Browsing by Title

Sort by: Order: Results:

Now showing items 12333-12352 of 24416
  • Moltchanova, Elena (2000)
    Bacterial meningitis (inflammation of brain lining) caused by Neisseria meningitidis (meningococcus) may be life-threatening, meningococcus of serogroup B being the predominant agent of disease in industrialized countries. Natural immunity against disease develops with age associated with an increase in serum bactericidal activity. Although bacterial MenB meningitis is relatively rare, its severity and possible sequelae necessitate search for efficient vaccine. Since human clinical trials are costly and are often limited by ethical considerations there is a need for animal model, in which disease development and protection would depend on the same mechanism as in humans. This experiment is part of the study to access the relevance of infant rat animal model. The experiment was randomised at two levels: human volunteers were randomly assigned Norwegian, Cuban, or placebo vaccines and outbred rat pups were randomly assigned into 6-rat groups. Each day of the trial 1 group was injected with saline solution and 1-3 groups were injected with heated human serum samples taken before and after the vaccination with interval of 6 month. Thus two sources of random variation must to be taken into account: the human sera variation and variation between rat pups. It is often the case in dose response studies, that the observed effect is a combination of latent natural and treatment responses, where the treatment effect is of interest. A common way to model a binary situation is Abbott's formula. It can be extended to account for a situation with ordinal response. The treatment effect was assigned proportional odds model with strain and treatment covariates, and a full Bayesian model with vague priors was set-up. Two outcomes were examined: the proportion of protected rats (binary) and proportional reduction of bacteremia (ordinal). Both models were estimated using programme WinBUGS12beta. Large variability was apparent both between human sera and between individual rats. Probability of natural response occurrence was high in both models, but no significant treatment effects was found. In order to access the relevancy of this infant rat model to human sera protective immunity, the results of this experiment should be compared with the results of human clinical trials.
  • Zhang, Qiongchao (2013)
    With the global changes in supply and demand for forest products and their international trade, analyzing the long-term development of the Finnish stumpage market and forecasting different assortments of Finnish stumpage prices is more and more important. There are limited number of studies on forecasting Finnish stumpage prices and even less up to date information about forecasting the markets. According to the previous studies, it is difficult to get precise forecasting results in real-life situations, purely utilizing simple time-series forecasting methods. In addition, the forecasting error is usually unavoidable in the price forecasting studies. The present study increases information on stumpage price forecasting using updated price data and testing alternative statistical approaches that take account of structural changes of stumpage prices in Finnish roundwood market. The aims of this study are to test applicability of alternative statistical approaches in forecasting long-run stumpage price development up to 2050. The annual price data are from the years 1967-2010. First we tested the stationarity of time-series data, using an augmented Dickey-Fuller (ADF) Unit root test. Compared to the complicated prices behaviors of sawlog, the prices behaviors of pulpwood are much more stationary. It can be seen clearly that there are three business cycles both in sawlog and pulpwood prices, around 30 years per cycle. Further studies can be analyzed involving some impact factors to the demand and supply of Finnish roundwood, such as prices of roundwood and forest products export, prices in domestic market, GDP of Finland, etc. Basing on the results of the study, the forecasted prices of all assortments of Finnish roundwood will decline from 2010 to 2023. We assume that the Finnish roundwood market will suffer from the global changes of demand and supply of forest products. Demands for many traditional end products are decreasing in Europe. Thus we recommend the Finnish roundwood market stakeholders should pay more attention on this situation. The forestry companies can change their products structure: develop more new products in bioenergy industry; what is more, companies can develop new markets in internationally. The forest private owners should communicate more frequently with roundwood market experts and forest industry to build a coherent picture on industry trends impacting roundwood price determination.
  • Miettinen, Jarkko (Helsingin yliopisto, 2009)
    This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.
