Airborne fungi in the city of Porto Alegre, Rio Grande do Sul, Brazil

Knowledge of anemophilous fungi in a given city or region is important for the ecological diagnosis and specific treatment of allergic manifestations induced by inhaled allergens. In order to diagnose the presence of anemophilous fungi, several qualitative and quantitative techniques are used depending on the study place. This study of fungal air spores was performed with a Rotorod Sampler®, an equipment which samples the air through a plastic rod attached to an electric engine that makes it spin fast enough to collect the particles in the air. The samples were collected once a week during 24 hours using the standard cycle of the manufacturers. A total of 52 samples were obtained from April 2000 through March 2001. The results revealed prevalence of ascosporos (50.49%), Cladosporium (17.86%), Aspergillus/Penicillium (15.03%), basidiosporos (3.84%), rusts (3.82%), and Helminthosporium (2.49%), and a lesser frequency of Botrytis (1.22%), Alternaria (1.19%), smuts (0.90%), Curvularia (0.87%), Nigrospora (0.61%), and Fusarium (0.08%). Also, 1.59% of the spores detected here could not be identified by the systematic key used. More fungal spores were observed during the summer than during the autumn.

Airborne fungi isolated from Fortaleza city, State of Ceará, Brazil

Airbone fungi are considered important causes of allergic rhinitis and allergic asthma. The knowledge of these fungi in a city or region is important for the ecological diagnosis and specific treatment of allergic manifestations induced by inhalation of fungal allergens. The airborne fungi of Fortaleza, State of Ceará, Brazil, were studied during a one year period. Five hundred and twenty Petri dishes with Sabouraud dextrose agar medium were exposed at ten different locations in the city. The dishes exposed yielded one thousand and five hundred and twenty one colonies of twenty four genera. The most predominants were: Aspergillus (44.7%), Penicillium (13.3%), Curvularia (9.8%), Cladosporium (6.8%), Mycelia sterilia (6.0%), Fusarium (3.5%), Rhizopus (3.1%), Drechslera (2.6%), Alternaria (2.4%) and Absidia (2.2%). The results shown that Aspergillus, Penicillium, Mycelia sterilia, Fusarium and Alternaria were found during all months in the year. Absidia was more frequent during the dry season. Anemophilous fungi and the high concentration of spores in the air are important because may result in an increased number of people with allergic respiratory disease.

Diversity and dynamics of airborne fungi in São Luis, State of Maranhão, Brazil

Introduction: This study aimed to identify airborne fungi in São Luis, Maranhão, Brazil, to determine the prevalent genera and to correlate these genera with the area and season. Methods: In total, 1,510 colony-forming units (CFUs) of airborne fungi were isolated from the north, south, east and west sides and from the center of the city from January to December 2007. The samples were collected on Petri dishes that were exposed to the fungi by the gravitational method. Results: Twenty genera of fungi were isolated; the most common were Aspergillus (33.5%), Penicillium (18.8%), Cladosporium (14.2%), Curvularia (10.6%) and Fusarium (7.6%). The CFUs of the fungi were statistically significant (p < 0.0001). Fungal biological diversity was present all year, without any large seasonal variations but with slight increases in May, August and September. Conclusions: The fungal genera identified in this study were correlated with natural systems and could be useful when evaluating the impact of environmental changes on the 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.

Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.

Estimation of soil moisture in the root-zone from remote sensing data

Field-based soil moisture measurements are cumbersome. Thus, remote sensing techniques are needed because allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. The objective of the study was to evaluate the accuracy of an empirical relationship to calculate soil moisture from remote sensing data of irrigated soils of the Apodi Plateau, in the Brazilian semiarid region. The empirical relationship had previously been tested for irrigated soils in Mexico, Egypt, and Pakistan, with promising results. In this study, the relationship was evaluated from experimental data collected from a cotton field. The experiment was carried out in an area of 5 ha with irrigated cotton. The energy balance and evaporative fraction (Λ) were measured by the Bowen ratio method. Soil moisture (θ) data were collected using a PR2 - Profile Probe (Delta-T Devices Ltd). The empirical relationship was tested using experimentally collected Λ and θ values and was applied using the Λ values obtained from the Surface Energy Balance Algorithm for Land (SEBAL) and three TM - Landsat 5 images. There was a close correlation between measured and estimated θ values (p<0.05, R² = 0.84) and there were no significant differences according to the Student t-test (p<0.01). The statistical analyses showed that the empirical relationship can be applied to estimate the root-zone soil moisture of irrigated soils, i.e. when the evaporative fraction is greater than 0.45.

