Origem e implicações dos ácidos carboxílicos na atmosfera

A general overview about the ambient levels of low molecular weight carboxylic acids and their possible emission sources, as well as the implication of them in the atmosphere is presented. Carboxylic acids are considered to be one of the dominant classes of organic compounds found in the atmosphere in a variety of phases, such as in rainwater, snow and ice, on aerosol particles and gas phase. They may be originated from biogenic and anthropogenic direct emissions and by photochemical reaction in situ. Emission sources and formation mechanisms of organic acids in the atmosphere are discussed.

Oceanografia e Química: unindo conhecimentos em prol dos oceanos e da sociedade

The marine environment is certainly one of the most complex systems to study, not only because of the challenges posed by the nature of the waters, but especially due to the interactions of physical, chemical and biological processes that control the cycles of the elements. Together with analytical chemists, oceanographers have been making a great effort in the advancement of knowledge of the distribution patterns of trace elements and processes that determine their biogeochemical cycles and influences on the climate of the planet. The international academic community is now in prime position to perform the first study on a global scale for observation of trace elements and their isotopes in the marine environment (GEOTRACES) and to evaluate the effects of major global changes associated with the influences of megacities distributed around the globe. This action can only be performed due to the development of highly sensitive detection methods and the use of clean sampling and handling techniques, together with a joint international program working toward the clear objective of expanding the frontiers of the biogeochemistry of the oceans and related topics, including climate change issues and ocean acidification associated with alterations in the carbon cycle. It is expected that the oceanographic data produced this coming decade will allow a better understanding of biogeochemical cycles, and especially the assessment of changes in trace elements and contaminants in the oceans due to anthropogenic influences, as well as its effects on ecosystems and climate. Computational models are to be constructed to simulate the conditions and processes of the modern oceans and to allow predictions. The environmental changes arising from human activity since the 18th century (also called the Anthropocene) have made the Earth System even more complex. Anthropogenic activities have altered both terrestrial and marine ecosystems, and the legacy of these impacts in the oceans include: a) pollution of the marine environment by solid waste, including plastics; b) pollution by chemical and medical (including those for veterinary use) substances such as hormones, antibiotics, legal and illegal drugs, leading to possible endocrine disruption of marine organisms; and c) ocean acidification, the collateral effect of anthropogenic emissions of CO2 into the atmosphere, irreversible in the human life time scale. Unfortunately, the anthropogenic alteration of the hydrosphere due to inputs of plastics, metal, hydrocarbons, contaminants of emerging concern and even with formerly "exotic" trace elements, such us rare earth elements is likely to accelerate in the near future. These emerging contaminants would likely soon present difficulties for studies in pristine environments. All this knowledge brings with it a great responsibility: helping to envisage viable adaptation and mitigation solutions to the problems identified. The greatest challenge faced by Brazil is currently to create a framework project to develop education, science and technology applied to oceanography and related areas. This framework would strengthen the present working groups and enhance capacity building, allowing a broader Brazilian participation in joint international actions and scientific programs. Recently, the establishment of the National Institutes of Science and Technology (INCTs) for marine science, and the creation of the National Institute of Oceanographic and Hydrological Research represent an exemplary start. However, the participation of the Brazilian academic community in the latest assaults on the frontier of chemical oceanography is extremely limited, largely due to: i. absence of physical infrastructure for the preparation and processing of field samples at ultra-trace level; ii. limited access to oceanographic cruises, due to the small number of Brazilian vessels and/or absence of "clean" laboratories on board; iii. restricted international cooperation; iv. limited analytical capacity of Brazilian institutions for the analysis of trace elements in seawater; v. high cost of ultrapure reagents associated with processing a large number of samples, and vi. lack of qualified technical staff. Advances in knowledge, analytic capabilities and the increasing availability of analytical resources available today offer favorable conditions for chemical oceanography to grow. The Brazilian academic community is maturing and willing to play a role in strengthening the marine science research programs by connecting them with educational and technological initiatives in order to preserve the oceans and to promote the development of society.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Population Dynamics Modeling of Arapaima gigas

Pirarucu (Arapaima gigas) has been of the most important natural fishing resources of the Amazon region. Due to its economic importance, and the necessity to preserve the species hand, field research concerning the habits and behavior of the pirarucu has been increasing for the last 20 years. The aim of this paper is to present a mathematical model for the pirarucu population dynamics considering the species peculiarities, particularly the male parental care over the offspring. The solution of the dynamical systems indicates three possible equilibrium points for the population. The first corresponds to extinction; the third corresponds to a stable population close to the environmental carrying capacity. The second corresponds to an unstable equilibrium located between extinction and full use of the carrying capacity. It is shown that lack of males’ parental care closes the gap between the point corresponding to the unstable equilibrium and the point of stable non-trivial equilibrium. If guarding failure reaches a critical point the two points coincide and the population tends irreversibly to extinction. If some event tends to destabilize the population equilibrium, as for instance inadequate parental care, the model responds in such a way as to restore the trajectory towards the stable equilibrium point avoiding the route to extinction. The parameters introduced to solve the system of equations are partially derived from limited but reliable field data collected at the Mamirauá Sustainable Development Reserve (MSDR) in the Brazilian Amazonian Region.

