Evidence map›Paper›PMID 24339850›Full record

ArticleBiomicrofluidics2012

Selective cell capture and analysis using shallow antibody-coated microchannels.

Kihoon Jang, Yo Tanaka, Jun Wakabayashi, Reina Ishii, Kae Sato, Kazuma Mawatari, Mats Nilsson, Takehiko Kitamori

Open access · bronzeAbstract read
In one paragraph

Article in Biomicrofluidics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 9 citations in OpenAlex.

  1. Advances in microfluidic cell separation and manipulation.Current opinion in chemical engineering · 2013
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Kihoon JangDepartment of Applied Chemistry, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8656, Japan.
Yo Tanaka
Jun Wakabayashi
Reina Ishii
Kae Sato
Kazuma Mawatari
Mats Nilsson
Takehiko Kitamori
The University of Tokyo · JPJapan Women's University · JPKobe Asahi Hospital · JPUppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Demand for analysis of rare cells such as circulating tumor cells in blood at the single molecule level has recently grown. For this purpose, several cell separation methods based on antibody-coated micropillars have been developed (e.g., Nagrath et al., Nature 450, 1235-1239 (2007)). However, it is difficult to ensure capture of targeted cells by these methods because capture depends on the probability of cell-micropillar collisions. We developed a new structure that actively exploits cellular flexibility for more efficient capture of a small number of cells in a target area. The depth of the sandwiching channel was slightly smaller than the diameter of the cells to ensure contact with the channel wall. For cell selection, we used anti-epithelial cell adhesion molecule antibodies, which specifically bind epithelial cells. First, we demonstrated cell capture with human promyelocytic leukemia (HL-60) cells, which are relatively homogeneous in size; in situ single molecule analysis was verified by our rolling circle amplification (RCA) method. Then, we used breast cancer cells (SK-BR-3) in blood, and demonstrated selective capture and cancer marker (HER2) detection by RCA. Cell capture by antibody-coated microchannels was greater than with negative control cells (RPMI-1788 lymphocytes) and non-coated microchannels. This system can be used to analyze small numbers of target cells in large quantities of mixed samples.

Identifiers

PMID24339850
PMCPMC3555508
OpenAlexW2083908155

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.