Recent Submissions

  • Salmenkari, Hanne (Helsingin yliopisto, 2019)
    The intestine is a major site of immune activity, and disturbances in the balance of proinflammatory and anti-inflammatory signals can lead to difficult and chronic diseases, like inflammatory bowel diseases, manifesting in uncontrolled inflammation in intestine. Local intestinal renin-angiotensin system (RAS) and glucocorticoid synthesis are recently uncovered complex mechanisms participating in the pathophysiology of intestinal diseases. These systems can offer new therapy options, either by repurposing well-known drugs like angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers or by novel innovations like mesenchymal stromal cell therapy. The aim of this thesis was to investigate intestinal RAS and glucocorticoid production in intestinal inflammation and examine potential treatments with the focus on these two systems. RAS and glucocorticoid production and their possible interactions in intestine were characterized in a dextran sodium sulfate (DSS)-induced experimental colitis model using in vitro stimulations and inhibition of RAS in vivo. Glucocorticoid synthesis and ACE shedding were investigated as the release of corticosterone and ACE protein from live tissue to incubation media in vitro. The effects of ACE inhibitor, captopril, and ACE-inhibiting milk-derived bioactive tripeptide, Ile-Pro-Pro, were examined on intestinal RAS and glucocorticoid synthesis. ACE inhibitor, enalapril, and angiotensin II receptor blocker, losartan, were tested alone and in combination in alleviation of colitis. Finally, freshly cultivated and cryopreserved platelet-lysate expanded mesenchymal stromal cells were compared and their feasibility was examined in the treatment of colitis. Enalapril and losartan were effective at alleviating colitis and lessening inflammation on their own but were without synergistic effects, supporting their potential to be investigated in clinical trials. MSC treatments proved feasible and without adverse effects, and freshly cultivated MSC treatments had a modest anti-inflammatory effect reflected by reduction in proinflammatory cytokine levels. We found a specific induction of ACE ectodomain shedding in distal colon, the most affected region in DSS-induced colitis, and in proximal colon following a high DSS dose. ACE shedding could be downregulated by cryopreserved MSCs and an ACE-inhibiting tripeptide Ile-Pro-Pro treatment in vivo. These data imply that cell-surface ACE levels are actively regulated in intestinal inflammation, which could be a feedback mechanism to reduce the proinflammatory angiotensin II (Ang II) signaling. Ang II induced glucocorticoid production in small intestine incubations in vitro, thus implying of an anti-inflammatory property in Ang II signaling. We suggest that Ang II enhances the TNFα-mediated induction of glucocorticoid production during intestinal inflammation. In vitro or in vivo inhibition of Ang II production or signaling did not modulate intestinal glucocorticoid production, although captopril abolished the gene expression of the rate-limiting enzyme of glucocorticoid synthesis, Cyp11b1, in vivo.
  • Nilsson, Sofia (Helsingin yliopisto, 2019)
    Understanding the mechanism of chemical reactions brings possibilities to optimization of reaction conditions. Microreactors coupled online to mass spectrometric detection provide a system highly suitable for mechanistic studies, enabling sensitive, selective, and rapid detection. By combining the information obtained with this experimental system with theoretical density functional theory investigations of the potential energy surface of the system, detailed information about the mechanism of a reaction can be obtained. On the other hand, molecularly imprinted polymers are useful tools for facilitating selective synthesis. This is achieved by formation of cavities within the polymer matrix, which are able to stabilize the transition state of the desired reaction. In this thesis, three different miniaturized reactors fabricated with additive manufacturing were combined online with electrospray ionization mass spectrometry for monitoring chemical reactions (Studies I-IV). The different miniaturized reactors were found to be variably suitable for this task. Overall, three different reactions were studied using miniaturized reactors coupled to a mass spectrometer – an inverse electron-demand Diels-Alder, followed by a retro Diels-Alder reaction (Studies I and II), an oxidation of a heptafulvene into the corresponding tropone by meta-chloroperoxybenzoic acid (Study III), and an acetylation reaction yielding the antibiotic drug linezolid (Study IV). The online mass spectrometry results obtained for the heptafulvene oxidation reaction were furthermore used as a basis for density functional theory studies of said reaction (Study III). Nine reaction pathways were investigated. The key step of the mechanism with the lowest energy barrier for oxidation of the studied heptafulvene into its corresponding tropone was identified as a Criegee-like rearrangement, while the overall reaction follows a Hock-like mechanism. Furthermore, highly porous molecularly imprinted polymer systems, which in flow injection quartz crystal microbalance studies exhibited enantioselectivity for a proposed transition state analogue of a transamination reaction, were developed and assessed (Study V). The molecularly imprinted systems prepared with n-heptane as porogen, and polystyrene beads, which, when extracted out, formed pores in the polymers that were imprinted with a molecule having either a D or L conformation of a proposed transition state analogue of a transaminase reaction, showed a clear selectivity for the transition state analogue enantiomer that they were imprinted with in flow injection quartz crystal microbalance studies. Otherwise these systems exhibited similar selectivity for the other analytes screened. The results presented in this thesis demonstrate that online combination of additively manufactured miniaturized reactors and mass spectrometry provides a convenient system for monitoring reactions online. At the same time, the results highlight limitations of the system such as memory effects arising from rough surfaces of the miniaturized reactors in combination with (from a mass spectrometry viewpoint) high concentrations of reactants used. However, the results from the oxidation study show that combinations of several methods can aid in overcoming limitations that one single approach may present. Finally, the developed hyperporous molecularly imprinted systems for enantioselective transamination reaction are promising for introduction into miniaturized reactors in the future.
