Assessing the association between phenolic compounds and the antioxidant activity of Brazilian red wines using chemometrics

The objective of this study was to evaluate the association among chemical parameters, the commercial value, and the antioxidant activity of Brazilian red wines using chemometric techniques. Twenty-nine samples from five different varieties were assessed. Samples were separated into three groups using hierarchical cluster analysis: cluster 1 presented the highest antioxidant activity towards DPPH (68.51% of inhibition) and ORAC (30,918.64 mu mol Trolox Equivalents/L), followed by cluster 3 (DPPH = 59.36% of inhibition: ORAC = 25,255.02 mu mol Trolox Equivalents/L) and then cluster 2 (DPPH = 46.67% of inhibition; ORAC = 19,395.74 gmol Trolox Equivalents/L). Although the correlation between the commercial value and the antioxidant activity on DPPH and ORAC was not statistically significant (P = 0.13 and P = 0.06, respectively), cluster 1 grouped the samples with higher commercial values. Cluster analysis applied to the variables suggested that non-anthocyanin flavonoids were the main phenolic class exerting antioxidant activity on Brazilian red wines. (C) 2010 Elsevier Ltd. All rights reserved.

Monitoring the authenticity of Brazilian UHT milk: A chemometric approach

In this work, chemometric methods are reported as potential tools for monitoring the authenticity of Brazilian ultra-high temperature (UHT) milk processed in industrial plants located in different regions of the country. A total of 100 samples were submitted to the qualitative analysis of adulterants such as starch, chlorine, formal. hydrogen peroxide and urine. Except for starch, all the samples reported, at least, the presence of one adulterant. The use of chemometric methodologies such as the Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) enabled the verification of the occurrence of certain adulterations in specific regions. The proposed multivariate approaches may allow the sanitary agency authorities to optimise materials, human and financial resources, as they associate the occurrence of adulterations to the geographical location of the industrial plants. (c) 2010 Elsevier Ltd. All rights reserved.

Visualizing inhibition of fatty acid synthase through mass spectrometric analysis of mitochondria from melanoma cells

Fatty acid synthase (FASN) is the metabolic enzyme responsible for the endogenous synthesis of the saturated long-chain fatty acid palmitate. In contrast to most normal cells, FASN is overexpressed in a variety of human cancers including cutaneous melanoma, in which its levels of expression are associated with a poor prognosis and depth of invasion. Recently, we have demonstrated the mitochondrial involvement in FASN inhibition-induced apoptosis in melanoma cells. Herein we compare, via electrospray ionization mass spectrometry (ESI-MS), free fatty acids (FFA) composition of mitochondria isolated from control (EtOH-treated cells) and Orlistat-treated B16-F10 mouse melanoma cells. Principal component analysis (PCA) was applied to the ESI-MS data and found to separate the two groups of samples. Mitochondria from control cells showed predominance of six ions, that is, those of m/z 157 (Pelargonic, 9:0), 255 (Palmitic, 16:0), 281 (Oleic, 18:1), 311 (Arachidic, 20:0), 327 (Docosahexaenoic, 22:6) and 339 (Behenic, 22:0). In contrast, FASN inhibition with Orlistat changes significantly mitochondrial FFA composition by reducing synthesis of palmitic acid, and its elongation and unsaturation products, such as arachidic and behenic acids, and oleic acid, respectively. ESI-MS of mitochondria isolated from Orlistat-treated cells presented therefore three major ions of m/z 157 (Pelargonic, 9:0), 193 (unknown) and 199 (Lauric, 12:0). These findings demonstrate therefore that FASN inhibition by Orlistat induces significant changes in the FFA composition of mitochondria. Copyright (C) 2011 John Wiley & Sons, Ltd.

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.

Distribution of major, minor, and trace metals in lake environments of Antarctica

The concentrations of major, minor and trace metals were measured in water samples collected from five shallow Antarctic lakes (Carezza, Edmonson Point (No 14 and 15a), Inexpressible Island and Tarn Flat) found in Terra Nova Bay (northern Victoria Land, Antarctica) during the Italian Expeditions of 1993-2001. The total concentrations of a large suite of elements (Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Gd, K, La, Li, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, Rb, Sc, Si, Sr, Ta, Ti, U, V, Y, W, Zn and Zr) were determined using spectroscopic techniques (ICP-AES, GF-AAS and ICP-MS). The results are similar to those obtained for the freshwater lakes of the Larsemann Hills, East Antarctica, and for the McMurdo Dry Valleys. Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed to identify groups of samples with similar characteristics and to find correlations between the variables. The variability observed within the water samples is closely connected to the sea spray input; hence, it is primarily a consequence of geographical and meteorological factors, such as distance from the ocean and time of year. The trace element levels, in particular those of heavy metals, are very low, suggesting an origin from natural sources rather than from anthropogenic contamination.

Using biplots to interpret gene expression patterns in plants

Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au.

