Machine Learning-Assisted Nanoenzyme/Bioenzyme Dual-Coupled Array for Rapid Detection of Amyloids.
Yu XuCheng QianYang YuShijie YangFangfang ShiLian XuXu GaoYuhang LiuHui HuangCallum StewartFei LiJinsong HanPublished in: Analytical chemistry (2023)
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.
Keyphrases
- machine learning
- high throughput
- high resolution
- early stage
- hydrogen peroxide
- high density
- artificial intelligence
- high fat diet induced
- deep learning
- big data
- label free
- nitric oxide
- quantum dots
- adipose tissue
- squamous cell carcinoma
- lymph node
- single cell
- living cells
- mass spectrometry
- room temperature
- sentinel lymph node
- neoadjuvant chemotherapy
- electron transfer