Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A partial least squares and principal component regression study of quinone compounds with trypanocidal activity

A quantitative structure-activity relationship (QSAR) study of 19 quinone compounds with trypanocidal activity was performed by Partial Least Squares (PLS) and Principal Component Regression (PCR) methods with the use of leave-one-out crossvalidation procedure to build the regression models. The trypanocidal activity of the compounds is related to their first cathodic potential (Ep(c1)). The regression PLS and PCR models built in this study were also used to predict the Ep(c1) of six new quinone compounds. The PLS model was built with three principal components that described 96.50% of the total variance and present Q(2) = 0.83 and R-2 = 0.90. The results obtained with the PCR model were similar to those obtained with the PLS model. The PCR model was also built with three principal components that described 96.67% of the total variance with Q(2) = 0.83 and R-2 = 0.90. The most important descriptors for our PLS and PCR models were HOMO-1 (energy of the molecular orbital below HOMO), Q4 (atomic charge at position 4), MAXDN (maximal electrotopological negative difference), and HYF (hydrophilicity index).

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chemical evolution in the Asteraceae. The Oxidation-Reduction mechanism and production of secondary metabolites

This work describes the application of partial least squares (PLS) regression to variables that represent the oxidation data of several types of secondary metabolite isolated from the family Asteraceae. The oxidation states were calculated for each carbon atom of the involved compounds after these had been matched with their biogenetic precursor. The states of oxidation variations were named oxidation steps. This methodology represents a new approach to inspect the oxidative changes in taxa. Partial least square (PLS) regression was used to inspect the relationships among terpenoids, cournarins, polyacetylenes, and flavonoids from a data base containing approximately 27,000 botanical entries. The results show an interdependence between the average oxidation states of each class of secondary metabolite at tribe and sub tribe levels.

Shell occupation by the South Atlantic endemic hermit crab Loxopagurus loxochelis (Moreira, 1901) (Anomura: Diogenidae)

The evaluation of population characteristics, particularly those of endemic species, aids in population preservation and management. Hermit crabs present an innate behavior of occupying shells, which tends to individual needs and limits their distribution. This study characterized the pattern of occupation of gastropod shells by the hermit Loxopagurus loxochelis in three bays of the southwestern coast of Brazil. Monthly collections were made from January/1998 to December/1999 in the bays Ubatumirim (UBM), Ubatuba (UBA) and Mar Virado (MV) with a shrimping boat. Overall, ten species of gastropod shells were occupied by L. loxochelis. The shell of Olivancillaria urceus represented 66.8% of those occupied. Morphometric relationships demonstrated a differential occupation of the more abundant shells among demographic groups, where most of the males occupied O. urceus, non-ovigerous females occupied O. urceus and Buccinanops cochlidium, and ovigerous females occupied B. cochlidium and Stramonita haemastoma. Most of the individuals occupied the more abundant shells, considered adequate for the morphology of this hermit crab species. Thus, the studied bays seem to be stable and propitious environments for population perpetuation and the settlement of new individuals.

A partial least squares regression study with antioxidant flavonoid compounds

The quantitative structure-activity relationship of a set of 19 flavonoid compounds presenting antioxidant activity was studied by means of PLS (Partial Least Squares) regression. The optimization of the structures and calculation of electronic properties were done by using the semiempirical method AMI. A reliable model (r(2) = 0.806 and q(2) = 0.730) was obtained and from this model it was possible to consider some aspects of the structure of the flavonoid compounds studied that are related with their free radical scavenging ability. The quality of the PLS model obtained in this work indicates that it can be used in order to design new flavonoid compounds that present ability to scavenge free radicals.

DETERMINATION of SILICON IN LUBRICANT OIL BY HIGH-RESOLUTION CONTINUUM SOURCE FLAME ATOMIC ABSORPTION SPECTROMETRY USING LEAST-SQUARE BACKGROUND CORRECTION and INTERNAL STANDARDIZATION

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivariate calibrations in gas chromatographic profiles for prediction of several physicochemical parameters of Brazilian commercial gasoline

Several Brazilian commercial gasoline physicochemical parameters, such as relative density, distillation curve (temperatures related to 10%, 50% and 90% of distilled volume, final boiling point and residue), octane numbers (motor and research octane number and anti-knock index), hydrocarbon compositions (olefins, aromatics and saturates) and anhydrous ethanol and benzene content was predicted from chromatographic profiles obtained by flame ionization detection (GC-FID) and using partial least square regression (PLS). GC-FID is a technique intensively used for fuel quality control due to its convenience, speed, accuracy and simplicity and its profiles are much easier to interpret and understand than results produced by other techniques. Another advantage is that it permits association with multivariate methods of analysis, such as PLS. The chromatogram profiles were recorded and used to deploy PLS models for each property. The standard error of prediction (SEP) has been the main parameter considered to select the "best model". Most of GC-FID-PLS results, when compared to those obtained by the Brazilian Government Petroleum, Natural Gas and Biofuels Agency - ANP Regulation 309 specification methods, were very good. In general, all PLS models developed in these work provide unbiased predictions with lows standard error of prediction and percentage average relative error (below 11.5 and 5.0, respectively). (C) 2007 Elsevier B.V. All rights reserved.

