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Type 2 diabetes mellitus (T2DM) is a metabolic disease with persistent hyperglycemia primarily caused by insulin resistance (IR). The number of diabetic patients globally has been rising over the past decades. Although significant progress has been made in treating diabetes mellitus (DM), existing clinical drugs for diabetes can no longer fully meet patients when they face complex and huge clinical treatment needs. As a traditional and effective medical system, traditional Chinese medicine (TCM) has a unique understanding of diabetes treatment and has developed many classic and practical prescriptions targeting DM. With modern medicine and pharmacy advancements, researchers have discovered that various bioactive metabolites isolated from TCM show therapeutic on DM. Compared with existing clinical drugs, these bioactive metabolites demonstrate promising prospects for treating DM due to their excellent biocompatibility and fewer adverse reactions. Accordingly, these valuable metabolites have attracted the interest of researchers worldwide. Despite the abundance of research works and specialized-topic reviews published over the past years, there is a lack of updated and systematic reviews concerning this fast-growing field. Therefore, in this review, we summarized the bioactive metabolites derived from TCM with the potential treatment of T2DM by searching several authoritative databases such as PubMed, Web of Science, Wiley Online Library, and Springer Link. For the convenience of readers, the content is divided into four parts according to the structural characteristics of these valuable compounds (flavonoids, terpenoids, alkaloids, and others). Meanwhile, the detailed mechanism and future directions of these promising compounds curing DM are also summarized in the related sections. We hope this review inspires increasingly valuable and significant research focusing on potential bioactive metabolites from TCM to treat DM in the future.

Gentiana rigescens Franch (Gentianaceae) is a famous medicinal plant for treatments of rheumatism, convulsion, and jaundice. Comprehensive investigation of different parts and cultivation years of this plant has not yet been conducted. This study presents the quantitative and qualitative characterization of iridoid glycosides from G. rigescens performed by HPLC and FTIR spectroscopy techniques. The accumulations of loganic acid, swertiamarin, gentiopicroside, and sweroside were determined. Results indicated that their content and distribution in different parts and cultivation years exhibit great variations. Gentiopicroside was identified as the most abundant compound among iridoid glycosides and its highest level was observed in the root of 2-year-old plant. With respect to qualitative variation of metabolic profile, the 1800–800 cm−1 band of FTIR spectra successfully discriminated different parts and cultivation years with the aid of PLS-DA. In addition, combined with PLSR, the feasibility of FTIR spectroscopy for determination of gentiopicroside was investigated by selecting characteristic wavelengths (1800–800 cm−1), which presented a good performance with a residual predictive deviation (RPD) of 3.646. Our results suggested that HPLC and FTIR techniques can complement each other and could be simultaneously applied for comparing and analyzing different parts and cultivation years of G. rigescens.

Boletus edulis and Boletus tomentipes are two well-known mushroom species which are widely consumed in Yunnan province due to their high nutritional and medicinal values. Fourier transform mid-infrared spectroscopy can determine exclusive spectra fingerprint of a sample and further analyse its quality when combined with appropriate chemometrics. In this study, identification and discrimination of B. edulis and B. tomentipes mushrooms from different geographical locations were performed based on Fourier transform midinfrared spectroscopy and chemometrics. Principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis allowed us to identify and discriminate mushroom samples depending on their unique metabolic spectral fingerprints. The range of 1800-400 cm-1, which exhibited major characteristics of mushroom samples was selected for next analysis. The unsupervised principal component analysis and hierarchical cluster analysis showed that mushroom samples from different geographical locations could be effectively identified. Furthermore, the supervised partial least squares discriminant analysis method was used to predict unknown mushroom samples successfully based on developed calibration model. In conclusion, these results indicated that Fourier transform midinfrared technique combined with appropriate chemometrics can be used as an effective and rapid strategy for quality control of B. edulis and B. tomentipes mushrooms with respect to their geographical locations. In addition, this technique also can be applied in other mushroom species for this purpose when coupled with reasonable chemometrics. [ABSTRACT FROM AUTHOR]