竞争包结法研究β-环糊精及其衍生物对灯盏花乙素的选择键合

以酚酞作为光谱探针,采用紫外-可见光谱滴定法测定了β-环糊精(β-CD),单(6-脱氧-乙二胺)-β-环糊精(en-β-CD),单(6-脱氧-二乙基三胺)-β-环糊精(dien-β-CD),羟丙基-β-环糊精(HP-β-CD),磺丁基醚-β-环糊精(SBE-β-CD)在30℃时,pH=10.50的0.025mol/L缓冲液中与灯盏花乙素所形成超分子配合物的稳定常数。结果表明,多种弱相互作用力协同作用于环糊精的配位过程,主-客体间的尺寸匹配决定所形成配合物的稳定性,环糊精衍生物的取代基影响主体的配位能力。5种环糊精主体化合物对灯盏花乙素客体分子的包合能力大小为:β-CDSBE-β-CDen-β-CDdien-β-CDHP-β-CD。     

薰衣草精油的衰减全反射红外光谱辨别分析

为建立薰衣草精油品种品质的快速辨别分析模型,采用衰减全反射红外光谱法测定三个品种共96个薰衣草精油样品,对原始光谱数据求二阶导数,通过方差计算,确定1 750～900 cm-1波长段为判别分析用数据。分析结果表明,主成分分析(PCA)基本能实现精油品种区分,前三个主成分主要代表着酯、醇和萜类物质。使用68个样品的校正集建立正交偏最小二乘判别分析(OPLS-DA)模型,三个品种薰衣草精油的回归曲线测定系数分别为0.959 2, 0.976 4, 0.958 8,验证集中三个品种精油预测均方根误差(RMSEP)分别为0.142 9, 0.127 3, 0.124 9,OPLS-DA法建立的模型对校正集和验证集的判别率和预测率都达到100%,模型对薰衣草精油品种品质有很好的识别能力。为薰衣草精油品种品质提供一个快速、直观的方法。     

LNG-HP-β-CD包合物制备、表征及其紫外稳定性研究

左炔诺孕酮(LNG)不溶于水和紫外光照易分解的特点,限制了其在鼠类不育剂中的应用。该研究采用溶液法,制备出LNG的羟丙基-β-环糊精(HP-β-CD)包合物,建立了准确简便的紫外光谱定量检测方法;通过相溶解度法确定了HP-β-CD与LNG的包合摩尔比为1∶1,25 ℃时LNG-HP-β-CD包合物的稳定常数为187.3 L·mol-1;通过紫外光谱、傅里叶变换红外光谱表征,验证了包合物的形成;对包合物的抗紫外光降解性能进行了测试,表明在50 h内包合物的降解率小于5%,远低于药物单体。结果表明,HP-β-CD对LNG具有良好的包合作用,可显著提高该药物的水溶性和紫外稳定性。     

水杨酸甲酯在β-环糊精水溶液中的双重荧光光谱

研究了β-环糊精(β-CD)及其衍生物甲基-β-环糊精(M-β-CD)、羟丙基-β-环糊精(HP-β-CD)对水杨酸甲酯(MS)双重荧光光谱的影响,并将其与MS在不同溶剂中的荧光光谱进行对比。结果表明,MS的双重荧光与所处微环境的氢键性质密切相关,β-CD取代基的大小会导致空腔口处的极性和空间位阻不同,相应改变了分子间氢键相互作用,当MS分子进入β-CDs空腔时会引起其基态互变异构体之间平衡的移动,从而导致光谱的变化。包合物稳定常数测定表明,三种β-CDs对MS包合能力的大小为M-β-CD>HP-β-CD>β-CD。     

环糊精衍生物对野黄芩素的增溶作用

采用相溶解度法考察了25℃时羟丙基-β-环糊精(HP-β-CD)、乙二胺-β-环糊精(en-β-CD)、二乙烯三胺-β-环糊精(dien-β-CD)对野黄芩素的增溶作用,得到野黄芩素在环糊精及其衍生物中的相溶解度曲线均为AL型,说明其与环糊精的包合比为1:1。结果表明3种环糊精主体化合物对野黄芩素的增溶作用大小为:en-β-CD>dien-β-CD>HP-β-CD。     

β-环糊精包合物的1H NMR研究

用¹H NMR研究外消旋和光学纯的色氨酸(Try) 分子与β-环糊精(β-CD)形成的包埋复合物,通过主-客体分子的化学位移的变化说明这种主-客体包埋系统的手性识别过程.     

