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)

PXRF and multivariate statistics analysis of pre-colonial pottery from northeast of Brazil

Portable system of energy dispersive X-ray fluorescence was used to determine the elemental composition of 68 pottery fragments from Sambaqui do Bacanga, an archeological site in Sao Luis, Maranhao, Brazil. This site was occupied from 6600 BP until 900 BP. By determining the element chemical composition of those fragments, it was possible to verify the existence of engobe in 43 pottery fragments. Obtained from two-dimensional graphs and hierarchical cluster analysis performed in fragments of stratigraphies from surface and 113-cm level, and 10 to 20, 132 and 144-cm level, it was possible to group these fragments in five distinct groups, according to their stratigraphies. The results of data grouping (two-dimensional graphics) are in agreement with hierarchical cluster analysis by Ward method. Copyright (C) 2011 John Wiley & Sons, Ltd.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Comparative study of dissolved organic matter from groundwater and surface water in the Florida coastal Everglades using multi-dimensional spectrofluorometry combined with multivariate statistics

Dissolved organic matter (DOM) in groundwater and surface water samples from the Florida coastal Everglades were studied using excitation–emission matrix fluorescence modeled through parallel factor analysis (EEM-PARAFAC). DOM in both surface and groundwater from the eastern Everglades S332 basin reflected a terrestrial-derived fingerprint through dominantly higher abundances of humic-like PARAFAC components. In contrast, surface water DOM from northeastern Florida Bay featured a microbial-derived DOM signature based on the higher abundance of microbial humic-like and protein-like components consistent with its marine source. Surprisingly, groundwater DOM from northeastern Florida Bay reflected a terrestrial-derived source except for samples from central Florida Bay well, which mirrored a combination of terrestrial and marine end-member origin. Furthermore, surface water and groundwater displayed effects of different degradation pathways such as photodegradation and biodegradation as exemplified by two PARAFAC components seemingly indicative of such degradation processes. Finally, Principal Component Analysis of the EEM-PARAFAC data was able to distinguish and classify most of the samples according to DOM origins and degradation processes experienced, except for a small overlap of S332 surface water and groundwater, implying rather active surface-to-ground water interaction in some sites particularly during the rainy season. This study highlights that EEM-PARAFAC could be used successfully to trace and differentiate DOM from diverse sources across both horizontal and vertical flow profiles, and as such could be a convenient and useful tool for the better understanding of hydrological interactions and carbon biogeochemical cycling.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

Discrimination of geomorphic surfaces with multivariate analysis of soil attributes in sandstone - basalt lithosequence

O conceito de superfície geomórfica permite uma interligação entre os diferentes ramos da ciência do solo, tais como geologia, geomorfologia e pedologia. Esta associação favorece a compreensão da distribuição espacial dos solos na paisagem, e torna possível compreender o comportamento dos atributos do solo, que estão principalmente relacionadas com a estratigrafia e formas do relevo. Assim, este estudo visa à aplicação da estatística multivariada para categorizar superfícies geomórficas em uma litossequência arenito-basalto, de modo a fornecer uma base para a avaliação do solo em áreas afins. A área de estudo está localizada no município de Pereira Barreto, São Paulo, Brasil. A área escolhida possui 530 hectares, onde foram localizadas e mapeadas três superfícies geomórficas (I, II e III). Na área, 134 amostras foram coletadas nas profundidades de 0,0-0,2 m e 0,8-1,0 m, foram determinados os conteúdos de areia, silte e argila, pH em CaCl2, conteúdo de MO, P, Ca, Mg, K, Al e H+Al. Com base nos resultados, foram realizadas a análise univariada e multivariada de variância, clusters e principal componente, a fim de comparar as três superfícies geomórficas. A análise estatística univariada dos atributos do solo não foi eficiente na identificação das três superfícies geomórficas. Utilizando-se os atributos físicos e químicos do solo, as técnicas estatísticas multivariada permitiram à separação dos três grupos de corpos naturais do solo que foram equivalentes as três superfícies geomórficas mapeadas. Estes resultados são interessantes, pois demonstram a viabilidade da utilização de classificação numérica das superfícies geomórficas para ajudar no mapeamento de solo.

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.