  • Yang, Zhen (Helsingin yliopisto, 2019)
    Role of lipid-modifying enzymes in oat and faba bean Increasing utilization of plant materials and especially their proteins is a global trend. One of the challenges in using grains and legumes as sources of protein is the off-flavour that is associated with them. Many of the undesirable flavour compounds are formed from lipids as a result of complex enzymatic and chemical reactions. To understand and control lipid-modifying enzymes is essential to prolong the shelf life of cereal and legume ingredients and products, and raise consumer acceptance towards them. The aim of this thesis was to study the role of lipid-modifying enzymes in oat and faba bean. To reach this aim, the levels of and variations in the lipid-modifying enzyme activities present in oat and faba bean seeds from selected cultivars and cultivation years were studied (Study I). In addition, the formation of non-volatile oxidised fatty acids (NVOFAs) by lipid-modifying enzymes in oat was investigated (Study II). Finally, the role of lipid-modifying enzymes in the formation of volatile off-flavour compounds in faba bean foods was studied (Study III). The results of Study I showed the presence of marked lipase and peroxygenase activities oat, while lipase and lipoxygenase (LOX) activities occurred in faba bean. The enzyme activities were affected by sample cultivars and cultivation years. Lipase activity in faba bean was surprisingly high, and it could effectively start lipid-derived off-flavour formation as soon as the seed structure is broken and it has access to inherent or added lipids as substrates. Study II showed that NVOFAs occurred in the flours of non-heat treated oat grains, and their amounts increased remarkably during the storage of oat samples. The formation of NVOFAs was in line with the release of free fatty acids by oat lipase. In addition, the formation of NVOFAs in the flour of heat-treated oat grains was quite small. In the third study, the optimum pH of faba bean lipase was found at 7.5-8, and for LOX the optimum pH was at 6. The LOX pathway produced various types and amounts of volatile lipid oxidation products using different substrates. In addition, adding rapeseed oil in emulsions increased the formation of volatile lipid oxidation products, and adding rapeseed oil fatty acids increased it even more. This study also showed that the pH levels greatly affected the extent of the reactions. Overall, this thesis evaluated the role of reactions catalysed by lipid-modifying enzymes together with chemical lipid oxidation for their potential to form lipid-derived off-flavours in oat and faba bean. The lipid-modifying enzymes should be properly inactivated to prevent the causing of potential problems. By studying comprehensively the lipid modifying enzymes, we are able to produce knowledge which assists in developing high-quality oat and faba bean based foods.
  • Heikkilä, Jaana (Helsingin yliopisto, 2019)
    A search for a pseudoscalar Higgs boson A is performed, focusing on its decay into a standard model-like Higgs boson h and a Z boson. Decays of the h boson into a pair of tau leptons are considered along with Z boson decays into a pair of light leptons (electrons or muons). A data sample of proton-proton collisions collected by the CMS experiment at the LHC at √s= 13 TeV is used, corresponding to an integrated luminosity of 35 inverse femtobarns. The search uses the reconstructed mass distribution of the A boson as the discriminating variable. This analysis is the first of its kind to utilise the svFit algorithm while exploiting the possibility to apply a mass constraint of 125 GeV in the h→ττ four-vector reconstruction. The resolution of the reconstructed mass of the A boson is improved compared to the mass resolution obtained in previous analyses targeting the same final state. No excess above the standard model expectation is observed in data. Model-independent as well as model-dependent upper limits in the mA – tanβ plane for two minimal supersymmetric standard model benchmark scenarios are set at 95% confidence level. The model-independent upper limit on the product of the gluon fusion production cross section and the branching fraction for the A→Zh→llττ decay ranges from 27 fb at 220 GeV to 5 fb at 400 GeV. The observed model-dependent limits on the process σ(gg→A+bbA)B(A→Zh→llττ) in case of the hMSSM (low-tb-high) scenario exclude tanβ values from 1.6 (1.8) at mA= 220 GeV to 3.7 (3.8) at mA = 300 GeV, respectively.
