Evidence map›Paper›PMID 29414993›Full record

ArticlePloS one2018

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

Jenny Jeong, Nicholas J Frohberg, Enlu Zhou, Todd Sulchek, Peng Qiu

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Tutorial on compressed ultrafast photography.Journal of biomedical optics · 2024
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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.

Jenny JeongDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.
Nicholas J FrohbergDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.
Enlu ZhouSchool of Industrial and System Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Todd SulchekSchool of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Peng QiuDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.ORCID 0000-0003-3256-0734

Funding

Identifying the cellular hierarchy and drug response of AML using cytometric dataR01CA163481 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI QIU, PENG · 2012 to 2015
$1.1M
NCI NIH HHS R01 CA163481NIH HHS R01 CA163481
6 · The paper itself

Abstract

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Indexed as

Lab-On-A-Chip DevicesSingle-Cell AnalysisAlgorithmsCell SeparationHumans

Identifiers

PMID29414993
PMCPMC5802930

What OpenQuestion holds

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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.