Metabolic profiling using principal component analysis, discriminant partial least squares, and genetic algorithms

The aim of this study was to evaluate evolutionary variable selection methods in improving the classification of ¹H nuclear magnetic resonance (NMR) metabonomic profiles, and to identify the metabolites that are responsible for the classification. Human plasma, urine, and saliva from a group of 150 healthy male and female subjects were subjected to ¹H NMR-based metabonomic analysis. The ¹H NMR spectra were analyzed using two pattern recognition methods, principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), to identify metabolites responsible for gender differences. The use of genetic algorithms (GA) for variable selection methods was found to enhance the classification performance of the PLS-DA models. The loading plots obtained by PCA and PLS-DA were compared and various metabolites were identified that are responsible for the observed separations. These results demonstrated that our approach is capable of identifying the metabolites that are important for the discrimination of classes of individuals of similar physiological conditions.     

Simultaneous spectrophotometric determination of ethinylestradiol and levonorgestrel by partial least squares and principal component regression multivariate calibration

Two spectrophotometric methods for the determination of Ethinylestradiol (ETE) and Levonorgestrel (LEV) by using the multivariate calibration technique of partial least square (PLS) and principal component regression (PCR) are presented. In this study the PLS and PCR are successfully applied to quantify both hormones using the information contained in the absorption spectra of appropriate solutions. In order to do this, a calibration set of standard samples composed of different mixtures of both compounds has been designed. The results found by application of the PLS and PCR methods to the simultaneous determination of mixtures, containing 4–11 μg ml⁻¹ of ETE and 2–23 μg ml⁻¹ of LEV, are reported. Five different oral contraceptives were analyzed and the results were very similar to that obtained by a reference liquid Chromatographic method.     

Multivariate analysis of remote laser-induced breakdown spectroscopy spectra using partial least squares,principal component analysis,and related techniques

Quantitative analysis with laser-induced breakdown spectroscopy traditionally employs calibration curves that are complicated by chemical matrix effects. These chemical matrix effects influence the laser-induced breakdown spectroscopy plasma and the ratio of elemental composition to elemental emission line intensity. Consequently, laser-induced breakdown spectroscopy calibration typically requires a priori knowledge of the unknown, in order for a series of calibration standards similar to the unknown to be employed. In this paper, three new Multivariate Analysis techniques are employed to analyze the laser-induced breakdown spectroscopy spectra of 18 disparate igneous and highly-metamorphosed rock samples. Partial Least Squares analysis is used to generate a calibration model from which unknown samples can be analyzed. Principal Components Analysis and Soft Independent Modeling of Class Analogy are employed to generate a model and predict the rock type of the samples. These Multivariate Analysis techniques appear to exploit the matrix effects associated with the chemistries of these 18 samples.     

Near-infrared spectroscopy quantitative determination of Pefloxacin mesylate concentration in pharmaceuticals by using partial least squares and principal component regression multivariate calibration

Pefloxacin mesylate, a broad-spectrum antibacterial fluoroquinolone, has been widely used in clinical practice. Therefore, it is very important to detect the concentration of Pefloxacin mesylate. In this research, the near-infrared spectroscopy (NIRS) has been applied to quantitatively analyze on 108 injection samples, which was divided into a calibration set containing 89 samples and a prediction set containing 19 samples randomly. In order to get a satisfying result, partial least square (PLS) regression and principal components regression (PCR) have been utilized to establish quantitative models. Also, the process of establishing the models, parameters of the models, and prediction results were discussed in detail. In the PLS regression, the values of the coefficient of determination (R²) and root mean square error of cross-validation (RMSECV) of PLS regression are 0.9263 and 0.00119, respectively. For comparison, though applying PCR method to get the values of R² and RMSECV we obtained are 0.9685 and 0.00108, respectively. And the values of the standard error of prediction set (SEP) of PLS and PCR models are 0.001480 and 0.001140. The result of the prediction set suggests that these two quantitative analysis models have excellent generalization ability and prediction precision. However, for this PFLX injection samples, the PCR quantitative analysis model achieved more accurate results than the PLS model. The experimental results showed that NIRS together with PCR method provide rapid and accurate quantitative analysis of PFLX injection samples. Moreover, this study supplied technical support for the further analysis of other injection samples in pharmaceuticals.     

