IgA nephropathy and Henoch-Schönlein nephritis in adults : with special reference to factors affecting outcome

IgA nephropathy (IgAN) is the most common primary glomerulonephritis. In one third of the patients the disease progresses, and they eventually need renal replacement therapy. IgAN is in most cases a slowly progressing disease, and the prediction of progression has been difficult, and the results of studies have been conflicting. Henoch-Schönlein nephritis (HSN) is rare in adults, and prediction of the outcome is even more difficult than in IgAN. This study was conducted to evaluate the clinical and histopathological features and predictors of the outcome of IgAN and HSN diagnosed in one centre (313 IgAN patients and 38 HSN patients), and especially in patients with normal renal function at the time of renal biopsy. The study also aimed to evaluate whether there is a difference in the progression rates in four countries (259 patients from Finland, 112 from UK, 121 from Australia and 274 from Canada), and if so, can this be explained by differences in renal biopsy policy. The third aim was to measure urinary excretions of cytokines interleukin 1ß (IL-1ß) and interleukin 1 receptor antagonist (IL-1ra) in patients with IgAN and HSN and the correlations of excretion of these substances with histopathological damage and clinical factors. A large proportion of the patients diagnosed in Helsinki as having IgAN had normal renal function (161/313 patients). Four factors, (hypertension, higher amounts of urinary erythrocytes, severe arteriolosclerosis and a higher glomerular score) which independently predicted progression (logistic regression analysis), were identified in mild disease. There was geographic variability in renal survival in patients with IgAN. When age, levels of renal function, proteinuria and blood pressure were taken into account, it showed that the variability related mostly to lead-time bias and renal biopsy indications. Amount of proteinuria more than 0.4g/24h was the only factor that was significantly related to the progression of HSN. the Hypertension and the level of renal function were found to be factors predicting outcome in patients with normal renal function at the time of diagnosis. In IgAN patients, IL-1ra excretion into urine was found to be decreased as compared with HSN patients and healthy controls. Patients with a high IL-1ra/IL-1ß ratio had milder histopathological changes in renal biopsy than patients with a low/normal IL-1ra/IL-1ß ratio. It was also found that the excretion of IL-1ß and especially IL-1ra were significantly higher in women. In conclusion, it was shown that factors associated with outcome can reliably be identified even in mild cases of IgAN. Predicting outcome in adult HSN, however, remains difficult.

Modelling of solute transport in a mild heterogeneous porous medium using stochastic finite element method: Effects of random source conditions

Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.

Improving GPS time series for geodynamic studies

Accurate and stable time series of geodetic parameters can be used to help in understanding the dynamic Earth and its response to global change. The Global Positioning System, GPS, has proven to be invaluable in modern geodynamic studies. In Fennoscandia the first GPS networks were set up in 1993. These networks form the basis of the national reference frames in the area, but they also provide long and important time series for crustal deformation studies. These time series can be used, for example, to better constrain the ice history of the last ice age and the Earth s structure, via existing glacial isostatic adjustment models. To improve the accuracy and stability of the GPS time series, the possible nuisance parameters and error sources need to be minimized. We have analysed GPS time series to study two phenomena. First, we study the refraction in the neutral atmosphere of the GPS signal, and, second, we study the surface loading of the crust by environmental factors, namely the non-tidal Baltic Sea, atmospheric load and varying continental water reservoirs. We studied the atmospheric effects on the GPS time series by comparing the standard method to slant delays derived from a regional numerical weather model. We have presented a method for correcting the atmospheric delays at the observational level. The results show that both standard atmosphere modelling and the atmospheric delays derived from a numerical weather model by ray-tracing provide a stable solution. The advantage of the latter is that the number of unknowns used in the computation decreases and thus, the computation may become faster and more robust. The computation can also be done with any processing software that allows the atmospheric correction to be turned off. The crustal deformation due to loading was computed by convolving Green s functions with surface load data, that is to say, global hydrology models, global numerical weather models and a local model for the Baltic Sea. The result was that the loading factors can be seen in the GPS coordinate time series. Reducing the computed deformation from the vertical time series of GPS coordinates reduces the scatter of the time series; however, the long term trends are not influenced. We show that global hydrology models and the local sea surface can explain up to 30% of the GPS time series variation. On the other hand atmospheric loading admittance in the GPS time series is low, and different hydrological surface load models could not be validated in the present study. In order to be used for GPS corrections in the future, both atmospheric loading and hydrological models need further analysis and improvements.

