Improvement of prediction ability of PLS models employing the wavelet packet transform: A case study concerning FT-IR determination of gasoline parameters

The wavelet packet transform (WPT) is a variant of the standard wavelet transform that offers greater flexibility in the decomposition of instrumental signals. Although encouraging results have been published concerning the use of WPT for signal compression and denoising, its application in multivariate calibration problems has received comparatively little attention, with very few contributions reported in the literature. This paper presents an investigation concerning the use of WPT as a feature extraction tool to improve the prediction ability of PLS models. The optimization of the wavelet packet tree is accomplished by using the classic dynamic programming algorithm and an entropy cost function modified to take into account the variance explained by the WPT coefficients. The selection of WPT coefficients for inclusion in the PLS model is carried out on the basis of correlation with the dependent variable, in order to exploit the joint statistics of the instrumental response and the parameter of interest. This WPT-PLS strategy is applied in a case study involving FT-IR spectrometric determination of four gasoline parameters, namely specific mass (SM) and the distillation temperatures at which 10%, 50%, 90% of the sample has evaporated. The dataset comprises 103 gasoline samples collected from gas stations and 6144 wavelengths in the range 2500-15000 nm. By applying WPT to the FT-IR spectra, considerable compression with respect to the original wavelength domain is achieved. The effect of varying the wavelet and the threshold level on the prediction ability of the resulting models is investigated. The results show that WPT-PLS outperforms standard PLS in most wavelet-threshold combinations for all determined parameters.     

Excited-state dynamics of carotenoids in light-harvesting complexes. 2. Dissecting pulse structures from optimal control experiments

Dispersed multipump-probe (PPP) spectroscopy was used to explore the role of saturation, annihilation, and structured pulses in recent coherent control experiments on the light-harvesting 2 complex from Rhodopseudomonas acidophila (Herek et al. Nature 2002, 417, 533). We discuss the complimentary aspects between the PPP technique and coherent control studies, in particular the ability to dissect complicated pulse structures and the utility in exploring incoherent mechanisms. With the aid of a simple multistate model involving only population dynamics, we illustrate how the optimized structured pulses may be explained in terms of an interplay between excited-state populations, saturation, and annihilation. Furthermore, we discuss the experimental conditions that are required for incoherent effects to contribute to control experimental signals, with particular emphasis on pulse intensities, and show that the optimization of a ratio of conservative signals (i.e., not modulated by external dynamics) is required to exclude saturation effects from coherent control studies.     

Reference values of urinary 3,5,6-trichloro-2-pyridinol in the Italian population--validation of analytical method and preliminary results (multicentric study)

The interlaboratory validation of analytical procedures for the assay of urinary 3,5,6-trichloro-2-pyridinol (TCP) in the general Italian population is reported. The determinations were performed by high-resolution gas chromatography (HRGS) with electron capture detection and HRGS with mass spectrometry (MS) in 2 laboratories. The urine samples were from 42 participants from 3 regions of Italy. The results were evaluated by interlaboratory quality control. Urinary TCP concentrations were above the detection limit (1.2 micrograms/L) in 88% of the population, with a mean detectable concentration [GM (GSD)] of 2.8 (1.9) micrograms/g creatinine (creat). (GM, geometric mean; GSD, geometric standard deviation.) The Mann-Whitney U test showed that wine consumption was a statistically significant variable (p < 0.05) for urinary concentrations of TCP. Analysis of variance of the logarithm of urinary TCP versus wine consumption and diet showed a statistically significant fit. The model used explained 30% of the total variance: wine consumption and diet accounted for 37 and 17% respectively of the explained variance.     

