Interactions métaboliques entre le bisphénol A et le naproxène dans un modèle de foie de rat isolé et perfusé

L'exposition aux mélanges de contaminants (environnementaux, alimentaires ou thérapeutiques) soulève de nombreuses interrogations et inquiétudes vis-à-vis des probabilités d'interactions toxicocinétiques et toxicodynamiques. Une telle coexposition peut influencer le mode d’action des composants du cocktail et donc de leur toxicité, suite à un accroissement de leurs concentrations internes. Le bisphénol A (4 dihydroxy-2,2-diphenylpropane) est un contaminant chimique répandu de manière ubiquitaire dans notre environnement, largement utilisé dans la fabrication des plastiques avec l’un des plus grands volumes de production à l’échelle mondiale. Il est un perturbateur endocrinien par excellence de type œstrogèno-mimétique. Cette molécule est biotransformée en métabolites non toxiques par un processus de glucuronidation. L'exposition concomitante à plusieurs xénobiotiques peut induire à la baisse le taux de glucuronidation du polluant chimique d'intérêt, entre autres la co-exposition avec des médicaments. Puisque la consommation de produits thérapeutiques est un phénomène grandissant dans la population, la possibilité d’une exposition simultanée est d’autant plus grande et forte. Sachant que l'inhibition métabolique est le mécanisme d'interaction le plus plausible pouvant aboutir à une hausse des niveaux internes ainsi qu’à une modulation de la toxicité prévue, la présente étude visait d'abord à confirmer et caractériser ce type d'interactions métaboliques entre le bisphénol A et le naproxène, qui est un anti-inflammatoire non stéroïdiennes (AINS), sur l'ensemble d'un organe intact en utilisant le système de foie de rat isolé et perfusé (IPRL). Elle visait ensuite à déterminer la cinétique enzymatique de chacune de ces deux substances, seule puis en mélange binaire. Dans un second temps, nous avons évalué aussi l’influence de la présence d'albumine sur la cinétique métabolique et le comportement de ces deux substances étudiées en suivant le même modèle de perfusion in vivo au niveau du foie de rat. Les constantes métaboliques ont été déterminées par régression non linéaire. Les métabolismes du BPA et du NAP seuls ont montré une cinétique saturable avec une vélocité maximale (Vmax) de 8.9 nmol/min/ mg prot de foie et une constante d'affinité de l'enzyme pour le substrat (Km) de 51.6 μM pour le BPA et de 3 nmol/min/mg prot de foie et 149.2 μM pour le NAP. L'analyse des expositions combinées suggère une inhibition compétitive partielle du métabolisme du BPA par le NAP avec une valeur de Ki estimée à 0.3542 μM. Les résultats obtenus montrent que l’analyse de risque pour les polluants environnementaux doit donc prendre en considération la consommation des produits pharmaceutiques comme facteur pouvant accroitre le niveau interne lors d’une exposition donnée. Ces données in vivo sur les interactions métaboliques pourraient être intégrées dans un modèle pharmacocinétique à base physiologique (PBPK) pour prédire les conséquences toxicococinétique (TK) de l'exposition d'un individu à ces mélanges chimiques.

Interactions métaboliques entre le bisphénol A et le naproxène dans un modèle de foie de rat isolé et perfusé

