Lysozyme as diffusion tracer for measuring aqueous solution viscosity

Measuring tracer diffusion provides a convenient approach for monitoring local changes in solution viscosity or for determining viscosity changes in response to multiple solution parameters including pH, temperature, salt concentrations or salt types. One common limitation of tracer diffusion in biologically relevant saline solutions is the loss of colloidal stability and aggregation of the tracer particles with increasing ionic strength. Using dynamic light scattering to measure tracer diffusion, we compared the performance of two different types of tracer particles, polystyrene nanobeads vs. the small protein lysozyme, for viscosity measurements of saline solutions. Polystyrene beads provide reliable values for water viscosity, but begin flocculating at ionic strengths exceeding about 100 mM. Using lysozyme, in contrast, we could map out viscosity changes of saline solutions for a variety of different salts, for salt concentrations up to 1 M, over a wide range of pH values, and over the temperature range most relevant for biological systems (5–40 °C). Due to its inherently high structural and colloidal stability, lysozyme provides a convenient and reliable tracer particle for all these measurements, and its use can be readily extended to other optical approaches towards localized measurements of tracer diffusion such as fluorescence correlation spectroscopy.     

近红外光谱快速测定红花逆流提取过程中羟基红花黄色素A的含量

采用近红外光谱(NIRS)透射法对红花罐组式逆流提取过程中羟基红花黄色素A(Hydroxysafflor yellow A,HSYA)的含量进行快速无损的测定.在红花逆流提取过程中,以高效液相色谱法(HPLC)为对照分析方法,测定提取液中羟基红花黄色素A的含量,运用偏最小二乘(PLS)法建立NIR光谱与羟基红花黄色素A的HPLC分析值之间多元校正模型,并对逆流提取过程的未知样本进行含量预测.校正模型相关系数达到0.982,预测相关系数达到0.965,RMSEC和RMSEP分别为0.053和0.075,RSEC和RSEP分别为3.96%和5.25%.结果表明,NIRS可以作为一种准确、快速、无损的检测方法用于检测中药逆流提取过程有效成分含量变化规律.     

基于串级质谱信息进行蛋白质数据库搜索的结果可靠性分析

SEQUEST与Mascot为目前蛋白组学分析研究中使用最为广泛的蛋白质库搜索工具.尝试将Mascot与SEQUEST搜索结果进行比较,进而采用不同多变量判别方法对二者的搜索结果进行判别分析,以降低其结果的假阳性率.通过对Mascot与SEQUEST搜索结果进行比较,发现所得结果差异很大;利用多变量判别分析方法对Mascot及SEQUEST搜索结果进行判别分析,可有效提高SEQUEST结果中假阳性结果与正确结果之间的区分能力.对于Mascot搜索结果,采用多变量判别分析方法仍无法显著降低其假阳性结果,利用Decoy库搜索结果进行估计时亦存在导致错误估计的风险.     

样条变换集成罚函数偏最小二乘方法用于光谱数据重构和定量分析

针对高维小样本光谱数据所显现的函数型数据(Functional data)特性、与性质参数的非线性关系及变量间存有的严重共线性,采用了样条变换集成罚函数偏最小二乘回归新技术.它首先以三次B基样条变换实现非线性光谱数据的线性化重构,随后将重构的新光谱矩阵交由罚函数偏最小二乘法(Penalized PLS)构建其与性质参变量间的校正模型,其中罚函数中的光滑因子由交叉验证优化确定以调控模型的拟合精度.最后,通过小麦样品水分含量的近红外光谱定量分析,结果显示该技术光谱数据重构稳健,去噪明显,并有效解决高维小样本的过拟合和变量间的共线性,而预测集的均方根误差(RMSEP)为0.1808%,方法的非线性校正模型预测能力得到了明显提高.     

Simultaneous kinetic spectrophotometric determination of cyanide and thiocyanate using the partial least squares (PLS) regression

The partial least squares (PLS-1) calibration model based on spectrophotometric measurement, for the simultaneous determination of CN⁻ and SCN⁻ ions is described. The method is based on the difference in the rate of the reaction between CN⁻ and SCN⁻ ions with chloramine-T in a pH 4.0 buffer solution and at 30 °C. The produced cyanogen chloride (CNCl) reacts with pyridine and the product condenses with barbituric acid and forms a final colored product. The absorption kinetic profiles of the solutions were monitored by measuring absorbance at 578 nm in the time range 20-180 s after initiation of the reaction with 2 s intervals. The experimental calibration matrix for partial least squares (PLS-1) calibration was designed with 31 samples. The cross-validation method was used for selecting the number of factors. The results showed that simultaneous determination could be performed in the range 10.0-900.0 and 50.0-1200.0 ng mL⁻¹ for CN⁻ and SCN⁻ ions, respectively. The proposed method was successfully applied to the simultaneous determination of cyanide and thiocyanate in water samples.     