  • Wiikinkoski, Elmo (Helsingin yliopisto, 2019)
    Each nuclear energy country has their strategy for handling the spent nuclear fuel: direct disposal, recycling or a combination of both. The advances in nuclear fuel partitioning enhance the safety of both of these approaches. The spent fuel contains fissionable material that could be used in modern and future reactors. The re-use, however, requires a separation of the fissionable material from the neutron poisoners that are also present in the spent fuel. Time-proven separation technologies exist for the recovery of uranium and plutonium, but for the trivalent actinides americium and curium, such technologies are still young. The majority of current separation technologies in nuclear fuel partitioning, such as the solvent extraction, are based on the recovery of target nuclides from liquids by organic extractants. Their application can be limited by the high radiation doses during the separation process. Ion exchange with inorganic materials offers a robust supportive role in the separation challenges for radionuclides. The materials are stable in high temperatures, high acidity and under extreme radiation, and are ion selective. By altering their structure, the desired ion selectivity can be further improved. Throughout the dissertation, a solid inorganic ion exchanger, α-zirconium phosphate, was investigated, developed and applied in column operation with one goal in mind: the application of ion exchange in the column separation of trivalent actinides from lanthanides. The α-zirconium phosphate proved suitable for americium-europium separation. The material was modified and the connections between synthesis, properties and ion selectivity between various products were investigated and discussed. Numerous characterization techniques were applied in the investigation of material properties. Radioactive materials and radiochemical methods were used in the investigation of ion selectivities for europium and americium. The materials were up to 400 times more selective towards europium over americium. For an application in nuclear fuel management, this order of preference is preferred, as americium can be readily recovered from the material for its fissioning, while europium is retained in the solid, a suitable matrix for nuclear waste disposal. In column operation, highly pure americium, up to 99.999 mol-%, could be separated from europium with high recovery in low pH. The effects of multiple factors on the separation, such as europium concentration, salt concentration and pH were investigated throughout the dissertation. Ion exchange can excel in such specific and demanding jobs, as the structures of the materials can be engineered to enhance the desirable separation properties. Whereas the well-established solvent extraction based separation processes are already applied in many areas of nuclear fuel management, I believe that ion exchange can have a supportive role in their shortcomings.
  • Tiikkaja, Samuli (Helsingin yliopisto, 2019)
    Paired Opposites: The Development of Einojuhani Rautavaara’s Harmonic Practices studies the music of the Finnish composer Einojuhani Rautavaara (1928–2016). The focus of this work is on Rautavaara’s preferences in writing harmonic motions. The main aim of the work is to investigate those aspects of Rautavaara’s harmonic practices that remained invariant, or at least relatively invariant, throughout his career. Rautavaara used various composing techniques in his long career and embraced many different aesthetic attitudes, but this study shows a common vein running through his music in most of its stylistic phases. Among the works studied are compositions from six decades of Rautavaara’s career, from the late 1940s to mid-1990s, by which time he can be considered to have reached a synthesis of all his previous stylistic phases. Most of Rautavaara’s music is based on tertian harmonies. Accordingly, it may be tempting to analyze his œuvre with tools designed for tonal music. However, Rautavaara very rarely employed tonal functions. Therefore, tonal cadences are replaced by various other means of regulating harmonic tension and release. The present study investigates Rautavaara’s harmonic practices with a tool called the Harmonic Circle, a ­<3, 4> compound interval cycle that can be used to trace tertian harmonies but does not imply functional tonality––even though, as the study shows, tonal music can also be analyzed with the Harmonic Circle. Analytic tools from the neo-Riemannian analytic tradition are also used to investigate harmonic motion in Rautavaara’s music. The Harmonic Circle provides insights into serial music, at least of the kind written by Rautavaara, where the hexachords of twelve-tone rows often create distinct harmonic areas. This study shows that it is the contrast of such harmonic areas that Rautavaara often manipulates in his music, serial or otherwise, to control harmonic tension and release. The notion of harmonic areas in Rautavaara’s music is associated with the principles of symmetry. Symmetries are explored in the study from both aesthetic and technical perspectives. For Rautavaara, symmetry was a way of regulating tone materials, and he associated symmetries with mandalas––circular diagrams that are used as meditational aids in Buddhism and Hinduism. On a purely technical level, he drew parallels between mandalas and serialism, as he saw twelve-tone composing as a way of controlling post-tonal harmony, much like concentrating on a mandala focuses a meditating person’s thoughts. Significantly, Rautavaara was prone to using symmetrical twelve-tone rows. After his first serial period (1957–1965), he sought to employ similar symmetrical structures and tone materials in his non-serial, neo­romantic music as well, in a stylistic phase which lasted for nearly 20 years, from 1967 to 1985. In his last period (1985–2016), he succeeded in fusing together serial writing with neoromantic timbres. His fondness of symmetries can also be seen to extend to his whole production; his habit of alluding to and quoting from his own previous compositions amounts to œuvre-wide symmetry, as motifs and themes from various earlier stages of his career keep reappearing in later compositions.
