Culture-Independent Assessment of Rhizobiales-Related Alphaproteobacteria and the Diversity of Methylobacterium in the Rhizosphere and Rhizoplane of Transgenic Eucalyptus

The rhizosphere is an ecosystem exploited by a variety of organisms involved in plant health and environmental sustainability. Abiotic factors influence microorganism-plant interactions, but the microbial community is also affected by expression of heterologous genes from host plants. In the present work, we assessed the community shifts of Alphaproteobacteria phylogenetically related to the Rhizobiales order (Rhizobiales-like community) in rhizoplane and rhizosphere soils of wild-type and transgenic eucalyptus. A greenhouse experiment was performed and the bacterial communities associated with two wild-type (WT17 and WT18) and four transgenic (TR-9, TR-15, TR-22, and TR-23) eucalyptus plant lines were evaluated. The culture-independent approach consisted of the quantification, by real-time polymerase chain reaction (PCR), of a targeted subset of Alphaproteobacteria and the assessment of its diversity using PCR-denaturing gradient gel electrophoresis (DGGE) and 16S rRNA gene clone libraries. Real-time quantification revealed a lesser density of the targeted community in TR-9 and TR-15 plants and diversity analysis by principal components analysis, based on PCR-DGGE, revealed differences between bacterial communities, not only between transgenic and nontransgenic plants, but also among wild-type plants. The comparison between clone libraries obtained from the transgenic plant TR-15 and wild-type WT17 revealed distinct bacterial communities associated with these plants. In addition, a culturable approach was used to quantify the Methylobacterium spp. in the samples where the identification of isolates, based on 16S rRNA gene sequences, showed similarities to the species Methylobacterium nodulans, Methylobacterium isbiliense, Methylobacterium variable, Methylobacterium fujisawaense, and Methylobacterium radiotolerans. Colonies classified into this genus were not isolated from the rhizosphere but brought in culture from rhizoplane samples, except for one line of the transgenic plants (TR-15). In general, the data suggested that, in most cases, shifts in bacterial communities due to cultivation of transgenic plants are similar to those observed when different wild-type cultivars are compared, although shifts directly correlated to transgenic plant cultivation may be found.

Transgenic tobacco revealing altered bacterial diversity in the rhizosphere during early plant development

The rhizosphere constitutes a complex niche that may be exploited by a wide variety of bacteria. Bacterium-plant interactions in this niche can be influenced by factors such as the expression of heterologous genes in the plant. The objective of this work was to describe the bacterial communities associated with the rhizosphere and rhizoplane regions of tobacco plants, and to compare communities from transgenic tobacco lines (CAB1, CAB2 and TRP) with those found in wild-type (WT) plants. Samples were collected at two stages of plant development, the vegetative and flowering stages (1 and 3 months after germination). The diversity of the culturable microbial community was assessed by isolation and further characterization of isolates by amplified ribosomal RNA gene restriction analysis (ARDRA) and 16S rRNA sequencing. These analyses revealed the presence of fairly common rhizosphere organisms with the main groups Alphaproteobacteria, Betaproteobacteria, Actinobacteria and Bacilli. Analysis of the total bacterial communities using PCR-DGGE (denaturing gradient gel electrophoresis) revealed that shifts in bacterial communities occurred during early plant development, but the reestablishment of original community structure was observed over time. The effects were smaller in rhizosphere than in rhizoplane samples, where selection of specific bacterial groups by the different plant lines was demonstrated. Clustering patterns and principal components analysis (PCA) were used to distinguish the plant lines according to the fingerprint of their associated bacterial communities. Bands differentially detected in plant lines were found to be affiliated with the genera Pantoea, Bacillus and Burkholderia in WT, CAB and TRP plants, respectively. The data revealed that, although rhizosphere/rhizoplane microbial communities can be affected by the cultivation of transgenic plants, soil resilience may be able to restore the original bacterial diversity after one cycle of plant cultivation.

