1.Production regionalization study of Chinese angelica based on MaxEnt model.
Hui YAN ; Xiao-Bo ZHANG ; Shou-Dong ZHU ; Da-Wei QIAN ; Lan-Ping GUO ; Lu-Qi HUANG ; Jin-Ao DUAN
China Journal of Chinese Materia Medica 2016;41(17):3139-3147
The distribution information of Chinese angelica was collected by interview investigation and field survey, and 43 related environmental factors were collected, some kinds of functional chemical constituents of Angelica sinensis were analyzed. Integrated climate, topography and other related ecological factors, the habitat suitability study was conducted based on Arc geographic information system(ArcGIS),and maximum entropy model. Application of R language to establish the relationship between the effective component of Chinese angelica and enviromental factors model, using ArcGIS software space to carry out space calculation method for the quality regionalization of Chinese angelica. The results showed that 4 major ecological factors had obvious influence on ecology suitability distributions of Chinese angelica, including altitude, soil sub category, May precipitation and the warmest month of the highest temperature, et al. It is suitable for the living habits of the Chinese angelica, cold and humid climate, which is suitable for the deep area of the soil. In addition, the ecological suitability regionalization based on the effect of Chinese angelica also provides a new suitable distribution area other than the traditional distribution area, which provides a scientific basis for the reasonable introduction of Chinese angelica.
2.Analysis and evaluation of eight active ingredients in Lilium lancifolium from different regions.
Huang-Qin ZHANG ; Hui YAN ; Da-Wei QIAN ; Zhen-Hua ZHU ; Sheng GUO ; Lan-Ping GUO ; Zhi-Shu TANG ; Jin-Ao DUAN
China Journal of Chinese Materia Medica 2017;42(2):311-318
This study established a rapid UPLC-TQ-MS/MS method for determination of eight active ingredients in Lilium lancifolium. The contents range of regaloside E, F, C and B are as follows: 0.604 0×10⁻¹-18.62×10⁻¹, 0.680 0×10⁻²-44.75×10⁻², 0.700 0×10⁻³-29.65×10⁻¹, 0.170 0×10⁻¹-4.724 mg•g⁻¹; the contents of chlorogenic acid, caffeic acid, protocatechualdehyde and ferulic acid, within the range of 6.827×10⁻³-16.07×10⁻³, 0.011 1×10⁻³-79.71×10⁻³, 0.593 7×10⁻³-2.962×10⁻³, 2.606×10⁻²-45.89×10⁻² mg•g⁻¹, respectively. According to PCA (principal components analysis) plotting, 35 batches can be divided into two categories, namely Anhui Huoshan and Hunan Longshan. The main different elements between these two categories are caffeic acid and ferulic acid according to the VIP (variable importance in the projection) points figure. Based on comprehensive principal component values, there are eight batches of L. lancifolium from Huoshan among the comprehensive ranking of ten. The UPLC-TQ-MS method for simultaneous analysis of eight active ingredients is accurate, efficient and convenient. This result can provide scientific basis for quality control of L. lancifolium.
3.Identification of metabolites of Zhali Nusi Prescription in rat plasma, bile, urine and feces after oral administration.
Ting ZHANG ; Yang NIU ; Kai-Di HUANG ; B U FAN-SHU ; Xiao-Kun BIAN ; Qiu-Long ZHAO ; Sheng GUO ; Er-Xin SHANG ; Da-Wei QIAN ; Jin-Ao DUAN
China Journal of Chinese Materia Medica 2020;45(21):5280-5288
This study was designed to determine the metabolites of Zhali Nusi Prescription(ZLNSP) in rats. The ultra-high performance liquid chromatography-LTQ Orbitrap mass spectrometric(UHPLC-LTQ-Orbitrap-MS) and mass defect filter techniques were applied to analyze the metabolites of ZLNSP in rat plasma, bile, urine and feces. The biological samples were analyzed by ACQUITY UPLC BEH T_3 column(2.1 mm×100 mm,1.7 μm), with 0.1% formic acid water(A)-acetonitrile(B) as mobile phase, and the biological samples were analyzed in negative ion mode by electrospray ionization mass spectrometry(ESI-MS). An analytical method for biological samples of rats was established, and 8 prototype components and 36 metabolites were identified. The results showed that the metabolic pathways of the main components of ZLNSP in rats included methylation, glucuronidation, sulfation and so on. It provi-ded information for the therapeutic effect of ZLNSP in vivo.
Administration, Oral
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Animals
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Bile
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Chromatography, High Pressure Liquid
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Feces
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Plasma
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Prescriptions
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Rats
4.Value discovery and resource utilization of by-products in production process of medicinal materials are important ways for poverty alleviation with Chinese herbal medicine industry.
Jin-Ao DUAN ; Sheng GUO ; Hui YAN ; Ming ZHAO ; Shu-Lan SU ; Lu-Qi HUANG
China Journal of Chinese Materia Medica 2020;45(2):285-289
Poverty alleviation by Chinese herbal medicine industry is an important way to implement the major strategic plan of the government and to effectively alleviate poverty and increase income of poor farmers in areas with high resource's endowment of Chinese medicinal materials. Based on the analysis of the existing achievements and problems in poverty alleviation by Chinese herbal medicine industry, this paper proposes that improving the comprehensive benefits of Chinese herbal medicine industry is an important direction for poverty alleviation in the poverty-stricken areas with the high endowment of traditional Chinese medicine resources in the future. Then, based on the concept of resource recycling of traditional Chinese medicinal materials, the feasibility and strategies of utilizing by-products in the production process of Chinese medicinal materials and expanding the ways of poverty alleviation were analyzed and discussed. The aim of all these works was to provide the support for enhancing the comprehensive competitiveness of the industry in poverty-stricken regions, enlarging the poverty alleviation effect of Chinese herbal medicine industry, and consolidating the achievements of poverty alleviation.
China
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Drug Industry/economics*
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Drugs, Chinese Herbal
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Herbal Medicine/economics*
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Medicine, Chinese Traditional
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Poverty
5.Correlation between Anxiety, Depression, and Sleep Quality in College Students.
Yu Tong ZHANG ; Tao HUANG ; Fang ZHOU ; Ao Di HUANG ; Xiao Qi JI ; Lu HE ; Qiang GENG ; Jia WANG ; Can MEI ; Yu Jia XU ; Ze Long YANG ; Jian Bo ZHAN ; Jing CHENG
Biomedical and Environmental Sciences 2022;35(7):648-651