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Issue 14, 2017
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A high throughput microfluidic platform for size-selective enrichment of cell populations in tissue and blood samples

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Abstract

Numerous applications in biology and medicine require the efficient and reliable separation of cells for disease diagnosis, genetic analysis, drug screening, and therapeutics. In this work, we demonstrate a novel technology that integrates a passive and an active device to separate, enrich and release cells on-demand from a complex blood sample, or cancer cells derived from a tissue biopsy. We exploit the high throughput (>1 mL min−1), size-based sorting capability of the passive spiral inertial microfluidic (iMF) device to focus particles/cells towards an active lateral cavity acoustic transducer (LCAT) device for size-selective enrichment. We demonstrate that this platform is capable of efficiently (>90%) removing smaller cells, such as RBCs in a blood sample or smaller cancer cells in a heterogeneous cell line, and providing 44 000× enrichment from the remaining sample within 5 min of device operation. Finally, we use this platform for two applications: selective enrichment of the side-population of DU-145 cells from tissue biopsy and isolation of larger monocytes from blood. Our platform integrates the high throughput (processing rate) capacity of spiral iMF with the high selectivity of LCAT, thereby offering a unique route for highly-selective, label-free particle/cell sorting, with potential application in lab-on-chip platforms for liquid biopsy and diagnostics applications.

Graphical abstract: A high throughput microfluidic platform for size-selective enrichment of cell populations in tissue and blood samples

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Publication details

The article was received on 18 Feb 2017, accepted on 14 May 2017 and first published on 21 Jun 2017


Article type: Paper
DOI: 10.1039/C7AN00290D
Citation: Analyst, 2017,142, 2558-2569
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    A high throughput microfluidic platform for size-selective enrichment of cell populations in tissue and blood samples

    N. Nivedita, N. Garg, A. P. Lee and I. Papautsky, Analyst, 2017, 142, 2558
    DOI: 10.1039/C7AN00290D

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