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Atomic Force Microscopy

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...

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Updated: Jun 28, 2025

Extracting the Young's Modulus of Native Murine Pulmonary Basement Membranes from Atomic Force Microscopy Derived Force Maps

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A method for analyzing AFM force mapping data obtained from soft tissue cryosections.

Cydney A Wong¹, Nina Sara Fraticelli Guzmán², A Thomas Read¹

¹Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.

Journal of Biomechanics

|April 22, 2024

Summary

This summary is machine-generated.

This study introduces a new atomic force microscopy (AFM) method for analyzing soft tissue mechanics using cryosections. This pipeline improves the reliability of mechanical property measurements in heterogeneous biological samples.

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Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

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Area of Science:

Biophysics
Materials Science
Ophthalmology

Background:

Atomic force microscopy (AFM) is crucial for evaluating biological sample mechanics.
Interpreting AFM data from heterogeneous whole tissues presents significant challenges.
Robust mechanical property estimation requires advanced analytical approaches.

Purpose of the Study:

To develop and validate an AFM force mapping and data analysis pipeline.
To characterize the mechanical properties of cryosectioned soft tissues.
To enhance the reliability of AFM measurements in complex biological samples.

Main Methods:

Utilized AFM force mapping on cryosectioned soft tissues.
Applied a data analysis pipeline including repeated measurements and outlier exclusion.
Employed log-normal data transformation for enhanced confidence in measurements.

Main Results:

Successfully characterized mechanical properties of mouse optic nerve head, rat trabecular meshwork, cornea, and sclera.
Demonstrated that repeated measurements, outlier exclusion, and log-normal transformation increase confidence in AFM data.
Validated the pipeline's effectiveness for heterogeneous soft tissue analysis.

Conclusions:

The developed AFM pipeline provides robust estimates of soft tissue mechanical properties.
The methodology is broadly applicable to cryosectioned soft tissues.
This approach enhances the utility of AFM in biological and materials science research.