Harder,better, faster,stronger: Weapon size is more sexually dimorphic than weapon biomechanical components in two freshwater anomuran species

Sexual selection influences the evolution of morphological traits that increase the likelihood of monopolizing scarce resources. When such traits are used during contests, they are termed weapons. Given that resources are typically linked to monopolizing mating partners, theory expects only males to bear weapons. In some species, however, females also bear weapons, although typically smaller than male weapons. Understanding why females bear smaller weapons can thus help us understand the selective pressures behind weapon evolution. However, most of our knowledge comes from studies on weapon size, while the biomechanics of weapons, such as the size of the muscles, efficiency, and shape are seldom studied. Our goal was to test if the theoretical expectations for weapon size sexual dimorphism also occur for weapon biomechanics using two aeglid crab species. Males of both species had larger claws which were also stronger than female claws. Male claws were also more efficient than females' claws (although we used only one species in this analysis). For weapon shape, though, only one species differed in the mean claw shape. Regarding scaling differences, in both species, male claws had higher size scaling than females, while only one species had a higher shape scaling. However, male weapons did not have higher scaling regarding strength and efficiency than females. Thus, males apparently allocate more resources in weapons than females, but once allocated, muscle and efficiency follow a similar developmental pathway in both sexes. Taken together, our results show that sexual dimorphism in weapons involves more than differences in size. Shape differences are especially intriguing because we cannot fully understand its causes. Yet, we highlight that such subtle differences can only be detected by measuring and analysing weapon shape and biomechanical components. Only then we might better understand how weapons are forged.     

Evolutionary history of the Pectoral Sparrow Arremon taciturnus: evidence for diversification during the Late Pleistocene

We focus on reconstructing a spatiotemporal scenario of diversification of a widespread South American species, the Pectoral Sparrow Arremon taciturnus (Aves: Passerellidae). This species is widely distributed in both the humid and the dry forests of South America and therefore provides an interesting model for understanding the connection between different biomes of South America. We examined nucleotide sequences of the mitochondrial genes Cytochrome b (cyt-b) and NADH subunit 2 (ND2) from 107 specimens, and one nuclear marker (intron 7 of the β-fibrinogen gene) from a subset of samples collected across the distribution ranges of A. t. taciturnus and A. t. nigrirostris. Six major lineages were recovered in the phylogenies that displayed high levels of variance of allele frequencies and corresponded to distinct geographical locations. The estimation of divergence times provided evidence that diversification of the six lineages of the Pectoral Sparrow occurred throughout the Late Pleistocene across major cis-Andean biomes and Amazonian interfluves. Our dataset for A. taciturnus provides further evidence that rivers in Amazonia constitute barriers promoting allopatric speciation, with occasional sharing of alleles among lineages, particularly those with adjacent distributions.     

Autophagic Cell Death in Dictyostelium Requires the Receptor Histidine Kinase DhkM

Dictyostelium constitutes a genetically tractable model for the analysis of autophagic cell death (ACD). During ACD, Dictyostelium cells first transform into paddle cells and then become round, synthesize cellulose, vacuolize, and die. Through random insertional mutagenesis, we identified the receptor histidine kinase DhkM as being essential for ACD. Surprisingly, different DhkM mutants showed distinct nonvacuolizing ACD phenotypes. One class of mutants arrested ACD at the paddle cell stage, perhaps through a dominant-negative effect. Other mutants, however, progressed further in the ACD program. They underwent rounding and cellulose synthesis but stopped before vacuolization. Moreover, they underwent clonogenic but not morphological cell death. Exogenous 8-bromo-cAMP restored vacuolization and death. A role for a membrane receptor at a late stage of the ACD pathway is puzzling, raising questions as to which ligand it is a receptor for and which moieties it phosphorylates. Together, DhkM is the most downstream-known molecule required for this model ACD, and its distinct mutants genetically separate previously undissociated late cell death events.     

Personalized Modeling for Prediction with Decision-Path Models

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach.     

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.     

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.