Objective To predict the quality markers of Alismatis Rhizoma and salted Alismatis Rhizoma based on fingerprints and multivariate statistical analysis combined with network pharmacology.Methods HPLC-DAD method was used to establish fingerprints of Alismatis Rhizoma and salted Alismatis Rhizoma.Based on the peak area data of the fingerprints,clustering analysis,principal component analysis and orthogonal partial least squares-discriminant analysis were employed to evaluate the quality of 10 batches of Alismatis Rhizoma and 12 batches of salted Alismatis Rhizoma.The main components with quality differences were screened.Network pharmacology was used to analyze the targets and related pathways of the screened components,A component-target-pathway network was constructed,and molecular docking was used to verify.Quality markers of Alismatis Rhizoma and salted Alismatis Rhizoma were predicted.Results The HPLC fingerprints of Alismatis Rhizoma and salted Alismatis Rhizoma were established.The similarity evaluation showed that the similarity of 10 batches of Alismatis Rhizoma and 12 batches of salted Alismatis Rhizoma ranges from 0.991 to 0.998,0.992 to 1.000,respectively.Nine components with quality differences were identified through multivariate statistical analysis,and five of them were identified as alismoxide,alisol C,alismol,alisol B,23-acetate alisol B.Network pharmacological analysis suggested 278 targets of action associated with the five components.The main signaling pathways of KEGG pathway enrichment analysis were closely related to the main efficacy and modern pharmacological effects of Alismatis Rhizoma and salted Alismatis Rhizoma.These 5 components were preliminary predicted as quality markers for Alismatis Rhizoma and salted Alismatis Rhizoma.Conclusion This study predicted 5 quality markers for Alismatis Rhizoma and salted Alismatis Rhizoma,which can provide reference for their quality control and further research.

Objective To establish a fingerprint spectrum for Qiangshen Oral Liquid;To predict its quality markers combined with network pharmacology.Methods HPLC-ELSD method was used to establish fingerprint spectrum of Qiangshen Oral Liquid,and common peaks were identified.Its targets and related pathways were predicted through network pharmacology.A component-target-pathway network was constructed,and molecular docking verification was performed to analyze the quality markers of Qiangshen Oral Liquid.Results The HPLC fingerprint spectrum of Qiangshen Oral Liquid was established.20 common peaks were identified and belonged to all prescription drug tastes.13 chromatographic peaks were located using reference standards.The similarity evaluation showed that the similarity of 19 batches of Qiangshen Oral Liquid ranged from 0 to 0.995.Network pharmacology identified 45 key targets related to 13 components,and KEGG enrichment analysis obtained 151 pathways.A component-target-pathway network was constructed,predicted that calycosin-7-O-glucoside,ginsenoside Rg1,ginsenoside Re,ginsenoside Rf,ginsenoside Rb1,astragaloside Ⅳ,ginsenoside Rd,ginsenoside Rb2,astragaloside Ⅱ,astragaloside Ⅰ,schisandrin A and panaxatriol were quality markers for Qiangshen Oral Liquid.Conclusion The fingerprint spectrum of Qiangshen Oral Liquid was established,and quality markers were predicted preliminarily,providing a reference for its standard establishment and quality evaluation.

Objective To establish a fingerprint spectrum for Qiangshen Oral Liquid;To predict its quality markers combined with network pharmacology.Methods HPLC-ELSD method was used to establish fingerprint spectrum of Qiangshen Oral Liquid,and common peaks were identified.Its targets and related pathways were predicted through network pharmacology.A component-target-pathway network was constructed,and molecular docking verification was performed to analyze the quality markers of Qiangshen Oral Liquid.Results The HPLC fingerprint spectrum of Qiangshen Oral Liquid was established.20 common peaks were identified and belonged to all prescription drug tastes.13 chromatographic peaks were located using reference standards.The similarity evaluation showed that the similarity of 19 batches of Qiangshen Oral Liquid ranged from 0 to 0.995.Network pharmacology identified 45 key targets related to 13 components,and KEGG enrichment analysis obtained 151 pathways.A component-target-pathway network was constructed,predicted that calycosin-7-O-glucoside,ginsenoside Rg1,ginsenoside Re,ginsenoside Rf,ginsenoside Rb1,astragaloside Ⅳ,ginsenoside Rd,ginsenoside Rb2,astragaloside Ⅱ,astragaloside Ⅰ,schisandrin A and panaxatriol were quality markers for Qiangshen Oral Liquid.Conclusion The fingerprint spectrum of Qiangshen Oral Liquid was established,and quality markers were predicted preliminarily,providing a reference for its standard establishment and quality evaluation.

