Graphene-integrated mesh electronics with converged multifunctionality for tracking multimodal excitation-contraction dynamics in cardiac microtissues
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-...
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| Published in | Nature communications Vol. 15; no. 1; pp. 2321 - 12 |
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| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
14.03.2024
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
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| 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.
Tracking electrical and mechanical activity in in-vitro cardiac microtissues is challenging. Here, authors develop tissue-like electronics that can ‘grow’ with the cardiac microtissues and realize the simultaneous tracking of both signals. |
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| AbstractList | 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. 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. 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.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. 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.Tracking electrical and mechanical activity in in-vitro cardiac microtissues is challenging. Here, authors develop tissue-like electronics that can ‘grow’ with the cardiac microtissues and realize the simultaneous tracking of both signals. 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. Tracking electrical and mechanical activity in in-vitro cardiac microtissues is challenging. Here, authors develop tissue-like electronics that can ‘grow’ with the cardiac microtissues and realize the simultaneous tracking of both signals. |
| ArticleNumber | 2321 |
| Author | Wang, Zhien Yao, Jun Wang, Siqi Kong, Jing Gao, Hongyan Wang, Xiaoyu Sun, Yubing Yang, Feiyu Liu, Xiaomeng Zhang, Quan |
| Author_xml | – sequence: 1 givenname: Hongyan surname: Gao fullname: Gao, Hongyan organization: Department of Electrical and Computer Engineering, University of Massachusetts – sequence: 2 givenname: Zhien surname: Wang fullname: Wang, Zhien organization: Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology – sequence: 3 givenname: Feiyu orcidid: 0000-0002-9825-8055 surname: Yang fullname: Yang, Feiyu organization: Department of Mechanical and Industrial Engineering, University of Massachusetts – sequence: 4 givenname: Xiaoyu surname: Wang fullname: Wang, Xiaoyu organization: Department of Electrical and Computer Engineering, University of Massachusetts – sequence: 5 givenname: Siqi surname: Wang fullname: Wang, Siqi organization: Department of Electrical and Computer Engineering, University of Massachusetts – sequence: 6 givenname: Quan surname: Zhang fullname: Zhang, Quan organization: Department of Electrical and Computer Engineering, University of Massachusetts – sequence: 7 givenname: Xiaomeng orcidid: 0000-0003-1463-9916 surname: Liu fullname: Liu, Xiaomeng organization: Department of Electrical and Computer Engineering, University of Massachusetts – sequence: 8 givenname: Yubing orcidid: 0000-0002-6831-3383 surname: Sun fullname: Sun, Yubing organization: Department of Mechanical and Industrial Engineering, University of Massachusetts, Institute for Applied Life Sciences, University of Massachusetts, Department of Biomedical Engineering, University of Massachusetts – sequence: 9 givenname: Jing orcidid: 0000-0003-0551-1208 surname: Kong fullname: Kong, Jing organization: Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology – sequence: 10 givenname: Jun orcidid: 0000-0002-5269-3190 surname: Yao fullname: Yao, Jun email: juny@umass.edu organization: Department of Electrical and Computer Engineering, University of Massachusetts, Institute for Applied Life Sciences, University of Massachusetts, Department of Biomedical Engineering, University of Massachusetts |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38485708$$D View this record in MEDLINE/PubMed |
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| Title | Graphene-integrated mesh electronics with converged multifunctionality for tracking multimodal excitation-contraction dynamics in cardiac microtissues |
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