Medicinal plant resources in Inner Mongolia autonomous region of China and Mongolia: a comparative study / 中国中药杂志

Inner Mongolia autonomous region of China and Mongolia are the primary regions where Chinese and Mongolian medicine and its medicinal plant resources are distributed. In this study, 133 families, 586 genera, and 1 497 species of medicinal plants in Inner Mongolia as well as 62 families, 261 genera, and 467 species of medicinal plants in Mongolia were collected through field investigation, specimen collection and identification, and literature research. And the species, geographic distribution, and influencing factors of the above medicinal plants were analyzed. The results revealed that there were more plant species utilized for medicinal reasons in Inner Mongolia than in Mongolia. Hotspots emerged in Hulunbuir, Chifeng, and Tongliao of Inner Mongolia, while there were several hotspots in Eastern province, Sukhbaatar province, Gobi Altai province, Bayankhongor province, Middle Gobi province, Kobdo province, South Gobi province, and Central province of Mongolia. The interplay of elevation and climate made a non-significant overall contribution to the diversity of plant types in Inner Mongolia and Mongolia. The contribution of each factor increased significantly when the vegetation types of Inner Mongolia and Mongolia were broadly divided into forest, grassland and desert. Thus, the distribution of medicinal plant resources and vegetation cover were jointly influenced by a variety of natural factors such as topography, climate and interactions between species, and these factors contributed to and constrained each other. This study provided reference for sustainable development and rational exploitation of medicinal plant resources in future.

Analysis on incidence trend of liver cancer in China, 2005-2016 / 中华流行病学杂志

Objective: To understand the incidence trend of liver cancer in China from 2005 to 2016, and explore the correlation between the incidence trend of liver cancer and the incidence trend of hepatitis B. Methods: The incidence data of liver cancer in China from 2005 to 2016 were collected from the Annual Report of Cancer Registry in China. The incidence data of hepatitis B were collected from China Public Health Science Data Center. World standardized incidence rate (WSR) was calculated according to the World Segi's population. Joinpoint regression model was used to analyze the trend of WSR of liver cancer [measured by average annual percentage change (AAPC)]. The age-period-cohort model was fitted to analyze the age, period and cohort effects in people aged 20- years and above. Pearson correlation coefficient was used to explore the correlation between the incidence of liver cancer and the incidence of hepatitis B. Results: The crude incidence of liver cancer in China showed a trend of first increase before 2009 and then relatively stable. The world standardized morbidity rate of liver cancer in China decreased from 19.11 per 100 000 in 2005 to 17.74 per 100 000 in 2016 (AAPC=-0.5%, 95%CI: -1.3%-0.3%, P=0.240). The incidence of liver cancer in male decreased significantly (AAPC=-1.0%, 95%CI: -1.5%--0.5%, P=0.001). The incidence of liver cancer in women increased from 2005 to 2010 [annual percentage change (APC)=1.7%, 95%CI: -0.1%-3.4%, P=0.059] but showed a significant decrease trend from 2010 to 2016 (APC=-1.6%, 95%CI: -2.3%--1.0%, P=0.001). From 2005 to 2016, the incidence of liver cancer showed a decreasing trend in urban areas (AAPC=-0.3%, 95%CI: -0.8%-0.3%, P=0.316) and rural areas (AAPC=-3.9%, 95%CI: -4.4%--3.3%, P<0.001). Risk for liver cancer increased with age, while the period effect showed a trend of first increase then decrease and cohort effect showed a decrease trend. The morbidity rates of both hepatitis B and liver cancer showed decrease trends from 2009 to 2016, and there was a significant correlation (r=0.71, 95%CI: 0.01-0.94, P=0.048). Conclusions: From 2005 to 2016, the morbidity rate of liver cancer in China showed a decrease trend, and there were significant gender and urban-rural area specific differences. Age effect had a great impact on the risk for liver cancer. With the progress of population aging in China, liver cancer is still a public health problem, to which close attention needs to be paid.