  • Heinilä, Kirsikka (Helsingin yliopisto, 2019)
    Optical snow monitoring methods have tendency to underestimate snow cover beneath the evergreen forest canopy due to the masking effect of trees. There is need to develop method for providing more reliable snow products and enhance their use e.g. in hydrological and climatological models. The main objective of this thesis is to provide information to improve the accuracy of snow mapping by algorithm development and its regional parameterization. This thesis exploits reflectance data derived from ground-based, mast-borne, airborne and space-borne sensors. Each datatype with different ground resolutions has specific strengths and weaknesses. Together this dataset provides valuable information to advance knowledge of reflectance properties of snow-covered forests and supports the interpretation of satellite-borne reflectance observations. Improvement of satellite-based snow cover mapping is essential because it is the only way to monitor snow cover spatially, temporally and economically effectively. To obtain information about certain geophysical variable using satellite data, a model for interpreting the satellite signal must be developed. The feasibility of satellite-borne observations in describing geophysical variables depends on the reliability of the model used. Here simple reflectance models based on the zeroth order radiative transfer equation and lineal mixing models are investigated. They are found to reliably describe the observed surface reflectances from snow-covered terrain, both in forests and in open areas. Additionally, to improve methods for seasonal snow cover monitoring in forests, the high spatial resolution observations are required to describe spectral properties and their temporal behaviour of different targets inside the investigated scene. It is also important to combine these target-specific reflectances with the in situ data to describe the characteristics of the target area. In this thesis the datasets complement each other so that while mast-borne data provides information on the temporal behaviour of the scene reflectance of the specific location where measurement conditions are well known, the airborne data provides information during a very short time (~1 hour) on the spatial variation of scene reflectance from the areas where land cover, forest characteristics and snow conditions are well defined. The results demonstrate the notable effect of forest on observed reflectance in both the temporal (changes in illumination geometry) and on the spatial (changes in forest structure) scale. The presence of tree canopy also weakens the capability of the Normalized Difference Snow Index (NDSI) to detect snow-covered areas. Additionally, the effect of melting snow cover on reflectances and NDSI is significant in all land covers producing high variation inside individual land cover types too.
  • Leinonen, Juho (Helsingin yliopisto, 2019)
    Data collected from the learning process of students can be used to improve education in many ways. Such data can benefit multiple stakeholders of a programming course. Data about students’ performance can be used to detect struggling students who can then be given additional support benefiting the student. If data shows that students have to read a certain section of the material multiple times, it could indicate either that that section is possibly more important than others, or it might be unclear and could be improved, which benefits the teacher. Data collected through surveys can yield insight into students’ motivations for studying. Ultimately, data can increase our knowledge of how students learn benefiting educational researchers. Different kinds of data can be collected in online courses. In programming courses, data is typically collected from tools that are specifically made for learning programming. These tools include Integrated Development Environments (IDEs), program visualization tools, automatic assessment tools, and online learning materials. The granularity of data collected from such tools varies. Fine-grained data is data that is collected frequently, while coarse-grained data is collected less frequently. In a programming course, coarse-grained data might include students’ submissions to exercises, whereas fine-grained data might include students’ actions within the IDE such as editing source code. An example of extremely fine-grained data is keystroke data, which typically includes each key pressed while typing together with a timestamp that tells when exactly the key was pressed. In this work, we study what benefits there are to collecting keystroke data in programming courses. We explore different aspects of keystroke data that could be useful for research and to students and educators. This is studied by conducting multiple quantitative experiments where information about students’ learning or the students themselves is inferred from keystroke data. Most of the experiments are based on examining how fast students are at typing specific character pairs. The results of this thesis show that students can be uniquely identified solely based on their typing whilst they are programming. This information could be used in online courses to verify that the same student completes all the assignments. Excessive collaboration can also be detected automatically based on the processes students take to reach a solution. Additionally, students’ programming experience and future performance in an exam can be inferred from typing, which could be used to detect struggling students. Inferring students’ programming experience is possible even when data is made less accurate so that identifying individuals is no longer feasible.
  • Toivonen, Jarkko (Helsingin yliopisto, 2019)
    In this thesis we aim to learn models that can describe the sites in DNA that a transcription factor (TF) prefers to bind to. We concentrate on probabilistic models that give each DNA sequence, of fixed length, a probability of binding. The probability models used are inhomogeneous 0th and 1st order Markov chains, which are called in our terminology Position-specific Probability Matrix (PPM) and Adjacent Dinucleotide Model (ADM), respectively. We consider both the case where a single TF binds in isolation to DNA, and the case where two TFs bind to proximal locations in DNA, possibly having interactions between the two factors. We use two algorithmic approaches to this learning task. Both approaches utilize data, which is assumed to have enriched number of binding sites of the TF(s) under investigation. Then the binding sites in the data need to be located and used to learn the parameters of the binding model. Both methods also assume that the length of the binding sites is known beforehand. We first introduce a combinatorial approach where we count `-mers that are either binding sites, background noise, or belong partly to both of these categories. The most common `-mer in the data and its Hamming neighbours are declared as binding sites. Then an algorithm to align these binding sites in an unbiased manner is introduced. To avoid false binding sites, the fraction of signal in the data is estimated and used to subtract the counts that rise from the background. The second approach has the following additional benefits. The division into signal and background is done in a rigorous manner using a maximum likelihood method, thus avoiding the problems due to the ad hoc nature of the first approach. Secondly, use of a mixture model allows learning multiple models simultaneously. Then, subsequently, this mixture model is extended to include dimeric models as combinations of two binding models. We call this reduction of dimers as monomers modularity. This allows investigating the preference of each distance, even the negative distance in the overlapping case, and relative orientation between these two models. The most likely mixture model that explains the data is optimized using an EM algorithm. Since all the submodels belong to the same mixture model, their relative popularity can be directly compared. The mixture model gives an intuitive and unified view of the different binding modes of a single TF or a pair of TFs. Implementations of all introduced algorithms, SeedHam and MODER for learning PPM models and MODER2 for learning ADM models, are freely available from GitHub. In validation experiments ADM models were ob- served to be slightly but consistently better than PPM models in explaining binding-site data. In addition, learning modularic mixture models confirmed many previously detected dimeric structures and gave new biological insights about different binding modes and their compact representations.
