FIRST REPORT ON Cryptococcus neoformans IN PIGEON EXCRETA FROM PUBLIC AND RESIDENTIAL LOCATIONS IN THE METROPOLITAN AREA OF CUIABÁ, STATE OF MATO GROSSO, BRAZIL

SUMMARYCryptococcosis is a severe systemic mycosis caused by two species of Cryptococcus that affect humans and animals: C. neoformans and C. gattii. Cosmopolitan and emergent, the mycosis results from the interaction between a susceptible host and the environment. The occurrence of C. neoformanswas evaluated in 122 samples of dried pigeon excreta collected in 49 locations in the City of Cuiabá, State of Mato Grosso, Brazil, including public squares (n = 5), churches (n = 4), educational institutions (n = 3), health units (n = 8), open areas covered with asbestos (n = 4), residences (n = 23), factory (n = 1) and a prison (n = 1). Samples collected from July to December of 2010 were seeded on Niger seed agar (NSA). Dark brown colonies were identified by urease test, carbon source assimilation tests and canavanine-glycine-bromothymol blue medium. Polymerase chain reaction primer pairs specific for C. neoformans were also used for identification. Cryptococcus neoformans associated to pigeon excreta was isolated from eight (6.6%) samples corresponding to six (12.2%) locations.Cryptococcus neoformans was isolated from urban areas, predominantly in residences, constituting a risk of acquiring the disease by immunocompromised and immunocompetent individuals.

DISTRIBUTION OF DERMATOPHYTES FROM SOILS OF URBAN AND RURAL AREAS OF CITIES OF PARAIBA STATE, BRAZIL

SUMMARYThe dermatophytes, keratinophilic fungi, represent important microorganisms of the soil microbiota, where there are cosmopolitan species and others with restricted geographic distribution. The aim of this study was to broaden the knowledge about the presence of dermatophytes in soils of urban (empty lots, schools, slums, squares, beaches and homes) and rural areas and about the evolution of their prevalence in soils of varying pH in cities of the four mesoregions of Paraiba State, Brazil. Soil samples were collected from 31 cities of Paraiba State. Of 212 samples, 62% showed fungal growth, particularly those from the Mata Paraibana mesoregion (43.5%), which has a tropical climate, hot and humid. Soil pH varied from 4.65 to 9.06, with 71% of the growth of dermatophytes occurring at alkaline pH (7.02 - 9.06) (ρ = 0.000). Of 131 strains isolated, 57.3% were geophilic species, particularly Trichophyton terrestre(31.3%) and Mycrosporum gypseum(21.4%). M. nanum and T. ajelloi were isolated for the first time in Paraiba State. The zoophilic species identified were T. mentagrophytes var.mentagrophytes (31.3 %) and T. verrucosum (7.6 %), and T. tonsurans was isolated as an anthropophilic species. The soils of urban areas including empty lots, schools, slums and squares of cities in the mesoregions of Paraiba State were found to be the most suitable reservoirs for almost all dermatophytes; their growth may have been influenced by environmental factors, soils with residues of human and/or animal keratin and alkaline pH.

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.

Basal temperature and thermal sum in phenological phases of nectarine and peach cultivars

The objective of this work was to evaluate basal temperature, thermal sum at different phenological stages, phenological phase duration, yield and seasonality of one nectarine and 14 peach cultivars, between 2006 and 2009. The considered phenological phases were: pruning-sprouting; sprouting-flowering, from swollen bud to open flower; flowering-fruiting, from petal fall to medium-sized fruit; and ripening. Minimum basal temperatures (Tb) obtained were: pruning-sprouting, 8°C, irrespective of the cultivars; sprouting-flowering, 10°C, except for 'Cascata 968', which required 8°C Tb; flowering-fruiting, 12°C, except for 'Oro Azteca', which required 14°C Tb; ripening, 14°C, except for 'Sunblaze', 'Diamante Mejorado' and 'Precocinho' with 12°C Tb. For most cultivars, the maximum basal temperatures were 30, 34, 34 and 28ºC for phases pruning-sprouting, sprouting-flowering, flowering-fruiting and ripening, respectively. 'Turmalina', 'Marli' and 'Tropic Beauty' showed average yields of 3,945.0, 3,969.3 and 3,954.0 kg ha-1, respectively, in 2009, while the nectarine 'Sunblaze' showed around 3,900 kg ha-1 in 2008 and 2009. The cultivars differed for their total cycle and for the accumulated thermal sums which varied, respectively, from 245 days and 1,881.4 degree-days for 'Oro Azteca', to144 days and 1,455.7 degree-days for 'Precocinho'.

