Tissue-like, converged sensing platform for tracking excitation-contraction dynamics in cardiac organoids
- Institution
- University of Massachusetts Amherst, MA
- Principal investigator
- Jun Yao
- Funding
- $400K
- Duration
- 2024–2027
Moonbase score
Still being scored
Abstract
Cardiac diseases are the leading cause of human morbidity and mortality. Drugs also need to be verified to not cause side effect in heart before they can be used clinically. It is inconvenient to study cardiac diseases or test drug effects by using living animals for multiple reasons, including that an animal heart is not that close to a human heart. A convenient strategy is to use heart-mimic tissue outside of the living body made from human-derived cells, which bypasses the use of living life but retains human information for relevant studies. Since the heart beating is coordinated by an electrical signal, it is often desirable to monitor both the mechanical beating and electrical signal together for better assessment of the tissue state involved in various studies. However, current sensing technologies are limited in achieving that—particularly deep inside the tissue—without causing perturbation to the tissue function or health. This project aims to tackle this challenge by developing cell-sized electronic sensors that can simultaneously detect the electrical and mechanical activities in cardiac tissue, incorporating these sensors on small ribbon threads having the lateral width still smaller than a cell, and embedding these threaded sensors into the cardiac tissue for real-time monitoring. For the small form factors in both the sensors and ribbon threads, the system is expected to introduce minimal invasiveness or perturbation to tissue function. Therefore, it will not only acquire enriched signals from both mechanical and electrical activities but also long-term stable monitoring, fundamentally improving the assessment of tissue state involved in cardiac disease studies and drug tests. Eventually, the research contributes to the improvement of cardiac disease remedy and alleviation of healthcare burden. To meet the overall goal, this project will accomplish the following key objectives: 1) A scalable assembly strategy will be developed to fabricate an array of three-dimensional sensor structures using planar semiconducting graphene material. The sensor structure is designed to be able to detect both electrical and mechanical stimuli. 2) These sensor devices will be evaluated for their multifunctional sensing capabilities by culturing planar cardiac tissue on them. 3) A scalable integration method will be developed to integrate these three-dimensional sensors on an ultra-flexible and porous mesh scaffold consisting of individual thin ribbons. 4) The sensor-integrated mesh system will be embedded into three-dimensional cardiac organoids for functional validation and tissue-state evaluation. Success in the research can lead to transformative biomedical devices and cardiac tissue models that have much improved feedback quantifications for various studies. It can also have the long-term potential to translate to implantable biomedical devices for heart monitoring and early disease prediction. The research will also be integrated into education for broadening the participation in science and engineering. 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.
LOADING MOONBASE SCORE
Questions for University of Massachusetts Amherst
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same researchers, same institution, same topic, scored first.
- NSF · University of Massachusetts Amherst56
Innervating stackable neural organoid slices with tissue-like mesh electrodes for improved neural circuit development and characterization
Yubing Sun · $565K · 2024–2027
- NSF · University of Massachusetts AmherstNot yet scored
ASCENT: Developing heterogeneous integration of Air-gen technology for the ubiquitous powering of semiconductor systems
Jun Yao · $1.5M · 2025–2029
- NSF · University of Massachusetts Amherst69
CAREER: Aquatic Therapy Assist-Tool Using a Real-Time Underwater Physiological and Musculokinetic Monitoring in Personalized Stroke Rehabilitation
Yeonsik Noh · $550K · 2023–2028