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Dai C, Xiong H, He R, Zhu C, Li P, Guo M, Gou J, Mei M, Kong D, Li Q, Wee ATS, Fang X, Kong J, Liu Y, Wei D. Electro-Optical Multiclassification Platform for Minimizing Occasional Inaccuracy in Point-of-Care Biomarker Detection. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2312540. [PMID: 38288781 DOI: 10.1002/adma.202312540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/13/2024] [Indexed: 02/06/2024]
Abstract
On-site diagnostic tests that accurately identify disease biomarkers lay the foundation for self-healthcare applications. However, these tests routinely rely on single-mode signals and suffer from insufficient accuracy, especially for multiplexed point-of-care tests (POCTs) within a few minutes. Here, this work develops a dual-mode multiclassification diagnostic platform that integrates an electrochemiluminescence sensor and a field-effect transistor sensor in a microfluidic chip. The microfluidic channel guides the testing samples to flow across electro-optical sensor units, which produce dual-mode readouts by detecting infectious biomarkers of tuberculosis (TB), human rhinovirus (HRV), and group B streptococcus (GBS). Then, machine-learning classifiers generate three-dimensional (3D) hyperplanes to diagnose different diseases. Dual-mode readouts derived from distinct mechanisms enhance the anti-interference ability physically, and machine-learning-aided diagnosis in high-dimensional space reduces the occasional inaccuracy mathematically. Clinical validation studies with 501 unprocessed samples indicate that the platform has an accuracy approaching 99%, higher than the 77%-93% accuracy of rapid point-of-care testing technologies at 100% statistical power (>150 clinical tests). Moreover, the diagnosis time is 5 min without a trade-off of accuracy. This work solves the occasional inaccuracy issue of rapid on-site diagnosis, endowing POCT systems with the same accuracy as laboratory tests and holding unique prospects for complicated scenes of personalized healthcare.
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Affiliation(s)
- Changhao Dai
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
| | - Huiwen Xiong
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Rui He
- School of Nuclear Science and Technology, Lanzhou University, Lanzhou, 73000, China
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Chenxin Zhu
- Institute of Biomedical Sciences, Fudan University, Shanghai, 200032, China
| | - Pintao Li
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Mingquan Guo
- Department of Laboratory Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Jian Gou
- Department of Physics, National University of Singapore, Singapore, 117542, Singapore
| | - Miaomiao Mei
- Yizheng Hospital of Traditional Chinese Medicine, Yangzhou, 211400, China
| | - Derong Kong
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
| | - Qiang Li
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Andrew Thye Shen Wee
- Department of Physics, National University of Singapore, Singapore, 117542, Singapore
| | - Xueen Fang
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Jilie Kong
- Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Yunqi Liu
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
| | - Dacheng Wei
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China
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2
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Gao H, Wang Z, Yang F, Wang X, Wang S, Zhang Q, Liu X, Sun Y, Kong J, Yao J. Graphene-integrated mesh electronics with converged multifunctionality for tracking multimodal excitation-contraction dynamics in cardiac microtissues. Nat Commun 2024; 15:2321. [PMID: 38485708 PMCID: PMC10940632 DOI: 10.1038/s41467-024-46636-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 03/05/2024] [Indexed: 03/18/2024] Open
Abstract
Cardiac microtissues provide a promising platform for disease modeling and developmental studies, which require the close monitoring of the multimodal excitation-contraction dynamics. However, no existing assessing tool can track these multimodal dynamics across the live tissue. We develop a tissue-like mesh bioelectronic system to track these multimodal dynamics. The mesh system has tissue-level softness and cell-level dimensions to enable stable embedment in the tissue. It is integrated with an array of graphene sensors, which uniquely converges both bioelectrical and biomechanical sensing functionalities in one device. The system achieves stable tracking of the excitation-contraction dynamics across the tissue and throughout the developmental process, offering comprehensive assessments for tissue maturation, drug effects, and disease modeling. It holds the promise to provide more accurate quantification of the functional, developmental, and pathophysiological states in cardiac tissues, creating an instrumental tool for improving tissue engineering and studies.
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Affiliation(s)
- Hongyan Gao
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Zhien Wang
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Feiyu Yang
- Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Xiaoyu Wang
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Siqi Wang
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Quan Zhang
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Xiaomeng Liu
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Yubing Sun
- Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA, 01003, USA
- Institute for Applied Life Sciences, University of Massachusetts, Amherst, MA, 01003, USA
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Jing Kong
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jun Yao
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, 01003, USA.
