Reference values for lysosomal enzymes activities using dried blood spots samples - a Brazilian experience

Background: Lysosomal storage diseases (LSD) are inherited disorders caused by deficiency of lysosomal enzymes in which early diagnosis is essential to provide timely treatment. This study reports interval values for the activity of lysosomal enzymes that are deficient in Mucopolysaccharidosis type I, Fabry, Gaucher and Pompe disease, using dried blood spots on filter paper (DBS) samples in a Brazilian population.Results: Reference activity values were obtained from healthy volunteers samples for alpha-galactosidase A (4.57 +/- 1.37 umol/L/h), beta-glucosidase (3.06 +/- 0.99 umol/L/h), alpha-glucosidase (ratio: 13.19 +/- 4.26; % inhibition: 70.66 +/- 7.60), alpha-iduronidase (3.45 +/- 1.21 umol/L/h) and beta-galactosidase (14.09 +/- 4.36 umol/L/h).Conclusion: Reference values of five lysosomal enzymes were determined for a Brazilian population sample. However, as our results differ from other laboratories, it highlights the importance of establishing specific reference values for each center

The ρ(1S,2S)\rho(1S,2S), ψ(1S,2S)\psi(1S,2S), Υ(1S,2S)\Upsilon(1S,2S) and ψt(1S,2S)\psi_t(1S,2S) mesons in a double pole QCD Sum Rule

We use the method of double pole QCD sum rule which is basically a fit with two exponentials of the correlation function, where we can extract the masses and decay constants of mesons as a function of the Borel mass. We apply this method to study the mesons: $\rho(1S,2S)$, $\psi(1S,2S)$, $\Upsilon(1S,2S)$ and $\psi_t(1S,2S)$. We also present predictions for the toponiuns masses $\psi_t(1S,2S)$ of m(1S)=357 GeV and m(2S)=374 GeV.Comment: 14 pages, 11 figures in Braz J Phys (2016

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Structure guided prediction of Pyrazinamide resistance mutations in pncA

Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

Relationship between functional fitness, medication costs and mood in elderly people

Objective: to verify if functional fitness (FF) is associated with the annual cost of medication consumption and mood states (MSt) in elderly people. Methods: a cross-sectional study with 229 elderly people aged 65 years or more at Santa Casa de Misericórdia de Coimbra, Portugal. Seniors with physical and psychological limitations were excluded, as well as those using medication that limits performance on the tests. The Senior Fitness Test was used to evaluate FF, and the Profile of Mood States - Short Form to evaluate the MSt. The statistical analysis was based on Mancova, with adjustment for age, for comparison between men and women, and adjustment for sex, for comparison between cardiorespiratory fitness quintiles. The association between the variables under study was made with partial correlation, controlling for the effects of age, sex and body mass index. Results: an inverse correlation between cardiorespiratory fitness and the annual cost of medication consumption was found (p < 0.01). FF is also inversely associated with MSt (p < 0.05). Comparisons between cardiorespiratory fitness quintiles showed higher medication consumption costs in seniors with lower aerobic endurance, as well as higher deterioration in MSt (p < 0.01). Conclusion: elderly people with better FF and, specifically, better cardiorespiratory fitness present lower medication consumption costs and a more positive MSt

A prediction rule to stratify mortality risk of patients with pulmonary tuberculosis

Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age >= 50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.44.4), >= 1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin = 6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.This work was supported by Fundacao Amelia de Mello/Jose de Mello Saude and Sociedade Portuguesa de Pneumologia (SPP). This work was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). NSO is a FCT (Fundacao para a Ciencia e Tecnologia) investigator. MS is an Associate FCT Investigator. The fundershad no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Chewing analysis in subjects aged between 07 to 12 years with unilateral cross bite