  • Talvitie, Topi (Helsingin yliopisto, 2019)
    Bayesian networks are probabilistic models that represent dependencies between random variables via directed acyclic graphs (DAGs). They provide a succinct representation for the joint distribution in cases where the dependency structure is sparse. Specifying the network by hand is often unfeasible, and thus it would be desirable to learn the model from observed data over the variables. In this thesis, we study computational problems encountered in different approaches to learning Bayesian networks. All of the problems involve counting or sampling DAGs under various constraints. One important computational problem in the fully Bayesian approach to structure learning is the problem of sampling DAGs from the posterior distribution over all the possible structures for the Bayesian network. From the typical modeling assumptions it follows that the distribution is modular, which means that the probability of each DAG factorizes into per-node weights, each of which depends only on the parent set of the node. For this problem, we give the first exact algorithm with a time complexity bound exponential in the number of nodes, and thus polynomial in the size of the input, which consists of all the possible per-node weights. We also adapt the algorithm such that it outperforms the previous methods in the special case of sampling DAGs from the uniform distribution. We also study the problem of counting the linear extensions of a given partial order, which appears as a subroutine in some importance sampling methods for modular distributions. This problem is a classic example of a #P-complete problem that can be approximately solved in polynomial time by reduction to sampling linear extensions uniformly at random. We present two new randomized approximation algorithms for the problem. The first algorithm extends the applicable range of an exact dynamic programming algorithm by using sampling to reduce the given instance into an easier instance. The second algorithm is obtained by combining a novel, Markov chain-based exact sampler with the Tootsie Pop algorithm, a recent generic scheme for reducing counting into sampling. Together, these two algorithms speed up approximate linear extension counting by multiple orders of magnitude in practice. Finally, we investigate the problem of counting and sampling DAGs that are Markov equivalent to a given DAG. This problem is important in learning causal Bayesian networks, because distinct Markov equivalent DAGs cannot be distinguished only based on observational data, yet they are different from the causal viewpoint. We speed up the state-of-the-art recursive algorithm for the problem by using dynamic programming. We also present a new, tree decomposition-based algorithm, which runs in linear time if the size of the maximum clique is bounded.
  • Lindblad, Annika (Helsingin yliopisto, 2019)
    This dissertation examines how macroeconomic variables influence financial market volatility and correlations using mixed frequency time series methods. The modelling framework allows combining high-frequency and low-frequency data within the same model and thus allows directly relating the economic data to the low-frequency component of volatility or correlations. The dissertation sheds light on which economic variables influence the low-frequency component of volatilities and correlations, as well as examines various methods to improve long horizon forecasts for stock market volatility by utilising the information in macroeconomic variables. The first essay considers the relative and combined importance of macroeconomic fundamentals and survey-based sentiment data for modelling US equity market volatility in a GARCH-MIDAS framework. It uses a data set which accurately takes into account real-time data revisions to lags of the macroeconomic data and extends the analysis to include several new variables. Forward-looking macroeconomic data is important for forecasting volatility, even after the information in sentiment indicators is controlled for. On the other hand, for example, consumer confidence indicators contain information complementary to forward-looking macroeconomic variables. Overall, models combining macroeconomic and sentiment data tend to improve in-sample fit and in some cases also out-of-sample forecast accuracy compared to models only driven by one type of data. The improvements in forecasting performance are, however, not statistically significant, and therefore the results do not strongly advocate using several explanatory variables in the MIDAS polynomial. In the second essay I assess the time-variation in predictive ability arising from the inclusion of macroeconomic and financial data in a GARCH-MIDAS model for US stock market volatility. I compare forecasts from a GARCH-MIDAS model to forecasts from a nested GARCH model, and therefore the differences in forecasting performance directly reflect the impact of economic data. While forecasting performance between the two models is similar when considered over the full out-of-sample period, there is clear time-variation in relative forecasting performance over sub-samples. I suggest the variation could arise from the phase of the business cycle or the volatility environment and find particularly strong evidence in favour of economic variables being important for volatility forecasting during low-volatility periods. Forecast combination methods and a decision rule based on conditional predictive ability produce consistently better forecasts than the GARCH model, although statistical significance of the improvements depend on the loss function considered. The third essay considers the time-variation in the co-movement of equity returns and exchange rate returns in several markets using the DCC-MIDAS model. Determining the economic drivers of the low-frequency correlation aids in differentiating between the various theoretical explanations for the correlation, which predict both a positive and a negative relationship. The essay concentrates on the portfolio rebalancing channel and on two hypotheses suggested in the earlier literature, namely flight-to-quality and quantitative easing (QE) related search-for-yield, in addition to examining the sensitivity of the correlation to other economic variables related to portfolio rebalancing motives, such as the business cycle. Although there are common elements driving the return correlation in the different markets, for instance, interest rate differentials and quantitative easing measures, their impact on the correlation varies, suggesting the underlying theoretical explanation differs across markets. While the onset of US QE1 had a clear impact on the correlations, overall the results suggest that being in a QE regime is more important than announcement effects for the long-term correlation.
