Generic relationships and dating of lineages in Winteraceae based on nuclear (ITS) and plastid (rpS16 and psbA-trnH) sequence data

Phylogenetic analyses of representative species from the five genera of Winteraceae (Drimys, Pseudowintera, Takhtajania, Tasmannia, and Zygogynum s.l.) were performed using ITS nuclear sequences and a combined data-set of ITS + psbA-trnH + rpS16 sequences (sampling of 30 and 15 species, respectively). Indel informativity using simple gap coding or gaps as a fifth character was examined in both data-sets. Parsimony and Bayesian analyses support the monophyly of Drimys, Tasmannia, and Zygogynum s.l., but do not support the monophyly of Belliolum, Zygogynum s.s., and Bubbia. Within Drimys, the combined data-set recovers two subclades. Divergence time estimates suggest that the splitting between Drimys and its sister clade (Pseudowintera + Zygogynum s.l.) occurred around the end of the Cretaceous; in contrast, the divergence between the two subclades within Drimys is more recent (15.5-18.5 MY) and coincides in time with the Andean uplift. Estimates suggest that the earliest divergences within Winteraceae could have predated the first events of Gondwana fragmentation. (C) 2009 Elsevier Inc. All rights reserved.

Balanced polymorphism in bottlenecked populations: The case of the CCR5 5 ` cis-regulatory region in Amazonian Amerindians

The 5` cis-regulatory region of the CCR5 gene exhibits a strong signature of balancing selection in several human populations. Here we analyze the polymorphism of this region in Amerindians from Amazonia, who have a complex demographic history, including recent bottlenecks that are known to reduce genetic variability. Amerindians show high nucleotide diversity (pi = 0.27%) and significantly positive Tajima`s D, and carry haplotypes associated with weak and strong gene expression. To evaluate whether these signatures of balancing selection could be explained by demography, we perform neutrality tests based on empiric and simulated data. The observed Tajima`s D was higher than that of other world populations: higher than that found for 18 noncoding regions of South Amerindians, and higher than 99.6% of simulated genealogies, which assume nonequilibrium conditions. Moreover, comparing Amerindians and Asians, the Fst for CCR5 cis-regulatory region was unusually low, in relation to neutral markers. These findings indicate that, despite their complex demographic history, South Amerindians carry a detectable signature of selection on the CCR5 cis-regulatory region. (C) 2010 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Five vicarious genera from Gondwana: the Velloziaceae as shown by molecules and morphology

Background and Aims The amount of data collected previously for Velloziaceae neither clarified relationships within the family nor helped determine an appropriate classification, which has led to huge discordance among treatment by different authors. To achieve an acceptable phylogenetic result and understand the evolution and roles of characters in supporting groups, a total evidence analysis was developed which included approx. 20 % of the species and all recognized genera and sections of Velloziaceae, plus outgroups representatives of related families within Pandanales. Methods Analyses were undertaken with 48 species of Velloziaceae, representing all ten genera, with DNA sequences from the atpB-rbcL spacer, trnL-trnF spacer, trnL intron, trnH-psbA spacer, ITS ribosomal DNA spacers and morphology. Key Results Four groups consistently emerge from the analyses. Persistent leaves, two phloem strands, stem cortex divided in three regions and violet tepals support Acanthochlamys as sister to Velloziaceae s. s., which are supported mainly by leaves with marginal bundles, transfusion tracheids and inflorescence without axis. Within Velloziaceae s. s., an African Xerophyta + Talbotia clade is uniquely supported by basal loculicidal capsules; an American clade, Barbacenia s. l. + Barbaceniopsis + Nanuza + Vellozia, is supported by only homoplastic characters. Barbacenia s. l. (Aylthonia + Barbacenia + Burlemarxia + Pleurostima) is supported by a double sheath in leaf vascular bundles and a corona; Barbaceniopsis + Nanuza + Vellozia is not supported by an unambiguous character, but Barbaceniopsis is supported by five characters, including diclinous flowers, Nanuza + Vellozia is supported mainly by horizontal stigma lobes and stem inner cortex cells with secondary walls, and Vellozia alone is supported mainly by pollen in tetrads. Conclusions The results imply recognition of five genera (Acanthochlamys (Xerophyta (Barbacenia (Barbaceniopsis, Vellozia)))), solving the long-standing controversies among recent classifications of the family. They also suggest a Gondwanan origin for Velloziaceae, with a vicariant pattern of distribution.

