Inflammatory Response and Oxidative Stress as Mechanism of Reducing Hyperuricemia of Gardenia jasminoides-Poria cocos with Network Pharmacology

Hyperuricemia (HUA) is a metabolic disease, closely related to oxidative stress and inflammatory responses, caused by reduced excretion or increased production of uric acid. However, the existing therapeutic drugs have many side effects. It is imperative to find a drug or an alternative medicine to effectively control HUA. It was reported that Gardenia jasminoides and Poria cocos could reduce the level of uric acid in hyperuricemic rats through the inhibition of xanthine oxidase (XOD) activity. But there were few studies on its mechanism. Therefore, the effective ingredients in G. jasminoides and P. cocoa extracts (GPE), the active target sites, and the further potential mechanisms were studied by LC-/MS/MS, molecular docking, and network pharmacology, combined with the validation of animal experiments. These results proved that GPE could significantly improve HUA induced by potassium oxazine with the characteristics of multicomponent, multitarget, and multichannel overall regulation. In general, GPE could reduce the level of uric acid and alleviate liver and kidney injury caused by inflammatory response and oxidative stress. The mechanism might be related to the TNF-α and IL-7 signaling pathway.

Alleviation of Androgenetic Alopecia with Aqueous Paeonia lactiflora and Poria cocos Extract Intake through Suppressing the Steroid Hormone and Inflammatory Pathway

Paeonia lactiflora Pallas (PL) and Poria cocos Wolf (PC) have been traditionally used to treat inflammatory diseases reported in Dongui Bogam and Shen Nong Ben Cao Jing, traditional medical books in Korean and China, respectively. We determined the efficacies and the molecular mechanisms of PL, PC, and PL + PC aqueous extracts on androgenetic alopecia (AGA) induced by testosterone propionate in C57BL/6 mice. The molecular mechanisms of PL and PC in AGA treatment were examined using experimental assays and network pharmacology. The AGA model was generated by topically applying 0.5% testosterone propionate in 70% ethanol solution to the backs of mice daily for 28 days while the normal-control (Normal-Con; no AGA induction) mice applied 70% ethanol. The 0.1% PL (AGA-PL), 0.1% PC (AGA-PC), 0.05% PL + 0.05% PC (AGA-MIX), and 0.1% cellulose (AGA-Con; control) were supplemented in a high-fat diet for 28 days in AGA-induced mice. Positive-control (AGA-Positive) were administered 2% finasteride daily on the backs of the AGA mice. Hair growth rates decreased in the order of AGA-PL, AGA-MIX, AGA-PC, AGA-Positive, and AGA-Con after 21 days of treatment (ED21). On ED28, skins were completely covered with hair in the AGA-PL and AGA-MIX groups. Serum testosterone concentrations were lower in the AGA-PL group than in the AGA-Con group and similar to concentrations in the Normal-Con group, whereas serum 17β-estradiol concentrations showed the opposite pattern with increasing aromatase mRNA expression (p < 0.05). In the dorsal skin, DKK1 and NR3C2 mRNA expressions were significantly lower, but TGF-β2, β-Catenin, and PPARG expressions were higher in the AGA-PL and AGA-PC groups than in the AGA-Con group (p < 0.05), whereas TNF-α and IL-6 mRNA expressions were lower in the AGA-PL, AGA-MIX, and Normal-Con groups than in the AGA-Con group (p < 0.05). The phosphorylation of Akt and GSK-3β in the dorsal skin was lower in AGA-Con than normal-Con, and PL and MIX ingestion suppressed their decrease similar to the Normal-Con. In conclusion, PL or PL + PC intake had beneficial effects on hair growth similar to Normal-Con. The promotion was related to lower serum testosterone concentrations and pro-inflammatory cytokine levels, and inhibition of the steroid hormone pathway, consistent with network pharmacology analysis findings.

Untargeted Metabolomics and Targeted Quantitative Analysis of Temporal and Spatial Variations in Specialized Metabolites Accumulation in Poria cocos (Schw.) Wolf (Fushen)

Poria cocos (Schw.) Wolf is a saprophytic fungus that grows around the roots of old, dead pine trees. Fushen, derived from the sclerotium of P. cocos but also containing a young host pine root, has been widely used as a medicine and food in China, Japan, Korea, Southeast Asian countries, and some European countries. However, the compound variations at the different growth periods and in the different parts of Fushen have not previously been investigated. In this study, an untargeted metabolomics approach based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) and targeted quantitative analysis was utilized to characterize the temporal and spatial variations in the accumulation of specialized metabolites in Fushen. There were 119 specialized metabolites tentatively identified using the UPLC-Q/TOF-MS. The nine growth periods of Fushen were divided into four groups using partial least squares discrimination analysis (PLS-DA). Four different parts of the Fushen [fulingpi (FP), the outside of baifuling (BO), the inside of baifuling (BI), and fushenmu (FM)] were clearly discriminated using a PLS-DA and orthogonal partial least squares discrimination analysis (OPLS-DA). Markers for the different growth periods and parts of Fushen were also screened. In addition, the quantitative method was successfully applied to simultaneously determine 13 major triterpenoid acids in the nine growth periods and four parts. The quantitative results indicated that the samples in January, March, and April, i.e., the late growth period, had the highest content levels for the 13 triterpenoid acids. The pachymic acid, dehydropachymic acid, and dehydrotumulosic acid contents in the FM were higher than those in other three parts in March, whereas the poricoic acid B, poricoic acid A, polyporenic acid C, dehydrotratrametenolic acid, dehydroeburicoic acid, and eburicoic acid in FP were higher beginning in October. These findings reveal characteristics in temporal and spatial distribution of specialized metabolites in Fushen and provide guidance for the identification of harvesting times and for further quality evaluations.