Evidence map›Paper›PMID 37915171›Full record

ArticleBiophysical journal2023

Bayesian traction force estimation using cell boundary-dependent force priors.

Ryosuke Fujikawa, Chika Okimura, Satoshi Kozawa, Kazushi Ikeda, Naoyuki Inagaki, Yoshiaki Iwadate, Yuichi Sakumura

Abstract read
In one paragraph

Article in Biophysical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Uncertainty-aware traction force microscopy.PLoS computational biology · 2025
    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

7 authors.

Ryosuke FujikawaGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan.
Chika OkimuraDepartment of Biology, Yamaguchi University, Yamaguchi, Japan.
Satoshi KozawaGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan.
Kazushi IkedaGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan; Data Science Center, Nara Institute of Science and Technology, Ikoma, Nara, Japan.
Naoyuki InagakiGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan.
Yoshiaki IwadateDepartment of Biology, Yamaguchi University, Yamaguchi, Japan.
Yuichi SakumuraGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan; Data Science Center, Nara Institute of Science and Technology, Ikoma, Nara, Japan. Electronic address: saku@bs.naist.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the principles of cell migration necessitates measurements of the forces generated by cells. In traction force microscopy (TFM), fluorescent beads are placed on a substrate's surface and the substrate strain caused by the cell traction force is observed as displacement of the beads. Mathematical analysis can estimate traction force from bead displacement. However, most algorithms estimate substrate stresses independently of cell boundary, which results in poor estimation accuracy in low-density bead environments. To achieve accurate force estimation at low density, we proposed a Bayesian traction force estimation (BTFE) algorithm that incorporates cell-boundary-dependent force as a prior. We evaluated the performance of the proposed algorithm using synthetic data generated with mathematical models of cells and TFM substrates. BTFE outperformed other methods, especially in low-density bead conditions. In addition, the BTFE algorithm provided a reasonable force estimation using TFM images from the experiment.

Indexed as

Mechanical PhenomenaTractionBayes TheoremMicroscopy, Atomic ForceModels, Theoretical

Identifiers

PMID37915171
PMCPMC10719052

What OpenQuestion holds

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LicenceCC BY
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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.