The non-coding RNA BC1 is down-regulated in the hippocampus of Wistar Audiogenic Rat (WAR) strain after audiogenic kindling

The aim of this study was to identify molecular pathways involved in audiogenic seizures in the epilepsy-prone Wistar Audiogenic Rat (WAR). For this, we used a suppression-subtractive hybridization (SSH) library from the hippocampus of WARs coupled to microarray comparative gene expression analysis, followed by Northern blot validation of individual genes. We discovered that the levels of the non-protein coding (npc) RNA BC1 were significantly reduced in the hippocampus of WARs submitted to repeated audiogenic seizures (audiogenic kindling) when compared to Wistar resistant rats and to both naive WARs and Wistars. By quantitative in situ hybridization, we verified lower levels of BC1 RNA in the GD-hilus and significant signal ratio reduction in the stratum radiatum and stratum pyramidale of hippocampal CA3 subfield of audiogenic kindled animals. Functional results recently obtained in a BC1-/- mouse model and our current data are supportive of a potential disruption in signaling pathways, upstream of BC1, associated with the seizure susceptibility of WARs. (C) 2010 Elsevier B.V. All rights reserved.

Mechanism of acetylcholine-induced calcium signaling during neuronal differentiation of P19 embryonal carcinoma cells in vitro

Muscarinic (mAChRs) and nicotinic acetylcholine receptors (nAChRs) are involved in various physiological processes, including neuronal development. We provide evidence for expression of functional nicotinic and muscarinic receptors during differentiation of P19 carcinoma embryonic cells, as an in vitro model of early neurogenesis. We have detected expression and activity alpha(2)-alpha(7), beta(2), beta(4) nAChR and M1-M5 mAChR subtypes during neuronal differentiation. Nicotinic alpha(3) and beta(2) mRNA transcription was induced by addition of retinoic acid to P19 cells. Gene expression Of alpha(2), alpha(4)-alpha(7), beta(4) nAChR subunits decreased during initial differentiation and increased again when P19 cells underwent final maturation. Receptor response in terms of nicotinic agonist-evoked Ca2+, flux was observed in embryonic and neuronal-differentiated cells. Muscarinic receptor response, merely present in undifferentiated P19 cells, increased during neuronal differentiation. The nAChR-induced elevation of intracellular calcium ([Ca2+](i)) response in undifferentiated cells was due to Ca2+ influx. In differentiated P19 neurons the nAChR-induced [Ca2+](i) response was reduced following pretreatment with ryanodine, while the mAChR-induced response was unaffected indicating the contribution of Ca2+ release from ryanodine-sensitive stores to nAChR- but not mAChR-mediated Ca2+ responses. The presence of functional nAChRs in embryonic cells suggests that these receptors are involved in triggering Ca2+ waves during initial neuronal differentiation. (C) 2007 Elsevier Ltd. All rights reserved.

Genetic and Functional Evidence Implicating DLL1 as the Gene That Influences Susceptibility to Visceral Leishmaniasis at Chromosome 6q27

Background. Visceral leishmaniasis (VL) is caused by Leishmania donovani and Leishmania infantum chagasi. Genome-wide linkage studies from Sudan and Brazil identified a putative susceptibility locus on chromosome 6q27. Methods. Twenty-two single-nucleotide polymorphisms (SNPs) at genes PHF10, C6orf70, DLL1, FAM120B, PSMB1, and TBP were genotyped in 193 VL cases from 85 Sudanese families, and 8 SNPs at genes PHF10, C6orf70, DLL1, PSMB1, and TBP were genotyped in 194 VL cases from 80 Brazilian families. Family-based association, haplotype, and linkage disequilibrium analyses were performed. Multispecies comparative sequence analysis was used to identify conserved noncoding sequences carrying putative regulatory elements. Quantitative reverse-transcription polymerase chain reaction measured expression of candidate genes in splenic aspirates from Indian patients with VL compared with that in the control spleen sample. Results. Positive associations were observed at PHF10, C6orf70, DLL1, PSMB1, and TBP in Sudan, but only at DLL1 in Brazil (combined P = 3 x 10(-4) at DLL1 across Sudan and Brazil). No functional coding region variants were observed in resequencing of 22 Sudanese VL cases. DLL1 expression was significantly (P = 2 x 10(-7)) reduced (mean fold change, 3.5 [SEM, 0.7]) in splenic aspirates from patients with VL, whereas other 6q27 genes showed higher levels (1.27 x 10(-6) < P < .01) than did the control spleen sample. A cluster of conserved noncoding sequences with putative regulatory variants was identified in the distal promoter of DLL1. Conclusions. DLL1, which encodes Delta-like 1, the ligand for Notch3, is strongly implicated as the chromosome 6q27 VL susceptibility gene.

