Separação de espectros simulados e de luminescência total através do método generalizado de anulação do posto (GRAM)

A multivariate curve resolution method, "GENERALIZED RANK ANNIHILATION METHOD (GRAM)", is discussed and tested with simulated and experimental data. The analysis of simulated data provides general guidelines concerning the condition for uniqueness of a solution for a given problem. The second-order emission-excitation spectra of human and animal dental calculus deposits were used as an experimental data to estimate the performance of the above method. Three porphyrinic spectral profiles, for both human and cat, were obtained by the use of GRAM.

Resolução multivariada de curvas com mínimos quadrados alternantes: descrição, funcionamento e aplicações

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a resolution method that has been efficiently applied in many different fields, such as process analysis, environmental data and, more recently, hyperspectral image analysis. When applied to second order data (or to three-way data) arrays, recovery of the underlying basis vectors in both measurement orders (i.e. signal and concentration orders) from the data matrix can be achieved without ambiguities if the trilinear model constraint is considered during the ALS optimization. This work summarizes different protocols of MCR-ALS application, presenting a case study: near-infrared image spectroscopy.

A simple RT-PCR-based strategy for screening connexin identity

Vertebrate gap junctions are aggregates of transmembrane channels which are composed of connexin (Cx) proteins encoded by at least fourteen distinct genes in mammals. Since the same Cx type can be expressed in different tissues and more than one Cx type can be expressed by the same cell, the thorough identification of which connexin is in which cell type and how connexin expression changes after experimental manipulation has become quite laborious. Here we describe an efficient, rapid and simple method by which connexin type(s) can be identified in mammalian tissue and cultured cells using endonuclease cleavage of RT-PCR products generated from "multi primers" (sense primer, degenerate oligonucleotide corresponding to a region of the first extracellular domain; antisense primer, degenerate oligonucleotide complementary to the second extracellular domain) that amplify the cytoplasmic loop regions of all known connexins except Cx36. In addition, we provide sequence information on RT-PCR primers used in our laboratory to screen individual connexins and predictions of extension of the "multi primer" method to several human connexins.

Evaluation of pesticide residues in oranges from São Paulo, Brazil

Pesticides in “PERA” orange samples (N = 57) from São Paulo City, Brazil were assessed and the pesticide intake contribution was estimated for chronic risk assessment. Seventy-six pesticides were evaluated by the gas chromatography multi-residue method, including isomers and metabolites (4.332 determinations). The mean recoveries at the limit of quantification level were in the range of 72-115% and the relative standard deviation for five replicate samples was 1-11%. The limits of detection and quantification ranged from 0.005 to 0.4 mg.kg−1 and from 0.01 to 0.8 mg.kg−1, respectively. Pesticides were found in 42.1% of the samples at levels ranging from 0.06 to 2.9 mg.kg−1. Of the contaminated samples, 3.5% contained residues (bifenthrin and clofentezine) above the maximum residue level and 12.3% contained unauthorized pesticides (azinphos-ethyl, parathion, myclobutanil, profenofos, and fenitrothion). The estimated risk characterization for orange intake by adults and children, respectively, ranged from 0.04 to 6.6% and from 0.1 to 26.5% of the acceptable daily intake. The detection of irregular residues emphasizes the need for better implementation of Good Agriculture Practices and greater control of formulated products. Other pesticides surveyed did not pose a health risk due to consumption.

Banco Nacional: jogo de Ponzi, PROER e FCVS

Banco Nacional: Ponzi game, PROER and FCVS. This paper analyses the causes of the failure of Banco Nacional and the resolution method adopted by the Brazilian central bank. The program (PROER) designed by the central bank and its legal framework allowed the failed bank to buy " defaulted securities" , financed by the central bank, and to use them as borrowing collateral. The paper also analyses the private and social costs of this bank failure.

Persistent asthma in adults: comparison of high resolution computed tomography of the lungs after one year of follow-up