The phylogeography of African Brazilians

Background/Aims: Approximately four million Africans were taken as slaves to Brazil, where they interbred extensively with Amerindians and Europeans. We have previously shown that while most White Brazilians carry Y chromosomes of European origin, they display high proportions of African and Amerindian mtDNA lineages, because of sex-biased genetic admixture. Methods: We studied the Y chromosome and mtDNA haplogroup structure of 120 Black males from Sao Paulo, Brazil. Results: Only 48% of the Y chromosomes, but 85% of the mtDNA haplogroups were characteristic of sub-Saharan Africa, confirming our previous observation of sexually biased mating. We mined literature data for mtDNA and Y chromosome haplogroup frequencies for African native populations from regions involved in Atlantic Slave Trade. Principal Components Analysis and Bayesian analysis of population structure revealed no genetic differentiation of Y chromosome marker frequencies between the African regions. However, mtDNA examination unraveled considerable genetic structure, with three clusters at Central-West Africa, West Africa and Southeast Africa. A hypothesis is proposed to explain this structure. Conclusion: Using these mtDNA data we could obtain for the first time an estimate of the relative ancestral contribution of Central-West (0.445), West (0.431) and Southeast Africa (0.123) to African Brazilians from Sao Paulo. These estimates are consistent with historical information. Copyright (c) 2008 S. Karger AG, Basel.

Diagnostic model based on Raman spectra of normal, hyperplasia and prostate adenocarcinoma tissues in vitro

This study evaluated the use of Raman spectroscopy to identify the spectral differences between normal (N), benign hyperplasia (BPH) and adenocarcinoma (CaP) in fragments of prostate biopsies in vitro with the aim of developing a spectral diagnostic model for tissue classification. A dispersive Raman spectrometer was used with 830 nm wavelength and 80 mW excitation. Following Raman data collection and tissue histopathology (48 fragments diagnosed as N, 43 as BPH and 14 as CaP), two diagnostic models were developed in order to extract diagnostic information: the first using PCA and Mahalanobis analysis techniques and the second one a simplified biochemical model based on spectral features of cholesterol, collagen, smooth muscle cell and adipocyte. Spectral differences between N, BPH and CaP tissues, were observed mainly in the Raman bands associated with proteins, lipids, nucleic and amino acids. The PCA diagnostic model showed a sensitivity and specificity of 100%, which indicates the ability of PCA and Mahalanobis distance techniques to classify tissue changes in vitro. Also, it was found that the relative amount of collagen decreased while the amount of cholesterol and adipocyte increased with severity of the disease. Smooth muscle cell increased in BPH tissue. These characteristics were used for diagnostic purposes.

PM(2.5) and PM(10): The influence of sugarcane burning on potential cancer risk

In Brazil, sugarcane fields are often burned to facilitate manual harvesting, and this burning causes environmental pollution from the large amounts of soot released into the atmosphere. This material contains numerous organic compounds such as PAHs. In this study, the concentrations of PAHs in two particulate-matter fractions (PM(2.5) and PM(10)) in the city of Araraquara (SE Brazil, with around 200,000 inhabitants and surrounded by sugarcane plantations) were determined during the sugarcane harvest (HV) and non-harvest (NHV) seasons in 2008 and 2009. The sampling strategy included four campaigns, with 60 samples in the NHV season and 220 samples in the HV season. The PM(2.5) and PM(10) fractions were collected using a dichotomous sampler (10 L min(-1), 24 h) with Teflon (TM) filters. The filter sets were extracted (ultrasonic bath with hexane/acetone (1:1 v/v)) and analyzed by HPLC/Fluorescence. The median concentration for total PAHs (PM(2.5) in 2009) was 0.99 ng m(-3) (NHV) and 3.3 ng m(-3) (HV). In the HV season, the total concentration of carcinogenic PAHs (benz(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, and benzo(a)pyrene) was 5 times higher than in the NHV season. B(a)P median concentrations were 0.017 ng m(-3) and 0.12 ng m(-3) for the NHV and HV seasons, respectively. The potential cancer risk associated with exposure through inhalation of these compounds was estimated based on the benzo[a]pyrene toxic equivalence (BaP(eq)), where the overall toxicity of a PAR mixture is defined by the concentration of each compound multiplied by its relative toxic equivalence factor (TEF). BaP(eq) median (2008 and 2009 years) ranged between 0.65 and 1.0 ng m(-3) and 1.2-1.4 ng m(-3) for the NHV and HV seasons, respectively. Considering that the maximum permissible BaPeq in ambient air is 1 ng m(-3), related to the increased carcinogenic risk, our data suggest that the level of human exposure to PAHs in cities surrounded by sugarcane crops where the burning process is used is cause for concern. (C) 2010 Published by Elsevier Ltd.

