Biohybrid Triboelectric Nanogenerator for Label-Free Pharmacological Fingerprinting in Cardiomyocytes.
Xianglin JiPeilin FangBingzhe XuKai XieHaibing YueXuan LuoZixun WangXi ZhaoPeng ShiPublished in: Nano letters (2020)
The development of new drugs requires high-throughput and cost-effective pharmacological assessment in relevant biological models. Here, we introduce a novel pharmacological screening platform that combines a biohybrid triboelectric nanogenerator (TENG) and informatic analysis for self-powered, noninvasive, and label-free biosensing in cardiac cells. The cyclic mechanical activity of functional cardiomyocytes is dynamically captured by a specially designed biohybrid TENG device and is analyzed by a custom-made machine learning algorithm to reveal distinctive fingerprints in response to different pharmacological treatment. The core of the TENG device is a multilayer mesh substrate with microscale-gapped triboelectric layers, which are induced to generate electrical outputs by the characteristic motion of cardiomyocytes upon pharmaceutical treatment. Later bioinformatic extraction from the recorded TENG signal is sufficient to predict a drug's identity and efficacy, demonstrating the great potential of this platform as a biocompatible, low-cost, and highly sensitive drug screening system.
Keyphrases
- label free
- high throughput
- machine learning
- low cost
- high glucose
- drug induced
- induced apoptosis
- mass spectrometry
- left ventricular
- deep learning
- gene expression
- endothelial cells
- diabetic rats
- heart failure
- risk assessment
- ionic liquid
- climate change
- high resolution
- electronic health record
- tandem mass spectrometry
- neural network