转基因产品分析方法的研究进展

简要介绍了转基因产品的发展历程、优缺点以及对转基因产品进行检测分析的迫切性,着重综述了近期基于DNA、蛋白质、生物传感器以及联用技术检测转基因产品的分析方法,最后对转基因产品的分析方法进行了展望.     

NIRS分析技术在饲料品质检测中的应用

简介近红外光谱（Near Infrared Spectroscopy,NIRS)分析技术的优点，原理和应用，并重点对其在饲料品质检测中的应用进行综述（引用文献共51篇）。     

转基因作物pat蛋白的双抗体夹心酶联免疫检测方法研究

将克隆到的pat基因构建原核表达载体pET30(+)-pat并在大肠杆菌中进行表达,分离纯化得到高纯度pat蛋白。用所得到的pat蛋白制备了兔多克隆抗体和鼠单抗2F6。多抗效价>8000,单抗效价为5×104;单抗为IgG1类,轻链为κ型。基于抗pat蛋白单克隆抗体和兔多克隆抗体建立了双抗夹心酶联免疫分析方法(Sandwich ELISA)。检测范围为1.6~100μg/L,线性回归方程y=0.6914x-2.572,决定系数为0.9951。用所建立的方法测定了5个转基因抗虫棉和2个非转基因棉花品种叶片中pat蛋白的含量,其中转基因抗虫棉中的3个品种检测出pat蛋白,其余均未检出pat蛋白。     

温控近红外光谱用于葡萄糖的高灵敏检测

温控近红外光谱在混合体系定量分析以及分子间相互作用分析中已得到应用.本工作利用互因子分析方法(MFA)探索了温控近红外光谱技术测定血清样品中低浓度葡萄糖含量的可行性.测量了不同温度下葡萄糖含量分别为1.0～15.0 mmol/L和0.0～1.0 mmol/L的两组血清溶液的近红外光谱,并利用MFA进行了定量计算.结果表明,利用该方法可以实现样品中微量葡萄糖的准确定量,MFA提取的标准信号(SS)的相对强度和葡萄糖浓度之间的线性相关系数R分别为0.9923和0.9895,预测均方根误差(RMSEP)分别为0.35和0.07 mmol/L.     

利用近红外光谱技术在线检测中药质量

传统的分析技术一般采用离线分析的手段，通常需要对待分析样品进行相应的预处理，存在分析结果滞后的缺陷。近红外技术可以克服这一缺点，使实验室和工厂的产品分析实现在线化，可以在几秒钟内得到待测参数。与反馈控制技术联用后，实现生产过程的在线控制。近红外光谱能够连续测定多个参数，实现绿色分析。     

基于编码微粒的多元与高通量生物分子检测技术研究进展

由于基因组和蛋白质组学的快速发展,生物医学检测、药物发现以及环境监测领域对于大量生物分子的检测提出了多元与高通量的技术需求.而生物分子结合反应是生物分子检测的一个重要基础,微粒技术在编码与识别生物分子结合反应以实现多元生物分子检测方面具有独到的优势,并且可以与高通量样品处理技术相整合,从而满足这一需求.本文主要介绍了多元与高通量生物分子检测技术的发展过程以及最新的微粒编码技术研究进展,同时对该技术的发展方向与面临的问题进行阐述.     

细胞功能分子的表面增强拉曼成像及其应用研究进展

表面增强拉曼光谱(surface-enhanced Raman spectroscopy, SERS)具有高灵敏、高通量的特性.基于SERS的拉曼成像技术是一种无损的生物成像技术,已被广泛应用于细胞表面与细胞内生物分子的检测和成像,如对聚糖、microRNA、蛋白质等分子的定量、结构分析与功能追踪等.这一技术也已用于细菌的快速检测、细胞或细菌间的信号通讯研究、细胞p H检测,并可通过活体肿瘤组织的边缘描绘指导手术切除. SERS成像可以规避生命体系中强的分子自荧光以及荧光成像中的光漂白现象,并可以利用不同拉曼信标的指纹光谱实现高灵敏、高通量的生物成像.通过与其他成像技术(如核磁共振成像、光声成像)的结合, SERS成像有望用于更复杂生命体系中生物分子的研究.本文综述了近年来细胞功能分子的表面增强拉曼成像及其应用方面的研究进展.     