  • Takolander, Antti (2014)
    Climate change has been predicted to cause extinctions and range shifts in European flora. Two common methodologies assessing climate impact on vegetation are statistical bioclimatic envelope models (BEMs) and process-based dynamic vegetation models. BEMs are relatively easy to implement, but have been criticized for being unreliable, because they assume equilibrium between species’ observed ranges and climate. Dynamic models can be considered biologically more sound, but require large quantities of detailed input data, which is often not available. The aim of this study is to investigate the effects of climate change on common tree species ranges in Europe and in Scandinavia, and to find out whether two commonly used modeling strategies, dynamic and statistical models, produce similar estimates of future ranges. To address these questions, I first built statistical models (bioclimatic envelope models) for five common European trees: Pedunculate Oak (Quercus robur, L.), Common Hazel (Corylus avellana L.), European Beech (Fagus sylvatica, L.), Scots Pine (Pinus sylvestris, L.) and Norway Spruce (Picea abies (L.) H. Karst.). All species are widely distributed and characteristic species in their ecosystems and thus their possible range shifts would indicate larger shifts in ecosystem structure and function. I then compare the projections produced with the statistical models to outputs of a tree speciesparameterized dynamic global vegetation model LPJ-GUESS, obtained from another study. The statistical model predictions are compared with dynamic model results for entire European distributions, while the statistical model predictions for Scandinavian area are examined in further detail. Input distribution data had great influence in future predictions of statistical models. Statistical models and the dynamic model produced very different future predictions, statistical models predicting increasing contractions on the southern edge of distribution towards the end of the century, indicating larger climatic impacts. The role of biological interactions, successional processes and modeling relationship between distribution and climate are discussed. I propose a way to assess the possible causes of differences between statistical and dynamic models to produce more robust future predictions on plant species distributions. Statistical model predictions in the Scandinavian area indicated substantial northward shift of hemiboreal vegetation zone by 2050.
  • Zheng, Chaozhi (Helsingin yliopisto, 2009)
    Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.
  • Autio, Ilkka (Helsingin yliopisto, 2008)
    In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.
  • Henriksson, Svante (Helsingin yliopisto, 2013)
    Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are 1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, 2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, 3) identifying a power law shape S(f) ∝ f−α for the spectrum of global mean temperature with α ∼ 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, 4) separating aerosol properties and climate effects in India by season and location 5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, 6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and 7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy design in India and other Asian countries.
  • Nord, Janne (Helsingin yliopisto, 2003)
  • Tanskanen, Aapo (Helsingin yliopisto, 2008)
    Solar UV radiation is harmful for life on planet Earth, but fortunately the atmospheric oxygen and ozone absorb almost entirely the most energetic UVC radiation photons. However, part of the UVB radiation and much of the UVA radiation reaches the surface of the Earth, and affect human health, environment, materials and drive atmospheric and aquatic photochemical processes. In order to quantify these effects and processes there is a need for ground-based UV measurements and radiative transfer modeling to estimate the amounts of UV radiation reaching the biosphere. Satellite measurements with their near-global spatial coverage and long-term data conti-nuity offer an attractive option for estimation of the surface UV radiation. This work focuses on radiative transfer theory based methods used for estimation of the UV radiation reaching the surface of the Earth. The objectives of the thesis were to implement the surface UV algorithm originally developed at NASA Goddard Space Flight Center for estimation of the surface UV irradiance from the meas-urements of the Dutch-Finnish built Ozone Monitoring Instrument (OMI), to improve the original surface UV algorithm especially in relation with snow cover, to validate the OMI-derived daily surface UV doses against ground-based measurements, and to demonstrate how the satellite-derived surface UV data can be used to study the effects of the UV radiation. The thesis consists of seven original papers and a summary. The summary includes an introduction of the OMI instrument, a review of the methods used for modeling of the surface UV using satellite data as well as the con-clusions of the main results of the original papers. The first two papers describe the algorithm used for estimation of the surface UV amounts from the OMI measurements as well as the unique Very Fast Delivery processing system developed for processing of the OMI data received at the Sodankylä satellite data centre. The third and the fourth papers present algorithm improvements related to the surface UV albedo of the snow-covered land. Fifth paper presents the results of the comparison of the OMI-derived daily erythemal doses with those calculated from the ground-based measurement data. It gives an estimate of the expected accuracy of the OMI-derived sur-face UV doses for various atmospheric and other conditions, and discusses the causes of the differences between the satellite-derived and ground-based data. The last two papers demonstrate the use of the satellite-derived sur-face UV data. Sixth paper presents an assessment of the photochemical decomposition rates in aquatic environment. Seventh paper presents use of satellite-derived daily surface UV doses for planning of the outdoor material weathering tests.
