Recognition-Enabled Automated Analyte Identification via 19 F NMR.
Zhenchuang XuSiyi GuYipeng LiJian WuYanchuan ZhaoPublished in: Analytical chemistry (2022)
Nuclear magnetic resonance (NMR) is an indispensable tool for structural elucidation and noninvasive analysis. Automated identification of analytes with NMR is highly pursued in metabolism research and disease diagnosis; however, this process is often complicated by the signal overlap and the sample matrix. We herein report a detection scheme based on 19 F NMR spectroscopy and dynamic recognition, which effectively simplifies the detection signal and mitigates the influence of the matrix on the detection. It is demonstrated that this approach can not only detect and differentiate capsaicin and dihydrocapsaicin in complex real-world samples but also quantify the ibuprofen content in sustained-release capsules. Based on the 19 F signals obtained in the detection using a set of three 19 F probes, automated analyte identification is achieved, effectively reducing the odds of misrecognition caused by structural similarity.
Keyphrases
- magnetic resonance
- loop mediated isothermal amplification
- real time pcr
- machine learning
- high resolution
- label free
- deep learning
- high throughput
- small molecule
- solid state
- bioinformatics analysis
- radiation therapy
- magnetic resonance imaging
- single molecule
- quantum dots
- radiation induced
- single cell
- fluorescent probe