Wet deposition of major ions in a rural area impacted by biomass burning emissions

This work concerns the influence of industrialized agriculture in the tropics on precipitation chemistry. A total of 264 rain events were sampled using a wet-only collector in central Sao Paulo State, Brazil, between January 2003 and July 2007. Electroneutrality balance calculations (considering H(+), K(+), Na(+), NH(4)(+), Ca(2)(+), Mg(2)(+), Cl(-), NO(3)(-), SO(4)(2-), F(-), PO(4)(3-), H(3)CCOO(-), HCOO(-), C(2)O(4)(2-) and HCO(3)(-)) showed that there was an excess of cations (similar to 15%), which was attributed to the presence of unmeasured organic anion species originating from biomass burning and biogenic emissions. On average, the three ions NH(4)(+), NO(3)(-) and H(+) were responsible for >55% of the total ion concentrations in the rainwater samples. Concentrations (except of H(+)) were significantly higher (t-test; P = 0.05), by between two to six-fold depending on species, during the winter sugar cane harvest period, due to the practice of pre-harvest burning of the crop. Principal component analysis showed that three components could explain 88% of the variance for measurements made throughout the year: PC1 (52%, biomass burning and soil dust resuspension); PC2 (26%, secondary aerosols); PC3 (10%, road transport emissions). Differences between harvest and non-harvest periods appeared to be mainly due to an increased relative importance of road transport/industrial emissions during the summer (non-harvest) period. The volume-weighted mean (VWM) concentrations of ammonium (23.4 mu mol L(-1)) and nitrate (17.5 mu mol L(-1)) in rainwater samples collected during the harvest period were similar to those found in rainwater from Sao Paulo city, which emphasizes the importance of including rural agro-industrial emissions in regional-scale atmospheric chemistry and transport models. Since there was evidence of a biomass burning source throughout the year, it appears that rainwater composition will continue to be affected by vegetation fires, even after sugar cane burning is phased out as envisaged by recent Sao Paulo State legislation. (C) 2011 Elsevier Ltd. All rights reserved.

Geographic call variation and further notes on habitat of Ameerega flavopicta (Anura, Dendrobatidae)

We describe habitat and inter-populational call variation of the dendrobatid frog Ameerega flavopicta. Data were collected in the Brazilian states ofminas Gerais and Goias. Principal component analysis separated the Goias population from others because of its higher call rates and shorter calls. The Paranaiba Rivermay represent themajor geographic barrier. We recognize the cephalic amplexus as themain type for the species. Although habitat disturbances increased since 1990, we did not notice differences in the density of callingmales at Serra do Cipo. Ameerega flavopicta appears to be quite resistant to alterations in its natural habitats caused by human activities.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Correlation of fungi and endotoxin with PM2.5 and meteorological parameters in atmosphere of Sao Paulo, Brazil

Particulate matter, especially PM2.5, is associated with increased morbidity and mortality from respiratory diseases. Studies that focus on the chemical composition of the material are frequent in the literature, but those that characterize the biological fraction are rare. The objectives of this study were to characterize samples collected in Sao Paulo, Brazil on the quantity of fungi and endotoxins associated with PM2.5, correlating with the mass of particulate matter, chemical composition and meteorological parameters. We did that by Principal Component Analysis (PCA) and multiple linear regressions. The results have shown that fungi and endotoxins represent significant portion of PM2.5, reaching average concentrations of 772.23 spores mu g(-1) of PM2.5 (SD: 400.37) and 5.52 EU mg(-1) of PM2.5 (SD: 4.51 EU mg(-1)), respectively. Hyaline basidiospores, Cladosporium and total spore counts were correlated to factor Ba/Ca/Fe/Zn/K/Si of PM2.5 (p < 0.05). Genera Pen/Asp were correlated to the total mass of PM2.5 (p < 0.05) and colorless ascospores were correlated to humidity (p < 0.05). Endotoxin was positively correlated with the atmospheric temperature (p < 0.05). This study has shown that bioaerosol is present in considerable amounts in PM2.5 in the atmosphere of Sao Paulo, Brazil. Some fungi were correlated with soil particle resuspension and mass of particulate matter. Therefore, the relative contribution of bioaerosol in PM2.5 should be considered in future studies aimed at evaluating the clinical impact of exposure to air pollution. (C) 2010 Elsevier Ltd. All rights reserved.

Structure activity relationship, acute toxicity and cytotoxicity of antimycobacterial neolignan analogues

Objectives The study`s aims were to evaluate the antimycobacterial activity of 13 synthetic neolignan analogues and to perform structure activity relationship analysis (SAR). The cytotoxicity of the compound 2-phenoxy-1-phenylethanone (LS-2, 1) in mammalian cells, such as the acute toxicity in mice, was also evaluated. Methods The extra and intracellular antimycobacterial activity was evaluated on Mycobacterium tuberculosis H37Rv. Cytotoxicity studies were performed using V79 cells, J774 macrophages and rat hepatocytes. Additionally, the in-vivo acute toxicity was tested in mice. The SAR analysis was performed by Principal Component Analysis (PCA). Key findings Among the 13 analogues tested, LS-2 (1) was the most effective, showing promising antimycobacterial activity and very low cytotoxicity in V79 cells and in J774 macrophages, while no toxicity was observed in rat hepatocytes. The selectivity index (SI) of LS-2 (1) was 91 and the calculated LD50 was 1870 mg/kg, highlighting the very low toxicity in mice. SAR analysis showed that the highest electrophilicity and the lowest molar volume are physical-chemical characteristics important for the antimycobacterial activity of the LS-2 (1). Conclusions LS-2 (1) showed promising antimycobacterial activity and very weak cytotoxicity in cell culture, as well as an absence of toxicity in primary culture of hepatocytes. In the acute toxicity study there was an indication of absence of toxicity on murine models, in vivo.

