Advanced Nanomaterials for Multimodal Molecular Imaging

The development of multimodal molecular imaging contrast agents based on versatile nanomaterials has recently attracted much attention in disease diagnosis and therapeutic delivery. Contrast agents made from nanoparticles and used for multimodal imaging in vivo provide a multidimensional pathophysiological overview of diseases. This review summarizes recently developed advanced nanomaterials for multimodal molecular imaging. We comprehensively discuss these nanoparticle contrast agents in terms of their targeting modalities, limitations in clinical translation and future directions.     

升华剂2,4,6-三异丙基-1,3,5-三氧六环的晶体结构及其热力性质研究

以升华剂2,4,6-三异丙基-1,3,5-三氧六环为溶质,无水乙醇为溶剂,采用溶液挥发法培养了2,4,6-三异丙基-1,3,5-三氧六环的单晶.利用X-射线单晶衍射法测定其单晶结构,并通过紫外光谱、热重和X-射线粉末衍射等手段对其进行了表征.结果表明,标题化合物属于正交晶系,Pnma空间群,晶胞参数:a=0.827 7(3)nm,b=1.024 4(3)nm,c=1.683 1(5)nm,α=β=γ=90°,V=1.427 1(8)nm~3,Z=42,Mr=216.81,Dc=1.007g/cm~3,μ=0.070mm~(-1),F(000)=480.0,T=293(2)K,最终偏差因子(对I2σ(I)的衍射点)R1=0.083 7,wR2=0.264 8.化合物分子中的六元环呈椅式构型,分子间存在的弱氢键作用使得其沿c轴方向形成了一维无限链状结构.通过测量其饱和蒸气压随温度变化,按Clausius-ClaPeyron方程计算得出其升华焓为15.82kJ/mol,再结合热重TGA-DTA曲线、DSC曲线和焓变分析,可以判定升华剂在80℃之前没有发生分解产生新的物质.     

LF-NMR结合化学模式识别鉴别油脂种类及餐饮废弃油脂

应用主成分分析(Principal component analysis,PCA)和聚类分析法(Cluster analysis,CA)对9种(27个)常见食用植物油及100个餐饮废油的低场核磁共振(Low-field nuclear magnetic resonance,LF-NMR)(T2)弛豫特性数据进行分析。结果表明:在正常食用油种类区分方面,主成分分析的效果较优,9种食用油在主成分分布图上按种类正确分组,边界清晰。而在正常食用油与餐饮废油的区分方面,聚类分析效果较优,引入30个待测样本后,聚类分析(127个样品,欧式距离=5)的正确率为94.49%,分析误判率为5.51%,分组效果良好。LF-NMR结合化学模式识别可实现对油脂种类及餐饮废弃油脂的鉴别。     

基于内源性致香物质和化学计量学的烟草感官评价研究

采用主成分分析法结合遗传算法和神经网络,建立了基于烟草内源性致香物质的感官质量评价预测模型。利用气相色谱-质谱(GC-MS)技术对超临界萃取-分子蒸馏所得烟草精油中的内源性致香组分进行定性定量分析,汇总各类致香指标后,对其进行主成分分析;以提取所得5个主成分的得分作为输入变量,感官评吸分数作为输出变量,分别使用标准BP神经网络和遗传算法(GA)优化的BP神经网络建立预测模型。对比实验结果表明,GA优化后的模型预测效果更优,其预测值与实验值间的相关系数为0.96,预测均方根误差为1.81,说明GA-BP模型具有更好的拟合能力和预测能力,该模型能有效地预测烟草精油的感官品质。     

弱凝胶钻井液成胶剂AM/AMPS/OA_8的合成与表征

针对水平井、大斜度井钻井过程中井眼润滑性、岩屑携带以及钻井速度的影响等问题,通过合理的分子设计,以丙烯酰胺(AM)、2-丙烯酰胺-2-甲基丙磺酸(AMPS)和实验室自制疏水单体丙烯酸正辛醇OA_8为原料,利用胶束聚合法,制备了一种弱凝胶成胶剂AMAMPSOA_8,其结构经1H NMR和IR表征。以AMAMPSOA_8在低剪切速率下的表观粘度为指标设计正交试验,确定最优反应条件为:AM与AMPS摩尔配比为4.8∶1,引发剂用量为单体总质量的0.04%,疏水单体浓度为0.75%,于70℃反应9 h。该条件下,0.5%AMAMPS0A_8聚合物溶液在低剪切速率3 r·min~(-1)下表观粘度可达23 680 mPa·s。利用热分析仪、高温滚子炉、高温高压流变仪对产物性能进行了研究。研究表明:AMAMPSOA_8的抗温性能可达160℃;聚合物溶液体系有明显的触变性,在40 min后溶液切力增加幅度变缓。     

Nanomaterial Based Biosensors for Detection of Biomarkers of Exposure to OP Pesticides and Nerve Agents: A Review

