二溴羧基偶氮胂测定铜

二溴羧基偶氮胂测定铜谢治民，欧阳则明，龙有前（湖南湘潭机电专科学校，４１１１０１）二溴羧基偶氮胂是测定稀土的高灵敏的新显色试剂￣［１］，我们用二溴羧基偶氮胂用于铜的试验，结果发现在ｐＨ８磷酸氢二钠－柠檬酸的缓冲介质中有良好的显色反应，配合物在波长５８...     

以聚乙二醇-b-聚四乙烯基吡啶为模板制备聚联苯胺微/纳米颗粒及其电容特性

以两亲性嵌段共聚物聚乙二醇-b-聚四乙烯基吡啶(PEO-b-P4VP)为模板制备聚联苯胺微/纳米颗粒,调节模板剂胶束溶液pH,得到了一系列形貌和尺寸可控的聚联苯胺微/纳米颗粒。利用红外光谱、核磁共振、透射电镜、循环伏安、恒电流放电、交流阻抗等测试对材料的结构和性能进行了表征。模板法合成的聚联苯胺为平均直径小于200nm的亚微米至纳米级棒状颗粒,其直径随着模板剂胶束溶液pH的降低而增加。所得聚联苯胺颗粒均显示了一定的电化学活性,当电流密度为1A/g时,聚联苯胺的比电容量达到306.3F/g,经过长时间的充放电测试,不同条件下合成的聚联苯胺的容量衰减率均很小,表现出良好的循环稳定性且各样品电化学性能呈现出随着直径的减小而增强的趋势。     

Empetrifranzinans A和Empetrifranzinans C的全合成及其抗肿瘤活性

以间苯三酚为起始原料,L-脯氨酸为催化剂,经由两步反应首次合成了Empetrifranzinans A(1a,总收率60%)和Empetrifranzinans C(总收率55%),其结构经1H NMR,13C NMR和HR-MS确证。初步药理筛选实验结果表明,1a对人结肠癌、肝癌、胃癌、肺腺癌、卵巢癌细胞表现出了较强的细胞毒作用,其IC50分别为<0.1,1.31,4.90,8.98和3.65μmol·L-1。     

毛细管电泳技术快速检测牙周病原菌

建立了毛细管电泳快速检测牙龈卟啉单胞菌(P.g)、齿垢密螺旋体(T.d)、福赛斯坦纳菌(T.f)3种牙周病病原菌种的方法。紫外分光光度法表明,采用无菌吸潮纸尖及PBS缓冲液可以实现牙周病原菌的快速有效提取。对提取的牙周病病原菌种做多聚酶链式反应(PCR)与多重PCR反应,最后以20 cm长,75μm内径的石英毛细管作为分离通道,分离电压4000 V,1.2%羟乙基纤维素(HEC,250 K)为筛分介质,牙周病病原菌菌种P.g,T.d,T.f PCR及多重PCR产物12 min内得到较好分离。结果表明,毛细管电泳与PCR技术相结合,可以实现牙周病原菌种快速鉴定,且检测限低至4.80×10-11ng/μL。方法已用于牙周病原菌菌种的快速检测。     

基于UPLC-MS/MS的2型糖尿病患者血清胆汁酸代谢产物分析

应用基于超高效液相色谱-串联质谱(UPLC-MS/MS)技术的代谢组学方法检测2型糖尿病患者血清胆汁酸代谢谱,获得代谢标志物,发掘可预测糖尿病的潜在预防治疗靶点。采用Waters ACQUITY UPLC BEH C18色谱柱(150 mm×2.1 mm,1.7 μm)分离,0.05%乙酸水溶液-乙腈为流动相,以0.40 mL/min流速进行梯度洗脱,用此方法测定了30例糖尿病患者和 50例正常人血清胆汁酸代谢谱。41种胆汁酸标准品在30 min内均得到良好分离,各成分在一定浓度范围内呈良好线性关系,检出限(LOD)为0.24~7.81 nmol/L,定量下限(LOQ)为0.49~15.63 nmol/L,相关系数(r2)为 0.986 7~0.999 7。血清中胆汁酸代谢谱与两组间存在相关性,通过正交偏最小二乘法-判别分析(OPLS-DA)发现,有12种胆汁酸(包括甘氨熊脱氧胆酸、甘氨胆酸、牛磺鹅脱氧胆酸、胆酸、熊去氧胆酸、甘氨鹅脱氧胆酸、甘氨脱氧胆酸、12 酮基石胆酸、鹅脱氧胆酸、脱氧胆酸、异石胆酸、石胆酸)承载了分组的重要信息。结合受试者工作特征(ROC)分析,最终获得牛磺鹅脱氧胆酸(AUC=0.68)、甘氨鹅脱氧胆酸(AUC=0.66)、甘氨熊脱氧胆酸(AUC=0.63)、胆酸(AUC=0.63)、脱氧胆酸(AUC=0.63)、甘氨脱氧胆酸(AUC=0.58) 6种胆汁酸代谢标志物,对于糖尿病的早期诊断及深入研究具有潜在的科研及临床价值。     

钛合金表面双层辉光离子无氢渗碳层摩擦磨损性能研究

利用双层辉光放电离子渗碳原理,以格栅状高纯度固体石墨作为源极,钛合金作为阴极,氩气作为工作气体,依靠辉光放电和空心阴极效应在钛合金(Ti6Al4V)材料表面制备了具有特殊物理、化学性能的渗碳层;采用X射线衍射和辉光放电光谱分析了渗碳层的相组成及C元素分布;并考察了渗层的摩擦磨损性能.结果表明:复合渗碳层中形成了高硬相TiC及游离态C减摩相;渗层内C元素的含量呈梯度分布;经复合渗碳处理后材料的表面硬度大幅度提高,由表及里硬度成梯度降低;经渗碳处理后材料的减摩和抗磨性能显著改善,摩擦系数降低50%以上,比磨损率降低3个以上数量级.     

Multi-Model Communication and Data Assimilation for Mitigating Model Error and Improving Forecasts

Models for weather and climate prediction are complex, and each model typi-cally has at least a small number of phenomena that are poorly represented, such as perhaps the Madden-Julian Oscillation (MJO for short) or El Ni\~{n}o-Southern Oscillation (ENSO for short) or sea ice. Furthermore, it is often a very challenging task to modify and improve a complex model without creating new deficiencies. On the other hand, it is sometimes possible to design a low-dimensional model for a particular phenomenon, such as the MJO or ENSO, with significant skill, although the model may not represent the dynamics of the full weather-climate system. Here a strategy is proposed to mitigate these model errors by taking advantage of each model''s strengths. The strategy involves inter-model data assimilation, during a forecast simulation, whereby models can exchange information in order to obtain more faithful representations of the full weather-climate system. As an initial investigation, the method is examined here using a simplified scenario of linear models, involving a system of stochastic partial differential equations (SPDEs for short) as an imperfect tropical climate model and stochastic differential equations (SDEs for short) as a low-dimensional model for the MJO. It is shown that the MJO prediction skill of the imperfect climate model can be enhanced to equal the predictive skill of the low-dimensional model. Such an approach could provide a route to improving global model forecasts in a minimally invasive way, with modifications to the prediction system but without modifying the complex global physical model itself.