- Institute for Applied Life Sciences, University of Massachusetts, Amherst, MA, 01003, USA.
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, 01003, USA.
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3
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Cheng X, Shen Z, Zhang Y. Bioinspired 3D flexible devices and functional systems. Natl Sci Rev 2024; 11:nwad314. [PMID: 38312384 PMCID: PMC10833470 DOI: 10.1093/nsr/nwad314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/21/2023] [Accepted: 11/28/2023] [Indexed: 02/06/2024] Open
Abstract
Flexible devices and functional systems with elaborated three-dimensional (3D) architectures can endow better mechanical/electrical performances, more design freedom, and unique functionalities, when compared to their two-dimensional (2D) counterparts. Such 3D flexible devices/systems are rapidly evolving in three primary directions, including the miniaturization, the increasingly merged physical/artificial intelligence and the enhanced adaptability and capabilities of heterogeneous integration. Intractable challenges exist in this emerging research area, such as relatively poor controllability in the locomotion of soft robotic systems, mismatch of bioelectronic interfaces, and signal coupling in multi-parameter sensing. By virtue of long-time-optimized materials, structures and processes, natural organisms provide rich sources of inspiration to address these challenges, enabling the design and manufacture of many bioinspired 3D flexible devices/systems. In this Review, we focus on bioinspired 3D flexible devices and functional systems, and summarize their representative design concepts, manufacturing methods, principles of structure-function relationship and broad-ranging applications. Discussions on existing challenges, potential solutions and future opportunities are also provided to usher in further research efforts toward realizing bioinspired 3D flexible devices/systems with precisely programmed shapes, enhanced mechanical/electrical performances, and high-level physical/artificial intelligence.
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Affiliation(s)
- Xu Cheng
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China
| | - Zhangming Shen
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China
| | - Yihui Zhang
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
- Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China
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Xiang Y, Shi K, Li Y, Xue J, Tong Z, Li H, Li Z, Teng C, Fang J, Hu N. Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording. NANO-MICRO LETTERS 2024; 16:132. [PMID: 38411852 PMCID: PMC10899154 DOI: 10.1007/s40820-024-01336-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 12/28/2023] [Indexed: 02/28/2024]
Abstract
The development of precise and sensitive electrophysiological recording platforms holds the utmost importance for research in the fields of cardiology and neuroscience. In recent years, active micro/nano-bioelectronic devices have undergone significant advancements, thereby facilitating the study of electrophysiology. The distinctive configuration and exceptional functionality of these active micro-nano-collaborative bioelectronic devices offer the potential for the recording of high-fidelity action potential signals on a large scale. In this paper, we review three-dimensional active nano-transistors and planar active micro-transistors in terms of their applications in electro-excitable cells, focusing on the evaluation of the effects of active micro/nano-bioelectronic devices on electrophysiological signals. Looking forward to the possibilities, challenges, and wide prospects of active micro-nano-devices, we expect to advance their progress to satisfy the demands of theoretical investigations and medical implementations within the domains of cardiology and neuroscience research.
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Affiliation(s)
- Yuting Xiang
- Department of Chemistry, Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, People's Republic of China
- Department of Obstetrics and Gynecology, The Tenth Affiliated Hospital, Southern Medical University, Dongguan, 523059, People's Republic of China
- Dongguan Key Laboratory of Major Diseases in Obstetrics and Gynecology, Dongguan, 523059, People's Republic of China
| | - Keda Shi
- Department of Lung Transplantation and General Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China
| | - Ying Li
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, People's Republic of China
| | - Jiajin Xue
- General Surgery Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children's Health, Hangzhou, 310052, People's Republic of China
| | - Zhicheng Tong
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China
| | - Huiming Li
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China
| | - Zhongjun Li
- Department of Obstetrics and Gynecology, The Tenth Affiliated Hospital, Southern Medical University, Dongguan, 523059, People's Republic of China.
- Dongguan Key Laboratory of Major Diseases in Obstetrics and Gynecology, Dongguan, 523059, People's Republic of China.
| | - Chong Teng
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China.
| | - Jiaru Fang
- School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China.
| | - Ning Hu
- Department of Chemistry, Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, People's Republic of China.