Organophosphorus (OP) pesticides are primarily used as insecticides and chemical warfare agents worldwide. Due to their impact on the environment and health, it is important to develop prompt and accurate pesticide analysis method. This review addresses recent advances and new trends in nanotechnology‐based biosensors for biological monitoring of exposures to OP pesticides and nerve agents. In order to determine them, we have to find the corresponding biomarkers. In 1989, the national academy of sciences (NAS)divided biomarkers into the following three categories: biomarker of exposure, biomarker of effect and biomarker of susceptibility (Figure 1A). The unique chemical and physical properties of nanomaterial have paved the way to new and improved sensing devices, in general, and electrochemical/optical biosensors, in particular. In this paper, background information and a general overview of electrochemical/immunoassay detection techniques are provided. Various nanomaterial labels are discussed. Usually nanomaterials can be roughly divided into nanometer powder, nanometer fiber, nanometer film, nanometer block and so on four classes, such as colloidal gold, semiconductor nanoparticles and carbon nanomaterial (Figure 1B). In addition, we discuss some future considerations and opportunities for advancing the use of biosensors for environmental and health studies.     

Antibacterial thermoplastic polyurethane electrospun fiber mats prepared by 3-aminopropyltriethoxysilane-assisted adsorption of Ag nanoparticles

Antibacterial thermoplastic polyurethane(TPU) electrospun fiber mats were prepared by adsorption of Ag nanoparticles(Ag NPs) onto TPU/3-aminopropyltriethoxysilane(APS) co-electrospun fiber mats from silver sol. The use of APS can functionalize TPU fibers with amino groups, facilitating the adsorption of Ag NPs. The effects of p H of silver sol and APS content on Ag NP adsorption and antibacterial activity were investigated. Ag NP adsorption was evidenced by TEM, XPS and TGA. Significant Ag NP adsorption occurred at p H = 3-5. The main driving force for Ag NP adsorption is electrostatic interaction between ―NH3~+ of the fibers and ―COO-derived from the ―COOH group capped on the surfaces of Ag NPs. The antibacterial activity of the Ag NP-decorated TPU/APS fiber mats was investigated using both gram-negative Escherichia coli and gram-positive Bacillus subtilis. The antibacterial rate increases with increasing APS content up to 5% where the antibacterial rates against both types of bacteria are over 99.9%.     

无模板法水热合成CoTe及其可见光光催化还原CO_2性能

本文利用无模版水热法合成了碲化钴(CoTe)纳米催化剂。为了避免引入残炭,所有的反应物均为无机化合物。利用X射线衍射(XRD)、扫描电子显微镜(SEM)、紫外-可见(UV-Vis)吸收光谱和X射线光电子能谱(XPS)等技术对所制备的CoTe纳米材料进行了表征。结果表明,所得产物为具有六方结构的海绵状CoTe,且具有可见光(λ420 nm)光催化活性。当以N,N-二甲基乙酰胺(DMA)或纯水为溶剂时,二氧化碳(CO_2)均可被光催化还原为甲烷(CH_4),但产率较低。而在催化体系中加入牺牲剂三乙醇胺(TEOA)后,产物由CH_4变为一氧化碳(CO)。这些实验结果表明,溶剂和牺牲剂的引入均可影响CoTe纳米催化剂对CO_2的光催化还原性能。     

基于旋转变换和鲁棒主成分分析的车牌校正方法

本文研究了受到非高斯噪声污染及边框信息不完整的车牌图像校正的问题.利用鲁棒主成分分析与旋转变换结合的方法,获得了更具普适性的车牌矫正方法.并通过与主成分分析法、旋转投影法的矫正结果相比较,推广了本文方法具有更好的鲁棒性和普适性的结果.     

Characterization of Chickpea Flour by Near Infrared Spectroscopy and Chemometrics

Near infrared (NIR) spectrometry was used for the rapid characterization of quality parameters in desi chickpea flour (besan). Partial least square regression, principal component regression (PCR), interval partial least squares (iPLS), and synergy interval partial least squares (siPLS) were used to determine the protein, carbohydrate, fat, and moisture concentrations of besan. Spectra were collected in reflectance mode using a lab-built predispersive filter-based instrument from 700 to 2500?nm. The quality parameters were also determined by standard methods. The root mean square error (RMSE) for the calibration and validation sets was used to evaluate the performance of the models. The correlation coefficients for moisture, fat, protein, and carbohydrates in chickpea flour exceeded 0.96 using PLS and PCR models using the full spectral range. Wavelengths from 2100 to 2345?nm had the lowest RMSE for quality parameters by iPLS. The error was further decreased by 0.41, 0.1, and 1.1% for carbohydrates, fats, and proteins by siPLS. The NIR spectral regions yielding the lowest RMSE of prediction were 1620–2345?nm for carbohydrates, 1180–1590?nm and 1860–2094?nm for fat, and 1700–2345?nm for proteins. The study shows that chickpea flour quality parameters were accurately determined using the optimized wavelengths.