OBJECTIVE: The aims of this study were to evaluate the role of high resolution computed tomography of the torax in detecting abnormalities in chronic asthmatic patients and to determine the behavior of these lesions after at least one year. METHOD: Fourteen persistent asthmatic patients with a mean forced expiratory volume in 1-second that was 63% of predicted and a mean forced expiratory volume in 1-second /forced vital capacity of 60% had two high resolution computed tomographys separated by an interval of at least one year. RESULTS: All 14 patients had abnormalities on both scans. The most common abnormality was bronchial wall thickening, which was present in all patients on both computed tomographys. Bronchiectasis was suggested on the first computed tomography in 5 of the 14 (36%) patients, but on follow-up, the bronchial dilatation had disappeared in 2 and diminished in a third. Only one patient had any emphysematous changes; a minimal persistent area of paraseptal emphysema was present on both scans. In 3 patients, a "mosaic" appearance was observed on the first scan, and this persisted on the follow-up computed tomography. Two patients had persistent areas of mucoid impaction. In a third patient, mucus plugging was detected only on the second computed tomography. CONCLUSIONS: We conclude that there are many abnormalities on the high resolution computed tomography of patients with persistent asthma. Changes suggestive of bronchiectasis, namely bronchial dilatation, frequently resolve spontaneously. Therefore, the diagnosis of bronchiectasis by high resolution computed tomography in asthmatic patients must be made with caution, since bronchial dilatation can be reversible or can represent false dilatation. Nonsmoking chronic asthmatic subjects in this study had no evidence of centrilobular or panacinar emphysema.

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Comparative analyses of classical phenotypic method and ribosomal RNA gene sequencing for identification of medically relevant Candida species

As the distribution of Candida species and their susceptibility to antifungal agents have changed, a new means of accurately and rapidly identifying these species is necessary for the successful early resolution of infection and the subsequent reduction of morbidity and mortality. The current work aimed to evaluate ribosomal RNA gene sequencing for the identification of medically relevant Candida species in comparison with a standard phenotypic method. Eighteen reference strains (RSs), 69 phenotypically identified isolates and 20 inconclusively identified isolates were examined. Internal transcribed spaces (ITSs) and D1/D2 of the 26S ribosomal RNA gene regions were used as targets for sequencing. Additionally, the sequences of the ITS regions were used to establish evolutionary relationships. The sequencing of the ITS regions was successful for 88% (94/107) of the RS and isolates, whereas 100% of the remaining 12% (13/107) of the samples were successfully analysed by sequencing the D1/D2 region. Similarly, genotypic analysis identified all of the RS and isolates, including the 20 isolates that were not phenotypically identified. Phenotypic analysis, however, misidentified 10% (7/69) of the isolates. Phylogenetic analysis allowed the confirmation of the relationships between evolutionarily close species. Currently, the use of genotypic methods is necessary for the correct identification of Candida species.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Development and validation of a high performance liquid chromatographic method for determination of cyclosporine-A from biodegradable intraocular implants

An HPLC method was developed and validated aiming to quantify the cyclosporine-A incorporated into intraocular implants, released from them; and in direct contact with the degradation products of PLGA. The separation was carried out in isocratic mode using acetonitrile/water (70:30) as mobile phase, a C18 column at 80 ºC and UV detection at 210 nm. The method provided selectivity based on resolution among peaks. It was linear over the range of 2.5-40.0 µg/mL. The quantitation and detection limits were 0.8 and 1.2 µg/mL, respectively. The recovery was 101.8% and intra-day and inter-day precision was close to 2%.

Set-up of a method using LC-UV to assay mometasone furoate in pharmaceutical dosage forms

A reliable method using LC-UV to assay mometasone furoate (MF) in creams or nasal sprays using the same chromatographic conditions was set up. Methanol:water 80:20 (v/v) (1.0 mL min-1) was used as mobile phase. MF was detected at 248 nm and analyzed in a concentration range from 1.0 to 20.0 µg mL-1. The method provided acceptable theoretical plates, peak simmetry, peak tailing factor and peak resolution a short run (5 min). The method showed specificity, good linearity (r = 0.9999) and the quantification limit was 0.379 µg mL-1. Furthermore, the method was precise (RSD < 2.0%), accurate (recovery > 97%) and robust.

Multi-component quantitation of loratadine, pseudoephedrine and paracetamol in plasma and pharmaceutical formulations with liquid chromatography-tandem mass spectrometry utilizing a monolithic column

The purpose of this study was to develop a rapid, simple and sensitive quantitation method for pseudoephedrine (PSE), paracetamol (PAR) and loratadine (LOR) in plasma and pharmaceuticals using liquid chromatography-tandem mass spectrometry with a monolithic column. Separation was achieved using a gradient composition of methanol-0.1% formic acid at a flow rate of 1.0 mL min-1. Mass spectral transitions were recorded in SRM mode. System validation was evaluated for precision, specificity and linearity. Limit of detection for pseudoephedrine, paracetamol, and loratadine were determined to be 3.14, 1.86 and 1.44 ng mL-1, respectively, allowing easy determination in plasma with % recovery of 93.12 to 101.56%.