ArticleBiophysical journal2015
Characterizing cell adhesion by using micropipette aspiration.
Article in Biophysical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- An integrated nanophotonic SPRM microsystem for real-time, label-free quantification of single-cell adhesion dynamics.Microsystems & nanoengineering · 2026Article
- Measurement of adhesion and traction of cells at high yield reveals an energetic ratchet operating during nephron condensation.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Mechanical properties of human tumour tissues and their implications for cancer development.Nature reviews. Physics · 2024Article
- Measurement of adhesion and traction of cells at high yield (MATCHY) reveals an energetic ratchet driving nephron condensation.bioRxiv : the preprint server for biology · 2024Article
- Biomechanics of Chondrocytes and Chondrons in Healthy Conditions and Osteoarthritis: A Review of the Mechanical Characterisations at the Microscale.Biomedicines · 2023Review
- Biophysical studies of cancer cells' traverse-vessel behaviors under different pressures revealed cells' motion state transition.Scientific reports · 2022Article
- Mechanical Studies of the Third Dimension in Cancer: From 2D to 3D Model.International journal of molecular sciences · 2021Review
- Review
- Recent Advances on the Model, Measurement Technique, and Application of Single Cell Mechanics.International journal of molecular sciences · 2020Review
- DLITE Uses Cell-Cell Interface Movement to Better Infer Cell-Cell Tensions.Biophysical journal · 2019Article
- Advances in Micropipette Aspiration: Applications in Cell Biomechanics, Models, and Extended Studies.Biophysical journal · 2019Review
- Adhesion analysis of single circulating tumor cells on a base layer of endothelial cells using open microfluidics.Chemical science · 2018Article
- Characterizing cellular mechanical phenotypes with mechano-node-pore sensing.Microsystems & nanoengineering · 2018Article
- Micropipette force probe to quantify single-cell force generation: application to T-cell activation.Molecular biology of the cell · 2017Article
- Mechanical Criterion for the Rupture of a Cell Membrane under Compression.Biophysical journal · 2016Article
- Measuring Cell Viscoelastic Properties Using a Microfluidic Extensional Flow Device.Biophysical journal · 2016Article
- Topography of Cells Revealed by Variable-Angle Total Internal Reflection Fluorescence Microscopy.Biophysical journal · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a technique to directly quantify cell-substrate adhesion force using micropipette aspiration. The micropipette is positioned perpendicular to the surface of an adherent cell and a constant-rate aspiration pressure is applied. Since the micropipette diameter and the aspiration pressure are our control parameters, we have direct knowledge of the aspiration force, whereas the cell behavior is monitored either in brightfield or interference reflection microscopy. This setup thus allows us to explore a range of geometric parameters, such as projected cell area, adhesion area, or pipette size, as well as dynamical parameters such as the loading rate. We find that cell detachment is a well-defined event occurring at a critical aspiration pressure, and that the detachment force scales with the cell adhesion area (for a given micropipette diameter and loading rate), which defines a critical stress. Taking into account the cell adhesion area, intrinsic parameters of the adhesion bonds, and the loading rate, a minimal model provides an expression for the critical stress that helps rationalize our experimental results.
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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.