正交实验法研究MAH-β-CD衍生物的制备工艺

用顺丁烯二酸酐（MAH）对β-环糊精（β-CD）进行化学改性,合成出了顺丁烯二酸酐-β-环糊精衍生物（MAH-β-CD）。针对影响衍生物制备的因素,采用正交实验法,以产物产率为评价指标,优选顺丁烯二酸酐-β-环糊精衍生物制备的最佳工艺条件为：投料比1∶10,反应温度80℃,反应时间9h。     

近红外光谱法快速测定新疆薰衣草精油主要组分

为建立快速测定新疆薰衣草精油中芳樟醇(linalool)、乙酸芳樟酯(linalyl acetate)含量的定量分析模型,采用近红外吸收光谱法(NIR)测定了165个精油样品,通过对近红外光谱吸收峰分析,在7 100～4 500 cm-1波数范围内化学信息量比较丰富且噪音低,可选择此波数段为分析区间。剔除8个异常样本后,通过聚类方法划分为105个校正集样本和52个验证集样本,结合气相色谱质谱(GC-MS)法测定的薰衣草精油linalool和linalyl acetate的含量,建立原始数据矩阵。对比不同的预处理方法对原始近红外光谱的过滤作用,其中正交信号变换(OSC)方法效果明显,对两种化合物的预测均方根误差(RMSEP) 分别为0.226和0.558,再用向前间隔偏最小二乘法(FiPLS)剔除与待测成分无关或呈非线性关系的波长点,最终得到8个间隔区间共160个波长点的数据子集。使用OSC-FiPLS优化处理的数据子集结合偏最小二乘法(PLS)建立新疆薰衣草精油中linalool和linalyl acetate的快速定量分析模型,在模型中二成分的隐变量数都为8。交互验证均方根误差(RMSECV)分别为0.170和0.416;预测均方根误差(RMSEP)分别为0.188和0.364。结果表明,经OSC和FiPLS预处理建立的PLS-NIR定量分析模型稳健性好,测定精度高,能快速测定薰衣草精油中linalool和linalyl acetate含量,并且具有良好的预测能力。可为新疆薰衣草精油主要成分的快速定量分析提供一种新的有效方法。     

阿维菌素包合物的红外光谱研究

依据β-环糊精的分子空腔容纳性质,利用饱和水溶液法制备出阿维菌素-β-环糊精包合物,利用高效液相色谱法测定其包封率。 结合红外光谱谱图说明了阿维菌素-β-环糊精包合物的形成;分析了阿维菌素光解所产生的化学结构变化;研究了所形成的包合物增强阿维菌素化学结构光稳定性的效应。 结果表明：阿维菌素-β-环糊精包合物的包封率为40.5%;从红外光谱谱图分析,说明阿维菌素-β-环糊精包合物形成了分子间氢键,组合效应与其物理混合物有区别。 阿维菌素B1a分子大环内酯结构可以被光分解破坏,分解后大环内酯结构中的C—O—C结构红外伸缩振动峰消失,内酯键发生明显断裂。 形成阿维菌素-β-环糊精包合物后,β-环糊精起包合作用的分子位点覆盖了阿维菌素B1a分子大环内酯结构,为阿维菌素B1a分子大环内酯结构中的C—O—C结构提供良好的避光保护作用,提高了阿维菌素B1a分子的光稳定性。 本实验的创新之处在于对所制备的阿维菌素-β-环糊精包合物的结构和特性从红外光谱角度进行了分析,此类包合物可望作为理想的阿维菌素保护型控释制剂中间体。     

反相薄层色谱法添加环糊精流动相分离D、L-组氨酸

研究了用β-环糊精(β-CD)作为流动相手性添加剂,在反相C18板上分离D、L-组氨酸对映体的薄层色谱法。该法不需将组氨酸进行衍生,展开剂最佳组成配比为β-CD饱和溶液∶甲酸∶甲醇=10∶4∶2.5(V/V/V),最佳分离温度为50℃。     

Controlled drug release applications of the inclusion complex of peracetylated-β-cyclodextrin and water-soluble drugs formed in supercritical carbon dioxide

Supercritical carbon dioxide (scCO₂) processing was performed with mixtures of CO₂-soluble peracetylated-β-cyclodextrin (PAc-β-CD) heptakis(2,3,6-tri-O-acetyl)-β-cyclodextrin, and highly water-soluble drug molsidomine (MOL) to prepare inclusion complexes of MOL and PAc-β-CD. The MOL/PAc-β-CD inclusion complex was confirmed by differential scanning calorimetry, X-ray diffractometry, and ¹H NMR analyses. The complexes were further investigated for their potential use in controlled drug delivery applications. The in-vitro release of MOL from the peanut oil suspensions into aqueous phase was found to be significantly retarded by the complexation with PAc-β-CD, mainly due to the hydrophobic properties associated with the PAc-β-CD.     

