Identification of COL6A1 as a differentially expressed gene in human astrocytomas

Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Identification of protein-coding and non-coding RNA expression profiles in CD34(+) and in stromal cells in refractory anemia with ringed sideroblasts

Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

Identification of Novel Immunoregulatory Molecules in Human Thymic Regulatory CD4(+)CD25(+) T Cells by Phage Display

Thymic CD4(+)CD25(+) cells play an important role in immune regulation and are continuously developed in the thymus as an independent lineage. How these cells are generated, what are their multiple pathways of suppressive activity and which are their specific markers are questions that remain unanswered. To identify molecules involved in the function and development of human CD4(+)CD25(+) T regulatory cells we targeted thymic CD4(+)CD25(+) cells by peptide phage display. A phage library containing random peptides was screened ex vivo for binding to human thymic CD4(+)CD25(+) T cells. After four rounds of selection on CD4(+)CD25(+) enriched populations of thymocytes, we sequenced several phage displayed peptides and selected one with identity to the Vitamin D Receptor (VDR). We confirmed the binding of the VDR phage to active Vitamin D in vitro, as well as the higher expression of VDR in CD4(+)CD25(+) cells. We suggest that differential expression of VDR on natural Tregs may be related to the relevance of Vitamin D in function and ontogeny of these cells.

The Essential Nucleolar Yeast Protein Nop8p Controls the Exosome Function during 60S Ribosomal Subunit Maturation

The yeast nucleolar protein Nop8p has previously been shown to interact with Nip7p and to be required for 60S ribosomal subunit formation. Although depletion of Nop8p in yeast cells leads to premature degradation of rRNAs, the biochemical mechanism responsible for this phenotype is still not known. In this work, we show that the Nop8p amino-terminal region mediates interaction with the 5.8S rRNA, while its carboxyl-terminal portion interacts with Nip7p and can partially complement the growth defect of the conditional mutant strain Dnop8/GAL:NOP8. Interestingly, Nop8p mediates association of Nip7p to pre-ribosomal particles. Nop8p also interacts with the exosome subunit Rrp6p and inhibits the complex activity in vitro, suggesting that the decrease in 60S ribosomal subunit levels detected upon depletion of Nop8p may result from degradation of pre-rRNAs by the exosome. These results strongly indicate that Nop8p may control the exosome function during pre-rRNA processing.

Diversity of free-living marine nematodes (Enoplida) from Baja California assessed by integrative taxonomy

We used morphological and molecular approaches to evaluate the diversity of free-living marine nematodes (order Enoplida) at four coastal sites in the Gulf of California and three on the Pacific coast of Baja California, Mexico. We identified 22 morphological species belonging to six families, of which Thoracostomopsidae and Oncholaimidae were the most diverse. The genus Mesacanthion (Thoracostomopsidae) was the most widespread and diverse. Five allopatric species, genetically and morphologically differentiated, were found in two localities in the Gulf of California (M. sp1 and M. sp2) and three in the Pacific coast (M. sp3, M. sp4 and M. sp5). Overall, we produced 19 and 20 sequences for the 18S and 28S genes, respectively. Neither gene displayed intraspecific polymorphisms, which allowed us to establish that some morphological variation was likely either ontogenetic or due to phenotypic plasticity. Although 18S and 28S phylogenies were topologically congruent (incongruence length difference test, P > 0.05), divergences between species were much higher in the 28S gene. Moreover, this gene possessed a stronger phylogenetic signal to resolve relationships involving Rhabdodemania and Bathylaimus. On the other hand, the close relationship of Pareurystomina (Enchilidiidae) with oncholaimids warrants further study. The 28S sequences (D2D3 domain) may be better suited for DNA barcoding of marine nematodes than those from the 18S rDNA, particularly for differentiating closely related or cryptic species. Finally, our results underline the relevance of adopting an integrative approach encompassing morphological and molecular analyses to improve the assessment of marine nematode diversity and advance their taxonomy.

The Influence of Different Land Uses on the Structure of Archaeal Communities in Amazonian Anthrosols Based on 16S rRNA and amoA Genes

Soil from the Amazonian region is usually regarded as unsuitable for agriculture because of its low organic matter content and low pH; however, this region also contains extremely rich soil, the Terra Preta Anthrosol. A diverse archaeal community usually inhabits acidic soils, such as those found in the Amazon. Therefore, we hypothesized that this community should be sensitive to changes in the environment. Here, the archaeal community composition of Terra Preta and adjacent soil was examined in four different sites in the Brazilian Amazon under different anthropic activities. The canonical correspondence analysis of terminal restriction fragment length polymorphisms has shown that the archaeal community structure was mostly influenced by soil attributes that differentiate the Terra Preta from the adjacent soil (i.e., pH, sulfur, and organic matter). Archaeal 16S rRNA gene clone libraries indicated that the two most abundant genera in both soils were Candidatus nitrosphaera and Canditatus nitrosocaldus. An ammonia monoxygenase gene (amoA) clone library analysis indicated that, within each site, there was no significant difference between the clone libraries of Terra Preta and adjacent soils. However, these clone libraries indicated there were significant differences between sites. Quantitative PCR has shown that Terra Preta soils subjected to agriculture displayed a higher number of amoA gene copy numbers than in adjacent soils. On the other hand, soils that were not subjected to agriculture did not display significant differences on amoA gene copy numbers between Terra Preta and adjacent soils. Taken together, our findings indicate that the overall archaeal community structure in these Amazonian soils is determined by the soil type and the current land use.

