Psychometric Validation Study of the Liebowitz Social Anxiety Scale - Self-Reported Version for Brazilian Portuguese

Social Anxiety Disorder (SAD) is prevalent and rarely diagnosed due to the difficulty in recognizing its symptoms as belonging to a disorder. Therefore, the evaluation/screening scales are of great importance for its detection, with the most used being the Liebowitz Social Anxiety Scale (LSAS). Thus, this study proposed to evaluate the psychometric properties of internal consistency and convergent validity, as well as the confirmatory factorial analysis and reliability of the self-reported version of the LSAS (LSAS-SR), translated into Brazilian Portuguese, in a sample of the general population (N = 413) and in a SAD clinical sample (N = 252). The convergent validity with specific scales for the evaluation of SAD and a general anxiety scale presented correlations ranging from 0.21 to 0.84. The confirmatory factorial analysis did not replicate the previously indicated findings of the literature, with the difficulty being in obtaining a consensus factorial structure common to the diverse cultures in which the instrument was studied. The LSAS-SR presented excellent internal consistency (α = 0.90–0.96) and test-retest reliability (Intraclass Correlation Coefficient = 0.81; Pearson’s = 0.82). The present findings support those of international studies that attest to the excellent psychometric properties of the LSAS-SR, endorsing its status as the gold standard.     

Integrative taxonomy of Flatbill Flycatchers (Tyrannidae) reveals a new species from the Amazonian lowlands

Integrative taxonomic studies continue to reveal that many current polytypic species of birds are in fact constituted by two or more species and therefore have been central in uncovering ‘hidden’ or ‘cryptic’ biodiversity. The Olivaceous Flatbill (Aves: Tyrannidae: Rhynchocyclus olivaceus) currently has nine recognized subspecies distributed throughout the Neotropics, but so far, no complete phylogenetic hypothesis exists to test the validity and evolutionary relationships among them. To remedy this, we conducted a multi-character integrative taxonomic revision of the genus Rhynchocyclus, focusing on the polytypic R. olivaceus. The combination of a taxonomically dense sampled multilocus phylogeny (including three mitochondrial and two nuclear genes) with phenotypic analyses including morphological and vocal characters pointed to several taxonomic inconsistencies within R. olivaceus. The analyses strongly support that R. olivaceus is paraphyletic, with an exclusively cis-Andean clade (where the topotypic R. olivaceus is found) clustering as sister to Rhynchocyclus fulvipectus, to the exclusion of a clade grouping trans-Andean and western Amazonian populations currently placed in R. olivaceus—one of which is unnamed and fully diagnosable based on vocal and genetic characters. Consistent with the phylogenetic results, our vocal analyses identified at least four morphologically cryptic lineages within R. olivaceus that can be mutually diagnosed from each other by different loudsongs and call parameters. Therefore, we provide evidence for splitting these four groups into separate species, two of which are sympatric but not syntopic in western Amazonia, including an unnamed species described herein—Rhynchocyclus cryptus, sp. nov. urn:lsid:zoobank.org:act:2DC17190-2BDD-49EC-88E6-4CF2FC2562A3.     

Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of

Various address georeferencing (AG) tools are currently available. But little is known about the quality of each tool. Using data from the EPIPorto cohort we compared the most commonly used AG tools in terms of positional error (PE) and subjects'' misclassification according to census tract socioeconomic status (SES), a widely used variable in epidemiologic studies. Participants of the EPIPorto cohort (n = 2427) were georeferenced using Geographical Information Systems (GIS) and Google Earth (GE). One hundred were randomly selected and georeferenced using three additional tools: 1) cadastral maps (gold-standard); 2) Global Positioning Systems (GPS) and 3) Google Earth, single and in a batch. Mean PE and the proportion of misclassified individuals were compared. Google Earth showed lower PE than GIS, but 10% of the addresses were imprecisely positioned. Thirty-eight, 27, 16 and 14% of the participants were located in the wrong census tract by GIS, GPS, GE (batch) and GE (single), respectively (p<0.001). Misclassification according to SES was less frequent but still non-negligible −14.4, 8.1, 4.2 and 2% (p<0.001). The quality of georeferencing differed substantially between AG tools. GE seems to be the best tool, but only if prudently used. Epidemiologic studies using spatial data should start including information on the quality and accuracy of their georeferencing tools and spatial datasets.     

Optimization strategies for metabolic networks

Background  

The increasing availability of models and data for metabolic networks poses new challenges in what concerns optimization for biological systems. Due to the high level of complexity and uncertainty associated to these networks the suggested models often lack detail and liability, required to determine the proper optimization strategies. A possible approach to overcome this limitation is the combination of both kinetic and stoichiometric models. In this paper three control optimization methods, with different levels of complexity and assuming various degrees of process information, are presented and their results compared using a prototype network.     

Nitrogen-fixing bacteria communities occurring in soils under different uses in the Western Amazon Region as indicated by nodulation of siratro (Macroptilium atropurpureum)

Understanding native communities is a crucial step for the management of biological nitrogen fixation, since they may be either a source of efficient strains or a limiting factor when efficient strains need to be introduced. This work aimed to evaluate the density, diversity and efficiency of Leguminosae nodulating bacterial (LNB) communities and their component strains in soils under various land use systems (LUSs): pristine forest, agriculture, pasture, agroforestry, young secondary forest, and old secondary forest,. The LNB communities were trapped from these soils by using the promiscuous host siratro under controlled conditions. We also studied their relationships with physical and chemical attributes of the soil. Agroforestry and agriculture soil samples induced the highest number of nodules in siratro, while forest soil samples induced the lowest number of nodules. No relationship was found between LNB and Leguminosae species diversity in the LUSs. The soil chemical variables that were most related to differences in nodule number and shoot dry matter weight of plants inoculated with soil suspensions of the LUSs were, respectively: Ca²⁺, Mg²⁺, base saturation, exchangeable bases and Cu²⁺; and pH, cation exchange capacity, B, Cu²⁺ and clay. Although, LNB communities from all LUSs were efficient under controlled and similar conditions, they were found to be composed of strains with variable efficiency: inefficient, efficient, highly efficient and superior efficiency. Efficient strains occurred at the highest frequency in all LUSs. The isolated strains presented similar and new sequences that were phylogenetically related to well known LNB genera in α-and β-Proteobacteria. Unusual genera in these branches, as well as in other branches, which are probably endophytic bacteria, were also isolated from nodules. These data support siratro as a useful trap species to study the LNB biodiversity of diverse ecosystems in tropical soils. The fact that the highest diversity and nodulation were seen in managed systems such as agriculture and agroforestry suggests a high resilience of LNB communities to changes in land use after deforestation in a region where large forest areas are still preserved and can be a source of propagules.