Descriptor-and fragment-based QSAR models for a series of Schistosoma mansoni purine nucleoside inhibitors

The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive molecular target for the treatment of major parasitic infectious diseases, with special emphasis on its role in the discovery of new drugs against schistosomiasis, a tropical disease that affects millions of people worldwide. In the present work, we have determined the inhibitory potency and developed descriptor- and fragment-based quantitative structure-activity relationships (QSAR) for a series of 9-deazaguanine analogs as inhibitors of SmPNP. Significant statistical parameters (descriptor-based model: r² = 0.79, q² = 0.62, r²pred = 0.52; and fragment-based model: r² = 0.95, q² = 0.81, r²pred = 0.80) were obtained, indicating the potential of the models for untested compounds. The fragment-based model was then used to predict the inhibitory potency of a test set of compounds, and the predicted values are in good agreement with the experimental results

Development and mechanical testing of a short intramedullary nail for fixation of femoral rotational osteotomy in cerebral palsy patients

Background: Rotational osteotomy is frequently indicated to correct excessive femoral anteversion in cerebral palsy patients. Angled blade plate is the standard fixation device used when performed in the proximal femur, but extensile exposure is required for plate accommodation. The authors developed a short locked intramedullary nail to be applied percutaneously in the fixation of femoral rotational osteotomies in children with cerebral palsy and evaluated its mechanical properties. Methods: The study was divided into three stages. In the first part, a prototype was designed and made based on radiographic measurements of the femoral medullary canal of ten-year-old patients. In the second, synthetic femoral models based on rapid-prototyping of 3D reconstructed images of patients with cerebral palsy were obtained and were employed to adjust the nail prototype to the morphological changes observed in this disease. In the third, rotational osteotomies were simulated using synthetic femoral models stabilized by the nail and by the AO-ASIF fixed-angle blade plate. Mechanical testing was done comparing both devices in bending-compression and torsion. Results: The authors observed proper adaptation of the nail to normal and morphologically altered femoral models, and during the simulated osteotomies. Stiffness in bending-compression was significantly higher in the group fixed by the plate (388.97 +/- 57.25 N/mm) than in that fixed by the nail (268.26 +/- 38.51 N/mm) as torsional relative stiffness was significantly higher in the group fixed by the plate (1.07 +/- 0.36 Nm/degrees) than by the nail (0.35 +/- 0.13 Nm/degrees). Conclusions: Although the device presented adequate design and dimension to fit into the pediatric femur, mechanical tests indicated that the nail was less stable than the blade plate in bending-compression and torsion. This may be a beneficial property, and it can be attributed to the more flexible fixation found in intramedullary devices.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

2D evaluation of crack openings using smeared and embedded crack models

This work deals with the determination of crack openings in 2D reinforced concrete structures using the Finite Element Method with a smeared rotating crack model or an embedded crack model In the smeared crack model, the strong discontinuity associated with the crack is spread throughout the finite element As is well known, the continuity of the displacement field assumed for these models is incompatible with the actual discontinuity However, this type of model has been used extensively due to the relative computational simplicity it provides by treating cracks in a continuum framework, as well as the reportedly good predictions of reinforced concrete members` structural behavior On the other hand, by enriching the displacement field within each finite element crossed by the crack path, the embedded crack model is able to describe the effects of actual discontinuities (cracks) This paper presents a comparative study of the abilities of these 2D models in predicting the mechanical behavior of reinforced concrete structures Structural responses are compared with experimental results from the literature, including crack patterns, crack openings and rebar stresses predicted by both models

Fast experimental identification of suspension models for control design

This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.

