Tracking and identifying wastewater toxicants and assessing their biodegradation products

Screening of wastewater effluents from municipal and industrial wastewater treatment plants with biotests showed that the treated wastewater effluents possess only minor acute toxic properties towards whole organisms (e.g. bacteria, algae, daphnia), if any. In vitro tests (sub-mitochondrial membranes and fish hepatocytes) were generally more susceptible to the effluents. Most of the effluents indicated the presence of hormonally active compounds, as the production of vitellogenin, an egg yolk precursor protein, was induced in fish hepatocytes exposed to wastewater. In addition, indications of slight genotoxic potential was found in one effluent concentrate with a recombinant bacteria test. Reverse electron transport (RET) of mitochondrial membranes was used as a model test to conduct effluent assessment followed by toxicant characterisations and identifications. Using a modified U.S. EPA Toxicity Identification Evaluation Phase I scheme and additional case-specific methods, the main compound in a pulp and paper mill effluent causing RET inhibition was characterised to be an organic, relatively hydrophilic high molecular weight (HMW) compound. The toxicant could be verified as HMW lignin by structural analyses using nuclear magnetic resonance. In the confirmation step commercial and in-house extracted lignin products were used. The possible toxicity related structures were characterised by statistical analysis of the chemical breakdown structures of laboratory-scale pulping and bleaching effluents and the toxicities of these effluents. Finally, the biological degradation of the identified toxicant and other wastewater constituents was evaluated using bioassays in combination with chemical analyses. Biological methods have not been used routinely in establishing effluent discharge limits in Finland. However, the biological effects observed in this study could not have been predicted using only routine physical and chemical effluent monitoring parameters. Therefore chemical parameters cannot be considered to be sufficient in controlling effluent discharges especially in case of unknown, possibly bioaccumulative, compounds that may be present in small concentrations and may cause chronic effects.

Protein cross-linking with oxidative enzymes and transglutaminase : Effects in meat protein systems

The effects of tyrosinase, laccase and transglutaminase (TG) were studied in different meat protein systems. The study was focused on the effects of the enzymes on the gel formation properties of myofibrils, and on the textural and water-holding properties of the heated meat systems. The cross-linking efficiency of a novel Trichoderma reesei tyrosinase was compared to that of the commercial Agaricus bisporus tyrosinase. Trichoderma tyrosinase was found to be superior compared to the Agaricus enzyme in its protein cross-linking efficiency and in the incorporation of a small molecule into a complex proteinaceous substrate. Tyrosinase, laccase and TG all polymerised myofibrillar proteins, but laccase was also found to cause protein fragmentation. A positive connection between covalent cross-link and gel formation was observed with tyrosinase and TG. Laccase was able to increase the gel formation only slightly. With an excessive laccase dosage the gel formation declined due to protein fragmentation. Tyrosinase, laccase and TG had different effects on the texture and water-holding of the heated chicken breast meat homogenates. Tyrosinase improved the firmness of the homogenate gels free of phosphate and with a low amount of meat. TG improved the firmness of all studied homogenates. Laccase weakened the gel firmness of the low-meat, low-salt and low-salt/phosphate homogenates and maintained the firmness on the control level in the homogenate free of phosphate. Tyrosinase was the only enzyme capable of reducing the weight loss in the homogenates containing a low amount of meat and a low amount of NaCl. TG was the only enzyme that could positively affect the firmness of the homogenate gel containing both low NaCl and phosphate amounts. In pilot scale the test products were made of coarsely ground chicken breast fillet with a moderate amount of salt. Increasining the amount of meat, salt and TG contents favoured the development of firmness of the test products. The evaporation loss decreased slightly along with increasing TG and NaCl amounts in the experimental conditions used, indicating a positive interaction between these two factors. In this work it was shown that tyrosinase, laccase and TG affected the same myofibrillar proteins, i.e. myosin and troponin T. However, these enzymes had distinguishable effects on the gel formation of a myofibril system as well as on the textural and water-holding properties of the finely ground meat homogenates, reflecting distinctions at least in the reaction mechanisms and target amino acid availability in the protein substrates for these enzymes.