基于自动磁珠转运的转基因蛋白Cry1Ab检测

基于自动磁珠转运,建立了转基因蛋白Cry1Ab免疫检测的新方法.利用水热法制备了粒径约400 nm的纳米磁球,并进行电镜表征,通过溶胶法对磁球表面进行氨基修饰,采用戊二醛偶联对磁珠实现抗体包被,在核酸提取仪中进行酶联免疫反应,采用分光光度法进行检测.本方法对转基因蛋白Cry1Ab的检出限低于1 μg/L,与商品化酶联免...     

迭代法在相思树近红外光谱分析中的应用

以相思树样本的克拉森木素含量为研究对象,利用多波长下的近红外光谱数据建立了若干个预测木素含量的子数学模型.使用加权平均值公式给出了木素含量的首次近似值.根据木素含量实验值与近似值之间所具有的较强线性关系,给出了建立近红外光谱数据预测模型的迭代法.模型的预测精度随迭代次数的增加而提高.本迭代法有望用于其它树木某些化学成分...     

基于过程分析技术和设计空间的金银花醇沉加醇过程终点检测

建立了一种新的基于过程分析技术(PAT)和质量源于设计(QbD)设计空间的中药制药过程终点分析与控制方法.以近红外(NIR)光谱技术为PAT工具, 采集正常操作条件下制药过程的多批次NIR光谱; 采用主成分分析结合移动块相对标准偏差(PCA-MBRSD)法, 确定每一批次过程的理想终点样本(DEPs), 由多批DEPs的光谱信息构成过程终点设计空间; 在过程终点设计空间确定的范围内, 建立多变量统计过程控制(MSPC)模型, 利用多变量Hotelling T²和SPE控制图对过程终点进行判断.应用上述方法, 进行了金银花醇沉加醇过程终点检测研究, 结果表明该方法灵敏、准确, 适宜于中药制药过程终点检测.     

近红外光谱法分析土壤中的有机质和氮素

应用近红外光谱技术测定土壤中的全氮、有机质、碱解氮，分别测定了2mm、0.15mm粒度的风干土在4000cm^-1～12000cm^-1波数范围的近红外光谱，用偏最小二乘法建立数学模型来进行含量预测，结果表明近红外光谱与土壤有机质、全氮、碱解氮具有良好的相关性，2mm风干土碱解氮建模的决定系数R^2为92.39，相对标准偏差为7.5%；2mm风干土全氮建模的决定系数R^2为88，相对标准偏差为8.2%;0.15mm的全氮建模的决定系数R2为89.86，相对标准偏差为7.2%;0.15mm风干土有机质建模的决定系数R^2为96.41，相对标准偏差为8.3%。因此，用近红外光普法测定土壤有机质、全氮、碱解氮的含量是可行的。     

New stable, isolable triarylmethyl based dyes absorbing in the near infrared

A series of new intensely coloured multicharged methylium compounds containing the 4-[2-ferrocenylethenyl]phenyl group and with significant electronic absorption in the near infrared have been prepared via acidification of the tertiary carbinols obtained by reaction of 4-[FcCHCH]C₆H₄Li with diethyl isophthalate, diethyl terephthalate, diethyl phthalate or the triethyl ester of 1,3,5-benzene carboxylic acid. Even more stable dyes were prepared from two new triarylmethanol derivatives containing 2,6-dimethoxy-4-[2-(ferrocenyl)ethenyl]phenyl or 2,6-dimethoxy-4-[2-[4-(dimethylamino)phenyl]ethenyl]phenyl groups which were prepared by reaction of 4-[FcCHCH]-2,6-MeO₂C₆H₂Li or 4-[4-Me₂NC₆H₄CHCH]-2,6-MeO₂C₆H₂Li (Fc = ferrocenyl) with diethyl carbonate. These carbinols on treatment with acid deposit dark-purple crystals which have been isolated and characterised spectroscopically. They absorb in the near infrared and, whereas their solutions begin to decolourise only after several days, they display long-term stability to air and moisture in the solid state.     

