Evidence map›Paper›PMID 28835648›Full record

ArticleScientific reports2017

BioFlow: a non-invasive, image-based method to measure speed, pressure and forces inside living cells.

Aleix Boquet-Pujadas, Timothée Lecomte, Maria Manich, Roman Thibeaux, Elisabeth Labruyère, Nancy Guillén, Jean-Christophe Olivo-Marin, Alexandre C Dufour

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Chemokine-biased robust self-organizing polarization of migrating cells in vivo.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  6. Bioimage Analysis and Cell Motility.Patterns (New York, N.Y.) · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

8 authors.

Aleix Boquet-PujadasInstitut Pasteur, Bioimage Analysis Unit, Paris, France.
Timothée LecomteInstitut Pasteur, Bioimage Analysis Unit, Paris, France.
Maria ManichInstitut Pasteur, Bioimage Analysis Unit, Paris, France.
Roman ThibeauxInstitut Pasteur, Cell Biology of Parasitism Unit, Paris, France.
Elisabeth LabruyèreInstitut Pasteur, Bioimage Analysis Unit, Paris, France.
Nancy GuillénInstitut Pasteur, Cell Biology of Parasitism Unit, Paris, France.
Jean-Christophe Olivo-MarinInstitut Pasteur, Bioimage Analysis Unit, Paris, France. jcolivo@pasteur.fr.
Alexandre C DufourInstitut Pasteur, Bioimage Analysis Unit, Paris, France. adufour@pasteur.fr.ORCID 0000-0002-9417-7389

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell motility is governed by a complex molecular machinery that converts physico-chemical cues into whole-cell movement. Understanding the underlying biophysical mechanisms requires the ability to measure physical quantities inside the cell in a simple, reproducible and preferably non-invasive manner. To this end, we developed BioFlow, a computational mechano-imaging method and associated software able to extract intracellular measurements including pressure, forces and velocity everywhere inside freely moving cells in two and three dimensions with high spatial resolution in a non-invasive manner. This is achieved by extracting the motion of intracellular material observed using fluorescence microscopy, while simultaneously inferring the parameters of a given theoretical model of the cell interior. We illustrate the power of BioFlow in the context of amoeboid cell migration, by modelling the intracellular actin bulk flow of the parasite Entamoeba histolytica using fluid dynamics, and report unique experimental measures that complement and extend both theoretical estimations and invasive experimental measures. Thanks to its flexibility, BioFlow is easily adaptable to other theoretical models of the cell, and alleviates the need for complex or invasive experimental conditions, thus constituting a powerful tool-kit for mechano-biology studies. BioFlow is open-source and freely available via the Icy software.

Indexed as

Models, TheoreticalMolecular ImagingSoftwareAlgorithmsCell MovementMechanical PhenomenaMicroscopy, FluorescencePhysical Phenomena

Identifiers

PMID28835648
PMCPMC5569094

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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.