Mutually connected phase-locked loop networks: dynamical models and design parameters

Distribution of timing signals is an essential factor for the development of digital systems for telecommunication networks, integrated circuits and manufacturing automation. Originally, this distribution was implemented by using the master-slave architecture with a precise master clock generator sending signals to phase-locked loops (PLL) working as slave oscillators. Nowadays, wireless networks with dynamical connectivity and the increase in size and operation frequency of the integrated circuits suggest that the distribution of clock signals could be more efficient if mutually connected architectures were used. Here, mutually connected PLL networks are studied and conditions for synchronous states existence are analytically derived, depending on individual node parameters and network connectivity, considering that the nodes are nonlinear oscillators with nonlinear coupling conditions. An expression for the network synchronisation frequency is obtained. The lock-in range and the transmission error bounds are analysed providing hints to the design of this kind of clock distribution system.

Development of Ramulosis Disease of Cotton Under Controlled Environment and Field Conditions

Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis disease of cotton, is widespread in Brazil and can cause severe yield loss. Because weather conditions greatly affect disease development, the objective of this work was to develop weather-based models to assess disease favorability. Latent period, incidence, and severity of ramulosis symptoms were evaluated in controlled environment experiments using factorial combinations of temperature (15, 20, 25, 30, and 35 degrees C) and leaf wetness duration (0, 4, 8, 16, 32, and 64 h after inoculation). Severity was modeled as an exponential function of leaf wetness duration and temperature. At the optimum temperature of disease development, 27 degrees C, average latent period was 10 days. Maximum ramulosis severity occurred from 20 to 30 degrees C, with sharp decreases at lower and higher temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. In field experiments at Piracicaba, Sao Paulo State, Brazil, cotton plots were inoculated (10(5) conidia ml(-1)) and ramulosis severity was evaluated weekly. The model obtained from the controlled environment study was used to generate a disease favorability index for comparison with disease progress rate in the field. Hourly measurements of solar radiation, temperature, relative humidity, leaf wetness duration, rainfall, and wind speed were also evaluated as possible explanatory variables. Both the disease favorability model and a model based on rainfall explained ramulosis growth rate well, with R(2) of 0.89 and 0.91, respectively. They are proposed as models of ramulosis development rate on cotton in Brazil, and weather-disease relationships revealed by this work can form the basis of a warning system for ramulosis development.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Development and In Vitro Evaluation of Propranolol Hydrochloride Controlled Release Tablets Using HPMC as Matrix Former

The purpose of this paper was to produce controlled-release matrices with 120 mg of propranolol hydrochloride (PHCl) employing hydroxypropyl methylcellulose (HPMC, Methocel (R) K100) as the gel forming barrier. Although this class of polymers has been commonly used for direct compression, with the intent of use reduced polymer concentrations to achieve controlled drug release, in this study tablets were produced by the wet granulation process. HPMC percentages ranged from 15-34 % and both soluble and non soluble diluents were tested in the 10 proposed tablet compositions. Dissolution testing of matrices was performed over a 12 h period in 1.2 pH medium (the first 2 h) and in pH 6.8 (10 h). Dissolution kinetic analysis was performed by applying Zero-order, First-order and Higuchi models with the aim of elucidating the drug release mechanism. All physical-chemical characteristics such as average weight, friability, hardness, diameter, height, and drug content were in accordance to the pharmacopeial specifications. Taking into account that PHCl is a very soluble drug, low concentrations (15 %) of HPMC were sufficient to reduce the drug release and to promote controlled release of PHCl, presenting good dissolution efficiencies, between 50 % and 63 %. The Higuchi model has presented the best fit to the 15 % HPMC formulations, indicating that the main release mechanism was diffusion. It could be concluded that the application of the wet granulation method reduced matrices erosion and promoted controlled release of the drug at low HPMC percentages.

