Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

State Space Analysis of Forest Fires

This paper studies forest fires from the perspective of dynamical systems. Burnt area, precipitation and atmospheric temperatures are interpreted as state variables of a complex system and the correlations between them are investigated by means of different mathematical tools. First, we use mutual information to reveal potential relationships in the data. Second, we adopt the state space portrait to characterize the system’s behavior. Third, we compare the annual state space curves and we apply clustering and visualization tools to unveil long-range patterns. We use forest fire data for Portugal, covering the years 1980–2003. The territory is divided into two regions (North and South), characterized by different climates and vegetation. The adopted methodology represents a new viewpoint in the context of forest fires, shedding light on a complex phenomenon that needs to be better understood in order to mitigate its devastating consequences, at both economical and environmental levels.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

Virulence profile of ten Paracoccidioides brasiliensis isolates: association with morphologic and genetic patterns

Ten isolates of Paracoccidioides brasiliensis were examined for differences in virulence in outbred mice intravenously inoculated with the fungus, associated with mycelial morphology, and genetic patterns measured by random amplified polymorphic DNA (RAPD). Virulence was evaluated by viable yeast cell recovery from lungs and demonstration of histopathologic lesions in different organs. The results showed that the isolates presented four virulence degrees: high virulence, intermediate, low and non-virulence. RAPD clustered the isolates studied in two main groups with 56% of genetic similarity. Strains with low virulence, Pb265 or the non-virulent, Pb192, showed glabrous/cerebriform morphology and high genetic similarity (98.7%) when compared to the other isolates studied. The same was observed with Bt79 and Bt83 that shared 96% genetic similarity, cottony colonies and high virulence. The RAPD technique could only discriminate P. brasiliensis isolates according to glabrous/cerebriform or cottony colonies, and also high from low virulence strains. Isolates with intermediate virulence such as Pb18, Pb18B6, Bt32 and Bt56 showed variability in their similarity coefficient suggesting that RAPD was able to detect genetic variability in this fungal specie. Virulence profile of P. brasiliensis demonstrated that both mycelial morphologic extreme phenotypes may be associated with fungal virulence and their in vitro subculture time. Thus, RAPD technique analysis employed in association with virulence, morphologic and immunologic aspects might prove adequate to detect differences between P. brasiliensis isolates.

Optimization of random amplified polymorphic DNA techniques for use in genetic studies of Cuban triatominae

Random amplified polymorphic DNA (RAPD) technique is a simple and reliable method to detect DNA polymorphism. Several factors can affect the amplification profiles, thereby causing false bands and non-reproducibility of assay. In this study, we analyzed the effect of changing the concentration of primer, magnesium chloride, template DNA and Taq DNA polymerase with the objective of determining their optimum concentration for the standardization of RAPD technique for genetic studies of Cuban Triatominae. Reproducible amplification patterns were obtained using 5 pmoL of primer, 2.5 mM of MgCl2, 25 ng of template DNA and 2 U of Taq DNA polymerase in 25 µL of the reaction. A panel of five random primers was used to evaluate the genetic variability of T. flavida. Three of these (OPA-1, OPA-2 and OPA-4) generated reproducible and distinguishable fingerprinting patterns of Triatominae. Numerical analysis of 52 RAPD amplified bands generated for all five primers was carried out with unweighted pair group method analysis (UPGMA). Jaccard's Similarity Coefficient data were used to construct a dendrogram. Two groups could be distinguished by RAPD data and these groups coincided with geographic origin, i.e. the populations captured in areas from east and west of Guanahacabibes, Pinar del Río. T. flavida present low interpopulation variability that could result in greater susceptibility to pesticides in control programs. The RAPD protocol and the selected primers are useful for molecular characterization of Cuban Triatominae.

Genetic diversity and antimicrobial resistance of enterococcal isolates from Southern region of Brazil

In the present study, a total of 455 enterococcal isolates, recovered from patients living in the city of Porto Alegre, State of Rio Grande do Sul, Brazil, during the period from July 1996 to June 1997, were identified to the species level by conventional biochemical and microbiological tests, and assayed for their susceptibilities to antimicrobial agents. The genetic diversity of antimicrobial resistant strains was evaluated by pulsed-field gel electrophoresis (PFGE) analysis of SmaI restricted chromosomal DNA. The most frequent species was Enterococcus faecalis (92.8%). Other species identified were: E. faecium (2.9%), E. gallinarum (1.5%), E. avium (1.1%), E. hirae (0.7%), E. casseliflavus (0.4%), E. durans (0.4%) and E. raffinosus (0.2%). The overall prevalence of isolates with high-level resistance (HLR) to aminoglycosides was 37.8%. HLR to gentamicin was found in 24.8%. No strains with acquired resistance to vancomycin were found. PFGE analysis showed the predominance of clonal group A, comprising strains isolated from different clinical specimens obtained from patients in three hospitals. These results suggest intra and inter-hospital dissemination of one predominant clonal group of E. faecalis isolates with HLR to gentamicin in the hospitals included in this study.