- General Surgery Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children's Health, Hangzhou, 310052, People's Republic of China.
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5
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Cho Y, Choi Y, Seong H. Nanoscale surface coatings and topographies for neural interfaces. Acta Biomater 2024; 175:55-75. [PMID: 38141934 DOI: 10.1016/j.actbio.2023.12.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/28/2023] [Accepted: 12/14/2023] [Indexed: 12/25/2023]
Abstract
With the lack of minimally invasive tools for probing neuronal systems across spatiotemporal scales, understanding the working mechanism of the nervous system and limited assessments available are imperative to prevent or treat neurological disorders. In particular, nanoengineered neural interfaces can provide a solution to this technological barrier. This review covers recent surface engineering approaches, including nanoscale surface coatings, and a range of topographies from the microscale to the nanoscale, primarily focusing on neural-interfaced biosystems. Specifically, the immobilization of bioactive molecules to fertilize the neural cell lineage, topographical engineering to induce mechanotransduction in neural cells, and enhanced cell-chip coupling using three-dimensional structured surfaces are highlighted. Advances in neural interface design will help us understand the nervous system, thereby achieving the effective treatments for neurological disorders. STATEMENT OF SIGNIFICANCE: • This review focuses on designing bioactive neural interface with a nanoscale chemical modification and topographical engineering at multiscale perspective. • Versatile nanoscale surface coatings and topographies for neural interface are summarized. • Recent advances in bioactive materials applicable for neural cell culture, electrophysiological sensing, and neural implants are reviewed.
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Affiliation(s)
- Younghak Cho
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Yunyoung Choi
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea; Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyejeong Seong
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea; Division of Bio-Medical Science and Technology, KIST School, Korea University of Science and Technology (UST), Seoul, Republic of Korea.
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6
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Bo R, Xu S, Yang Y, Zhang Y. Mechanically-Guided 3D Assembly for Architected Flexible Electronics. Chem Rev 2023; 123:11137-11189. [PMID: 37676059 PMCID: PMC10540141 DOI: 10.1021/acs.chemrev.3c00335] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Indexed: 09/08/2023]
Abstract
Architected flexible electronic devices with rationally designed 3D geometries have found essential applications in biology, medicine, therapeutics, sensing/imaging, energy, robotics, and daily healthcare. Mechanically-guided 3D assembly methods, exploiting mechanics principles of materials and structures to transform planar electronic devices fabricated using mature semiconductor techniques into 3D architected ones, are promising routes to such architected flexible electronic devices. Here, we comprehensively review mechanically-guided 3D assembly methods for architected flexible electronics. Mainstream methods of mechanically-guided 3D assembly are classified and discussed on the basis of their fundamental deformation modes (i.e., rolling, folding, curving, and buckling). Diverse 3D interconnects and device forms are then summarized, which correspond to the two key components of an architected flexible electronic device. Afterward, structure-induced functionalities are highlighted to provide guidelines for function-driven structural designs of flexible electronics, followed by a collective summary of their resulting applications. Finally, conclusions and outlooks are given, covering routes to achieve extreme deformations and dimensions, inverse design methods, and encapsulation strategies of architected 3D flexible electronics, as well as perspectives on future applications.
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Affiliation(s)
- Renheng Bo
- Applied
Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084 Beijing, People’s Republic of China
- Laboratory
of Flexible Electronics Technology, Tsinghua
University, 100084 Beijing, People’s Republic
of China
| | - Shiwei Xu
- Applied
Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084 Beijing, People’s Republic of China
- Laboratory
of Flexible Electronics Technology, Tsinghua
University, 100084 Beijing, People’s Republic
of China
| | - Youzhou Yang
- Applied
Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084 Beijing, People’s Republic of China
- Laboratory
of Flexible Electronics Technology, Tsinghua
University, 100084 Beijing, People’s Republic
of China
| | - Yihui Zhang
- Applied
Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, 100084 Beijing, People’s Republic of China
- Laboratory
of Flexible Electronics Technology, Tsinghua
University, 100084 Beijing, People’s Republic
of China
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7
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Fu S, Park JH, Gao H, Zhang T, Ji X, Fu T, Sun L, Kong J, Yao J. Two-Terminal MoS 2 Memristor and the Homogeneous Integration with a MoS 2 Transistor for Neural Networks. NANO LETTERS 2023. [PMID: 37338212 DOI: 10.1021/acs.nanolett.2c05007] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Memristors are promising candidates for constructing neural networks. However, their dissimilar working mechanism to that of the addressing transistors can result in a scaling mismatch, which may hinder efficient integration. Here, we demonstrate two-terminal MoS2 memristors that work with a charge-based mechanism similar to that in transistors, which enables the homogeneous integration with MoS2 transistors to realize one-transistor-one-memristor addressable cells for assembling programmable networks. The homogenously integrated cells are implemented in a 2 × 2 network array to demonstrate the enabled addressability and programmability. The potential for assembling a scalable network is evaluated in a simulated neural network using obtained realistic device parameters, which achieves over 91% pattern recognition accuracy. This study also reveals a generic mechanism and strategy that can be applied to other semiconducting devices for the engineering and homogeneous integration of memristive systems.
