Rational design of a high-throughput droplet sorter

Schütz, Simon; Beneyton, Thomas; Baret, Jean‐Christophe; Schneider, Tobias

doi:10.1039/c9lc00149b

Cited by 29 publications

(18 citation statements)

References 38 publications

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“…At the same time, in the case of several biomedical applications, the fluorescence staining of cells can affect their behavior and thereby compromising their potential clinical implementation, therefore, it can be favorable if the cells get sorted in their native state. Based on the microfluidic design principles developed for fluorescence‐activated droplet sorting, [ 16,17 ] we set out to use the physical parameters obtained by the developed optical device for real‐time, label‐free droplet sorting. Toward this end, a combination of parameters including the SSD and the binarized size (yellow polygon in Figure 4B) was chosen to trigger the separation of cell‐laden droplets from empty droplets (Figure 5A).…”

Section: Resultsmentioning

confidence: 99%

“…Using a machine learning approach, the manual selection of the parameter space will be further facilitated and automated. With a potent and optimized microfluidic setup, [17,18] the maximum achievable analysis rate of 10 000 Hz roughly leads to a theoretical sorting capacity of >3000 droplets/s. In addition to identification of cellloaded droplets, a proper selection of analyzed parameters will enable classification of the cells inside the droplet, for example by their size, morphology, or stage.…”

Section: Discussionmentioning

confidence: 99%

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Label‐free monitoring and manipulation of microfluidic water‐in‐oil droplets

Frey

Pfeil

Neckernuß

et al. 2020

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Droplet-based microfluidic technology offers several benefits: the integration of multiple laboratory functions into a single microfabricated chip, manual intervention possibilities, minimal sample consumption, and increased analysis speed and data precision. These advantages have boosted the widespread application of this technology in biological and biomedical research. Despite recent progress, considerable challenges remain to be addressed for end-user applications. This especially concerns the difficulty of creating powerful and easy to implement methods for real-time analysis and active manipulation of passing droplets. Toward this end, we developed a very sensitive optical device equipped with smart algorithms for real-time label-free monitoring and active manipulation of passing droplets. We demonstrate the advanced properties of the developed optical device by measuring different droplet production parameters as well as the label-free detection of cells in droplets. Moreover, the newly developed technology was connected with a function generator system to allow for subsequent manipulation of the monitored droplets based on the measured parameters. As an example, we performed electric field-mediated, label-free sorting of cell-containing droplets from empty ones. Furthermore, we achieved an efficient size-based separation of droplets. We envision that the developed optical device will be a useful tool for the online monitoring of passing droplets and will be implemented for the integration and automation of various droplet-based microfluidic functional units. K E Y W O R D S active droplet manipulation, droplet-based microfluidics, high-throughput, label-free, realtime observation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Label‐free monitoring and manipulation of microfluidic water‐in‐oil droplets

Frey

Pfeil

Neckernuß

et al. 2020

VIEW

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“…Two separate channels loaded with a concentrated salt solution, and located adjacent to the sorting junction were responsible for inducing a dielectrophoretic force, required for sorting, on the droplet. 39,40 The sorting channel then led to a storage line having a high depth so that droplets decelerated and approximately 30 of the last sorted droplets could be stored in the sequence they were sorted ( Fig. 1A-4).…”

Section: A Monolithic Microfluidic Device For Droplet Generation MIXmentioning

confidence: 99%

Deep learning guided image-based droplet sorting for on-demand selection and analysis of single cells and 3D cell cultures

et al. 2020

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“…A maximum of only 20 min incubation was required, and spike‐in experiments (with a target cell:WBC ratio of as little as 10:200 000) showed that the detection rate was ≈60%. Given that there are many powerful droplet sorting platforms, one could also make use of these for collecting the acidified droplets for further analysis.…”

Section: Detecting Biomarkers For Cancer Diagnosis and Stratificationmentioning

confidence: 99%

Microfluidics as an Enabling Technology for Personalized Cancer Therapy

Mathur

Ballinger

Utharala

et al. 2019

Small

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Tailoring patient‐specific treatments for cancer is necessary in order to achieve optimal results but requires new diagnostic approaches at affordable prices. Microfluidics has immense potential to provide solutions for this, as it enables the processing of samples that are not available in large quantities (e.g., cells from patient biopsies), is cost efficient, provides a high level of automation, and allows the set‐up of complex models for cancer studies. In this review, individual solutions in the fields of genetics, circulating tumor cell monitoring, biomarker analysis, phenotypic drug sensitivity tests, and systems providing controlled environments for disease modeling are discussed. An overview on how these early stage achievements can be combined or developed further is showcased, and the required translational steps before microfluidics becomes a routine tool for clinical applications are critically discussed.

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Rational design of a high-throughput droplet sorter

Abstract: The high-throughput selection of individual droplets is an essential function in droplet-based microfluidics.

Cited by 29 publications

References 38 publications

Label‐free monitoring and manipulation of microfluidic water‐in‐oil droplets

Label‐free monitoring and manipulation of microfluidic water‐in‐oil droplets

Deep learning guided image-based droplet sorting for on-demand selection and analysis of single cells and 3D cell cultures

Microfluidics as an Enabling Technology for Personalized Cancer Therapy

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