CPS: Medium: An AI-enabled Cyber-Physical-Biological System for Cardiac Organoid Maturation
CPS: Medium: An AI-enabled Cyber-Physical-Biological System for Cardiac Organoid Maturation
批准号:
2038603
负责人:
Jia Liu
金额:
$89.82万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-15 至 2023-08-31
中文摘要
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英文摘要
The ability to determine and control the maturation of human-induced pluripotent stem cell (hiPSC) derived tissues is critical to tissue engineering, regenerative medicine, pharmacology, and synthetic biology, which requires the interrogation and intervention of cellular activities across the three-dimensional (3D) volume of tissues and over the time course of tissue development at cellular resolution. This proposal aims to build an AI-enabled cyber-physical-biological system to monitor and control the maturation of hiPSC derived cardiomyocyte (hiPSC-CM) organoids during development. The proposed research will develop “tissue-like” nanoelectronics that can be integrated into the developing cardiac organoids, distributing the electronic sensor and actuator network throughout the entire 3D volume of the tissue and enabling tissue-level recording and control over the entire time course of development at single-cell resolution. In situ single-cell RNA sequencing will be used to integrate gene expression data with continuous physical sensing data. Machine learning and statistical models will be built for interpreting the online sensing data, and cyber-control methods will be developed for the closed-loop online control of the cardiac organoid maturation. The developed hardware and software can be applied to virtually any current biological systems, in which the change of cellular states can be reliably recorded and controlled through the electronic sensors and actuators. The success of this proposal will further merge the field of AI, nanoelectronics, and biology, bringing unlimited opportunities for access and control to biological and biomedical engineering. The multidisciplinary teamwork will represent a successful case that schools of thought from diverse fields including bioengineering, machine learning, statistics, control theory, etc. inspire and complement each other to create state-of-the-art research results in each field. The research team will also collaborate with internal and external partners to launch educational and societal activities for students from diverse backgrounds, such as providing e-seminars, workshops and new courses for undergraduate students on advanced nanoelectronics fabrication, and workshops and tours for local K-12 students to explore stem cell culture, online videos to disseminate new research in genomics, mathematical and computational modeling, integration of AI, nanoelectronics, and biology.We propose to develop a seamless integration of cyber-physical systems with biological systems, enabling a closed-loop control, capable of real-time, bidirectionally, and long-term stably interrogating and intervening cellular activities across the 3D volume of tissue networks at single-cell resolution. As a demonstration, we will apply this cyber-physical-biological system to the hiPSC-CM organoids, promoting and accelerating their maturation. We will achieve our goal through the following 4 technical innovations: (A) developing technologies to integrate stretchable mesh nanoelectronics with multifunctional sensors and actuators to the cardiac organoids, enabling real-time monitoring and control of organoid development; (B) precisely registering electronic sensors during in situ single-cell RNA sequencing to determine the molecular maturation of cardiac organoids and correlate spatial gene expression profiling with sensing data at single-cell resolution; (C) developing novel machine learning models and tools to identify the statistical interference between gene expression and organoid-wide electrical and mechanical recording and also building online predictive models to real-time determine the maturation of cardiac organoids; (D) developing effective and scalable Reinforcement Learning (RL) methods to determine optimized electrical activation patterns to promote the maturation of cardiac organoids and to test its performance in patient-specific cardiac organoids.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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DOI:
10.1287/opre.2021.2226
发表时间:
2019-12
期刊:
Oper. Res.
影响因子:
--
作者:
[Guannan Qu;A. Wierman;N. Li]
通讯作者:
Guannan Qu;A. Wierman;N. Li
Tissue-embedded stretchable nanoelectronics reveal endothelial cell-mediated electrical maturation of human 3D cardiac microtissues.
