Evidence map›Paper›PMID 31015629›Full record

ArticleNature biomedical engineering2018

Elastomeric sensor surfaces for high-throughput single-cell force cytometry.

Ivan Pushkarsky, Peter Tseng, Dylan Black, Bryan France, Lyndon Warfe, Cynthia J Koziol-White, William F Jester, Ryan K Trinh, Jonathan Lin, Philip O Scumpia and 4 more

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Trial
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  11. Article
  12. Article
  13. Field Guide to Traction Force Microscopy.Cellular and molecular bioengineering · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Ivan PushkarskyDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Peter TsengDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Dylan BlackDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Bryan FranceCalifornia NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, USA.
Lyndon WarfeDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Cynthia J Koziol-WhiteRutgers Institute for Translational Medicine and Science, Child Health Institute, Rutgers University, New Brunswick, NJ, USA.
William F JesterRutgers Institute for Translational Medicine and Science, Child Health Institute, Rutgers University, New Brunswick, NJ, USA.
Ryan K TrinhDepartment of Microbiology, Immunology and Molecular Genetics and The Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA.
Jonathan LinDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Philip O ScumpiaDivision of Dermatology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Sherie L MorrisonDepartment of Microbiology, Immunology and Molecular Genetics and The Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA.
Reynold A PanettieriRutgers Institute for Translational Medicine and Science, Child Health Institute, Rutgers University, New Brunswick, NJ, USA.
Robert DamoiseauxCalifornia NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, USA.
Dino Di CarloDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA. dicarlo@seas.ucla.edu.

Funding

Engineering the Intracellular Micro- and NanoenvironmentDP2OD007113 · OD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DI CARLO, DINO · 2010 to 2010
$2.3M
Force phenotyping of airway smooth muscle cells to develop novel asthma therapies R21EB024081 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DI CARLO, DINO, PANETTIERI, REYNOLD ALEXANDER · 2017 to 2018
$444k
NIBIB NIH HHS R21 EB024081NIH HHS DP2 OD007113
6 · The paper itself

Abstract

As cells with aberrant force-generating phenotypes can directly lead to disease, cellular force-generation mechanisms are high-value targets for new therapies. Here, we show that single-cell force sensors embedded in elastomers enable single-cell force measurements with ~100-fold improvement in throughput than was previously possible. The microtechnology is scalable and seamlessly integrates with the multi-well plate format, enabling highly parallelized time-course studies. In this regard, we show that airway smooth muscle cells isolated from fatally asthmatic patients have innately greater and faster force-generation capacity in response to stimulation than healthy control cells. By simultaneously tracing agonist-induced calcium flux and contractility in the same cell, we show that the calcium level is ultimately a poor quantitative predictor of cellular force generation. Finally, by quantifying phagocytic forces in thousands of individual human macrophages, we show that force initiation is a digital response (rather than a proportional one) to the proper immunogen. By combining mechanobiology at the single-cell level with high-throughput capabilities, this microtechnology can support drug-discovery efforts for clinical conditions associated with aberrant cellular force generation.

Indexed as

AsthmaCell DifferentiationCells, CulturedElastomersFluorescent DyesFormoterol FumarateHeterocyclic Compounds, 4 or More RingsHumansMacrophagesMesenchymal Stem CellsMicroscopy, FluorescenceMyocardial ContractionMyocytes, Smooth MusclePhagocytosisSingle-Cell AnalysisblebbistatinElastomersFluorescent DyesFormoterol FumarateHeterocyclic Compounds, 4 or More Rings

Identifiers

PMID31015629
PMCPMC6619436

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.