Avaluació de la toxicitat de metalls pesants i arsènic en diferents models biològics

En aquest estudi, la toxicitat de diversos metalls pesants i l'arsènic va ser analitzada utilitzant diferents models biològics. En la primera part d'aquest treball, el bioassaig de toxicitat Microtox, el qual està basat en la variació de l'emissió lumínica del bacteri luminiscent Vibrio fischeri, va ser utilitzat per establir les corbes dosi-resposta de diferents elements tòxics com el Zn(II), Pb(II), Cu(II), Hg(II), Ag(I), Co(II), Cd(II), Cr(VI), As(V) i As(III) en solucions aquoses. Els experiments es varen portar a terme a pH 6.0 i 7.0 per tal de mostrar que el pH pot influir en la toxicitat final mesurada d'alguns metalls degut als canvis relacionats amb la seva especiació química. Es varen trobar diferents tipus de corbes dosi-resposta depenent del metall analitzat i el pH del medi. En el cas de l'arsènic, l'efecte del pH en la toxicitat de l'arsenat i l'arsenit es va investigar utilitzant l'assaig Microtox en un rang de pHs comprès entre pH 5.0 i 9.0. Els valors d'EC50 determinats per l'As(V) disminueixen, reflectint un augment de la toxicitat, a mesura que el pH de la solució augmenta mentre que, en el cas de l'As(III), els valors d'EC50 quasi bé no varien entre pH 6.0 i 8.0 i només disminueixen a pH 9.0. HAsO42- i H2AsO3- es varen definir com les espècies més tòxiques. Així mateix, una anàlisi estadística va revelar un efecte antagònic entre les espècies químiques d'arsenat que es troben conjuntament a pH 6.0 i 7.0. D'altra banda, els resultats de dos mètodes estadístics per predir la toxicitat i les possibles interaccions entre el Co(II), Cd(II), Cu(II), Zn(II) i Pb(II) en mescles binàries equitòxiques es varen comparar amb la toxicitat observada sobre el bacteri Vibrio fischeri. L'efecte combinat d'aquests metalls va resultar ser antagònic per les mescles de Co(II)-Cd(II), Cd(II)-Zn(II), Cd(II)-Pb(II) i Cu(II)-Pb(II), sinèrgic per Co(II)-Cu(II) i Zn(II)-Pb(II) i additiu en els altres casos, revelant un patró complex de possibles interaccions. L'efecte sinèrgic de la combinació Co(II)-Cu(II) i la forta disminució de la toxicitat del Pb(II) quan es troba en presència de Cd(II) hauria de merèixer més atenció quan s'estableixen les normatives de seguretat ambiental. La sensibilitat de l'assaig Microtox també va ser determinada. Els valors d'EC20, els quals representen la toxicitat llindar mesurable, varen ser determinats per cada element individualment i es va veure que augmenten de la següent manera: Pb(II) < Ag(I) < Hg(II)  Cu(II) < Zn(II) < As(V) < Cd(II)  Co(II) < As(III) < Cr(VI). Aquests valors es varen comparar amb les concentracions permeses en aigues residuals industrials establertes per la normativa oficial de Catalunya (Espanya). L'assaig Microtox va resultar ser suficientment sensible per detectar els elements assajats respecte a les normes oficials referents al control de la contaminació, excepte en el cas del cadmi, mercuri, arsenat, arsenit i cromat. En la segona part d'aquest treball, com a resultats complementaris dels resultats previs obtinguts utilitzant l'assaig de toxicitat aguda Microtox, els efectes crònics del Cd(II), Cr(VI) i As(V) es varen analitzar sobre la taxa de creixement i la viabilitat en el mateix model biològic. Sorprenentment, aquests productes químics nocius varen resultar ser poc tòxics per aquest bacteri quan es mesura el seu efecte després de temps d'exposició llargs. Tot i això, en el cas del Cr(VI), l'assaig d'inhibició de la viabilitat va resultar ser més sensible que l'assaig de toxicitat aguda Microtox. Així mateix, també va ser possible observar un clar fenomen d'hormesis, especialment en el cas del Cd(II), quan s'utilitza l'assaig d'inhibició de la viabilitat. A més a més, diversos experiments es varen portar a terme per intentar explicar la manca de toxicitat de Cr(VI) mostrada pel bacteri Vibrio fischeri. La resistència mostrada per aquest bacteri podria ser atribuïda a la capacitat d'aquest bacteri de convertir el Cr(VI) a la forma menys tòxica de Cr(III). Es va trobar que aquesta capacitat de reducció depèn de la composició del medi de cultiu, de la concentració inicial de Cr(VI), del temps d'incubació i de la presència d'una font de carboni. En la tercera part d'aquest treball, la línia cel·lular humana HT29 i cultius primaris de cèl·lules sanguínies de Sparus sarba es varen utilitzar in vitro per detectar la toxicitat llindar de metalls mesurant la sobreexpressió de proteines d'estrès. Extractes de fangs precedents de diverses plantes de tractament d'aigues residuals i diferents metalls, individualment o en combinació, es varen analitzar sobre cultius cel·lulars humans per avaluar el seu efecte sobre la taxa de creixement i la capacitat d'induir la síntesi de les proteïnes Hsp72 relacionades amb l'estrès cel·lular. No es varen trobar efectes adversos significatius quan els components s'analitzen individualment. Nogensmenys, quan es troben conjuntament, es produeix un afecte advers sobre tan la taxa de creixement com en l'expressió de proteins d'estrès. D'altra banda, cèl·lules sanguínies procedents de Sparus sarba es varen exposar in vitro a diferents concentracions de cadmi, plom i crom. La proteïna d'estrès HSP70 es va sobreexpressar significativament després de l'exposició a concentracions tan febles com 0.1 M. Sota les nostres condicions de treball, no es va evidenciar una sobreexpressió de metal·lotioneïnes. Nogensmenys, les cèl·lules sanguínies de peix varen resultar ser un model biològic interessant per a ser utilitzat en anàlisis de toxicitat. Ambdós models biològics varen resultar ser molt adequats per a detectar acuradament la toxicitat produïda per metalls. En general, l'avaluació de la toxicitat basada en l'anàlisi de la sobreexpressió de proteïnes d'estrès és més sensible que l'avaluació de la toxicitat realitzada a nivell d'organisme. A partir dels resultats obtinguts, podem concloure que una bateria de bioassaigs és realment necessària per avaluar acuradament la toxicitat de metalls ja que existeixen grans variacions entre els valors de toxicitat obtinguts emprant diferents organismes i molts factors ambientals poden influir i modificar els resultats obtinguts.