Involvement of Clostridium gasigenes and C. algidicarnis in `blown pack` spoilage of Brazilian vacuum-packed beef

The objectives of this study were to isolate psychrotrophic clostridia from Brazilian vacuum-packed beef cuts (spoiled or not) and to identify the isolates by using 16S rRNA gene sequencing. Anaerobic psychrotrophic microorganisms were also enumerated and samples were collected to verify the incidence of psychrotrophic clostridia in the abattoir environment. Vacuum-packed beef cuts (n = 8 grossly distended and n = 5 non-spoiled) and environmental samples were obtained from a beef packing plant located in the state of Sao Paulo, Brazil. Each sample was divided in three subsamples (exudate, beef surface and beef core) that were analyzed for vegetative forms, total spore-forming, and sulfide reducing spore-forming, both activated by alcohol and heat. Biochemical profiles of the isolates were obtained using API20A, with further identification using 16S rRNA gene sequencing. The growth temperature and the pH range were also assessed. Populations of psychrotrophic anaerobic vegetative microorganisms of up to 10(10) CFU/(g, mL or 100 cm(2)) were found in `blown pack` samples, while in non-spoiled samples populations of 10(5) CFU/(g, CFU/mL or CFU/100cm(2)) was found. Overall, a higher population of total spores and sulfide reducing spores activated by heat in spoiled samples was found. Clostridium gasigenes (n = 10) and C. algidicarnis (n = 2) were identified using 16S rRNA gene sequencing. Among the ten C. gasigenes isolates, six were from spoiled samples (C1, C2 and C9), two were isolated from non-spoiled samples (C4 and C5) and two were isolated from the hide and the abattoir corridor/beef cut conveyor belt. C. algidicarnis was recovered from spoiled beef packs (C2). Although some samples (C3, C7, C10 and C14) presented signs of `blown pack` spoilage, Clostridium was not recovered. C. algidicarnis (n = 1) and C. gasigenes (n = 9) isolates have shown a psychrotrophic behavior, grew in the range 6.2-8.2. This is the first report on the isolation of psychrotrophic Clostridium (C. gasigenes and C. algidicarnis) in Brazil. This study shows that psychrotrophic Clostridium may pose a risk for the stability of vacuum-packed beef produced in tropical countries during shelf-life and highlights the need of adopting control measures to reduce their incidence in abattoir and the occurrence of `blown pack` spoilage. (C) 2011 Elsevier B.V. All rights reserved.

Identification of the biodiesel source using an electronic nose

Biodiesel is an important new alternative fuel. The feedstock used and the process employed determines whether it fulfills the required specifications. In this work, an identification method is proposed using an electronic nose (e-nose). Four samples of biodiesel from different sources and one of petrodiesel were analyzed and well-recognized by the e-nose. Both pure biodiesel and B20 blends were studied. Furthermore, an innovative semiquantitative method is proposed on the basis of the smellprints correlated by a feed-forward artificial neural network. The results have demonstrated that the e-nose can be used to identify the biodiesel source and as a preliminary quantitative assay in place of expensive equipment.

Identification and Validation of Brazilian Chronic Pain Descriptors

Appropriate pain assessment is very important for managing chronic pain. Given the cultural differences in verbally expressing pain and in psychosocial problems, specific tools are needed. The goal of this study was to identify and validate Brazilian pain descriptors. A purposive sample of health professionals and chronic pain patients was recruited. Four studies were conducted using direct and indirect psychophysical methods: category estimation, magnitude estimation, and magnitude estimation and tine-length. Results showed the descriptors which best describe chronic pain in Brazilian culture and demonstrated that there is not a significant correlation between patients and health professionals and that the psychophysical scale of judgment of pain descriptors is valid, stable, and consistent. Results reinforced that the translations of word descriptors and research tools into another language may be inappropriate, owing to differences in perception and communication and the inadequacy of exact translations to reflect the intended meaning. Given the complexity of the chronic pain, personal suffering involved, and the need for accurate assessment of chronic pain using descriptors stemming from Brazilian culture and language, it is essential to investigate the most adequate words to describe chronic pain. Although it requires more refinement, the Brazilian chronic pain descriptors can be used further to develop a multidimensional pain assessment tool that is culturally sensitive. (C) 2009 by the American Society for Pain Management Nursing

Identification of nurses` competencies in primary health care through a Delphi study in southern Brazil

Objective: This investigation aimed to identify and analyze the general and specific competencies of nurses in the primary health care practice of Brazil. Design: The Delphi Technique was used as the method of study. Sample: 2 groups of participants were selected: One contained primary health care nurses (n=52) and the other specialists (n=57), including public health nurses and public or community health faculty. Measurements: 3 questionnaires were developed for the study. The first asked participants to indicate general and specific competencies, which were compiled into a list for each group. A Likert scale of 1-5 was added to these 2 lists in the second and third questionnaires. A consensus criterion of 75% for score 4 or 5 was adopted. Results: In the nurses` group, 17 general and 8 specific competencies reached the consensus criterion; 19 general and 9 specific competencies reached the criterion in the specialists` group. These competencies were classified into 10 domains: professional values, communication, teamwork, management, community-oriented, health promotion, problem solving, health care, and education and basic public health sciences. Conclusions: These competencies reflect Brazilian health policy and constitute a reference for health professional practice and education.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Harmonic identification using parallel neural networks in single-phase systems

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.