A Historical Approach to Children s Physics Education : Modelling of DC-circuit Phenomena in a Small Group

This three-phase design research describes the modelling processes for DC-circuit phenomena. The first phase presents an analysis of the development of the DC-circuit historical models in the context of constructing Volta s pile at the turn of the 18th century. The second phase involves the designing of a teaching experiment for comprehensive school third graders. Among other considerations, the design work utilises the results of the first phase and research literature of pupils mental models for DC-circuit phenomena. The third phase of the research was concerned with the realisation of the planned teaching experiment. The aim of this phase was to study the development of the external representations of DC-circuit phenomena in a small group of third graders. The aim of the study has been to search for new ways to guide pupils to learn DC-circuit phenomena while emphasing understanding at the qualitative level. Thus, electricity, which has been perceived as a difficult and abstract subject, could be learnt more comprehensively. Especially, the research of younger pupils learning of electricity concepts has not been of great interest at the international level, although DC-circuit phenomena are also taught in the lower classes of comprehensive schools. The results of this study are important, because there has tended to be more teaching of natural sciences in the lower classes of comprehensive schools, and attempts are being made to develop this trend in Finland. In the theoretical part of the research an Experimental-centred representation approach, which emphasises the role of experimentalism in the development of pupil s representations, is created. According to this approach learning at the qualitative level consists of empirical operations like experimenting, observations, perception, and prequantification of nature phenomena, and modelling operations like explaining and reasoning. Besides planning teaching, the new approach can be used as an analysis tool in describing both historical modelling and the development of pupils representations. In the first phase of the study, the research question was: How did the historical models of DC-circuit phenomena develop in Volta s time? The analysis uncovered three qualitative historical models associated with the historical concept formation process. The models include conceptions of the electric circuit as a scene in the DC-circuit phenomena, the comparative electric-current phenomenon as a cause of different observable effect phenomena, and the strength of the battery as a cause of the electric-current phenomenon. These models describe the concept formation process and its phases in Volta s time. The models are portrayed in the analysis using fragments of the models, where observation-based fragments and theoretical fragements are distinguished from each other. The results emphasise the significance of the qualitative concept formation and the meaning of language in the historical modelling of DC-circuit phenomena. For this reason these viewpoints are stressed in planning the teaching experiment in the second phase of the research. In addition, the design process utilised the experimentation behind the historical models of DC-circuit phenomena In the third phase of the study the research question is as follows: How will the small group s external representations of DC-circuit phenomena develop during the teaching experiment? The main question is divided into the following two sub questions: What kind of talk exists in the small group s learning? What kinds of external representations for DC-circuit phenomena exist in the small group discourse during the teaching experiment? The analysis revealed that the teaching experiment of the small group succeeded in its aim to activate talk in the small group. The designed connection cards proved especially successful in activating talk. The connection cards are cards that represent the components of the electric circuit. In the teaching experiment the pupils constructed different connections with the connection cards and discussed, what kinds of DC-circuit phenomena would take place in the corresponding real connections. The talk of the small group was analysed by comparing two situations, firstly, when the small group discussed using connections made with the connection cards and secondly with the same connections using real components. According to the results the talk of the small group included more higher-order thinking when using the connection cards than with similar real components. In order to answer the second sub question concerning the small group s external representations that appeared in the talk during the teaching experiment; student talk was visualised by the fragment maps which incorporate the electric circuit, the electric current and the source voltage. The fragment maps represent the gradual development of the external representations of DC-circuit phenomena in the small group during the teaching experiment. The results of the study challenge the results of previous research into the abstractness and difficulty of electricity concepts. According to this research, the external representations of DC-circuit phenomena clearly developed in the small group of third graders. Furthermore, the fragment maps uncover that although the theoretical explanations of DC-circuit phenomena, which have been obtained as results of typical mental model studies, remain undeveloped, learning at the qualitative level of understanding does take place.

