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

Anqi YangXiang LinZijian LiuXin DuanYurou YuanJiaxuan ZhangQilin LiangXianglin JiNannan SunHuajun YuWeiwei HeLili ZhuBingzhe XuXudong Lin
Published in: Nano letters (2023)
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.
Keyphrases
  • high throughput
  • bioinformatics analysis
  • machine learning
  • single cell
  • small molecule
  • emergency department
  • healthcare
  • stem cells
  • bone marrow
  • high speed
  • adverse drug