模型诊断用于近红外光谱建模校正集中奇异样本的识别

由于校正集样本的质量决定校正模型的质量,校正集中奇异样本的检测在多元校正建模中具有非常重要的意义.本研究建立了一种用于近红外光谱多元校正建模时校正集中奇异样本的检测方法.本方法基于奇异样本的定义和偏最小二乘方法的原理,通过考察每个校正集样本在模型的每个因子(或主成分)中对模型的贡献,将与多数样本表现不同的样本识别为奇异样本.采用218个橘汁样本构成的近红外光谱数据进行了分析,结果表明,校正集中存在6个奇异样本,扣除奇异样本后,校正集的交叉验证均方根误差由16.870减小为4.809,预测集的均方根误差从3.688减小为3.332.     

Feasibility study on the use of infrared spectroscopy for the direct authentication of Iberian pig fattening diet

The feasibility of using both middle- and near-infrared spectroscopy for discrimination between subcutaneous fat of Iberian pigs reared on different fattening diets has been evaluated. The sample set was formed by subcutaneous fat of pigs fattened outdoors (extensively) with natural resources (montanera) and pigs fattened on commercial feeds, either with standard feed or with especial formulations with higher content in oleic acid (HO-formulated feed). Linear discriminant analysis was used to classify the samples according to the fattening diet using the scores obtained from principal component analysis of near- and middle-infrared spectra as variables to construct the discriminant functions. The most influential variables were identified using a stepwise procedure. The discriminant potential of each spectral region was investigated. Best results were obtained with the combination of both regions with 91.7% of the standard feed and 100% of montanera and HO-formulated feed samples correctly classified. Chemical explanations are provided based on the correlation of these variables with fatty acid content in the samples.     

粮油作物及茶叶中农药多残留检测的前处理技术进展

综述了粮油作物和茶叶中农药多残留检测的前处理技术,包括超临界流体萃取、加速溶剂萃取、搅拌棒吸附萃取、分散固相萃取、固相微萃取和在线凝胶渗透色谱等样品前处理方式,并详细介绍了各种方法的原理、优点及适用范围,可为粮油作物和茶叶中农药多残留检测技术的发展提供参考。     

Study of the similarity between distribution maps of concentration in near-infrared spectroscopy chemical imaging obtained by different multivariate calibration approaches

Nowadays, near-infrared spectroscopy chemical imaging (NIR-CI) has been widely used in pharmaceutical analysis since it provides important surface information about the samples. In this work the information of NIR-CI at the pixel level was compared through calculation of the similarity between distribution maps of concentration obtained by different multivariate calibration approaches. The comparison was performed by using four different multivariate methods (MCR, MLR, CLS and PLS) in analysis of carbamazepine pharmaceutical formulations. For global determination, all models developed showed RMSEP below 1.9% (w/w) for active principal ingredient (API) and better than 4.6% (w/w) for excipients. Also, the distribution maps obtained by PLS, CLS and MCR showed great similarity for all compounds of the formulation as well with concentrations in the tablets. However, comparing the distribution maps obtained by MLR with those from the other chemometric tools, a lower similarity was observed. Thus, this fitted model does not ensure, by itself, that the images obtained are reliable or accurate. The paper also compares the distribution maps of concentrations obtained from all constituents present in the pharmaceutical formulation with their respective micrographs.     

应用近红外光谱分析技术快速分析饲料质量

以饲料质量分析为例,综述了近红外光谱分析技术及仪器的发展、回归校正技术及在快速分析饲料质量中的应用,引用文献２５篇     

Strategies for constructing the calibration set for a near infrared spectroscopic quantitation method

Three strategies for the construction of calibration sets have been tried, with the objective to develop and to validate a NIR quantitation method.The first two approaches consist of the use of two types of samples, named: samples of laboratory obtained by mixing the ingredients that compose the drug, and doped samples obtained by under- and over-dosed production samples. In order to improve the prediction results, production samples have been added to each calibration model. The ensuing models were validated with a view to determine their fitness for purpose. However, spectral differences between the laboratory samples and doped samples resulted in spurious predictions in quantifying samples of one type using the model developed from samples of the other.Such differences were studied in depth and a third procedure has been proposed, based on a calibration model constructed with an unique type of sample (laboratory sample) for later to correct it with a few doped samples. This corrected model has a good predictive ability on production samples.