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.     

基于指标自动筛选的新疆开孔河流域生态健康评价

生态健康评价对了解区域生态健康状况和促进区域可持续发展具有重要意义,如何自动筛选出能反映生态系统特性的重要指标,是生态健康定量评估的关键问题。基于压力-状态-响应(PSR,Press-State-Response)框架和生态等级网络框架(EHN,Ecological Hierarchy Network),通过文献调研和因果分析建立要素层与指标层之间的交叉联系,构建了生态健康评价"网状"指标体系;在保证指标体系完备性基础上,通过结合主成分分析和熵权法的候选指标权重的客观计算,基于目标优化理论构建了评价指标的自动筛选模型,并基于中选指标计算了新疆开孔河流域2001—2017年生态健康指数(EHCI,Ecological Health Comprehensive Indexes),分析其空间分异和时间变化特征。结果表明:利用所建立的评价指标自动筛选模型,开孔河流域生态健康评价指标由31个候选指标自动筛选出了17个中选指标,用54.8%的指标表达了85.98%的信息,中选的17个指标在干旱/半干旱区域有关文献中应用较多,使用频次比例都在20%以上,其中归一化植被指数(NDVI,Normalized Difference Vegetation Index)、年降水量和植被覆盖度(FVC,Fractional Vegetation Coverage)3个指标的使用频次百分比均超过了50%,说明指标自动筛选模型的合理性;开孔河流域空间分布差异显著,总体上西北高、东南低,东南部和中部绿洲区外围生态健康状况较差,西北部河谷地带和中部两大绿洲区生态健康状况较好;17年来,流域生态质量整体趋于改善,显著改善区域占10.26%,远高于显著退化的1.61%,显著改善区域以孔雀河绿洲最为明显。开孔河流域生态健康的总体好转趋势说明区域生态综合治理取得一定成效。     

Stochastic Sensitivity Analysis and Kernel Inference via Distributional Data

Cellular processes are noisy due to the stochastic nature of biochemical reactions. As such, it is impossible to predict the exact quantity of a molecule or other attributes at the single-cell level. However, the distribution of a molecule over a population is often deterministic and is governed by the underlying regulatory networks relevant to the cellular functionality of interest. Recent studies have started to exploit this property to infer network states. To facilitate the analysis of distributional data in a general experimental setting, we introduce a computational framework to efficiently characterize the sensitivity of distributional output to changes in external stimuli. Further, we establish a probability-divergence-based kernel regression model to accurately infer signal level based on distribution measurements. Our methodology is applicable to any biological system subject to stochastic dynamics and can be used to elucidate how population-based information processing may contribute to organism-level functionality. It also lays the foundation for engineering synthetic biological systems that exploit population decoding to more robustly perform various biocomputation tasks, such as disease diagnostics and environmental-pollutant sensing.     

Identification of chalcone synthase genes and their expression patterns reveal pollen abortion in cotton

Chalcone synthase (CHS) is a key enzyme and producing flavonoid derivatives as well play a vital roles in sustaining plant growth and development. However, the systematic and comprehensive analysis of CHS genes in island cotton (G. barbadense) has not been reported yet especially response to cytoplasmic male sterility (CMS). To fill this knowledge gap, a genome-wide investigation of CHS genes were studied in island cotton. A total of 20 GbCHS genes were identified and grouped into five GbCHSs. The gene structure analysis revealed that most of GbCHS genes consisted of two exons and one intron, and 20 motifs were identified. Twenty five pairs duplicated events (12 GbCHS genes) were identified including 23 segmental duplication pairs and two tandem duplication events, representing that GbCHS gene family amplification mainly owned to segmental duplication events and evolving slowly. Gene expression analysis exhibited that the GbCHS family genes presented a diversity expression patterns in various organs of cotton. Coupled with functional predictions and gene expression, the abnormal expression of GbCHS06, 10, 16 and 19 might be associated with pollen abortion of CMS line in island cotton. Conclusively, GbCHS genes exhibited diversity and conservation in many aspects, which will help to better understand functional studies and a reference for CHS research in island cotton and other plants.     

F10蛋白及mRNA在部分正常组织及癌组织中的表达

目的:了解F10基因在部分正常组织及肿瘤组织中的表达情况。方法:利用原位杂交和免疫组化方法对F10在部分正常组织和肿瘤组织中的mRNA和蛋白表达情况进行分析。结果:F10基因不仅在腺癌组织中表达呈阳性,在鳞癌组织中表现出较腺癌更强的强阳性,并且在正常组织中也有一定的表达。结论:F10是一个在多种组织普遍表达的细胞内蛋白,其功能可能与物质转运相关。