A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality.
Drugs, Chinese Herbal ; administration & dosage ; chemistry ; standards ; Medicine, Chinese Traditional ; standards ; Quality Control ; Reproducibility of Results ; Risk Assessment

Huge amount of data becomes available from the pharmaceutical manufacturing process with wide application of in- dustrial automatic control technology in traditional Chinese medicine (TCM) industry. The industrial big data thus provides golden op- portunities to better understand the manufacturing process and improve the process performance. Therefore it is important to implement data integration and management systems in TCM plants to easily collect, integrate, store, analyze, communicate and visulize the data with high efficiency. It could break the data island and discover useful information and knowledge to improve the manufacturing process performance. The key supporting technologies for TCM manufacturing and industrial big data management were introduced in this paper, with a specific focus on data mining and visualization technologies. Using historic data collected from a manufacturing plant of Shengmai injection of SZYY group, we illustrated the usefulness and discussed future prospects of data mining and visualization technologies.
Cluster Analysis ; Computer Graphics ; Data Mining ; methods ; Manufactured Materials ; Medicine, Chinese Traditional ; methods ; Quality Control

OBJECTIVETo investigate the relationship between hormone sensitive lipase (HSL) gene polymorphism and aerobic endurance.

METHODSThe (CA)n repeats polymorphism genotypes in HSL intro 6 of 123 outstanding long distance runners and 127 controls of Han nationality in northern China were analyzed by PCR and Fluorescence labeled STR-genescan. Repeat polymorphisms were grouped according to segmentation point and alleles were divided into long or short chains. Chi-square test was used to analyze the frequency difference of allelic and genotypic between athlete and control groups.

RESULTS(CA) n repeats polymorphism in HSL gene was total of 9 different repeat number of alleles, which composed of 25 different genotypes. The chi-square test result showed that when compared short and long chain alleles split by 4, there was a significant difference (P <0.05) of genotype distribution in 5/10 km group compared with control. Compared the rest groups with control, there was no significant difference.

CONCLUSIONCompared short and long chain alleles split by 4, the LL genotype of (CA)n of HSL was associated with aerobic endurance and it might be a molecular marker of elite 5/10 km long distance runners.

Alleles ; China ; Ethnic Groups ; Genotype ; Humans ; Physical Endurance ; Polymerase Chain Reaction ; Polymorphism, Genetic ; Sterol Esterase ; genetics

Objective To investigate the epidemiology of bacterial infections after liver transplantation and anaIyze the antimi- crobial susceptibility of major pathogens to provide reference for clinical therapy.Methods A retrospective survey was conduc ted in 174 patients who underwent liver transplantation during 2001 and 2004.Identification and susceptibility of pathogens were assayed by Microscan Walkaway 40 Automatic System.Results Infection was identified in 59.8% of the 174 patients after liver transplantation.A total of 218 non-duplicate strains were isolated.Most infections were caused by single pathogen.The infection was frequently identified in respiratory tract,biliary tract,blood stream or intra-abdominal cavity.The top 5 patho- gens were Acinetobacter baumannii,Staphylococcus aureus,Pseudomonas aeruginosa,Stenotrophomonas maltophilia and Escherichia coli.Gram-negative bacilli were usually resistant to multiple antimicrobial agents,but less resistant to piperacillin- tazobactam or imipenem.Most of S.aureus isolates were methicillin-resistant,which were susceptible to vancomyein.Conclu- sions Pathogens of postoperative infections in liver transplantation recipients are mostly multi-drug resistant.The microbiologi- cal surveillance is important for guiding clinical therapy.

A set of central composite design experiments were designed by using four factors which were ethanol amount, ethanol concentration, refrigeration temperature and refrigeration time. The relation between these factors with the target variables of the retention rate of schizandrol A, the soluble solids content, the removal rate of fructose and the removal rate of glucose were analyzed with Bayesian networks, and ethanol amount and ethanol concentration were found as the critical process parameters. Then a network model was built with 2 inputs and 4 outputs using back propagation artificial neural networks which was optimized by genetic algorithms. The R2 and MSE from the training set were 0.983 8 and 0.001 1. The R2 and MSE from the test set were 0.975 9 and 0.001 8. The results showed that network analysis method could be used for modeling of Schisandrae Chinensis Fructus ethanol precipitation process and identify critical operating parameters.
Bayes Theorem ; Chemical Precipitation ; Cold Temperature ; Cyclooctanes ; chemistry ; Ethanol ; chemistry ; Fructose ; analysis ; Fruit ; chemistry ; Glucose ; analysis ; Lignans ; chemistry ; Neural Networks (Computer) ; Polycyclic Compounds ; chemistry ; Reproducibility of Results ; Schisandra ; chemistry ; Time Factors

