Rheumatoid arthritis(RA), a chronic autoimmune disease, is featured by persistent joint inflammation. The development of RA is associated with the disturbance of endogenous metabolites and intestinal microbiota. Gardeniae Fructus(GF), one of the commonly used medicinal food in China, is usually prescribed for the prevention and treatment of jaundice, inflammation, ache, fever, and skin ulcers. GF exerts an effect on ameliorating RA, the mechanism of which remains to be studied. In this study, ultra-perfor-mance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)-based serum non-target metabolomics and 16S rDNA high-throughput sequencing were employed to elucidate the mechanism of GF in ameliorating RA induced by complete Freund's adjuvant in rats. The results showed that GF alleviated the pathological conditions in adjuvant arthritis(AA) rats. The low-and high-dose GF lo-wered the serum levels of interleukin(IL)-6, tumor necrosis factor-α(TNF-α), IL-1β, and prostaglandin E2 in the rats(P<0.05, P<0.01). Pathways involved in metabolomics were mainly α-linolenic acid metabolism and glycerophospholipid metabolism. The results of 16S rDNA sequencing showed that the Streptococcus, Facklamia, Klebsiella, Enterococcus, and Kosakonia were the critical gut microorganisms for GF to treat AA in rats. Spearman correlation analysis showed that the three differential metabolites PE-NMe[18:1(9Z)/20:0], PC[20:1(11Z)/18:3(6Z,9Z,12Z)], and PC[20:0/18:4(6Z,9Z,12Z,15Z)] were correlated with the differential bacteria. In conclusion, GF may ameliorate RA by regulating the composition of intestinal microbiota, α-linolenic acid metabolism, and glycerophospholipid metabolism. The findings provide new ideas and data for elucidating the mechanism of GF in relieving RA.
Rats ; Animals ; Chromatography, Liquid ; Gardenia ; Tandem Mass Spectrometry ; Gastrointestinal Microbiome ; alpha-Linolenic Acid ; Metabolomics/methods* ; Arthritis, Rheumatoid/drug therapy* ; Inflammation ; Glycerophospholipids

The aim of this study was to compare crocins in the fruit of Gardenia jasminoides and Gardenia jasminoides var. radicans. Acchrom XCharge C_(18) column(4.6 mm×250 mm, 5 μm) was used for separation, with mobile phase of acetonitrile and 0.1% formic acid for gradient elution. The detection wavelength was set at 440 nm with a flow rate of 1.0 mL·min~(-1), and the column temperature was 30 ℃. The high performance liquid chromatography(HPLC) fingerprint of crocin in Gardenia species was established by testing 20 batches of G. jasminoides and 8 batches of G. jasminoides var. radicans samples from different sources, and UHPLC-ESI-Orbitrap-MS/MS technology and reference substances were used to predict and identify the common peaks. The results showed that 20 common chromatographic peaks from the samples were selected and the structures of 16 common peaks were predicted by mass spectrum. Four common peaks(crocin Ⅰ, Ⅱ, Ⅲ, and Ⅳ) were identified by the comparison with reference substances. The content of crocin Ⅰ, Ⅱ, Ⅲ, and Ⅳ was determined simultaneously under the same chromatographic condition, and both the system suitability and the methodological investigation results met the requirements of content determination. The relative similarity of HPLC fingerprint of 28 samples to the reference fingerprint was above 0.98. The results of cluster analysis(CA) showed that G. jasminoides and G. jasminoides var. radicans were separately grouped into one group. In the 20 batches of G. jasminoides, the content of crocin Ⅰ, Ⅱ, Ⅳ, and Ⅲ was between 3.58-9.58, 0.230-1.452, 0.014 5-0.135, and 0.301-1.12 mg·g~(-1), respectively, and the total content was between 4.12-12.25 mg·g~(-1). In the 8 batches of G. jasminoides var. radicans, the content of crocin Ⅰ, Ⅱ, Ⅳ, and Ⅲ was between 5.84-11.48, 0.308-0.898, 0.010 6-0.025 5, and 0.675-1.34 mg·g~(-1), respectively, and the total content was between 6.97-13.72 mg·g~(-1). The existing results showed that there is a certain similarity between G. jasminoides and G. jasminoides var. radicans in the composition of crocin, which needs further proved by more batches of samples. The method established in this paper provides references for the quality control of G. jasminoides, G. jasminoides var. radicans, and related products.
Carotenoids/analysis* ; Chromatography, High Pressure Liquid/methods* ; Fruit/chemistry* ; Gardenia/chemistry* ; Tandem Mass Spectrometry