Multispectral remote sensing for site-specific nitrogen fertilizer management

The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R²=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

ANION-BINDING AND SENSING PROPERTIES OF NOVEL RECEPTORS BASED ON N-(INDOL-3-YLGLYOXYLYL)BENZYLAMINE

Indole-based receptors such as biindole, carbazole, and indolocarbazole are regarded as some of the most favorable anion receptors in molecular recognition. This is because indole groups possess N–H groups as hydrogen-bonding donors. The introduction of amide groups in the indole framework can induce strong binding properties and good water solubility. In this study, we designed and synthesized a series of N-(indol-3-ylglyoxylyl)benzylamine derivatives as novel and simple anion receptors. The receptors derived by aryl and aliphatic amines can selectively recognize F– based on a color change from colorless-to-yellow in DMSO. The receptors derived by hydrazine hydrate can recognize F–, AcO–, and H2PO4– by similar color changes in DMSO and can even enable the selective recognition of F– in a DMSO–H2O binary solution by the naked eye. Spectrographic data indicate that complexes are formed between receptors and anions through multiple hydrogen-bonding interactions in dual solutions.

Factors affecting density of airborne Gibberella zeae inoculum

Fusarium head blight (FHB) is a disease of increasing concern in the production of wheat (Triticum aestivum). This work studied some of the factors affecting the density of airborne Gibberella zeae inoculum. Spore samplers were placed at the edge of a field in order to observe spore deposition over a period of 45 days and nights in September and October, the period that coincides with wheat flowering. Gibberella zeae colonies were counted for each period and values transformed to relative density. A stepwise regression procedure was used to identify weather variables helpful in predicting spore cloud density. In general, a predominant night-time spore deposition was observed. Precipitation and daily mean relative humidity over 90% were the factors most hightly associated with peak events of spores in the air. Models for predicting spore cloud density simulated reasonably well with the fluctuation of airborne propagules during both night and day, with potential to be integrated into an FHB risk model framework.

Progress of Asian soybean rust and airborne urediniospores of Phakopsora pachyrhizi in southern Brazil

Asian soybean rust, caused by the fungus Phakopsora pachyrhizi, was reported at epidemic levels in 2003/2004 and is the main soybean disease in Brazil. The aim of this study was to investigate the spread of Asian soybean rust and to quantify airborne urediniospores in the region of Campo Mourão, Paraná State, Brazil. Three experiments were conducted under field conditions during the 2007/08 and 2008/09 crop seasons. Using the disease gradient method, provided by the application of increasing levels of the fungicide tebuconazole, four Asian soybean rust epidemics at different intensities were obtained in each experiment. To quantify the urediniospores, weathercock-type spore collectors were installed during and between the two crop seasons. Disease progress curves were plotted for each epidemic, and maximum severity was estimated. The curves were fit to the logistic model, which provided higher coefficients of determination and more randomly distributed residuals plotted over time. Analyses of the area under the disease progress curve showed that the largest epidemics occurred in the 2007/2008 crop season and that the progress rates were higher for severity, even among plants protected with the fungicide. The number of urediniospores collected in the air was related to the presence of soybean plants in the cultivated crops. The quantity of urediniospores was also positively correlated to the disease severity and incidence, as well as to cumulative rainfall and favorable days for P. Pachyrhizi infection.