Simultaneous spectrophotometric determination of tartrazine, patent blue V, and indigo carmine in commercial products by partial least squares and principal component regression methods

Two multivariate calibration methods, partial least squares (PLS-1) and principal component regression (PCR) were proposed and successfully applied to the simultaneous determination of three dyes, tartrazine (T) (E-102), patent blue V (P) (E-131), and indigo carmine (I) (E-132) in mixtures by ultraviolet-visible absorption spectrophotometry. Calibration models were evaluated by internal validation (prediction of dyes concentration in its own designed training set of calibration), by cross-validation (obtaining statistical parameters that show the efficiency for a calibration fit model), and by external validation over 19 synthetic mixtures of the three dyes in different ratios containing 2.4-17.6 mg l(-1) of T, 1.6-5.6 mg l(-1) of P, and 3.2-17.5 mg/l(-1) of I, with recoveries between 93.5 and 103.1% and over three commercial products, in which the proposed calibration models were satisfactorily applied without separation step. Repeatability and reproducibility studies (with the Students's and F tests) were achieved over two series of nine standards for each dye, showing no significant differences at 95% confidence level.     

Simultaneous spectrophotometric determination of Tartrazine, Sunset Yellow and Ponceau 4R in commercial products by partial least squares and principal component regression multivariate calibration methods

Three multivariate calibration methods, partial least squares (PLS-1 and PLS-2) and principal component regression (PCR), were proposed and successfully applied to the simultaneous determination of three dyes, Tartrazine (E-102), Sunset Yellow (E-110) and Ponceau 4R (E-124) in mixtures by ultraviolet-visible absorption spectrophotometry. The designed and optimized training set of calibration was applied to the determination of the three dyes in several synthetic mixtures, containing 1.6–20.0 mg/L of Tartrazine, 3.2–40.0 mg/L of Sunset Yellow and 3.2– 36.0 mg/L of Ponceau 4R. 94.5–105.3% recovery values were obtained. Three commercial foods that contained the three dyes were also satisfactorily analyzed without separation step. The results obtained by the application of the three chemometric approaches in the commercial products are discussed and compared with those obtained by an HPLC method and very similar values were found by all methods. Repeatability and reproducibility studies (with the Student’s and F tests) were achieved over two series of nine standards for each dye, showing no significant differences at the 95% confidence level. Received: 27 October 1997 / Revised: 9 January 1998 / Accepted: 24 January 1998     

Simultaneous spectrophotometric determination of Tartrazine, Sunset Yellow and Ponceau 4R in commercial products by partial least squares and principal component regression multivariate calibration methods

Three multivariate calibration methods, partial least squares (PLS-1 and PLS-2) and principal component regression (PCR), were proposed and successfully applied to the simultaneous determination of three dyes, Tartrazine (E-102), Sunset Yellow (E-110) and Ponceau 4R (E-124) in mixtures by ultraviolet-visible absorption spectrophotometry. The designed and optimized training set of calibration was applied to the determination of the three dyes in several synthetic mixtures, containing 1.6–20.0 mg/L of Tartrazine, 3.2–40.0 mg/L of Sunset Yellow and 3.2– 36.0 mg/L of Ponceau 4R. 94.5–105.3% recovery values were obtained. Three commercial foods that contained the three dyes were also satisfactorily analyzed without separation step. The results obtained by the application of the three chemometric approaches in the commercial products are discussed and compared with those obtained by an HPLC method and very similar values were found by all methods. Repeatability and reproducibility studies (with the Student’s and F tests) were achieved over two series of nine standards for each dye, showing no significant differences at the 95% confidence level.     

Maintenance of a calibration model for near infrared spectrometry by a combined principal component analysis-partial least squares approach

A novel strategy for building and maintaining calibration models has been developed for use when the future boundaries of the sample set are unknown or likely to change. Such a strategy could have an impact on the economics and time required to obtain and maintain a calibration model for routine analysis. The strategy is based on both principal component analysis (PCA) and partial least squares (PLS) multivariate techniques. The principal action of the strategy is to define how “similar” a new sample is to the samples currently defining the calibration dataset. This step is performed by residuals analysis, following PCA. If the new sample is considered to have a spectrum “similar” to previously available spectra, then the model is assumed able to predict the analyte concentration. Conversely, if the new sample is considered “dissimilar”, then there is new information in this sample, which is unknown to the calibration model and the new sample is added automatically to the calibration set in order to improve the model. The strategy has been applied to a real industrial dataset provided by BP Amoco Chemicals. The data consists of spectra of 102 sequential samples of a raw material. The strategy produced an accurate calibration model for both target components starting with only the first four samples, and required a further 17 reference measurements to maintain the model for the whole sampling sequence, which was over a 1-year period.     