Objective To predict the quality markers of Alismatis Rhizoma and salted Alismatis Rhizoma based on fingerprints and multivariate statistical analysis combined with network pharmacology.Methods HPLC-DAD method was used to establish fingerprints of Alismatis Rhizoma and salted Alismatis Rhizoma.Based on the peak area data of the fingerprints,clustering analysis,principal component analysis and orthogonal partial least squares-discriminant analysis were employed to evaluate the quality of 10 batches of Alismatis Rhizoma and 12 batches of salted Alismatis Rhizoma.The main components with quality differences were screened.Network pharmacology was used to analyze the targets and related pathways of the screened components,A component-target-pathway network was constructed,and molecular docking was used to verify.Quality markers of Alismatis Rhizoma and salted Alismatis Rhizoma were predicted.Results The HPLC fingerprints of Alismatis Rhizoma and salted Alismatis Rhizoma were established.The similarity evaluation showed that the similarity of 10 batches of Alismatis Rhizoma and 12 batches of salted Alismatis Rhizoma ranges from 0.991 to 0.998,0.992 to 1.000,respectively.Nine components with quality differences were identified through multivariate statistical analysis,and five of them were identified as alismoxide,alisol C,alismol,alisol B,23-acetate alisol B.Network pharmacological analysis suggested 278 targets of action associated with the five components.The main signaling pathways of KEGG pathway enrichment analysis were closely related to the main efficacy and modern pharmacological effects of Alismatis Rhizoma and salted Alismatis Rhizoma.These 5 components were preliminary predicted as quality markers for Alismatis Rhizoma and salted Alismatis Rhizoma.Conclusion This study predicted 5 quality markers for Alismatis Rhizoma and salted Alismatis Rhizoma,which can provide reference for their quality control and further research.

OBJECTIVE To improve the quality standard for Jubei mixture . METHODS The chemical reaction of trinitrophenol and hydrocyanic acid was used to identify Armeniacae Amarum solution . Platycodon grandiflorus ，Fritillaria thunbergii，Scutellaria baicalensis ，the leaves of Eriobotrya japonica and Glycyrrhiza uralensis in Jubei mixture were identified by thin-layer chromatography （TLC）. High-performance liquid chromatography was used to simultaneously determine the contents of four active components ，such as amygdalin ，baicalin，wogonoside and monoammonium glycyrrhizinate in Jubei mixture . RESULTS Trinitrophenol test paper showed brick red . TLC spots of five medicinal materials were clear ，without interference from negative control . The linear ranges of amygdalin ，baicalin，wogonoside and monoammonium glycyrrhizinate were 0.066 8-1.335 5 μg（R2＝0.9994），0.189 8-3.796 9 μg（R2＝0.999 9），0.062 6-1.251 3 μg（R2＝0.999 9），0.041 8-0.835 5 μg（R2＝0.999 8）， respectively. RSDs of precision ，repeatability and stability tests were all lower than 2%. The average recoveries were 98.2%， 99.5%，98.3%，99.6%，and RSDs were 0.7%，1.6%，1.5%，1.1%（n＝6）. The contents of 15 batches of samples were different ， and the content of sample from company A was generally lower than those from companies B and C . CONCLUSIONS The standard established can reflect the inherent quality of Jubei mixture well .