  • Wang, Kai (Helsingin yliopisto, 2019)
    The plant phyllosphere environment offers a habitat for multiple kinds of microbes, including bacteria, fungi, yeast, etc. Microbes can be beneficial, pathogenic, or mostly neutral to plants. Increasingly the interaction patterns and related plant immunity signaling pathways against bacteria and filamentous fungi have been extensively studied. However, the interaction between plants and yeast or yeast-like fungi is largely unclear. Phyllosphere yeast-like fungi from wild Arabidopsis were isolated and characterized in this study. Around a hundred yeast isolates, including ascomycete Protomyces species, were identified and cultured. Protomyces species have been described as pathogens of plants in the Umbelliferae and Compositae families, however, with questionable phylogeny and little genomic information. We isolated and investigated the interaction of a strain Protomyces sp. SC29 (SC29) with Arabidopsis. SC29 can persist in the Arabidopsis phylloplane, and activate Arabidopsis immune responses with MAPKs (mitogen-activated protein kinases) activation and upregulation of salicylic acid signaling and camalexin biosynthesis marker genes. Additionally, indolic compounds produced by Protomyces species are able to activate plant auxin responses. The genomes of SC29 and all currently available Protomyces species were sequenced, assembled, and annotated. Comparative genomic analysis revealed genomic characters of SC29 related to adaptation to the phyllosphere environment. Genomic insights into the pathogenesis of Protomyces species were also discovered. The phylogenetic relationships of both the genus Protomyces and the subphylum Taphrinomycotina were re-constructed with genome-wide single-copy protein sequences. Small secreted proteins from the genomes of Protomyces spp. were analyzed as candidate effectors. Physiological, phylogenetic, and genomic evidence supported SC29 to be a novel species distinct from currently accepted Protomyces species. Thus, the study of SC29 and its interaction with Arabidopsis represents a new model system for the exploration of the genetics of plant interactions with phyllosphere resident yeasts.
  • Hunter, Kerri (Helsingin yliopisto, 2019)
    In order to maintain health, growth, and productivity, plants must be able to adapt to increasingly variable environmental conditions. Plants are continuously flooded with information from their surrounding environment, which must be sensed, incorporated, and responded to accordingly. Much of the communication between plant cells and the extracellular environment is carried out by the receptor-like protein kinases (RLKs), including the cysteine-rich receptor-like kinase (CRK) subfamily. Despite the large size of the CRK gene family, their physiological roles and functions on a biochemical and cellular level remain largely uncharacterized. We performed large scale phenotyping of a crk T-DNA mutant collection in Arabidopsis thaliana (Arabidopsis), which suggested roles for the CRKs in several developmental processes, as well as during abiotic and biotic stress responses. CRK2 emerged as an important CRK, with several strong loss-of-function phenotypes and a notable phylogenetic position. We established that CRK2 enhances salt tolerance through the regulation of callose synthase 1 (CALS1) dependent callose deposition at plasmodesmata. This revealed a previously uncharacterized role for callose deposition in response to high salinity. We showed that this callose deposition has an effect on plasmodesmal permeability, and therefore a potential impact on intercellular signalling. Additionally, CRK2 was found to regulate the formation of an unknown vesicle type during salt stress, which could possibly be involved in cell-to-cell signalling as well. We have described how CRK2 regulates ROS production during immunity by regulation of RBOHD via C-terminal phosphorylation. We observed highly specific changes in the subcellular localization of CRK2 in response to various stress treatments, and demonstrated that these localization patterns are critical for protein function and interactions. The subcellular localization and many of the cellular functions of CRK2 were dependent on phospholipase D alpha 1 (PLDɑ1) activity, and PLDɑ1 was consistently identified as one of the top proteins to interact with CRK2. Thus, we propose that CRK2 is a fundamental CRK, which acts in connection with PLDɑ1 to regulate several cellular processes during the response to environmental stimuli.