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Effects of anthropogenic impacts on benthic macroinvertebrates assemblages in subtropical mountain streams

The nature of the riparian and surrounding landscape has been modified by anthropogenic activities, which may subsequently alter the composition and functional structure of macroinvertebrate assemblages. The effect of these changes on function of benthic fauna is difficult to assess due to the scarce knowledge on functional structures in tropical streams. In this study we evaluate whether sites impacted and unimpacted by anthropogenic alterations differed in assemblage composition and density, richness and diversity of each functional feeding group. The selection of the sites was related to their distinct riparian characteristics, following the QBRy riparian quality index. Collector-gatherer was the dominant functional feeding group, comprising 91% of total density, whereas the proportion of shredders was very low, representing less of 0.5% of total density. Asemblage composition of macroinvertebrates differed between impacted and unimpacted sites. Predators were dominant in taxa number, representing about 60% of total taxa richness. In addition, the diversity and richness of collector-gatherers differed significantly between degraded and unimpacted sites, reflecting the sensitivity of this group to environmental changes and the utility to be used in the assessment of anthropogenic modifications. The results of this study reinforce the idea that riparian corridor management is critical for the distribution of macroinvertebrate assemblages as well as functional organization of lotic streams.

Modeling AIDS vaccines: the cellular level

This paper discuses current strategies for the development of AIDS vaccines wich allow immunzation to disturb the natural course of HIV at different detailed stages of its life cycle. Mathematical models describing the main biological phenomena (i.e. virus and vaccine induced T4 cell growth; virus and vaccine induced activation latently infected T4 cells; incremental changes immune response as infection progress; antibody dependent enhancement and neutralization of infection) and allowing for different vaccination strategies serve as a backgroud for computer simulations. The mathematical models reproduce updated information on the behavior of immune cells, antibody concentrations and free viruses. The results point to some controversial outcomes of an AIDS vaccine such as an early increase in virus concentration among vaccinated when compared to nonvaccinated individuals.

The stabilizing effects of the acquired immunity on the schistosomiasis transmission modeling - the sensitivity Analysis

A mathematical model is proposed to analyze the effects of acquired immunity on the transmission of schistosomiasis in the human host. From this model the prevalence curve dependent on four parameters can be obtained. These parameters were estimated fitting the data by the maximum likelihood method. The model showed a good retrieving capacity of real data from two endemic areas of schistosomiasis: Touros, Brazil (Schistosoma mansoni) and Misungwi, Tanzania (S. haematobium). Also, the average worm burden per person and the dispersion of parasite per person in the community can be obtained from the model. In this paper, the stabilizing effects of the acquired immunity assumption in the model are assessed in terms of the epidemiological variables as follows. Regarded to the prevalence curve, we calculate the confidence interval, and related to the average worm burden and the worm dispersion in the community, the sensitivity analysis (the range of the variation) of both variables with respect to their parameters is performed.

Molecular Modeling Approaches for Determining Gene Function: application to a Putative Poly-A Binding Protein from Leishmania amazonensis (LaPABP)

The great expansion in the number of genome sequencing projects has revealed the importance of computational methods to speed up the characterization of unknown genes. These studies have been improved by the use of three dimensional information from the predicted proteins generated by molecular modeling techniques. In this work, we disclose the structure-function relationship of a gene product from Leishmania amazonensis by applying molecular modeling and bioinformatics techniques. The analyzed sequence encodes a 159 aminoacids polypeptide (estimated 18 kDa) and was denoted LaPABP for its high homology with poly-A binding proteins from trypanosomatids. The domain structure, clustering analysis and a three dimensional model of LaPABP, basically obtained by homology modeling on the structure of the human poly-A binding protein, are described. Based on the analysis of the electrostatic potential mapped on the model's surface and conservation of intramolecular contacts responsible for folding stabilization we hypothesize that this protein may have less avidity to RNA than it's L. major counterpart but still account for a significant functional activity in the parasite. The model obtained will help in the design of mutagenesis experiments aimed to elucidate the mechanism of gene expression in trypanosomatids and serve as a starting point for its exploration as a potential source of targets for a rational chemotherapy.

Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

Schistosoma mansoni major egg antigen Smp40: molecular modeling and potential immunoreactivity for anti-pathology vaccine development

The pathogenesis of Schistosoma mansoni infection is largely determined by host T-cell mediated immune responses such as the granulomatous response to tissue deposited eggs and subsequent fibrosis. The major egg antigens have a valuable role in desensitizing the CD4+ Th cells that mediate granuloma formation, which may prevent or ameliorate clinical signs of schistosomiasis.S. mansoni major egg antigen Smp40 was expressed and completely purified. It was found that the expressed Smp40 reacts specifically with anti-Smp40 monoclonal antibody in Western blotting. Three-dimensional structure was elucidated based on the similarity of Smp40 with the small heat shock protein coded in the protein database as 1SHS as a template in the molecular modeling. It was figured out that the C-terminal of the Smp40 protein (residues 130 onward) contains two alpha crystallin domains. The fold consists of eight beta strands sandwiched in two sheets forming Greek key. The purified Smp40 was used for in vitro stimulation of peripheral blood mononuclear cells from patients infected with S. mansoni using phytohemagglutinin mitogen as a positive control. The obtained results showed that there is no statistical difference in interferon-g, interleukin (IL)-4 and IL-13 levels obtained with Smp40 stimulation compared with the control group (P > 0.05 for each). On the other hand, there were significant differences after Smp40 stimulation in IL-5 (P = 0.006) and IL-10 levels (P < 0.001) compared with the control group. Gaining the knowledge by reviewing the literature, it was found that the overall pattern of cytokine profile obtained with Smp40 stimulation is reported to be associated with reduced collagen deposition, decreased fibrosis, and granuloma formation inhibition. This may reflect its future prospect as a leading anti-pathology schistosomal vaccine candidate.

Anthropogenic influence on the distribution, abundance and diversity of sandfly species (Diptera: Phlebotominae: Psychodidae), vectors of cutaneous leishmaniasis in Panama

In Panama, species of the genus Lutzomyia are vectors of American cutaneous leishmaniasis (ACL). There is no recent ecological information that may be used to develop tools for the control of this disease. Thus, the goal of this study was to determine the composition, distribution and diversity of Lutzomyia species that serve as vectors of ACL. Sandfly sampling was conducted in forests, fragmented forests and rural environments, in locations with records of ACL. Lutzomyia gomezi, Lutzomyia panamensis and Lutzomyia trapidoi were the most widely distributed and prevalent species. Analysis of each sampling point showed that the species abundance and diversity were greatest at points located in the fragmented forest landscape. However, when the samples were grouped according to the landscape characteristics of the locations, there was a greater diversity of species in the rural environment locations. The Kruskal Wallis analysis of species abundance found that Lu. gomezi and Lu. trapidoi were associated with fragmented environments, while Lu. panamensis, Lutzomyia olmeca bicolor and Lutzomyia ylephiletor were associated with forested environments. Therefore, we suggest that human activity influences the distribution, composition and diversity of the vector species responsible for leishmaniasis in Panama.

Soil organic matter and fertility of anthropogenic dark earths (Terra Preta de Índio) in the Brazilian Amazon basin

Fertility properties, total C (Ctot), and chemical soil organic matter fractions (fulvic acid fraction - FA, humic acid fraction - HA, humin fraction - H) of anthropogenic dark earths (Terra Preta de Índio) of the Amazon basin were compared with those of Ferralsols with no anthropogenic A horizon. Terra Preta soils had a higher fertility (pH: 5.1-5.4; Sum of bases, SB: 8.93-10.33 cmol c kg-1 , CEC: 17.2-17.5 cmol c kg-1 , V: 51-59 %, P: 116-291 mg kg-1) and Ctot (44.6-44.7 g kg-1) than adjacent Ferralsols (pH: 4.4; SB: 2.04 cmol c kg-1, CEC: 9.5 cmol c kg-1, V: 21 %, P 5 mg kg-1, C: 37.9 g kg-1). The C distribution among humic substance fractions (FA, HA, H) in Terra Preta soils was also different, as shown by the ratios HA:FA and EA/H (EA=HA+FA) (2.1-3.0 and 1.06-1.08 for Terra Preta and 1.2 and 0.72 for Ferralsols, respectively). While the cation exchange capacity (CEC), of Ferralsols correlated with FA (r = 0.97), the CEC of Terra Preta correlated with H (r = 0.82). The correlation of the fertility of Terra Preta with the highly stable soil organic matter fraction (H) is highly significant for the development of sustainable soil fertility management models in tropical ecosystems.

Diagnostic techniques applied in geostatistics for agricultural data analysis

The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.