MicroRNA expression is differentially altered by xenobiotic drugs in different human cell lines

Several noncoding microRNAs (miR or miRNA) have been shown to regulate the expression of drug-metabolizing enzymes and transporters. Xenobiotic drug-induced changes in enzyme and transporter expression may be associated with the alteration of miRNA expression. Therefore, this study investigated the impact of 19 xenobiotic drugs (e. g. dexamethasone, vinblastine, bilobalide and cocaine) on the expression of ten miRNAs (miR-18a, -27a, -27b, -124a, -148a, -324-3p, -328, -451, -519c and -1291) in MCF-7, Caco-2, SH-SY5Y and BE(2)-M17 cell systems. The data revealed that miRNAs were differentially expressed in human cell lines and the change in miRNA expression was dependent on the drug, as well as the type of cells investigated. Notably, treatment with bilobalide led to a 10-fold increase of miR-27a and a 2-fold decrease of miR-148a in Caco-2 cells, but no change of miR-27a and a 2-fold increase of miR-148a in MCF-7 cells. Neuronal miR-124a was generally down-regulated by psychoactive drugs (e. g. cocaine, methadone and fluoxetine) in BE(2)-M17 and SH-SY5Y cells. Dexamethasone and vinblastine, inducers of drug-metabolizing enzymes and transporters, suppressed the expression of miR-27b, -148a and -451 that down-regulate the enzymes and transporters. These findings should provide increased understanding of the altered gene expression underlying drug disposition, multidrug resistance, drug-drug interactions and neuroplasticity. Copyright (C) 2011 John Wiley & Sons, Ltd.

Fur controls iron homeostasis and oxidative stress defense in the oligotrophic alpha-proteobacterium Caulobacter crescentus

In most bacteria, the ferric uptake regulator (Fur) is a global regulator that controls iron homeostasis and other cellular processes, such as oxidative stress defense. In this work, we apply a combination of bioinformatics, in vitro and in vivo assays to identify the Caulobacter crescentus Fur regulon. A C. crescentus fur deletion mutant showed a slow growth phenotype, and was hypersensitive to H(2)O(2) and organic peroxide. Using a position weight matrix approach, several predicted Fur-binding sites were detected in the genome of C. crescentus, located in regulatory regions of genes not only involved in iron uptake and usage but also in other functions. Selected Fur-binding sites were validated using electrophoretic mobility shift assay and DNAse I footprinting analysis. Gene expression assays revealed that genes involved in iron uptake were repressed by iron-Fur and induced under conditions of iron limitation, whereas genes encoding iron-using proteins were activated by Fur under conditions of iron sufficiency. Furthermore, several genes that are regulated via small RNAs in other bacteria were found to be directly regulated by Fur in C. crescentus. In conclusion, Fur functions as an activator and as a repressor, integrating iron metabolism and oxidative stress response in C. crescentus.