Gênero e estresse em trabalhadores de uma universidade pública do estado de São Paulo

The aim of this paper was to identify, according to gender, the indexes of Mental Health and the Psychosocial Risk Factors in workers at a state University. A sample of 400 was randomly selected, 253 female and 147 male. They were assessed by means of The Questionnaire SWS Survey (Self, Work and Social) (Ostermann & Gutiérrez, 1992), validated in Brazil by Guimarães and Macfadden (1999). Univariate, bivariate, multivariate statistics were assessed. Significant associations emerged from Mental Health and Gender, and Psychosocial Risk Factors and Gender. Women showed greater Psychosocial Risk Factors, Work and Social Stress, worst mental health than men (p < 0.05), which place them at greater risk for developing physical and/or mental illness.

Origem e dispersão dos Tupiguarani: o que diz a morfologia craniana?

A origem e a dispersão dos povos Tupiguarani têm sido intensamente debatidas entre arqueólogos e linguistas nas últimas cinco décadas. Em resumo, pode-se dizer que a ideia de que esses povos, que ocuparam grande parte do território brasileiro e parte da Bolívia, do Paraguai, do Uruguai e da Argentina, tiveram sua etnogênese na Amazônia e dali partiram para o leste e para o sul, por volta de 2.500 anos antes do presente, é bastante aceita entre os especialistas, embora uma dispersão no sentido oposto, isto é, do sul para o norte, com origem na bacia do Tietê-Paraná, não seja completamente descartada. Entre os arqueólogos que consideram a Amazônia como berço desses povos, alguns acreditam que esse surgimento se deu na Amazônia central. Outros acreditam que a etnogênese Tupiguarani ocorreu no sudoeste da Amazônia, onde hoje se concentra a maior diversidade linguística do tronco Tupi. Neste trabalho, a morfologia de 19 crânios associados à cerâmica Tupiguarani ou etnograficamente classificados como tais foram comparados a várias séries cranianas pré-históricas e etnográficas brasileiras por meio de estatísticas multivariadas. Duas técnicas multivariadas foram empregadas: Análise de Componentes Principais, aplicada sobre os centróides de cada série, e Distâncias de Mahalanobis, aplicadas aos dados individuais. Os resultados obtidos sugerem uma origem amazônica para os povos Tupiguarani, sobretudo pela forte associação encontrada entre crânios Tupi e Guarani do sudeste e do sul brasileiro e dos Tupi do norte do Brasil, com os espécimes provenientes da ilha de Marajó incluídos no estudo.

Dimorfismo sexual alar em Aedes scapularis (Diptera: Culicidae)

A detecção do sexo de mosquitos da família Culicidae é importante em estudos faunísticos e epidemiológicos, pois somente as fêmeas possuem competência vetora para patógenos. O dimorfismo sexual de genitália e de apêndices cefálicos é, em geral, facilmente visível em culicídeos. As asas também podem ser dimórficas e assim poderiam complementar o procedimento de sexagem. No entanto, tal distinção não é facilmente notável à observação direta. Visando descrever formalmente o dimorfismo sexual alar em Aedes scapularis, um culicídeo vetorialmente competente para arbovírus e filárias, asas de machos e fêmeas foram comparadas usando-se métodos de morfometria geométrica e análise estatística multivariada. Nestas análises, populações dos municípios São Paulo e Pariquera-Açu (Estado de São Paulo) foram amostradas. A forma das asas mostrou evidente dimorfismo sexual, o que permitiu um índice de acurácia de 100% em testes-cegos de reclassificação, independentemente da origem geográfica. Já o tamanho alar foi sexualmente dimórfico apenas na população de São Paulo. Aparentemente, a forma alar é evolutivamente mais estável que o tamanho, interpretação que está de acordo com a teoria de Dujardin (2008b), de que a forma alar de insetos seria composta por caracteres genéticos quantitativos e pouco influenciada por fatores não-genéticos, enquanto que o tamanho alar seria predominantemente determinado por plasticidade decorrente de influências ambientais.