Simultaneous spectrophotometric determination of ezetimibe and simvastatin in pharmaceutical preparations using chemometric techniques

Two spectrophotometric methods are described for the simultaneous determination of ezetimibe (EZE) and simvastatin (SIM) in pharmaceutical preparations. The obtained data was evaluated by using two different chemometric techniques, Principal Component Regression (PCR) and Partial Least-Squares (PLS-1). In these techniques, the concentration data matrix was prepared by using the mixtures containing these drugs in methanol. The absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbances in the range of 240 - 300 nm in the intervals with Δλ = 1 nm at 61 wavelengths in their zero order spectra, then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of EZE and SIM in their mixture. The procedure did not require any separation step. The linear range was found to be 5 - 20 µg mL-1 for EZE and SIM in both methods. The accuracy and precision of the methods were assessed. These methods were successfully applied to a pharmaceutical preparation, tablet; and the results were compared with each other.

Quantitative structure-retention relationships analysis of retention index of essential oils

Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.

Least squares regression with errors in both variables: case studies

Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.

Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectroscopy and chemometric techniques for the determination of adulteration in petrodiesel/biodiesel blends

We propose an analytical method based on fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectroscopy to detect the adulteration of petrodiesel and petrodiesel/palm biodiesel blends with African crude palm oil. The infrared spectral fingerprints from the sample analysis were used to perform principal components analysis (PCA) and to construct a prediction model using partial least squares (PLS) regression. The PCA results separated the samples into three groups, allowing identification of those subjected to adulteration with palm oil. The obtained model shows a good predictive capacity for determining the concentration of palm oil in petrodiesel/biodiesel blends. Advantages of the proposed method include cost-effectiveness and speed; it is also environmentally friendly.

UV determination of epinephrine, uric acid, and acetaminophen in pharmaceutical formulations and some human body fluids using multivariate calibration

In this work, a spectrophotometric methodology was applied in order to determine epinephrine (EP), uric acid (UA), and acetaminophen (AC) in pharmaceutical formulations and spiked human serum, plasma, and urine by using a multivariate approach. Multivariate calibration methods such as partial least squares (PLS) methods and its derivates were used to obtain a model for simultaneous determination of EP, UA and AC with good figures of merit and mixture design was in the range of 1.8 - 35.3, 1.7 - 16.8, and 1.5 - 12.1 µg mL-1. The 2nd derivate PLS showed recoveries of 95.3 - 103.3, 93.3 - 104.0, and 94.0 - 105.5 µg mL-1 for EP, UA, and AC, respectively.

VIS-NIR SPECTROMETRY, SOIL PHOSPHATE EXTRACTION METHODS AND INTERACTIONS OF SOIL ATTRIBUTES

The objective of this study was to evaluate the relationships between the spectra in the Vis-NIR range and the soil P concentrations obtained from the PM and Prem extraction methods as well as the effects of these relationships on the construction of models predicting P concentration in Oxisols. Soil samples' spectra and their PM and Prem extraction solutions were determined for the Vis-NIR region between 400 and 2500 nm. Mineralogy and/or organic matter content act as primary attributes allowing correlation of these soil phosphorus fractions with the spectra, mainly at wavelengths between 450-550, 900-1100 nm, near 1400 nm and between 2200-2300 nm. However, the regression models generated were not suitable for quantitative phosphate analysis. Solubilization of organic matter and reactions during the PM extraction process hindered correlations between the spectra and these P soil fractions. For Prem,, the presence of Ca in the extractant and preferential adsorption by gibbsite and iron oxides, particularly goethite, obscured correlations with the spectra.

SIMULTANEOUS DETERMINATION OF PROTOCATECHUIC ALDEHYDE AND PROTOCATECHUIC ACID USING THE LOCALIZED SURFACE PLASMON RESONANCE PEAK OF SILVER NANOPARTICLES AND CHEMOMETRIC METHODS

A simple and sensitive spectrophotometric method is proposed for the simultaneous determination of protocatechuic acid and protocatechuic aldehyde. The method is based on the difference in the kinetic rates of the reactions of analytes with [Ag(NH3)2]+ in the presence of polyvinylpyrrolidone to produce silver nanoparticles. The data obtained were processed by chemometric methods using principal component analysis artificial neural network and partial least squares. Excellent linearity was obtained in the concentration ranges of 1.23-58.56 µg mL-1 and 0.08-30.39 µg mL-1 for PAC and PAH, respectively. The limits of detection for PAC and PAH were 0.039 and 0.025 µg mL-1, respectively.