Reliability and validity of the Brazilian-Portuguese version of the Burns Specific Pain Anxiety Scale (BSPAS)

Background: Pain and anxiety are a common problem in all recovery phases after a burn. The Burns Specific Pain Anxiety Scale (BSPAS) was proposed to assess anxiety in burn patients related to painful procedures. Objectives: To assess internal consistency, discriminative construct validity, dimensionality and convergent construct validity of the Brazilian-Portuguese version of the Burns Specific Pain Anxiety Scale. Design: In this cross-sectional study, the original version of the BSPAS, adapted into Brazilian Portuguese, was tested for internal consistency (Cronbach`s Alpha), discriminative validity (related to total body surface area burned and sex), dimensionality (through factor analysis), and convergent construct validity (applying the Visual Analogue Scale for pain and State-Anxiety-STAI) in a group of 91 adult burn patients. Results: The adapted version of the BSPAS displayed a moderate and positive correlation with pain assessments: immediately before baths and dressings (r = 0.32; p < 0.001), immediately after baths and dressings (r = 0.31; p < 0.001) and during the relaxation period (r= 0.31; p < 0.001) and with anxiety assessments (r = 0.34; p < 0.001). No statistically significant differences were observed when comparing the mean of the adapted version of the BSPAS scores with sex (p = 0.194) and total body surface area burned (p = 0.162) (discriminative validity). The principal components analysis applied to our sample seems to confirm anxiety as one single domain of the Brazilian-Portuguese version of the BSPAS. Cronbach`s Alpha showed high internal consistency of the adapted version of the scale (0.90). Conclusion: The Brazilian-Portuguese version of the BSPAS 9-items has shown statically acceptable levels of reliability and validity for pain-related anxiety evaluation in burn patients. This scale can be used to assess nursing interventions aimed at decreasing pain and anxiety related to the performance of painful procedures. (c) 2010 Elsevier Ltd. All rights reserved.

Assessing the impact of deforestation and climate change on the range size and environmental niche of bird species in the Atlantic forests, Brazil

Aim Habitat loss and climate change are two major drivers of biological diversity. Here we quantify how deforestation has already changed, and how future climate scenarios may change, environmental conditions within the highly disturbed Atlantic forests of Brazil. We also examine how environmental conditions have been altered within the range of selected bird species. Location Atlantic forests of south-eastern Brazil. Methods The historical distribution of 21 bird species was estimated using Maxent. After superimposing the present-day forest cover, we examined the environmental niches hypothesized to be occupied by these birds pre- and post-deforestation using environmental niche factor analysis (ENFA). ENFA was also used to compare conditions in the entire Atlantic forest ecosystem pre- and post-deforestation. The relative influence of land use and climate change on environmental conditions was examined using analysis of similarity and principal components analysis. Results Deforestation in the region has resulted in a decrease in suitable habitat of between 78% and 93% for the Atlantic forest birds included here. Further, Atlantic forest birds today experience generally wetter and less seasonal forest environments than they did historically. Models of future environmental conditions within forest remnants suggest generally warmer conditions and lower annual variation in rainfall due to greater precipitation in the driest quarter of the year. We found that deforestation resulted in a greater divergence of environmental conditions within Atlantic forests than that predicted by climate change. Main conclusions The changes in environmental conditions that have occurred with large-scale deforestation suggest that selective regimes may have shifted and, as a consequence, spatial patterns of intra-specific variation in morphology, behaviour and genes have probably been altered. Although the observed shifts in available environmental conditions resulting from deforestation are greater than those predicted by climate change, the latter will result in novel environments that exceed temperatures in any present-day climates and may lead to biotic attrition unless organisms can adapt to these warmer conditions. Conserving intra-specific diversity over the long term will require considering both how changes in the recent past have influenced contemporary populations and the impact of future environmental change.

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.

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.

Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

Multivariate analysis of the energy cycle of the South American rainy season

The South American (SA) rainy season is studied in this paper through the application of a multivariate Empirical Orthogonal Function (EOF) analysis to a SA gridded precipitation analysis and to the components of Lorenz Energy Cycle (LEC) derived from the National Centers for Environmental Prediction (NCEP) reanalysis. The EOF analysis leads to the identification of patterns of the rainy season and the associated mechanisms in terms of their energetics. The first combined EOF represents the northwest-southeast dipole of the precipitation between South and Central America, the South American Monsoon System (SAMS). The second combined EOF represents a synoptic pattern associated with the SACZ (South Atlantic convergence zone) and the third EOF is in spatial quadrature to the second EOF. The phase relationship of the EOFs, as computed from the principal components (PCs), suggests a nonlinear transition from the SACZ to the fully developed SAMS mode by November and between both components describing the SACZ by September-October (the rainy season onset). According to the LEC, the first mode is dominated by the eddy generation term at its maximum, the second by both baroclinic and eddy generation terms and the third by barotropic instability previous to the connection to the second mode by September-October. The predominance of the different LEC components at each phase of the SAMS can be used as an indicator of the onset of the rainy season in terms of physical processes, while the existence of the outstanding spectral peaks in the time dependence of the EOFs at the intraseasonal time scale could be used for monitoring purposes. Copyright (C) 2009 Royal Meteorological Society

