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.
| Original language | English |
|---|---|
| Pages (from-to) | 1280–1288 |
| Journal | Nano Letters |
| Volume | 23 |
| Issue number | 4 |
| Online published | 31 Jan 2023 |
| DOIs | |
| Publication status | Published - 22 Feb 2023 |
Research Keywords
- triboelectric nanogenerator
- microfluidics
- Caenorhabditis elegans
- high-throughput
- drug screening
- CAENORHABDITIS-ELEGANS
- BEHAVIORAL-ANALYSIS
- SMALL MOLECULES
- IDENTIFICATION
- CAFFEINE