Evidence map›Paper›PMID 28723132›Full record

ArticleACS sensors2017

Single-Cell Mechanical Characteristics Analyzed by Multiconstriction Microfluidic Channels.

Xiang Ren, Parham Ghassemi, Hesam Babahosseini, Jeannine S Strobl, Masoud Agah

Abstract read
In one paragraph

Article in ACS sensors, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
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

18 citing papers in PubMed.

  1. Article
  2. Immune organoid for cancer immunotherapy.Acta pharmaceutica Sinica. B · 2025
    Review
  3. Article
  4. Review
  5. Measuring cell deformation by microfluidics.Frontiers in bioengineering and biotechnology · 2023
    Review
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  7. Article
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  9. Article
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  12. Article
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  15. Article
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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

5 authors.

Xiang RenThe Bradley Department of Electrical and Computer Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States.ORCID http://orcid.org/0000-0002-8882-6362
Parham GhassemiThe Bradley Department of Electrical and Computer Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States.
Hesam BabahosseiniThe Bradley Department of Electrical and Computer Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States.
Jeannine S StroblThe Bradley Department of Electrical and Computer Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States.
Masoud AgahThe Bradley Department of Electrical and Computer Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States.

Funding

High Throughput Mechanical Modulatory Assay for Breast Cancer Drug TestingR21CA210126 · NCI · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI AGAH, MASOUD · 2016 to 2017
$395k
NCI NIH HHS R21 CA210126
6 · The paper itself

Abstract

A microfluidic device composed of variable numbers of multiconstriction channels is reported in this paper to differentiate a human breast cancer cell line, MDA-MB-231, and a nontumorigenic human breast cell line, MCF-10A. Differences between their mechanical properties were assessed by comparing the effect of single or multiple relaxations on their velocity profiles which is a novel measure of their deformation ability. Videos of the cells were recorded via a microscope using a smartphone, and imported to a tracking software to gain the position information on the cells. Our results indicated that a multiconstriction channel design with five deformation (50 μm in length, 10 μm in width, and 8 μm in height) separated by four relaxation (50 μm in length, 40 μm in width, and 30 μm in height) regions was superior to a single deformation design in differentiating MDA-MB-231 and MCF-10A cells. Velocity profile criteria can achieve a differentiation accuracy around 95% for both MDA-MB-231 and MCF-10A cells.

Indexed as

breast cancer cellsmicrofluidic cell separationmulticonstriction channelparticle trackingsmartphone imagingvelocity profilesvideo/image processing

Identifiers

PMID28723132
PMCPMC5533582

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Registered trials

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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.