A comparison of three canopy interception models for a leafless mixed deciduous forest stand in the eastern United States

Canopy interception of incident precipitation is a critical component of the forest water balance during each of the four seasons. Models have been developed to predict precipitation interception from standard meteorological variables because of acknowledged difficulty in extrapolating direct measurements of interception loss from forest to forest. No known study has compared and validated canopy interception models for a leafless deciduous forest stand in the eastern United States. Interception measurements from an experimental plot in a leafless deciduous forest in northeastern Maryland (39°42'N, 75°5'W) for 11 rainstorms in winter and early spring 2004/05 were compared to predictions from three models. The Mulder model maintains a moist canopy between storms. The Gash model requires few input variables and is formulated for a sparse canopy. The WiMo model optimizes the canopy storage capacity for the maximum wind speed during each storm. All models showed marked underestimates and overestimates for individual storms when the measured ratio of interception to gross precipitation was far more or less, respectively, than the specified fraction of canopy cover. The models predicted the percentage of total gross precipitation (PG) intercepted to within the probable standard error (8.1%) of the measured value: the Mulder model overestimated the measured value by 0.1% of PG; the WiMo model underestimated by 0.6% of PG; and the Gash model underestimated by 1.1% of PG. The WiMo model’s advantage over the Gash model indicates that the canopy storage capacity increases logarithmically with the maximum wind speed. This study has demonstrated that dormant-season precipitation interception in a leafless deciduous forest may be satisfactorily predicted by existing canopy interception models.

