The fraud phenomenon is currently widespread in the traditional Chinese medicine Radix Astragali (RA) market, especially where high-quality RA is substituted with low-quality RA. In this case, focused on polysaccharides from RA, the classification models were established for discrimination of RA from different growth patterns, origins, species, and growth years. 1H Nuclear Magnetic Resonance (H¹-NMR) was used to establish the spectroscopy of polysaccharides from RA, which were used to distinguish RA via chemical pattern recognition methods. Specifically, orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were used to successfully establish the classification models for RA from different growth patterns, origins, species, and growth years. The satisfactory parameters and high accuracy of internal and external verification of each model exhibited the reliable and good prediction ability of the developed models. In addition, the polysaccharide content and immunological activity were also tested, which was evaluated by the phagocytic activity of RAW 264.7. And the result showed that growth patterns and origins significantly affected the quality of RA. However, there was no significant difference in the aspects of origins and growth years. Accordingly, the developed strategy combined with chemical information, biological activity, and multivariate statistical method can provide new insight for the quality evaluation of traditional Chinese medicine.

Exogenous contaminants in traditional Chinese medicine (TCM), including pesticide residues, heavy metals, mycotoxins, and sulfur dioxide residues, pose significant risks to human health and environmental safety. Conventional detection methods are limited by insufficient sensitivity, complex sample preparation, and challenges in multi-residue analysis, compromising accuracy and efficiency. To address these critical bottlenecks—particularly the escalating regulatory demands and trade barriers due to contamination incidents—this review establishes the first integrated ‘dual track’ quality control framework for TCM contaminants. We propose a novel risk stratified strategy synergizing laboratory grade accuracy with field deployable screening, overcoming the sensitivity portability trade-off. This work provides a roadmap for establishing globally harmonized standards. Future research should prioritize high-throughput methods, intelligent analytics, and green detection technologies. Integrating AI-driven automation with data traceability could establish unified systems for contaminant detection and degradation, enhancing TCM quality control and global competitiveness.

This study explores the antifungal properties of Agaricus blazei Murrill, a valuable medicinal and edible fungus. Six compounds (1–6) were first isolated from A. blazei using various isolation techniques and identified using spectroscopic methods. These compounds include linoleic acid, 1,1′-oxybis(2,4-di-tert-butylbenzene), glycerol monolinoleate, volemolide (17R)-17-methylincisterol, (24s)-ergosta-7-en-3-ol, and dibutyl phthalate. This study also assesses the antifungal activities of these compounds against Trichophyton mentagrophology, Trichophyton rubrum, Candida albicans, and Cryptococcus neoformans. The results demonstrate varied sensitivities against these pathogenic fungi, with compound 2 showing significant inhibition against T. mentagrophology, compound 3 showing significant inhibition against T. rubrum, and compound 6 showing significant inhibition against C. albicans. This study underscores the medicinal potential of A. blazei as an antifungal agent and sheds light on its valuable research implications.

With the escalating demand for Astragalus polysaccharides products developed from Radix Astragali (RA), the necessity for quality control of polysaccharides in RA has become increasingly urgent. In this study, a specific method for the simultaneous determination of seven monosaccharides in polysaccharides extracted from Radix Astragali (RA) has been developed and validated using ultra-performance liquid chromatography equipped with an ultraviolet detector (UHPLC-UV) for the first time. The 1-phenyl-3-methyl-5-pyrazolone (PMP) derivatizations were separated on a C18 column (Waters ACQUITY^TM, Milfor, MA, USA, 1.8 µm, 2.1 × 100 mm) using gradient elution with a binary system of 5 mm ammonium formate (0.1% formic acid)-acetonitrile for 24 min. Additionally, seven monosaccharides showed good linear relationships (R², 0.9971–0.9995), adequate precision (RSD < 4.21%), and high recoveries (RSD < 4.70%). The established method was used to analyze 109 batches of RA. Results showed that the Astragalus polysaccharides (APSs) mainly consist of mannose (Man), rhamnose (Rha), glucose (Glu), galactose (Gal), arabinose (Ara), xylose (Xyl); and fucose (Fuc); however, their composition was different among RA samples from different growth patterns, species, growth years, and origins, and the growth mode of RA and the age of wild-simulated RA can be accurately distinguished by principal component analysis (PCA). In addition, the immunological activity of APSs were also evaluated jointly by measurement of the NO release with RAW264.7, with the results showing that APSs have a promoting effect on the release of NO and exhibit a significant correlation with Man, Glu, Xyl, and Fuc contents. Accordingly, the new established monosaccharides analytical method and APS-immune activity determination in this study can provide a reference for quality evaluation and the establishment of quality standards for RA.

Lonicerae japonicae flos and Lonicerae flos are increasingly widely used in food and traditional medicine products around the world. Due to their high demand and similar appearance, they are often used in a confused or adulterated way; therefore, a rapid and comprehensive analytical method is highly required. In this case, the comparative analysis of a total of 100 samples with different species, growth modes, and processing methods was carried out by nuclear magnetic resonance (¹H-NMR) spectroscopy and chemical pattern recognition analysis. The obtained ¹H-NMR spectrums were employed by principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA). Specifically, after the dimensionality reduction of data, linear discriminant analysis (LDA) exhibited good classification abilities for the species, growth modes, and processing methods. It is worth noting that the sample prediction accuracy from the testing set and the cross-validation predictions of the LDA models were higher than 95.65% and 98.1%, respectively. In addition, the results showed that macranthoidin A, macranthoidin B, and dipsacoside B could be considered as the main differential components of Lonicerae japonicae flos and Lonicerae Flos, while secoxyloganin, secologanoside, and sweroside could be responsible for distinguishing cultivated and wild Lonicerae japonicae Flos. Accordingly, ¹H-NMR spectroscopy combined with chemical pattern recognition gives a comprehensive overview and provides new insight into the quality control and evaluation of Lonicerae japonicae flos.

Sample pretreatment plays an important role in analytical performance, but it is often the rate-limiting step in scientific research. With the development of automation technology, automated sample preparation has become a powerful tool for liberating labor and improving efficiency. In this study, the automatic pretreatment of traditional Chinese medicine test was realized by module combination, and an intelligent robotic platform Alpha Test 1 was developed to decompose the complex preparation method of traditional Chinese medicine into automatic modular components. It includes a multi-channel liquid feeding device, an extraction bottle device, a reflux condensing pipe ring, a reflux extraction and a water bath extraction device. Each module is connected through modular combinations such as liquid injection control, intelligent sorting, and water bath condensation, and the difficulty of manual operation is gradually tackled to achieve the goal of replacing manual labor in the pretreatment process. We selected two representative traditional Chinese medicines, Xianglian Pills and Erzhi Pills, to explore their application in the testing of traditional Chinese medicine. The results of Alpha Test 1 in the identification and content determination met the requirements of Chinese Pharmacopoeia, and the operation was simple, rapid and efficient compared with the manual pretreatment method. This method can meet the requirements of daily laboratory testing and provide technical support for the quality control evaluation and testing of traditional Chinese medicine.