ArticleBiophysical journal2016
Inference of Internal Stress in a Cell Monolayer.
Article in Biophysical journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
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Who cites it
42 citing papers in PubMed, 102 citations in OpenAlex.
- Mechanical memory of confinement pressure governs expansion size in epithelial monolayers.Life science alliance · 2026Article
- Extracellular-matrix mediated stresses spatially bias myoblast fusion and myotube growth.Nature communications · 2026Article
- Fibronectin matrix remodelling modulates the active nematic dynamics of cancer-associated fibroblasts.Nature materials · 2026Article
- napariTFM: An open-source tool for traction force microscopy and monolayer stress microscopy.PLoS computational biology · 2026Article
- Reduced-order modeling of solute transport within physiologically realistic solid tumor microenvironment.Frontiers in pharmacology · 2026Article
- REDUCED-ORDER MODELING OF SOLUTE TRANSPORT WITHIN PHYSIOLOGICALLY REALISTIC SOLID TUMOR MICROENVIRONMENT.bioRxiv : the preprint server for biology · 2025Article
- Uncertainty-aware traction force microscopy.PLoS computational biology · 2025Article
- Force transmission is a master regulator of mechanical cell competition.Nature materials · 2025Article
- Flocking and giant fluctuations in epithelial active solids.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- An Open-source Python Tool for Traction Force Microscopy on Micropatterned Substrates.Bio-protocol · 2025Article
- Different Biomechanical Cell Behaviors in an Epithelium Drive Collective Epithelial Cell Extrusion.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- 3D Traction Force Microscopy in Biological Gels: From Single Cells to Multicellular Spheroids.Annual review of biomedical engineering · 2024Review
- Mechanical imbalance between normal and transformed cells drives epithelial homeostasis through cell competition.bioRxiv : the preprint server for biology · 2024Article
- Mechanical convergence in mixed populations of mammalian epithelial cells.The European physical journal. E, Soft matter · 2024Article
- A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation.Biophysical journal · 2023Article
- MAP4K4 regulates forces at cell-cell and cell-matrix adhesions to promote collective cell migration.Life science alliance · 2023Article
- Mapping mechanical stress in curved epithelia of designed size and shape.Nature communications · 2023Article
- Appetizer on soft matter physics concepts in mechanobiology.Development, growth & differentiation · 2023Review
- Mechanical stress driven by rigidity sensing governs epithelial stability.Nature physics · 2023Article
- Mechanochemical subcellular-element model of crawling cells.Frontiers in cell and developmental biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
Abstract
We combine traction force data with Bayesian inversion to obtain an absolute estimate of the internal stress field of a cell monolayer. The method, Bayesian inversion stress microscopy, is validated using numerical simulations performed in a wide range of conditions. It is robust to changes in each ingredient of the underlying statistical model. Importantly, its accuracy does not depend on the rheology of the tissue. We apply Bayesian inversion stress microscopy to experimental traction force data measured in a narrow ring of cohesive epithelial cells, and check that the inferred stress field coincides with that obtained by direct spatial integration of the traction force data in this quasi one-dimensional geometry.
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Registered trials
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.