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Affiliation(s)
- Shuai Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Ji-Hoon Park
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Hongyan Gao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Tianyi Zhang
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Xiang Ji
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Tianda Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Lu Sun
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Jing Kong
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Jun Yao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, Massachusetts 01003, United States
- Department of Biomedical Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States
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8
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Lin Z, Garbern JC, Liu R, Li Q, Mancheño Juncosa E, Elwell HL, Sokol M, Aoyama J, Deumer US, Hsiao E, Sheng H, Lee RT, Liu J. Tissue-embedded stretchable nanoelectronics reveal endothelial cell-mediated electrical maturation of human 3D cardiac microtissues. SCIENCE ADVANCES 2023; 9:eade8513. [PMID: 36888704 PMCID: PMC9995081 DOI: 10.1126/sciadv.ade8513] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Clinical translation of stem cell therapies for heart disease requires electrical integration of transplanted cardiomyocytes. Generation of electrically matured human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) is critical for electrical integration. Here, we found that hiPSC-derived endothelial cells (hiPSC-ECs) promoted the expression of selected maturation markers in hiPSC-CMs. Using tissue-embedded stretchable mesh nanoelectronics, we achieved a long-term stable map of human three-dimensional (3D) cardiac microtissue electrical activity. The results revealed that hiPSC-ECs accelerated the electrical maturation of hiPSC-CMs in 3D cardiac microtissues. Machine learning-based pseudotime trajectory inference of cardiomyocyte electrical signals further revealed the electrical phenotypic transition path during development. Guided by the electrical recording data, single-cell RNA sequencing identified that hiPSC-ECs promoted cardiomyocyte subpopulations with a more mature phenotype, and multiple ligand-receptor interactions were up-regulated between hiPSC-ECs and hiPSC-CMs, revealing a coordinated multifactorial mechanism of hiPSC-CM electrical maturation. Collectively, these findings show that hiPSC-ECs drive hiPSC-CM electrical maturation via multiple intercellular pathways.
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Affiliation(s)
- Zuwan Lin
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Jessica C. Garbern
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
- Department of Cardiology, Boston Children’s Hospital, Boston, MA, USA
| | - Ren Liu
- School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA
| | - Qiang Li
- School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA
| | | | - Hannah L.T. Elwell
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Morgan Sokol
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Junya Aoyama
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Undine-Sophie Deumer
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Emma Hsiao
- School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA
| | - Hao Sheng
- School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA
| | - Richard T. Lee
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Corresponding author. (J.L.), (R.T.L.)
| | - Jia Liu
- School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA
- Corresponding author. (J.L.), (R.T.L.)
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9
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Fu T, Fu S, Yao J. Recent progress in bio-voltage memristors working with ultralow voltage of biological amplitude. NANOSCALE 2023; 15:4669-4681. [PMID: 36779566 DOI: 10.1039/d2nr06773k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Neuromorphic systems built from memristors that emulate bioelectrical information processing in the brain may overcome the limitations of traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50-120 mV at least 10 times lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. Reducing the functional voltage in memristors to this biological amplitude can thus advance neuromorphic engineering and bio-emulated integration. This review aims to provide a timely update on the effort and progress in this burgeoning research direction, covering the aspects of device material composition, performance, working mechanism, and potential application.
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Affiliation(s)
- Tianda Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA 01003, USA.
| | - Shuai Fu
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA 01003, USA
| | - Jun Yao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA 01003, USA.
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA 01003, USA
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA 01003, USA
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