A novel LoC-SERS device integrated with aptamer recognition strategy for the highly sensitive and specific detection of thrombin and platelet-derived growth factor-B. (25th January 2023)

• Record Type: Journal Article
• Authors: Zhu, Jinhua; Shi, Ruihua; Qian, Yayun; Hua, Zhaolai; Feng, Xiang; Chen, Hong; Cao, Xiaowei; Feng, Yadong; Yu, Ting; Lu, Qin
• Is Part Of: New journal of chemistry. Volume 47:Number 7(2023)
• Page Start: 3481
• Page End: 3491
• Publication Date: 2023-01-25
• Subjects: Chemistry -- Periodicals; Chimie -- Périodiques; 540
• DOI: 10.1039/d2nj05214h
• Languages: English
• ISSNs: 1144-0546

Abstract

Abstract : A LoC-SERS device integrated with aptamer recognition strategy for the highly sensitive and specific detection of thrombin and platelet-derived growth factor-B. Abstract : Detection of tumor biomarkers is of great significance for early diagnosis of cancer. Herein, we fabricated a novel lab-on-a chip surface-enhanced Raman scattering (SERS) (LoC-SERS) biosensing platform for highly sensitive and specific detection of thrombin and platelet-derived growth factor-B (PDGF-B) using aptamer recognition technology. This strategy relies on the specific aptamer recognition between SERS probes (Ag–Au core–shell nanorods (Ag–AuNRs) modified with Raman reporter molecules and detection aptamer) and SERS capture substrate (Au nanoflower (AuNF) substrates modified with capture aptamer), which significantly amplify the plasmonic coupling effect that allows the ultrasensitive and high specificity SERS detection. The limits of detection (LODs) are as low as 3.62 fM for thrombin and 2.86 fM for PDGF-B. Such LoC-SERS platform is further employed to simultaneously detect two types of gastric carcinoma-related with high sensitivity and specificity, which meanwhile exhibit robust capacity of resisting disturbance in practical samples. The results revealed that the present LoC-SERS platform displayed excellent analytical performance, including superior reproducibility, specificity, and sensitivity. Satisfactory results were obtained in real sample analysis with the LoC-SERS platform.