Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

SAGE analysis highlights the putative role of underexpression of ribosomal proteins in GH-secreting pituitary adenomas

Background: Although the molecular pathogenesis of pituitary adenomas has been assessed by several different techniques, it still remains partially unclear. Ribosomal proteins (RPs) have been recently related to human tumorigenesis, but they have not yet been evaluated in pituitary tumorigenesis. Objective: The aim of this study was to introduce serial analysis of gene expression (SAGE), a high-throughput method, in pituitary research in order to compare differential gene expression. Methods: Two SAGE cDNA libraries were constructed, one using a pool of mRNA obtained from five GH-secreting pituitary tumors and another from three normal pituitaries. Genes differentially expressed between the libraries were further validated by real-time PCR in 22 GH-secreting pituitary tumors and in 15 normal pituitaries. Results: Computer-generated genomic analysis tools identified 13 722 and 14 993 exclusive genes in normal and adenoma libraries respectively. Both shared 6497 genes, 2188 were underexpressed and 4309 overexpressed in tumoral library. In adenoma library, 33 genes encoding RPs were underexpressed. Among these, RPSA, RPS3, RPS14, and RPS29 were validated by real-time PCR. Conclusion: We report the first SAGE library from normal pituitary tissue and GH-secreting pituitary tumor, which provide quantitative assessment of cellular transcriptome. We also validated some downregulated genes encoding RPs. Altogether, the present data suggest that the underexpression of the studied RP genes possibly collaborates directly or indirectly with other genes to modify cell cycle arrest, DNA repair, and apoptosis, leading to an environment that might have a putative role in the tumorigenesis, introducing new perspectives for further studies on molecular genesis of somatotrophinomas.

Decreasing the number of false positives in sequence classification

Abstract Background A large number of probabilistic models used in sequence analysis assign non-zero probability values to most input sequences. To decide when a given probability is sufficient the most common way is bayesian binary classification, where the probability of the model characterizing the sequence family of interest is compared to that of an alternative probability model. We can use as alternative model a null model. This is the scoring technique used by sequence analysis tools such as HMMER, SAM and INFERNAL. The most prevalent null models are position-independent residue distributions that include: the uniform distribution, genomic distribution, family-specific distribution and the target sequence distribution. This paper presents a study to evaluate the impact of the choice of a null model in the final result of classifications. In particular, we are interested in minimizing the number of false predictions in a classification. This is a crucial issue to reduce costs of biological validation. Results For all the tests, the target null model presented the lowest number of false positives, when using random sequences as a test. The study was performed in DNA sequences using GC content as the measure of content bias, but the results should be valid also for protein sequences. To broaden the application of the results, the study was performed using randomly generated sequences. Previous studies were performed on aminoacid sequences, using only one probabilistic model (HMM) and on a specific benchmark, and lack more general conclusions about the performance of null models. Finally, a benchmark test with P. falciparum confirmed these results. Conclusions Of the evaluated models the best suited for classification are the uniform model and the target model. However, the use of the uniform model presents a GC bias that can cause more false positives for candidate sequences with extreme compositional bias, a characteristic not described in previous studies. In these cases the target model is more dependable for biological validation due to its higher specificity.

Bearded capuchin monkeys` and a human`s efficiency at cracking palm nuts with stone tools: field experiments

Wild bearded capuchins, Cebus libidinosus, in Fazenda Boa Vista, Brazil crack tough palm nuts using hammer stones. We analysed the contribution of intrinsic factors (body weight, behaviour), size of the nuts and the anvil surface (flat or pit) to the efficiency of cracking. We provided capuchins with local palm nuts and a single hammer stone at an anvil. From video we scored the capuchins` position and actions with the nut prior to each strike, and outcomes of each strike. The most efficient capuchin opened 15 nuts per 100 strikes (6.6 strikes per nut). The least efficient capuchin that succeeded in opening a nut opened 1.32 nuts per 100 strikes (more than 75 strikes per nut). Body weight and diameter of the nut best predicted whether a capuchin would crack a nut on a given strike. All the capuchins consistently placed nuts into pits. To provide an independent analysis of the effect of placing the nut into a pit, we filmed an adult human cracking nuts on the same anvil using the same stone. The human displaced the nut on proportionally fewer strikes when he placed it into a pit rather than on a flat surface. Thus the capuchins placed the nut in a more effective location on the anvil to crack it. Nut cracking as practised by bearded capuchins is a striking example of a plastic behaviour where costs and benefits vary enormously across individuals, and where efficiency requires years to attain. (C) 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Analysis of energy dissipation in stirred suspension polymerisation reactors using computational fluid dynamics