Application of remote sensing technology in medicinal plant resources / 中国中药杂志

The sustainable use of medicinal plants is the foundation of the inheritance of traditional Chinese medicine(TCM) and the acquisition of information on medicinal plants is the basis for the development of TCM. The traditional methods of investigating medicinal plant resources are disadvantageous in strong subjectivity and poor timeliness, making it difficult to real-time monitor medicinal plant resources. In recent years, remote sensing technology has become an important means of obtaining information on medicinal plants. The application of this technology has made up for the shortcomings of traditional methods. The open-access remote sensing data with medium spatial resolution satellites provide an opportunity for extracting information on medicinal plant resources. This study firstly introduced the principles of remote sensing technology, summarized the satellites and the parameters commonly used in the field of medicinal plant resources, and compared the survey methods of remote sensing technology with traditional methods. Secondly, it reviewed the applications of remote sensing technology in the extraction of information on the cultivation of medicinal plants and the common methods for extracting the planting structure information of medicinal plants based on remote sensing technology. Thirdly, the applications of remote sensing technology in the investigation and monitoring of medicinal plants were further analyzed with the research objects divided into wild and cultivated medicinal plants according to the characteristics of the habitats. Finally, it pointed out the key unsolved technical problems in the remote sensing monitoring of medicinal plant resources, and proposed solutions for the intelligent information processing of medicinal plants based on remote sensing big data, which is expected to provide references for the development of remote sensing technology in derivative application in medicinal plant resources.

Contrastive analysis of extraction of Polygonatum cyrtonema planting area based on data of "Resource 3" / 中国中药杂志

Polygonatum cyrtonema is a famous bulk medicinal material which is the medicinal and edible homologous. With the implementation of the traditional Chinese medicine industry to promote precise poverty alleviation, the planting area of P. cyrtonema in Jinzhai is becoming larger and larger in recent years. Jinzhai is located in the Dabie Mountainous area, which is the largest mountain area and county in Anhui Province. The cultivation of P. cyrtonema is scattered, and the traditional Chinese medicine resources investigation is not only inefficient and accurate. In this study,the "Resource 3"(ZY-3) remote sensing image was used as the best observation phase,and the method of support vector machine classification was used. The method of parallelepiped, minimum distance, mahalanob is distance, maximum likelihood classification and neural net were used to classify and recognize the P. cyrtonema in the whole region. In order to determine the accuracy and reliability of classification results, the accuracy of six supervised classification results was evaluated by confusion matrix method, and the advantages and disadvantages of six supervised classification methods for extracting P. cyrtonema field planting area were compared and analyzed. The results showed that the method of support vector machine classification was more appropriate than that using other classification methods. It provides a scientific basis for monitoring the planting area of P. cyrtonemain field.

Suitable planting area of Poria cocos in Jinzhai county of Dabie Mountains region / 中国中药杂志

Dabie Mountain in Anhui province is a genuine producing area of Poria cocos, commonly known as Anling. Jinzhai county in Anhui province is a traditional producing area of P. cocos, and it is also a key county for poverty alleviation in Dabie Mountains. Poverty alleviation of traditional Chinese medicine producing area is an important measure to implement the major strategic deployment of the central government. The planting of P. cocos is helpful to promote the development of traditional Chinese medicine industry in Dabie Mountains and help poverty alleviation. P. cocos is a saprophytic fungus with special demands on soil and ecological environment, and its planting appears a scattered and irregular distribution. Traditional investigation methods are time-consuming and laborious, and the results are greatly influenced by subjective factors. In order to obtain the suitable planting area of P. cocos in Jinzhai county, according to the field survey, the research team has explored the regional, biological characteristics and cultivation methods of P. cocos in the county, and obtained the altitude distribution area suitable for the growth of P. cocos. Then, the MaxEnt niche model was used to analyze the relationship between ecological factors and distribution areas, and the potential distribution zoning of P. cocos in Jinzhai county was studied. Combined with the characteristics of P. cocos planting pattern, taking ZY-3 remote sensing image as the data source, the maximum likelihood method was used to extract the area that could be used for P. cocos cultivation in Jinzhai county, and the reason why artificial planting P. cocos was mainly distributed in the west of Jinzhai county was analyzed. The suitable regional classification of P. cocos in Jinzhai county was obtained by superposition of suitable altitude distribution area, MaxEnt analysis and area extracted from remote sensing image, which provided data support for the planting planning of P. cocos in Jinzhai county.

