimentation setups. Moreover, commercially available monitoring equipment is expensive and therefore limited to a few laboratories worldwide. In this work, we validated for the first time an easy-to-use, open-source Bonsai visual programming language to accurately measure in real-time droplets generated in a microfluidic device. With this method, droplets are found and characterized from bright-field images with high processing speed. We used off-the-shelf components to achieve an optical system that allows sensitive image-based, label-free, and cost-effective monitoring. As a test of its use we present the results, in terms of droplet radius, circulation speed and production frequency, of our method and compared its performance with that of the widely-used ImageJ software. Moreover, we show that similar results are obtained regardless of the degree of expertise. Finally, our goal is to provide a robust, simple to integrate, and user-friendly tool for monitoring droplets, capable of helping researchers to get started in the laboratory immediately, even without programming experience, enabling analysis and reporting of droplet data in real-time and closed-loop experiments. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14730197
- Volume :
- 23
- Issue :
- 14
- Database :
- Academic Search Index
- Journal :
- Lab on a Chip
- Publication Type :
- Academic Journal
- Accession number :
- 164879391
- Full Text :
- https://doi.org/10.1039/d3lc00327b