Sporothrix schenckii COMPLEX: SUSCEPTIBILITIES TO COMBINED ANTIFUNGAL AGENTS AND CHARACTERIZATION OF ENZYMATIC PROFILES

SUMMARY Sporothrix schenckiiwas reclassified as a complex encompassing six cryptic species, which calls for the reassessment of clinical and epidemiological data of these new species. We evaluated the susceptibility of Sporothrix albicans (n = 1) , S. brasiliensis (n = 6) , S. globosa (n = 1), S. mexicana(n = 1) and S. schenckii(n = 36) to terbinafine (TRB) alone and in combination with itraconazole (ITZ), ketoconazole (KTZ), and voriconazole (VRZ) by a checkerboard microdilution method and determined the enzymatic profile of these species with the API-ZYM kit. Most interactions were additive (27.5%, 32.5% and 5%) or indifferent (70%, 50% and 52.5%) for TRB+KTZ, TRB+ITZ and TRB+VRZ, respectively. Antagonisms were observed in 42.5% of isolates for the TRB+VRZ combination. Based on enzymatic profiling, the Sporothrix schenckii strains were categorized into 14 biotypes. Leucine arylamidase (LA) activity was observed only for S. albicans and S. mexicana. The species S. globosaand S. mexicanawere the only species without β-glucosidase (GS) activity. Our results may contribute to a better understanding of virulence and resistance among species of the genus Sporothrixin further studies.

Interaction paradigms versus age-related user profiles: an evaluation on content selection

Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, despite the recent boom of different natural interaction paradigms, it hasn't been systematically evaluated how these interfaces influence a user's performance or whether each interface could be more or less appropriate when it comes to: 1) different age groups; and 2) different basic operations, as data selection, insertion or manipulation. This work presents the first step of an exploratory evaluation about whether or not the users' performance is indeed influenced by the different interfaces. The key point is to understand how different interaction paradigms affect specific target-audiences (children, adults and older adults) when dealing with a selection task. 60 participants took part in this study to assess how different interfaces may influence the interaction of specific groups of users with regard to their age. Four input modalities were used to perform a selection task and the methodology was based on usability testing (speed, accuracy and user preference). The study suggests a statistically significant difference between mean selection times for each group of users, and also raises new issues regarding the “old” mouse input versus the “new” input modalities.

Design and optimization of an extrusion die for the production of wood–plastic composite profiles

In this work, the optimization of an extrusion die designed for the production of a wood–plastic composite (WPC) decking profile is investigated. The optimization was performed with the help of numerical tools, more precisely, by solving the continuity and momentum conservation equations that govern such flow, and aiming to balance properly the flow distribution at the extrusion die flow channel outlet. To capture the rheological behavior of the material, we used a Bird-Carreau model with parameters obtained from a fit to the (shear viscosity versus shearrate) experimental data, collected from rheological tests. To yield a balanced output flow, several numerical runs were performed by adjusting the flow restriction at different regions of the flow-channel parallel zone crosssection. The simulations were compared with the experimental results and an excellent qualitative agreement was obtained, allowing, in this way, to attain a good balancing of the output flow and emphasizing the advantages of using numerical tools to aid the design of profile extrusion dies.

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.

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275

Human capital in growth regressions: how much difference does data quality make? An update and further results

We construct estimates of educational attainment for a sample of OECD countries using previously unexploited sources. We follow a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. We then construct indicators of the information content of our series and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that, after correcting for measurement error bias, the value of this parameter is well above 0.50.

The Technological Specialization of Countries: An Analysis of Patent Data

New methods of analysis of patent statistics allow assessing country profiles of technological specialization for the period 1990-2006. We witness a modest decrease in levels of specialization, which we show to be negatively influenced by country size and degree of internationalization of inventive activities.

Community Profiles Tool

The Community Profiles Tool can be used to develop local health and wellbeing profiles from over 200 health-related indicators compiled from a range of data sources. Users can create tables, maps and charts of health-related indicators, and integrate this with key public health documents from the Health Well website such as relevant interventions, policies, and evidence related to each indicator.

Hepatitis B and C in the hemodialysis unit of Tocantins, Brazil: serological and molecular profiles

A survey was conducted in the hemodialysis population of the state of Tocantins, Brazil, aiming to assess the prevalence of hepatitis B virus (HBV) and hepatitis C virus (HCV) infections, to analyze associated risk factors, and also to investigate these viruses genotypes distribution. During January and March 2001, all patients (n = 100) were interviewed at the unique dialysis unit in Tocantins. Blood samples were collected and serum samples were screened for HBV serological markers. Hepatitis B surface antigen positive samples were tested for HBV DNA. All samples were also tested for anti-HCV antibodies and HCV RNA. An overall prevalence of 45% was found for HBV infection (4% were HBsAg/anti-HBc positive, 2% were anti-HBc only and 39% had anti-HBc/anti-HBs markers). Concerning HCV infection, anti-HCV and HCV RNA were detected in 13% and 14% of the subjects, respectively. Three patients were HCV RNA positive and anti-HCV negative, resulting in an overall HCV prevalence of 16%. Univariate analysis of risk factors showed that only shift and length of time on hemodialysis were associated with HBV and HCV positivity, respectively. Among the four HBsAg-positive samples, HBV DNA was detected in three of them, which were identified as genotype A by restriction fragment length polymorphism (RFLP) analysis. All 14 HCV RNA-positive samples were genotyped by INNO-LiPA. Genotypes 1a and 3a were found in 85% and 15%, respectively. The present data show low HBsAg and HCV prevalence rates. The risk factors associated with HBV and HCV positivity suggest that nosocomial transmission may influence in spreading these viruses in the dialysis unit studied.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Characterization of Aspergillus species based on fatty acid profiles

