Studying effect of total flavonoid extracts from Lonicera japonica Thunb on some index of lipidemia. Rats were drunk cholesterol at a dose of 0.5g/kg/24hours for 6 consecutive weeks in order to cause hyperlipidemia. The result showed that: flavonoid extracted from Lonicera japonica Thunb at a dose of 0.45g/kg and 0.9g/kg decreased plasma triglyceride, total cholesterol, LDL-C and increased HDL-C in white rats drunk cholesterol in vitro. The effects of flavonoid at the dose of 0.45g/kg and 0.90g/kg on some index of lipidemia were the same. There was no differences in increasing body weight of rats in all studied rat groups
Flavonoids ; Flowers ; Lonicera ; Hyperlipidemias

In vitro, flavonoids from Lonicera japonica Thunb flavonoids stimulate the catalysis of hydrolysis starch. This stimulating effect depended on the concentration of Lonicera japonica flavonoid but their in vitro stimulations weren’t strong. The anti-inflammatory effects were stronger when combining flavonoid with -amylase on dextran-induced edema mouse legs. So active catalysis stimulation of -amylase could be associated with anti-inflammation process; with unclear mechanisms. This result suggested the need of further research of anti-inflammatory drugs according to combine of traditional medicine and anti-inflammatory enzyme
Flavonoids ; Anti-Inflammatory Agents ; Lonicera

OBJECTIVETo compare morphological characteristics of pollen of Lonicera japonica in different cultivars cultivated in Shandong and provide a basis for distinguishing different cultivars and selecting fine breeding.

METHODThe scanning electron microscope (SEM) was applied to observe and compare the outside characteristics of pollen,and the data were analyzed by SAS 9.1 software.

RESULTSome difference was found among pollen size, aperture length and the density of spine. The biggest pollen size and aperture length is Dajizhao with 61.97 microm polar axis and 61.79 microm quarter major axis and 18.03 microm aperture length,and the smallest is Honggengzi with 57.46 microm polar axis and 57.29 microm quarter major axis and 18.03 microm aperture length.

CONCLUSIONThe morphological characteristics of pollen can provide a basis for distinguishing different cultivars of L. japonica.

OBJECTIVETo study genetic diversity and genetic relationships among Lonicera macranthoides cultivars.

METHODFive cultivars were estimated by ISSR and SRAP. The data of amplified bands were analyzed by Treeconw software. The system diagram of genetic relationship was built by UPGMA.

RESULTTwenty ISSR primers amplified 186 bands with 103 (54.63%) polymorphic bands and 58 SRAP primer combinations amplified 591 bands with 347(55.46%) polymorphic bands. Genetic distance ranges were 0.058 4-0.230 8 (by ISSRs) and 0.1071-0.2611 (by SRAPs). Both ISSR and SRAP analyses revealed a middle level of genetic diversity in L. macranthoides cultivars. The dendrograms based on SRAP and ISSR markers were not all the same.

CONCLUSIONThe genetic diversity of L. macranthoides cultivars is middle. ISSR and SRAP markers can be effectively applied to genetic analysis in L. macranthoides cultivars.

We collected 22 cultivated population of Lonicera japonica from 17 areas. The characteristics of non-glandular hairs were observed and measured by the scanning electron microscopy. The principal components analysis and correlation analysis were conduct based on length and density of L. japonica. The results showed a significant negative correlation between length and density of non-glandular hairs, and the characteristics of non-glandular was not corrrelated significantly with latitude. The correlation results indicated that the density was a key to separate "Damaohua" and "Jizhuahua". The contribution of climate and soil was important to the cultivated population. This reminded that the characteristics of non-glandular hairs were affected by environmental and genetic interaction.
Lonicera ; anatomy & histology ; growth & development ; ultrastructure

Identification of Chinese medicinal materials is a fundamental part and an important premise of the modern Chinese medicinal materials industry. As for the traditional Chinese medicinal materials that imitate wild cultivation, due to their scattered, irregular, and fine-grained planting characteristics, the fine classification using traditional classification methods is not accurate. Therefore, a deep convolution neural network model is used for imitating wild planting. Identification of Chinese herbal medicines. This study takes Lonicera japonica remote sensing recognition as an example, and proposes a method for fine classification of L. japonica based on a deep convolutional neural network model. The GoogLeNet network model is used to learn a large number of training samples to extract L. japonica characteristics from drone remote sensing images. Parameters, further optimize the network structure, and obtain a L. japonica recognition model. The research results show that the deep convolutional neural network based on GoogLeNet can effectively extract the L. japonica information that is relatively fragmented in the image, and realize the fine classification of L. japonica. After training and optimization, the overall classification accuracy of L. japonica can reach 97.5%, and total area accuracy is 94.6%, which can provide a reference for the application of deep convolutional neural network method in remote sensing classification of Chinese medicinal materials.
Lonicera ; Neural Networks, Computer ; Remote Sensing Technology

