Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

The role of exon shuffling in shaping protein-protein interaction networks

Background: Physical protein-protein interaction (PPI) is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results: We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners) in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains), self-interacting (able to interact with another copy of themselves) and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions: Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

Psychological stress and recurrent aphthous stomatitis

INTRODUCTION AND OBJECTIVES: Recurrent aphthous stomatitis (RAS) is the most common type of ulcerative disease of the oral mucosa. Despite its worldwide occurrence and the extensive amount of research that has been devoted to the subject, the etiology of RAS remains unclear. Nevertheless, several hereditary, nutritional, infectious and psychological factors have been associated with RAS. The aim of this case-control study was to assess the influence of psychological stress on the manifestation of RAS. METHOD: Fifty patients were enrolled in the trial. Twenty-five RAS patients constituted the study group and another 25 non-RAS patients who were similarly matched for sex, age and socioeconomic status constituted the control group. Each patient was evaluated in terms of the four domains of stress (emotional, physical, social and cognitive) using an internationally validated questionnaire, which was comprised of 59 items and measured the frequency and intensity of stress symptoms. The RAS group was interviewed during an active RAS episode. Completed questionnaires were submitted to proper analytical software and interpreted by an expert psychologist. RESULTS: There was a higher level of psychological stress among RAS group patients when compared to the control group (P < 0.05). CONCLUSION: Psychological stress may play a role in the manifestation of RAS; it may serve as a trigger or a modifying factor rather than being a cause of the disease.

Systemic treatment in severe cases of recurrent aphthous stomatitis: an open trial

PURPOSE: This study aimed to evaluate the efficacy of the systemic drugs thalidomide, dapsone, colchicine, and pentoxifylline in the treatment of severe manifestations of RAS. METHODS: An open, 4-year clinical trial was carried out for 21 consecutive patients with severe RAS. Initially, patients were given a 2-week course of prednisone to bring them to a baseline status. Simultaneously, one of the four test drugs was assigned to each patient to be taken for a period of 6 months. During the course of the trial, patients were switched to one of the other three drugs whenever side effects or a lack of satisfactory results occurred, and the 6-month limit of the treatment was then reset. RESULTS: The most efficient and best-tolerated drug was thalidomide, which was administered to a total of eight patients and resulted in complete remission in seven (87.5%). Dapsone was prescribed for a total of nine patients, of whom eight (89%) showed improvement in their symptoms, while five showed complete remission. Colchicine was administered to a total of ten patients, with benefits observed in nine (90%), of whom four showed complete remission. Pentoxyfilline was administered to a total of five patients, with benefits observed in three (60%), of whom one patient showed complete remission. CONCLUSION: The therapeutic methods used in this trial provided significant symptom relief. Patients experienced relapses of the lesions; however, this occurred after withdrawal of their medication during the follow-up period.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Risk factors for recurrent falls among Brazilian women and men: the Brazilian Osteoporosis Study (BRAZOS)

The objective of the study was to estimate the frequency of recurrent falls and identify the main associated risk factors. The BRAZOS is the first epidemiological study performed on a representative sample of the Brazilian population. Anthropometric data, living habits, previous fractures, falls, dietary intake, physical activity and quality of life were evaluated in 2,420 individuals aged 40 and older. Recurrent falls were reported by 15.5% of men and 25.6% of women. Among women, the risk factors significantly associated to recurrent falls were age, previous fracture, sedentary lifestyle, poor quality of life, diabetes mellitus and current use of benzodiazepine. In men, the risk factors were age, poor quality of life, intake of alcoholic beverages, diabetes mellitus, previous fracture and use of benzodiazepine. A greater intake of vitamin D had a protector effect on the risk of recurrent falls. These findings demonstrated the high prevalence of recurrent falls and emphasize that a multidisciplinary approach is necessary to minimize recurrent falls and their consequences, including osteoporotic fractures.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Respiratory infection, exposure to mouse allergen and breastfeeding: role in recurrent wheezing in early life

