Reversible Photorheology in Solutions of Cetyltrimethylammonium Bromide, Salicylic Acid, and trans-2,4,4 '-Trihydroxychalcone

We show photorheology in aqueous solutions of weakly entangled wormlike micelles prepared with cetyltrimethylammonium bromide (CTAB), salicylic acid (HSal), and dilute amounts of the photochromic multistate compound trans-2,4,4'-trihydroxychalcone (Ct). Different chemical species of Ct are associated with different colorations and propensities to reside within or outside CTAB micelles. A light-induced transfer between the intra- and intermicellar space is used to alter the mean length of wormlike micelles and hence the rheological properties of the fluid, studied in steady-state shear Bow and in dynamic rheological measurements. Light-induced changes of fluid rheology are reversible by a the relaxation process. at relaxation rates which depend on pH and which are consistent with photochromic reversion rates measured by UV-vis absorption spectroscopy. Parameterizing viscoelostic rheological states by their effective relaxation time tau(c) and corresponding response modulus G(c), we find the light and dark states of the system to fall onto a characteristic state curve defined by comparable experiments conducted without photosensitive components. These reference experiments were prepared with the same concentration of CTAB, but different concentrations of HSal or sodium salicylote (NaSal), and tested at different temperatures.

New heterogeneous catalysts for trans-esterification of triglycerides

This paper describes preliminary work done towards the development of new metallic heterogeneous catalysts to be used in the transesterification reaction of triglycerides, which is of considerable interest in the production of biodiesel. Biodiesel, is a mixture of mono-alkyl esters of fatty acids, and is currently manufactured by transesterification of triglycerides with methanol using NaOH or KOH as liquid base catalyst. Catalysts as such are corrosive to the equipment, and as these catalysts are in liquid phase must be neutralized after the completion of the reaction, typically using HCl, thus producing salt streams. Moreover, due to the presence of free fatty acids it reacts to form soaps as unwanted by-products, hence requiring more expensive separation processes. Therefore, there is a great need on the development of industrial processes for biodiesel production using solid acid catalysts. The key benefit of using solid acid catalysts is that no polluting by-products are formed and the catalysts do not have to be removed since they do not mix with the biodiesel product.

Processos de trans-nacionalização da linguagem publicitária. Não basta colocar as campanhas publicitárias internacionais no ar. É necessário que os conceitos criativos possam “voar”.

Este artigo analisa a questão da trans-nacionalização da linguagem publicitária e da sua eficácia. O mundo actual está num processo de grande transformação social e dele emerge um novo paradigma da comunicação comercial. A trans-nacionalização da linguagem publicitária põe em marcha dois processos paralelos. Por um lado, contribui para uma certa homogeneização cultural (visível sobretudo nos conceitos globais e na utilização do inglês como língua de ancoragem de sentido universal) e para a emergência de valores sociais de cariz global, porque desterritorizados. Outro processo é o da diversificação cultural, com valores diferenciados (que nascem da apropriação, transformação e re-contextualização de significações) que passam a operar como códigos, mais ou menos fechados, de comunidades sociais, de toda a espécie, que em torno deles se estruturam. Essa ocorrência, parece ser mais frequente entre as novas gerações (mas não necessariamente) e estas também usam, normalmente, certas marcas e certos objectos de consumo, quase sempre ligados ao segmento da moda, que se transformam em símbolos de pertença da tribo. A mudança de paradigma faz realçar o factor criatividade como garante da eficácia publicitária. Uma das principais consequências desta mudança de paradigma é que as marcas deixarão de entrar facilmente na casa do consumidor e na sua mente através de uma estratégia cerrada de “bombardeamento” e a linguagem publicitária deverá retornar aos valores sociais e culturais importantes, oferecendo espectáculo, sonho, significado e relação. Porque, afinal, não basta colocar as campanhas publicitárias internacionais no ar, é necessário que os conceitos criativos possam “voar”.