黄芩苷包合物的拉曼光谱和红外光谱研究

通过FT-IR(傅里叶变换红外光谱)和Raman(共焦激光拉曼光谱)分析黄芩苷包合物,对拉曼光谱法作为一种新的验证包合物形成方法的可行性进行验证.采用饱和水溶液法制备黄芩苷包合物,共焦拉曼光谱仪和傅里叶转换红外光谱仪分别测定并获得p-环糊精、黄芩苷、黄芩苷与β-环糊精物理混合物及黄芩苷包合物四种固体粉末的拉曼图谱和红外...     

对乙酰氨基酚包合物拉曼光谱和红外光谱研究

通过拉曼光谱和红外光谱法分析对乙酰氨基酚包合物,探讨拉曼光谱作为一种新的验证包合物形成方法的可行性.采用饱和水溶液法制备对乙酰氨基酚包合物,共焦拉曼光谱仪和傅里叶转换红外光谱仪分别测定并获得β-CD、对乙酰氨基酚、摩尔比1:1的β-CD与对乙酰氨基酚物理混合物及其包合物四种物质粉末的拉曼图谱和红外图谱并将其进行对照分析...     

Main Components of Xinjiang Lavender Essential Oil Determined by Partial Least Squares and Near Infrared SpectroscopySCIEI北大核心CSCD

This work was undertaken to establish a quantitative analysis model which can rapid determinate the content of linalool, linalyl acetate of Xinjiang lavender essential oil. Totally 165 lavender essential oil samples were measured by using near infrared absorption spectrum(NIR), after analyzing the near infrared spectral absorption peaks of all samples, lavender essential oil have abundant chemical information and the interference of random noise may be relatively low on the spectral intervals of 7100-4 500 cm(-1). Thus, the PLS models was constructed by using this interval for further analysis. 8 abnormal samples were eliminated. Through the clustering method, 157 lavender essential oil samples were divided into 105 calibration set samples and 52 validation set samples. Gas chromatography mass spectrometry (GC-MS) was used as a tool to determine the content of linalool and linalyl acetate in lavender essential oil. Then the matrix was established with the GC-MS raw data of two compounds in combination with the original NIR data. In order to optimize the model, different pretreatment methods were used to preprocess the raw NIR spectral to contrast the spectral filtering effect, after analysizing the quantitative model results of linalool and linalyl acetate, the root mean square error prediction(RMSEP) of orthogonal signal transformation (OSC) was 0.226, 0.558, spectrally, it was the optimum pretreatment method. In addition, forward interval partial least squares (FiPLS) method was used to exclude the wavelength points which has nothing to do with determination composition or present nonlinear correlation, finally 8 spectral intervals totally 160 wavelength points were obtained as the dataset. Combining the data sets which have optimized by OSC-FiPLS with partial least squares(PLS) to establish a rapid quantitative analysis model for determining the content of linalool and linalyl acetate in Xinjiang lavender essential oil, numbers of hidden variables of two components were 8 in the model. The performance of the model was evaluated according to root mean square error of cross-validation (RMSECV) 9 root mean square error of prediction (RMSEP). In the model, RESECV of linalool and linalyl acetate were 0.170 and 0.416, respectively; RMSEP were 0.188 and 0.364. The results indicated that raw data was pretreated by OSC and FiPLS, the NIR-PLS quantitative analysis model with good robustness, high measurement precision; it could quickly determine the content of linalool and linalyl acetate in lavender essential oil. In addition, the model has a favorable prediction ability. The study also provide a new effective method which could rapid quantitative analysis the major components of Xinjiang lavender essential oil.     

Preparation and Characterization of Polyacrylonitrile and Polyacrylonitrile/β-cyclodextrins Microspheres

Polyacrylonitrile (PAN) and PAN/β-cyclodextrin (β-CD) microspheres were prepared via an electrospinning method. The PAN microspheres could be successfully obtained in a suitable range of concentrations of electrospun PAN solutions. When β-CD was added to the PAN solutions, electrospun PAN/β-CD composite spheres were prepared. The morphology of the spheres was characterized by scanning electron microscopy (SEM); it showed that the spheres had uniform diameter and a smooth surface. The composition of the composite microspheres was studied by Fourier transform infrared spectroscopy (FTIR). The results showed that the β-CD was incorporated in the polymer microspheres.