beta-Correction as a preprocessing method for partial least squares in simultaneous determination of zinc and lead

An error analysis of predicted values using spectral correction matrix and partial least squares (PLS) modeling is applied for the determination of Zn²⁺ and Pb²⁺ with methylthymol blue (MTB) as a metallochromic indicator. The concentration ranges for Pb²⁺ and Zn²⁺ in standard solution sets are 0.5-5.2 and 0.1-2.5 μg ml⁻¹, respectively. The experimental calibration set was composed of 20 sample solutions using a random design for two component mixtures. The absorption spectra were recorded from 400 to 700 nm. The two wavelengths, which exert the minimum error in prediction of two metal ion concentrations, are chosen according to an error analysis of different pairs of wavelengths. The effect of the pH on the sensitivity in determination of Zn²⁺ and Pb²⁺ using MTB was studied in order to choose the optimum pH (pH=6) for determination. The values of root mean square difference (RMSD) for lead and zinc using β-correction partial least squares were 0.0977 and 0.1266, respectively. The effect of diverse ions and several experimental parameters were studied. The method was used for the determination of lead and zinc in alloy samples.     

Simultaneous determination of copper, nickel, cobalt and zinc using zincon as a metallochromic indicator with partial least squares

The partial least squares (PLS) applied to the simultaneous determination of the divalent ions of copper, nickel, cobalt and zinc based on the formation of their complexes with 2-carboxy-2′-hydroxy-5′-sulfoformazyl benzene (zincon). The absorption spectra were recorded from 515 through 750 nm. The effect of pH on sensitivity and the selectivity was studied in the range 3.0-10.0 and the pH 8.0 was choused according to net analyte signal (NAS) as a function of pH. The concentration range for Cu²⁺, Ni²⁺, Co²⁺and Zn²⁺ in solution calibration sets were 0-2.6, 0-4.6, 0-3.0 and 0-4.92 ppm, respectively. The root mean squares differences (RMSD) for copper, nickel, cobalt and zinc were 0.0181, 0.0488, 0.0309 and 0.0463, respectively.     

Simultaneous determination of domperidone and cinnarizine in a binary mixture using derivative spectrophotometry,partial least squares and principle component regression calibration

This work is concerned with the simultaneous determination of domperidone maleate (DOM) and cinnarizine (CINN) in a binary mixture form, without previous separation, by two different techniques. The first method is the application of derivative spectrophotometry where the linearity range and percentage recoveries for DOM and CINN were 2.5-30 micro g mL(-1), 5-25 micro g mL(-1) and 100.06+/-1.157, 99.93+/-1.377, respectively. The second method depends on the application of partial least squares (PLS) and principle component regression (PCR) models. A training set consisting of 10 mixtures containing 5-20 micro g mL(-1) for each component was used for the construction of the PCR and PLS models. These models were used after their validation for the prediction of the concentration of DOM and CINN in their mixtures. The proposed procedures were successfully applied for the simultaneous determination of both drugs in laboratory prepared mixtures and in commercial tablet preparations. The validity of the proposed methods was assessed by applying the standard addition technique where the percentage recovery of the added standard was found to be 99.98+/-0.297 and 99.84+/-0.700 for DOM and CINN, respectively, using the derivative spectrophotometric method and 100.29+/-0.398 and 100.11+/-0.363 for DOM and CINN, respectively, using the PLS and PCR methods.The proposed procedures are rapid, simple, require no preliminary separation steps and can be used for routine analysis of both drugs in quality control laboratories.     