  • Vanhanen, Santeri (Helsingin yliopisto, 2019)
    Better knowledge of cultivation and plant gathering enables a deeper understanding of prehistoric societies. People-plant interactions have resulted in the creation of human ecological niches and, over time, people began to increasingly gain their subsistence from productive economies. However, in Finland prehistoric cultivation and plant gathering remain poorly understood. What plants were gathered during the prehistoric period, and how would they have been used? When do the first signs of cultivation occur, and where did it originate from? How did cultivation develop after its introduction? This study reviews and expands on archaeobotanical data on cultivation and plant gathering in Finland. The aim is to provide a long-term perspective of plant-people interactions in the area. Such knowledge is valuable for scholars studying prehistoric societies, plant use and agricultural history. The primary method employed in this study is the archaeobotanical analysis of plant macrofossils. This method enables species-level identifications of plant remains found at archaeological sites. In this study, such plant remains were retrieved from flotation samples gathered at archaeological sites in Finland and Sweden. Altogether, approximately 800 samples were studied. In addition, several remains of plants were directly accelerator mass spectrometry (AMS) radiocarbon dated, thus enabling an absolute chronology for these particular remains. Secondary methods employed in the study include the anthracological analysis of wood charcoal, ethnography and geochemistry. A review of charred and waterlogged plant remains from the Stone Age in Finland show that numerous wild plants were collected. During the Holocene thermal maximum, hazel and water chestnut grew further north than today. Wild plants were used throughout Finland during the Stone Age, although the number of taxa diminished northwards. Use of starch-rich plants, such as water-lilies, appears to have decreased after the onset of agriculture. The earliest macrofossil remains of cultivated plants in Finland, naked barley and naked wheat, were found at Pitted Ware Culture sites on the Åland Islands. Radiocarbon dates show that these remains date from the years 3300–2500 cal BC. Cultivated plants occur for the first time in mainland Finland during the second millennium BC. Radiocarbon-dated plant remains indicate continuous cultivation of barley on mainland Finland since approximately 1500 cal BC. The early development of plant cultivation is, however, poorly understood. Larger assemblages of plant remains have been discovered during the first millennium AD. At Isokylä, in southern Finland, such assemblages show that barley was the main crop cultivated during the Iron Age, cal AD 200–550. Both hulled and naked barley were cultivated together with other crops. Here, the earliest find of hemp in Finland was discovered and directly dated to cal AD 258–425. The Late Iron Age can be considered as a period of agricultural expansion. The site of Orijärvi shows that permanent field cultivation, with hulled barley as the main crop, was conducted from approximately cal AD 600 onwards. The results of this study have implications especially for studies of prehistoric societies, which can be better understood with a deeper knowledge of their plant use. Plants not only provided nutrients, medicine, fuel and construction materials, but people could even construct their niches by removing or preserving certain plants in their surroundings. The active role of humans should be considered when studying past environmental changes, for example via pollen analytical studies. Cereal grains found at Pitted Ware Culture sites on Åland forces us to consider whether these hunter-gatherers could have conducted small-scale cultivation, possibly even reaching mainland Finland. Cultivation most probably originated from east-central Sweden, where it was first introduced by the Funnel Beaker Culture approximately 4000 cal BC. Later, continuous cultivation throughout the Bronze Age must have had social consequences, and the appearance of numerous cairns might well be associated with an increasing reliance on agriculture. The Iron Age find of hemp at Isokylä might indicate contacts with areas farther south. Remains of ancient fields and the archaeobotanical material at Orijärvi and other similar sites show that field cultivation was conducted in Finland at the latest since the Late Iron Age. These finds call into question whether we can consider slash-and-burn cultivation as the earliest cultivation method in Finland.