Research on remote sensing recognition of wild planted Lonicera japonica based on deep convolutional neural network / 中国中药杂志

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.

Differences in spatial distribution of medicinal plant resources in Yinshan region of Inner Mongolia / 中国中药杂志

Yinshan Mountains stands on the southern edge of the Inner Mongolia Plateau, which stretches 1 200 km from east to west and 50 to 100 km from north to south. The rich and varied topographic environment of the Yinshan Mountains has created a variety of vegetation floras, which also makes the species of medicinal plant resources in this area unevenly distributed. Therefore, studying the spatial distribution difference of medicinal plant resources among various banners, counties, and districts in the Yinshan area is of great significance to formulate the protection policy and promote the industry development of medicinal plant. This study is based on the fourth national survey of traditional Chinese medicine resources in Inner Mongolia, regarding the results of the third national survey of traditional Chinese medicine resources. The species of medicinal plant resources in the Yinshan area around 31 banners, counties and districts were counted in detail. Then, using exploratory spatial data analysis(ESDA), trend surface analysis, spatial autocorrelation, geographical detector and other geostatistical analysis methods to analyze the differences in the spatial distribution of medicinal plant resources of the Yinshan area in Inner Mongolia. After discussing and analyzing the experimental results to account for the reasons for the overall trend of change and the degree of aggregation, the author further put forward relevant constructive suggestions. The results show that the areas with the most abundant and concentrated distribution of medicinal plant resources in the Yinshan area are located in Guyang county, Shiguai District of Baotou city, Tutou right banner, and Tuoketuo county; the higher richness and concentrated distribution of medicinal plant resources is in Wulate front banner, Wulate middle banner, Wulate back banner; areas with relatively low abundance and concentrated distribution of medicinal plant resources located in Qingshan district of Baotou city, Saihan district and Yuquan district of Hohhot city; areas with the lowest abundance and concentrated distribution of medicinal plant resources are located in Xincheng district and Huimin district of Hohhot city. It can be concluded that the horizontal distribution difference of multiple ecological factors, the special wetland environment of the river, the vertical difference of elevation, the farmland and other factors have an important influence on the richness of the medicinal plant resources species.

A systematic review on the association between meteorological factors with traffic accident injury / 中华疾病控制杂志

In recent years, the impact of meteorological factors on health and injury has been paid more and more attention. Severe weather events were considered to be an important risk factor for traffic accident injuries. Evidence from a large number of epidemiological studies suggests that meteorological factors, including high temperatures, rainfall, snowfall, wind and visibility, might be related to the occurrence of traffic accidents. This systematic review attempts to summarize the current research status of meteorological factors on traffic accident injury, systematically review the relationship between meteorological factors and traffic accident injury, and discuss how to further carry out related research.

Bletilla striata planting area in Ningshan county extraction based on multi-temporal remote sensing images / 中国中药杂志

Traditional Chinese medicine is planted in mountainous areas with suitable natural conditions. The planting area is complex in terrain,and the planting plots are mostly irregularly shaped. It is difficult to accurately calculate the planting area by traditional survey methods. The method of extracting Chinese herbal medicine planting area combined with remote sensing and GIS technology is of great significance for the rational development and utilization of traditional Chinese medicine resources. Taking Bletilla striata planting in Ningshan county of Shaanxi province as an example,the extraction method of planting area of traditional Chinese medicine in county was studied. High-resolution ZY-3 and GF-1 multi-spectral multi-temporal remote sensing images were used as data sources. Through field sampling,samples such as B. striata,cultivated land,forest land,water body,artificial surface,alpine meadow,etc. are collected. The spectral features,texture features and shape features of remotely identifiable objects in different planting areas and cultivated land,vegetable sheds were analyzed,confusing ground objects were eliminated and interpretation marks were establish. The method of visual interpretation is used to realize the extraction of B. striata planting areas,and the B. striata planting area are calculated by combining GIS technology. The results showed that the method of visual interpretation,using high-resolution ZY-3 and GF-1 multi-spectral multi-temporal remote sensing image data extracted the planting area of 403.05 mu. It can effectively extract the B. striata planting area in research region.

