Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 293

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Double spiral microchannel for label-free tumor cell separation and enrichment

Sun, Jiashu, Li, Mengmeng, Liu, Chao, Zhang, Yi, Liu, Dingbin, Liu, Wenwen, Hu, Guoqing, Jiang, Xingyu·2012·Lab on a Chip

Abstract

This work reports on a passive double spiral microfluidic device allowing rapid and label-free tumor cell separation and enrichment from diluted peripheral whole blood, by exploiting the size-dependent hydrodynamic forces. A numerical model is developed to simulate the Dean flow inside the curved geometry and to track the particle/cell trajectories, which is validated against the experimental observations and serves as a theoretical foundation for optimizing the operating conditions. Results from separating tumor cells (MCF-7 and Hela) spiked into whole blood indicate that 92.28% of blood cells and 96.77% of tumor cells are collected at the inner and the middle outlet, respectively, with 88.5% tumor recovery rate at a throughput of 3.33 × 10(7) cells min(-1). We expect that this label-free microfluidic platform, driven by purely hydrodynamic forces, would have an impact on fundamental and clinical studies of circulating tumor cells.

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/c2lc40679a

Cites

1 of 1 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 1 references

Cited by

See all 293

Metadata

Authors
Sun, J., Li, M., Liu, C., Zhang, Y., Liu, D., Liu, W., Hu, G., & Jiang, X.
Venue
Lab on a Chip
Published
2012
Volume
12
Issue
20
Pages
3952
ISSN
  • 1473-0189 (ISSN-L)
  • 1473-0197
OpenAlex
W2030593367
Cited by
293
References
1
FWCI
12.56
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: Double spiral microchannel for label-free tumor cell separation and enrichment. https://app.cochat.ai/papers/10.1039/c2lc40679a
The paper
Sun, J., Li, M., Liu, C., Zhang, Y., Liu, D., Liu, W., Hu, G., & Jiang, X. (2012). Double spiral microchannel for label-free tumor cell separation and enrichment. Lab on a Chip. https://doi.org/10.1039/c2lc40679a

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.