已核实 DOI 相关产品: 95

Engineered rGO-AuNPs@MXene hybrid nanocomposites for highly efficient electrochemical aptasensing of alpha-fetoprotein

Journal 2025 · IF 5.1 · 发表于 2025 年 5 月 13 日
作者: Imamdin Chandio,Suet Cheung,Lei Wu,Mengyang Cui,Yongjian Ai,Qionglin Liang
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摘要

Early detection of cancer is critical for reducing mortality and improving patient outcomes, yet it remains a challenge due to limitations in existing diagnostic methods. Alpha-fetoprotein (AFP), a glycoprotein predominantly produced during fetal development, has emerged as a vital biomarker for diagnosing cancers such as hepatocellular carcinoma (HCC), germ cell tumours, and yolk sac tumours. However, conventional methods for AFP detection, including immunoassays and enzyme-linked techniques, face challenges such as high costs and limited sensitivity. Here, we have developed a novel label-free electrochemical aptasensor based on a reduced graphene oxide-gold nanoparticle-MXene composite (rGO-AuNPs@MXene). This hybrid material leverages the high conductivity and catalytic activity of AuNPs, the large surface area and stability of rGO, and the exceptional electrochemical properties of MXenes. The rGO-AuNPs@MXene based composite offers high sensitivity, excellent selectivity, and favorable biocompatibility for the detection of AFP. NH 2 -aptamers were immobilized onto the rGO-AuNPs@MXene-modified electrode, enabling precise AFP recognition through specific aptamer-target interactions. The aptasensor demonstrated a broad detection range (10 fg mL −1 to 1 μg mL −1 ), with an ultra-low limit of detection of 13.91 fg mL −1 (S/N = 3). It demonstrated excellent stability, with only a 3.80 % decrease in signal after 8 days of storage, and remarkable reproducibility, showing a relative standard deviation of 1.85 % across five electrodes. These findings emphasize the remarkable efficiency of the rGO-AuNPs@MXene composite in producing highly sensitive and reliable electrochemical aptasensors. This innovation underscores its substantial potential for advancing early cancer detection and improving clinical diagnosis.

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