Simultaneous determination of tin, germanium and molybdenum by diode array detection-flow injection analysis with partial least squares calibration model

Simultaneous determination of tin, germanium and molybdenum in food samples has been established by flow injection-charge coupled detector (CCD) diode array detection spectrophotometry with partial least squares (PLS) algorithm. The method was based on the chromogenic reaction of metal ions and salicylflurone in the presence of cetyltrimethyl ammonium bromide. The overlapping spectra of these complexes are collected by CCD diode array detector and the multi-wavelength absorbance data are processed using partial least squares algorithm. The reaction conditions and analytical parameters of flow injection analysis have been investigated. The method was applied to directly determine Ge, Mo and Sn in several food samples after digestion with satisfactory results. The recoveries of spiked samples were 80.0-102.0% for tin, 86.3-92.0% for germanium and 83.2-95.2% for molybdenum, and the relative standard deviations for samples were 4.4-7.8%. Molybdenum in certified reference material of cattle liver was determined by the proposed method (n=8). The differential values between determined and guarantee values were within the given uncertain value ranges (t=1.687, P>0.05 for t-test). The samples of mung bean, kelp and pork liver were analyzed by the proposed method and inductively couple plasma-atomic emission spectroscopy (ICP-AES) method. The determination results of the two methods are in good agreement. The sampling rate is 30 samples h⁻¹.     

Spectrophotometric simultaneous determination of cobalt, copper and nickel using nitroso-R-salt in alloys by partial least squares

Partial least squares modeling as a powerful multivariate statistical tool applied to spectrophotometric simultaneous determination of cobalt, copper, and nickel in aqueous solutions. The concentration range for cobalt, copper and nickel were 0.4-2.6, 0.6-3.4, 0.5-5.5 ppm, respectively. The experimental calibration set was composed with 36 sample solutions using a mixture design for three component mixtures. The absorption spectra were recorded from 470 to 600 nm. The effect of pH on the sensitivity and selectivity was studied according to net analyte signal (NAS). The values of root mean square difference (RMSD) for cobalt, copper and nickel using partial least squares (PLS) were 0.0192, 0.0263 and 0.0446 ppm, respectively. The effects of various cations and anions were investigated. The method was used to determination of cobalt, copper and nickel in two sample alloys based on copper, nickel and cobalt (known as cunico) and based on cobalt, nickel and iron (known as conife).     

Gas-chromatographic fatty-acid fingerprints and partial least squares modeling as a basis for the simultaneous determination of edible oil mixtures

Partial least squares modeling and gas-chromatographic fatty-acid fingerprints are reported as a method for the simultaneous determination of cottonseed, olive, soybean and sunflower edible oil mixtures. In this work, two sets of three- and four-component combinations of oils were prepared, hydrolyzed and the obtained free fatty acids analyzed by gas chromatography (GC) without any further derivatization. The normalized percentages of the myristic (14:0), palmitic (16:0), palmitoleic (16:1), stearic (18:0), oleic (18:1), linoleic (18:2) and linolenic (18:3) acids were chromatographically measured in samples and used for constructing calibration matrix. The cross-validation method was used to select the number of factors and the proposed methods were validated by using two sets of synthetic oil mixture samples. The relative standard error for each oil in mixture samples was less than 10%. This approach allows determining possible adulteration in each of the four edible oils.     

Resolution of ternary mixtures of salicylic, salicyluric and gentisic acids by partial least squares and principal component regression: Optimization of the scanning path in the excitation-emission matrices

The resolution of ternary mixtures of salicylic, salicyluric and gentisic acids has been accomplished by partial least squares (PLS) and principal component regression (PCR) multivariate calibration. The total luminescence information of the compounds has been used to optimize the spectral data set to perform the calibration. A comparison between the predictive ability of the three multivariate calibration methods, PLS-1, PLS-2 and PCR, on three spectral data sets, excitation, emission and synchronous spectra, has been performed. The excitation spectrum has been the best scanning path for salicylic and salicyluric acid determinations, while the emission spectrum has been the best for the gentisic acid determination. The convenience of analysing the total luminescence spectrum information when using multivariate calibration methods on fluorescence data is demonstrated.     