  • Kortejärvi, Hanna (Helsingin yliopisto, 2008)
    The bioavailability and bioequivalency of oral drug depends on gastrointestinal tract physiology and drug-related physicochemical and pharmacokinetic factors. In general, bioavailability of a new drug substance or new formulation is studied in vivo with healthy volunteers. In vivo bioequivalency studies are needed for generic drug products or if a formulation is significantly altered during clinical trials. In certain cases, in vitro dissolution studies can be used as a surrogate for in vivo bioavailability or bioequivalency studies, referred to as a “biowaiver”. These biowaivers are based either on in vitro-in vivo correlation (IVIVC) or the biopharmaceutical classification system (BCS). For drugs with dissolution rate-controlled absorption and level A IVIVC, a direct relationship between in vivo drug input and in vitro dissolution may be found. A BCS biowaiver can be utilised for BCS I drugs that have complete absorption due to high solubility and high permeability. In this thesis, in vitro dissolution methods and computer simulation models were developed to predict relative bioavailability and bioequivalency and to probe properties of drugs suitable for biowaivers. A level A IVIVC model with a stochastic approach was developed for a modified-release formulation series of levosimendan. Firstly, the criteria for selection of a dissolution method for the level A IVIVC model were evaluated. Secondly, a stochastic Bayesian approach was integrated with the level A IVIVC model in order to get a predictions of concentration-time profiles of different formulations. BCS biowaiver studies included literature data evaluation of immediate release formulations of ranitidine, a BCS III drug with high solubility and low permeability. Ranitidine was evaluated as a potential BCS biowaiver candidate. Generalised rules to estimate the risk of bioinequivalency and to suggest new potential biowaivers were evaluated by theoretical pharmacokinetic simulations. Gastrointestinal tract physiology, formulation type and drug solubility, dissolution, absorption and elimination rates were taken into account in the pharmacokinetic simulation model. A dissolution method using pH 5.8 and a rotation speed of 100rpm/min provided acceptable discrimination between formulations based on the level B IVIVC and comparisons of pharmacokinetic parameters (MRT and Tmax) to the dissolution profiles for levosimendan. The level A IVIVC model with Bayesian approach has good external predictability for the formulation series, although an averaged IVIVC model with the same data failed. Subject-specific in vivo data was utilised and predictions were obtained as probability distributions. The BCS III drug ranitidine was suggested as a biowaiver candidate based on data from the literature. Generally, the simulations suggest that BCS III drugs are better biowaiver candidates than some BCS I drugs because they have a lower risk of bioinequivalence and they are less sensitive to differences in gastric emptying rates and formulation types. BCS I drugs are currently accepted for biowaivers, although a short half-life of elimination and rapid rate of absorption cause a high risk of bioinequivalency. Pharmacokinetic models were constructed and tested to predict in vitro-in vivo correlations, relative bioavailability, risk of bioinequivalency and potential for biowaivers. These models are useful new tools in formulation development and regulatory applications.
  • Thum, Tea (Helsingin yliopisto, 2009)
    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.