Antigenic and genetic characterization of the first rabies virus isolated from the bat Eumops perotis in Brazil

Although the main transmitters of rabies in Brazil are dogs and vampire bats, the role of other species such as insectivorous and frugivorous bats deserves special attention, as the rabies virus has been isolated from 36 bat species. This study describes the first isolation of the rabies virus from the insectivorous bat Eumops perotis. The infected animal was found in the city of Ribeirão Preto, São Paulo. The virus was identified by immunofluorescence antibody test (FAT) in central nervous system (CNS) samples, and the isolation was carried out in N2A cell culture and adult mice. The sample was submitted to antigenic typing using a panel of monoclonal antibodies (CDC/Atlanta/USA). The DNA sequence of the nucleoprotein gene located between nucleotides 102 and 1385 was aligned with homologous sequences from GenBank using the CLUSTAL/W method, and the alignment was used to build a neighbor-joining distance-based phylogenetic tree with the K-2-P model. CNS was negative by FAT, and only one mouse died after inoculation with a suspension from the bat's CNS. Antigenic typing gave a result that was not compatible with the patterns defined by the panel. Phylogenetic analysis showed that the virus isolated segregated into the same cluster related to other viruses isolated from insectivorous bats belonging to genus Nyctinomops ssp. (98.8% nucleotide identity with each other).

FAS -670A>G genetic polymorphism Is associated with Treatment Resistant Depression

Background Hippocampal neurogenesis has been suggested as a downstream event of antidepressants (AD) mechanism of action and might explain the lag time between AD administration and the therapeutic effect. Despite the widespread use of AD in the context of Major Depressive Disorder (MDD) there are no reliable biomarkers of treatment response phenotypes, and a significant proportion of patients display Treatment Resistant Depression (TRD). Fas/FasL system is one of the best-known death-receptor mediated cell signaling systems and is recognized to regulate cell proliferation and tumor cell growth. Recently this pathway has been described to be involved in neurogenesis and neuroplasticity. Methods Since FAS -670A>G and FASL -844T>C functional polymorphisms never been evaluated in the context of depression and antidepressant therapy, we genotyped FAS -670A>G and FASL -844T>C in a subset of 80 MDD patients to evaluate their role in antidepressant treatment response phenotypes. Results We found that the presence of FAS -670G allele was associated with antidepressant bad prognosis (relapse or TRD: OR=6.200; 95% CI: [1.875–20.499]; p=0.001), and we observed that patients carrying this allele have a higher risk to develop TRD (OR=10.895; 95% CI: [1.362–87.135]; p=0.008).Moreover, multivariate analysis adjusted to potentials confounders showed that patients carrying G allele have higher risk of early relapse (HR=3.827; 95% CI: [1.072–13.659]; p=0.039). FAS mRNA levels were down-regulated among G carriers, whose genotypes were more common in TRD patients. No association was found between FASL-844T>C genetic polymorphism and any treatment phenotypes. Limitations Small sample size. Patients used antidepressants with different mechanisms of action. Conclusion To the best of our knowledge this is the first study to evaluate the role of FAS functional polymorphism in the outcome of antidepressant therapy. This preliminary report associates FAS -670A>G genetic polymorphism with Treatment Resistant Depression and with time to relapse. The current results may possibly be given to the recent recognized role of Fas in neurogenesis and/or neuroplasticity.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Multidimensional Scalling Analysis of the World Economy During the Period 1972-2012

The last 40 years of the world economy are analyzed by means of computer visualization methods. Multidimensional scaling and the hierarchical clustering tree techniques are used. The current Western downturn in favor of Asian partners may still be reversed in the coming decades.

