Self-perception, complaints and vocal quality among undergraduate students enrolled in a Pedagogy course

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudo da Estrutura da Proteína SH do Vírus Sincicial Respiratório Humano: análise funcional da estrutura pentamérica por ferramentas de bioinformática

Pós-graduação em Biofísica Molecular - IBILCE

Eletroforese das proteínas séricas e urinárias de cães com erliquiose na fase aguda

Pós-graduação em Medicina Veterinária - FCAV

The relationship between obesity, low back pain, and lumbar disc degeneration when genetics and the environment are considered: a systematic review of twin studies

BACKGROUND CONTEXT: The relationships between obesity and low back pain (LBP) and lumbar disc degeneration (LDD) remain unclear. It is possible that familial factors, including genetics and early environment, affect these relationships.PURPOSE: To investigate the relationship between obesity-related measures (eg, weight, body mass index [BMI]) and LBP and LDD using twin studies, where the effect of genetics and early environment can be controlled.STUDY DESIGN: A systematic review with meta-analysis.METHODS: MEDLINE, CINAHL, Scopus, Web of Science, and EMBASE databases were searched from the earliest records to August 2014. All cross-sectional and longitudinal observational twin studies identified by the search strategy were considered for inclusion. Two investigators independently assessed the eligibility, conducted the quality assessment, and extracted the data. Metaanalyses (fixed or random effects, as appropriate) were used to pool studies'estimates of association.RESULTS: In total, 11 articles met the inclusion criteria. Five studies were included in the LBP analysis and seven in the LDD analysis. For the LBP analysis, pooling of the five studies showed that the risk of having LBP for individuals with the highest levels of BMI or weight was almost twice that of people with a lower BMI (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.6-2.0; I-2 = 0%). A dose-response relationship was also identified. When genetics and the effects of a shared early environment were adjusted for using a within-pair twin case-control analysis, pooling of three studies showed a reduced but statistically positive association between obesity and prevalence of LBP (OR 1.5; 95% CI 1.1-2.1; I-2 = 0%). However, the association was further diminished and not significant (OR 1.4; 95% CI 0.8-2.3; I-2 = 0%) when pooling included two studies on monozygotic twin pairs only. Seven studies met the inclusion criteria for LDD. When familial factors were not controlled for, body weight was positively associated with LDD in all five cross-sectional studies. Only two cross-sectional studies investigated the relationship between obesity-related measures and LDD accounting for familial factors, and the results were conflicting. One longitudinal study in LBP and three longitudinal studies in LDD found no increase in risk in obese individuals, whether or not familial factors were controlled for.CONCLUSIONS: Findings from this review suggest that genetics and early environment are possible mechanisms underlying the relationship between obesity and LBP; however, a direct causal link between these conditions appears to be weak. Further longitudinal studies using the twin design are needed to better understand the complex mechanisms underlying the associations between obesity, LBP, and LDD.

Identificação de genes candidatos à indução do florescimento em cana-de-açúcar em câmara de fotoperíodo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização funcional e estrutural das proteínas RUV-1 e RUV-2 do fungo Neurospora crassa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise de formas planas em imagens digitais

Given the widespread use of computers, the visual pattern recognition task has been automated in order to address the huge amount of available digital images. Many applications use image processing techniques as well as feature extraction and visual pattern recognition algorithms in order to identify people, to make the disease diagnosis process easier, to classify objects, etc. based on digital images. Among the features that can be extracted and analyzed from images is the shape of objects or regions. In some cases, shape is the unique feature that can be extracted with a relatively high accuracy from the image. In this work we present some of most important shape analysis methods and compare their performance when applied on three well-known shape image databases. Finally, we propose the development of a new shape descriptor based on the Hough Transform.

A novel system for large-scale gene expression analysis: bacterial colonies array

In the present work, we report the use of bacterial colonies to optimize macroarray technique. The devised system is significantly cheaper than other methods available to detect large-scale differential gene expression. Recombinant Escherichia coli clones containing plasmid-encoded copies of 4,608 individual expressed sequence tag (ESTs) were robotically spotted onto nylon membranes that were incubated for 6 and 12 h to allow the bacteria to grow and, consequently, amplify the cloned ESTs. The membranes were then hybridized with a beta-lactamase gene specific probe from the recombinant plasmid and, subsequently, phosphorimaged to quantify the microbial cells. Variance analysis demonstrated that the spot hybridization signal intensity was similar for 3,954 ESTs (85.8%) after 6 h of bacterial growth. Membranes spotted with bacteria colonies grown for 12 h had 4,017 ESTs (87.2%) with comparable signal intensity but the signal to noise ratio was fivefold higher. Taken together, the results of this study indicate that it is possible to investigate large-scale gene expression using macroarrays based on bacterial colonies grown for 6 h onto membranes.

Crystallization and preliminary X-ray diffraction analysis of XAC1151, a small heat-shock protein from Xanthomonas axonopodis pv. citri belonging to the alpha-crystallin family

The hspA gene (XAC1151) from Xanthomonas axonopodis pv. citri encodes a protein of 158 amino acids that belongs to the small heat-shock protein ( sHSP) family of proteins. These proteins function as molecular chaperones by preventing protein aggregation. The protein was crystallized using the sitting-drop vapour-diffusion method in the presence of ammonium phosphate. X-ray diffraction data were collected to 1.65 angstrom resolution using a synchrotron-radiation source. The crystal belongs to the rhombohedral space group R3, with unit-cell parameters a = b = 128.7, c = 55.3 angstrom. The crystal structure was solved by molecular-replacement methods. Structure refinement is in progress.

A comparison of mycolic acid analysis for nontuberculous mycobacteria identification by thin-layer chromatography and molecular methods

The development of fast, inexpensive, and reliable tests to identify nontuberculous mycobacteria (NTM) is needed. Studies have indicated that the conventional identification procedures, including biochemical assays, are imprecise. This study evaluated a proposed alternative identification method in which 83 NTM isolates, previously identified by conventional biochemical testing and in-house M. avium IS1245-PCR amplification, were submitted to the following tests: thin-layer chromatography (TLC) of mycolic acids and PCR-restriction enzyme analysis of hsp65 (PRA). High-performance liquid chromatography (HPLC) analysis of mycolic acids and Southern blot analysis for M. avium IS1245 were performed on the strains that evidenced discrepancies on either of the above tests. Sixty-eight out of 83 (82%) isolates were concordantly identified by the presence of IS1245 and PRA and by TLC mycolic acid analysis. Discrepant results were found between the phenotypic and molecular tests in 12/83 (14.4%) isolates. Most of these strains were isolated from non-sterile body sites and were most probably colonizing in the host tissue. While TLC patterns suggested the presence of polymycobacterial infection in 3/83 (3.6%) cultures, this was the case in only one HPLC-tested culture and in none of those tested by PRA. The results of this study indicated that, as a phenotypic identification procedure, TLC mycolic acid determination could be considered a relatively simple and cost-effective method for routine screening of NTM isolates in mycobacteriology laboratory practice with a potential for use in developing countries. Further positive evidence was that this method demonstrated general agreement on MAC and M. simiae identification, including in the mixed cultures that predominated in the isolates of the disseminated infections in the AIDS patients under study. In view of the fact that the same treatment regimen is recommended for infections caused by these two species, TLC mycolic acid analysis may be a useful identification tool wherever molecular methods are unaffordable.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.