Extraction of distribution information of Angelicae sinensis plants in Weiyuan county based on remote sensing technology / 中国中药杂志

Due to the large amount of nutrients required during the cultivation of Angelica sinensis and in order to prevent the occurrence of pests and diseases,and the annual reduction of the planting area of Angelica and the balance of supply and demand of A. sinensis,the A. sinensis plantation adopts the rotation mode. This paper takes Wuyuan county of Gansu province as the research scope and use GF-1 Satellite data as the data source,using remote sensing technology combined with field survey results,to explore the effective method of visual interpretation for the extraction of A. sinensis planting area. A sample was selected to generate a spectrum according to different feature types. The different characteristics of A. sinensis and other features were analyzed and distinguished in remote sensing images,so that the A. sinensis planting plots were extracted and verified in remote sensing images. The results showed that the accuracy verification value of the visual interpretation method was 95. 85%. It is determined that the visual interpretation method can effectively extract the A. sinensis planting plots within the research scope and realize the comprehensive grasp of the spatial distribution information of A. sinensis.

Remote sensing extraction method of Codonopsis pilosula planting area in Weiyuan county / 中国中药杂志

Due to the large amount of Codonopsis pilosula planted in Weiyuan county,and the arable land area,the local medicinal materials office uses a large amount of manpower,financial resources and material resources to estimate its area every year. In order to extract the information of local Chinese medicinal materials more quickly and simply,we try to apply remote sensing technology to the extraction of Chinese medicinal materials. This paper will use Weiyuan county of Gansu province as the research area,and use the domestic ZY-3 Satellite multi-spectral remote sensing image as the data source to find out the spectral characteristics of the party's participation in other remote sensing images. The visual interpretation method was used to extract the planting area of the C. pilosula in Weiyuan county. The estimated value of the planting area of C. pilosula using satellite remote sensing technology was 75 965 mu( 1 mu≈667 m2),which was basically consistent with the field survey data of the local medicinal materials office. After the accuracy verification,it was found that the precision of C. pilosula planted by visual interpretation was more than 70%. It is concluded that the satellite remote sensing technology can be used to extract the information of C. pilosula and it can provide the relevant information of the planting area of Chinese medicinal materials quickly and accurately.

Research on extraction of Zizyphus jujuba planting area in Jia county of Shaanxi / 中国中药杂志

With digital satellite remote sensing image data of GF-1,in 2018 the object-oriented classification method was used to extract Zizyphus jujuba planting area in Jia county of Shaanxi province. The results showed that the remote sensing classification method based on rule set could extract and reckon Z. jujube planting area in the study area effectively. The planting area of Z. jujube in Jia county was about 5. 34×104 hm2 and the area of consistent accuracy was 97. 92%. The method used in this study could provide a technical reference for the area extraction of the same type of medicinal materials. And it is of great significance to provide decision support for the protection and utilization of Z. jujube resources.

Monitoring of Saposhnikovia divaricate planting area based on texture and pop information in Naiman banner / 中国中药杂志

The planting area of Chinese medicinal materials is an important basis for formulating policies such as production and poverty alleviation of Chinese medicinal materials and is determining the quantity of medicinal materials trade. Accurately mastering the information of the distribution,area and yield of Chinese medicinal materials cultivation is the basis of the adjustment of the planting structure of traditional Chinese medicine. It is now the largest planting place of Mongolian traditional Chinese medicinal materials in Naiman banner that is belonging to Tongliao city,Inner Mongolia. It is of great significance to obtain the planting area of Mongolian Chinese medicinal materials in Naiman banner in time and effectively for the development of subsequent industries. In this study,Saposhnikovia divaricata,a medicinal plant planted in Naiman banner,was selected as an example,and the fusion 2 m resolution ZY-3 remote sensing image was used as the data source. Based on the ground survey data,the sample data of each typical ground object were selected,and the spectral characteristic curves of different ground objects were obtained,and the S. divaricata spectral information was obtained. Using the filtering texture analysis method based on probability statistics,five kinds of texture image display results under different texture filtering were compared and analyzed,and finally the S. divaricata texture features based on information entropy are determined. The distribution range and planting area of S. divaricata in Naiman banner were extracted and interpreted by using the texture and spectral information of remote sensing images. The results showed that: S. divaricata was mainly distributed in the northeast and central south of Naiman banner,and the planting area was 5 336 mu( 1 mu≈667 m2). The field verification data were in good agreement with the remote sensing interpretation results,and the difference was small. It shows that the combination of spectral information and texture information can realize the discrimination of S. divaricata,and the interpretation results can provide a reference for the county to formulate the poverty alleviation action of Chinese medicinal material industry and the economic development plan of agricultural producing areas.

