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.

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.

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.

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.

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.

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.

Analysis of Insect Cuticular Compounds by Non-lethal Solid Phase Micro Extraction with Styrene-Divinylbenzene Copolymers

Insect cuticular hydrocarbons including relatively non-volatile chemicals play important roles in cuticle protection and chemical communication. The conventional procedures for extracting cuticular compounds from insects require toxic solvents, or non-destructive techniques that do not allow storage of subsequent samples, such as the use of SPME fibers. In this study, we describe and tested a non-lethal process for extracting cuticular hydrocarbons with styrene-divinylbenzene copolymers, and illustrate the method with two species of bees and one species of beetle. The results demonstrate that these compounds can be efficiently trapped by ChromosorbA (R) (SUPELCO) and that this method can be used as an alternative to existing methods.

A proteomic analysis of the functional effects of fatty acids in NIH 3T3 fibroblasts

Previous studies have demonstrated that long chain fatty acids influence fibroblast function at sub-lethal concentrations. This study is the first to assess the effects of oleic, linoleic or palmitic acids on protein expression of fibroblasts, as determined by standard proteomic techniques. The fatty acids were not cytotoxic at the concentration used in this work as assessed by membrane integrity, DNA fragmentation and the MTT assay but significantly increased cell proliferation. Subsequently, a proteomic analysis was performed using two dimensional difference gel electrophoresis (2D-DIGE) and MS based identification. Cells treated with 50 μM oleic, linoleic or palmitic acid for 24 h were associated with 24, 22, 16 spots differentially expressed, respectively. Among the identified proteins, α-enolase and far upstream element binding protein 1 (FBP-1) are of importance due to their function in fibroblast-associated diseases. However, modulation of α-enolase and FBP-1 expression by fatty acids was not validated by the Western blot technique.

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.

ERIC-PCR genotypic characterization of Haemophilus parasuis isolated from Brazilian swine

Haemophilus parasuis infection, known as Glässer’s disease, is characterized by fibrinous polyserositis, arthritis and meningitis in piglets. Although traditional diagnosis is based on herd history, clinical signs, bacterial isolation and serotyping, the molecular-based methods are alternatives for species-specific tests and epidemiologic study. The aim of this study was to characterize H. parasuis strains isolated from different states of Brazil by serotyping, PCR and ERIC-PCR. Serotyping revealed serovar 4 as the most prevalent (24 %), followed by serovars 14 (14 %), 5 (12 %), 13 (8 %) and 2 (2 %), whereas 40 % of the strains were considered as non-typeable. From 50 strains tested 43 (86%) were positive to Group 1 vtaA gene that have been related to virulent strains of H.parasuis. ERIC-PCR was able to type isolates tested among 23 different patterns, including non-typeable strains. ERIC-PCR patterns were very heterogeneous and presented high similarity between strains of the same animal or farm origin. The results indicated ERIC-PCR as a valuable tool for typing H. parasuis isolates collected in Brazil.

Systematic Evaluation of Extraction Methods for Multiplatform-Based Metabotyping: Application to the Fasciola hepatica Metabolome

Combining data from multiple analytical platforms is essential for comprehensive study of the molecular phenotype (metabotype) of a given biological sample. The metabolite profiles generated are intrinsically dependent on the analytical platforms, each requiring optimization of instrumental parameters, separation conditions, and sample extraction to deliver maximal biological information. An in-depth evaluation of extraction protocols for characterizing the metabolome of the hepatobiliary fluke Fasciola hepatica, using ultra performance liquid chromatography and capillary electrophoresis coupled with mass spectroscopy is presented. The spectrometric methods were characterized by performance, and metrics of merit were established, including precision, mass accuracy, selectivity, sensitivity, and platform stability. Although a core group of molecules was common to all methods, each platform contributed a unique set, whereby 142 metabolites out of 14,724 features were identified. A mixture design revealed that the chloroform:methanol:water proportion of 15:59:26 was globally the best composition for metabolite extraction across UPLC-MS and CE-MS platforms accommodating different columns and ionization modes. Despite the general assumption of the necessity of platform-adapted protocols for achieving effective metabotype characterization, we show that an appropriately designed single extraction procedure is able to fit the requirements of all technologies. This may constitute a paradigm shift in developing efficient protocols for high-throughput metabolite profiling with more-general analytical applicability.