Chemotaxonomic relationships in Celastraceae inferred from principal component analysis (PCA) and partial least squares (PLS)

This paper describes a chemotaxonomic analysis of a database of triterpenoid compounds from the Celastraceae family using principal component analysis (PCA). The numbers of occurrences of thirty types of triterpene skeleton in different tribes of the family were used as variables. The study shows that PCA applied to chemical data can contribute to an intrafamilial classification of Celastraceae, once some questionable taxa affinity was observed, from chemotaxonomic inferences about genera and they are in agreement with the phylogeny previously proposed. The inclusion of Hippocrateaceae within Celastraceae is supported by the triterpene chemistry.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

A chemometric study of the 5-HT1A receptor affinities presented by arylpiperazine compounds

Arylpiperazine compounds are promising 5-HT1A receptor ligands that can contribute for accelerating the onset of therapeutic effect of selective serotonin reuptake inhibitors. In the present work, the chemometric methods HCA, PCA, KNN, SIMCA and PLS were employed in order to obtain SAR and QSAR models relating the structures of arylpiperazine compounds to their 5-HT1A receptor affinities. A training set of 52 compounds was used to construct the models and the best ones were obtained with nine topological descriptors. The classification and regression models were externally validated by means of predictions for a test set of 14 compounds and have presented good quality, as verified by the correctness of classifications, in the case of pattern recognition studies, and b, the high correlation coefficients (q(2) = 0.76, r(2) = 0.83) and small prediction errors for the PLS regression. Since the results are in good agreement with previous SAR studies, we can suggest that these findings can help in the search for 5-HT1A receptor ligands that are able to improve antidepressant treatment. (c) 2007 Elsevier Masson SAS. All rights reserved.

NEAR INFRARED SPECTROSCOPY FOR ESTIMATING SUGARCANE BAGASSE CONTENT IN MEDIUM DENSITY FIBERBOARD

Medium density fiberboard (MDF) is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC) bagasse to Eucalyptus wood in MDF panels using near infrared (NIR) spectroscopy. Principal component analysis (PCA) and partial least square (PLS) regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96) between the NIR-predicted and Lab-determined values and a low standard error of prediction (similar to 1.5%) in the cross-validations. A key role of resins (adhesives), cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.

Chemometric Studies on Natural Products as Potential Inhibitors of the NADH Oxidase from Trypanosoma cruzi Using the VolSurf Approach

Natural products have widespread biological activities, including inhibition of mitochondrial enzyme systems. Some of these activities, for example cytotoxicity, may be the result of alteration of cellular bioenergetics. Based on previous computer-aided drug design (CADD) studies and considering reported data on structure-activity relationships (SAR), an assumption regarding the mechanism of action of natural products against parasitic infections involves the NADH-oxidase inhibition. In this study, chemometric tools, such as: Principal Component Analysis (PCA), Consensus PCA (CPCA), and partial least squares regression (PLS), were applied to a set of forty natural compounds, acting as NADH-oxidase inhibitors. The calculations were performed using the VolSurf+ program. The formalisms employed generated good exploratory and predictive results. The independent variables or descriptors having a hydrophobic profile were strongly correlated to the biological data.

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

3D face computational photography using PCA spaces

In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

Chemical profile of rums as a function of their origin. The use of chemometric techniques for their identification

To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.

A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

Tissue inflammatory response to implantation of calcium hydroxide and iodoform in the back of rats

PURPOSE: This study evaluated the inflammatory reaction caused by the implantation of iodoform and calcium hydroxide in the back of rats. These drugs may be used as intracanal dressings to eliminate residual bacteria of the root canal system. METHODS: Twenty albinic rats (Rattus norvegicus, var Wistar) were divided into four groups: control group 1 (CG1) had normal skin; control group 2 (CG2) had wounded tissue without drugs; in groups 3 and 4, iodoform (IG) and calcium hydroxide (CHG) were inserted into the wounds, respectively. After 3, 5 and 11 days, slices of the implanted areas were macroscopically and microscopically observed regarding to their qualitative and quantitative aspects. RESULTS: In the macroscopical analysis, the CHG showed a large area of necrosis and swelling, which progressively decreased; in the IG the presence of iodoform surrounded by normal tissue was observed. The qualitative and quantitative histological analysis showed that IG promoted a shorter delay in the inflammatory response than the CHG. CONCLUSION: The inflammatory reaction for iodoform had a peak period five days after the drug insertion. By comparison, calcium hydroxide showed a very large area of necrosis that could only be partially eliminated after eleven days.

