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基于聚酰胺-胺(PAMAM)树状大分子的机器学习辅助传感器阵列用于诊断阿尔茨海默病。

Machine Learning-Assisted Sensor Array Based on Poly(amidoamine) (PAMAM) Dendrimers for Diagnosing Alzheimer's Disease.

机构信息

State Key Laboratory of Natural Medicines and National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 211109, China.

Ming Wai Lau Centre for Reparative Medicine, Karolinska Institutet, 17177 Stockholm, Sweden.

出版信息

ACS Sens. 2022 May 27;7(5):1315-1322. doi: 10.1021/acssensors.2c00132. Epub 2022 May 18.

Abstract

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, and the early diagnosis of AD remains challenging. Here we have developed a fluorescent sensor array composed of three modified polyamidoamine dendrimers. Proteins of various properties were differentiated via this array with 100% accuracy, proving the rationality of the array's design. The mechanism of the fluorescence response was discussed. Furthermore, the robust three-element array enables parallel detection of multiple Aβ40/Aβ42 aggregates (0.5 μM) in diverse interferents, serum media, and cerebrospinal fluid (CSF) with high accuracy, through machine learning algorithms, demonstrating the tremendous potential of the sensor array in Alzheimer's disease diagnosis.

摘要

阿尔茨海默病(AD)是最常见的神经退行性疾病,AD 的早期诊断仍然具有挑战性。在这里,我们开发了一种由三个修饰的聚酰胺-胺树枝状大分子组成的荧光传感器阵列。通过该阵列以 100%的准确率对具有不同性质的蛋白质进行了区分,证明了该阵列设计的合理性。讨论了荧光响应的机制。此外,稳健的三元阵列通过机器学习算法能够在高浓度的多种干扰物、血清介质和脑脊液(CSF)中同时平行检测多种 Aβ40/Aβ42 聚集物(0.5 μM),具有很高的准确性,展示了该传感器阵列在阿尔茨海默病诊断中的巨大潜力。

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