This study aimed to explore the correlation of the content of 15 non-crocin components of Gardeniae Fructus with its external properties(shape and color). The fruit shape was quantified according to the length/diameter measured by ruler and vernier calliper and the chromaticity values L~*, a~*, b~*, and ΔE~* of all samples were determined by chroma meter. Chromatographic separation was conducted on a Welch Ultimate XB C_(18) column(4.6 mm×250 mm, 5 μm) under gradient elution with acetonitrile solution(A) and 0.1% formic acid aqueous solution(B) as the mobile phase at a flow rate of 1.0 mL·min~(-1). The column temperature was 30 ℃ and the detection wavelength was 238 nm. The high-performance liquid chromatography(HPLC) method was established for simultaneous determination of the content of eight iridoid glycosides, six phenolic acids, and one flavonoid in 21 batches of Gardeniae Fructus samples. The correlation of the content of the 15 components with shapes and chromaticity values in each sample was analyzed by multivariate statistical analysis. According to the circulation situation and traditional experience, 21 batches of Gardeniae Fructus samples were divided into three categories, namely 14 batches of Jiangxi products(small and round, red and yellow), 4 batches of Fujian products(oval, red) and 3 batches of Shuizhizi(Gardenia jasminoides, longest, reddest). The Gardeniae Fructus samples were sequenced as Jiangxi products(1.71) < Fujian products(1.99) < Shuizhizi(2.55) in terms of the length/diameter average, Jiangxi products(17.7) < Fujian products(19.7) ≈ Shuizhizi(19.6) in terms of average value of a~*(red and green), Jiangxi products(24.4) > Fujian products(19.2) ≈ Shuizhizi(19.3) in terms of b~*(yellow and blue), and Jiangxi products(49.8) > Fujian products(48.0) ≈ Shuizhizi(47.8) in terms of L~*(brightness). The total content of the 15 components, 8 iridoid glycosides, 6 phenolic acids, and rutin in Jiangxi products was in the ranges of 65.53-99.64, 52.15-89.16, 6.10-11.83, and 0.145-1.81 mg·g~(-1), respectively. The total amount of the 15 components, 8 iridoid glycosides, 6 phenolic acids, and rutin in Fujian products was in the ranges of 69.33-94.35, 63.52-85.19, 5.39-8.41, and 0.333-0.757 mg·g~(-1), respectively. In Shuizhizi, the total content of the 15 components, 8 iridoid glycosides, 6 phenolic acids, and rutin was in the ranges of 77.35-85.98, 68.69-76.56, 7.30-9.05, and 0.368-0.697 mg·g~(-1), respectively. Pearson correlation analysis revealed that Gardeniae Fructus with leaner and longer fruit shape possessed lower content of total phenolic acids(the sum of the six phenolic acids) and rutin, but the correlation with iridoid glycosides was not high. Additionally, the higher content of total phenolic acids and rutin denoted the yellow coloration of Gardeniae Fructus, and the higher content of cryptochlorogenic acid, chlorogenic acid, and rutin meant the brighter color of Gardeniae Fructus. However, the higher content of geniposide and neochlorogenic acid and the lower content of deacetyl asperulosidic acid methyl ester led to the red coloration of Gardeniae Fructus. The results indicated that the morphological characters of Gardeniae Fructus were closely related to its chemical components. The more round shape and the yellower color reflected the higher content of phenolic acids and flavonoid, and Gardeniae Fructus with redder color had higher content of geniposide. OPLA-DA showed that the length/diameter and the content of six iridoid glycosides(gardoside, shanzhiside, gardenoside, genipin 1-gentiobioside, 6β-hydroxy geniposide, and deacetyl asperulosidic acid methyl ester), two phenolic acids(neochlorogenic acid and cryptochlorogenic acid) and rutin could be used as markers to distinguish three types of samples. This study provided experimental data for the scientific connotation of "quality evaluation through morphological identification" of Gardeniae Fructus.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/analysis* ; Esters/analysis* ; Flavonoids/analysis* ; Fruit/chemistry* ; Gardenia/chemistry* ; Iridoids/analysis* ; Rutin/analysis*

