Anti-Melanogenesis Effect of Polysaccharide from Saussurea involucrata on Forskolin-Induced Melanogenesis in B16F10 Melanoma Cells.

As one of the prominent medicinal plants listed in the Chinese pharmacopoeia (2020), Saussurea involucrata (Kar. et Kir.) Sch.-Bip was demonstrated to possess various therapeutic effects. In our recent research, we extracted the polysaccharides from S. involucrata (SIP) at optimal conditions and conducted further structure elucidation on the main fraction as well as the confirmation of its possible anti-inflammatory activity. Hence, in this work, we assessed the in vitro antioxidant activity and anti-melanogenesis effects of the crude SIP in forskolin-induced B16F10 melanoma cells. The results show that SIP possessed strong antioxidant activity and was effective in concentration-dependently decreasing melanin formation and inhibiting tyrosinase activity in forskolin-induced B16F10 cells. Based on these results, the inhibitory mechanism of melanogenesis was investigated by measuring Tyrosinase (TYR), Tyrosinase related protein-1 (TRP-1), Tyrosinase related protein-2 (TRP-2), Microphthalmia-associated transcription factor (MITF), cAMP-response element binding protein (CREB), mitogen-activated protein kinases (MAPK) signaling protein members, and ß-catenin degradation in forskolin-induced B16F10 cells. The anti-melanogenesis response of SIP might be attributed to the regulation of c-Jun N-terminal kinase (JNK) phosphorylation and ß-catenin degradation pathways. These results suggest that polysaccharides from S. involucrata possess a strong anti-melanogenic effect, and thus could be used as a high-value natural material for skin whitening in cosmeceutical industries.

Spectrum-effect relationship between UPLC fingerprints and antidiabetic and antioxidant activities of Rosa rugosa.

In this study, the antidiabetic and antioxidant properties of the chemical constituents of Rosa rugosa Thunb. (R. rugosa) was evaluated through analysis of spectrum-effect relationship. The ultra-performance liquid chromatography (UPLC) fingerprints of 21 batches of R. rugosa were evaluated by similarity analysis (SA) and hierarchical clustering analysis (HCA). The 28 common components were identified by ultra-high-performance liquid chromatography coupled to quadrupole-orbitrap high resolution mass spectrometry (UHPLC-Q-orbitrap-HRMS/MS). Meanwhile, the antidiabetic activities and antioxidant activities of 21 batches of R. rugosa were estimated in vitro. Besides, four chemometrics named principal component analysis (PCA), grey correlation analysis (GRA), partial least squares regression (PLSR) and the bivariate correlations analysis (BCA) were applied to construct spectrum-effect relationship between the UPLC fingerprints and biological activities of R. rugosa. The spectrum-effect relationship study revealed that di-O-galloyl-HHDP-glucoside, galloyl-HHDP-glucoside and avicularin were more relevant to antidiabetic activity. Di-O-galloyl-HHDP-glucoside, galloyl-HHDP-glucoside and ellagic acid were the main antioxidant components of R. rugosa. The current bioassay and spectrum-effect relationships are proper for associating sample quality with the active ingredient, and our finding would provide foundation and further understanding of the quality evaluation and quality control of R. rugosa.

Development of Plant Metabolomics Analytical Approach Based on Liquid Chromatography Tandem Mass Spectrometry in Artemisia rupestris L / 分析化学

Due to the diversity and complexity, the change of chemical components in medicinal plant according to the time, cultivated varieties or ecological condition is difficult to recognize using traditional phytochemistry method. In order to analyze the pharmacodynamics material basis in Uighur medicinal plant Artemisia rupestris L. in an effective and comprehensive way, a plant metabolomics approach was established based on liquid chromatography-tandem mass spectrometry (LC-MS/MS). This study firstly focused on the effect of extraction solvents,redissolve solvents and ultrasonic time on the untargeted metabolomics, then the optimal preparation condition was selected according to metabolites coverage. After methodology validation, the approach was applied to acquire metabolic information in root, stem, branchlet, leaf and flower of Artemisia rupestris L. The results showed that the metabolome in flower was obviously different with the other organs. Coupling with multivariate statistical analysis, a batch of differential metabolites were picked out, in which 61 flavonoids, 97 rupestonic acid derivatives, 7 chlorogenic acids and 15 other compounds were primarily recognized according to the characteristic fragmentation rules of specific structure type and database retrieval. Additionally,the distribution characteristics of the above 180 differential metabolites was illustrated by cluster heat map. In conclusion,this study provided important information about the rational utilization of effective parts from Artemisia rupestris L.,and offered a novel strategy for quality control,variety improvement and reasonable development of medicinal plants.