  • Haapala, Jari (Helsingin yliopisto, 2000)
  • Heinävaara, Sirpa (2003)
    MONISYÖPÄPOTILAIDEN ELINAIKAENNUSTEET TAUSTA Yhä useammalla syöpäpotilaalla on diagnosoitu kaksi tai useampia primaarisyöpiä. Näiden monisyöpäpotilaiden joukko kasvaa, koska useimpien syöpäpotilaiden elinaikaennusteet ovat parantuneet ja odotettavissa oleva elinikä on pidentynyt. Tämän potilasjoukon kasvaessa on yhä kiinnostavampaa tietää, kuinka monisyöpäpotilaat selviytyvät uudesta primaarisyövästään verrattuna niihin potilaihin, jotka sairastavat samaa syöpää ensimmäisenä syöpänään. Aiheesta tehtyjen aikaisempien tutkimusten tulokset ovat olleet ristiriitaisia. Ristiriitaisten tulosten taustalla saattaa olla käytettyjen analyysimenetelmien heikkous: Seuraajasyöpään liittyvää elinaikaennustetta arvioitaessa ei ole huomioitu taustalla olevan ensimmäisen syövän vaikutusta kuolleisuuteen. TAVOITE: MONISYÖPÄPOTILAIDEN ELINAIKAENNUSTEET MAHDOLLIKSI Väitöskirjassa esitellään neljä vaihtoehtoista tilastollista mallia, joilla monisyöpäpotilaiden eloonjäämistä voidaan arvioida ensimmäisen ja seuraajasyövän osalta. Uudet vaihtoehdot ovat laajennuksia ja mukaelmia malleista, joita käytetään arvioitaessa syöpäpotilaiden suhteellista (relative) ja syykohtaista (cause-specific) eloonjäämistä. Eloonjäämistä vertaillaan mallien välillä sekä saman syövän suhteen ensimmäisenä ja seuraajasyöpänä. Toiseen syöpään liittyvän eloonjäämisen arvioiminen loi tarpeen luoda uusia käsitteitä, erityisesti kun kyse oli kahdesti samaan primaarisyöpään sairastuneista monisyöpäpotilaista: On pystyttävä arvioimaan eloon-jäämistä esim. rintasyövän suhteen sekä ensimmäisenä että seuraajasyöpänä. TULOKSET JA JOHTOPÄÄTÖKSET Eloonjäämistä ensimmäisen ja seuraajasyövän suhteen voidaan arvioida uusilla suhteelliseen ja syykohtaiseen eloonjäämiseen perustuvilla malleilla. Seuraajasyöpään liittyvää eloonjäämistä ei tulisi arvioida, jollei taustalla olevaan ensimmäiseen syöpään liittyvää kuolleisuutta ole otettu huomioon. Eloonjäämisennusteisiin ensimmäisen ja seuraajasyövän suhteen vaikuttavat mm. syövän sijainti ja se, onko monisyöpäpotilaalla kaksi samaa primaarisyöpää vai ei. Useimmiten eloonjäämisennusteet eivät eroa ensimmäisen ja seuraajasyövän välillä. Voimakkaiden päätelmien teko on edelleen vaikeaa, sillä käytettävissä olevat väestöpohjaisetkin aineistot ovat toistaiseksi varsin suppeita.
  • Heinävaara, Sirpa (2003)
    With increasing number of subsequent primary cancers there is a growing concern to know how cancer patients survive with their subsequent cancer compared to those with their respective first cancer. Results of earlier studies have been conflicting and have not lead to firm conclusions. One reason for conflicting results might be a lack appropriate methodology as survival from subsequent cancer has usually not been adjusted for an extra hazard due to an underlying first cancer. This study presents four alternative models for estimating survival of patients with multiple cancers. Models are extensions and modifications to those proposed earlier for estimating relative and cause-specific survival of patients with a single cancer. The assessment of survival from subsequent cancer raised a need for introducing new concepts, especially when survival of patients with their multiple cancers of the same site is concerned. Survival estimates from cancer are compared between the models, and between a first and subsequent tumour of the same site. The importance of adjusting survival from subsequent cancer to that from a underlying first cancer is also highlighted. The results show that survival from cancer as a first and subsequent tumour can be reliably assessed with the newly introduced models based either on the relative and cause-specific survival. The results also show that survival from cancer as a first and subsequent tumour may be dependent on the site of cancer and whether patients' cancers are of the same site or not. Nevertheless, survival from a subsequent cancer is not usually different from that from a respective first cancer. However, even with large population-based data, a lack of power often prevents the detection of modest differences in survival.
