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A spectrum-activity relationship is established with high performance liquid chromatography(HPLC) fingerprints and the in vitro antioxidant activity to improve the quality evaluation system of Aralia taibaiensis. The HPLC profiles of 12 batches of samples were collected, and the similarity evaluation, heat map analysis and principal component analysis were conducted for the chemometric study of the fingerprint data. Combined with grey correlation analysis, the contributions of the common peaks in the fingerprints to the antioxidant activity were clarified, and the important peaks reflecting the efficacy were identified. The results showed that 17 common peaks were found in 12 batches of A. taibaiensis samples, and 6 of them were identified as saponins. Similarity evaluation, heat map analysis and principal component analysis roughly classified the A. taibaiensis herbs into two categories, i.e.,(1) S1-S10, S12 and(2) S11. Twelve batches of samples showed different antioxidant activities in a dose-dependent manner. In particular, S9 had the strongest antioxidant activity, while S11 was the weakest in antioxidant capacity, which was basically consistent with the overall score results. The results of grey correlation analysis demonstrated that the 17 common peaks scavenged DPPH radicals in the following order: X_3gt;X_(17)gt;X_4gt;X_8gt;X_7gt;X_(13)gt;X_2gt;X_6gt;X_(11)gt;X_(10)gt;X_(16)gt;X_(12)gt;X_9gt;X_5gt;X_(14)gt;X_1gt;X_(15), and scavenged ABTS radicals in the order of X_4gt;X_3gt;X_7gt;X_8gt;X_2gt;X_(17)gt;X_(13)gt;X_6gt;X_(16)gt;X_(11)gt;X_5gt;X_(12)gt;X_(10)gt;X_9gt;X_(14)gt;X_1gt;X_(15). Among them, X_3, X_4, X_7(araloside C), X_8 and X_(17) were the important peaks reflecting the efficacy of A. taibaiensis, which were basically consistent with those contained in the principal component 1. In this study, the correlation between the HPLC fingerprints of 12 batches of A. taibaiensis and its antioxidant activity provides a reference for the Q-marker screening and quality control of A. taibaiensis.

The aim of this paper was to investigate the protective effect of Shengdihuang Decoction(SDHD) on premature ovarian failure in rats and to explore its protective mechanism. Totally 48 adult female SD rats were randomly divided into six groups with 8 rats in each group: control group,model group,Bujiale group,SDHD high,medium and low dose group(12,6,3 g·kg-1). Rats were administered with Tripterygium Glycosides Tablets for 14 d to make model of premature ovarian failure except for control group. Rats were treated with corresponding medicines for 21 d after that. The oestrous cycle was observed,ovarian index and uterine index were detected,respectively. The variation in contents of E2,P,FSH,LH was detected with radioimmunoassay,the morphological changes of ovary and uterus were observed by HE staining,SOD activity and MDA content were detected in serum. The expression of ERα in ovarian and uterine tissues was detected by SABC,and the expression of ERα in uterus tissue was detected by Western blot. Compared with the model group,the index of the uterus and ovary in the high and middle dose group of Shengdihuang Decoction increased(P0. 05),the level of serum E2 and P increased(P0. 01,P0. 05) and the level of LH decreased(P0. 01). The number of ovarian follicles increased,the endometrium thickened,and the glands were developed,the activity of SOD was enhanced and the content of MDA decreased in serum,the expression of ERα in the follicle granulosa cells and the epithelial cells of the uterus increased,and the expression of ERα in the uterus increased. Shengdihuang Decoction could improve the morphology and function of the uterus and ovary,and relieve the premature failure of the ovary. The effect may be achieved by enhancing the antioxidant capacity of ovarian granulosa cells,restoring ovarian function,promoting serum estradiol and progesterone secretion,and increasing the expression of ER in uterine mucosal epithelial cells and ovarian granulosa cells.

To reveal the extraction regularity of volatile oil from galangal by GC-MS analysis. The volatile oil in galangal was extracted by steam distillation. The extract was collected every 30 min, the oil part and the water part were separated. GC-MS was used to analyze the extraction liquid collected at different time periods. A total of 140 volatile components were obtained by GC-MS analysis. Among them, the main components were eucalyptus oil alcohol, alpha-pine oil alcohol and 4-terpene alcohol; 22 special components were dissolved in water, 77 special components were dissolved in oil and 41 components were dissolved in both oil and water. With the increase of specific components in water, the content of Eucalyptus in water increased in a linear manner. The increase of eucalyptus oil further promoted the dissolution or dispersion of alpha PN in water, and the change of specific components in oil was positively correlated with the content of Eucalyptus and alpha-terpilenol in oil. The results of principal component analysis show that the physical and chemical properties of the compounds were important factors affecting the distribution of components. PC1 (molecular weight, melting point, boiling point positive correlation), PC2 (negative correlation of refractive index) and PC3 (positive correlation of water solubility) were the main components that lead to the differences in composition distribution. The process of extracting volatile oil from galangal through steam distillation was affected by the physical and chemical properties of volatile components. Some components were specifically distributed in the fragrance and volatile oil system. The endemic components of aromatic water increased the content of the main components in the water system, which may lead to the "emulsification", reduction of the yield and low quality of the volatile oil.