The aim of this paper was to observe the anti-inflammatory action and mechanism of Lonicerae Japonicae Flos extract and Lonicerae Flos extract in xylene-induced ear swelling experiment and lipopolysaccharide(LPS)-induced RAW264.7 cell inflammatory model. In vivo, xylene-induced mouse auricle swelling model was used to detect the auricle swelling degree and swelling inhibition rate of Lonicerae Japonicae Flos extract and Lonicerae Flos extract; the pathological changes of mice auricle were observed by hematoxylin eosin(HE) staining. In vitro, RAW264.7 inflammatory cell model was induced by LPS, where the cytotoxic effects of Lonicerae Japonicae Flos extract and Lonicerae Flos extract on RAW264.7 cells were detected by CCK-8 method; Griess method was used to detect the effect of Lonicerae Japonicae Flos extract and Lonicerae Flos extract on nitric oxide(NO) production, and ELISA method was used to detect the content of inflammatory factors interleukin-6(IL-6), IL-1β, and tumor necrosis factor-α(TNF-α). At last, Western blot was used to detect the protein changes of cyclooxygenase 1(COX1), COX2 and inducible nitric oxide synthetase(iNOS) for RAW264.7 cells. The results showed that both Lonicerae Japonicae Flos extract and Lonicerae Flos extract could significantly inhibit the degree of auricle swelling caused by xylene in mice and the inhibition rate was positively correlated with the drug dose. Furthermore, both of them could reduce the infiltration of lymphocytes and neutrophils in mouse ear tissues. For in vitro experiments, both Lonicerae Japonicae Flos extract and Lonicerae Flos extract inhibited NO secretion in RAW264.7 cells, down-regulated the release of IL-1β, IL-6 and TNF-α, and down-regulated iNOS protein and COX2, NF-κB p65 protein content. In conclusion, both Lonicerae Japonicae Flos extract and Lonicerae Flos extract have good anti-inflammatory effect, and the mechanism may be related with the inhibition of NF-κB signaling pathway.
Animals ; Anti-Inflammatory Agents ; Lipopolysaccharides ; Lonicera ; Mice ; Plant Extracts

Pruning branches and leaves is the measure to stimulate the growth of Lonicera japonica flower buds, and consequently, the resources of pruned leaves are inevitably and seriously wasted in production. High-performance liquid chromatography(HPLC) was applied for content determination of seven active ingredients(chlorogenic acid, galuteolin, isochlorogenic acids A, B, and C, secologanic acid, and secoxyloganin) in L. japonica leaves from March to November. The results showed that the tillering removed from the trunk of L. japonica in March, the leaves pruned from May to July, and the leaves after the first frost date in November were rich in active ingredients, which deserved further exploitation and utilization. The total content(TC) of active ingredients in pruned L. japonica leaves in early March was the highest. The content of active ingredients in L. japonica leaves increased significantly after the first frost date, which was close to that in the bud tillers pruned in early and middle March. After the first frost date, L. japonica leaves are incapable of photosynthesis, and the harvesting of L. japonica leaves does not affect the physiological activities of the tree. In addition to huge resources, the content of active ingredients is high during this period, which is the best harvesting period of L. japonica leaves.
Chromatography, High Pressure Liquid/methods* ; Flowers ; Lonicera ; Plant Leaves

OBJECTIVETo extract and identify the chemical constituents of essential oil from Lonicera fulvotomentosa in different collected periods (bud, Silver-flower and Golden-flower periods).

METHODExtracts in three different collected periods were subjected to GC-MS analysis for determination of their chemical constituents.

RESULTThe 29, 34 and 28 kinds of chemical constituents corresponding to the above three periods were found, and 44 kinds of compounds were identified. The relative content of every chemical constituents in each essential oil was obtained by area normalization method.

CONCLUSIONThe O-tolyl isocyanide was detected from essential oil of Lonicera for the first time. The result indicated that the highest relative content in essential oil in the three periods is alcohol substance and the second is ester and aldehyde. Many common constituents in the essential oil from L. fulvotomentosa, including linalool, hyacinthin, O-tolyl isocyanide, geraniol, methyl anthranilate, and so on, all could be detected in the three periods. However, the differences of their relative content are obvious.

OBJECTIVETo establish a chromatographic fingerprint of Lonicera japonica and apply it to identify geo-authentic of L. japonica.

METHODThe HPLC was applied in chromatographic separation and data were analysed by "computed aided similarity evaluation" software.

RESULTThere exited distinct difference of chemical components group between and non-authentic samples.

CONCLUSIONThe established HPLC fingerprint can be used for the identification of geo-authentic of L. japonica.