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High Throughput Single-cell and Multiple-cell Micro-encapsulation
Published on: June 15, 2012
Sheathless inertial cell ordering for extreme throughput flow cytometry.
Soojung Claire Hur1, Henry Tat Kwong Tse, Dino Di Carlo
1Mechanical and Aerospace Engineering Department, University of California, Los Angeles, CA 90095, USA.
Lab on a Chip
|January 22, 2010
Summary
This study introduces a novel microfluidic device for high-throughput, label-free cell analysis. The system uses parallel channels to achieve extreme speeds for accurate cell counting in biological samples.
Area of Science:
- Biomedical Engineering
- Microfluidics
- Cellular Analysis
Background:
- Accurate cell type differentiation is crucial for research and medicine.
- Flow cytometry is standard for cell analysis but limited by low throughput for rare cells.
- Existing methods struggle with analyzing rare cells in dilute solutions efficiently.
Purpose of the Study:
- To develop a label- and sheath-free parallel flow cytometry system with extreme throughput.
- To overcome the throughput limitations of traditional flow cytometry for rare cell analysis.
- To demonstrate a proof-of-concept for automated blood cell counting at high speeds.
Main Methods:
- Utilized inertial effects within a microfluidic device containing 256 parallel channels.
- Achieved particle/cell focusing to a uniform z-position and downstream velocity.
- Employed high-speed optical interrogation for parallel cell analysis.
Main Results:
- Demonstrated a sample rate up to 1 million cells per second.
- Achieved precise cell focusing (SD = +/-1.81 microm) and uniform velocity (U(ave) = 0.208 +/- 0.004 m s(-1)).
- Obtained high counting sensitivity and specificity (86-97%) for RBC and leukocyte counts in diluted whole blood.
Conclusions:
- The developed microfluidic device enables label- and sheath-free parallel flow cytometry at extreme throughputs.
- This approach significantly enhances speed for cell analysis compared to conventional methods.
- Potential for cost-effective hematology and rare-cell analysis platforms with integrated imaging.

