An integrated approach of software development and test processes to distributed teams

The Distributed Software Development (DSD) is a development strategy that meets the globalization needs concerned with the increase productivity and cost reduction. However, the temporal distance, geographical dispersion and the socio-cultural differences, increased some challenges and, especially, added new requirements related with the communication, coordination and control of projects. Among these new demands there is the necessity of a software process that provides adequate support to the distributed software development. This paper presents an integrated approach of software development and test that considers distributed teams peculiarities. The approach purpose is to offer support to DSD, providing a better project visibility, improving the communication between the development and test teams, minimizing the ambiguity and difficulty to understand the artifacts and activities. This integrated approach was conceived based on four pillars: (i) to identify the DSD peculiarities concerned with development and test processes, (ii) to define the necessary elements to compose the integrated approach of development and test to support the distributed teams, (iii) to describe and specify the workflows, artifacts, and roles of the approach, and (iv) to represent appropriately the approach to enable the effective communication and understanding of it.

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

Expression of non-TLR pattern recognition receptors in the spleen of BALB/c mice infected with Plasmodium yoelii and Plasmodium chabaudi chabaudi AS

The spleen plays a crucial role in the development of immunity to malaria, but the role of pattern recognition receptors (PRRs) in splenic effector cells during malaria infection is poorly understood. In the present study, we analysed the expression of selected PRRs in splenic effector cells from BALB/c mice infected with the lethal and non-lethal Plasmodium yoelii strains 17XL and 17X, respectively, and the non-lethal Plasmodium chabaudi chabaudi AS strain. The results of these experiments showed fewer significant changes in the expression of PRRs in AS-infected mice than in 17X and 17XL-infected mice. Mannose receptor C type 2 (MRC2) expression increased with parasitemia, whereas Toll-like receptors and sialoadhesin (Sn) decreased in mice infected with P. chabaudi AS. In contrast, MRC type 1 (MRC1), MRC2 and EGF-like module containing mucin-like hormone receptor-like sequence 1 (F4/80) expression decreased with parasitemia in mice infected with 17X, whereas MRC1 an MRC2 increased and F4/80 decreased in mice infected with 17XL. Furthermore, macrophage receptor with collagenous structure and CD68 declined rapidly after initial parasitemia. SIGNR1 and Sn expression demonstrated minor variations in the spleens of mice infected with either strain. Notably, macrophage scavenger receptor (Msr1) and dendritic cell-associated C-type lectin 2 expression increased at both the transcript and protein levels in 17XL-infected mice with 50% parasitemia. Furthermore, the increased lethality of 17X infection in Msr1 -/- mice demonstrated a protective role for Msr1. Our results suggest a dual role for these receptors in parasite clearance and protection in 17X infection and lethality in 17XL infection.

Cross-reactivity of antipneumococcal surface protein C (PspC) antibodies with different strains and evaluation of inhibition of human complement factor H and secretory IgA binding via PspC

Pneumococcal surface protein C (PspC) is an important candidate for a cost-effective vaccine with broad coverage against pneumococcal diseases. Previous studies have shown that Streptococcus pneumoniae is able to bind to both human factor H (FH), an inhibitor of complement alternative pathway, and human secretory IgA (sIgA) via PspC. PspC was classified into 11 groups based on variations of the gene. In this work, we used three PspC fragments from different groups (PspC3, PspC5, and PspC8) to immunize mice for the production of antibodies. Immunization with PspC3 induced antibodies that recognized the majority of the clinical isolates as analyzed by Western blotting of whole-cell extracts and flow cytometry of intact bacteria, while anti-PspC5 antibodies showed cross-reactivity with the paralogue pneumococcal surface protein A (PspA), and anti-PspC8 antibodies reacted only with the PspC8-expressing strain. Most of the isolates tested showed strong binding to FH and weaker interaction with sIgA. Preincubation with anti-PspC3 and anti-PspC5 IgG led to some inhibition of binding of FH, and preincubation with anti-PspC3 partially inhibited sIgA binding in Western blotting. The analysis of intact bacteria through flow cytometry showed only a small decrease in FH binding after incubation of strain D39 with anti-PspC3 IgG, and one clinical isolate showed inhibition of sIgA binding by anti-PspC3 IgG. We conclude that although anti-PspC3 antibodies were able to recognize PspC variants from the majority of the strains tested, partial inhibition of FH and sIgA binding through anti-PspC3 antibodies in vitro could be observed for only a restricted number of isolates.

