Our investigation showed hospital pharmacists in a northern region of China had a reasonable knowledge of and positive attitudes towards pharmacovigilance. However, the majority of pharmacists had never reported an ADR in their career. Pharmacists' ADR education and increasing involvement in patient care would be important in improving ADR reporting in hospitals.

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Objective: To determine associations between lipid profiles in early pregnancy stratified by body mass index (BMI) and risk of developing gestational diabetes mellitus (GDM). Study Design: A total of 2488 healthy pregnant women were enrolled prospectively. Fasting plasma lipid profiles were measured at mean 11 weeks of gestation including triglycerides (TGs), total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and cholesterol (CHO). We assessed early pregnancy maternal lipid concentrations in different tertiles in association with the risk of GDM stratified for BMI. Multivariable logistic regression analyses were used to estimate the relative risk of GDM by calculating odds ratios and 95% confidence intervals (CIs). Results: In univariate analyses, pregnant women with GDM had significantly increased serum TG, CHO, LDL concentrations, LDL/HDL ratio, and decreased LDL concentrations, compared to control groups, each P < .01, respectively. After adjustment for confounders, there was a 1.8-fold increase in risk for GDM in the lean group (95% CI: 1.2-2.7) and 2.7-fold increase in the obese group (95% CI: 1.1-6.6), respectively, if TG 1.58 mmol/L. About a 50% decrease in the risk of GDM was observed in lean women with HDL 2.22 mmol/L (95% CI: 0.3-0.9). No significant correlations of other lipid profiles with the risk of developing GDM were observed. Conclusion: Early pregnancy dyslipidemia is associated with the risk of developing GDM. Lean or obese women with higher TG concentrations are at an increased risk for developing GDM while lean women with high HDL are protected.

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The application of lithium-ion (Li-ion) battery energy storage system (BESS) to achieve the dispatchability of a renewable power plant is examined. By taking into consideration the effects of battery cell degradation evaluated using electrochemical principles, a power flow model (PFM) of the BESS is developed specifically for use in system-level study. The PFM allows the long-term performance and lifetime of the battery be predicted as when the BESS is undertaking the power dispatch control task. Furthermore, a binary mode BESS control scheme is proposed to prevent the possible over-charge/overdischarge of the BESS due to the uncertain renewable input power. Analysis of the resulting new dispatch control scheme shows that a proposed adaptive BESS state of energy controller can guarantee the stability of the dispatch process. A particle swarm optimization algorithm is developed and is incorporated into a computational procedure for which the optimum battery capacity and power rating are determined, through minimizing the capital cost of the BESS plus the penalty cost of violating the dispatch power commitment. Results of numerical examples used to illustrate the proposed design approach show that in order to achieve hourly-constant power dispatchability of a 100-MW wind farm, the minimum-cost Li-ion BESS is rated 31-MW/22.6-MWh.