Three-dimensional structure of heat shock protein 90 from Plasmodium falciparum: molecular modelling approach to rational drug design against malaria

We have recently implicated heat shock protein 90 from Plasmodium falciparum (PfHsp90) as a potential drug target against malaria. Using inhibitors specific to the nucleotide binding domain of Hsp90, we have shown potent growth inhibitory effects on development of malarial parasite in human erythrocytes. To gain better understanding of the vital role played by PfHsp90 in parasite growth, we have modeled its three dimensional structure using recently described full length structure of yeast Hsp90. Sequence similarity found between PfHsp90 and yeast Hsp90 allowed us to model the core structure with high confidence. The superimposition of the predicted structure with that of the template yeast Hsp90 structure reveals an RMSD of 3.31 angstrom. The N-terminal and middle domains showed the least RMSD (1.76 angstrom) while the more divergent C-terminus showed a greater RMSD (2.84 angstrom) with respect to the template. The structure shows overall conservation of domains involved in nucleotide binding, ATPase activity, co-chaperone binding as well as inter-subunit interactions. Important co-chaperones known to modulate Hsp90 function in other eukaryotes are conserved in malarial parasite as well. An acidic stretch of amino acids found in the linker region, which is uniquely extended in PfHsp90 could not be modeled in this structure suggesting a flexible conformation. Our results provide a basis to compare the overall structure and functional pathways dependent on PfHsp90 in malarial parasite. Further analysis of differences found between human and parasite Hsp90 may make it possible to design inhibitors targeted specifically against malaria.

Local numerical modelling of magnetoconvection and turbulence - implications for mean-field theories

During the last decades mean-field models, in which large-scale magnetic fields and differential rotation arise due to the interaction of rotation and small-scale turbulence, have been enormously successful in reproducing many of the observed features of the Sun. In the meantime, new observational techniques, most prominently helioseismology, have yielded invaluable information about the interior of the Sun. This new information, however, imposes strict conditions on mean-field models. Moreover, most of the present mean-field models depend on knowledge of the small-scale turbulent effects that give rise to the large-scale phenomena. In many mean-field models these effects are prescribed in ad hoc fashion due to the lack of this knowledge. With large enough computers it would be possible to solve the MHD equations numerically under stellar conditions. However, the problem is too large by several orders of magnitude for the present day and any foreseeable computers. In our view, a combination of mean-field modelling and local 3D calculations is a more fruitful approach. The large-scale structures are well described by global mean-field models, provided that the small-scale turbulent effects are adequately parameterized. The latter can be achieved by performing local calculations which allow a much higher spatial resolution than what can be achieved in direct global calculations. In the present dissertation three aspects of mean-field theories and models of stars are studied. Firstly, the basic assumptions of different mean-field theories are tested with calculations of isotropic turbulence and hydrodynamic, as well as magnetohydrodynamic, convection. Secondly, even if the mean-field theory is unable to give the required transport coefficients from first principles, it is in some cases possible to compute these coefficients from 3D numerical models in a parameter range that can be considered to describe the main physical effects in an adequately realistic manner. In the present study, the Reynolds stresses and turbulent heat transport, responsible for the generation of differential rotation, were determined along the mixing length relations describing convection in stellar structure models. Furthermore, the alpha-effect and magnetic pumping due to turbulent convection in the rapid rotation regime were studied. The third area of the present study is to apply the local results in mean-field models, which task we start to undertake by applying the results concerning the alpha-effect and turbulent pumping in mean-field models describing the solar dynamo.