  • Heinävaara, Sirpa (Helsingin yliopisto, 2003)
  • Lindström, Riitta (Helsingin yliopisto, 2014)
    Mesencephalic astrocyte-derived neurotrophic factor (MANF) and cerebral dopamine neurotrophic factor (CDNF) proteins form a family of neurotrophic factors. Neurotrophic factors have been intensively studied as a putative therapeutic approach to treat neuronal injuries and neurodegenerative diseases. Mammalian MANF and CDNF have been shown to have protective and restorative effects on the nigrostriatal dopaminergic system. In addition, several studies have reported a role for MANF in the endoplasmic reticulum (ER) stress response. A recently established MANF knockout mouse model revealed that MANF functions in the pancreatic insulin-producing beta cells and might be involved in the pathogenesis of diabetes mellitus. Beyond their neurotrophic properties, MANF and CDNF appear to play a more general role in the maintenance of cellular homeostasis. In this study, Drosophila melanogaster was used as a model organism to explore the function and interaction of the MANF/CDNF protein family in vivo. The sole member of the MANF/CDNF family in Drosophila, DmManf, was discovered to be crucial for fly development. The human orthologues, HsMANF and HsCDNF, were found to be able to substitute the endogenous DmManf. Likewise, DmManf had the cytoprotective properties of mammalian MANF in cultured murine neurons. These results support that the findings from the Drosophila model can be adapted for research in mammalian systems. MANF/CDNF proteins consist of amino (N) - and carboxy (C) -terminal domains. In this work, several functional features identified in mammalian MANF structure were explored in the Drosophila model. Separate N- or C-terminal domain constructs, even when co-expressed together, failed to complement for the loss of endogenous DmManf. The ER retention of DmManf, mediated by the C-terminal signal sequence, and the positive charge of the N-terminal surface amino acid residues were found to be important for appropriate DmManf function. Furthermore, entering the secretory pathway via ER was essential for the stability of DmManf protein. A CXXC motif characteristic for oxidoreductases is located in the C-terminal domain of MANF. In this study, effects of a point mutation (C129S) in CXXC motif of DmManf were analysed in vivo. Intact CXXC motif was discovered to be vital for DmManf function. Furthermore, the expression of DmManf-C129S in wild type background was harmful for fly viability suggesting that this specific mutation represents either a dominant negative or a gain-of-function allele of DmManf. Utilising the unique potential of Drosophila model for in vivo screening, interactions of DmManf were studied in this work. Consistent with a previous in vitro study, a genetic interaction was found between DmManf and the fly homologue of the major ER chaperone GRP78. Moreover, DmManf interacted with other genes that encode components of ER function and the unfolded protein response. Finally, novel interactions with DmManf and genes involved in the ubiquinone synthesis pathway and mitochondria were discovered. Taken together, this study demonstrates the functional conservation of mammalian and fly proteins and provides meaningful information on structural and functional features of the MANF/CDNF protein family in vivo. The genetic interaction studies confirmed and expanded the previous knowledge on the ER-associated functions of MANF. Furthermore, novel interactions with mitochondria-related genes and DmManf were discovered.
