Integrated landmark and outline-based morphometric methods efficiently distinguish species of Euglossa (Hymenoptera, Apidae, Euglossini)

Morphometric methods permit identification of insect species and are an aid for taxonomy. Quantitative wing traits were used to identify male euglossine bees. Landmark- and outline-based methods have been primarily used independently. Here, we combine the two methods using five Euglossa. Landmark-based methods correctly classified 84% and outline-based 77%, but an integrated analysis correctly classified 91% of samples. Some species presented significantly high reclassification percentages when only wing cell contour was considered, and correct identification of specimens with damaged wings was also obtained using this methodology.

Performance of fluorescence-based and conventional methods of occlusal caries detection in primary molars - an in vitro study

International Journal of Paediatric Dentistry 2012; 22: 459466 Aim. This in vitro study aimed to test the performance of fluorescence-based methods in detecting occlusal caries lesions in primary molars compared to conventional methods. Design. Two examiners assessed 113 sites on 77 occlusal surfaces of primary molars using three fluorescence devices: DIAGNOdent (LF), DIAGNOdent pen (LFpen), and fluorescence camera (VistaProof-FC). Visual inspection (ICDAS) and radiographic methods were also evaluated. One examiner repeated the evaluations after one month. As reference standard method, the lesion depth was determined after sectioning and evaluation in stereomicroscope. The area under the ROC curve (Az), sensitivity, specificity, and accuracy of the methods were calculated at enamel (D1) and dentine caries (D3) lesions thresholds. The intra and interexaminer reproducibility were calculated using the intraclass correlation coefficient (ICC) and kappa statistics. Results. At D1, visual inspection presented higher sensitivities (0.970.99) but lower specificities (0.180.25). At D3, all the methods demonstrated similar performance (Az values around 0.90). Visual and radiographic methods showed a slightly higher specificity (values higher than 0.96) than the fluorescence based ones (values around 0.88). In general, all methods presented high reproducibility (ICC higher than 0.79). Conclusions. Although fluorescence-based and conventional methods present similar performance in detecting occlusal caries lesions in primary teeth, visual inspection alone seems to be sufficient to be used in clinical practice.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

Secondary production of sandy beach macrofauna: An evaluation of predictive models

During the last three decades, several predictive models have been developed to estimate the somatic production of macroinvertebrates. Although the models have been evaluated for their ability to assess the production of macrobenthos in different marine ecosystems, these approaches have not been applied specifically to sandy beach macrofauna and may not be directly applicable to this transitional environment. Hence, in this study, a broad literature review of sandy beach macrofauna production was conducted and estimates obtained with cohort-based and size-based methods were collected. The performance of nine models in estimating the production of individual populations from the sandy beach environment, evaluated for all taxonomic groups combined and for individual groups separately, was assessed, comparing the production predicted by the models to the estimates obtained from the literature (observed production). Most of the models overestimated population production compared to observed production estimates, whether for all populations combined or more specific taxonomic groups. However, estimates by two models developed by Cusson and Bourget provided best fits to measured production, and thus represent the best alternatives to the cohort-based and size-based methods in this habitat. The consistent performance of one of these Cusson and Bourget models, which was developed for the macrobenthos of sandy substrate habitats (C&B-SS), shows that the performance of a model does not depend on whether it was developed for a specific taxonomic group. Moreover, since some widely used models (e.g., the Robertson model) show very different responses when applied to the macrofauna of different marine environments (e.g., sandy beaches and estuaries), prior evaluation of these models is essential.

Genetic diversity of Leishmania amazonensis strains isolated in northeastern Brazil as revealed by DNA sequencing, PCR-based analyses and molecular karyotyping

Abstract Background Leishmania (Leishmania) amazonensis infection in man results in a clinical spectrum of disease manifestations ranging from cutaneous to mucosal or visceral involvement. In the present study, we have investigated the genetic variability of 18 L. amazonensis strains isolated in northeastern Brazil from patients with different clinical manifestations of leishmaniasis. Parasite DNA was analyzed by sequencing of the ITS flanking the 5.8 S subunit of the ribosomal RNA genes, by RAPD and SSR-PCR and by PFGE followed by hybridization with gene-specific probes. Results ITS sequencing and PCR-based methods revealed genetic heterogeneity among the L. amazonensis isolates examined and molecular karyotyping also showed variation in the chromosome size of different isolates. Unrooted genetic trees separated strains into different groups. Conclusion These results indicate that L. amazonensis strains isolated from leishmaniasis patients from northeastern Brazil are genetically diverse, however, no correlation between genetic polymorphism and phenotype were found.