This work evaluates the spatial distribution of normalised rates of droplet breakage and droplet coalescence in liquidliquid dispersions maintained in agitated tanks at operation conditions normally used to perform suspension polymerisation reactions. Particularly, simulations are performed with multiphase computational fluid dynamics (CFD) models to represent the flow field in liquidliquid styrene suspension polymerisation reactors for the first time. CFD tools are used first to compute the spatial distribution of the turbulent energy dissipation rates (e) inside the reaction vessel; afterwards, normalised rates of droplet breakage and particle coalescence are computed as functions of e. Surprisingly, multiphase simulations showed that the rates of energy dissipation can be very high near the free vortex surfaces, which has been completely neglected in previous works. The obtained results indicate the existence of extremely large energy dissipation gradients inside the vessel, so that particle breakage occurs primarily in very small regions that surround the impeller and the free vortex surface, while particle coalescence takes place in the liquid bulk. As a consequence, particle breakage should be regarded as an independent source term or a boundary phenomenon. Based on the obtained results, it can be very difficult to justify the use of isotropic assumptions to formulate particle population balances in similar systems, even when multiple compartment models are used to describe the fluid dynamic behaviour of the agitated vessel. (C) 2011 Canadian Society for Chemical Engineering

Bioelectrical Impedance Analysis and Skinfold Thickness Sum in Assessing Body Fat Mass of Renal Dialysis Patients

Objective: In chronic renal failure patients under hemodialysis (HD) treatment, the availability of simple, safe, and effective tools to assess body composition enables evaluation of body composition accurately, in spite of changes in body fluids that occur in dialysis therapy, thus contributing to planning and monitoring of nutritional treatment. We evaluated the performance of bioelectrical impedance analysis (BIA) and the skinfold thickness sum (SKF) to assess fat mass (FM) in chronic renal failure patients before (BHD) and after (AHD) HD, using air displacement plethysmography (ADP) as the standard method. Design: This single-center cross-sectional trial involved comparing the FM of 60 HD patients estimated BHD and AHD by BIA (multifrequential; 29 women, 31 men) and by SKF with those estimated by the reference method, ADP. Body fat-free mass (FFM) was also obtained by subtracting the total body fat from the individual total weight. Results: Mean estimated FM (kg [%]) observed by ADP BHD was 17.95 +/- 0.99 kg (30.11% +/- 1.30%), with a 95% confidence interval (CI) of 16.00 to 19.90 (27.56 to 32.66); mean estimated FM observed AHD was 17.92 +/- 1.11 kg (30.04% +/- 1.40%), with a 95% CI of 15.74 to 20.10 (27.28 to 32.79). Neither study period showed a difference in FM and FFM (for both kg and %) estimates by the SKF method when compared with ADP; however, the BIA underestimated the FM and overestimated the FFM (for both kg and %) when compared with ADP. Conclusion: The SKF, but not the BIA, method showed results similar to ADP and can be considered adequate for FM evaluation in HD patients. (C) 2012 by the National Kidney Foundation, Inc. All rights reserved.

Genome-Wide Analysis in Brazilian Xavante Indians Reveals Low Degree of Admixture

Characterization of population genetic variation and structure can be used as tools for research in human genetics and population isolates are of great interest. The aim of the present study was to characterize the genetic structure of Xavante Indians and compare it with other populations. The Xavante, an indigenous population living in Brazilian Central Plateau, is one of the largest native groups in Brazil. A subset of 53 unrelated subjects was selected from the initial sample of 300 Xavante Indians. Using 86,197 markers, Xavante were compared with all populations of HapMap Phase III and HGDP-CEPH projects and with a Southeast Brazilian population sample to establish its population structure. Principal Components Analysis showed that the Xavante Indians are concentrated in the Amerindian axis near other populations of known Amerindian ancestry such as Karitiana, Pima, Surui and Maya and a low degree of genetic admixture was observed. This is consistent with the historical records of bottlenecks experience and cultural isolation. By calculating pair-wise F-st statistics we characterized the genetic differentiation between Xavante Indians and representative populations of the HapMap and from HGDP-CEPH project. We found that the genetic differentiation between Xavante Indians and populations of Ameridian, Asian, European, and African ancestry increased progressively. Our results indicate that the Xavante is a population that remained genetically isolated over the past decades and can offer advantages for genome-wide mapping studies of inherited disorders.

Proteomic analysis of Porphyromonas gingivalis exposed to nicotine and cotinine

Cogo K, de Andrade A, Labate CA, Bergamaschi CC, Berto LA, Franco GCN, Goncalves RB, Groppo FC. Proteomic analysis of Porphyromonas gingivalis exposed to nicotine and cotinine. J Periodont Res 2012; 47: 766775. (c) 2012 John Wiley & Sons A/S Background and Objective: Smokers are more predisposed than nonsmokers to infection with Porphyromonas gingivalis, one of the most important pathogens involved in the onset and development of periodontitis. It has also been observed that tobacco, and tobacco derivatives such as nicotine and cotinine, can induce modifications to P. gingivalis virulence. However, the effect of the major compounds derived from cigarettes on expression of protein by P.gingivalis is poorly understood. Therefore, this study aimed to evaluate and compare the effects of nicotine and cotinine on the P.gingivalis proteomic profile. Material and Methods: Total proteins of P gingivalis exposed to nicotine and cotinine were extracted and separated by two-dimensional electrophoresis. Proteins differentially expressed were successfully identified through liquid chromatography-mass spectrometry and primary sequence databases using MASCOT search engine, and gene ontology was carried out using DAVID tools. Results: Of the approximately 410 protein spots that were reproducibly detected on each gel, 23 were differentially expressed in at least one of the treatments. A particular increase was seen in proteins involved in metabolism, virulence and acquisition of peptides, protein synthesis and folding, transcription and oxidative stress. Few proteins showed significant decreases in expression; those that did are involved in cell envelope biosynthesis and proteolysis and also in metabolism. Conclusion: Our results characterized the changes in the proteome of P.gingivalis following exposure to nicotine and cotinine, suggesting that these substances may modulate, with minor changes, protein expression. The present study is, in part, a step toward understanding the potential smokepathogen interaction that may occur in smokers with periodontitis.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

