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机器学习辅助纳米酶/生物酶双重偶联阵列用于快速检测淀粉样蛋白。

Machine Learning-Assisted Nanoenzyme/Bioenzyme Dual-Coupled Array for Rapid Detection of Amyloids.

机构信息

State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China.

Department of Pathology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing 211166, China.

出版信息

Anal Chem. 2023 Mar 14;95(10):4605-4611. doi: 10.1021/acs.analchem.2c04244. Epub 2023 Mar 1.

Abstract

Array-based sensing methods offer significant advantages in the simultaneous detection of multiple amyloid biomarkers and thus have great potential for diagnosing early-stage Alzheimer's disease. Yet, detecting low concentrations of amyloids remains exceptionally challenging. Here, we have developed a fluorescent sensor array based on the dual coupling of a nanoenzyme (AuNPs) and bioenzyme (horseradish peroxidase) to detect amyloids. Various ss-DNAs were bound to the nanoenzyme for regulating enzymatic activity and recognizing amyloids. A simplified sensor array was generated from a screening model via machine learning algorithms and achieved signal amplification through a two-step enzymatic reaction. As a result, our sensing system could discriminate the aggregation species and aggregation kinetics at 200 nM with 100% accuracy. Moreover, AD model mice and healthy mice were distinguished with 100% accuracy through the sensor array, providing a powerful sensing platform for diagnosing AD.

摘要

基于阵列的传感方法在同时检测多种淀粉样蛋白生物标志物方面具有显著优势,因此在诊断早期阿尔茨海默病方面具有很大的潜力。然而,检测低浓度的淀粉样蛋白仍然极具挑战性。在这里,我们开发了一种基于纳米酶(金纳米粒子)和生物酶(辣根过氧化物酶)双重偶联的荧光传感器阵列来检测淀粉样蛋白。各种 ss-DNA 被结合到纳米酶上,以调节酶活性并识别淀粉样蛋白。通过机器学习算法从筛选模型中生成简化的传感器阵列,并通过两步酶反应实现信号放大。结果,我们的传感系统能够以 100%的准确率区分 200 nM 时的聚集物种类和聚集动力学。此外,通过传感器阵列可以 100%准确地区分 AD 模型小鼠和健康小鼠,为 AD 的诊断提供了一个强大的传感平台。

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