Using an aerial system of remote sensing to detect different nutritional status in Brachiaria decumbens

The aim of this study was to use digital images acquired by cameras attached to a helium balloon to detect variation of the nutritional status in Brachiaria decumbens. The treatments consisted of five doses of nitrogen (0, 50, 100, 150 e 200kg ha-1) with six replications each, evaluated in a completely randomized statistical design. A remote sensing system composed of digital cameras and microcomputers was used for image acquisition, and a helium balloon lifted the cameras to the heights of 15, 20, 25 and 30m. A portable chlorophyll meter and analyses of leaf nitrogen content were used to make comparisons with data obtained by the remote sensing system. Data was acquired in two phases, in different climatic conditions. At the end of each phase, dry matter production was measured. Three vegetation indices were used to evaluate the detection of different nutritional status. The three indices were able to detect the effects of N doses. The indices constructed with the Green spectral band showed to be more efficient.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Extracellular calcium-sensing receptor: structural and functional features and association with diseases

The recently cloned extracellular calcium-sensing receptor (CaR) is a G protein-coupled receptor that plays an essential role in the regulation of extracellular calcium homeostasis. This receptor is expressed in all tissues related to this control (parathyroid glands, thyroid C-cells, kidneys, intestine and bones) and also in tissues with apparently no role in the maintenance of extracellular calcium levels, such as brain, skin and pancreas. The CaR amino acid sequence is compatible with three major domains: a long and hydrophilic aminoterminal extracellular domain, where most of the activating and inactivating mutations described to date are located and where the dimerization process occurs, and the agonist-binding site is located, a hydrophobic transmembrane domain involved in the signal transduction mechanism from the extracellular domain to its respective G protein, and a carboxyterminal intracellular tail, with a well-established role for cell surface CaR expression and for signal transduction. CaR cloning was immediately followed by the association of genetic human diseases with inactivating and activating CaR mutations: familial hypocalciuric hypercalcemia and neonatal severe hyperparathyroidism are caused by CaR-inactivating mutations, whereas autosomal dominant hypoparathyroidism is secondary to CaR-activating mutations. Finally, we will comment on the development of drugs that modulate CaR function by either activating (calcimimetic drugs) or antagonizing it (calcilytic drugs), and on their potential therapeutic implications, such as medical control of specific cases of primary and uremic hyperparathyroidism with calcimimetic drugs and a potential treatment for osteoporosis with a calcilytic drug.

Comparative performance of two air samplers for monitoring airborne fungal propagules

Many studies have attempted to evaluate the importance of airborne fungi in the development of invasive fungal infection, especially for immunocompromised hosts. Several kinds of instruments are available to quantitate fungal propagule levels in air. We compared the performance of the most frequently used air sampler, the Andersen sampler with six stages, with a portable one, the Reuter centrifugal sampler (RCS). A total of 84 samples were analyzed, 42 with each sampler. Twenty-eight different fungal genera were identified in samples analyzed with the Andersen instrument. In samples obtained with the RCS only seven different fungal genera were identified. The three most frequently isolated genera in samples analyzed with both devices were Penicillium, Aspergillus and Cladophialophora. In areas supplied with a high efficiency particulate air filter, fungal spore levels were usually lower when compared to areas without these filters. There was a significant correlation between total fungal propagule measurements taken with both devices on each sampling occasion (Pearson coefficient = 0.50). However, the Andersen device recovered a broader spectrum of fungi. We conclude that the RCS can be used for quantitative estimates of airborne microbiological concentrations. For qualitative studies, however, this device cannot be recommended.

An acid-sensing ion channel that detects ischemic pain

Ischemic pain occurs when there is insufficient blood flow for the metabolic needs of an organ. The pain of a heart attack is the prototypical example. Multiple compounds released from ischemic muscle likely contribute to this pain by acting on sensory neurons that innervate muscle. One such compound is lactic acid. Here, we show that ASIC3 (acid-sensing ion channel #3) has the appropriate expression pattern and physical properties to be the detector of this lactic acid. In rats, it is expressed only in sensory neurons and then only on a minority (~40%) of these. Nevertheless, it is expressed at extremely high levels on virtually all dorsal root ganglion sensory neurons that innervate the heart. It is extraordinarily sensitive to protons (Hill slope 4, half-activating pH 6.7), allowing it to readily respond to the small changes in extracellular pH (from 7.4 to 7.0) that occur during muscle ischemia. Moreover, both extracellular lactate and extracellular ATP increase the sensitivity of ASIC3 to protons. This final property makes ASIC3 a "coincidence detector" of three molecules that appear during ischemia, thereby allowing it to better detect acidosis caused by ischemia than other forms of systemic acidosis such as hypercapnia.