MicroRNAs miR-146-5p and let-7f as prognostic tools for aggressive papillary thyroid carcinoma: a case report

Papillary thyroid cancer (PTC) is the most incident histotype of thyroid cancer. A certain fraction of PTC cases (5%) are irresponsive to conventional treatment, and refractory to radioiodine therapy. The current prognostic factors for aggressiveness are mainly based on tumor size, the presence of lymph node metastasis, extrathyroidal invasion and, more recently, the presence of the BRAFT(1799A) mutation. MicroRNAs (miRNAs) have been described as promising molecular markers for cancer as their deregulation is observed in a wide range of tumors. Recent studies indicate that the over-expression of miR-146b-5p is associated with aggressiveness and BRAFT(1799A) mutation. Furthermore, down-regulation of let-7f is observed in several types of tumors, including PTC. In this study, we evaluated the miR146b-5p and let-7f status in a young male patient with aggressive, BRAFT(1799A)-positive papillary thyroid carcinoma, with extensive lymph node metastases and short-time recurrence. The analysis of miR-146b-5p and let-7f expression revealed a distinct pattern from a cohort of PTC patients, suggesting caution in evaluating miRNA expression data as molecular markers of PTC diagnosis and prognosis. Arq Bras Endocrinol Metab. 2012;56(8):552-7

Metabolic oligosaccharide engineering of Plasmodium falciparum intraerythrocytic stages allows direct glycolipid analysis by mass spectrometry

A recent addition to the arsenal of tools for glycome analysis is the use of metabolic labels that allow covalent tagging of glycans with imaging probes. In this work we show that N-azidoglucosamine was successfully incorporated into glycolipidic structures of Plasmodium falciparum intraerythrocytic stages. The ability to tag glycoconjugates selectively with a fluorescent reporter group permits TLC detection of the glycolipids providing a new method to quantify dynamic changes in the glycosylation pattern and facilitating direct mass spectrometry analyses. Presence of glycosylphosphatidylinositol and glycosphingolipid structures was determined in the different extracts. Furthermore, the fluorescent tag was used as internal matrix for the MALDI experiment making even easier the analysis. (C) 2012 Elsevier B.V. All rights reserved.

VIBRATIONAL ANALYSIS OF COORDINATION COMPOUNDS OF NICKEL (II): AN APPROACH TO THE TEACHING OF POINT GROUPS

VIBRATIONAL ANALYSIS OF COORDINATION COMPOUNDS OF NICKEL (II): AN APPROACH TO THE TEACHING OF POINT GROUPS. This paper presents an IR and Raman experiment executed during the teaching of the course "Chemical Bonds" for undergraduated students of Science and Technology and Chemistry at the Federal University of ABC, in order to facilitate and encourage the teaching and learning of group theory. Some key aspects of this theory are also outlined. We believe that student learning was more significant with the introduction of this experiment, because there was an increase in the discussions level and in the performance during evaluations. This work also proposes a multidisciplinary approach to include the use of quantum chemistry tools.

Effects of an adapted physical activity program on the physical condition of elderly women: an analysis of efficiency

Background: Specific research tools and designs can assist in identifying the efficiency of physical activity in elderly women. Objectives: To identify the effects of physical activity on the physical condition of older women. Method: A one-year-long physical activity program (123 sessions) was implemented for women aged 60 years or older. Four physical assessments were conducted, in which weight, height, BMI, blood pressure, heart rate, absences, grip strength, flexibility, VO2max, and static and dynamic balance were assessed. The statistical analyses included a repeated measures analysis, both inferential (analysis of variance - ANOVA) and effect size (Cohen's d coefficient), as well as identification of the participants' efficiency (Data Envelopment Analysis - DEA). Results: Despite the observation of differences that depended on the analysis used, the results were successful in the sense that they showed that physical activity adapted to older women can effectively change the decline in physical ability associated with aging, depending on the purpose of the study. The 60-65 yrs group was the most capable of converting physical activity into health benefits in both the short and long term. The >65 yrs group took less advantage of physical activity. Conclusions: Adherence to the program and actual time spent on each type of exercise are the factors that determine which population can benefit from physical activity programs. The DEA allows the assessment of the results related to time spent on physical activity in terms of health concerns. Article registered in Clinicaltrials.gov under number NCT01558401.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Multidimensional Projections for Visual Analysis of Social Networks

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in attribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.