Prevalence and risk factors of Hepatitis C virus infection in Brazil, 2005 through 2009: a cross-sectional study

Abstract Background Hepatitis C chronic liver disease is a major cause of liver transplant in developed countries. This article reports the first nationwide population-based survey conducted to estimate the seroprevalence of HCV antibodies and associated risk factors in the urban population of Brazil. Methods The cross sectional study was conducted in all Brazilian macro-regions from 2005 to 2009, as a stratified multistage cluster sample of 19,503 inhabitants aged between 10 and 69 years, representing individuals living in all 26 State capitals and the Federal District. Hepatitis C antibodies were detected by a third-generation enzyme immunoassay. Seropositive individuals were retested by Polymerase Chain Reaction and genotyped. Adjusted prevalence was estimated by macro-regions. Potential risk factors associated with HCV infection were assessed by calculating the crude and adjusted odds ratios, 95% confidence intervals (95% CI) and p values. Population attributable risk was estimated for multiple factors using a case–control approach. Results The overall weighted prevalence of hepatitis C antibodies was 1.38% (95% CI: 1.12%–1.64%). Prevalence of infection increased in older groups but was similar for both sexes. The multivariate model showed the following to be predictors of HCV infection: age, injected drug use (OR = 6.65), sniffed drug use (OR = 2.59), hospitalization (OR = 1.90), groups socially deprived by the lack of sewage disposal (OR = 2.53), and injection with glass syringe (OR = 1.52, with a borderline p value). The genotypes 1 (subtypes 1a, 1b), 2b and 3a were identified. The estimated population attributable risk for the ensemble of risk factors was 40%. Approximately 1.3 million individuals would be expected to be anti-HCV-positive in the country. Conclusions The large estimated absolute numbers of infected individuals reveals the burden of the disease in the near future, giving rise to costs for the health care system and society at large. The known risk factors explain less than 50% of the infected cases, limiting the prevention strategies. Our findings regarding risk behaviors associated with HCV infection showed that there is still room for improving strategies for reducing transmission among drug users and nosocomial infection, as well as a need for specific prevention and control strategies targeting individuals living in poverty.

Impact of diabetes mellitus on arterial stiffness in a representative sample of an urban Brazilian population

Background Independent of other cardiovascular (CV) risk factors, increased arterial stiffness has been established as a predictor of morbidity and mortality. The main aim of this study was to investigate the impact of diabetes on arterial stiffness in a representative sample of an urban Brazilian population plus Amerindians. Methods A total of 1,415 individuals from the general population were randomly selected plus 588 Amerindians from a native community in Brazil. In addition, a sub-sample of 380 individuals from the general population had 5-year follow-up data. Pulse wave velocity (PWV) was measured with a non-invasive automatic device (Complior, Colson; Garges les Gonesses, France) and increased arterial stiffness was defined as PWV ≥ 12 m/s. Results In the overall group, diabetic individuals had higher frequencies of increased arterial stiffness and hypertension. They also had higher values of PWV, body mass index, total cholesterol, triglycerides, systolic and diastolic blood pressures compared to non-diabetic individuals (p < 0.01). In an analysis stratified by hypertension, PWV values and increased arterial stiffness frequency were higher in diabetic individuals in both groups (hypertensive and non-hypertensive) (p < 0.05). Furthermore, higher risk for increased arterial stiffness was observed in the diabetic individuals from the overall group (OR = 2.27; CI = 1.47-3.52, p < 0.001) and from the hypertensive group (OR = 2.70; CI = 1.58-4.75, p < 0.001), adjusted for covariates. Regarding the ethnic stratification, diabetic individuals from Amerindian, White, and Mulatto (mixed-race) groups had higher PWV values and a greater frequency of increased arterial stiffness compared to non-diabetic individuals. Both diabetic and non-diabetic individuals had higher PWV values after 5 years. There was no significant difference in the 5-year PWV progression in diabetic compared to non-diabetic individuals. Conclusions These results confirm, in a sample of Brazilian population, that the presence of diabetes is associated with increased arterial stiffness and it may contribute in part to increased cardiovascular risk in diabetic patients.