Insights into the mechanism of progressive RNA degradation by the archaeal exosome

Initially identified in yeast, the exosome has emerged as a central component of the RNA maturation and degradation machinery both in Archaea and eukaryotes. Here we describe a series of high-resolution structures of the RNase PH ring from the Pyrococcus abyssi exosome, one of them containing three 10-mer RNA strands within the exosome catalytic chamber, and report additional nucleotide interactions involving positions N5 and N7. Residues from all three Rrp41-Rrp42 heterodimers interact with a single RNA molecule, providing evidence for the functional relevance of exosome ring-like assembly in RNA processivity. Furthermore, an ADP-bound structure showed a rearrangement of nucleotide interactions at site N1, suggesting a rationale for the elimination of nucleoside diphosphate after catalysis. In combination with RNA degradation assays performed with mutants of key amino acid residues, the structural data presented here provide support for a model of exosome-mediated RNA degradation that integrates the events involving catalytic cleavage, product elimination, and RNA translocation. Finally, comparisons between the archaeal and human exosome structures provide a possible explanation for the eukaryotic exosome inability to catalyze phosphate-dependent RNA degradation.

Precificação de opções de dólar no mercado brasileiro utilizando redes neurais e algoritmos genéticos

Esse trabalho comparou, para condições macroeconômicas usuais, a eficiência do modelo de Redes Neurais Artificiais (RNAs) otimizadas por Algoritmos Genéticos (AGs) na precificação de opções de Dólar à Vista aos seguintes modelos de precificação convencionais: Black-Scholes, Garman-Kohlhagen, Árvores Trinomiais e Simulações de Monte Carlo. As informações utilizadas nesta análise, compreendidas entre janeiro de 1999 e novembro de 2006, foram disponibilizadas pela Bolsa de Mercadorias e Futuros (BM&F) e pelo Federal Reserve americano. As comparações e avaliações foram realizadas com o software MATLAB, versão 7.0, e suas respectivas caixas de ferramentas que ofereceram o ambiente e as ferramentas necessárias à implementação e customização dos modelos mencionados acima. As análises do custo do delta-hedging para cada modelo indicaram que, apesar de mais complexa, a utilização dos Algoritmos Genéticos exclusivamente para otimização direta (binária) dos pesos sinápticos das Redes Neurais não produziu resultados significativamente superiores aos modelos convencionais.

Caracterização parcial de um fragmento e detecção por RT-PCR de Rice Stripe Necrosis Virus

O enrolamento do arroz é uma doença viral emergente no Brasil causada pelo Rice stripe necrosis virus (RSNV) que é transmitido pelo protozoário Polymyxa graminis. RSNV é um membro do gênero Benyvirus com genoma dividido em 4 RNAs de fita simples no sentido positivo (ssRNA +). Em função da falta de conhecimento sobre a seqüência de nucleotídeos do seu genoma, a detecção de RSNV através de métodos moleculares não é utilizada. O objetivo deste trabalho foi identificar seqüências do genoma de RSNV que possibilitassem sua detecção em plantas de arroz através da técnica de transcrição reversa seguida da reação em cadeia da polimerase (RT-PCR). As seqüências do genoma foram identificadas a partir de clones de uma biblioteca de cDNAs obtidos de uma amostra do vírus parcialmente purificado. Os clones que hibridizaram com sondas sintetizadas a partir de RNA de plantas infectadas com RSNV foram seqüenciados e comparados às seqüências do GenBank. Um fragmento de 957 nt da extremidade 3’ da fita de um dos 4 RNAs genômicos de RSNV foi obtido. A análise da seqüência nucleotídeos desse fragmento não revelou qualquer similaridade com seqüências conhecidas, tampouco indicou uma possível função. Um par de oligonucleotídeos iniciadores foi desenhado a partir de um clone que potencialmente contém uma seqüência de RSNV. A especificidade e a sensibilidade da RT-PCR utilizando esse par de oligonucleotídeos iniciadores, bem como sua eficiência na detecção do vírus em diferentes partes da planta de arroz, foram avaliadas. Os resultados indicam que a RT-PCR é específica para RSNV e pode detectar o vírus em tecido oriundo das raízes, do colo e de folhas com distorção. Comparada ao diagnóstico da doença através da observação de sintomas e de estruturas do vetor, a RT-PCR é uma ferramenta confiável para a diagnose do enrolamento do arroz.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Emprego de redes neurais artificiais supervisionadas e não supervisionadas no estudo de parâmetros reológicos de excipientes farmacêuticos sólidos

In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

Contribuição para o estudo do embarque de uma rede neural artificial em field programmable gate array (FPGA)

This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed