SC-ICP-MS法测定金属元素的方法研究

为了使用单细胞电感耦合等离子体质谱(SC-ICP-MS)方法准确测定单个细胞中的铬(Cr)、锰(Mn)、铁(Fe)、铜(Cu)和锌(Zn)等多种内源性金属元素,该文基于动态反应池(DRC)模式对目标分析物的反应气流量和极杆抑制参数q(RPq)进行了优化,并研究了进样速度、细胞密度、驻留时间等因素对SC-ICP-MS检测的影响。分别采用细胞悬液直接进样、使用超声波探头使细胞悬液中的细胞破碎后进样和使用浓硝酸消解细胞后进样的ICP-MS测定结果对SC-ICP-MS定量结果的准确性进行验证分析。实验结果表明,可采用超声波破碎细胞的ICP-MS测定结果评估SC-ICP-MS测定的单细胞内Zn和Cu含量的准确性,采用酸消解细胞的ICP-MS检测结果验证单细胞内Fe和Cr的含量。缺少细胞标准物质时对SC-ICP-MS方法定量结果进行多角度验证是必要的。研究表明,使用SC-ICP-MS法可以较好地进行单细胞元素相关分析。     

Determination of Hydrocortisone in Cosmetics by CdSe/CdS Quantum Dots-Based Fluoroimmunoassay Using Magnetic Fe3O4/Au Nanoparticles as Solid Carriers

This work demonstrated the feasibility of detecting hydrocortisone in cosmetics using a novel CdSe/CdS quantum dots‐based competitive fluoroimmunoassay with magnetic core/shell Fe₃O₄/Au nanoparticles (MCFN) as solid carriers. Hydrocortisone antigen was labeled with the synthesized core/shell CdSe/CdS quantum dots (QDs) to form the antigen‐QDs conjugate. Meanwhile, hydrocortisone antibody was incubated with MCFN and the immobilized antibody was obtained. The immobilized antibody was then mixed sequentially with hydrocortisone and a slightly excess amount of the QDs‐labeled hydrocortisone antigen, allowing their competition for binding with the antibody immobilized on MCFN. The bound hydrocortisone and the antigen‐QDs conjugates on MCFN were removed subsequently after the mixture was applied to a magnetic force. The analyte concentration was obtained by measuring the fluorescence intensity of the unbound hydrocortisone antigen‐QDs conjugates. The proposed method was characterized by simplicity, rapidity, and high sensitivity with a wide linear working range of 0.5 to 15000 pg·mL^?1 and a low detection limit of 0.5 pg·mL^?1. The proposed method was successfully applied to the determination of hydrocortisone in cosmetics with satisfactory results.     

边界振动的微腔中薛定谔猫态的产生

采用全量子理论,考虑了边界振动的微腔(振动边界视作频率为ωm的量子谐振子)与单模辐射场构成的系统,在薛定谔绘景中,给出了系统的时间演化算符,得到了系统的态函数随时间的演化关系.结果表明,当振动边界回到初态时的腔场态能给出许多与已有文献不同的薛定谔猫态,且通过调整单模辐射场的频率可以选择想要的薛定谔猫态.     

准经典轨线方法对Ca+CD3Ⅰ→CaⅠ+CD3同位素效应的动力学研究

在扩展Lond-Eyring-Polanyi-Sato(LEPS)势能面上,采用准经典轨线方法对反应Ca+CD3I→CaI+CD3进行了动力学计算,并讨论了该反应的同位素效应.在同位素效应作用下,产物CaI的振动态分布向低振动态转移,反应体系的散射截面在低碰撞能和高碰撞能处有较小的变化.同时,受到反应物的质量因子变化的影响,产物转动取向值减少,产物转动取向增强.仅有产物的角分布受同位素效应的影响不明显.     