The performance of four molecular methods for the laboratory diagnosis of congenital toxoplasmosis in amniotic fluid samples

Introduction Toxoplasmosis may be life-threatening in fetuses and in immune-deficient patients. Conventional laboratory diagnosis of toxoplasmosis is based on the presence of IgM and IgG anti-Toxoplasma gondii antibodies; however, molecular techniques have emerged as alternative tools due to their increased sensitivity. The aim of this study was to compare the performance of 4 PCR-based methods for the laboratory diagnosis of toxoplasmosis. One hundred pregnant women who seroconverted during pregnancy were included in the study. The definition of cases was based on a 12-month follow-up of the infants. Methods Amniotic fluid samples were submitted to DNA extraction and amplification by the following 4 Toxoplasma techniques performed with parasite B1 gene primers: conventional PCR, nested-PCR, multiplex-nested-PCR, and real-time PCR. Seven parameters were analyzed, sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and efficiency (Ef). Results Fifty-nine of the 100 infants had toxoplasmosis; 42 (71.2%) had IgM antibodies at birth but were asymptomatic, and the remaining 17 cases had non-detectable IgM antibodies but high IgG antibody titers that were associated with retinochoroiditis in 8 (13.5%) cases, abnormal cranial ultrasound in 5 (8.5%) cases, and signs/symptoms suggestive of infection in 4 (6.8%) cases. The conventional PCR assay detected 50 cases (9 false-negatives), nested-PCR detected 58 cases (1 false-negative and 4 false-positives), multiplex-nested-PCR detected 57 cases (2 false-negatives), and real-time-PCR detected 58 cases (1 false-negative). Conclusions The real-time PCR assay was the best-performing technique based on the parameters of Se (98.3%), Sp (100%), PPV (100%), NPV (97.6%), PLR (â^ž), NLR (0.017), and Ef (99%).

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Characterization of Haemophilus parasuis isolated from Brazilian swine through serotyping, AFLP and PFGE

Haemophilus parasuis infection in pigs is characterized by fibrinous polyserositis, arthritis and meningitis. Despite the fact that traditional diagnosis is based on herd history, clinical signs, bacterial isolation and serotyping, molecular-based methods are alternatives for species-specific tests and epidemiological studies. The aim of this study was to characterize H. parasuis field strains from different states of Brazil, employing serotyping and genotyping methods. Serotyping revealed that serovar 4 was the most prevalent (26.1%), followed by serovars 5(17.4%), 14(8.7%), 13 (4.4%) and 2 (4.4%), whereas 39% of the strains were considered as untypeable. AFLP with a single enzyme and PFGE were able to type all isolates tested, generating 34 and 20 different profiles, respectively, including untypeable strains. Besides the slightly higher discrimination index presented by AFLP, PFGE with Not I restriction enzyme showed a better correlation with epidemiological data, grouping strains of the same serovar, animal or farm origin. The results indicated AFLP and PFGE as valuable tools for typing H. parasuis isolates collected in Brazil. (C) 2011 Elsevier Ltd. All rights reserved.

JC virus-associated central nervous system diseases in HIV-infected patients in Brazil: clinical presentations, associated factors with mortality and outcome

Introduction: Several presentations of neurologic complications caused by JC virus (JCV) in human immunodeficiency virus (HIV)-infected patients have been described and need to be distinguished from the "classic" form of progressive multifocal leukoencephalopathy (PML). The objectives of this study were: 1) to describe the spectrum and frequency of presentations of JCV-associated central nervous system (CNS) diseases; 2) identify factors associated with in-hospital mortality of patients with JCV-associated CNS disease; and 3) to estimate the overall mortality of this population. Material and methods: This was a retrospective study of HIV-infected patients admitted consecutively for JCV-associated CNS diseases in a referral teaching center in Sao Paulo, Brazil, from 2002 to 2007. All patients with laboratory confirmed JCV-associated CNS diseases were included using the following criteria: compatible clinical and radiological features associated with the presence of JCV DNA in the cerebrospinal fluid. JCV-associated CNS diseases were classified as follows: 1) classic PML; 2) inflammatory PML; and 3) JC virus granule cell neuronopathy (GCN). Results: We included 47 cases. JCV-associated CNS diseases were classified as follows: 1) classic PML: 42 (89%); 2) inflammatory PML: three (6%); and 3) JC virus GCN: four (9%). Nosocomial pneumonia (p = 0.003), previous diagnosis of HIV infection (p = 0.03), and imaging showing cerebellar and/or brainstem involvement (p = 0.02) were associated with in-hospital mortality. Overall mortality during hospitalization was 34%. Conclusions: Novel presentations of JCV-associated CNS diseases were observed in our setting; nosocomial pneumonia, previous diagnosis of HIV infection, and cerebellar and/or brainstem involvement were associated with in-hospital mortality; and overall mortality was high. (C) 2012 Elsevier Editora Ltda. All rights reserved.

