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Worm Generator: A System for High-Throughput in Vivo Screening.
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.
Afiliación
  • Yang A; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Lin X; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Liu Z; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Duan X; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Yuan Y; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Zhang J; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Liang Q; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Ji X; Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China.
  • Sun N; Department of Biochemistry and Molecular Biology, Guangdong Medical University, Zhanjiang 524023, China.
  • Yu H; Department of Biochemistry and Molecular Biology, Guangdong Medical University, Zhanjiang 524023, China.
  • He W; School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Zhu L; School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Xu B; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
  • Lin X; Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China.
Nano Lett ; 23(4): 1280-1288, 2023 02 22.
Article en En | MEDLINE | ID: mdl-36719250
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Caenorhabditis elegans Tipo de estudio: Diagnostic_studies / Screening_studies Límite: Animals Idioma: En Revista: Nano Lett Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Caenorhabditis elegans Tipo de estudio: Diagnostic_studies / Screening_studies Límite: Animals Idioma: En Revista: Nano Lett Año: 2023 Tipo del documento: Article País de afiliación: China
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