Planting area estimation of Paeonia ostii based on RS--by case study in Dangshan of Anhui province / 中国中药杂志

Moutan Cortex is one kind of famous medicinal materials. The dry root bark of Paeonia ostii which is a genuine medicinal material produced in Tongling,Anhui province,and later was introduced to Heze,Shandong province and Bozhou,Anhui province.Dangshan county is located at the northern end of Anhui province and adjacent to Shandong province. Its medicinal seedlings were came from Heze,Shandong province. At present,there is a lack of scientific investigation on the planting area of P. ostii in north China plain. On the basis of field investigation and remote sensing technology,through the data source provided by the remote sensing image of " Resources 3"( ZY-3),combined with the biological characteristics of P. ostii,the planting area of P. ostii in Dangshan county was extracted by field investigation and supervisory classification. The supervise classification method with the highest interpretation accuracy so far,the overall accuracy was 97. 81%,Kappa coefficient 0. 96. The results showed that the remote sensing classification method based on the maximum likelihood classification could extract P. ostii plots in the study area effectively. This study provides a scientific basis for the protection and rational utilization of traditional Chinese medicine resources,the development policy of traditional Chinese medicine industry and the long-term development plan in Dangshan county,and provides technical support for the poverty alleviation of traditional Chinese medicine industry in Dangshan county. It provides scientific reference for the application of remote sensing technology to investigate the planting area of P. ostii in in north China plain.

Extracting Paeonia lactiflora planted area in Dangshan of Anhui province based on ZY-3 remote sensing image / 中国中药杂志

In order to comprehensively monitor the dynamic change of Paeonia lactiflora planting area,the investigation of P. lactiflora planting area in Dangshan was carried out. It can provide reference for the planting detection of P. lactiflora in Huaibei Plain.Based on remote sensing technology,this paper extracts the planting area of P. lactiflora in Dangshan in 2018 by using the minimum distance method,maximum likelihood method,parallel hexahedron method and Mahalanobis distance method,using the remote sensing image of ZY-3 Satellite as the data source,and makes a comparative analysis with the results. The results show that the maximum likelihood method is better than the other three methods. This method can provide reference for remote sensing monitoring of P. lactiflora planting area in China.

Study of extracting natural resources of Chinese medicinal materials planted area in Luoning of Henan province based on UAV of low altitude remote sensing technology and remote sensing image of satellite / 中国中药杂志

The study is aimed to effectively obtain the planting area of traditional Chinese medicine resources. The herbs used as the material for traditional Chinese medicine are mostly planted in natural environment suitable mountainous areas. The UAV low altitude remote sensing data were used as the samples and the GF-2 remote sensing images were applied for the data source to extract the planting area of Salvia miltiorrhiza and Artemisia argyi in Luoning county combined with field investigation. Remote sensing satellite data of standard processing obtain specific remote sensing data coverage. The UAV data were pre-processed to visually interpret the species and distribution of traditional Chinese medicine resources in the sample quadrat. Support vector machine( SVM) was used to classify and estimate the area of traditional Chinese medicine resources in Luoning county,confusion matrix was used to determine the accuracy of spatial distribution of traditional Chinese medicine resources. The result showed that the application of UAV of low altitude remote sensing technology and remote sensing image of satellite in the extraction of S. miltiorrhiza and other varieties planting area was feasible,it also provides a scientific reference for poverty alleviation policies of the traditional Chinese medicine Industry in local areas.Meanwhile,research on remote sensing classification of Chinese medicinal materials based on multi-source and multi-phase high-resolution remote sensing images is actively carried out to explore more effective methods for information extraction of Chinese medicinal materials.

