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CRISPR-Enhanced Photocurrent Polarity Switching for Dual-lncRNA Detection Combining Deep Learning for Cancer Diagnosis.
Yang, Ruiying; Ji, Jiangying; Ding, Lihua; Yuan, Xinxin; Qu, Lingbo; Wu, Yongjun; Li, Yuling.
Afiliação
  • Yang R; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
  • Ji J; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
  • Ding L; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
  • Yuan X; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
  • Qu L; College of Chemistry, Zhengzhou University, Zhengzhou 450001, China.
  • Wu Y; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
  • Li Y; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Anal Chem ; 2024 Aug 02.
Article em En | MEDLINE | ID: mdl-39092917
ABSTRACT
Abnormal expression in long noncoding RNAs (lncRNAs) is closely associated with cancers. Herein, a novel CRISPR/Cas13a-enhanced photocurrent-polarity-switching photoelectrochemical (PEC) biosensor was engineered for the joint detection of dual lncRNAs, using deep learning (DL) to assist in cancer diagnosis. After target lncRNA-activated CRISPR/Cas13a cleaves to induce DNAzyme bidirectional walkers with the help of cofactor Mg2+, nitrogen-doped carbon-Cu/Cu2O octahedra are introduced into the biosensor, producing a photocurrent in the opposite direction of CdS quantum dots (QDs). The developed PEC biosensor shows high specificity and sensitivity with limits of detection down to 25.5 aM for lncRNA HOTAIR and 53.1 aM for lncRNA MALAT1. More importantly, this platform for the lncRNA joint assay in whole blood can successfully differentiate cancers from healthy people. Furthermore, the DL model is applied to explore the potential pattern hidden in data of the established technology, and the accuracy of DL cancer diagnosis can acquire 93.3%. Consequently, the developed platform offers a new avenue for lncRNA joint detection and early intelligent diagnosis of cancer.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Anal Chem Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Anal Chem Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China