Avaliação do ácido trans, trans-mucônico urinário como biomarcador de exposição ao benzeno

OBJETIVO: Avaliar o uso do ácido trans, trans-mucônico urinário como biomarcador na monitorização da exposição ocupacional ao benzeno. MÉTODOS: Foi estudado o comportamento do ácido trans, trans-mucônico em amostras de urina de indivíduos expostos (N=36) e não expostos (N=116) ocupacionalmente ao solvente. A concentração urinária do ácido foi determinada por Cromatografia Líquida de Alta Eficiência. A amostra foi constituída de indivíduos expostos ao benzeno em uma refinaria de petróleo localizada em Belo Horizonte, MG. Foram empregados os testes estatísticos não-paramétricos de Kruskall-Wallis, Mann Witney e de correlação de Spearman, ao nível de significância de 0,05%. RESULTADOS: A exposição média ao benzeno dos trabalhadores selecionados foi de 0,15±0,05 mg/m³ (0,05 ppm) o que resultou em um valor médio do metabólito urinário de 0,19±0,04 mg/g de creatinina. A faixa de referência do ácido trans, trans-mucônico no grupo não exposto variou de 0,03 a 0,26 mg/g de creatinina (média de 0,10±0,08 mg/g de creatinina). Foi encontrada uma diferença significativa entre os níveis de ácido trans, trans-mucônico do grupo exposto e não exposto. Entretanto, não houve correlação entre os níveis do metabólito urinário e do benzeno no ar. Foi observada a correlação entre ácido trans, trans-mucônico e hábito de fumar no grupo de indivíduos expostos. A ingestão de álcool num período de até 48 horas antes da coleta das amostras não mostrou interferir nos níveis do metabólito nos dois grupos estudados. Foi observada a correlação entre ácido trans, trans-mucônico e idade (faixa etária de 18 a 25 anos) no grupo de não expostos. CONCLUSÕES: Os resultados obtidos evidenciaram a importância de ser mais bem avaliada a influência do hábito de fumar e da faixa etária do trabalhador nos níveis urinários do ácido trans, trans-mucônico.

A colonoscopia virtual no rastreio do cancro colo rectal

O cancro colo - rectal (CCR) é um problema de saúde mundial, estando associadas elevadas taxas de mortalidade e morbilidade. A maioria de CCR deriva de pólipos adenomatosos.. Um estudo retrospectivo, efectuado no serviço de Radiologia, dos achados imagiológicos típicos e atípicos, entre Janeiro de 2008 e Junho 2010. A Colonoscopia Virtual, apresenta uma sensibilidade elevada na detecção de lesões, com dimensão superior a 10mm, permitindo um diagnóstico precoce, é um exame rápido, pouco invasivo, não há necessidade de sedação e é efectuada em ambulatório.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

Trans fatty acid intake among the population of the city of São Paulo, Brazil

OBJECTIVE: To analyze the monounsaturated and polyunsaturated trans fatty acid intake among the general population. METHODS: A cross-sectional study was conducted in São Paulo, Southeastern Brazil, in 2003, on a representative sample of 2,298 male and female subjects, including 803 adolescents (12 to 19 years), 713 adults (20 to 59 years) and 782 elderly people (60 years or over). Food intake was measured using 24-hour recall. Mean trans fatty acid intake was described according to gender and age group. RESULTS: The mean trans fatty acid intake was 5.0 g/day (SE = 0.1), accounting for 2.4% (SE = 0.1) of total energy and 6.8% (SE = 0.1) of total lipids. The adolescents had the highest mean intake levels (7.4 g/day; 2.9% of energy) while the adults and the elderly had similar intake (2.2% of energy for both; 6.4% of lipids and 6.5% of lipids, respectively). The mean trans fatty acid intake among adult and elderly women (approximately 2.5% of energy and 7.0% of lipids) was higher than among men in the same age group. The food item with the highest contribution towards trans fatty acids was margarine, accounting for more than 30% of total intake, followed by filled cookies among adolescents and meat among adults and the elderly. CONCLUSIONS: The trans fatty acid intake is above the level recommended by the World Health Organization. Replacement of the trans fatty acids in manufactured food items may be an effective measure for reducing trans fatty acid intake in Brazil.

Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization

Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.