摘要
Detection of sialic acid (SA) is crucial for the early diagnosis of ovarian cancer. In this study, we present the construction of a novel boronic acid functionalized covalent organic framework (TMTA-PBA-COF) for the first time for the accurate detection of SA. By combining the excellent luminescent properties of TMTA-COF with the specific binding capability of the boronic acid moiety to the cis-diol moiety in SA, the constructed fluorescent sensor achieved a sensitive and selective detection of SA in human serum within the linear range of 1–500 μM with a low detection limit of 0.45 μM. Crucially, we also established an intelligent back propagation neural network model to process the fluorescence sensing results, enabling accurate identification of SA concentrations through deep machine learning without cumbersome data processing. In addition, the practical application of TMTA-PBA-COF is extended to the visual identification of latent fingerprints. This work provides an intelligent and efficient analytical method for the early diagnosis of ovarian cancer and expands the multifunctional application of the material.
危险品化学品经营许可证(带存储)