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Smart Materials in Medicine
Article . 2024 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Smart Materials in Medicine
Article . 2024
Data sources: DOAJ
https://doi.org/10.2139/ssrn.4...
Article . 2023 . Peer-reviewed
Data sources: Crossref
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A Detailed Protocol for Cell Force Measurement by Traction Force Microscopy

Authors: Man Zhang; Yu Zhang; Peng Wang; Qian Sun; Xin Wang; Yi Cao; Qiang Wei;

A Detailed Protocol for Cell Force Measurement by Traction Force Microscopy

Abstract

Cellular traction forces (CTFs) are generated by adherent cells and involved in regulating migration, morphology, and homeostasis. Accurate measurement of CTFs is crucial for understanding fundamental biological processes such as morphogenesis, angiogenesis, and wound healing. However, directly measuring CTFs, which typically range in the nanonewton scale, is challenging. Cellular traction force microscopy (TFM) has been developed to quantify CTFs, but detailed operational procedures and complex data analysis limit its applicability. In this study, hydrogels embedded with fluo-spheres serve as the substrate for TFM measurement under a detailed TFM protocol. Additionally, we designed a user-friendly program for easy parameter setting. An open-source program called Python Fourier transform traction cytometry (pyFTTC) is introduced for data analysis, utilizing particle image velocimetry (PIV) to calculate the traction force from a batch of images. Cross-correlation based PIV and L2-regularized FTTC are applied to all images for data analysis. This article provides a straightforward protocol for quantifying CTFs in standard laboratories, facilitating both cell biology studies and biomaterials development.

Related Organizations
Keywords

Mechanobiology, Hydrogel, Technology, T, Cell adhesion, Traction force microscopy

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    8
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
gold