Experimental Model of Isolated Lung Perfusion in Rats: First Brazilian Experience Using the IL-2 Isolated Perfused Rat or Guinea Pig Lung System

Introduction. Lung transplantation has become the mainstay therapy for patients with end-stage lung disease refractory to medical management. However, the number of patients listed for lung transplantation largely exceeds available donors. The study of lung preservation requires accurate, cost-effective small animal models. We have described a model of ex vivo rat lung perfusion using a commercially available system. Methods. Male Wistar rats weighing 250 g-300 g were anesthetized with intraperitoneal sodium thiopental (50 mg/kg body weight). The surgical technique included heart-lung block extraction, assembly, and preparation for perfusion and data collection. We used an IL-2 Isolated Perfused Rat or Guinea Pig Lung System (Harvard Apparatus, Holliston, Mass, United States; Hugo Sachs Elektronik, Alemanha). Results. Preliminary results included hemodynamic and pulmonary mechanics data gathered in the experiments. Conclusion. The isolated rat lung perfusion system is a reliable method to assess lung preservation.

Experimental tuberculosis: Designing a better model to test vaccines against tuberculosis

Experimental models of infection are good tools for establishing immunological parameters that have an effect on the host-pathogen relationship and also for designing new vaccines and immune therapies. In this work, we evaluated the evolution of experimental tuberculosis in mice infected with increasing bacterial doses or via distinct routes. We showed that mice infected with low bacterial doses by the intratracheal route were able to develop a progressive infection that was proportional to the inoculum size. In the initial phase of disease, mice developed a specific Th1-driven immune response independent of inoculum concentration. However, in the late phase, mice infected with higher concentrations exhibited a mixed Th1/Th2 response, while mice infected with lower concentrations sustained the Th1 pattern. Significant IL-10 concentrations and a more preeminent T regulatory cell recruitment were also detected at 70 days post-infection with high bacterial doses. These results suggest that mice infected with higher concentrations of bacilli developed an immune response similar to the pattern described for human tuberculosis wherein patients with progressive tuberculosis exhibit a down modulation of IFN-gamma production accompanied by increased levels of IL-4. Thus, these data indicate that the experimental model is important in evaluating the protective efficacy of new vaccines and therapies against tuberculosis. (C) 2010 Elsevier Ltd. All rights reserved.

Experimental model for study of anorectal sphincter musculature by manometry and computerized tomography in piglets

There seems to be controversy on the anorectal sphincter presentation and anatomical division, as well as on its functional representation. Evaluation of the anorectal sphincter musculature has been achieved through several methods, including anorectal manometry and computerized tomography, but to date there is no experimental model allowing a detailed manometric study of this muscle complex. In this work, we have developed such a model, which should enable the manometric and radiographic study of the anatomical features and functional mechanisms of sphincteric injuries, as well as the assessment of drug effects on the anorectal musculature upon incontinence and constipation. Twenty-two piglets (aged 25-30 days, weighing 5-7 kg) were studied by anorectal manometry (rectoanal inhibitory reflex and vector volume) and computerized tomography (anorectal angle and anal canal length). The data obtained for the rectoanal inhibitory reflex, represented here as the average and standard deviation, were the following: relaxation duration = 14.75 +/- 3.62 s, sphincter basal pressure = 41.58 +/- 8.20 mmHg, relaxation index = 87.26 +/- 11.52%, speed of relaxation = 5.90 +/- 2.10 mm/s, and speed of relaxation recovery = 4.03 +/- 1.78 mm/s. As for the vector volume, results were as follows: vector volume = 2692.32 +/- 1298.12 mmHg(2) cm, sphincter length = 11.82 +/- 2.74 mm, high pressure zone length = 5.09 +/- 1.34 mm, maximum pressure = 61.50 +/- 20.58 mmHg, and asymmetry index = 43.50 +/- 10.03%. Radiographic evaluation led to the following results: anal canal length = 9.61 +/- 2.14 mm and anorectal angle = 137.91 +/- 7.75 degrees. The experimental model designed here allows both anorectal manometry and computerized tomography to be carried out in the same way it is performed in human beings, as long as animal sedation is strictly controlled.

Heart rate and arterial pressure variability in the experimental renovascular hypertension model in rats

This study was conducted in one kidney, one clip (1K1C) Goldblatt hypertensive rats to evaluate vascular and cardiac autonomic control using different approaches: 1) evaluation of the autonomic modulation of heart rate (HR) and systolic arterial pressure (SAP) by means of autoregressive power spectral analysis 2) assessment of the cardiac baroreflex sensitivity; and 3) double blockade with methylatropine and propranolol. The 1K1C group developed hypertension and tachycardia. The 1K1C group also presented reduction in variance as well as in LF (0.23 +/- 0.1 vs. 1.32 +/- 0.2 ms(2)) and HF (6.6 +/- 0.49 vs. 15.1 +/- 0.61 ms(2)) oscillations of pulse interval. Autoregressive spectral analysis of SAP showed that 1K1C rats had an increase in variance and LF band (13.3 +/- 2.7 vs. 7.4 +/- 1.01 mmHg(2)) in comparison with the sham group. The baroreflex gain was attenuated in the hypertensive 1K1C (- 1.83 +/- 0.05 bpm/mmHg) rats in comparison with normotensive sham (-3.23 +/- 0.06 bpm/MmHg) rats. The autonomic blockade caused an increase in the intrinsic HR and sympathetic predominance on the basal HR of 1K1C rats. Overall, these data indicate that the tachycardia observed in the 1K1C group may be attributed to intrinsic cardiac mechanisms (increased intrinsic heart rate) and to a shift in the sympathovagal balance towards cardiac sympathetic over-activity and vagal suppression associated to depressed baroreflex sensitivity. Finally, the increase in the LF components of SAP also suggests an increase in sympathetic activity to peripheral vessels. (c) 2008 Elsevier B.V. All rights reserved.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.

Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.

Elastic moduli of model random three-dimensional closed-cell cellular solids

Most cellular solids are random materials, while practically all theoretical structure-property results are for periodic models. To be able to generate theoretical results for random models, the finite element method (FEM) was used to study the elastic properties of solids with a closed-cell cellular structure. We have computed the density (rho) and microstructure dependence of the Young's modulus (E) and Poisson's ratio (PR) for several different isotropic random models based on Voronoi tessellations and level-cut Gaussian random fields. The effect of partially open cells is also considered. The results, which are best described by a power law E infinity rho (n) (1<n<2), show the influence of randomness and isotropy on the properties of closed-cell cellular materials, and are found to be in good agreement with experimental data. (C) 2001 Acta Materialia Inc. Published by Elsevier Science Ltd. All rights reserved.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

A comparison between three and five factor models of Pakistani personality data

The Eysenck Personality Questionnaire-Revised (EPQ-R), the Eysenck Personality Profiler Short Version (EPP-S), and the Big Five Inventory (BFI-V4a) were administered to 135 postgraduate students of business in Pakistan. Whilst Extraversion and Neuroticism scales from the three questionnaires were highly correlated, it was found that Agreeableness was most highly correlated with Psychoticism in the EPQ-R and Conscientiousness was most highly correlated with Psychoticism in the EPP-S. Principal component analyses with varimax rotation were carried out. The analyses generally suggested that the five factor model rather than the three-factor model was more robust and better for interpretation of all the higher order scales of the EPQ-R, EPP-S, and BFI-V4a in the Pakistani data. Results show that the superiority of the five factor solution results from the inclusion of a broader variety of personality scales in the input data, whereas Eysenck's three factor solution seems to be best when a less complete but possibly more important set of variables are input. (C) 2001 Elsevier Science Ltd. All rights reserved.

A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Model based procedure for scale-up of wet overflow ball mills Part 1: Outline of the methodology

Bond's method for ball mill scale-up only gives the mill power draw for a given duty. This method is incompatible with computer modelling and simulation techniques. It might not be applicable for the design of fine grinding ball mills and ball mills preceded by autogenous and semi-autogenous grinding mills. Model-based ball mill scale-up methods have not been validated using a wide range of full-scale circuit data. Their accuracy is therefore questionable. Some of these methods also need expensive pilot testing. A new ball mill scale-up procedure is developed which does not have these limitations. This procedure uses data from two laboratory tests to determine the parameters of a ball mill model. A set of scale-up criteria then scales-up these parameters. The procedure uses the scaled-up parameters to simulate the steady state performance of full-scale mill circuits. At the end of the simulation, the scale-up procedure gives the size distribution, the volumetric flowrate and the mass flowrate of all the streams in the circuit, and the mill power draw.

Model-based procedure for scale-up of wet, overflow ball mills - Part II: Worked example

A new ball mill scale-up procedure is developed which uses laboratory data to predict the performance of MI-scale ball mill circuits. This procedure contains two laboratory tests. These laboratory tests give the data for the determination of the parameters of a ball mill model. A set of scale-up criteria then scales-up these parameters. The procedure uses the scaled-up parameters to simulate the steady state performance of the full-scale mill circuit. At the end of the simulation, the scale-up procedure gives the size distribution, the volumetric flowrate and the mass flowrate of all the streams in the circuit, and the mill power draw. A worked example shows how the new ball mill scale-up procedure is executed. This worked example uses laboratory data to predict the performance of a full-scale re-grind mill circuit. This circuit consists of a ball mill in closed circuit with hydrocyclones. The MI-scale ball mill has a diameter (inside liners) of 1.85m. The scale-up procedure shows that the full-scale circuit produces a product (hydrocyclone overflow) that has an 80% passing size of 80 mum. The circuit has a recirculating load of 173%. The calculated power draw of the full-scale mill is 92kW (C) 2001 Elsevier Science Ltd. All rights reserved.

Model-based procedure for scale-up of wet, overflow ball mills - Part III: Validation and discussion

A new ball mill scale-up procedure is developed. This procedure has been validated using seven sets of Ml-scale ball mil data. The largest ball mills in these data have diameters (inside liners) of 6.58m. The procedure can predict the 80% passing size of the circuit product to within +/-6% of the measured value, with a precision of +/-11% (one standard deviation); the re-circulating load to within +/-33% of the mass-balanced value (this error margin is within the uncertainty associated with the determination of the re-circulating load); and the mill power to within +/-5% of the measured value. This procedure is applicable for the design of ball mills which are preceded by autogenous (AG) mills, semi-autogenous (SAG) mills, crushers and flotation circuits. The new procedure is more precise and more accurate than Bond's method for ball mill scale-up. This procedure contains no efficiency correction which relates to the mill diameter. This suggests that, within the range of mill diameter studied, milling efficiency does not vary with mill diameter. This is in contrast with Bond's equation-Bond claimed that milling efficiency increases with mill diameter. (C) 2001 Elsevier Science Ltd. All rights reserved.