Combining synchronous fluorescence spectroscopy with multivariate methods for the analysis of petrol-kerosene mixtures

Synchronous fluorescence spectroscopy (SFS) is a rapid, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. The present study demonstrates the use of SFS and multivariate methods for the analysis of petroleum products which is a complex mixture of multiple fluorophores. Two multivariate techniques principal component regression (PCR) and partial least square regression (PLSR) have been successfully applied for the classification of petrol-kerosene mixtures. Calibration models were constructed using 35 samples and their validation was carried out with varying composition of petrol and kerosene in the calibration range. The results showed that the method could be used for the estimation of kerosene in kerosene-mixed petrol. The model was found to be sensitive, detecting even 1% contamination of kerosene in petrol.     

Infrared spectroscopy and outer product analysis for quantification of fat, nitrogen, and moisture of cocoa powder

The combination of the near infrared (NIR) and Fourier-transform infrared (FTIR) absorbance spectra (1100-2500 nm and 4000-600 cm⁻¹) of 100 cocoa powder samples was used to build calibration models for the determination of the content of fat, nitrogen, and moisture. The samples that comprised the dataset had an average composition of 13.51% of fat, 3.77% nitrogen, and 3.98% moisture. The fat content ranged from 2.42 to 22.00%, the nitrogen from 0.88 to 4.48%, and moisture from 1.60 to 7.80%. For NIR, the relative root mean square error of cross-validation (RMSECV) was 7.0% (R² = 0.96) for fat, 1.7% (R² = 0.98) for nitrogen, and 5.2% (R² = 0.94) for moisture. For FTIR, the relative RMSECV was 10.4% (R² = 0.94) for fat and 3.9% (R² = 0.95) for nitrogen. However, for moisture, it was not possible to build a calibration model with suitable predictability. The combination of the NIR and FTIR domains (data fusion) by outer product analysis PLS1 allowed to predict these parameters and to characterise frequencies in one domain based on the information of the other domain. This work allows to conclude that the second derivative of NIR is the recommended procedure to quantify fat, nitrogen, and moisture content in cocoa powders by infrared spectroscopy.     

Calibration transfer strategy to compensate for instrumental drift in portable quadrupole mass spectrometers

We report the use of a calibration transfer strategy to correct for drift in the quantitative sensitivity of a portable quadrupole mass spectrometer (QMS) aimed at process monitoring applications. Gas mixtures of CH₄/Ar/C₂H₆/CO₂ were studied with calibration phase measurements made of the pure gases for a univariate analysis and of 40 multi-component mixtures for a multivariate approach. To evaluate calibrations, test set spectra of a CH₄/Ar/C₂H₆/CO₂ gas mixture were recorded bi-weekly over a period of 12 months. As part of the strategy a standard of pure argon was measured during both calibration and test phases so that correction factors could be calculated for each measurement day. It was shown that in the absence of a calibration transfer strategy quantifications of test set spectra could be inaccurate by more than an order of magnitude over 12 months. Furthermore, due to the effects of drift in the sensitivity over the 6 days required to record the training set in the calibration phase it was found that the multivariate analysis quantified test spectra less accurately than the univariate analysis. However, by applying the calibration transfer strategy across all measurements (both calibration and test phases) it was shown that the errors in prediction using the multivariate analysis previously seen after 2 weeks were not observed until approximately 12 months later.     

Poly[(N-isopropylacrylamide-co-acrylamide-co-(hydroxyethylmethacrylate))] thermoresponsive microspheres: An accurate method based on solute exclusion technique to determine the volume phase transition temperature

Poly[(N-isopropylacrylamide-co-acrylamide-co-(hydroxyethylmethacrylate))] [poly(NIPAAm-co-AAm-co-HEMA)] copolymer was synthesized as a new thermoresponsive material possessing a lower critical solution temperature (LCST) around 37 °C in phosphate buffer, pH 7.4, at a solution concentration of 1%, w/v. The influence of polymer concentration on LCST was determined by cloud point measurements and by microcalorimetric analysis. The copolymer was transformed in hydrogel microspheres by suspension reticulation of OH groups with glutaraldehyde. The volume phase transition temperature (VPTT) of microspheres was determined by a new approach, which involves measurement of the increase in concentration of a blue dextran (BD) solution at different temperatures in the presence of dry microspheres. The minimum BD concentration that gives reliable and reproducible results was determined to be 1 mg/ml. However, the higher is the concentration of BD in solution the smaller is the error. Contrary to solution of the linear polymer which displays a sharp phase transition temperature, the dependence of water regain of the hydrogel with temperature lasts from 4 °C to 50 °C.     

Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.