Evidence map›Paper›PMID 30858424›Full record

ArticleScientific reports2019

Quantitative reconstruction of time-varying 3D cell forces with traction force optical coherence microscopy.

Jeffrey A Mulligan, Xinzeng Feng, Steven G Adie

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Field Guide to Traction Force Microscopy.Cellular and molecular bioengineering · 2024
    Review
  6. Review
  7. Review
  8. Harnessing mechanobiology for kidney organoid research.Frontiers in cell and developmental biology · 2023
    Review
  9. Article
  10. Impact of Doxorubicin on Cell-Substrate Topology.International journal of molecular sciences · 2022
    Article
  11. A primer to traction force microscopy.The Journal of biological chemistry · 2022
    Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Jeffrey A MulliganSchool of Electrical and Computer Engineering, Cornell University, Ithaca, New York, 14853, USA.
Xinzeng FengInstitute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, 78712, USA.
Steven G AdieNancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, 14853, USA. sga42@cornell.edu.

Funding

Volumetric Traction Force Tomography of Collective Cell Migration DynamicsR21EB022927 · NIBIB · CORNELL UNIVERSITY · PI ADIE, STEVEN GRAHAM · 2016 to 2017
$434k
NIBIB NIH HHS R21 EB022927
6 · The paper itself

Abstract

Cellular traction forces (CTFs) play an integral role in both physiological processes and disease, and are a topic of interest in mechanobiology. Traction force microscopy (TFM) is a family of methods used to quantify CTFs in a variety of settings. State-of-the-art 3D TFM methods typically rely on confocal fluorescence microscopy, which can impose limitations on acquisition speed, volumetric coverage, and temporal sampling or coverage. In this report, we present the first quantitative implementation of a new TFM technique: traction force optical coherence microscopy (TF-OCM). TF-OCM leverages the capabilities of optical coherence microscopy and computational adaptive optics (CAO) to enable the quantitative reconstruction of 3D CTFs in scattering media with minute-scale temporal sampling. We applied TF-OCM to quantify CTFs exerted by isolated NIH-3T3 fibroblasts embedded in Matrigel, with five-minute temporal sampling, using images spanning a 500 × 500 × 500 μm

Indexed as

Mechanical PhenomenaAlgorithmsAnimalsCell AdhesionComputer SimulationFibroblastsImaging, Three-DimensionalMiceMicroscopy, Atomic ForceMicroscopy, ConfocalNIH 3T3 CellsTraction

Identifiers

PMID30858424
PMCPMC6411852

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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.