偏最小二乘分光光度法同时测定痕量铁、锰、铜、锌、钴和镍

痕量Fe^3 ,Mn^2 ,Cu^2 ,Zn^2 ,Co^2 ,Ni^2 与2－（5－溴－2－吡啶偶氮）－5－二乙氨基苯酚（5－Br-PADAP)和溴化十六烷基三甲基铵（CTMAB）在PH8．3时发生高灵敏显色反应，所形成的三元胶束络合的吸收光谱严重重叠，采用偏最小二乘法（PLS）辅助分光光度法测定了合成试样及饲料中上述6种痕量组分，结果表明，PLS法是化学计量学中一种可适用于基体较复杂的实际试样中痕量组分分光度同时测定的多元计算方法。     

主成分-偏最小二乘分光光度法同时测定饲料中的痕量铁、锰、铜、锌

痕量Fe^3＋、Mn^2＋、Cu^2＋、Zn^2＋与2-（5-溴-2-吡啶偶氮）．5-二乙氨基苯酚（5-Br-PADAP）和对．（1,1,3,3．四甲基丁基）苯基醚（Triton X-100）在pH8．3发生高灵敏显色反应,所形成的三元胶束络合物的吸收光谱严重重叠。本文采用主成分-偏最小二乘法（PC—PLS）辅助分光光度法成功地测定了合成试样及饲料中上述4种痕量组分。结果表明,PC—PLS法是化学计量学法中一种可适用于基体较复杂的实际试样中痕量组分同时分光光度测定的优良的多元计算方法。     

Solid-phase UV spectroscopic multisensor for the simultaneous determination of caffeine, dimenhydrinate and acetaminophen by using partial least squares multicalibration

A straightforward flow-through multisensor was developed for the fast simultaneous determination of caffeine (CF), dimenhydrinate (DMH) and acetaminophen (AAP) based on the integration of their retention and UV detection. A diode array spectrophotometer was used to monitor the inherent UV full-spectra in the range 245-310 nm of the analytes retained on C(18) bonded phase beads packed in a flow cell, without requiring additional reagents or derivatization processes. The extensively overlapped spectra of the analytes retained on the solid support could be resolved by partial least squares (PLS) regression. After collecting the response of the multisensor, its active microzone was regenerated by using methanol as the eluting agent, leaving it ready for the next determination. The proposed multisensor has been satisfactorily applied for the analysis of synthetic and real samples with different nominal contents of these active principles.     

Comparative study of net analyte signal-based methods and partial least squares for the simultaneous determination of amoxycillin and clavulanic acid by stopped-flow kinetic analysis

A comparative study about advantages and limitations of net analyte signal (NAS)-based methods (NBMs) and partial least squares (PLS) calibration in kinetic analysis has been performed. The different multivariate calibration methods were applied to the determination of binary mixtures of amoxycillin and clavulanic acid, by stopped-flow kinetic analysis. The reactions of oxidation of these compounds with cerium(IV), in sulphuric acid medium, were monitored by following the changes on the fluorescence of the oxidation products, in stopped-flow mode. The differences on the kinetic profiles obtained at λ_ex=256 nm and λ_em=351 nm, were used to determine mixtures of both compounds by multivariate calibration of the kinetic data, using PLS-1, a modification of hybrid linear analysis (HLA) and net analyte pre-processing combined with classical least squares (NAP/CLS) methods. The NBMs allowed the selection of optimal time data regions by calculating the minimum error indicator function (EIF), improving the results and making NBMs very convenient for the analysis. In addition, the use of the net analyte signal concept allows the calculation of the analytical figures of merit, limit of detection (LOD), sensitivity and selectivity, for each component.     

Simultaneous determination of potassium guaiacolsulfonate, guaifenesin, diphenhydramine HCl and carbetapentane citrate in syrups by using HPLC-DAD coupled with partial least squares multivariate calibration

A simple and rapid analytical procedure was proposed for the determination of chromatographic peaks by means of partial least squares multivariate calibration (PLS) of high-performance liquid chromatography with diode array detection (HPLC-DAD). The method is exemplified with analysis of quaternary mixtures of potassium guaiacolsulfonate (PG), guaifenesin (GU), diphenhydramine HCI (DP) and carbetapentane citrate (CP) in syrup preparations. In this method, the area does not need to be directly measured and predictions are more accurate. Though the chromatographic and spectral peaks of the analytes were heavily overlapped and interferents coeluted with the compounds studied, good recoveries of analytes could be obtained with HPLC-DAD coupled with PLS calibration. This method was tested by analyzing the synthetic mixture of PG, GU, DP and CP. As a comparison method, a classsical HPLC method was used. The proposed methods were applied to syrups samples containing four drugs and the obtained results were statistically compared with each other. Finally, the main advantage of HPLC-PLS method over the classical HPLC method tried to emphasized as the using of simple mobile phase, shorter analysis time and no use of internal standard and gradient elution.