PURPOSE: to analyze the function of chewing, related to the posterior unilateral crossbite in children aged between 07 to 12 years. METHODS: 10 samples of both genders with posterior unilateral crossbite, with no orthodontic treatment history. During the speech language pathology evaluation the examined items were: food cutting, side of the chewing, rhythm, lips position, food escape, jaw movement, exaggerated participation of the perioral muscles, food accumulation in the vestibule of the mouth, position and size of the alimentary cake. RESULTS: from the 10 evaluated samples, 80% demonstrated unilateral chewing of the same side of the posterior unilateral crossbite and 20% bilateral chewing. From the 08 analyzed samples, the results were: previous cut, without escape of food and rotatory movements 100%; slow rhythm 50% and fast rhythm 50%; closed lips 75%; exaggerated participation of perioral muscles 62,5%; without accumulation of food 87,5%; alimentary cake cente-red 62,5%; small cale size 62,5%. CONCLUSION: from the evaluated cases, it was observed that 80% confirmed the relation between unilateral chewing and unilateral posterior crossbite, corroborating the literature s reporting. In the chewing, no any alterations related to the posterior unilateral crossbite and unilateral chewing have been noted.OBJETIVO: analisar a função de mastigação relacionada à mordida cruzada posterior unilateral em crianças na faixa etária de sete a doze anos. MÉTODOS: dez indivíduos de ambos os sexos com mordida cruzada unilateral posterior sem intervenção ortodôntica. Na avaliação fonoaudiológica os itens considerados foram: corte do alimento, lado da mastigação, ritmo, postura labial, escape de alimentos, movimento de mandíbula, participação exagerada da musculatura perioral, acúmulo de alimento no vestíbulo da boca, posição e tamanho do bolo alimentar. RESULTADOS: dos dez indivíduos avaliados, 80% apresentaram mastigação unilateral do mesmo lado da mordida cruzada posterior unilateral e 20% mastigação bilateral. Dos oito indivíduos analisados com mastigação unilateral, os resultados encontrados foram: corte anterior, sem escape de alimentos e movimentos rotatórios 100%; ritmo lento 50% e rápido 50%; lábios fechados 75%; participação exagerada da musculatura perioral 62,5%; sem acúmulo de alimentos 87,5%; bolo alimentar centralizado 75%; tamanho do bolo pequeno 62,5%. CONCLUSÃO: dos casos avaliados, observou-se que 80% confirmam a relação entre mastigação unilateral e mordida cruzada posterior unilateral. Na mastigação, não foram evidenciadas quaisquer outras alterações que possam estar relacionadas à mordida cruzada posterior unilateral e mastigação unilateral.Prefeitura do Rio de JaneiroUniversidade do Estado do Rio de JaneiroCEFAC - Saúde e EducaçãoHospital Estadual Adão Pereira NunesUniversidade Federal de São Paulo (UNIFESP) Setor de Investigação em Doenças NeuromuscularesUniversidade Federal de São Paulo (UNIFESP)UNIFESP, Setor de Investigação em Doenças NeuromuscularesUNIFESPSciEL

Drivers of genetic diversity in secondary metabolic gene clusters within a fungal species

Drivers of genetic diversity in secondary metabolic gene clusters within a fungal speciesFilamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here, we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed 5 general types of variation in SM gene clusters: nonfunctional gene polymorphisms; gene gain and loss polymorphisms; whole cluster gain and loss polymorphisms; allelic polymorphisms, in which different alleles corresponded to distinct, nonhomologous clusters; and location polymorphisms, in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms, the detection of which requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and nonhomologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, and genomic deletion and insertion events as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic diversity operating within a fungal species shown here are sufficient to explain SM cluster macroevolutionary patterns.National Science Foundation (grant number DEB-1442113). Received by AR. U.S. National Library of Medicine training grant (grant number 2T15LM007450). Received by ALL. Conselho Nacional de Desenvolvimento Cientı´fico e 573 Tecnológico. Northern Portugal Regional Operational Programme (grant number NORTE-01- 0145-FEDER-000013). Received by FR. Fundação de Amparo à Pesquisa do 572 Estado de São Paulo. Received by GHG. National Institutes of Health (grant number R01 AI065728-01). Received by NPK. National Science Foundation (grant number IOS-1401682). Received by JHW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Combating mutations in genetic disease and drug resistance: understanding molecular mechanisms to guide drug design

INTRODUCTION: Mutations introduce diversity into genomes, leading to selective changes and driving evolution. These changes have contributed to the emergence of many of the current major health concerns of the 21st century, from the development of genetic diseases and cancers to the rise and spread of drug resistance. The experimental systematic testing of all mutations in a system of interest is impractical and not cost-effective, which has created interest in the development of computational tools to understand the molecular consequences of mutations to aid and guide rational experimentation. AREAS COVERED: Here, the authors discuss the recent development of computational methods to understand the effects of coding mutations to protein function and interactions, particularly in the context of the 3D structure of the protein. EXPERT OPINION: While significant progress has been made in terms of innovative tools to understand and quantify the different range of effects in which a mutation or a set of mutations can give rise to a phenotype, a great gap still exists when integrating these predictions and drawing causality conclusions linking variants. This often requires a detailed understanding of the system being perturbed. However, as part of the drug development process it can be used preemptively in a similar fashion to pharmacokinetics predictions, to guide development of therapeutics to help guide the design and analysis of clinical trials, patient treatment and public health policy strategies.This work was funded by the Jack Brockhoff Foundation (JBF 4186, 2016) and a Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) (MR/M026302/1). This research was supported by the Victorian Life Sciences Computation Initiative (VLSCI), an initiative of the Victorian Government, Australia, on its Facility hosted at the University of Melbourne (UOM0017). D.E.V.P. received support from the René Rachou Research Center (CPqRR/FIOCRUZ Minas), Brazil. DBA was supported by a C. J. Martin Research Fellowship from the National Health and Medical Research Council of Australia (APP1072476), and the Department of Biochemistry, University of Melbourne