Marine ecosystem models for earth systems applications: the MarQUEST experience

The MarQUEST (Marine Biogeochemistry and Ecosystem Modelling Initiative in QUEST) project was established to develop improved descriptions of marine biogeochemistry, suited for the next generation of Earth system models. We review progress in these areas providing insight on the advances that have been made as well as identifying remaining key outstanding gaps for the development of the marine component of next generation Earth system models. The following issues are discussed and where appropriate results are presented; the choice of model structure, scaling processes from physiology to functional types, the ecosystem model sensitivity to changes in the physical environment, the role of the coastal ocean and new methods for the evaluation and comparison of ecosystem and biogeochemistry models. We make recommendations as to where future investment in marine ecosystem modelling should be focused, highlighting a generic software framework for model development, improved hydrodynamic models, and better parameterisation of new and existing models, reanalysis tools and ensemble simulations. The final challenge is to ensure that experimental/observational scientists are stakeholders in the models and vice versa.

Intrinsic disorder prediction from the analysis of multiple protein fold recognition models

Motivation: Intrinsic protein disorder is functionally implicated in numerous biological roles and is, therefore, ubiquitous in proteins from all three kingdoms of life. Determining the disordered regions in proteins presents a challenge for experimental methods and so recently there has been much focus on the development of improved predictive methods. In this article, a novel technique for disorder prediction, called DISOclust, is described, which is based on the analysis of multiple protein fold recognition models. The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified. Results: The DISOclust method is shown to add the most value to a simple consensus of methods, even in the absence of target sequence homology to known structures. A simple consensus of methods that includes DISOclust can significantly outperform all of the previous individual methods tested.

Antiviral effects of antisense morpholino oligomers in murine coronavirus infection models

The recent emergence of novel pathogenic human and animal coronaviruses has highlighted the need for antiviral therapies that are effective against a spectrum of these viruses. We have used several strains of murine hepatitis virus (MHV) in cell culture and in vivo in mouse models to investigate the antiviral characteristics of peptide-conjugated antisense phosphorodiamidate morpholino oligomers (P-PMOs). Ten P-PMOs directed against various target sites in the viral genome were tested in cell culture, and one of these (5TERM), which was complementary to the 5' terminus of the genomic RNA, was effective against six strains of MHV. Further studies were carried out with various arginine-rich peptides conjugated to the 5TERM PMO sequence in order to evaluate efficacy and toxicity and thereby select candidates for in vivo testing. In uninfected mice, prolonged P-PMO treatment did not result in weight loss or detectable histopathologic changes. 5TERM P-PMO treatment reduced viral titers in target organs and protected mice against virus-induced tissue damage. Prophylactic 5TERM P-PMO treatment decreased the amount of weight loss associated with infection under most experimental conditions. Treatment also prolonged survival in two lethal challenge models. In some cases of high-dose viral inoculation followed by delayed treatment, 5TERM P-PMO treatment was not protective and increased morbidity in the treated group, suggesting that P-PMO may cause toxic effects in diseased mice that were not apparent in the uninfected animals. However, the strong antiviral effect observed suggests that with further development, P-PMO may provide an effective therapeutic approach against a broad range of coronavirus infections.

Population genetic models can be used to study the evolution of the interacting behaviours of parents and their progeny

An example of the evolution of the interacting behaviours of parents and progeny is studied using iterative equations linking the frequencies of the gametes produced by the progeny to the frequencies of the gametes in the parental generation. This population genetics approach shows that a model in which both behaviours are determined by a single locus can lead to a stable equilibrium in which the two behaviours continue to segregate. A model in which the behaviours are determined by genes at two separate loci leads eventually to fixation of the alleles at both loci but this can take many generations of selection. Models of the type described in this paper will be needed to understand the evolution of complex behaviour when genomic or experimental information is available about the genetic determinants of behaviour and the selective values of different genomes. (c) 2007 Elsevier Inc. All rights reserved.

