In Nano letters ; h5-index 188.0
Large-scale screening of molecules in organisms requires high-throughput and cost-effective evaluating tools during preclinical development. Here, a novel in vivo screening strategy combining hierarchically structured biohybrid triboelectric nanogenerators (HB-TENGs) arrays with computational bioinformatics analysis for high-throughput pharmacological evaluation using Caenorhabditis elegans is described. Unlike the traditional methods for behavioral monitoring of the animals, which are laborious and costly, HB-TENGs with micropillars are designed to efficiently convert animals' behaviors into friction deformation and result in a contact-separation motion between two triboelectric layers to generate electrical outputs. The triboelectric signals are recorded and extracted to various bioinformation for each screened compound. Moreover, the information-rich electrical readouts are successfully demonstrated to be sufficient to predict a drug's identity by multiple-Gaussian-kernels-based machine learning methods. This proposed strategy can be readily applied to various fields and is especially useful in in vivo explorations to accelerate the identification of novel therapeutics.
Yang Anqi, Lin Xiang, Liu Zijian, Duan Xin, Yuan Yurou, Zhang Jiaxuan, Liang Qilin, Ji Xianglin, Sun Nannan, Yu Huajun, He Weiwei, Zhu Lili, Xu Bingzhe, Lin Xudong
2023-Jan-31
Caenorhabditis elegans, drug screening, high-throughput, microfluidics, triboelectric nanogenerator
