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A soft and ultrasensitive force sensing diaphragm for probing cardiac organoids instantaneously and wirelessly

Quanxia Lyu, Shu Gong, Jarmon G. Lees, Jialiang Yin, Lim Wei Yap, Anne M. Kong, Qianqian Shi, Runfang Fu, Qiang Zhu, Ash Dyer, Jennifer M. Dyson, Shiang Y. Lim and Wenlong Cheng ()
Additional contact information
Quanxia Lyu: Monash University
Shu Gong: Monash University
Jarmon G. Lees: St. Vincent’s Institute of Medical Research
Jialiang Yin: Monash University
Lim Wei Yap: Monash University
Anne M. Kong: St. Vincent’s Institute of Medical Research
Qianqian Shi: Monash University
Runfang Fu: Monash University
Qiang Zhu: The Melbourne Centre for Nanofabrication
Ash Dyer: The Melbourne Centre for Nanofabrication
Jennifer M. Dyson: Biomedicine Discovery Institute
Shiang Y. Lim: St. Vincent’s Institute of Medical Research
Wenlong Cheng: Monash University

Nature Communications, 2022, vol. 13, issue 1, 1-13

Abstract: Abstract Time-lapse mechanical properties of stem cell derived cardiac organoids are important biological cues for understanding contraction dynamics of human heart tissues, cardiovascular functions and diseases. However, it remains difficult to directly, instantaneously and accurately characterize such mechanical properties in real-time and in situ because cardiac organoids are topologically complex, three-dimensional soft tissues suspended in biological media, which creates a mismatch in mechanics and topology with state-of-the-art force sensors that are typically rigid, planar and bulky. Here, we present a soft resistive force-sensing diaphragm based on ultrasensitive resistive nanocracked platinum film, which can be integrated into an all-soft culture well via an oxygen plasma-enabled bonding process. We show that a reliable organoid-diaphragm contact can be established by an ‘Atomic Force Microscope-like’ engaging process. This allows for instantaneous detection of the organoids’ minute contractile forces and beating patterns during electrical stimulation, resuscitation, drug dosing, tissue culture, and disease modelling.

Date: 2022
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DOI: 10.1038/s41467-022-34860-y

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