It is the objective of this study to optimize the extraction process of red ginseng to minimize the unit cost of extracting effective ingredients. The relation between the target variables of total quantity of ginsenosides and first extraction time, first extraction solution amount, second extraction time, second extract solution amount were studied with Box-Behnken experimental design method. At the same we also considered the cost of extraction solution and energy usage. The objective function was set as unit cost of target (total quantity of ginsenosides or its purity) for the multi-objective optimization of extraction process. As a result, the optimal process parameters were found as first extraction time (108.7 min), first extraction solution amount folds (12), second extraction time (30 min), second extraction solution amount folds (8) to minimize the unit cost. It indicated that this approach could potentially be used to optimize industrial extraction process for manufacturing Chinese medicine.
Chemistry, Pharmaceutical ; economics ; methods ; Cost Control ; Drugs, Chinese Herbal ; analysis ; economics ; isolation & purification ; Panax ; chemistry

It is the objective of this study to develop dynamic predictive model for the extraction process of red Ginseng using NIR spectroscopy. NIR spectroscopy was collected online and PLSR models were developed for total quantity of ginsenosides. The performance of NIR prediction model achieved R, RMSEC, RMSEP of 0.996 09, 0.018 9, 0.016 8, respectively. A first order dynamic mass transfer model was combined with NIR prediction of the quality indicator to predict the trajectory of the extraction process based upon the initial 3 or 4 data points. The results showed good agreement with actual measurements indicating reasonable accuracy of the predictive model. It could potentially be used for advanced predictive control of the extraction process.
Chemical Fractionation ; methods ; Ginsenosides ; chemistry ; isolation & purification ; Models, Theoretical ; Panax ; chemistry ; Spectroscopy, Near-Infrared

Air ; analysis ; Air Pollutants, Occupational ; analysis ; Chromatography, Gas ; methods ; Environmental Monitoring ; methods ; Toluene ; analogs & derivatives ; analysis ; Workplace

Objective To investigate the present status of casualty epidemiology in Zhengzhou and the effects of different trauma care model.Method Statistic study of the classification of emergency disease and the number of ambulance responses to the call in Zhengzhou emergency rescue center from January,2004 through December 2006 was carried out and the efficiency between the trauma care model of an inclusive emergency rescue survices station and that of a simple emergency survices station was analyzed.Results The percentage of ambulance departure responses by Zbengzhou emergency rescue center for trauma care was 45.3 %,44.7 % and 45.8% of in 2004,2005 and 2006,respectively.There were 26 emergency rescue service stationa in Zhengzhou, including one independent station,eight internal medicine dominated semi-independent stations and seventeen simple model stations.The indicated surgical intervention can lye performed on the patients with severe multi- trauma in the independent emergency station in order to win the optimal operation time and reduce the mortality. Conclusions The trauma is the major reason for the emergency call.Emergency rescue service stations properly distrihtted,can offer quick and efficient pro-hospital first aid.The independent emergency rescue service station can increase successful resuscitation rate of serious casualties.

BACKGROUND: Recent studies have demonstrated that sterol regulatory element binding protein-2 (SREBP-2) plays a key role in osteoarthritis, but its exact pathogenesis remains incompletely understood yet. OBJECTIVE:To investigate the expression of SREBP-2 in the process of interleukin-1β-induced articular chondrocyte degenerationin vitro. METHODS: Articular chondrocytes obtained from C57BL/6J mice were culturedin vitro. After the second passage, cels were randomly divided into four groups: control group, and three experimental groups treated with 10 μg/L interleukin-1β for 24, 48 and 72 hours, respectively. RESULTS AND CONCLUSION:The cels became hypertrophic after being stimulated by interleukin-1β, and the staining of colagen X was positive at 72 hours. MTT assay demonstrated that the cel activity after stimulation with interleukin-1β decreased with time. Results of RT-PCR showed that the expression of SREBP-2 and SREBP cleavage activating protein mRNA was significantly increased after stimulation with interleukin-1βas compared with the control group and increased with time. On the contrary, the expression of aggrecan and colagen II mRNA was decreased with time. It is revealed that interleukin-1β could inhibit the proliferation of regular chondrocytes and the expression of its extracelular matrix, and furthermore, induce chondrocyte hypertrophy. The expression of SREBP-2 showed a negative relationship with key cartilage genes during this interleukin-1β-induced degeneration.