Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Residues of b-lactams and quinolones in tissues and milk samples. Confirmatory analysis by liquid chromatography-mass spectrometry

The aim of this work is to optimize and validate methods for the multiresidue determination of series of families of antibiotics as quinolones, penicillins and cephalosporins included in European regulation in food samples using LC-MS/MS. Different extraction techniques and clean-up applied to antibiotics in meat were compared. The quality parameters were established according with EU guideline. The developed method was applied to 49 positive raw milk samples from animal medicated with different antibiotics; the 63% of the analyzed samples were found to be compliant. ___________________________________________________________________________________________

Microextração em fase líquida (LPME): fundamentos da técnica e aplicações na análise de fármacos em fluidos biológicos

The analysis of drugs and metabolites in biological fluids usually requires extraction procedures to achieve sample clean-up and analyte preconcentration. Commonly, extraction procedures are performed using liquid-liquid extraction or solid-phase extraction. Nevertheless, these extraction techniques are considered to be time-consuming and require a large amount of organic solvents. On this basis, microextraction techniques have been developed. Among them, liquid-phase microextraction has been standing out. This review describes the liquid-phase microextraction technique based on hollow fibers as a novel and promising alternative in sample preparation prior to chromatographic or electrophoretic analysis. The basic concepts related to this technique and its applicability in extraction of drugs are discussed.

Técnicas de extrações e procedimentos de clean-up para a determinação de hidrocarbonetos policílicos aromáticos (HPA) em sedimentos da costa do Ceará

Extraction and clean-up are essential points in polycyclic aromatic hydrocarbon (PAHs) analysis in a solid matrix. This work compares extraction techniques and clean-up procedures for PAH analysis. PAH levels, their toxicological significance and source were also evaluated in the waters of the Cocó and Ceará rivers. The efficiency of PAH recovery was higher for the soxhlet and ultrasonic techniques. PAH recovery varied from 69.3 to 99.3%. Total PAH concentration (ΣHPA) varied from 720.73 to 2234.76 µg kg-1 (Cocó river) and 96.4 to 1859.21 µg kg-1 (Ceará river). The main PAH sources are pyrolytic processes and the levels were classified as medium so that adverse effects are possible.

Biodiesel renovável derivado de microalgas: avanços e perspectivas tecnológicas

Microalgae are a promising source of raw material for biodiesel production. This review discusses the latest developments related to the application of microalgae biomass for biodiesel production. Characterization of fatty acid of microalgae and comparisons with other sources of raw materials and processes are presented. Furthermore, technological perspectives and approaches for growing microalgae in photobioreactors, microalgal oil extraction techniques, and procedures for synthesizing biodiesel are reviewed.

Determination of patulin in apple juice by HPLC using a simple and fast sample preparation method

The goal of this work was to develop a simple and rapid preparation method for patulin analysis in apple juice without previous clean-up. This method combined sonication and liquid extraction techniques and was used for determination of patulin in 37 commercial apple juices available on the market in the South of Brazil. The method performance characteristics were determined using a sample obtained in a local market fortified at five concentration levels of patulin and done in triplicates. The coefficient of variation for repeatability at the fortification level of 20.70µg.L-1 was 3.53 % and the recovery 94.63 %, respectively. The correlation coefficient was 0.9996 and agrees with the requirements for a linear analytical method value. The detection limit was 0.21µg.L-1 and the quantification limit 0.70 µg.L-1. Only three of the analyzed samples were upper the allowed level of 50.00 µg.L-1 recommended for the World Health Organization.

Geochemistry and mineralogical association of heavy metal contaminants in fine grained sediment, Welland River, Southern Ontario /