组织包裹的可拉伸纳米电子学揭示了内皮细胞介导的人类3D心脏微动物的电气成熟。
DOI:
10.1126/sciadv.ade8513
发表时间:
2023-03-10
期刊:
SCIENCE ADVANCES
影响因子:
13.6
作者:
[Lin, Zuwan, Garbern, Jessica C., Liu, Ren, Li, Qiang, Juncosa, Estela Mancheno, Elwell, Hannah L. T., Sokol, Morgan, Aoyama, Junya, Deumer, Undine-Sophie, Hsiao, Emma, Sheng, Hao, Lee, Richard T., Liu, Jia]
通讯作者:
Liu, Jia
DOI:
10.1016/j.automatica.2022.110741
发表时间:
2023
期刊:
Automatica
影响因子:
6.4
作者:
[Tang, Yujie, Ren, Zhaolin, Li, Na]
通讯作者:
Li, Na
DOI:
10.1016/j.cell.2023.03.023
发表时间:
2023-04
期刊:
Cell
影响因子:
64.5
作者:
[Qiang Li;Zuwan Lin;Ren Liu;Xin-Hui Tang;Jiahao Huang;Yichun He;Xin Sui;Weiwen Tian;Haolan Shen;Haowen Zhou;Hao Sheng;Hailing Shi;Li Xiao;Xiao Wang;Jia Liu]
通讯作者:
Qiang Li;Zuwan Lin;Ren Liu;Xin-Hui Tang;Jiahao Huang;Yichun He;Xin Sui;Weiwen Tian;Haolan Shen;Haowen Zhou;Hao Sheng;Hailing Shi;Li Xiao;Xiao Wang;Jia Liu
Score-Based Hypothesis Testing for Unnormalized Models
非标准化模型的基于分数的假设检验
DOI:
10.1109/access.2022.3187991
发表时间:
2022
期刊:
IEEE Access
影响因子:
3.9
作者:
[Wu, Suya, Diao, Enmao, Elkhalil, Khalil, Ding, Jie, Tarokh, Vahid]
通讯作者:
Tarokh, Vahid
共 12 条
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批准号:2338987
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项目类别:Standard Grant
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资助金额:$20.0万
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财政年份:2023
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负责人:Jia Liu
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ERASE-PFAS: Exploring efficient pilot-scale treatment of per- and polyfluoroalkyl substances and comingled chlorinated solvents in groundwater using magnetic nanomaterials
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FMSG: Cyber: Federated Deep Learning for Future Ubiquitous Distributed Additive Manufacturing
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Preparing to Care for a Culturally and Linguistically Diverse UK Patient Population: How Healthcare Students Develop Their Cultural Competence
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财政年份:2021
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SpecEES: Toward Spectral and Energy Efficient Cross-Layer Designs for Millimeter-Wave-Based Massive MIMO Networks
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批准号:2140277
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资助金额:$55.0万
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负责人:Jia Liu
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依托单位:
CAREER: Computing-Aware Network Optimization for Efficient Distributed Data Analytics at the Wireless Edge
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批准号:2110259
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项目类别:Continuing Grant
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资助金额:$52.41万
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财政年份:2020
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负责人:Jia Liu
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依托单位:
NeTS: Small: Toward Optimal, Efficient, and Holistic Networking Design for Massive-MIMO Wireless Networks
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批准号:2102233
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项目类别:Standard Grant
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CAREER: Computing-Aware Network Optimization for Efficient Distributed Data Analytics at the Wireless Edge
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负责人:Jia Liu
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依托单位:
CIF: Small: Taming Convergence and Delay in Stochastic Network Optimization with Hessian Information
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资助金额:$31.79万
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NeTS: Small: Toward Optimal, Efficient, and Holistic Networking Design for Massive-MIMO Wireless Networks
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资助金额:$55.0万
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SpecEES: Toward Spectral and Energy Efficient Cross-Layer Designs for Millimeter-Wave-Based Massive MIMO Networks
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资助金额:$55.0万
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CIF: Small: Taming Convergence and Delay in Stochastic Network Optimization with Hessian Information
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项目类别:Standard Grant
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资助金额:$31.79万
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财政年份:2017
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依托单位:
Cosmology in the Non-Linear Regime with Weak Gravitational Lensing
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批准号:1602663
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资助金额:$8.9万
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项目类别:Standard Grant
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资助金额:$31.79万
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NeTS: Small: Toward Optimal, Efficient, and Holistic Networking Design for Massive-MIMO Wireless Networks
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批准号:1527078
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项目类别:Standard Grant
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资助金额:$30.0万
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财政年份:2015
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SBIR Phase I: Novel Utilization of Fly Ash using a Sustainable Process
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资助金额:$15.0万
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负责人:Jia Liu
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依托单位:
NSF East Asia and Pacific Summer Institute for FY 2012 in Japan
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批准号:1209836
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项目类别:Fellowship Award
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资助金额:$0.58万
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财政年份:2012
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负责人:Jia Liu
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依托单位:
海外基金