Optimal design for multi-compartment cell elasticity estimation using AFM and super-resolution imaging

Emilio A. Mendiola; Brandon K. Walther; Anahita Mojiri; John P. Cooke; Jacques Ohayon; Roderic I. Pettigrew; Reza Avazmohammadi

doi:10.1016/j.cmpb.2026.109269

February 14, 2026Computer Methods and Programs in BiomedicineOpen Access

Optimal design for multi-compartment cell elasticity estimation using AFM and super-resolution imaging

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Key Points

This approach enhances cell elasticity estimation, aiding in understanding mechanotransduction in disease.
Improved consistency and reproducibility in biomechanical characterizations were observed.
Analysis utilizes advanced techniques, including atomic force microscopy (AFM) and super-resolution imaging.
This work may enable better standardization across mechanobiological studies, advancing disease research.

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Abstract

We expect our approach to assist with standardizing the biomechanical characterizations of subcellular structures, improve the consistency and reproducibility of the estimations across mechanobiological studies, and ultimately improve our understanding of the role of mechanotransduction in disease progression.

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Mendiola et al. (2026) studied this question.

synapsesocial.com/papers/69a76132c6e9836116a2ee3c https://doi.org/10.1016/j.cmpb.2026.109269

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Optimal design for multi-compartment cell elasticity estimation using AFM and super-resolution imaging

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Optimal design for multi-compartment cell elasticity estimation using AFM and super-resolution imaging

Key Points

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Abstract

Discussion

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