Antinociceptive and anti-inflammatory properties of 7-hydroxycoumarin in experimental animal models: potential therapeutic for the control of inflammatory chronic pain

Objectives In the present study we investigated the anti nociceptive, anti-inflammatory and antipyretic effects of 7-hydroxycoumarin (7-HC) in animal models. Methods The effects of oral 7-HC were tested against acetic acid-induced writhing, formalin test, tail flick test, complete Freund`s adjuvant (CFA)-induced hypemociception, carrageenan-induced paw oedema, lipopolysaccharide-induced fever and the rota rod test. Key findings 7-HC (3-60 mg/kg) produced a dose-related antinociception against acetic acid-induced writhing in mice and in the formalin test. In contrast, treatment with 7-HC did not prevent thermal nociception in the tail flick test. A single treatment with 7-HC, 60 mg/kg, produced a long-lasting antinociceptive effect against CFA-induced hypernociception, a chronic inflammatory pain stimulus. Notably, at 60 mg/kg per day over 4 days the administration of 7-HC produced a continuous antinociceptive effect against CFA-induced hypernociception. 7-HC (30-120 mg/kg) produced anti-inflammatory and antipyretic effects against carrageenan-induced inflammation and lipopolysaccharide-induced fever, respectively. Moreover, 7-HC was found to be safe with respect to ulcer induction. In the rota rod test, 7-HC-treated mice did not show any motor performance alterations. Conclusions The prolonged antinociceptive and anti-inflammatory effects of 7-HC, in association with its low ulcerogenic activity, indicate that this molecule might be a good candidate for development of new drugs for the control of chronic inflammatory pain and fever.

Antiulcerogenic Activity of the Essential Oil of Baccharis dracunculifolia on Different Experimental Models in Rats

Baccharis dracunculifolia DC (Asteraceae), a native plant from Brazil, commonly known as `Alecrim-do-campo` is widely used in folk medicine to treat inflammation, hepatic disorders and stomach ulcers, and it is the most important botanical source of Southeastern Brazilian propolis, known as green propolis. Its essential oil is composed of non-oxygenated and oxygenated terpenes. In this work, the effects of the essential oil obtained from the aerial parts of R dracunculifolia on gastric ulcers were evaluated. The antiulcer assays were undertaken using the following protocols in rats: nonsteroidal antiinflammatory drug (NSAID)-induced ulcer, ethanol-induced ulcer, stress-induced ulcer, and determination of gastric secretion using ligated pylorus. The treatment in the doses of 50, 250 and 500 mg/kg of R dracunculifolia essential oil significantly diminished the lesion index, the total lesion area and the percentage of lesions in comparison with both positive and negative control groups. With regard to the model of gastric secretion a reduction of gastric juice volume and total acidity was observed, as well as an increase in the gastric pH. No sign of toxicity was observed in the acute toxicity study. Considering the results, it is suggested that the essential oil of B. dracunculifolia could probably be a good therapeutic agent for the development of new phytotherapeutic medicine for the treatment of gastric ulcer. Copyright (C) 2009 John Wiley & Sons, Ltd.

Language policy spread: Learning from health and social policy models

Except for a few large scale projects, language planners have tended to talk and argue among themselves rather than to see language policy development as an inherently political process. A comparison with a social policy example, taken from the United States, suggests that it is important to understand the problem and to develop solutions in the context of the political process, as this is where decisions will ultimately be made.

Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

The Development of Science Education Research in Brazil and Contributions from the History and Philosophy of Science

Over the last 50 years a new research area, science education research, has arisen and undergone singular development worldwide. In the specific case of Brazil, research in science education first appeared systematically 40 years ago, as a consequence of an overall renovation in the field of science education. This evolution was also related to the political events taking place in the country. We will use the theoretical work of Rene Kaes on the development of groups and institutions as a basis for our discussion of the most important aspects that have helped the area of science education research develop into an institution and kept it operating as such. The growth of this area of research can be divided into three phases: The first was related to its beginning and early configurations; the second consisted of a process of consolidation of this institution; and the third consists of more recent developments, characterised by a multiplicity of research lines and corresponding challenges to be faced. In particular, we will analyse the special contributions to this study gleaned from the field known as the history and philosophy of science.