In order to realize rapid and non-destructive identification of the origin of Gardeniae Fructus, a technical method based on hyperspectral imaging technology was established in this study. Spectral information of Gardeniae Fructus samples from eight production origins was acquired from visible NIR(410-990 nm, VNIR) and short wavelength NIR(950-2 500 nm, SWIR) bands based on hyperspectral imaging techniques. The average spectral reflectance within the region of interest was extracted and calculated using the ENVI 5.3 software, resulting in 1 600 sample data. The visible short wavelength infrared band(fused bands) spectral data covering the range 410-2 500 nm were obtained after combining the spectral data of VNIR and SWIR. Data were de-noised by five common preprocessing methods, including multivariate scatter correction, Savitzky-Golay smoothing, standard normal variate, first derivative(FD), and second derivative from VNIR, SWIR, and fused bands(VNIR+SWIR). Partial least squares discriminant analysis, linear support vector classification(LinearSVC), and random forest were used to establish the model for origin identification of Gardeniae Fructus. The results indicated that the identification model of Gardeniae Fructus origin established after FD pretreatment of the spectral data in the fused bands could yield good results. According to the confusion matrix evaluation results, the model prediction set using LinearSVC reached 100% accuracy, so the optimum identification model of Gardeniae Fructus origin was determined as fusion bands-FD-LinearSVC. Therefore, the hyperspectral imaging technology can achieve rapid, nondestructive, and accurate identification of Gardeniae Fructus samples of different origins, which provides a technical reference for the differential detection of Gardeniae Fructus and other Chinese medicines.
Gardenia ; Hyperspectral Imaging ; Fruit ; Least-Squares Analysis ; Technology

Gardenia ; Iridoids ; Pigmentation ; Plant Extracts

To study the time-toxicity relationship and mechanism of Gardeniae Fructus extract on the hepatoxicity in rats. Rats were randomly divided into C group(0 day), D5 group(5 days), D12 group(12 days), D19 group(19 days), and D26 group(7 days recovery after 19 days of administration). The rats in normal group received normal saline through intragastric administration, and the rats in other groups received 10 g·kg~(-1 )Gardeniae Fructus extract through intragastric administration. After the final administration, the livers were collected. Hematoxylin-eosin staining was used to observe the histopathological changes in the liver tissue. Total liver proteins were extracted for proteomic analysis, detected by the Nano-ESI liquid-mass spectrometry system and identified by Protein Disco-very software. SIEVE software was used for relative quantitative and qualitative analysis of proteins. The protein-protein interaction network was constructed based on STRING. Cytoscape software was used for cluster analysis of differential proteins. Kyoto encyclopedia of genes and genomes(KEGG) database was used to perform enrichment signal pathway analysis. Pearson correlation analysis was performed for the screened differential protein expression and liver pathology degree score. The results showed that the severity of liver injury in D5, D12 and D19 groups was significantly higher than that in group C. The degree of liver damage in D5 group was slightly higher than that in D12 and D19 groups, with no significant difference between group D26 and group C. Totally 147 key differential proteins have been screened out by proteomics and mainly formed 6 clusters, involving in drug metabolism pathways, retinol metabolism pathways, proteasomes, amino acid biosynthesis pathways, and glycolysis/gluconeogenesis pathways. The results of Pearson correlation analysis indicated that differential protein expressions had a certain temporal relationship with the change of liver pathological degree. The above results indicated that the severity of liver damage caused by Gardeniae Fructus extract did not increase with time and would recover after drug with drawal. The above pathways may be related to the mechanism of liver injury induced by Gardeniae Fructus extract.
Animals ; Drugs, Chinese Herbal/toxicity* ; Fruit ; Gardenia ; Liver ; Proteomics ; Rats ; Signal Transduction

The chromatic values of the broken-fried and single-fried Gardeniae Fructus Praeparatus(GFP) were measured by the color analyzer to analyze the color variation rule, and the contents of 10 main components were determined by ultra-high performance liquid chromatography(UPLC). The multivariate statistical analysis, Pearson correlation analysis, and discriminant analysis were conducted to investigate the color and components of GFP samples. The experimental results revealed that L~*, a~*, b~*, and E~*ab decreased continuously during processing, and the color of samples gradually deepened. The trend and range of chromatic values during broken-frying and single-frying processes were basically identical. Gardenoside, crocin-Ⅰ(C-Ⅰ), and crocin-Ⅱ(C-Ⅱ) showed an obviously downward trend, while the contents of geniposidic acid and 5-hydroxymethylfurfural(5-HMF) increased significantly. Shanzhiside, deacetyl-asperulosidic acid methyl ester, and geniposide(G2) showed a downward trend. Scandoside methyl ester rose first and fell later. Genipin-1-O-gentiobioside(G1) went through a decrease-increase-decrease trend. The change trends of component contents during broken-frying and single-frying processes were generally consistent, but the change range was different. Among all the components, scandoside methyl ester and G1 showed obvious change. Because of different stir-frying time, the change rate of each component content in the process of broken-frying was higher than that in single-frying process. Additionally, geniposidic acid, gardenoside, scandoside methyl ester, C-Ⅰ, C-Ⅱ, and 5-HMF exhibited a higher correlation with apparent color. On the basis of above findings, the discriminant function of two frying processes was established, which could be applied to the discrimination of broken-fried and single-fried samples. This study analyzed the dynamic quality change rule of GFP during broken-frying and single-frying processes based on color-component correlation analysis, and found the two methods showed consistent change trend, yet with slight difference in the quality of samples. This study can provide data support for the processing of GFP.
Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal ; Fruit ; Gardenia

