# Untargeted Metabolomic Profiling of _Fructus Chebulae_ and _Fructus Terminaliae Billericae_
## 3 Results
### Analysis of Differential Metabolites  
Multivariate analysis focuses more on the relationships between metabolites and their agonistic/antagonistic effects in biological processes. By taking into account the results of both statistical analyses, we can examine the data from different perspectives and draw informed conclusions [20]. We identified distinct metabolites using Student's \(t\)-test with a significance threshold of \(p<0.05\) and a variable importance in projection (VIP) > 1 in the initial principal component of the OPLS-DA model. As shown in Figure 4, in the volcano plot, every point corresponds to a metabolite, with the \(x\)-axis showing the log2 fold change for each metabolite in the group and the \(y\)-axis representing the \(p\)-value of the \(t\)-test (\(-\)log10 n). In the scatterplot, the size of the data points corresponds to the VIP value of the OPLS-DA model, with bigger points indicating higher VIP values. Data points are color-coded to indicate the final assessment of significance, with red representing significantly upregulated metabolites, blue representing significantly downregulated metabolites, and gray representing metabolites with no significant change. We found 110 differential metabolites  
Figure 3: Schematic representation of the different classes (**A,B**) and PCA(The horizontal axis PC1 and the vertical axis PC2 represent the two directions where the data variation is greatest. Percentage represents the proportion of variation in each direction to the total variation.) of FTB and FC metabolites in the positive and negative ion modes (**C,D**). in the positive ion mode, of which 29 were upregulated and 81 were downregulated. These metabolites encompassed 23 classes of compounds, including flavonoids, phenols, iridoids, polyketides, lignans, phenylpropionoids, and amino acid derivatives. In the negative ion mode, a grand total of 87 distinct metabolites were detected, with 26 showing an increase in levels and 61 showing a decrease. These metabolites consisted of 15 classes of compounds, including flavonoids, terpenoids, phenols, phenylpropionoids, and amino acid derivatives. Distinct metabolites frequently share comparable or supplementary biological roles and are controlled in a positive or negative manner by identical metabolic pathways, as in  
Figure 4: Volcano plots of differential metabolites in positive (**A**) and negative ion modes (**B**). dicated by exhibiting similar or contrasting expression profiles across various experimental sets. Hierarchical clustering allows the grouping of metabolites with similar characteristics and the identification of differences in metabolites among experimental groups. We performed complete-linkage clustering of differential metabolites by generating a Euclidean distance matrix (EDM) based on the quantitative expression of the differential metabolites and analyzed the top 20 differentially expressed metabolites (DEMs) (Figure 5) [21]. Each column and row of the heatmap correspond to each sample and metabolite, respectively. Color blocks show the metabolites' expression levels, with red representing high expression and blue representing low expression. Betulinic acid, L-asparagine, and polyphyllin VI were highly significant for differential expression markers in the positive ion mode. Betulinic acid is a pentacyclic triterpen abundant in plants of the genus _Betula_, such as birch bark. Pharmacological studies found that betulinic acid has anti-inflammatory, antitumor, anti-HIV, and anti-ulcer properties [22]. L-asparagine specifically hydrolyzes the amide bond of asparagine and catalyzes the generation of aspartate and ammonia from asparagine. L-asparagine can inhibit tumor growth by lowering the level of asparagine in vivo. Polyphyllin is the main active ingredient of Paris polyphyllla and has been shown to mediate anti-inflammatory, antioxidant, antitumor, antibacterial, and antietic effects. Salidroside, ethyl gallate, and L-tryptophan were found to be highly significant in the negative ion mode for differentially expressed metabolites.