Autor: |
Song Ge, Mingxin Wang, Shunhua Zhu, Han Wu, Jing Li, Dongsheng Liu, Qingli Huang, Shibao Li, Xiaojing Sun |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Sensors and Actuators Reports, Vol 7, Iss , Pp 100198- (2024) |
Druh dokumentu: |
article |
ISSN: |
2666-0539 |
DOI: |
10.1016/j.snr.2024.100198 |
Popis: |
Purpose: As an important reference index for the early diagnosis of non-small cell lung cancer (NSCLC), CYFRA21-1 still lacks the detection of low equipment cost, wide linear range and high sensitivity. Surface-enhanced Raman scattering (SERS) is a vibration spectrum technology based on the surface plasma of precious metal nanoparticles, which has been effectively applied to the detection of tumor markers. The combination of SERS technology and sensors has great potential in the ultrasensitive detection of tumor markers. The purpose of this study was to develop a sensitive method using SERS to quantitatively detect CYFRA21-1 for early diagnosis of NSCLC. Methods: A double-antibody sandwich immunoassay based on SERS was designed and tested to implement the ultrasensitive detection of CYFRA21-1 in the serum of NSCLC patients. Results: Gold @Ag nanorods (Au @Ag NRs) with higher Raman signals were prepared and used as probes, while magnetic graphene oxide was used as a magnetic substrate. The immunized probe, immune substrate and CYFRA21-1 standard substance in the buffer system formed a double-antibody sandwich structure. The standard curve displayed a liner range from 1pg mL−1 to 10 ng mL−1, and the detection limit (LOD) is 0.8943pg mL−1. The Raman intensity exhibited a wide linear relationship with the logarithm of CYFRA21-1 concentration. Conclusion: Our study successfully established a double-antibody sandwich immunoassay based on SERS. This method demonstrated high specificity and sensitivity for detecting CYFRA21-1 protein content in serum. It has the potential to be applied for early detection of lung cancer biomarkers. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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