Modelo de avaliação de maturidade em gerenciamento de projetos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Metabolite profiles of essential oils in citrus peels and their taxonomic implications

China is an important center of origin for the genus Citrus L. of the family Rutaceae and is rich in wild Citrus species. The taxonomy of Citrus has been a subject of controversy for more than a half century. We propose that the metabolite profiles of Chinese native Citrus species can be used for classification and understanding of the taxonomic relationships within the Citrus germplasm. In this study, triplicate gas chromatography-mass spectrometry (GC-MS) metabolite profiles of 20 Citrus species/varieties were acquired, including 10 native varieties originating in China. R-(+)-limonene, alpha-pinene, sabinene and alpha-terpinene were found to be major characteristic components of the essential oils analyzed in this study, and these compounds contributed greatly to the metabolic classification. The three basic species of the subgenus Eucitrus (Swingle's system), i.e., C. reticulata Blanco, C. medica L. and C. grandis Osb., were clearly differentiated based upon their metabolite profiles using hierarchical cluster analysis (HCA) and partial least square-discriminant analysis (PLS-DA). All the presumed hybrid genotypes, including sweet orange (C. sinensis Osb.), sour orange (C. aurantium L.), lemon (C. limon Burm.f.), rough lemon (C. jambhiri Lush.), rangpur lime (C. limonia Osb.) and grapefruit (C. paradisi Macf.), were grouped closely together with one of their suggested parent species in the HCA-dendrogram and the PLS-DA score plot. These results clearly demonstrated that the metabolite profiles of Citrus species could be utilized for the taxonomic classification of the genus and are complementary to the existing taxonomic evidence, especially for the identification and differentiation of hybrid species.

Multivariate quality control studies applied to Ca(II) and Mg(II) determination by a portable method

A portable or field test method for simultaneous spectrophotometric determination of calcium and magnesium in water using multivariate partial least squares (PLS) calibration methods is proposed. The method is based on the reaction between the analytes and methylthymol blue at pH 11. The spectral information was used as the X-block, and the Ca(II) and Mg(II) concentrations obtained by a reference technique (ICP-AES) were used as the Y-block. Two series of analyses were performed, with a month's difference between them. The first series was used as the calibration set and the second one as the validation set. Multivariate statistical process control (MSPC) techniques, based on statistics from principal component models, were used to study the features and evolution with time of the spectral signals. Signal standardization was used to correct the deviations between series. Method validation was performed by comparing the predictions of the PLS model with the reference Ca(II) and Mg(II) concentrations determined by ICP-AES using the joint interval test for the slope and intercept of the regression line with errors in both axes. (C) 1998 John Wiley & Sons, Ltd.

Escherichia coli phylogenetic group determination and its application in the identification of the major animal source of fecal contamination

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analyzing the effect of homogeneous frustration in protein folding

The energy landscape theory has been an invaluable theoretical framework in the understanding of biological processes such as protein folding, oligomerization, and functional transitions. According to the theory, the energy landscape of protein folding is funneled toward the native state, a conformational state that is consistent with the principle of minimal frustration. It has been accepted that real proteins are selected through natural evolution, satisfying the minimum frustration criterion. However, there is evidence that a low degree of frustration accelerates folding. We examined the interplay between topological and energetic protein frustration. We employed a Cα structure-based model for simulations with a controlled nonspecific energetic frustration added to the potential energy function. Thermodynamics and kinetics of a group of 19 proteins are completely characterized as a function of increasing level of energetic frustration. We observed two well-separated groups of proteins: one group where a little frustration enhances folding rates to an optimal value and another where any energetic frustration slows down folding. Protein energetic frustration regimes and their mechanisms are explained by the role of non-native contact interactions in different folding scenarios. These findings strongly correlate with the protein free-energy folding barrier and the absolute contact order parameters. These computational results are corroborated by principal component analysis and partial least square techniques. One simple theoretical model is proposed as a useful tool for experimentalists to predict the limits of improvements in real proteins. © 2013 Wiley Periodicals, Inc.