Background: Environmental factors may influence the development of allergen sensitization and asthma. The aim of this study was to evaluate the role of endotoxin and allergen exposure in early life as a risk factor for recurrent wheezing. Methods: One hundred and four infants from low-income families, at high risk of asthma, were enrolled at birth. Dust samples were collected from the bedding and bedroom floor within 6 months after birth. Recurrent wheezing was defined as 3 or more wheezing episodes in the past year. Endotoxin was determined by Limulus amebocyte lysate assay, and major indoor allergens were quantitated by ELISA in dust extracts. IgE antibodies were measured by ImmunoCAP at 30 months of age. Results: At 30 months, 51 of the 99 infants who completed the study (51.5 per cent) had recurrent wheezing. Respiratory infection was strongly associated with recurrent wheezing (OR 6.67, 95 per cent CI 1.96-22.72), whereas exclusive breastfeeding for at least 1 month was a protective factor (OR 0.09, 95 per cent CI 0.01-0.51). Exposure to high levels of mouse allergen was more frequent among non-recurrent wheezers, approaching significance (OR 0.12, 95 per cent CI 0.01-1.13; p = 0.064). None of the children were sensitized to mouse. Sensitization to mite was found in 26/90 (28.8 per cent) children, with no association with recurrent wheezing. Conclusion: Respiratory infection was strongly associated with recurrent wheezing in the first 30 months of life, in children at high risk of asthma, living in a socially deprived community in Brazil

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Fully Connected PLL Networks: How Filter Determines the Number of Nodes

Synchronization plays an important role in telecommunication systems, integrated circuits, and automation systems. Formerly, the masterslave synchronization strategy was used in the great majority of cases due to its reliability and simplicity. Recently, with the wireless networks development, and with the increase of the operation frequency of integrated circuits, the decentralized clock distribution strategies are gaining importance. Consequently, fully connected clock distribution systems with nodes composed of phase-locked loops (PLLs) appear as a convenient engineering solution. In this work, the stability of the synchronous state of these networks is studied in two relevant situations: when the node filters are first-order lag-lead low-pass or when the node filters are second-order low-pass. For first-order filters, the synchronous state of the network shows to be stable for any number of nodes. For second-order filter, there is a superior limit for the number of nodes, depending on the PLL parameters. Copyright (C) 2009 Atila Madureira Bueno et al.

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

Age of Child, More than HPV Type, Is Associated with Clinical Course in Recurrent Respiratory Papillomatosis

Background: RRP is a devastating disease in which papillomas in the airway cause hoarseness and breathing difficulty. The disease is caused by human papillomavirus (HPV) 6 or 11 and is very variable. Patients undergo multiple surgeries to maintain a patent airway and in order to communicate vocally. Several small studies have been published in which most have noted that HPV 11 is associated with a more aggressive course. Methodology/Principal Findings: Papilloma biopsies were taken from patients undergoing surgical treatment of RRP and were subjected to HPV typing. 118 patients with juvenile-onset RRP with at least 1 year of clinical data and infected with a single HPV type were analyzed. HPV 11 was encountered in 40% of the patients. By our definition, most of the patients in the sample (81%) had run an aggressive course. The odds of a patient with HPV 11 running an aggressive course were 3.9 times higher than that of patients with HPV 6 (Fisher's exact p = 0.017). However, clinical course was more closely associated with age of the patient (at diagnosis and at the time of the current surgery) than with HPV type. Patients with HPV 11 were diagnosed at a younger age (2.4y) than were those with HPV 6 (3.4y) (p = 0.014). Both by multiple linear regression and by multiple logistic regression HPV type was only weakly associated with metrics of disease course when simultaneously accounting for age. Conclusions/Significance Abstract: The course of RRP is variable and a quarter of the variability can be accounted for by the age of the patient. HPV 11 is more closely associated with a younger age at diagnosis than it is associated with an aggressive clinical course. These data suggest that there are factors other than HPV type and age of the patient that determine disease course.