A comparison between three and five factor models of Pakistani personality data

The Eysenck Personality Questionnaire-Revised (EPQ-R), the Eysenck Personality Profiler Short Version (EPP-S), and the Big Five Inventory (BFI-V4a) were administered to 135 postgraduate students of business in Pakistan. Whilst Extraversion and Neuroticism scales from the three questionnaires were highly correlated, it was found that Agreeableness was most highly correlated with Psychoticism in the EPQ-R and Conscientiousness was most highly correlated with Psychoticism in the EPP-S. Principal component analyses with varimax rotation were carried out. The analyses generally suggested that the five factor model rather than the three-factor model was more robust and better for interpretation of all the higher order scales of the EPQ-R, EPP-S, and BFI-V4a in the Pakistani data. Results show that the superiority of the five factor solution results from the inclusion of a broader variety of personality scales in the input data, whereas Eysenck's three factor solution seems to be best when a less complete but possibly more important set of variables are input. (C) 2001 Elsevier Science Ltd. All rights reserved.

Carapace dentition patterns, morphometrics and allozyme differentiation amongst two toothed freshwater crab species (Potamonautes warreni and P-unispinus) (Decapoda : Brachyura : Potamonautidae) from river systems in South Africa

The taxonomic relationship between two toothed South African river crabs, Potamonautes warreni and P. unispinus, is unclear. The problem stems from the widespread variation in carapace dentition patterns amongst P. warreni individuals over its biogeographic range, where single toothed individuals may appear similar in carapace morphology to P. unispinus. Ten populations of P. warreni and 18 populations of P. unispinus were collected and the morphometric and genetic differentiation between the two taxa quantified. Patterns of morphometric and genetic variation were examined using multivariate statistics and protein gel electrophoresis, respectively. Principal component analyses of carapace characters showed that the two species are morphologically indistinguishable. However, discriminate functions analyses and additional statistical results corroborate the morphological distinction between the two taxa. Allozyme electrophoresis of 17 protein coding loci, indicated a close genetic similarity between the two species (I = 0.92). A fixed allelic difference at one locus (LT-2) and extensive genetic variability at another locus (PGM-1) indicate that two gene pools are present and that the two taxa are genetically isolated. Intraspecific genetic I values for both species were > 0.97 and indicated no apparent genetic structuring on a micro or macro-geographic scale. The variation in carapace dentition among P. warreni populations possesses no genetic basis and may possibly toe the product of ecogenesis. The value of dentition patterns in the systematics of river crabs is discussed. Dentition patterns among river crab species appear to be conserved and reliable as species specific diagnostic markers, but should ideally be used in combination with other morphological data sets and genetic evidence.

Treatment outcome in individuals with chronic pain: is the Pain Stages of Change Questionnaire (PSOCQ) a useful tool? Jenny StrongCorresponding Author Contact Information, E-mail The Corresponding Author, a, Kym Westburya, Glen Smithb, Ian McKenziec and William Ryan

The efficacy of psychological treatments emphasising a self-management approach to chronic pain has been demonstrated by substantial empirical research. Nevertheless, high drop-out and relapse rates and low or unsuccessful engagement in self-management pain rehabilitation programs have prompted the suggestion that people vary in their readiness to adopt a self-management approach to their pain. The Pain Stages of Change Questionnaire (PSOCQ) was developed to assess a patient's readiness to adopt a self-management approach to their chronic pain. Preliminary evidence has supported the PSOCQ's psychometric properties. The current study was designed to further examine the psychometric properties of the PSOCQ, including its reliability, factorial structure and predictive validity. A total of 107 patients with an average age of 36.2 years (SD = 10.63) attending a multi-disciplinary pain management program completed the PSOCQ, the Pain Self-Efficacy Questionnaire (PSEQ) and the West Haven-Yale Multidimensional Pain Inventory (WHYMPI) pre-admission and at discharge from the program. Initial data analysis found inadequate internal consistencies of the precontemplation and action scales of the PSOCQ and a high correlation (r = 0.66, P < 0.01) between the action and maintenance scales. Principal component analysis supported a two-factor structure: 'Contemplation' and 'Engagement'. Subsequent analyses revealed that the PSEQ was a better predictor of treatment outcome than the PSOCQ scales. Discussion centres upon the utility of the PSOCQ in a clinical pain setting in light of the above findings, and a need for further research. (C) 2002 International Association for the Study of Pain. Published by Elsevier Science B.V. All rights reserved.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.