Extending the reservoir of bla IMP-5: the emerging pathogen Acinetobacter bereziniae

Acinetobacter bereziniae clinical relevance is starting to be recognized; however, very few descriptions of its carbapenem resistance currently exist. Here we characterize two carbapenem-resistant A. bereziniae isolates. Materials & methods: Isolates were obtained from environmental and clinical samples. Carbapenemases were searched by phenotypic, biochemical and PCR assays. Clonality was studied by ApaI-PFGE and genetic location for carbapenemase genes were assessed by I-CeuI and S1 hybridizations. Results: Isolates were not clonally related but both produced the exclusively Portuguese IMP-5, with the clinical isolate also producing an OXA-58. The carbapenemase genes were plasmid located. Conclusion: Our results emphasize the role of non-baumannii Acinetobacter species as important reservoirs of clinically relevant resistance genes that could also contribute to their emergence as nosocomial pathogens

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Extracting kinetic information from literature with KineticRE

To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

Polyphasic identification of a Rhizopus species and a putative novel Gongronella which both degrade the fungicide metalaxyl

Apresentação efetuada na MicroBiotec’15

Towards the design and implementation of aspect-oriented programming for spreadsheets

A spreadsheet usually starts as a simple and singleuser software artifact, but, as frequent as in other software systems, quickly evolves into a complex system developed by many actors. Often, different users work on different aspects of the same spreadsheet: while a secretary may be only involved in adding plain data to the spreadsheet, an accountant may define new business rules, while an engineer may need to adapt the spreadsheet content so it can be used by other software systems.Unfortunately,spreadsheetsystemsdonotoffermodular mechanisms, and as a consequence, some of the previous tasks may be defined by adding intrusive “code” to the spreadsheet. In this paper we go through the design and implementation of an aspect-oriented language for spreadsheets so that users can work on different aspects of a spreadsheet in a modular way. For example, aspects can be defined in order to introduce new business rules to an existing spreadsheet, or to manipulate the spreadsheet data to be ported to another system. Aspects are defined as aspect-oriented program specifications that are dynamically woven into the underlying spreadsheet by an aspect weaver. In this aspect-oriented style of spreadsheet development, differentusers develop,orreuse,aspects withoutaddingintrusive code to the original spreadsheet. Such code is added/executed by the spreadsheet weaving mechanism proposed in this paper.

BiYacc: Roll your parser and reflective printer into one

In: A. Cunha, E. Kindler (eds.): Proceedings of the Fourth International Workshop on Bidirectional Transformations (Bx 2015), L’Aquila, Italy, July 24, 2015, published at http://ceur-ws.org

Superhydrophobic surfaces as a tool for the fabrication of hierarchical spherical polymeric carriers

Hierarchical polymeric carriers with high encapsulation efficiencies are fabricated via a biocompatible strategy developed using superhydrophobic (SH) surfaces. The carries are obtained by the incorporation of cell/BSA-loaded dextran-methacrylate (DEXT-MA) microparticles into alginate (ALG) macroscopic beads. Engineered devices like these are expected to boost the development of innovative and customizable systems for biomedical and biotechnological purposes.

Fetal behavior and heart rate in twin pregnancy: a review

Fetal movements and fetal heart rate (FHR) are well-established markers of fetal well-being and maturation of the fetal central nervous system. The purpose of this paper is to review and discuss the available knowledge on fetal movements and heart rate patterns in twin pregnancies. There is some evidence for an association or similarity in fetal movement incidences or FHR patterns between both members of twin pairs. However, the temporal occurrence of these patterns seems to be for the most part asynchronous, especially when stricter criteria are used to define synchrony. The available data suggest that fetal behavior is largely independent of sex combination, fetal position, and presentation. Conversely, chorionicity appears to have some influence on fetal behavior, mainly before 30 weeks of gestation. There is preliminary evidence for the continuity of inter-individual differences in fetal activity and FHR patterns over pregnancy. Comparisons between studies are limited by large methodological differences and absence of uniform concepts and definitions. Future studies with high methodological quality are needed to provide a more comprehensive knowledge of normal fetal behavior in twin pregnancy.