L'exposition aux mélanges de contaminants (environnementaux, alimentaires ou thérapeutiques) soulève de nombreuses interrogations et inquiétudes vis-à-vis des probabilités d'interactions toxicocinétiques et toxicodynamiques. Une telle coexposition peut influencer le mode d’action des composants du cocktail et donc de leur toxicité, suite à un accroissement de leurs concentrations internes. Le bisphénol A (4 dihydroxy-2,2-diphenylpropane) est un contaminant chimique répandu de manière ubiquitaire dans notre environnement, largement utilisé dans la fabrication des plastiques avec l’un des plus grands volumes de production à l’échelle mondiale. Il est un perturbateur endocrinien par excellence de type œstrogèno-mimétique. Cette molécule est biotransformée en métabolites non toxiques par un processus de glucuronidation. L'exposition concomitante à plusieurs xénobiotiques peut induire à la baisse le taux de glucuronidation du polluant chimique d'intérêt, entre autres la co-exposition avec des médicaments. Puisque la consommation de produits thérapeutiques est un phénomène grandissant dans la population, la possibilité d’une exposition simultanée est d’autant plus grande et forte. Sachant que l'inhibition métabolique est le mécanisme d'interaction le plus plausible pouvant aboutir à une hausse des niveaux internes ainsi qu’à une modulation de la toxicité prévue, la présente étude visait d'abord à confirmer et caractériser ce type d'interactions métaboliques entre le bisphénol A et le naproxène, qui est un anti-inflammatoire non stéroïdiennes (AINS), sur l'ensemble d'un organe intact en utilisant le système de foie de rat isolé et perfusé (IPRL). Elle visait ensuite à déterminer la cinétique enzymatique de chacune de ces deux substances, seule puis en mélange binaire. Dans un second temps, nous avons évalué aussi l’influence de la présence d'albumine sur la cinétique métabolique et le comportement de ces deux substances étudiées en suivant le même modèle de perfusion in vivo au niveau du foie de rat. Les constantes métaboliques ont été déterminées par régression non linéaire. Les métabolismes du BPA et du NAP seuls ont montré une cinétique saturable avec une vélocité maximale (Vmax) de 8.9 nmol/min/ mg prot de foie et une constante d'affinité de l'enzyme pour le substrat (Km) de 51.6 μM pour le BPA et de 3 nmol/min/mg prot de foie et 149.2 μM pour le NAP. L'analyse des expositions combinées suggère une inhibition compétitive partielle du métabolisme du BPA par le NAP avec une valeur de Ki estimée à 0.3542 μM. Les résultats obtenus montrent que l’analyse de risque pour les polluants environnementaux doit donc prendre en considération la consommation des produits pharmaceutiques comme facteur pouvant accroitre le niveau interne lors d’une exposition donnée. Ces données in vivo sur les interactions métaboliques pourraient être intégrées dans un modèle pharmacocinétique à base physiologique (PBPK) pour prédire les conséquences toxicococinétique (TK) de l'exposition d'un individu à ces mélanges chimiques.

Referral to rehabilitation following traumatic brain injury: a model for understanding inequities in access

Identifying inequities in access to health care requires critical scrutiny of the patterns and processes of care decisions. This paper describes a conceptual model. derived from social problems theory. which is proposed as a useful framework for explaining patterns of post-acute care referral and in particular, individual variations in referral to rehabilitation after traumatic brain injury (TBI). The model is based on three main components: (1) characteristics of the individual with TBI, (2) activities of health care professionals and the processes of referral. and (3) the contexts of care. The central argument is that access to rehabilitation following TBI is a dynamic phenomenon concerning the interpretations and negotiations of health care professionals. which in turn are shaped by the organisational and broader health care contexts. The model developed in this paper provides opportunity to develop a complex analysis of post-acute care referral based on patient factors, contextual factors and decision-making processes. It is anticipated that this framework will have utility in other areas examining and understanding patterns of access to health care. (C) 2002 Elsevier Science Ltd. All rights reserved.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.

Adsorption of p-nitrophenol in untreated and treated activated carbon

The adsorption of p-nitrophenol in one untreated activated carbon (F100) and three treated activated carbons (H-2, H2SO4 and Urea treated F100) was carried out at undissociated and dissociated conditions. To characterize the carbon, N-2 and CO2 adsorption were used. X-ray Photoelectron Spectroscopy (XPS) was used to analyze the surface of the activated carbon. The experimental isotherms are fitted via the Langmuir homogenous model and Langmuir binary model. Variation of the model parameters with the solution pH is studied. Both Q(max) and the adsorption affinity coefficient (K-1) were dependent on the PZC of the carbons and solution pH. The Effect of pH must be considered due to its combined effects on the carbon surface and on the solute molecules. Adsorption of p-nitrophenol at higher pH was found to be dependent on the concentration of the anionic form of the solute.

Lifetime cover in private insurance markets

In the last few decades, private health insurance rates have declined in many countries. In countries and states with community rating, a major cause is adverse selection. In order to address age-based adverse selection, Australia has recently begun a novel approach which imposes stiff penalties for buying private insurance later in life, when expected costs are higher. In this paper, we analyze Australiarsquos Lifetime Cover in the context of a modified version of the Rothschild-Stiglitz insurance model (Rothschild and Stiglitz, 1976). We allow empirically-based probabilities to increase by age for low-risk types. The model highlights the shortcomings of the Australian plan. Based on empirically-based probabilities of illness, we predict that Lifetime Cover will not arrest adverse selection. The model has many policy implications for government regulation encouraging long-term health coverage.