APPLICATION OF PARAFAC AND OPLS-DA ANALYSES ON HPLC FINGERPRINTS FOR THE CHARACTERIZATION OF Hibiscus sabdariffaCALYXES

The calyxes of Hibiscus sabdariffa are used in traditional medicine around the world. However, quality assurance protocols and chemical variability have not been previously analyzed. In the present study, chemical characterization of a set of samples of H. sabdariffa calyxes commercialized in Colombia was accomplished with the aim to explore the chemical variability among them. Chemometrics-based analyses on the data obtained from the HPLC-UV-DAD-derived profiles were then performed. Thus, the pre-processed single-wavelength data were subjected to principal component analysis (PCA). The PCA-derived results evidenced different groups which were well-correlated to the corresponding total phenolic and total anthocyanin contents. Multi-wavelength chromatographic (HPLC-UV-DAD surfaces) data were additionally examined via parallel factor analysis (PARAFAC) as data reduction method and the obtained loadings were subsequently submitted to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). Results were thus consistent with those from single-wavelength data. PCA loadings were employed to determine those chemical components responsible for the data variance and OPLS-DA model, constructed from PARAFAC loadings, and indicated differentiation according total anthocyanin contents among samples. The present chemometric analysis therefore demonstrated to be an excellent tool for differentiation of H. sabdariffacalyxes according to their chemical composition.

Characteristics of pyridine adsorption on Au(111) and Au(210) by EIS parameters fitting procedure

Some aspects of the application of electrochemical impedance spectroscopy to studies of solid electrode / solution interface, in the absence of faradaic processes, are analysed. In order to perform this analysis, gold electrodes with (111) and (210) crystallographic orientations in an aqueous solution containing 10 mmol dm-3 KF, as supporting electrolyte, and a pyridine concentration varying from 0.01 to 4.6 mmol dm-3, were used. The experimental data was analysed by using EQUIVCRT software, which utilises non-linear least squares routines, attributing to the solid electrode / solution interface behaviour described by an equivalent circuit with a resistance in series with a constant phase element. The results of this fitting procedure were analysed by the dependence on the electrode potential on two parameters: the pre-exponential factor, Y0, and the exponent n f, related with the phase angle shift. By this analysis it was possible to observe that the pyridine adsorption is strongly affected by the crystallographic orientation of the electrode surface and that the extent of deviation from ideal capacitive behaviour is mainly of interfacial origin.

Determination of sulfur in diesel using ATR/FTIR and multivariate calibration

The aim of this present work was to provide a more fast, simple and less expensive to analyze sulfur content in diesel samples than by the standard methods currently used. Thus, samples of diesel fuel with sulfur concentrations varying from 400 and 2500 mgkg-1 were analyzed by two methodologies: X-ray fluorescence, according to ASTM D4294 and by Fourier transform infrared spectrometry (FTIR). The spectral data obtained from FTIR were used to build multivariate calibration models by partial least squares (PLS). Four models were built in three different ways: 1) a model using the full spectra (665 to 4000 cm-1), 2) two models using some specific spectrum regions and 3) a model with variable selected by classic method of variable selection stepwise. The model obtained by variable selection stepwise and the model built with region spectra between 665 and 856 cm-1 and 1145 and 2717 cm-1 showed better results in the determination of sulfur content.

Volume of polyethylene bags for development of papaya seedlings in protected environments

The objective of this study was to test container of polyethylene bags and protected environments on the papaya seedlings production, from May to August of 2008, in Aquidauana state of Mato Grosso do Sul (MS), Brazil. Five bags of polyethylene were used: 7.5 cm x 11.5 cm, 205.9 cm³; 8.4 cm x 10.6 cm, 238.1cm³; 10.0 cm x 16.5 cm, 525.2 cm³; 12.0 cm x 12.0 cm, 550.0 cm³ and 15.0 cm x 21.5 cm, 1539.8 cm³. These containers were placed in three protected environments: greenhouse; screened nursery with Sombrite® and screened nursery with Aluminet®. Because there is no replication of growing environment, each one was considered an experiment. For each cultivation environment, it was adopted a completely randomized design with eight replications of two plants each. Initially, data were submitted to analysis of individual variance of the container (for each cultivation environment), then performing the evaluation of the residual mean squares and the combined analysis of these environments for comparison of protected environments. The greenhouse and nursery with thermal reflector screen produced the best seedlings. The bags of 15.0 x 21.5 cm produced the best papaya seedlings. The Dickson Quality Index pointed the nursery with screen of thermal reflector as the environment that produced the most vigorous seedlings, when using the best container.