Regional cultitvation and dynamic change of garden Ginseng in Changbai county based on multi-source and multi-temporal satellite remote sensing data / 中国中药杂志

The dried roots of Panax ginseng are used as medicines. In this paper,multi-time satellite sensing image data are used for image registration by radiometric correction,atmospheric pressure correction,the data of different years were compared. The multiscale segmentation of the sensing image was successively carried out by using object-oriented method. Combining with the characteristics of the sensing image participated in the field survey,the objective was to understand the speckles of the environmental parameters distribution map of Changbai county in 2017 and 2018. The parameter area of Changbai county was calculated by using GIS spatial analysis tools. The union,erase and intersect tools of " analysis to OLS" overlay in " Arc Toolbox" were used to analyze the parametric area of Changbai county from 2017 to 2018. The results showed that the parameter area of Changbai county in 2017 was 27 400 mu( 1 mu≈667 m2),and the parameter area in 2018 was 13 900 mu. The parameter area of the new park in Changbai County in 2018 was 12 500 mu,and the harvested area in 2017 was 27 000 mu. Through the analysis and study of the regional change of the park participating in the training area,it has significance for guiding the park participating in the actual production planning and layout in Changbai county in the next step.

Application of UAV remote sensing in monitoring of Callicarpa nudiflora / 中国中药杂志

In order to solve the problem of manual area measurement,the traditional methods of medicinal planting area statistics are difficult to meet the needs of rapid area survey application. This paper uses the UAV remote sensing method with the advantages of unmanned,automatic,high efficiency,high score and short production cycle to monitor the shape of Callicarpa nudiflora. A solution for aerial photography,image data acquisition and data processing of drones were designed for characteristics and planting conditions. After data processing and statistical analysis,detailed information on the location and area of the C. nudiflora in the target area was obtained. Then the accuracy comparison analysis was carried out with the measured results of the C. nudiflora. The results show that the UAV is feasible for the monitoring of C. nudiflora,and has a good application prospect in the monitoring of Chinese herbal medicine planting.

Random forest classification of Callicarpa nudiflora from WorldView-3 imagery based on optimized feature space / 中国中药杂志

Taking the Xiushui township of Baisha county in Hainan province as the research area,the random forest algorithm with obvious advantages in feature selection and classification extraction was used to extract the information of the Callicarpa nudiflora planting in the study area. Firstly,four kinds of different characteristic variables were generated based on World View-3 data,including spectral features,principal component features,vegetation index and texture features. Secondly,the spatial distribution of the C. nudiflora in the study area was extracted by remote sensing by random forest classification algorithm. Finally,the feature space of the random forest classification algorithm was optimized based on the feature importance to obtain the best random forest classification results,and this result is compared with the classification result of the random forest algorithm of the unoptimized feature space. The results showed that:①The overall accuracy of the C. nudiflora extracted by World View-3 image was 89. 97%,and the Kappa coefficient was 0. 84,which indicates that the random forest algorithm had higher classification accuracy and better applicability in Hainan C. nudiflora recognition.② The overall accuracy of extracting C. nudiflora with the dimension reduction feature was 90. 4,and the Kappa coefficient was 0. 85,which indicates that the random forest algorithm can effectively select features. At the same time as the feature variable data mining,the precision of the information extraction of the C. nudiflora was still guaranteed,and the operation efficiency was improved. This study provides a new idea,method and technical means for information extraction of cultivated medicinal plant resources in terms of feature selection and method selection.

Effect of ACE/Ang Ⅱ/AT1 axis and ACE2/Ang(1-7)/Mas axis on glucose and lipid metabolism in adipose tissue / 基础医学与临床

The renin angiotensin system(RAS)includes two counterbalance axes:the ACE/Ang Ⅱ/AT1 axis and the ACE2/Ang(1-7)/Mas axis.The RAS can regulate glucose and lipid metabolism in adipose tissue.Most of evi-dences demonstrated that the ACE/Ang Ⅱ/AT1 axis can induce glucose metabolism disorders in adipose tissue, while ACE2/Ang(1-7)/Mas axis improves glucose metabolism.The RAS,which is over activated in obese patient, has been considered to be a potential link among obesity,dyslipidemia and insulin resistance.The effect of ACE/AngⅡ/AT1 axis and ACE2/Ang(1-7)/Mas axis on lipid and glucose metabolism in adipose tissue should be futh-er investigated,and we may find a new target for improving glucose and lipid metabolism.