Fractional State Space Analysis of Temperature Time Series

Atmospheric temperatures characterize Earth as a slow dynamics spatiotemporal system, revealing long-memory and complex behavior. Temperature time series of 54 worldwide geographic locations are considered as representative of the Earth weather dynamics. These data are then interpreted as the time evolution of a set of state space variables describing a complex system. The data are analyzed by means of multidimensional scaling (MDS), and the fractional state space portrait (fSSP). A centennial perspective covering the period from 1910 to 2012 allows MDS to identify similarities among different Earth’s locations. The multivariate mutual information is proposed to determine the “optimal” order of the time derivative for the fSSP representation. The fSSP emerges as a valuable alternative for visualizing system dynamics.

Genetic diversity and primary resistance among HIV-1-positive patients from Maringá, Paraná, Brazil

The objective of this study is to identify subtypes of Human Immunodeficiency Virus type 1 (HIV-1) and to analyze the presence of mutations associated to antiretroviral resistance in the protease (PR) and reverse transcriptase (RT) regions from 48 HIV-1 positive treatment naïve patients from an outpatient clinic in Maringá, Paraná, Brazil. Sequencing was conducted using PR, partial RT and group-specific antigen gene (gag) nested PCR products from retrotranscribed RNA. Transmitted resistance was determined according to the Surveillance Drug Resistance Mutation List (SDRM) algorithm. Phylogenetic and SimPlot analysis of concatenated genetic segments classified sequences as subtype B 19/48 (39.6%), subtype C 12/48 (25%), subtype F 4/48 (8.3%), with 13/48 (27.1%) recombinant forms. Most recombinant forms were B mosaics (B/F 12.5%, B/C 10.4%), with one C/F (2.1%) and one complex B/C/F mosaic (2.1%). Low levels of transmitted resistance were found in this study, 2/48 (2.1% to NRTIs and 2.1% for PI). This preliminary data may subsidize the monitoring of the HIV evolution in the region.

Scientific authorships and collaboration network analysis on Chagas disease: papers indexed in PubMed (1940-2009)

Chagas disease is a chronic, tropical, parasitic disease, endemic throughout Latin America. The large-scale migration of populations has increased the geographic distribution of the disease and cases have been observed in many other countries around the world. To strengthen the critical mass of knowledge generated in different countries, it is essential to promote cooperative and translational research initiatives. We analyzed authorship of scientific documents on Chagas disease indexed in the Medline database from 1940 to 2009. Bibliometrics was used to analyze the evolution of collaboration patterns. A Social Network Analysis was carried out to identify the main research groups in the area by applying clustering methods. We then analyzed 13,989 papers produced by 21,350 authors. Collaboration among authors dramatically increased over the study period, reaching an average of 6.2 authors per paper in the last five-year period. Applying a threshold of collaboration of five or more papers signed in co-authorship, we identified 148 consolidated research groups made up of 1,750 authors. The Chagas disease network identified constitutes a "small world," characterized by a high degree of clustering and a notably high number of Brazilian researchers.

Algorithms for information extraction and signal annotation on long-term biosignals using clustering techniques

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

The HIF1A Functional Genetic Polymorphism at Locus +1772 Associates with Progression to Metastatic Prostate Cancer and Refractoriness to Hormonal Castration

The hypoxia inducible factor 1 alpha (HIF1a) is a key regulator of tumour cell response to hypoxia, orchestrating mechanisms known to be involved in cancer aggressiveness and metastatic behaviour. In this study we sought to evaluate the association of a functional genetic polymorphism in HIF1A with overall and metastatic prostate cancer (PCa) risk and with response to androgen deprivation therapy (ADT). The HIF1A +1772 C>T (rs11549465) polymorphism was genotyped, using DNA isolated from peripheral blood, in 1490 male subjects (754 with prostate cancer and 736 controls cancer-free) through Real-Time PCR. A nested group of cancer patients who were eligible for androgen deprivation therapy was followed up. Univariate and multivariate models were used to analyse the response to hormonal treatment and the risk for developing distant metastasis. Age-adjusted odds ratios were calculated to evaluate prostate cancer risk. Our results showed that patients under ADT carrying the HIF1A +1772 T-allele have increased risk for developing distant metastasis (OR, 2.0; 95%CI, 1.1-3.9) and an independent 6-fold increased risk for resistance to ADT after multivariate analysis (OR, 6.0; 95%CI, 2.2-16.8). This polymorphism was not associated with increased risk for being diagnosed with prostate cancer (OR, 0.9; 95%CI, 0.7-1.2). The HIF1A +1772 genetic polymorphism predicts a more aggressive prostate cancer behaviour, supporting the involvement of HIF1a in prostate cancer biological progression and ADT resistance. Molecular profiles using hypoxia markers may help predict clinically relevant prostate cancer and response to ADT.