Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 368

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Sheathless inertial cell ordering for extreme throughput flow cytometry

Hur, Soojung Claire, Tse, Henry Tat Kwong, Di Carlo, Dino·2010·Lab Chip

Abstract

Rapid and accurate differentiation of cell types within a heterogeneous solution is a challenging but important task for various applications in biological research and medicine. Flow cytometry is the gold standard in cell analysis and is regularly used for blood analysis (i.e., complete blood counts). Flow cytometry, however, lacks sufficient throughput to analyze rare cells in blood or other dilute solutions in a reasonable time period because it is an inherently serial process. In this study, we exploit inertial effects for label- and sheath-free parallel flow cytometry with extreme throughput. We demonstrate a microfluidic device that consists of 256 high-aspect (W = 16 microm, H = 37 microm) parallel channels yielding a sample rate up to 1 million cells s(-1), only limited by the field-of-view of our high-speed optical interrogation method. The particles or cells flowing through the channels are focused to one uniform z-position (SD = +/-1.81 microm) with uniform downstream velocity (U(ave) = 0.208 +/- 0.004 m s(-1)) to reduce the probability of overlap and out-of-focus blur and provide similar cell signature images for accurate detection and analysis. To demonstrate a proof-of-concept application of our system operating at these throughputs, we conducted automated RBC and leukocyte counts on diluted whole blood and achieved high counting sensitivity and specificity (86-97%) compared to visual inspection of raw images. As no additional external forces are required to create ordered streams of cells, this approach has the potential for future applications in cost-effective hematology or rare-cell analysis platforms with extreme throughput capabilities when integrated with suitable large field-of view imaging or interrogation methods.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1039/b919495a

Cites

16 of 16 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 16 references

Cited by

See all 368

Metadata

Authors
Hur, S. C., Tse, H. T. K., & Di Carlo, D.
Venue
Lab Chip
Published
2010
Volume
10
Issue
3
Pages
274-280
ISSN
  • 1473-0189 (ISSN-L)
  • 1473-0197
OpenAlex
W2086798403
Cited by
368
References
16
FWCI
14.56
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Sheathless inertial cell ordering for extreme throughput flow cytometry. https://app.cochat.ai/papers/10.1039/b919495a
The paper
Hur, S. C., Tse, H. T. K., & Di Carlo, D. (2010). Sheathless inertial cell ordering for extreme throughput flow cytometry. Lab Chip. https://doi.org/10.1039/b919495a

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.