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

Long-term social recognition memory in adult male rats: factor analysis of the social and non-social behaviors

A modified version of the intruder-resident paradigm was used to investigate if social recognition memory lasts at least 24 h. One hundred and forty-six adult male Wistar rats were used. Independent groups of rats were exposed to an intruder for 0.083, 0.5, 2, 24, or 168 h and tested 24 h after the first encounter with the familiar or a different conspecific. Factor analysis was employed to identify associations between behaviors and treatments. Resident rats exhibited a 24-h social recognition memory, as indicated by a 3- to 5-fold decrease in social behaviors in the second encounter with the same conspecific compared to those observed for a different conspecific, when the duration of the first encounter was 2 h or longer. It was possible to distinguish between two different categories of social behaviors and their expression depended on the duration of the first encounter. Sniffing the anogenital area (49.9% of the social behaviors), sniffing the body (17.9%), sniffing the head (3%), and following the conspecific (3.1%), exhibited mostly by resident rats, characterized social investigation and revealed long-term social recognition memory. However, dominance (23.8%) and mild aggression (2.3%), exhibited by both resident and intruders, characterized social agonistic behaviors and were not affected by memory. Differently, sniffing the environment (76.8% of the non-social behaviors) and rearing (14.3%), both exhibited mostly by adult intruder rats, characterized non-social behaviors. Together, these results show that social recognition memory in rats may last at least 24 h after a 2-h or longer exposure to the conspecific.

Caracterização físico-química de polpas de frutos da Amazônia e sua correlação com a atividade anti-radical livre

Características físico-químicas (cor, pH, acidez total titulável, sólidos solúveis totais, conteúdo de lipídios e umidade) e níveis de compostos bioativos (ácido ascórbico, fenólicos totais) foram determinados em quinze amostras de polpas de frutos procedentes da região Amazônica (abiu, acerola, açaí, araçá-boi, bacaba, bacuri, buriti, cajá, cajarana, caju, cupuaçu, graviola, murici, noni e tamarindo). A atividade de radicais livres foi avaliada pelo método de ABTS. Algumas polpas apresentaram alta potencialidade antioxidante, associada com a atividade antirradicais livres obtida e os conteúdos dos componentes bioativos como compostos fenólicos e ácido ascórbico, destacando-se acerola e acaí. O conteúdo total de compostos fenólicos foi correlacionado à capacidade antioxidante das polpas.

Condições socioeconômicas e padrões alimentares de crianças de 4 a 11 anos: estudo SCAALA - Salvador/ Bahia

OBJETIVOS: identificar os padrões alimentares de crianças e sua associação com o nível socioeconômico das famílias. MÉTODOS: estudo transversal com 1260 crianças de 4 a 11 anos, residentes em Salvador-Bahia que incluiu aplicação de um Questionário de Frequência Alimentar semi-quantitativo. Os padrões alimentares foram identificados, empregando-se análise fatorial por componentes principais. O nível socioeconômico foi avaliado por meio de um indicador socioeconômico composto. Regressão logística multivariada foi empregada. RESULTADOS: identificaram-se quatro padrões que explicaram 45,9% da variabilidade dos dados de frequência alimentar. Crianças que pertencem ao nível socioeconômico mais alto têm 1,60 vezes mais chance (p<0,001) de apresentarem maior frequência de consumo de alimentos do padrão 1 (frutas, verduras, leguminosas, cereais e pescados) e 3,09 vezes mais chance (p<0,001) de apresentarem maior frequência de consumo dos alimentos do padrão 2 (leite/ derivados, catchup/ maionese/ mostarda e frango), quando se compara com aquele de crianças de nível socioeconômico mais baixo. Resultado inverso foi observado no padrão 4 (embutidos, ovos e carnes vermelhas); isto é, quanto maior o nível socioeconômico menor a chance da adoção desse padrão. Tendência similar foi notada para o padrão 3 (frituras, doces, salgadinhos, refrigerante/ suco artificial). CONCLUSÕES: padrões alimentares de crianças são dependentes das condições socioeconômicas das famílias e a adoção de itens alimentares mais saudáveis associa-se aos grupos de mais altos níveis socioeconômicos.