Extractive summarization using complex networks and syntactic dependency

The realization that statistical physics methods can be applied to analyze written texts represented as complex networks has led to several developments in natural language processing, including automatic summarization and evaluation of machine translation. Most importantly, so far only a few metrics of complex networks have been used and therefore there is ample opportunity to enhance the statistics-based methods as new measures of network topology and dynamics are created. In this paper, we employ for the first time the metrics betweenness, vulnerability and diversity to analyze written texts in Brazilian Portuguese. Using strategies based on diversity metrics, a better performance in automatic summarization is achieved in comparison to previous work employing complex networks. With an optimized method the Rouge score (an automatic evaluation method used in summarization) was 0.5089, which is the best value ever achieved for an extractive summarizer with statistical methods based on complex networks for Brazilian Portuguese. Furthermore, the diversity metric can detect keywords with high precision, which is why we believe it is suitable to produce good summaries. It is also shown that incorporating linguistic knowledge through a syntactic parser does enhance the performance of the automatic summarizers, as expected, but the increase in the Rouge score is only minor. These results reinforce the suitability of complex network methods for improving automatic summarizers in particular, and treating text in general. (C) 2011 Elsevier B.V. All rights reserved.

Impact of pediatric epilepsy surgery on intellectual efficiency

Introduction. Epilepsy surgery may be a promising alternative therapy for seizure control in patients with refractory seizures, resistant to medication. Cognitive outcome is another important factor in favor of the surgical decision. Aim. To investigate the correlation between seizure outcome and cognitive outcome after epilepsy surgery in a pediatric population. Patients and methods. A total of 59 pediatric patients were retrospectively assessed with the WISC-III (Full Scale, Verbal Scale and Performance Scale) before and, at least, 6 months after surgery. Patients were divided into two groups according whether or not improvement of seizure control after surgery. Data collected for each child included: epileptic syndrome, etiology, age at epilepsy onset, duration of epilepsy and seizure frequency. Results. Comparison using a MANOVA test revealed significant differences across pre-operative Full Scale, Verbal Scale and Performance Scale (p = 0.01) with seizure reduction group performing better than no seizure reduction group. Seizure improvement group achieved significant Performance Scale improvement (p = 0.01) and no seizure improvement group showed significant Verbal Scale worsened after surgery (p = 0.01). Conclusions. Our results suggest that the success of the epilepsy surgery in childhood when the seizure control is achieved may also provide an improvement in the Performance Scale whereas the seizure maintenance may worsen the Verbal Scale.

Biogeographic and diversification patterns of Neotropical Troidini butterflies (Papilionidae) support a museum model of diversity dynamics for Amazonia

Background: The temporal and geographical diversification of Neotropical insects remains poorly understood because of the complex changes in geological and climatic conditions that occurred during the Cenozoic. To better understand extant patterns in Neotropical biodiversity, we investigated the evolutionary history of three Neotropical swallowtail Troidini genera (Papilionidae). First, DNA-based species delimitation analyses were conducted to assess species boundaries within Neotropical Troidini using an enlarged fragment of the standard barcode gene. Molecularly delineated species were then used to infer a time-calibrated species-level phylogeny based on a three-gene dataset and Bayesian dating analyses. The corresponding chronogram was used to explore their temporal and geographical diversification through distinct likelihood-based methods. Results: The phylogeny for Neotropical Troidini was well resolved and strongly supported. Molecular dating and biogeographic analyses indicate that the extant lineages of Neotropical Troidini have a late Eocene (33-42 Ma) origin in North America. Two independent lineages (Battus and Euryades + Parides) reached South America via the GAARlandia temporary connection, and later became extinct in North America. They only began substantive diversification during the early Miocene in Amazonia. Macroevolutionary analysis supports the "museum model" of diversification, rather than Pleistocene refugia, as the best explanation for the diversification of these lineages. Conclusions: This study demonstrates that: (i) current Neotropical biodiversity may have originated ex situ; (ii) the GAARlandia bridge was important in facilitating invasions of South America; (iii) colonization of Amazonia initiated the crown diversification of these swallowtails; and (iv) Amazonia is not only a species-rich region but also acted as a sanctuary for the dynamics of this diversity. In particular, Amazonia probably allowed the persistence of old lineages and contributed to the steady accumulation of diversity over time with constant net diversification rates, a result that contrasts with previous studies on other South American butterflies.

Bootstrap confidence intervals for industrial recurrent event data

Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.