Replication of dengue viruses in mosquito cell cultures: a model from ultrastructural observations

Mosquito cell cultures infected with human sera from dengue-1 and dengue-2 outbreaks, started in Rio de Janeiro by 1986 and 1990 respectively, were examined by electron microscopy at different times post the infection of cell cultures. More information was obtained about cell penetration of virus particles in the presence or not of antibodies, their pathway inside the cells, replication mode and exit. Infectiveness of the virus at those different stages can only be attributed to the particles appearing inside the trans-Golgi vesicles; most of all newly formed virus particles remain inside the RER-derived cell vesicles or inside lysosomes, even during cell lysis. Groups of larges particles, 65-75 nm in diameter at dengue-2 infections, persist during cell passage. The large amounts of smooth membrane structures, as vesicles or tabules inside the RER are attributed to a cell response to viral infection.

Recent advances and prospective researches on molecular epidemiology of dengue viruses

The determination of amino acid changes in the envelop protein by direct sequencing of either genomic RNA or PCR-amplified cDNA fragments provides useful informations for assessing the genetic variability and the geographic distribution of the actually most widespread dengue-2 serotype. The possible link of variations in the envelope protein-gene and virus virulence is discussed.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Ultrastructural aspects of virus replication in one fatal case and several other isolates from a dengue type 2 outbreak in Rio de Janeiro

Dengue virus replication in mosquito cell cultures was observed by electron microscopy in one fatal and 40 classical isolates from a dengue type 2 outbreak in Rio de Janeiro and compared with the prototype New Guinea C strain. All the Brazilian isolates presented, beside the classical structured dengue virus particles, fuzzy coated virus-like particles, never observed in thereferencial New Guinea C virus strain. more numerous DEN-2 virus particles, fuzzy coated virus-like particles, defective virus particles and smooth membrane structures inside the rough endoplasmic reticulum characterized the unique fatal isolate examined.

Cytokine responses to Dengue Infection among Puerto Rican Patients

Recently, a strong correlation between high concentration of tumor necrosis factor (TNFalpha) in blood and severity of dengue hemorrhagic fever/dengue shock syndrome has been reported from Asia and the Pacific. We wished to determine if a similar relationship could be found in dengue patients in the Americas where adult patients with severe syndromes have been observed more frequently than in Asia where severe cases have been observed mostly among children. The concentrations of interleukin-1 (IL-1beta) in hospistalized adult groups were significantly lower than that in outpatient adults. In contrast, the levels of interleukin 6 (IL-6) were significantly higher in hospistalized adults and children than in the corresponding outpatients. Levels of TNFalpha were higher in hospistalized children than in outpatient children or hospistalized adults. There was no significant difference in the levels of these three cytokines among hospitalized patients with or without hemorrhagic manifestations. Thus, an elevated IL-6 level was positively associated with severity of dengue infection in both children and adults, but IL-1beta level was negatively associated with severity in adults.

Dengue in Brazil - situation, transmission and control: a proposal for ecological control

This article discusses dengue in terms of its conceptual and historical aspects, epidemiological and clinical/pathological nature, and evolution up to the present situation in Brazil. The author discusses the ecological relationship in both the production of dengue and its control. Comparison is made between traditional dengue-control programs and a proposed socially-controlled program of an ecological nature without the use of insecticides. Stress is placed on interdisciplinary technical and scientific activity, broadbased participation by communities in discussing methodological aspects involving them, and prospective evaluation comparing the communities selected for intervention and control communities with regard to clinical and subclinical dengue cases and vector infestation rates in relation to climatic, socio-economic, and behavioural factors.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

A Simple Reverse Transcription-Polymerase Chain Reaction for Dengue Type 2 Virus Identification

We show here a simplified reverse transcription-polymerase chain reaction (RT-PCR) for identification of dengue type 2 virus. Three dengue type 2 virus strains, isolated from Brazilian patients, and yellow fever vaccine 17DD, as a negative control, were used in this study. C6/36 cells were infected with the virus, and tissue culture fluids were collected after 7 days of infection period. The RT-PCR, a combination of RT and PCR done after a single addition of reagents in a single reaction vessel was carried out following a digestion of virus with 1% Nonidet P-40. The 50ml assay reaction mixture included 50 pmol of a dengue type 2 specific primer pair amplifying a 210 base pair sequence of the envelope protein gene, 0.1 mM of the four deoxynucleoside triphosphates, 7.5U of reverse transcriptase, and 1U of thermostable Taq DNA polymerase. The reagent mixture was incubated for 15 min at 37oC for RT followed by a variable amount of cycles of two-step PCR amplification (92oC for 60 sec, 53oC for 60 sec) with slow temperature increment. The PCR products were subjected to 1.7% agarose gel electrophoresis and visualized with UV light after gel incubation in ethidium bromide solution. DNA bands were observed after 25 and 30 cycles of PCR. Virus amount as low as 102.8 TCID50/ml was detected by RT-PCR. Specific DNA amplification was observed with the three dengue type 2 strains. This assay has advantages compared to other RT-PCRs: it avoids laborious extraction of virus RNA; the combination of RT and PCR reduces assay time, facilitates the performance and reduces risk of contamination; the two-step PCR cycle produces a clear DNA amplification, saves assay time and simplifies the technique

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.