This investigation of geochemistry and mineralogy of heavy metals in fine grained (<63^m) sediment of the Welland River was imdertaken to: 1) describe metal dispersion patterns relative to a source, identify minerals forming and existing at the outfall region and relate sediment particle size to chemistry; 2) to delineate sample handling, preparation and evaluate, modify and develop analytical methods for heavy metal analysis of complex environmental samples. Ajoint project between Brock University and Geoscience Laboratories was initiated to test a contaminated site of the Welland River at the base of Atlas Speciality Steels Co. Methods were developed and utilized for particle size separation and two acid extraction techniques: 1) Partial extraction; 2) Total extraction. The mineralogical assessment identified calcite, dolomite, quartz and clays. These minerals are typical of the carbonate-shale rock basement of the Niagara Peninsula. Minerals such as, mullite and ferrocolumbite were found at the outfall region. These are not typical of the local geology and are generally associated with industrial pollutants. Partial and total extraction techniques were used to characterize the sediments based on chemical distribution, elemental behaviour and analytical differences. The majority of elements were lower in concentration in the partial extraction technique; suggesting these elements are bound in an acid extractable phase (exchangeable, organic and carbonate phases). The total extraction technique yielded higher elemental concentrations taking difficult oxides and silicates into solution. Geochemical analyses of grain size separates revealed that heavy metal (Co, Ni, V, Mn, Fe, Ba) concentrations did not increase with decreasing grain size. This is a function of the anthropogenic mill scale input into the river. The background elements (Sc, Y, Sr, Mg, Al and Ti) showed an increase in concentration to the finest grain size suggesting that it is directly related to the local mineralogy and geology. Dispersion patterns ofmetals fall into two distinct categories: 1) the heavy metals (Co, Cu, Ni, Zn, V and Cr), and 2) the background elements (Be, Sc, Y, Sr, Al and Ti). The heavy metals show a marked increase in the outfall region, while the background elements show a significant decrease at the outfall. This pattern is attributed to a "dilution effect" ofthe natural sediments by the anthropogenic mill scale sediments. Multivariant statistical analysis and correlation coefficient matrix results clearly support these results and conclusions. These results indicate the outfall region ofthe Welland River is highly contaminated with to heavy metals from the industrialized area of Welland. A short distance downstream, the metal concentrations return to baseline geochemical levels. It appears, contaminants rapidly come out of suspension and are deposited in close proximity to the source. Therefore, it is likely that dredging the sediment from the river may cause resuspension of contaminated sediments, but may not distribute the sediment as far as initially anticipated.

The development of automated methods for the determination of trace concentrations of carbomate pesticides in water using solid sorbent pre-concentration methods and high performance liquid chromatography /

Several automated reversed-phase HPLC methods have been developed to determine trace concentrations of carbamate pesticides (which are of concern in Ontario environmental samples) in water by utilizing two solid sorbent extraction techniques. One of the methods is known as on-line pre-concentration'. This technique involves passing 100 milliliters of sample water through a 3 cm pre-column, packed with 5 micron ODS sorbent, at flow rates varying from 5-10 mUmin. By the use of a valve apparatus, the HPLC system is then switched to a gradient mobile phase program consisting of acetonitrile and water. The analytes, Propoxur, Carbofuran, Carbaryl, Propham, Captan, Chloropropham, Barban, and Butylate, which are pre-concentrated on the pre-column, are eluted and separated on a 25 cm C-8 analytical column and determined by UV absorption at 220 nm. The total analytical time is 60 minutes, and the pre-column can be used repeatedly for the analysis of as many as thirty samples. The method is highly sensitive as 100 percent of the analytes present in the sample can be injected into the HPLC. No breakthrough of any of the analytes was observed and the minimum detectable concentrations range from 10 to 480 ng/L. The developed method is totally automated for the analysis of one sample. When the above mobile phase is modified with a buffer solution, Aminocarb, Benomyl, and its degradation product, MBC, can also be detected along with the above pesticides with baseline resolution for all of the analytes. The method can also be easily modified to determine Benomyl and MBC both as solute and as particulate matter. By using a commercially available solid phase extraction cartridge, in lieu of a pre-column, for the extraction and concentration of analytes, a completely automated method has been developed with the aid of the Waters Millilab Workstation. Sample water is loaded at 10 mL/min through a cartridge and the concentrated analytes are eluted from the sorbent with acetonitrile. The resulting eluate is blown-down under nitrogen, made up to volume with water, and injected into the HPLC. The total analytical time is 90 minutes. Fifty percent of the analytes present in the sample can be injected into the HPLC, and recoveries for the above eight pesticides ranged from 84 to 93 percent. The minimum detectable concentrations range from 20 to 960 ng/L. The developed method is totally automated for the analysis of up to thirty consecutive samples. The method has proven to be applicable to both purer water samples as well as untreated lake water samples.