Cation distribution in LiMgVO4 and LiZnVO4: structural and spectroscopic study

The room temperature cation occupancy in LiMgVO(4) and LiZnVO(4) crystallographic sites is obtained by means of the combined use of X-ray powder diffraction (XRPD), (7)Li and (51)V magic angle spinning nuclear magnetic resonance (MAS NMR), and micro-Raman measurements. In the LiMgVO(4) Cmcm orthorhombic structure, the 4c (C(2)(v) symmetry) tetrahedral vanadium site is fully ordered; on the contrary, the Li 4c tetrahedral site and the 4b (C(2)(h) symmetry) Mg octahedral site display about 22% of reciprocal cationic exchange. Higher cationic disorder is observed in LiZnVO(4): the three cations can distribute on the three tetrahedral and distinct sites of the R-3 structure. XRPD and MAS NMR analysis results highly agree for what concerns vanadium ion distribution on the three cationic sites (about 25, 26, and 47%). From the full profile fitting of XRPD patterns with the Rietveld method, it is also obtained that Li(+) displays a slightly preferred occupation of the T1 position (approximately 55%) and Zn(2+) of the T2 position (approximately 46%). The vibrational spectra of the two compounds are characterized by different peak positions and broadening of the Raman modes, reflecting the cation distribution and the local vibrational unit distortion. A comparison is also made with recent Raman results on Li(3)VO(4). High temperature XRPD measurements rule out possible structural transitions up to 673 K for both compounds.     

A simple method for the determination of enantiomeric excess and identity of chiral carboxylic acids

The association between an achiral copper(II) host (1) and chiral carboxylate guests was studied using exciton-coupled circular dichroism (ECCD). Enantiomeric complexes were created upon binding of the enantiomers of the carboxylate guests to the host, and the sign of the resultant CD signal allowed for determination of the configuration of the studied guest. The difference in magnitudes and shapes of the CD signals, in conjunction with linear discriminant analysis (LDA), allowed for the identity of the guest to be determined successfully. A model was created for the host-guest complexes which successfully predicts the sign of the observed CD signal. Further, Taft parameters were used in the model, leading to rationalization of the observed magnitudes of the CD signals. Finally, the enantiomeric excess (ee) of unknown samples of three chiral carboxylic acid guests was determined with an average absolute error of ±3.0%.     

An in silico expert system for the identification of eye irritants

This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient chemicals for eye irritancy potential, which is based upon exclusion rules of five physicochemical properties – molecular weight (MW), hydrophobicity (log P), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA) and polarizability (Pol). These rules were developed using the ADMET Predictor software and a dataset of 917 eye irritant chemicals. The dataset was divided into 826 (90%) chemicals used for training set and 91 (10%) chemicals used for external validation set (every 10th chemical sorted by molecular weight). The sensitivity of these rules for the training and validation sets was 72.3% and 71.4%, respectively. These rules were also validated for their specificity using an external validation set of 2011 non-irritant chemicals to the eye. The specificity for this validation set was revealed as 77.3%. This method facilitates rapid screening and prioritization of data poor chemicals that are unlikely to be tested for eye irritancy in the Draize test.     

Extraction of climatic signals from fossil organic compounds in marine sediments up to 11.7 Ma old (IODP-U1318)

This study focuses on the extraction of climate signals and processes using a combined approach which includes the analysis of a high number of lipid molecules in marine sediments, and the chemometric analysis of the acquired data. Neutral and acidic fractions of marine sediments from site IODP-U1318 (south-west of the UK, Porcupine Seabight) were quantified by GC–MS. The alkenone unsaturation index, U^k′₃₇, was estimated from the composition of C₃₇ alkenones and it was then used for the estimation of sea surface temperatures (SST) for reference. Principal component analysis (PCA), explained 77.45% of the total data variance, and differentiated neutral fraction GC–MS total ion current (TIC) profiles according to SST values of the different sediment sections. GC–MS TIC chromatograms were correlated to sea surface temperatures (SST) by partial least squares regression (PLSR). The compounds more robustly in line with SST values at each sediment section explained 93% of the SST variance and they were identified using the variable importance in projection (VIP) scores method. The proposed approach enables an objective identification of organic compounds sensitive to SST variability throughout complete chromatographic profiles. As a result of this multivariate unbiased approach, lipid composition of sediments was differentiated between compounds of marine (long chain n-alkanes, long chain n-alkan-1-ols) and terrestrial (short chain n-alkan1-ols, alkenols, cholesterol, squalene) origin, whose concentrations were directly and inversely correlated to SST, respectively.     