Gelatinization of starch in mixed sugar systems

Sugars affect the gelatinization of starch, with the effect varying significantly between sugars. Since many food products contain a mixture of sugar sources, it is important to understand how their mixtures affect starch gelatinization. In a Rapid Visco Analyser study of maize starch gelatinization, changing proportions in binary mixtures of refined sugars saw a largely proportionate change in starch gelatinization properties. However, binary mixture of pure sugars and honey, or a model honey system (the main sugars in honey) and honey responded differently. Generally, replacing 25% or 50% of the refined sugar or model honey system with honey gave a large change in starch gelatinization properties, while further increases in honey level had little further effect. Differences between honey and buffered model honey system (either gluconic acid, or a mixture of citric acid and di-sodium phosphate) showed the sensitivity of starch gelatinization to the composition of the nonsaccharide component. (c) 2004 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.

A simulation model of cereal-legume intercropping systems for semi-arid regions I. Model development

Cereal-legume intercropping plays an important role in subsistence food production in developing countries, especially in situations of limited water resources. Crop simulation can be used to assess risk for intercrop productivity over time and space. In this study, a simple model for intercropping was developed for cereal and legume growth and yield, under semi-arid conditions. The model is based on radiation interception and use, and incorporates a water stress factor. Total dry matter and yield are functions of photosynthetically active radiation (PAR), the fraction of radiation intercepted and radiation use efficiency (RUE). One of two PAR sub-models was used to estimate PAR from solar radiation; either PAR is 50% of solar radiation or the ratio of PAR to solar radiation (PAR/SR) is a function of the clearness index (K-T). The fraction of radiation intercepted was calculated either based on Beer's Law with crop extinction coefficients (K) from field experiments or from previous reports. RUE was calculated as a function of available soil water to a depth of 900 mm (ASW). Either the soil water balance method or the decay curve approach was used to determine ASW. Thus, two alternatives for each of three factors, i.e., PAR/SR, K and ASW, were considered, giving eight possible models (2 methods x 3 factors). The model calibration and validation were carried out with maize-bean intercropping systems using data collected in a semi-arid region (Bloemfontein, Free State, South Africa) during seven growing seasons (1996/1997-2002/2003). The combination of PAR estimated from the clearness index, a crop extinction coefficient from the field experiment and the decay curve model gave the most reasonable and acceptable result. The intercrop model developed in this study is simple, so this modelling approach can be employed to develop other cereal-legume intercrop models for semi-arid regions. (c) 2004 Elsevier B.V. All rights reserved.

Sexual selection for male dominance reduces opportunities for female mate choice in the European bitterling (Rhodeus sericeus)

Sexual selection involves two main mechanisms: intrasexual competition for mates and intersexual mate choice. We experimentally separated intrasexual (male-male interference competition) and intersexual (female choice) components of sexual selection in a freshwater fish, the European bitterling (Rhodeus sericeus). We compared the roles of multiple morphological and behavioural traits in male success in both components of sexual competition, and their relation to male reproductive success, measured as paternity of offspring. Body size was important for both female choice and male-male competition, though females also preferred males that courted more vigorously. However, dominant males often monopolized females regardless of female preference. Subordinate males were not excluded from reproduction and sired some offspring, possibly through sneaked ejaculations. Male dominance and a greater intensity of carotenoid-based red colouration in their iris were the best predictors of male reproductive success. The extent of red iris colouration and parasite load did not have significant effects on female choice, male dominance or male reproductive success. No effect of parasite load on the expression of red eye colouration was detected, though this may have been due to low parasite prevalence in males overall. In conclusion, we showed that even though larger body size was favoured in both intersexual and intrasexual selection, male-male interference competition reduced opportunities for female choice. Females, despite being choosy, had limited control over the paternity of their offspring. Our study highlights the need for reliable measures of male reproductive success in studies of sexual selection.