Landscape geochemical investigations in the vicinity of a lead deposit near Snertingdal, southern Norway

Landscape geochemical investigations were conducted upon portions of a natural uniform landscape in southern Norway. This consisted of sampling both soil profile samples and spruce tree twigs for the analysis of twelve chemical elements. These elements were cobalt, copper, nickel, lead, zinc, manganese, magnesium, iron, calcium, sodium, potassium and aluminum which were determined by atomic absorption analysis on standardized extraction techniques for both organic and inorganic materials. Two "landscape traverses" were chosen for a comparative study of the effects of varying landscape parameters upon the trace element distribution patterns throughout the landscape traverses. The object of this study was to test this method of investigation and the concept of an ideal uniform landscape under Norwegian conditions. A "control traverse" was established to represent uniform landscape conditions typical of the study area and was used to determine "normal" or average trace element distribution patterns. A "signal traverse" was selected nearby over an area of lead mineralization where the depth to bedrock is very small. The signal traverse provided an area of similar landscape conditions to those of the control traverse with significant differences in the bedrock configuration and composition. This study was also to determine the effect of the bedrock mineralization upon the distribution patterns of the twelve chemical elements within the major components of the two landscape traverses (i.e. soil profiles and tree branches). The lead distribution within the soils of the signal traverse showed localized accumulations of lead within the overburden with maximum values occurring within the organic A horizon of soil profile #10. Above average concentrations of lead were common within the signal traverse, however, the other elements studied were not significantly different from those averages determined throughout the soils of the control traverse. The spruce twig samples did not have corresponding accumulations of lead near the soil lead anomaly. This is attributable to the very localized nature of the lead dispersion pattern within the soils. This approach to the study of the geochemistry of a natural landscape was effective in establishing: a) average or "normal" trace element distribution patterns b) local variations in the landscape morphology and c) the effect of unusually high lead concentrations upon the geochemistry of the landscape (i.e. within the soil profiles and tree branches). This type of study provides the basis for further more intensive studies and serves only as a first approximation of the behaviour of elements within a natural landscape.

Élaboration d'un corpus étalon pour l'évaluation d'extracteurs de termes

Ce travail porte sur la construction d’un corpus étalon pour l’évaluation automatisée des extracteurs de termes. Ces programmes informatiques, conçus pour extraire automatiquement les termes contenus dans un corpus, sont utilisés dans différentes applications, telles que la terminographie, la traduction, la recherche d’information, l’indexation, etc. Ainsi, leur évaluation doit être faite en fonction d’une application précise. Une façon d’évaluer les extracteurs consiste à annoter toutes les occurrences des termes dans un corpus, ce qui nécessite un protocole de repérage et de découpage des unités terminologiques. À notre connaissance, il n’existe pas de corpus annoté bien documenté pour l’évaluation des extracteurs. Ce travail vise à construire un tel corpus et à décrire les problèmes qui doivent être abordés pour y parvenir. Le corpus étalon que nous proposons est un corpus entièrement annoté, construit en fonction d’une application précise, à savoir la compilation d’un dictionnaire spécialisé de la mécanique automobile. Ce corpus rend compte de la variété des réalisations des termes en contexte. Les termes sont sélectionnés en fonction de critères précis liés à l’application, ainsi qu’à certaines propriétés formelles, linguistiques et conceptuelles des termes et des variantes terminologiques. Pour évaluer un extracteur au moyen de ce corpus, il suffit d’extraire toutes les unités terminologiques du corpus et de comparer, au moyen de métriques, cette liste à la sortie de l’extracteur. On peut aussi créer une liste de référence sur mesure en extrayant des sous-ensembles de termes en fonction de différents critères. Ce travail permet une évaluation automatique des extracteurs qui tient compte du rôle de l’application. Cette évaluation étant reproductible, elle peut servir non seulement à mesurer la qualité d’un extracteur, mais à comparer différents extracteurs et à améliorer les techniques d’extraction.

Semantic-level Visual Content Descriptor combining visual and textual cues as collaterals

In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.

Collaterally cued labelling framework underpinning semantic-level visual content descriptor

In this paper, we introduce a novel high-level visual content descriptor devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt for bridging the so called "semantic gap". The proposed image feature vector model is fundamentally underpinned by an automatic image labelling framework, called Collaterally Cued Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts accompanying the images with the state-of-the-art low-level visual feature extraction techniques for automatically assigning textual keywords to image regions. A subset of the Corel image collection was used for evaluating the proposed method. The experimental results indicate that our semantic-level visual content descriptors outperform both conventional visual and textual image feature models.

