Worm Generator : A System for High-Throughput in Vivo Screening

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

6 Scopus Citations
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Author(s)

  • Anqi Yang
  • Xiang Lin
  • Zijian Liu
  • Xin Duan
  • Yurou Yuan
  • Jiaxuan Zhang
  • Qilin Liang
  • Nannan Sun
  • Huajun Yu
  • Weiwei He
  • Lili Zhu
  • Bingzhe Xu
  • Xudong Lin

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1280–1288
Journal / PublicationNano Letters
Volume23
Issue number4
Online published31 Jan 2023
Publication statusPublished - 22 Feb 2023

Abstract

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 nano-generators (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. © 2023 American Chemical Society.

Research Area(s)

  • triboelectric nanogenerator, microfluidics, Caenorhabditis elegans, high-throughput, drug screening, CAENORHABDITIS-ELEGANS, BEHAVIORAL-ANALYSIS, SMALL MOLECULES, IDENTIFICATION, CAFFEINE

Citation Format(s)

Worm Generator: A System for High-Throughput in Vivo Screening. / Yang, Anqi; Lin, Xiang; Liu, Zijian et al.
In: Nano Letters, Vol. 23, No. 4, 22.02.2023, p. 1280–1288.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review