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

Models of windblown pollen or spore movement are required to predict gene flow from genetically modified (GM) crops and the spread of fungal diseases. We suggest a simple form for a function describing the distance moved by a pollen grain or fungal spore, for use in generic models of dispersal. The function has power-law behaviour over sub-continental distances. We show that air-borne dispersal of rapeseed pollen in two experiments was inconsistent with an exponential model, but was fitted by power-law models, implying a large contribution from distant fields to the catches observed. After allowance for this 'background' by applying Fourier transforms to deconvolve the mixture of distant and local sources, the data were best fit by power-laws with exponents between 1.5 and 2. We also demonstrate that for a simple model of area sources, the median dispersal distance is a function of field radius and that measurement from the source edge can be misleading. Using an inverse-square dispersal distribution deduced from the experimental data and the distribution of rapeseed fields deduced by remote sensing, we successfully predict observed rapeseed pollen density in the city centres of Derby and Leicester (UK).

Aldose reductase and the importance of experimental design

Kinetic studies on the AR (aldose reductase) protein have shown that it does not behave as a classical enzyme in relation to ring aldose sugars. As with non-enzymatic glycation reactions, there is probably a free radical element involved derived from monosaccharide autoxidation. in the case of AR, there is free radical oxidation of NADPH by autoxidizing monosaccharides, which is enhanced in the presence of the NADPH-binding protein. Thus any assay for AR based on the oxidation of NADPH in the presence of autoxidizing monosaccharides is invalid, and tissue AR measurements based on this method are also invalid, and should be reassessed. AR exhibits broad specificity for both hydrophilic and hydrophobic aldehydes that suggests that the protein may be involved in detoxification. The last thing we would want to do is to inhibit it. ARIs (AR inhibitors) have a number of actions in the cell which are not specific, and which do not involve them binding to AR. These include peroxy-radical scavenging and effects of metal ion chelation. The AR/ARI story emphasizes the importance of correct experimental design in all biocatalytic experiments. Developing the use of Bayesian utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has led to the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K-m and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimizes the error in the parameters estimated, and is suitable for simple or complex steady-state models.

Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

In areas such as drug development, clinical diagnosis and biotechnology research, acquiring details about the kinetic parameters of enzymes is crucial. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. We demonstrate that a Bayesian approach (the use of prior knowledge) can produce major gains quantifiable in terms of information, productivity and accuracy of each experiment. Developing the use of Bayesian Utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has enabled the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K-M and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. (C) 2003 Elsevier Science B.V. All rights reserved.

Evaluation of data for atmospheric models: master equation/RRKM calculations on the combination reaction, BrO+NO2 -> BrONO2, a conundrum

Experimental data for the title reaction were modeled using master equation (ME)/RRKM methods based on the Multiwell suite of programs. The starting point for the exercise was the empirical fitting provided by the NASA (Sander, S. P.; Finlayson-Pitts, B. J.; Friedl, R. R.; Golden, D. M.; Huie, R. E.; Kolb, C. E.; Kurylo, M. J.; Molina, M. J.; Moortgat, G. K.; Orkin, V. L.; Ravishankara, A. R. Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation Number 15; Jet Propulsion Laboratory: Pasadena, California, 2006)(1) and IUPAC (Atkinson, R.; Baulch, D. L.; Cox, R. A.: R. F. Hampson, J.; Kerr, J. A.; Rossi, M. J.; Troe, J. J. Phys. Chem. Ref. Data. 2000, 29, 167) 2 data evaluation panels, which represents the data in the experimental pressure ranges rather well. Despite the availability of quite reliable parameters for these calculations (molecular vibrational frequencies (Parthiban, S.; Lee, T. J. J. Chem. Phys. 2000, 113, 145)3 and a. value (Orlando, J. J.; Tyndall, G. S. J. Phys. Chem. 1996, 100,. 19398)4 of the bond dissociation energy, D-298(BrO-NO2) = 118 kJ mol(-1), corresponding to Delta H-0(circle) = 114.3 kJ mol(-1) at 0 K) and the use of RRKM/ME methods, fitting calculations to the reported data or the empirical equations was anything but straightforward. Using these molecular parameters resulted in a discrepancy between the calculations and the database of rate constants of a factor of ca. 4 at, or close to, the low-pressure limit. Agreement between calculation and experiment could be achieved in two ways, either by increasing Delta H-0(circle) to an unrealistically high value (149.3 kJ mol(-1)) or by increasing , the average energy transferred in a downward collision, to an unusually large value (> 5000 cm(-1)). The discrepancy could also be reduced by making all overall rotations fully active. The system was relatively insensitive to changing the moments of inertia in the transition state to increase the centrifugal effect. The possibility of involvement of BrOONO was tested and cannot account for the difficulties of fitting the data.