  • Ruusuvuori, Kai (Helsingin yliopisto, 2015)
    New particle formation is an important process in the atmosphere. As ions are constantly produced in the atmosphere, the behaviour and role of charged particles in atmospheric processes needs to be understood. In order to gain insight on the role of charge in atmospheric new particle formation, the electron structure of the molecules taking part in this process needs to be taken into account using quantum chemical methods. Quantum chemical density functional theory was employed in an effort to reproduce an experimentally observed sign preference. While computational results on molecular structures agreed well with results obtained by other groups, the computationally obtained sign preference was opposite to the experimentally observed. Possible reasons for this discrepancy were found in both computational results and experiments. Simulations of clusters containing water, pyridine, ammonia and a proton were performed using density functional theory. The clusters were found to form a core consisting of ammonium ion and water with the pyridine molecule bonding to the ammonium ion. However, the solvation of the ammonium ion was observed to affect the possibility of proton transfer. Calculations of proton affinities and gas phase basicities of several compounds, which can be considered as candidates to form atmospheric ions in the boreal forest, were performed. The generally small differences between the calculated gas phase basicites and proton affinities implied only small entropy changes in the protonation reaction. Comparison with experiments resulted in the conclusion that the largest experimentally observed peaks of atmospheric ions most likely corresponded to pyridine and substituted pyridines. Furthermore, a combination of low proton affinity and high observed cation concentration was concluded to imply a high concentration of neutral parent molecules in the atmosphere. A combination of quantum chemistry and a code for modelling cluster dynamics was employed to study the use of protonated acetone monomers and dimers as the ionization reagent in a chemical ionization atmospheric pressure interface time-of-flight mass spectrometer (CI-APi-TOF). The results showed that the ionization reagents successfully charged dimethylamine monomers. However, there were discrepancies between the simulated and measured cluster distributions. Possible reasons for this discrepancy were found in both measurements and the modelling parameters.
  • Hiippala, Tuomo (Helsingin yliopisto, 2013)
    This dissertation studied the structure of multimodal artefacts, or how language, image and other semiotic modes combine and interact in documents. This places the study within the emerging field of multimodal research, which uses linguistic methods to study the interaction of multiple semiotic modes. Despite the growing amount of multimodal research, the structure of multimodal artefacts has not received the attention it warrants. Previous studies have been either very detailed or exceedingly abstract, leaving a significant gap between data and theory, which this dissertation attempted to bridge. To do so, the dissertation adopted a data-driven approach to multimodal analysis, addressing the structure of multimodal artefacts, the factors that shape the artefact structure, and the role of structure in the recognition and interpretation of the artefacts. The data consisted of tourist brochures produced by the city of Helsinki between 1967 and 2008, which allowed a longitudinal perspective to their multimodal structure. A total of 58 double-pages were annotated for their content, visual appearance, layout and rhetorical organisation, and compiled into an XML-based multimodal corpus. To study the corpus, the dissertation developed visualisation methods that combined information from multiple analytical layers of the corpus to represent the multimodal structures in the data. The study revealed the functional motivation behind the structure of the tourist brochures, identifying patterns in their hierarchical and rhetorical organisation, which were used to fulfil specific communicative tasks. The configuration of these patterns, in turn, signalled how the brochure was to be interpreted. The results also showed that after the year 1985, which marked the introduction of desktop publishing software, the organising principles of the tourist brochures have shifted towards a more fragmented and non-linear structure.
  • Repola, Jaakko (2013)
    Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands (908 pine, 613 spruce and 127 birch trees). These stands located mainly on mineral soil sites representing a large part of Finland. Biomass equations were derived for the total aboveground biomass and for the individual tree components (stem wood, stem bark, living and dead branches, needles, stump, and roots). Three multivariate models with different number of independent variables for above-ground biomass and one for below-ground biomass were constructed. The simplest model formulations, multivariate models (1) were based mainly on tree diameter and height as independent variables. In more elaborated multivariate models (2) and (3) additional commonly measured tree variables such age, crown length, bark thickness and radial growth rate were added. In the modelling approach, the basic assumption was that the biomasses of the tree components on the same site and in the same tree are dependent. This statistical dependency was taken into account by applying a multivariate procedure. Based on the verified statistical dependence among the biomass components, the multivariate procedure had a number of advantages compared to the traditionally independently estimated equations by enabling more flexible application of the equations, ensuring better biomass additivity, and giving the more reliable parameter estimates. The generalization and applicability of the models may be restricted by the fact that the study material was not an objective, representative sample, and some tree components were poorly represented. Despite these shortcomings, the models provided logical biomass predictions for individual tree components in Finland.