Cellular fatty acid (FA) composition was utilized as a taxonomic tool to discriminate between different Aspergillus species. Several of the tested species had the same FA composition and different relative FA concentrations. The most important FAs were palmitic acid (C16:0), estearic acid (C18:0), oleic acid (C18:1) and linoleic acid (C18:2), which represented 95% of Aspergillus FAs. Multivariate data analysis demonstrated that FA analysis is a useful tool for differentiating species belonging to genus Aspergillus. All the species analyzed showed significantly FA acid profiles (p < 0.001). Furthermore, it will be possible to distinguish among Aspergillus spp. in the Flavi Section. FA composition can serve as a useful tool for the identification of filamentous fungi.

Different profiles of immune reconstitution in children and adults with HIV-infection after highly active antiretroviral therapy.

BACKGROUND Recent advances in characterizing the immune recovery of HIV-1-infected people have highlighted the importance of the thymus for peripheral T-cell diversity and function. The aim of this study was to investigate differences in immune reconstitution profiles after highly active antiretroviral therapy (HAART) between HIV-children and adults. METHODS HIV patients were grouped according to their previous clinical and immunological status: 9 HIV-Reconstituting-adults (HIV-Rec-adults) and 10 HIV-Reconstituting-children (HIV-Rec-children) on HAART with viral load (VL) or=500 cells/microL at least during 6 months before the study and CD4+ data suggest that HIV-Rec-children had better thymic function than HIV-Rec-adults and this fact affects the peripheral T-cell subsets. Thus, T-cell recovery after HAART in HIV-Rec-adults could be the consequence of antigen-independent peripheral T-cell expansion while in HIV-Rec-children thymic output could play a predominant role in immune reconstitution.

Clinical data and molecular analysis of Mycobacterium tuberculosis isolates from drug-resistant tuberculosis patients in Goiás, Brazil

Drug resistance is one of the major concerns regarding tuberculosis (TB) infection worldwide because it hampers control of the disease. Understanding the underlying mechanisms responsible for drug resistance development is of the highest importance. To investigate clinical data from drug-resistant TB patients at the Tropical Diseases Hospital, Goiás (GO), Brazil and to evaluate the molecular basis of rifampin (R) and isoniazid (H) resistance in Mycobacterium tuberculosis. Drug susceptibility testing was performed on 124 isolates from 100 patients and 24 isolates displayed resistance to R and/or H. Molecular analysis of drug resistance was performed by partial sequencing of the rpoB and katGgenes and analysis of the inhA promoter region. Similarity analysis of isolates was performed by 15 loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing. The molecular basis of drug resistance among the 24 isolates from 16 patients was confirmed in 18 isolates. Different susceptibility profiles among the isolates from the same individual were observed in five patients; using MIRU-VNTR, we have shown that those isolates were not genetically identical, with differences in one to three loci within the 15 analysed loci. Drug-resistant TB in GO is caused by M. tuberculosis strains with mutations in previously described sites of known genes and some patients harbour a mixed phenotype infection as a consequence of a single infective event; however, further and broader investigations are needed to support our findings.

One person with two DNA profiles: a(nother) case of mosaicism or chimerism.

Nuclear DNA markers, such as short tandem repeats (STR), are widely used for crime investigation and paternity testing. STR were used to determine whether a piece of tissue regurgitated by a dog was part of the penis of a dead, emasculated, man. Unexpectedly, when analyzing the recovered material and a blood sample from the deceased, five out of the 18 loci differed. According to the results, one could have concluded that these samples originated from two different persons. However, taking into account contextual information and data from complementary genetic analyses, the most likely hypothesis was that the deceased was a genetic mosaic or a chimera. Within a forensic genetic context, such genetic peculiarities may prevent associating the perpetrator of an offense with a stain left at a crime scene or lead to false paternity exclusions. Fast recognition of mosaics or chimeras, adapted sampling scheme, as well as careful interpretation of the data should allow avoiding such pitfalls.

Universal features of personality traits from the observer's perspective: Data from 50 cultures

To test hypotheses about the universality of personality traits, college students in 50 cultures identified an adult or college-aged man or woman whom they knew well and rated the 11,985 targets using the 3rd-person version of the Revised NEO Personality Inventory. Factor analyses within cultures showed that the normative American self-report structure was clearly replicated in most cultures and was recognizable in all. Sex differences replicated earlier self-report results, with the most pronounced differences in Western cultures. Cross-sectional age differences for 3 factors followed the pattern identified in self-reports, with moderate rates of change during college age and slower changes after age 40. With a few exceptions, these data support the hypothesis that features of personality traits are common to all human groups.