Artificial intelligence–enabled “inherited noninvasive intracellular recording” for prolonged monitoring of cardiac action potentials

Intracellular action potential (AP) recording that allows long-term monitoring is challenging because permanent membrane penetration is impossible due to cell death or resealing of perforated cell membrane. Herein, an "inherited noninvasive intracellular recording" methodology was proposed, which was based on the fusion of artificial intelligence (AI) with microelectrode array (MEA)-electroporation system (AI-MEA-EP) to enable prolonged monitoring of intracellular APs in cardiomyocytes. It used MEA-electroporation (MEA-EP) for minimally invasive collection of intracellular signals transiently (~1 minute), as well as noninvasive recording of extracellular signals in long term. The recorded extracellular APs were converted into corresponding intracellular APs by a convolutional neural network-long short-term memory-based AI model enhanced by model self-calibration. The intracellular APs detected by the AI-MEA-EP exhibited high consistency with those physically obtained through MEA-EP. It was demonstrated to monitor cardiac intracellular AP under drug treatments and glucose challenging during >5 consecutive days. This method offers a unique solution to achieve prolonged recording of intracellular signals for advancing cardiac research.

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Publication Details

Journal
Science Advances
Published
2026-01-16
DOI
https://doi.org/10.1126/sciadv.ady3617
Citations
1
Primary Topic
Microbial Inactivation Methods
Type
article
Field-Weighted Citation Impact
27.96
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article

Artificial intelligence–enabled “inherited noninvasive intracellular recording” for prolonged monitoring of cardiac action potentials

Minghao Li, Xinshuo Huang, Xiaoping Xu, Li Yan et al.
1 citations
Science Advances
Microbial Inactivation Methods
27.96
article

Artificial intelligence–enabled “inherited noninvasive intracellular recording” for prolonged monitoring of cardiac action potentials

Minghao Li, Xinshuo Huang, Xiaoping Xu, Li Yan, Xinyue Li, Shuang Huang, Zhengjie Liu, Guanbin Li, Chuanjie Yao, Ji Wang, Hui-jiuan Chen, Xi Chen, Jing Liu, Yijing Cai, Mingqiang Li, Xi Xie, Lisheng Hou, Suhang Liu
article en
1 citations

Abstract

Intracellular action potential (AP) recording that allows long-term monitoring is challenging because permanent membrane penetration is impossible due to cell death or resealing of perforated cell membrane. Herein, an "inherited noninvasive intracellular recording" methodology was proposed, which was based on the fusion of artificial intelligence (AI) with microelectrode array (MEA)-electroporation system (AI-MEA-EP) to enable prolonged monitoring of intracellular APs in cardiomyocytes. It used MEA-electroporation (MEA-EP) for minimally invasive collection of intracellular signals transiently (~1 minute), as well as noninvasive recording of extracellular signals in long term. The recorded extracellular APs were converted into corresponding intracellular APs by a convolutional neural network-long short-term memory-based AI model enhanced by model self-calibration. The intracellular APs detected by the AI-MEA-EP exhibited high consistency with those physically obtained through MEA-EP. It was demonstrated to monitor cardiac intracellular AP under drug treatments and glucose challenging during >5 consecutive days. This method offers a unique solution to achieve prolonged recording of intracellular signals for advancing cardiac research.

Science AdvancesVol. 12(3)
Sun Yat-sen University (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), Shanghai Chengtou (China) (CN), Third Affiliated Hospital of Sun Yat-sen University (CN), First Affiliated Hospital of Jinan University (CN)
Openalex Percentile: Top 2%
Microbial Inactivation Methods
27.96
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