The chromaticity space parameters of the samples during the processing of Gardeniae Fructus Praeparatus(Jiaozhizi in Chinese herbal name, JZZ) were measured by the visual analyzer to analyze the color variation rule during the processing of JZZ, and the content changes of total reducing sugar, total amino acid and 5-hydroxymethylfurfural(5-HMF) related to Maillard reaction were measured. Pearson correlation analysis and linear regression analysis of the data were carried out by SPSS 24.0 software. The experimental results showed that the objective coloration of the samples in the processing of JZZ was basically consistent with the traditional subjective color judgment; the contents of total reducing sugar and total amino acids showed a decreasing trend during the processing of JZZ, and the content of 5-HMF showed an increasing trend, which was in line with Maillard reaction law. Pearson correlation analysis results showed that there was a significant correlation between the chromaticity space parameters L~*(lightness value), a~*(red green value), b~*(yellow blue value), E~*ab(total color value) and the contents of total reducing sugar, total amino acid and 5-HMF(P<0.01), among which the values of L~*, a~*, b~*, E~*ab were positively correlated with the contents of total reducing sugar and total amino acid, and negatively correlated with the contents of 5-HMF. The results of linear regression analysis also showed that these two were highly correlated. In this study, by establishing the correspondence relationship between the color change of JZZ processing and Maillard reactants, wecan not only provide a basis for the objective digital expression of subjective color of JZZ, but also provide a reference for explaining the processing mechanism of JZZ from a new perspective.
Amino Acids ; Color ; Drugs, Chinese Herbal ; Fruit ; Gardenia ; Maillard Reaction

This research is to establish an HPLC method for determination of geniposidic acid, genipin-1-β-D-gentiobioside, geniposide, p-trans-coumaroylgenipin gentiobioside, chlorogenic acid, crocin-Ⅰ, crocin-Ⅱ and crocin-Ⅲ in Gardeniae Fructus at different harvest time. The detection wavelength was 238, 320 and 440 nm. Principal component analysis(PCA), correlation analysis, regression analysis and partial least squares(PLS) analysis were used to explore the relationship of color and content of eight components in Gardeniae Fructus. The result showed that the trend of the eight components in Gardeniae Fructus at harvest time in different three years was varied similarly. According to the variation of eight components at different harvest time, the mature and immaturate Gardeniae Fructus were discriminated. The content of crocin-Ⅰwas correlated positively with a~* of color significance. The redder color of Gardeniae Fructus showed the higher value of a~* and content of crocin-Ⅰ, indicating the better quality of Gardeniae Fructus. This method provided reference for justifying the color and quality of Gardeniae Fructus and scientific evidence for "assessing quality by distinguishing color".
Chlorogenic Acid ; Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal ; Fruit ; Gardenia

Gardeniae Fructus has the traditional effects of promoting intelligence and inducing resuscitation, but its mechanism is unclear. In this study, the relationship between Gardeniae Fructus's traditional effect of promoting intelligence and inducing resuscitation and anti-Alzheimer's disease effect was taken as the starting point to investigate the anti-Alzheimer's disease mechanism of the major absorbed components in Gardeniae Fructus by the network pharmacology method. The network pharmacology research model of "absorbed composition-target-pathway-disease" was adopted. In this study, the active components screening and target prediction technology were used to determine the active components and targets of Gardeniae Fructus in treatment of Alzheimer's disease. The enrichment pathway and biological process of Gardeniae Fructus were studied by using the bioinformatics annotation database(DAVID), and the results of molecular docking validation network analysis were used to elaborate the mechanism of Gardeniae Fructus in treatment of Alzheimer's disease. It was found that 35 absorbed components of Gardeniae Fructus not only regulated 48 targets such as cholines-terase(BCHE) and carbonic anhydrase 2(CA2), but also affected 11 biological processes(e.g. transcription factor activity, nuclear receptor activity, steroid hormone receptor activity, amide binding and peptide binding) and 7 metabolic pathways(MAPK signaling pathway, Alzheimer disease and estrogen signaling pathway, etc.). Molecular docking results showed that more than 60% of the active components could be well docked with key targets, and the relevant literature also showed that the active components could inhibit the MAPK1 expression of key targets, indicating a high reliability of results. These results indicated that Gardeniae Fructus may play its anti-Alzheimer's disease action via a "multi-ingredients-multi-targets and multi-pathways" mode, providing a scientific basis for further drug research and development.
Alzheimer Disease ; Drugs, Chinese Herbal ; Gardenia ; Humans ; Molecular Docking Simulation ; Reproducibility of Results