Modelling boreal forest CO2 exchange and seasonality

Man-induced climate change has raised the need to predict the future climate and its feedback to vegetation. These are studied with global climate models; to ensure the reliability of these predictions, it is important to have a biosphere description that is based upon the latest scientific knowledge. This work concentrates on the modelling of the CO2 exchange of the boreal coniferous forest, studying also the factors controlling its growing season and how these can be used in modelling. In addition, the modelling of CO2 gas exchange at several scales was studied. A canopy-level CO2 gas exchange model was developed based on the biochemical photosynthesis model. This model was first parameterized using CO2 exchange data obtained by eddy covariance (EC) measurements from a Scots pine forest at Sodankylä. The results were compared with a semi-empirical model that was also parameterized using EC measurements. Both of the models gave satisfactory results. The biochemical canopy-level model was further parameterized at three other coniferous forest sites located in Finland and Sweden. At all the sites, the two most important biochemical model parameters showed seasonal behaviour, i.e., their temperature responses changed according to the season. Modelling results were improved when these changeover dates were related to temperature indices. During summer-time the values of the biochemical model parameters were similar at all the four sites. Different control factors for CO2 gas exchange were studied at the four coniferous forests, including how well these factors can be used to predict the initiation and cessation of the CO2 uptake. Temperature indices, atmospheric CO2 concentration, surface albedo and chlorophyll fluorescence (CF) were all found to be useful and have predictive power. In addition, a detailed simulation study of leaf stomata in order to separate physical and biochemical processes was performed. The simulation study brought to light the relative contribution and importance of the physical transport processes. The results of this work can be used in improving CO2 gas exchange models in boreal coniferous forests. The meteorological and biological variables that represent the seasonal cycle were studied, and a method for incorporating this cycle into a biochemical canopy-level model was introduced.

Evaluation and modelling of the spatial and temporal variability of particulate matter in urban areas

This thesis contains three subject areas concerning particulate matter in urban area air quality: 1) Analysis of the measured concentrations of particulate matter mass concentrations in the Helsinki Metropolitan Area (HMA) in different locations in relation to traffic sources, and at different times of year and day. 2) The evolution of traffic exhaust originated particulate matter number concentrations and sizes in local street scale are studied by a combination of a dispersion model and an aerosol process model. 3) Some situations of high particulate matter concentrations are analysed with regard to their meteorological origins, especially temperature inversion situations, in the HMA and three other European cities. The prediction of the occurrence of meteorological conditions conducive to elevated particulate matter concentrations in the studied cities is examined. The performance of current numerical weather forecasting models in the case of air pollution episode situations is considered. The study of the ambient measurements revealed clear diurnal variation of the PM10 concentrations in the HMA measurement sites, irrespective of the year and the season of the year. The diurnal variation of local vehicular traffic flows seemed to have no substantial correlation with the PM2.5 concentrations, indicating that the PM10 concentrations were originated mainly from local vehicular traffic (direct emissions and suspension), while the PM2.5 concentrations were mostly of regionally and long-range transported origin. The modelling study of traffic exhaust dispersion and transformation showed that the number concentrations of particles originating from street traffic exhaust undergo a substantial change during the first tens of seconds after being emitted from the vehicle tailpipe. The dilution process was shown to dominate total number concentrations. Minimal effect of both condensation and coagulation was seen in the Aitken mode number concentrations. The included air pollution episodes were chosen on the basis of occurrence in either winter or spring, and having at least partly local origin. In the HMA, air pollution episodes were shown to be linked to predominantly stable atmospheric conditions with high atmospheric pressure and low wind speeds in conjunction with relatively low ambient temperatures. For the other European cities studied, the best meteorological predictors for the elevated concentrations of PM10 were shown to be temporal (hourly) evolutions of temperature inversions, stable atmospheric stability and in some cases, wind speed. Concerning the weather prediction during particulate matter related air pollution episodes, the use of the studied models were found to overpredict pollutant dispersion, leading to underprediction of pollutant concentration levels.