Evaluating the Taxonomic Identity in Four Species of the Lobose Testate Amoebae Genus Arcella Ehrenberg, 1832

The taxonomic identity in microbial eukaryotes remains an impediment to discussing ecology, biogeography and phylogeny, mainly due to a lack of standards in organism descriptions and few comparative works. The lobose testate amoebae (Arcellinida) present an ideal study system, as progress is severely hindered due to taxonomic confusion. In the present survey, we have examined the morphology, biometry and ecology of 2400 individuals in the genus Arcella Ehrenberg, 1832, collected from the Tiete River in Sao Paulo, Brazil. We then contrasted these new data with 26 previously described species, varieties and forms, looking for consistencies and trying to establish distinct entities. Using a combination of morphology and multivariate statistics we were able to determine 4 distinct taxa (Arcella hemisphaerica, Arcella discoides, Arcella gibbosa and Arcella brasiliensis), each of them encompassing a number of other non-distinct nominal taxa. We describe in detail each of the 4 taxa with notes on ecology and biogeography, and list the indistinguishable names in an effort to make identification and taxonomy in the testate amoebae a more objective and precise exercise by clarifying the taxonomic identity.

Changes in the genetic structure of Bacteria and microbial activity in an agricultural soil amended with tannery sludge

The application of tannery sludge to soils is a form of recycling; however, few studies have examined the impacts of this practice on soil microbial properties. We studied effects of two applications (2006 and 2007) of tannery sludge (with a low chromium content) on the structure of the bacterial community and on the microbial activity of soils. We fertilized an agricultural area in Rolandia, Parana state, Brazil with different doses of sludge based on total N content, which ranged from 0 to 1200 kg N ha(-1). Sludge remained on the soil surface for three months before being plowed. Soils were sampled seven times during the experiment. Bacterial community structure, assessed by denaturing gradient gel electrophoresis (DGGE), was modified by the application of tannery sludge. Soon after the first application, there was clear separation between the bacterial communities in different treatments, such that each dose of sludge was associated with a specific community. These differences remained until 300 days after application and also after the second sludge application, but 666 days after the beginning of the experiment no differences were found in the bacterial communities of the lowest doses and the control. The principal response curve (PRC) analysis showed that the first sludge application strongly stimulated biological activity even 300 days after application. The second application also stimulated activity, but at a lower magnitude and for a shorter time, given that 260 days after the second application there was no difference in biological activity among treatments. PRC also showed that the properties most influenced by the application of tannery sludge were enzymatic activities related to N cycling (asparaginase and urease). The redundancy analysis (RDA) showed that tannery sludge`s influence on microbial activity is mainly related to increases in inorganic N and soil pH. Results showed that changes in the structure of the bacterial community in the studied soils were directly related to changes of their biological activity. (C) 2010 Elsevier Ltd. All rights reserved.

Characterization of Brazilian lager and brown ale beers based on color, phenolic compounds, and antioxidant activity using chemometrics

BACKGROUND: Epidemiological studies have shown that beer has positive effects on inhibiting atherosclerosis, decreasing the content of serum low-density lipoprotein cholesterol and triglycerides, by acting as in vivo free radical scavenger. In this research, the antioxidant activity of commercial Brazilian beers (n = 29) was determined by the oxygen radical absorbance capacity (ORAC) and 1,1 -diphenyl-2-picrylhydrazyl (DPPH(center dot)) assays and results were analyzed by chemometrics. RESULTS: The brown ale samples (n = 11) presented higher (P < 0.05) flavonoids (124.01 mg L(-1)), total phenolics (362.22 mg L(-1)), non-flavonoid phenolics (238.21 mg L(-1)), lightness (69.48), redness (35.75), yellowness (55.71), color intensity (66.86), hue angle (59.14), color saturation (0.9620), DPPH(center dot) values (30.96% inhibition), and ORAC values (3,659.36 mu mol Trolox equivalents L(-1)), compared to lager samples (n = 18). Brown ale beers presented higher antioxidant properties (P < 0.05) measured by ORAC (1.93 times higher) and DPPH (1.65 times higher) compared to lager beer. ORAC values correlated well with the content of flavonoids (r = 0.47; P = 0.01), total phenolic compounds (r = 0.44; P < 0.01) and DPPH (r = 0.67; P < 0.01). DPPH values also correlated well to the content of flavonoids (r = 0.69; P < 0.01), total phenolic compounds (r = 0.60; P < 0.01), and non-flavonoid compounds (r = 0.46; P = 0.01). CONCLUSION: The results suggest that brown ale beers, and less significantly lager beers, could be sources of bioactive compounds with suitable free radical scavenging properties. (C) 2010 Society of Chemical Industry

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.