Traditional Chinese medicines (TCMs) are highly valued and widely used worldwide. However, their complex compositions and various preparation processes have brought considerable challenges to the quality evaluation of Chinese medicines. The traditional methods for TCM quality evaluation suffer from the problems of cumbersome sample preparation, a long detection time, low sensitivity, etc. A more efficient and accurate evaluation method is urgently needed to ensure the stability and reliability of the quality of TCMs. As an emerging analytical technology, a fluorescent probe has the advantages of high sensitivity, high selectivity, easy operation, etc. It is capable of generating a specific fluorescent signal response to specific components in traditional Chinese medicines, realizing rapid and accurate detection of target components, which effectively solves the many difficulties of traditional methods. The purpose of this paper is to discuss the application of fluorescent probes in the quality evaluation of traditional Chinese medicines and the challenges they face. By introducing the principles, advantages and specific application cases of fluorescent probe technology in the quality evaluation of traditional Chinese medicines, we hope to provide new and efficient analytical ideas for the quality evaluation of traditional Chinese medicines.

In the clinical application of Traditional Chinese Medicine (TCM) substitutes, the consistency evaluation of TCM substitutes from different sources is recognized as the main bottleneck. As the most widely used analytical method in TCM consistency evaluation, fingerprint similarity evaluation suffers from insufficient method sensitivity and poor conformity with the actual characteristics of TCM, which is difficult to adapt to the analytical needs of complex substance systems of TCM. This work aims to develop an effective and more accurate method for consistency evaluation using omics strategy and machine learning algorithms. The natural calculus bovis (NCB) were graded into three groups according to the similarity to in vitro cultured bovis (IVCB), and chemical markers between samples of each grade were screened out. Support vector machine (SVM) models with different kernels were then constructed by using the chemical markers as feature variables. The results showed that the classification accuracy of the SVM classifier of NCB and the consistency evaluation SVM model classifier was 95.74% and 100.0%, respectively. The approach demonstrated in the study presented a good analytical performance with higher sensitivity, accuracy for consistency evaluation of TCM.

As a Mongolian native medicine and Ewenki folk medicinal plant, Gentianella acuta has been widely used for the treatment of diarrhea, hepatitis, arrhythmia, and coronary heart disease. In the course of investigating efficacy compounds to treat diarrhea using a mouse isolated intestine tissue model, we found 70% EtOH extract of G. acuta whole plants had an inhibitory effect on intestine contraction tension. Here, nineteen constituents, including five new compounds, named as gentiiridosides A (1), B (2), gentilignanoside A (3), (1R)-2,2,3-trimethyl-4-hydroxymethylcyclopent-3-ene-1-methyl-O-β-d-glucopyranoside (4), and (3Z)-3-hexene-1,5-diol 1-O-α-l-arabinopyranosyl(1→6)-β-d-glucopyranoside (5) were obtained from it. The structures of them were elucidated by chemical and spectroscopic methods. Furthermore, the inhibitory effects on motility of mouse isolated intestine tissue of the above mentioned compounds and other thirteen iridoid- and secoiridoid-type monoterpenes (7–10, 13–16, 18, 19, 21, 22, and 25) previously obtained in the plant were analyzed. As results, new compound 5, some secoiridoid-type monoterpenes 7, 10, 12–14, 16, and 17, as well as 7-O-9′-type lignans 31 and 32 displayed significant inhibitory effect on contraction tension at 40 μM.