Cholangiocarcinoma (CCA) has emerged as an intractable cancer with scanty therapeutic regimens. The aberrant activation of Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ) are reported to be common in CCA patients. However, the underpinning mechanism remains poorly understood. Deubiquitinase (DUB) is regarded as a main orchestrator in maintaining protein homeostasis. Here, we identified Josephin domain-containing protein 2 (JOSD2) as an essential DUB of YAP/TAZ that sustained the protein level through cleavage of polyubiquitin chains in a deubiquitinase activity-dependent manner. The depletion of JOSD2 promoted YAP/TAZ proteasomal degradation and significantly impeded CCA proliferation

Objective To analyze the death characteristics and disease burden of the labor force in Jingzhou City from 2015 to 2018, and to provide a basis for formulating policies to protect the labor force population and propose effective prevention and control measures to reduce the death level and disease burden. Methods The death data of the labor force in Jingzhou City from 2015 to 2018 was collected and statistically analyzed. The death levels, causes of death, and disease burden of the labor force in different years, sexes, ages, and regions were analyzed. Results From 2015 to 2018, the death toll of the labor force accounted for 24.79% of total deaths in Jingzhou City, with a mortality rate of 219.61/100 000 and a standardized mortality rate of 192.17/100 000. There was no significant difference in the mortality rate in different years (P=0.34). The male and female mortality rates were 297.77/100 000 and 139.63/100 000, and the standardized mortality rates were 257.36/100 000 and 119.57/100 000, respectively. The male and female YLL rates were 9.55% and 4.47%, and the standardized YLL rates were 6.75% and 3.12%, respectively. The male mortality and YLL rates were higher than those of the female (P<0.01). The mortality and YLL rate of different age groups increased with age (P<0.01). The mortality rates of urban and rural population were 187.37/100 000 and 229.07/100 000, respectively, the standardized mortality rates were 141.87/100 000 and 208.58/100 000, respectively, the YLL rates were 5.90% and 7.37% respectively, and the standardized YLL rates were 4.13% and 5.20%, respectively. The mortality rate and YLL rate of rural population were higher than those of urban population (P<0.01). The first cause of death in the labor force population was malignant tumor, with the mortality and YLL rate being 87.19/100 000 and 2.90%, respectively. The second cause was injury, with the mortality and YLL rate of 42.60/100 000 and 1.56%, respectively. The leading cause of death was injury in the 15 and 25 years old groups, and malignant tumor in the 35, 45 and 55 years old groups. Lung cancer and liver cancer were the main types of lethal cancers. Transportation accidents and suicide were the main types of lethal injuries. Conclusion The disease burden of the rural labor force was heavy. It is important to strengthen health education for the rural labor force, especially male laborers over the age of 45, and to implement early cancer diagnosis and treatment and injury intervention programs to effectively improve the health of the labor population.

Objective To investigate the role of long noncoding RNA-AJ227913 in the pathogenesis of primary gout arthritis (GA). Methods The subjects were divided into three groups:30 acute gout patients (AGA), 30 non-acute gout patients (NAGA), 30 healthy controlsand 30 hyperuricemia patients (HUA). Real-time quantitative polymerase chain reaction (RT-qPCR) was employed to examine the expression of AJ227913 in peripheral blood mononuclear cells(PBMCs) from four groups. 100 μg/ml monosodium urate (MSU) was used to stimulate the peripheral blood of NAGA and healthy controls patients. Then the expression ofAJ227913 was detected by RT-qPCR. Kruskal-Wallis test, Mann-Whitney test, Spearman correlations were used for statistical analysis. Results The expression level of AJ227913 in the AGA group (0.0557 ±0.0156) was higher than that in the NAGA group (0.0223±0.018) and healthy controls group (0.0038±0.0013). There was significant difference between the NAGA group and healthy controls group (P>0.05). Compared with the control group, the expression of AJ227913 in NAGA group which were stimulated by MSU was significantly increased. The Spearman correlation analysis found that the AJ227913 expression levels in GA groups were correlated with UREA (r=0.608, P<0.01), CREA (r=0.337, P<0.05), CYSC (r=0.422, P<0.01). Conclusion Altered expression of AJ227913 may be involved in the inflammatory process of GA and the balance of uricacid.

Aberrant activation of the phosphatidylinositol 3-kinase(PI3K)-protein kinase B(PKB,Akt)-mammalian target of rapamycin(mTOR) pathway is commonly observed in human cancer and is critical for cell survival, proliferation and differentiation.A variety of small molecule inhibitors targeting PI3K-Akt-mTOR pathway are under clinical studies.This review will summarize the recent studies in terms of the PI3K-Akt-mTOR signaling pathway and cancer,research progress of the antitumor activity possessed by PI3K-Akt-mTOR inhibitors,as well as the recent research in the related field conducted by our group.