Using Amino Acid Correlation and Community Detection Algorithms to Identify Functional Determinants in Protein Families

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

QK-Means: A clustering technique based on community detection and K-Means for deployment of cluster head nodes

Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large number of WSN nodes is usually deployed in the monitoring area to increase WSN dependability. Therefore, the best cluster head positioning is a desirable characteristic in a WSN. In this paper, we propose a hybrid clustering algorithm based on community detection in complex networks and traditional K-means clustering technique: the QK-Means algorithm. Simulation results show that QK-Means detect communities and sub-communities thus lost message rate is decreased and WSN coverage is increased. © 2012 IEEE.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

Implementação do algoritmo de Newman para identificação de comunidades em placas gráficas

Communities are present on physical, chemical and biological systems and their identification is fundamental for the comprehension of the behavior of these systems. Recently, available data related to complex networks have grown exponentially, demanding more computational power. The Graphical Processing Unit (GPU) is a cost effective alternative suitable for this purpose. We investigate the convenience of this for network science by proposing a GPU based implementation of Newman community detection algorithm. We showed that the processing time of matrix multiplications of GPUs grow slower than CPUs in relation to the matrix size. It was proven, thus, that GPU processing power is a viable solution for community dentification simulation that demand high computational power. Our implementation was tested on an integrated biological network for the bacterium Escherichia coli

Human respiratory syncytial virus detection in children admitted at a community hospital in Botucatu, SP, Brazil

O Vírus Respiratório Sincicial Humano (VRSH) é descrito como o mais importante patógeno viral causador de doenças respiratórias agudas das vias respiratórias inferiores em crianças. Neste estudo 84 amostras de crianças com idade abaixo dos dois anos apresentando sintomas de doença respiratória aguda, foram obtidas no período de setembro de 2000 a novembro de 2001. Analise por imunofluorescência indireta e transcrição reversa seguida de PCR, revelou que 18% (15/84) das amostras foram positivas, sendo que em 80% (12/15) dos casos a detecção de VRSH foi observada em crianças abaixo dos seis meses, e também que os subgrupos A e B co-circularam. Estes são os primeiros dados obtidos para a cidade de Botucatu, sendo que a sazonalidade mostrou-se evidente pela maior circulação desse vírus entre os meses de maio e julho

Reproducibility and accuracy of the ICDAS-II for occlusal caries detection

Objectives:The aim of this in vitro study was to assess the inter- and intra-examiner reproducibility and the accuracy of the International Caries Detection and Assessment System-II (ICDAS-II) in detecting occlusal caries.Methods:One hundred and sixty-three molars were independently assessed twice by two experienced dentists using the 0- to 6-graded ICDAS-II. The teeth were histologically prepared and classified using two different histological systems [Ekstrand et al. (1997) Caries Research vol. 31, pp. 224-231; Lussi et al. (1999) Caries Research vol. 33, pp. 261-266] and assessed for caries extension. Sensitivity, specificity, accuracy and area under the ROC curve (A(z)) were obtained at D(2) and D(3) thresholds. Unweighted kappa coefficient was used to assess inter- and intra-examiner reproducibility.Results:For the Ekstrand et al. histological classification the sensitivity was 0.99 and 1.00, specificity 1.00 and 0.69 and accuracy 0.99 and 0.76 at D(2) and D(3), respectively. For the Lussi et al. histological classification the sensitivity was 0.91 and 0.75, specificity 0.47 and 0.62 and accuracy 0.86 and 0.68 at D(2) and D(3), respectively. The A(z) varied from 0.54 to 0.73. The inter- and intra-examiner kappa values were 0.51 and 0.58, respectively.Conclusions:ICDAS-II presented good reproducibility and accuracy in detecting occlusal caries, especially caries lesions in the outer half of the enamel.

Prevalence and risk factors for human toxoplasmosis in a rural community

Toxoplasma gondii infection may lead to important pathological questions, especially in rural areas, where several sources of infection exist. Therefore, it is important to determine risk factors in order to establish adequate prophylactic measures. The present study aimed to assess the prevalence and risk factors involved in human toxoplasmosis infection in a rural community, in Eldorado, Mato Grosso do Sul State, Brazil. This community was composed of 185 farms - with 671 inhabitants - from which 20 were randomly chosen. In these farms, blood samples were collected from rural workers, who also answered a risk factor questionnaire. Serum samples were analyzed by means of direct agglutination test for the detection of anti-Toxoplasma gondii antibodies. From 73 samples collected, 79.45% were positive. None of the studied variables was significantly associated with the prevalence of the infection. However, among the individuals who reported eyesight impairments, 94.4% had anti-T. gondii antibodies, compared with 74.0% who did not report eyesight changes (p = 0.0594). Moreover, most individuals in the study (68.20%) were older than 18 years and presented 84.44% positivity, compared with 66.67% of positive individuals younger than 18 years old. We were able to conclude that a high prevalence of antibodies did not imply significant associations with the risk factors studied.

Detection of serum antibodies to parainfluenza type 3 virus, respiratory syncytial virus, bovine viral diarrhea virus, and herpes virus type 1 in sheep in the region of Botucatu, São Paulo - Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Staphylococcal enterotoxins: molecular aspects and detection methods

Members of the Staphylococcus genus, especially Staphylococcus aureus, are the most common pathogens found in hospitals and in community-acquired infections. Some of their pathogenicity is associated with enzyme and toxin production. Until recently, S. aureus was the most studied species in the genus; however, in last few years, the rise of infections caused by coagulase-negative staphylococci has pointed out the need for further studies on virulence factors that have not yet been completely elucidated so as to better characterize the pathogenic potential of this group of microorganisms. Several staphylococcal species produce enterotoxins, a family of related proteins responsible for many diseases, such as the toxic-shock syndrome, septicemia and food poisoning. To this date, 23 different enterotoxin types have been identified besides toxic-shock syndrome toxin-1 (TSST-1), and they can be divided into five phylogenetic groups. The mechanism of action of these toxins includes superantigen activity and emetic properties, which can lead to biological effects of infection. Various methods can detect genes that encode enterotoxins and their production. Molecular methods are the most frequently used at present. This review article has the objective to describe aspects related to the classification, structure and regulation of enterotoxins and toxic-shock syndrome toxin-1 detection methods.