On fusion for multispectral iris recognition

Multispectral iris recognition uses information from multiple bands of the electromagnetic spectrum to better represent certain physiological characteristics of the iris texture and enhance obtained recognition accuracy. This paper addresses the questions of single versus cross spectral performance and compares score-level fusion accuracy for different feature types, combining different wavelengths to overcome limitations in less constrained recording environments. Further it is investigated whether Doddington's “goats” (users who are particularly difficult to recognize) in one spectrum also extend to other spectra. Focusing on the question of feature stability at different wavelengths, this work uses manual ground truth segmentation, avoiding bias by segmentation impact. Experiments on the public UTIRIS multispectral iris dataset using 4 feature extraction techniques reveal a significant enhancement when combining NIR + Red for 2-channel and NIR + Red + Blue for 3-channel fusion, across different feature types. Selective feature-level fusion is investigated and shown to improve overall and especially cross-spectral performance without increasing the overall length of the iris code.

Anomalous content of chromium in a Cretaceous sandstone aquifer of the Bauru Basin, state of Sao Paulo, Brazil

Anomalous and natural concentrations of Cr(6+), occasionally exceeding the permitted limit for human consumption (0.05 mg/L), have been detected in groundwater in the northwestern region of the state of Sao Paulo. As part of a water-rock interaction investigation, this article describes the chemical and mineralogical characterization of rock samples taken from boreholes in the municipality of Urania, with the objective of identifying Cr-bearing minerals and determining how chromium is associated with these minerals. Rock sample analysis were performed using X-ray Fluorescence, X-ray Diffraction, Scanning Electron Microscopy, electron microprobe and sequential extraction techniques. Chemical analyses indicated that the quartzose sandstones show a geochemical anomaly of chromium, with an average content of 221 ppm, which is higher than the reported chromium content of generic sandstones (35 ppm). Diopside was identified as the primary Cr-bearing mineral potentially subject to weathering processes, with a chromium content of up to 1.2% as Cr(2)O(3). Many of the diopside grains showed dissolution features, confirming the occurrence of weathering. Sequential extraction experiments indicated that 99.3% of the chromium in samples is tightly bonded to minerals, whereas 0.24% is weakly bonded via adsorption. Assuming hypothetically that all adsorbed chromium is released via desorption, the theoretical Cr concentration in water would be one order of magnitude higher than the concentrations of Cr(6+) detected in groundwater. (C) 2010 Elsevier Ltd. All rights reserved.

Caracterização química da erva mate (Ilex paraguariensis) : aplicação de diferentes processos de extração e influência das condições de plantio sobre a composição química

O objetivo deste trabalho foi estudar a composição química das folhas de erva-mate, sob diferentes condições agronômicas e técnicas de extração. Os métodos de extração usados foram maceração, ultra-som, extração com líquido pressurizado e extração com fluído supercrítico. Foram investigadas as variáveis que podem influenciar no processo de extração, tais como temperatura, pressão, polaridade do solvente, tempo de extração, massa de amostra, entre outras. A identificação dos compostos foi realizada por cromatografia gasosa acoplada à espectrometria de massas. Todos os métodos de extração utilizados mostraram-se eficientes para a obtenção dos extratos, com as diferenças sendo mais quantitativas do que qualitativas . Entre os métodos de extração que utilizam solventes orgânicos, a extração com líquido pressurizado mostrou-se mais eficiente, produzindo maior rendimento em massa de extrato e maior concentração de alguns dos compostos de interesse, com as vantagens de redução de solvente e tempo de extração. A composição química da erva-mate é influenciada pelas condições agronômicas de plantio, bem como pelas condições de extração de suas folhas. A melhor condição agronômica avaliada, ou seja, aquela que produziu maior quantidade de extrato, foi o cultivo das plantas a pleno sol, adubadas com nitrogênio e com idade de poda de 18 meses. A variável mais importante das técnicas de extração utilizadas foi a polaridade do solvente. Solventes de maior polaridade produziram maior rendimento em extrato. A análise cromatográfica dos extratos obtidos permitiu identificar cerca de 50 compostos qualitativamente e 6 quantitativamente, destacando-se a cafeína, fitol, ácido palmítico, ácido esteárico, esqualeno e vitamina E.