Comparison of wing geometry data and genetic data for assessing the population structure of Aedes aegypti

Aedes aegypti is the most important vector of dengue viruses in tropical and subtropical regions. Because vaccines are still under development, dengue prevention depends primarily on vector control. Population genetics is a common approach in research involving Ae. aegypti. In the context of medical entomology, wing morphometric analysis has been proposed as a strong and low-cost complementary tool for investigating population structure. Therefore, we comparatively evaluated the genetic and phenotypic variability of population samples of Ae. aegypti from four sampling sites in the metropolitan area of Sao Paulo city, Brazil. The distances between the sites ranged from 7.1 to 50 km. This area, where knowledge on the population genetics of this mosquito is incipient, was chosen due to the thousands of dengue cases registered yearly. The analysed loci were polymorphic, and they revealed population structure (global F-ST = 0.062; p < 0.05) and low levels of gene flow (Nm = 0.47) between the four locations. Principal component and discriminant analyses of wing shape variables (18 landmarks) demonstrated that wing polymorphisms were only slightly more common between populations than within populations. Whereas microsatellites allowed for geographic differentiation, wing geometry failed to distinguish the samples. These data suggest that microevolution in this species may affect genetic and morphological characters to different degrees. In this case, wing shape was not validated as a marker for assessing population structure. According to the interpretation of a previous report, the wing shape of Ae. aegypti does not vary significantly because it is stabilised by selective pressure. (C) 2011 Elsevier B.V. All rights reserved.

How far can we go in simplifying biomonitoring assessments? An integrated analysis of taxonomic surrogacy, taxonomic sufficiency and numerical resolution in a megadiverse region

The need for biodiversity conservation is increasing at a rate much faster than the acquisition of knowledge of biodiversity, such as descriptions of new species and mapping species distributions. As global changes are winning the race against the acquisition of knowledge, many researchers resort to the use of surrogate groups to aid in conservation decisions. Reductions in taxonomic and numerical resolution are also desirable, because they could allow more rapid the acquisition of knowledge while requiring less effort, if little important information is lost. In this study, we evaluated the congruence among 22 taxonomic groups sampled in a tropical forest in the Amazon basin. Our aim was to evaluate if any of these groups could be used as surrogates for the others in monitoring programs. We also evaluated if the taxonomic or numerical resolution of possible surrogates could be reduced without greatly reducing the overall congruence. Congruence among plant groups was high, whereas the congruence among most animal groups was very low, except for anurans in which congruence values were only slightly lower than for plants. Liana (Bignoniaceae) was the group with highest congruence, even using genera presence-absence data. The congruence among groups was related to environmental factors, specifically the clay and phosphorous contents of soil. Several groups showed strong spatial clumping, but this was unrelated to the congruence among groups. The high degree of congruence of lianas with the other groups suggests that it may be a reasonable surrogate group, mainly for the other plant groups analyzed, if soil data are not available. Although lianas are difficult to count and identify, the number of studies on the ecology of lianas is increasing. Most of these studies have concluded that lianas are increasing in abundance in tropical forests. In addition to the high congruence, lianas are worth monitoring in their own right because they are sensitive to global warming and the increasing frequency and severity of droughts in tropical regions. Our findings suggest that the use of data on surrogate groups with relatively low taxonomic and numerical resolutions can be a reliable shortcut for biodiversity assessments, especially in megadiverse areas with high rates of habitat conversion, where the lack of biodiversity knowledge is pervasive. (c) 2012 Elsevier Ltd. All rights reserved.

Cryptic species in Iphisa elegans Gray, 1851 (Squamata: Gymnophthalmidae) revealed by hemipenial morphology and molecular data

Iphisa elegans Gray, 1851 is a ground-dwelling lizard widespread over Amazonia that displays a broadly conserved external morphology over its range. This wide geographical distribution and conservation of body form contrasts with the expected poor dispersal ability of the species, the tumultuous past of Amazonia, and the previously documented prevalence of cryptic species in widespread terrestrial organisms in this region. Here we investigate this homogeneity by examining hemipenial morphology and conducting phylogenetic analyses of mitochondrial (CYTB) and nuclear (C-MOS) DNA sequence data from 49 individuals sampled across Amazonia. We detected remarkable variation in hemipenial morphology within this species, with multiple cases of sympatric occurrence of distinct hemipenial morphotypes. Phylogenetic analyses revealed highly divergent lineages corroborating the patterns suggested by the hemipenial morphotypes, including co-occurrence of different lineages. The degrees of genetic and morphological distinctness, as well as instances of sympatry among mtDNA lineages/morphotypes without nuDNA allele sharing, suggest that I. elegans is a complex of cryptic species. An extensive and integrative taxonomic revision of the I. elegans complex throughout its wide geographical range is needed. (c) 2012 The Linnean Society of London, Zoological Journal of the Linnean Society, 2012, 166, 361376.

Modeling the emergence of HIV-1 drug resistance resulting from antiretroviral therapy: Insights from theoretical and numerical studies

The use of antiretroviral therapy has proven to be remarkably effective in controlling the progression of human immunodeficiency virus (HIV) infection and prolonging patient's survival. Therapy however may fail and therefore these benefits can be compromised by the emergence of HIV strains that are resistant to the therapy. In view of these facts, the question of finding the reason for which drug-resistant strains emerge during therapy has become a worldwide problem of great interest. This paper presents a deterministic HIV-1 model to examine the mechanisms underlying the emergence of drug-resistance during therapy. The aim of this study is to determine whether, and how fast, antiretroviral therapy may determine the emergence of drug resistance by calculating the basic reproductive numbers. The existence, feasibility and local stability of the equilibriums are also analyzed. By performing numerical simulations we show that Hopf bifurcation may occur. The model suggests that the individuals with drug-resistant infection may play an important role in the epidemic of HIV. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Experimental and numerical analysis of dry contact in the pin on disc test

The reduction of friction and wear in systems presenting metal-to-metal contacts, as in several mechanical components, represents a traditional challenge in tribology. In this context, this work presents a computational study based on the linear Archard's wear law and finite element modeling (FEM), in order to analyze unlubricated sliding wear observed in typical pin on disc tests. Such modeling was developed using finite element software Abaqus® with 3-D deformable geometries and elastic–plastic material behavior for the contact surfaces. Archard's wear model was implemented into a FORTRAN user subroutine (UMESHMOTION) in order to describe sliding wear. Modeling of debris and oxide formation mechanisms was taken into account by the use of a global wear coefficient obtained from experimental measurements. Such implementation considers an incremental computation for surface wear based on the nodal displacements by means of adaptive mesh tools that rearrange local nodal positions. In this way, the worn track was obtained and new surface profile is integrated for mass loss assessments. This work also presents experimental pin on disc tests with AISI 4140 pins on rotating AISI H13 discs with normal loads of 10, 35, 70 and 140 N, which represent, respectively, mild, transition and severe wear regimes, at sliding speed of 0.1 m/s. Numerical and experimental results were compared in terms of wear rate and friction coefficient. Furthermore, in the numerical simulation the stress field distribution and changes in the surface profile across the worn track of the disc were analyzed. The applied numerical formulation has shown to be more appropriate to predict mild wear regime than severe regime, especially due to the shorter running-in period observed in lower loads that characterizes this kind of regime.