On the behaviour of some physical parameterization methods in high-resolution numerical weather prediction models

Modern-day weather forecasting is highly dependent on Numerical Weather Prediction (NWP) models as the main data source. The evolving state of the atmosphere with time can be numerically predicted by solving a set of hydrodynamic equations, if the initial state is known. However, such a modelling approach always contains approximations that by and large depend on the purpose of use and resolution of the models. Present-day NWP systems operate with horizontal model resolutions in the range from about 40 km to 10 km. Recently, the aim has been to reach operationally to scales of 1 4 km. This requires less approximations in the model equations, more complex treatment of physical processes and, furthermore, more computing power. This thesis concentrates on the physical parameterization methods used in high-resolution NWP models. The main emphasis is on the validation of the grid-size-dependent convection parameterization in the High Resolution Limited Area Model (HIRLAM) and on a comprehensive intercomparison of radiative-flux parameterizations. In addition, the problems related to wind prediction near the coastline are addressed with high-resolution meso-scale models. The grid-size-dependent convection parameterization is clearly beneficial for NWP models operating with a dense grid. Results show that the current convection scheme in HIRLAM is still applicable down to a 5.6 km grid size. However, with further improved model resolution, the tendency of the model to overestimate strong precipitation intensities increases in all the experiment runs. For the clear-sky longwave radiation parameterization, schemes used in NWP-models provide much better results in comparison with simple empirical schemes. On the other hand, for the shortwave part of the spectrum, the empirical schemes are more competitive for producing fairly accurate surface fluxes. Overall, even the complex radiation parameterization schemes used in NWP-models seem to be slightly too transparent for both long- and shortwave radiation in clear-sky conditions. For cloudy conditions, simple cloud correction functions are tested. In case of longwave radiation, the empirical cloud correction methods provide rather accurate results, whereas for shortwave radiation the benefit is only marginal. Idealised high-resolution two-dimensional meso-scale model experiments suggest that the reason for the observed formation of the afternoon low level jet (LLJ) over the Gulf of Finland is an inertial oscillation mechanism, when the large-scale flow is from the south-east or west directions. The LLJ is further enhanced by the sea-breeze circulation. A three-dimensional HIRLAM experiment, with a 7.7 km grid size, is able to generate a similar LLJ flow structure as suggested by the 2D-experiments and observations. It is also pointed out that improved model resolution does not necessary lead to better wind forecasts in the statistical sense. In nested systems, the quality of the large-scale host model is really important, especially if the inner meso-scale model domain is small.

Aspects of Inflationary Models at Low Energy Scales

Cosmological inflation is the dominant paradigm in explaining the origin of structure in the universe. According to the inflationary scenario, there has been a period of nearly exponential expansion in the very early universe, long before the nucleosynthesis. Inflation is commonly considered as a consequence of some scalar field or fields whose energy density starts to dominate the universe. The inflationary expansion converts the quantum fluctuations of the fields into classical perturbations on superhorizon scales and these primordial perturbations are the seeds of the structure in the universe. Moreover, inflation also naturally explains the high degree of homogeneity and spatial flatness of the early universe. The real challenge of the inflationary cosmology lies in trying to establish a connection between the fields driving inflation and theories of particle physics. In this thesis we concentrate on inflationary models at scales well below the Planck scale. The low scale allows us to seek for candidates for the inflationary matter within extensions of the Standard Model but typically also implies fine-tuning problems. We discuss a low scale model where inflation is driven by a flat direction of the Minimally Supersymmetric Standard Model. The relation between the potential along the flat direction and the underlying supergravity model is studied. The low inflationary scale requires an extremely flat potential but we find that in this particular model the associated fine-tuning problems can be solved in a rather natural fashion in a class of supergravity models. For this class of models, the flatness is a consequence of the structure of the supergravity model and is insensitive to the vacuum expectation values of the fields that break supersymmetry. Another low scale model considered in the thesis is the curvaton scenario where the primordial perturbations originate from quantum fluctuations of a curvaton field, which is different from the fields driving inflation. The curvaton gives a negligible contribution to the total energy density during inflation but its perturbations become significant in the post-inflationary epoch. The separation between the fields driving inflation and the fields giving rise to primordial perturbations opens up new possibilities to lower the inflationary scale without introducing fine-tuning problems. The curvaton model typically gives rise to relatively large level of non-gaussian features in the statistics of primordial perturbations. We find that the level of non-gaussian effects is heavily dependent on the form of the curvaton potential. Future observations that provide more accurate information of the non-gaussian statistics can therefore place constraining bounds on the curvaton interactions.

