Liu Junjie, Geng Qingfubo, Geng Zhaoxin
School of Information Engineering, Minzu University of China, Beijing 100081, China.
Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing 100081, China.
Micromachines (Basel). 2024 Aug 31;15(9):1116. doi: 10.3390/mi15091116.
Alpha-fetoprotein (AFP) is a key marker for early cancer detection and assessment. However, the current detection methods struggle to balance accuracy with the need for decentralized medical treatment. To address this issue, a new AFP analysis platform utilizing digital image colorimetry has been developed. Functionalized gold nanoparticles act as colorimetric agents, changing from purple-red to light gray-blue when exposed to different AFP concentrations. A smartphone app captures these color changes and calculates the AFP concentration in the sample. To improve detection accuracy, a hardware device ensures uniform illumination. Testing has confirmed that this system can quantitatively analyze AFP using colorimetry. The limit of detection reached 0.083 ng/mL, and the average accuracy reached 90.81%. This innovative method enhances AFP testing by offering portability, precision, and low cost, making it particularly suitable for resource-limited areas.
甲胎蛋白(AFP)是早期癌症检测和评估的关键标志物。然而,当前的检测方法难以在准确性与分散医疗需求之间取得平衡。为解决这一问题,已开发出一种利用数字图像比色法的新型AFP分析平台。功能化金纳米颗粒用作比色剂,在暴露于不同AFP浓度时从紫红色变为浅灰蓝色。一款智能手机应用程序捕捉这些颜色变化并计算样品中的AFP浓度。为提高检测准确性,一种硬件设备可确保均匀照明。测试已证实该系统能够使用比色法对AFP进行定量分析。检测限达到0.083 ng/mL,平均准确率达到90.81%。这种创新方法通过提供便携性、精确性和低成本增强了AFP检测,使其特别适用于资源有限的地区。