Combining standard addition method and second-order advantage for direct determination of salicylate in undiluted human plasma by spectrofluorimetry

Second-order advantage turns possible a determination in the presence of unknown interferences. This work presented an application of the second-order advantage provided by parallel factor analysis (PARAFAC). The aim was the direct determination of salicylic acid (SA), the main product of aspirin degradation, in undiluted human plasma by spectrofluorimetry. The strategy of this analysis combined the use of PARAFAC, for extraction of the pure analyte signal, with the standard addition method, for a determination in the presence of a strong matrix effect caused by the quenching effect of the proteins present in the plasma. For each sample, four standard additions were performed, in triplicates. A specific PARAFAC model was built for each triplicate of each sample, from three-way arrays formed by 436 emission wavelengths, 7 excitation wavelengths and 5 measurements (sample plus 4 additions). In all the cases, the models were built with three factors and explained more than 99.90% of the total variance. The obtained loadings were related to SA and two background interferences. The scores related to SA were used for a linear regression in the standard addition method. Good results were obtained for determinations in the SA concentration range from 3.0 to 24.0 μg ml⁻¹, providing errors of prediction between 0.7 and 6.3%.     

Models of polychlorinated dibenzodioxins, dibenzofurans, and biphenyls binding affinity to the aryl hydrocarbon receptor developed using (13)c NMR data

Quantitative spectroscopic data-activity relationship (QSDAR) models for polychlorinated dibenzofurans (PCDFs), dibenzodioxins (PCDDs), and biphenyls (PCBs) binding to the aryl hydrocarbon receptor (AhR) have been developed based on simulated (13)C nuclear magnetic resonance (NMR) data. All the models were based on multiple linear regression of comparative spectral analysis (CoSA) between compounds. A 1.0 ppm resolution CoSA model for 26 PCDF compounds based on chemical shifts in five bins had an explained variance (r(2)) of 0.93 and a leave-one-out (LOO) cross-validated variance (q(2)) of 0.90. A 2.0 ppm resolution CoSA model for 14 PCDD compounds based on chemical shifts in five bins had an r(2) of 0.91 and a q(2) of 0.81. The 1.0 ppm resolution CoSA model for 12 PCB compounds based on chemical shifts in five bins had an r(2) of 0.87 and a q(2) of 0.45. The models with more compounds had a better q(2) because there are more multiple chemical shift populated bins available on which to base the linear regression. A 1.0 ppm resolution CoSA model for all 52 compounds that was based on chemical shifts in 12 bins had an r(2) of 0.85 and q(2) of 0.71. A canonical variance analysis of the 1.0 ppm CoSA model for all 52 compounds when they were separated into 27 strong binding and 25 weak binding compounds was 98% correct. Conventional quantitative structure-activity relationship (QSAR) modeling suffer from errors introduced by the assumptions and approximations involved in calculated electrostatic potentials and the molecular alignment process. QSDAR modeling is not limited by such errors since electrostatic potential calculations and molecular alignment are not done. The QSDAR models provide a rapid, simple and valid way to model the PCDF, PCDD, and PCB binding activity in relation to the aryl hydrocarbon receptor (AhR).     

