ArticleBiophysical journal2024
Analytical method for reconstructing the stress on a spherical particle from its surface deformation.
Article in Biophysical journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Volume and surface methods for microparticle traction force microscopy: a computational and experimental comparison.Soft matter · 2026Article
- Mechanically Programmable DNA Hydrogel Microparticles for 3D Cellular Systems.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- A new friend for measuring forces in living tissues.Biophysical journal · 2025Article
- 3D multiscale shape analysis of nuclei and in vivo elastic stress sensors allows force inference.Biophysical journal · 2025Article
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Authors and funding
6 authors.
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Abstract
The mechanical forces that cells experience from the tissue surrounding them are crucial for their behavior and development. Experimental studies of such mechanical forces require a method for measuring them. A widely used approach in this context is bead deformation analysis, where spherical particles are embedded into the tissue. The deformation of the particles then allows to reconstruct the mechanical stress acting on them. Existing approaches for this reconstruction are either very time-consuming or not sufficiently general. In this article, we present an analytical approach to this problem based on an expansion in solid spherical harmonics that allows us to find the complete stress tensor describing the stress acting on the tissue. Our approach is based on the linear theory of elasticity and uses an ansatz specifically designed for deformed spherical bodies. We clarify the conditions under which this ansatz can be used, making our results useful also for other contexts in which this ansatz is employed. Our method can be applied to arbitrary radial particle deformations and requires a very low computational effort. The usefulness of the method is demonstrated by an application to experimental data.
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