Evaluating trends in abundance of immature green turtles, Chelonia mydas, in the Greater Caribbean

Many long-lived marine species exhibit life history traits. that make them more vulnerable to overexploitation. Accurate population trend analysis is essential for development and assessment of management plans for these species. However, because many of these species disperse over large geographic areas, have life stages inaccessible to human surveyors, and/or undergo complex developmental migrations, data on trends in abundance are often available for only one stage of the population, usually breeding adults. The green turtle (Chelonia mydas) is one of these long-lived species for which population trends are based almost exclusively on either numbers of females that emerge to nest or numbers of nests deposited each year on geographically restricted beaches. In this study, we generated estimates of annual abundance for juvenile green turtles at two foraging grounds in the Bahamas based on long-term capture-mark-recapture (CMR) studies at Union Creek (24 years) and Conception Creek (13 years), using a two-stage approach. First, we estimated recapture probabilities from CMR data using the Cormack-Jolly-Seber models in the software program MARK; second, we estimated annual abundance of green turtles. at both study sites using the recapture probabilities in a Horvitz-Thompson type estimation procedure. Green turtle abundance did not change significantly in Conception Creek, but, in Union Creek, green turtle abundance had successive phases of significant increase, significant decrease, and stability. These changes in abundance resulted from changes in immigration, not survival or emigration. The trends in abundance on the foraging grounds did not conform to the significantly increasing trend for the major nesting population at Tortuguero, Costa Rica. This disparity highlights the challenges of assessing population-wide trends of green turtles and other long-lived species. The best approach for monitoring population trends may be a combination of (1) extensive surveys to provide data for large-scale trends in relative population abundance, and (2) intensive surveys, using CMR techniques, to estimate absolute abundance and evaluate the demographic processes' driving the trends.

A framework for the study of genetic variation in migratory behaviour

Evolutionary change results from selection acting on genetic variation. For migration to be successful, many different aspects of an animal's physiology and behaviour need to function in a co-coordinated way. Changes in one migratory trait are therefore likely to be accompanied by changes in other migratory and life-history traits. At present, we have some knowledge of the pressures that operate at the various stages of migration, but we know very little about the extent of genetic variation in various aspects of the migratory syndrome. As a consequence, our ability to predict which species is capable of what kind of evolutionary change, and at which rate, is limited. Here, we review how our evolutionary understanding of migration may benefit from taking a quantitative-genetic approach and present a framework for studying the causes of phenotypic variation. We review past research, that has mainly studied single migratory traits in captive birds, and discuss how this work could be extended to study genetic variation in the wild and to account for genetic correlations and correlated selection. In the future, reaction-norm approaches may become very important, as they allow the study of genetic and environmental effects on phenotypic expression within a single framework, as well as of their interactions. We advocate making more use of repeated measurements on single individuals to study the causes of among-individual variation in the wild, as they are easier to obtain than data on relatives and can provide valuable information for identifying and selecting traits. This approach will be particularly informative if it involves systematic testing of individuals under different environmental conditions. We propose extending this research agenda by using optimality models to predict levels of variation and covariation among traits and constraints. This may help us to select traits in which we might expect genetic variation, and to identify the most informative environmental axes. We also recommend an expansion of the passerine model, as this model does not apply to birds, like geese, where cultural transmission of spatio-temporal information is an important determinant of migration patterns and their variation.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Playing in continuous spaces: Some analysis and extension of population-based incremental learning

As an alternative to traditional evolutionary algorithms (EAs), population-based incremental learning (PBIL) maintains a probabilistic model of the best individual(s). Originally, PBIL was applied in binary search spaces. Recently, some work has been done to extend it to continuous spaces. In this paper, we review two such extensions of PBIL. An improved version of the PBIL based on Gaussian model is proposed that combines two main features: a new updating rule that takes into account all the individuals and their fitness values and a self-adaptive learning rate parameter. Furthermore, a new continuous PBIL employing a histogram probabilistic model is proposed. Some experiments results are presented that highlight the features of the new algorithms.

The dynamics of a genetic algorithm under stabilizing selection

A formalism recently introduced by Prugel-Bennett and Shapiro uses the methods of statistical mechanics to model the dynamics of genetic algorithms. To be of more general interest than the test cases they consider. In this paper, the technique is applied to the subset sum problem, which is a combinatorial optimization problem with a strongly non-linear energy (fitness) function and many local minima under single spin flip dynamics. It is a problem which exhibits an interesting dynamics, reminiscent of stabilizing selection in population biology. The dynamics are solved under certain simplifying assumptions and are reduced to a set of difference equations for a small number of relevant quantities. The quantities used are the population's cumulants, which describe its shape, and the mean correlation within the population, which measures the microscopic similarity of population members. Including the mean correlation allows a better description of the population than the cumulants alone would provide and represents a new and important extension of the technique. The formalism includes finite population effects and describes problems of realistic size. The theory is shown to agree closely to simulations of a real genetic algorithm and the mean best energy is accurately predicted.