eEF-2 Phosphorylation Down-Regulates P-Glycoprotein Over-Expression in Rat Brain Microvessel Endothelial Cells

ObjectiveWe investigated whether glutamate, NMDA receptors, and eukaryote elongation factor-2 kinase (eEF-2K)/eEF-2 regulate P-glycoprotein expression, and the effects of the eEF-2K inhibitor NH125 on the expression of P-glycoprotein in rat brain microvessel endothelial cells (RBMECs).MethodsCortex was obtained from newborn Wistar rat brains. After surface vessels and meninges were removed, the pellet containing microvessels was resuspended and incubated at 37°C in culture medium. Cell viability was assessed by the MTT assay. RBMECs were identified by immunohistochemistry with anti-vWF. P-glycoprotein, phospho-eEF-2, and eEF-2 expression were determined by western blot analysis. Mdr1a gene expression was analyzed by RT-PCR.ResultsMdr1a mRNA, P-glycoprotein and phospho-eEF-2 expression increased in L-glutamate stimulated RBMECs. P-glycoprotein and phospho-eEF-2 expression were down-regulated after NH125 treatment in L-glutamate stimulated RBMECs.ConclusionseEF-2K/eEF-2 should have played an important role in the regulation of P-glycoprotein expression in RBMECs. eEF-2K inhibitor NH125 could serve as an efficacious anti-multidrug resistant agent.     

Statistical Inference Methods for Two Crossing Survival Curves: A Comparison of Methods

A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman’s smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér—von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman’s smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.     

药物组合物封闭式权利要求的解读与侵权判定 ——由最高人民法院（2012)民提字第10号判决案例谈起

从最高人民法院的一个典型案例出发，探讨药物组合物封闭式权利要求保护范围的解读及其专利侵权判定标准，比较其他国家 的相关规定和判例，并对药物组合物封闭式权利要求的专利授权、确权审查、侵权判定以及申请文件撰写技巧提出见解，以供借鉴和参考。     

Phylogenetic diversity is a better predictor of wetland community resistance to Alternanthera philoxeroides invasion than species richness

• Highly biodiversity communities have been shown to better resist plant invasions through complementarity effects. Species richness (SR) is a widely used biodiversity metric but lacks explanatory power when there are only a few species. Communities with low SR can have a wide variety of phylogenetic diversities (PD), which might allow for a better prediction of invasibility.
• We assessed the effect of diversity reduction of a wetland community assemblage typical of the Beijing area on biotic resistance to invasion of the exotic weed Alternanthera philoxeroides and compared the reduction in SR and PD in predicting community invasibility.
• The eight studied resident species performed similarly when grown alone and when grown in eight‐species communities together with the invasive A. philoxeroides. Variation partitioning showed that PD contributed more to variation in both A. philoxeroides traits and community indicators than SR. All A. philoxeroides traits and community indicators, except for evenness index, showed a linear relationship with PD. However, only stem length of A. philoxeroides differed between the one‐ and two‐species treatments, and the diversity index of the communities differed between the one‐ and two‐species treatments and between the one‐ and four‐species treatments.
• Our results showed that in natural or semi‐natural wetlands with relatively low SR, PD may be a better predictor of invasibility than SR. When designing management strategies for mitigating A. philoxeroides invasion, deliberately raising PD is expected to be more efficient than simply increasing species number.

     

Enrichment of AT-TA transversion at 5′-CAG-3′ motif is not a unique mutational signature of aristolochic acid

<正>Aristolochic acids, mutational signature, and hepatocellular carcinoma Aristolochic acids (AA) are the etiologic agents of aristolochic acid nephropathy (AAN) and contribute to the global prevalence of chronic kidney disease and urothelial cancer (Grollman et al., 2007). DNA adducts formed by AA generate a unique AT transversions mutation spectrum at     

Theoretical calculation of the sugar concentrations during enzymatic production of fructooligosaccharides

Summary In a batch production of fructooligosaccharides from sucrose, the concentrations of residual sucrose, glucose and fructooligosaccharides at a given reaction time(t) and initial sucrose concentration(S₀) were theoretically calculated by the following correlation equations: Glucose(t) = 0.0653 S₀ × ln(t); Fructooligosaccharides(t) = 0.1636 S₀ × ln(t); Sucrose(t)=S₀ - Glucose(t) + FOS(t).