Zebrafish as a model of Parkinson's disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease among the elderly. Its etiology is unknown and no disease-modifying drugs are available. Thus, more information concerning its pathogenesis is needed. Among other genes, mutated PTEN-induced kinase 1 (PINK1) has been linked to early-onset and sporadic PD, but its mode of action is poorly understood. Most animal models of PD are based on the use of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). MPTP is metabolized to MPP+ by monoamine oxidase B (MAO B) and causes cell death of dopaminergic neurons in the substantia nigra in mammals. Zebrafish has been a widely used model organism in developmental biology, but is now emerging as a model for human diseases due to its ideal combination of properties. Zebrafish are inexpensive and easy to maintain, develop rapidly, breed in large quantities producing transparent embryos, and are readily manipulated by various methods, particularly genetic ones. In addition, zebrafish are vertebrate animals and results derived from zebrafish may be more applicable to mammals than results from invertebrate genetic models such as Drosophila melanogaster and Caenorhabditis elegans. However, the similarity cannot be taken for granted. The aim of this study was to establish and test a PD model using larval zebrafish. The developing monoaminergic neuronal systems of larval zebrafish were investigated. We identified and classified 17 catecholaminergic and 9 serotonergic neuron populations in the zebrafish brain. A 3-dimensional atlas was created to facilitate future research. Only one gene encoding MAO was found in the zebrafish genome. Zebrafish MAO showed MAO A-type substrate specificity, but non-A-non-B inhibitor specificity. Distribution of MAO in larval and adult zebrafish brains was both diffuse and distinctly cellular. Inhibition of MAO during larval development led to markedly elevated 5-hydroxytryptamine (serotonin, 5-HT) levels, which decreased the locomotion of the fish. MPTP exposure caused a transient loss of cells in specific aminergic cell populations and decreased locomotion. MPTP-induced changes could be rescued by the MAO B inhibitor deprenyl, suggesting a role for MAO in MPTP toxicity. MPP+ affected only one catecholaminergic cell population; thus, the action of MPP+ was more selective than that of MPTP. The zebrafish PINK1 gene was cloned in zebrafish, and morpholino oligonucleotides were used to suppress its expression in larval zebrafish. The functional domains and expression pattern of zebrafish PINK1 resembled those of other vertebrates, suggesting that zebrafish is a feasible model for studying PINK1. Translation inhibition resulted in cell loss of the same catecholaminergic cell populations as MPTP and MPP+. Inactivation of PINK1 sensitized larval zebrafish to subefficacious doses of MPTP, causing a decrease in locomotion and cell loss in one dopaminergic cell population. Zebrafish appears to be a feasible model for studying PD, since its aminergic systems, mode of action of MPTP, and functions of PINK1 resemble those of mammalians. However, the functions of zebrafish MAO differ from the two forms of MAO found in mammals. Future studies using zebrafish PD models should utilize the advantages specific to zebrafish, such as the ability to execute large-scale genetic or drug screens.

Bootstrapping the Error Correction Model Cointegration Test

This paper is concerned with using the bootstrap to obtain improved critical values for the error correction model (ECM) cointegration test in dynamic models. In the paper we investigate the effects of dynamic specification on the size and power of the ECM cointegration test with bootstrap critical values. The results from a Monte Carlo study show that the size of the bootstrap ECM cointegration test is close to the nominal significance level. We find that overspecification of the lag length results in a loss of power. Underspecification of the lag length results in size distortion. The performance of the bootstrap ECM cointegration test deteriorates if the correct lag length is not used in the ECM. The bootstrap ECM cointegration test is therefore not robust to model misspecification.