Analysis of contamination of endodontic absorbent paper points

PURPOSE: The aim of this study was to assess the contamination status of endodontic absorbent paper points from sterilized or not sterilized commercial packs, as well as paper points exposed to the dental office environment. METHODS: Twenty absorbent paper points were evaluated for contamination status packed under different conditions: commercial/sterilized pack, commercial/non-sterilized pack, exposed to the clinical environment, and intentionally contaminated (positive control). Contamination was determined qualitatively and quantitatively by aerobiosis, capnophilic growth, and pour plate. The Petri dishes were analyzed with a colony counter, and the results were expressed as colony-forming units. The data were analyzed by Kruskal-Wallis test (α=0.05). RESULTS: No difference in colony-forming units was found among the groups of endodontic absorbent paper points. All groups were contaminated by fungi and bacteria. CONCLUSION: It can be concluded that the sterilization of absorbent endodontic paper points before clinical use should be recommended regardless of commercial presentation

Doença periodontal em portadoras de valvopatia durante a gravidez: estudo clínico e microbiológico

FUNDAMENTO: A doença periodontal representa risco à gestante portadora de valvopatia reumática, seja para contrair endocardite infecciosa, seja por propiciar complicações obstétricas. OBJETIVO: Estudar a frequência da doença periodontal em portadoras de valvopatia reumática durante a gravidez. MÉTODOS: Foram estudadas 140 gestantes, comparáveis quanto a idade e o nível socioeconômico, divididas em: 70 portadoras de doença valvar reumática e 70 mulheres saudáveis. Todas se submeteram a: 1) avaliação clínica odontológica que incluiu a análise dos seguintes parâmetros: 1.1) profundidade à sondagem, 1.2) distância da linha esmalte-cemento à margem gengival, 1.3) nível clínico de inserção, 1.4) índice de sangramento, 1.5) índice de placa bacteriana, e, 1.6) comprometimento de furca; e, 2) exame microbiológico nas amostras de saliva e do cone que considerou o controle positivo para as cepas das bactérias Porphyromonas gingivalis, Tannerella forsithia e Aggregobacter actinomycetemcomitans. RESULTADOS: A lesão valvar mitral foi prevalente (65 casos = 92,8%) dentre as gestantes cardiopatas. A comparação entre os grupos mostrou não haver diferenças entre idade e a paridade, e embora tenham sido verificadas diferenças entre as medidas da distância da linha esmalte-cemento à margem gengival (p = 0,01) e o índice de placa (p=0,04), a frequência da doença periodontal identificada em 20 (14,3%) gestantes, não foi diferente entre os grupos (p = 0,147). O exame microbiológico mostrou uma proporção maior da bactéria P. gingivalis na saliva de gestantes saudáveis (p = 0,004). CONCLUSÃO: O estudo clínico e microbiológico periodontal durante a gravidez demonstrou igual frequência da doença periodontal em portadoras de valvopatia reumática quando comparada às mulheres saudáveis.

Composition, functional properties and sensory characteristics of Mozzarella cheese manufactured from different somatic cell counts in milk

In the present study, composition, functional properties and sensory characteristics of Mozzarella cheese produced from milk with somatic cell counts (SCC) at low (<200,000 cells/mL), intermediate (≈400,000 cells/mL) and high (>800,000 cells/mL) levels were investigated. Three batches of cheese were produced for each SCC category. The cheeses were vacuum packed in plastic bags and analysed after 2, 9, 16, 23 and 30 days of storage at 4ºC. SCC level did not affect the moisture, fat, total protein and ash content, mesophilic and psychrotrophic bacteria, and sensory parameters of Mozzarella cheese. However, meltability increased in cheese manufactured from high SCC milk. Results indicated that raw milk used to produce Mozzarella cheese should not contain high SCC (>800,000 cells/mL) in order to avoid changes in the functional properties of the Mozzarella cheese.

Quality of sausage elaborated using minced Nile Tilapia submmitted to cold storage

Filleting yield of Nile tilapia Oreochromis niloticus (L.) is low (30%) and generates large amount of wastes that may turn into environmental and economic problem. However, these wastes can be used for the extraction of minced fish (MF) which can be used in the preparation of sausages. The objective of this study was to assess the quality of sausages prepared with 0, 20, 40, 60, 80 and 100% of MF from Nile tilapia filleting waste during storage at 0±0.3ºC. Alterations in the instrumental color (L*, a* and b*), lipid oxidation (TBARS), total volatile nitrogenous bases (TVB-N), pH, microbiological condition (pathogenic bacteria and aerobic psychrotrophic bacteria), and sensory attributes (color, odor, flavor, texture and overall acceptability) were evaluated for up to 40 days. The addition of MF to sausages increased TBARS values and decreases TVB-N, L*, a* and b* values. Acceptability of color attribute decreased with increasing MF; best flavor, texture and overall acceptability scores were registered for sausages containing 40 and 60% MF; best odor was registered for 100% MF. Pathogenic microorganisms were not detected, but decrease in pH and proliferation of aerobic psychrotrophic bacteria which, however, did not compromise sensory evaluation of sausages were registered throughout storage. Sausages prepared with MF from tilapia filleting waste have a shelf-life of 40 days when stored at 0±0.3ºC, and the maximum recommended MF inclusion to maintain good sensory quality is 60%.