Evidence map›Paper›PMID 29931016›Full record

ArticleLab on a chip2018

An acoustofluidic trap and transfer approach for organizing a high density single cell array.

Korine A Ohiri, Sean T Kelly, Jeffrey D Motschman, Kevin H Lin, Kris C Wood, Benjamin B Yellen

Abstract read
In one paragraph

Article in Lab on a chip, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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

6 authors.

Korine A OhiriDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA. yellen@duke.edu.
Sean T Kelly
Jeffrey D Motschman
Kevin H Lin
Kris C Wood
Benjamin B Yellen

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007171 · NIGMS · DUKE UNIVERSITY · PI KONTOS, CHRISTOPHER D · 1985 to 2021
$31.2M
Magnetically directed single cell transcriptome analysis in HIV latencyR01GM123542 · NIGMS · DUKE UNIVERSITY · PI MURDOCH, DAVID MARTIN · 2016 to 2018
$1.7M
Magnetically directed single cell transcriptome analysis in HIV latencyR01AI150465 · NIAID · DUKE UNIVERSITY · PI MURDOCH, DAVID MARTIN · 2019 to 2020
$1.1M
An Instrument for Negative Acoustic Contrast Bead-based Cell Sorting and StainingR21GM111584 · NIGMS · DUKE UNIVERSITY · PI YELLEN, BENJAMIN BIRON · 2014 to 2016
$544k
Single cell functional dissection of tumor microenviornment-driven drug resistanceR21CA220082 · NCI · DUKE UNIVERSITY · PI WOOD, KRIS C. · 2018 to 2019
$359k
NCI NIH HHS R21 CA220082NIAID NIH HHS R01 AI150465NIGMS NIH HHS R01 GM123542NIGMS NIH HHS R21 GM111584NIGMS NIH HHS T32 GM007171
6 · The paper itself

Abstract

We demonstrate a hybrid microfluidic system that combines fluidic trapping and acoustic switching to organize an array of single cells at high density. The fluidic trapping step is achieved by balancing the hydrodynamic resistances of three parallel channel segments forming a microfluidic trifurcation, the purpose of which was to capture single cells in a high-density array. Next, the cells were transferred into adjacent larger compartments by generating an array of streaming micro-vortices to move the cells to the desired streamlines in a massively parallel format. This approach can compartmentalize single cells with efficiencies of ≈67% in compartments that have diameters on the order of ∼100 um, which is an appropriate size for single cell proliferation studies and other single cell biochemical measurements.

Indexed as

AcousticsLab-On-A-Chip DevicesCell Line, TumorHumansHydrodynamicsSingle-Cell AnalysisTissue Array Analysis

Identifiers

PMID29931016
PMCPMC6078799

What OpenQuestion holds

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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.