Characterization of a Stable Adaptive Calibration Model Using Near-Infrared Spectroscopy and Partial Least Squares with a Kalman Filter

The calibration model of near-infrared (NIR) spectra established using the Kalman filter-partial least square (partial least squares combined with a Kalman filter) method can be adapted to outdated equipment, environmental changes, external samples, and other applications. However, the variance of the measurement noise estimation for NIR spectrum measurements cannot be easily obtained using Kalman filter-partial least squares; therefore, the variance in the measurement noise is often assumed to be zero for the Kalman filter-partial least square calibration model, which affects the stability of the model. In this study, the measured input and output data were used effectively, and the gamma test method for estimating the measurement noise variance was used to improve the stability of the Kalman filter-partial least square calibration model. First, an accurate estimation of the measurement noise variance was obtained, and accurate modeling was then performed using Kalman filter-partial least squares. Finally, 600 abandoned drilling fluid samples were used to confirm the validity of the proposed method. The Kalman filter-partial least square and gamma test-Kalman filter-partial least square methods are compared. Testing of external samples 401–600 demonstrated that the stability of the Kalman filter-partial least square model decreased. The root mean square error of the prediction of the Kalman filter-partial least square model was 27.135, which was worse than that of the gamma test-Kalman filter-partial least square model (20.307). The validation results show that the proposed method has better stability in tracking the evolution of the NIR spectrometer’s measurement state.     

Thermal, spectroscopic, and dissolution studies of the simvastatin–acetylsalicylic acid mixtures

The objective of the present investigation was to study the effect of eutectic formation on in vitro dissolution of simvastatin (SIM) released from mixtures with acetylsalicylic acid (ASA) prepared by a grinding method. SIM–ASA mixtures were characterized by means of differential scanning calorimetry (DSC), infrared spectroscopy (IR), X-ray powder diffractometry (XRPD), and in vitro dissolution tests. IR spectroscopy and XRPD studies indicated no interaction between SIM and ASA in the solid state. The DSC investigation has revealed that SIM and ASA form a simple eutectic system containing 66.6 % w/w of SIM at the eutectic point. In vitro dissolution studies of SIM and its mixtures with ASA were carried out. The eutectic mixture shows an appreciable increase in the dissolution rate in comparison with other ratios and SIM in 0.5 % w/v sodium lauryl sulfate. The dissolution enhancement of SIM was related to the effective wetting of the drug particles with a significantly reduced size released from eutectic composition. In conclusion, dissolution of SIM can be enhanced through eutectic formation with ASA by means of simple mechanical activation (a grinding method).     

Structural evidence of differential forms of nanosponges of beta-cyclodextrin and its effect on solubilization of a model drug

Nanosponges (NS) are a recently developed class of hyper-branched polymers, nano-structured to form three dimensional meshwork; obtained by reacting cyclodextrins with a cross linker like diphenyl carbonate. Herein, we report an anomalous behavior of NS with regards to physical and morphological characteristics and drug encapsulation behavior by minor synthetic modification. Two distinct forms viz. crystalline and para-crystalline of NS were identified and extensively characterized by use of high resolution transmission electron microscopy (HR-TEM), X-ray powder diffraction (XRPD), scanning electron microscope, atomic force microscope, optical microscope and Fourier transform infra-red attenuated total reflectance spectroscopy (FTIR-ATR). Dimension of the crystal lattice was found to be equal to 0.61 nm. Higher magnifications clearly showed a zone axis with a hexagonal symmetry as that of beta-cyclodextrin. XRPD patterns were in concurrence with the HR-TEM results. Solubility studies with a model drug dexamethasone (DEX) showed more than three folds increase in the solubility of the drug in the crystalline NS as compared to the para-crystalline ones. Percent drug association and drug loading for DEX was found to be higher in the crystalline type of NS. An In vitro drug kinetic study evidenced a faster release of DEX from the crystalline type NS. The particle sizes of the formulations were as follows: crystalline NS: 688.6 ± 38.0 nm, para-crystalline NS: 702.2 ± 21.2 nm with polydispersity indices of 0.155 and 0.132; zeta-potential of ?26.55 ± 1.7 and ?23.42 ± 2.1 respectively. Differential scanning calorimetry and thermogravimetric analysis revealed that both forms encapsulated the drug satisfactorily. FTIR-ATR and Raman spectroscopy showed weak interactions. Crystallinity of NS was thus found to be an important factor in solubilization, in vitro kinetics and encapsulation behavior and can be tuned to give a tailored drug release profile or formulation characteristics.