Kinetic models as a route to control acrylamide formation in food

Reports that heat processing of foods induces the formation of acrylamide heightened interest in the chemistry, biochemistry, and safety of this compound. Acrylamide-induced neurotoxicity, reproductive toxicity, genotoxicity, and carcinogenicity are potential human health risks based on animal studies. Because exposure of humans to acrylamide can come from both external sources and the diet, there exists a need to develop a better understanding of its formation and distribution in food and its role in human health. To contribute to this effort, experts from eight countries have presented data on the chemistry, analysis, metabolism, pharmacology, and toxicology of acrylamide. Specifically covered are the following aspects: exposure from the environment and the diet; biomarkers of exposure; risk assessment; epidemiology; mechanism of formation in food; biological alkylation of amino acids, peptides, proteins, and DNA by acrylamide and its epoxide metabolite glycidamide; neurotoxicity, reproductive toxicity, and carcinogenicity; protection against adverse effects; and possible approaches to reducing levels in food. Cross-fertilization of ideas among several disciplines in which an interest in acrylamide has developed, including food science, pharmacology, toxicology, and medicine, will provide a better understanding of the chemistry and biology of acrylamide in food, and can lead to the development of food processes to decrease the acrylamide content of the diet.

Theoretical and experimental approaches towards the determination of solute effective diffusivities in foods

The aim of this review paper is to present experimental methodologies and the mathematical approaches used to determine effective diffusivities of solutes in food materials. The paper commences by describing the diffusion phenomena related to solute mass transfer in foods and effective diffusivities. It then focuses on the mathematical formulation for the calculation of effective diffusivities considering different diffusion models based on Fick's second law of diffusion. Finally, experimental considerations for effective diffusivity determination are elucidated primarily based on the acquirement of a series of solute content versus time curves appropriate to the equation model chosen. Different factors contributing to the determination of the effective diffusivities such as the structure of food material, temperature, diffusion solvent, agitation, sampling, concentration and different techniques used are considered. (c) 2005 Elsevier Inc. All rights reserved.

Crumpet structures: experimental and modelling studies

Crumpets are made by heating fermented batter on a hot plate at around 230°C. The characteristic structure dominated by vertical pores develops rapidly: structure has developed throughout around 75% of the product height within 30s, which is far faster than might be expected from transient heat conduction through the batter. Cooking is complete within around 3 min. Image analysis based on results from X-ray tomography shows that the voidage fraction is approximately constant and that there is continual coalescence between the larger pores throughout the product although there is also a steady level of small bubbles trapped within the solidified batter. We report here experimental studies which shed light on some of the mechanisms responsible for this structure, together with some models of key phenomena.Three aspects are discussed here: the role of gas (carbon dioxide and nitrogen) nuclei in initiating structure development; convective heat transfer inside the developing pores; and the kinetics of setting the batter into an elastic solid structure. It is shown conclusively that the small bubbles of carbon dioxide resulting from the fermentation stage play a crucial role as nuclei for pore development: without these nuclei, the result is not a porous structure, but rather a solid, elastic, inedible, gelatinized product. These nuclei are also responsible for the tiny bubbles which are set in the final product. The nuclei form the source of the dominant pore structure which is largely driven by the, initially explosive, release of water vapour from the batter together with the desorption of dissolved carbon dioxide. It is argued that the rapid evaporation, transport and condensation of steam within the growing pores provides an important mechanism, as in a heat pipe, for rapid heat transfer, and models for this process are developed and tested. The setting of the continuous batter phase is essential for final product quality: studies using differential scanning calorimetry and on the kinetics of change in the visco-elastic properties of the batter suggest that this process is driven by the kinetics of gelatinization. Unlike many thermally driven food processes the rates of heating are such that gelatinization kinetics cannot be neglected. The implications of these results for modelling and for the development of novel structures are discussed.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.