双－苯并噻唑非环冠醚的合成与表征

2-巯基苯并噻唑(MBT)与二溴缩甘醇在碳酸钾存在下发生S-烷基化反应生成双－苯并噻唑非环冠醚化合物1～4,并通过元素分析、IR、NMR(^1H,^13C)、MS波谱进行结构表征。     

Highly efficient NMR enantiodiscrimination of 1,1,1,3,3-pentafluoro-2-(fluoromethoxy)-3-methoxypropane,a chiral degradation product of sevoflurane,by heptakis(2,3-di-O-acetyl-6-O-tert-butyldimethylsilyl)-β-cyclodextrin

The molecular basis of the efficient enantiodiscrimination of 1,1,1,3,3-pentafluoro-2-(fluoromethoxy)-3-methoxypropane, a chiral degradation product of the inhalation anaesthetic sevoflurane, using heptakis(2,3-di-O-acetyl-6-O-tert-butyldimethylsilyl)-β-cyclodextrin as chiral selector, has been investigated by NMR spectroscopy. An interaction mechanism is proposed, which highlights the role of the functional groups on the β-cyclodextrin rims in addition to a partial molecular inclusion.     

汉字识别的加工模型

通过文献分析,概述了认知心理学关于汉字识别过程及其加工机制研究的几种主要的加工模型,即经成分识别模型、多层次交互激活模型、连接主义模型、合体汉字字形识别模型和汉字识别的多层次格式塔双向加工模型.     

超高效液相色谱-四极杆/静电场轨道阱高分辨质谱对粮谷产品中20种真菌毒素的快速筛查和确证

建立了超高效液相色谱-四极杆/静电场轨道阱高分辨质谱快速筛查和确证粮谷产品中20种真菌毒素的方法。样品经乙腈（含2%（体积分数）甲酸）提取,用Captiva EMR-Lipid小柱净化,采用Thermo Hypersil Gold C₁₈柱（100 mm×2.1 mm,1.9 μm）分离,用四极杆/静电场轨道阱高分辨质谱进行分析。在全扫描模式下以分析物的保留时间和一级母离子信息实现快速筛查,以自动触发采集的二级碎片离子信息进行确证。结果显示,目标分析物在各自的质量浓度范围内线性关系良好（相关系数r²>0.99）,方法检出限为0.25~20 μg/kg,回收率为72.9%~117.8%,相对标准偏差为2.9%~15.2%（n=6）。该方法灵敏度高,结果准确、可靠,适用于粮谷产品中20种真菌毒素的快速筛查和确证。     

Higgs-boson two-loop contributions to electric dipole moments in the MSSM

The complete set of Higgs-boson two-loop contributions to electric dipole moments of the electron and neutron is calculated in the minimal supersymmetric standard model. The electric dipole moments are induced by CP-violating trilinear couplings of the `CP-odd' and charged Higgs bosons to the scalar top and bottom quarks. Numerical estimates of the individual two-loop contributions to electric dipole moments are given.     

Classification of visible and infrared hyperspectral images based on image segmentation and edge-preserving filtering

The classification of hyperspectral images with a few labeled samples is a major challenge which is difficult to meet unless some spatial characteristics can be exploited. In this study, we proposed a novel spectral-spatial hyperspectral image classification method that exploited spatial autocorrelation of hyperspectral images. First, image segmentation is performed on the hyperspectral image to assign each pixel to a homogeneous region. Second, the visible and infrared bands of hyperspectral image are partitioned into multiple subsets of adjacent bands, and each subset is merged into one band. Recursive edge-preserving filtering is performed on each merged band which utilizes the spectral information of neighborhood pixels. Third, the resulting spectral and spatial feature band set is classified using the SVM classifier. Finally, bilateral filtering is performed to remove “salt-and-pepper” noise in the classification result. To preserve the spatial structure of hyperspectral image, edge-preserving filtering is applied independently before and after the classification process. Experimental results on different hyperspectral images prove that the proposed spectral-spatial classification approach is robust and offers more classification accuracy than state-of-the-art methods when the number of labeled samples is small.