The Interactive Effect of GHR-Exon 3 and -202 A/C IGFBP3 Polymorphisms on rhGH Responsiveness and Treatment Outcomes in Patients with Turner Syndrome

Context: There is great interindividual variability in the response to recombinant human (rh) GH therapy in patients with Turner syndrome (TS). Ascertaining genetic factors can improve the accuracy of growth response predictions. Objective: The objective of the study was to assess the individual and combined influence of GHR-exon 3 and -202 A/C IGFBP3 polymorphisms on the short-and long-term outcomes of rhGH therapy in patients with TS. Design and Patients: GHR-exon 3 and -202 A/C IGFBP3 genotyping (rs2854744) was correlated with height data of 112 patients with TS who remained prepubertal during the first year of rhGH therapy and 65 patients who reached adult height after 5 +/- 2.5 yr of rhGH treatment. Main Outcome Measures: First-year growth velocity and adult height were measured. Results: Patients carrying at least one GHR-d3 or -202 A-IGFBP3 allele presented higher mean first-year growth velocity and achieved taller adult heights than those homozygous for GHR-fl or -202 C-IGFBP3 alleles, respectively. The combined analysis of GHR-exon 3 and -202 A/C IGFBP3 genotypes showed a clear nonadditive epistatic influence on adult height of patients with TS treated with rhGH (GHR-exon 3 alone, R-2 = 0.27; -202 A/C IGFBP3, R-2 = 0.24; the combined genotypes, R-2 = 0.37 at multiple linear regression). Together with clinical factors, these genotypes accounted for 61% of the variability in adult height of patients with TS after rhGH therapy. Conclusion: Homozygosity for the GHR-exon3 full-length allele and/or the -202C-IGFBP3 allele are associated with less favorable short-and long-term growth outcomes after rhGH treatment in patients with TS. (J Clin Endocrinol Metab 97: E671-E677, 2012)

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado ��� the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different ���omics��� technologies with patient���s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Soil carbon balance in a tropical grassland: Estimation of soil respiration and its partitioning using a semi-empirical model

In savannah and tropical grasslands, which account for 60% of grasslands worldwide, a large share of ecosystem carbon is located below ground due to high root:shoot ratios. Temporal variations in soil CO2 efflux (R-S) were investigated in a grassland of coastal Congo over two years. The objectives were (1) to identify the main factors controlling seasonal variations in R-S and (2) to develop a semi-empirical model describing R-S and including a heterotrophic component (R-H) and an autotrophic component (R-A). Plant above-ground activity was found to exert strong control over soil respiration since 71% of seasonal R-S variability was explained by the quantity of photosynthetically active radiation absorbed (APAR) by the grass canopy. We tested an additive model including a parameter enabling R-S partitioning into R-A and R-H. Assumptions underlying this model were that R-A mainly depended on the amount of photosynthates allocated below ground and that microbial and root activity was mostly controlled by soil temperature and soil moisture. The model provided a reasonably good prediction of seasonal variations in R-S (R-2 = 0.85) which varied between 5.4 mu mol m(-2) s(-1) in the wet season and 0.9 mu mol m(-2) s(-1) at the end of the dry season. The model was subsequently used to obtain annual estimates of R-S, R-A and R-H. In accordance with results reported for other tropical grasslands, we estimated that R-H accounted for 44% of R-S, which represented a flux similar to the amount of carbon brought annually to the soil from below-ground litter production. Overall, this study opens up prospects for simulating the carbon budget of tropical grasslands on a large scale using remotely sensed data. (C) 2012 Elsevier B.V. All rights reserved.