  • Kero, Mia (Helsingin yliopisto, 2019)
    One of the leading health challenges worldwide is dementia, the incidence of which is rapidly increasing along with increasing life expectancy. The number of people with dementia is estimated to reach 150 million by 2050. Thus, the estimated financial costs associated will be enormous, and there is tremendous pressure to find better tools for the prevention, early detection and treatments of dementia. The most common neurodegenerative disease is Alzheimer´s disease (AD), covering at least 50% of patients with dementia. Other common dementing diseases include vascular dementia (VaD) (20%), frontotemporal lobar degeneration (FTLD) (10%) and dementia with Lewy bodies (DLB) (5%). In addition, neuropathological studies have suggested some recently identified neurodegenerative entities to be common in the very elderly population. One such entity is hippocampal sclerosis of aging (HS-Aging), which is characterized by neuronal loss in the hippocampal CA1 and subiculum, and TDP-43 -positive inclusions in the hippocampal dentate fascia. The general aim of this thesis project was to investigate the frequency and genetic background of age-associated neurodegenerative diseases, particularly HS-Aging and other TDP-43 proteinopathies, in the Finnish population. In Study I, we determined the prevalence of HS-Aging and the associated neuropathological changes in a population-based sample of very elderly Finns (Vantaa85+ study). In Study II, the associations of previously identified risk variants with HS-Aging were investigated in a combined dataset of Finnish and British population-based cohorts. In Study III, the prevalence of an amyloid precursor protein (APP) mutation, previously shown to be protective against AD, was determined among the oldest old Finns. In the last study, Study IV, we investigated the neuropathological and molecular genetic phenotype of Finnish familial patients with FTLD associated with a rare tumor, dysplastic gangliocytoma. HS-Aging was detected in 16% of Finns aged over 85 years. HS-Aging without any other comorbid neuropathologies was seen in only one individual (2% of cases). 51% of subjects with HS-Aging exhibited a bilateral disease, indicating that pathological sections should be taken from both hippocampi for neuropathological diagnostics. Dementia and TDP-43-, p62- and Tau-positive granular cell inclusions were strongly associated (p< 0.001) with HS-Aging (I). The population -representative cohorts confirmed polymorphisms in GRN and TMEM106 to be genetic risk factors for HS-Aging and accumulation of TDP-43 positive inclusions in hippocampus (II). The protective APP mutation (A673T) was detected in only one very aged female (0.19%) subject. This individual exhibited HS-Aging, but no AD pathology, indicating that this mutation probably protects against AD changes (III). The familial FTLD was characterized neuropathologically by abundant hippocampal and cortical TDP-43- and cerebellar p62-pathology, and it was shown to be caused by a hexanucleotide repeat expansion mutation in C9orf72. In addition, C9orf72 repeat expansion mutation hypothetically promoted the development of dysplastic gangliocytoma (IV). In conclusion, this study provided new information on the prevalence and genetic background of HS-Aging and other TDP-43-proteinopathies in the Finnish population. Key words: HS-Aging, population-based, oldest old, risk alleles, APP mutation, C9orf72 expansion
  • Hemminki, Samuli (Helsingin yliopisto, 2019)
    Motion sensing is one of the most important sensing capabilities of mobile devices, enabling monitoring physical movement of the device and associating the observed motion with predefined activities and physical phenomena. The present thesis is divided into three parts covering different facets of motion sensing techniques. In the first part of this thesis, we present techniques to identify the gravity component within three-dimensional accelerometer measurements. Our technique is particularly effective in the presence of sustained linear acceleration events. Using the estimated gravity component, we also demonstrate how the sensor measurements can be transformed into descriptive motion representations, able to convey information about sustained linear accelerations. To quantify sustained linear acceleration, we propose a set of novel peak features, designed to characterize movement during mechanized transportation. Using the gravity estimation technique and peak features, we proceed to present an accelerometer-based transportation mode detection system able to distinguish between fine-grained automotive modalities. In the second part of the thesis, we present a novel sensor-assisted method, crowd replication, for quantifying usage of a public space. As a key technical contribution within crowd replication, we describe construction and use of pedestrian motion models to accurately track detailed motion information. Fusing the pedestrian models with a positioning system and annotations about visual observations, we generate enriched trajectories able to accurately quantify usage of public spaces. Finally in the third part of the thesis, we present two exemplary mobile applications leveraging motion information. As the first application, we present a persuasive mobile application that uses transportation mode detection to promote sustainable transportation habits. The second application is a collaborative speech monitoring system, where motion information is used to monitor changes in physical configuration of the participating devices.
  • Winkel, Frederike (Helsingin yliopisto, 2019)
    Structural brain plasticity is an essential process to adjust maladapted networks, but it dramatically declines after closure of the critical periods during early postnatal life. Growing evidence suggests, however, that certain interventions, such as environmental enrichment and antidepressant treatment, can reinstate a network plasticity that is similar to that observed during the critical periods. Chronic treatment with the antidepressant fluoxetine, for example, can reopen visual cortex plasticity when combined with monocular deprivation. Further, it promotes the erasure of previously acquired fear memory when combined with extinction training. Fluoxetine can bind to and activate the neurotrophic TrkB receptor and can therefore regulate the downstream pathway to induce synaptic plasticity. Considering that TrkB receptors are expressed in essentially all neurons, the question to be answered is through which neuronal subpopulation are the plasticity effects regulated within these two circuitries. Visual cortex plasticity is tightly regulated by the inhibitory Parvalbumin (PV)-specific GABAergic network, which highly expresses TrkB receptors. During the critical periods TrkB’s ligand Brain- Derived Neurotrophic Factor (BDNF) promotes the maturation of PV interneurons, thereby stimulating a precocious onset and closure of critical periods. Hence, our first aim was to understand TrkB actions specifically in PV interneurons and their subsequent effects on visual cortex plasticity during adulthood. We used optically activated TrkB (optoTrkB) expressed only in PV interneurons of the visual cortex and found that optoTrkB activation by light combined with monocular deprivation is sufficient to induce ocular dominance plasticity. Strikingly, optoTrkB activation rapidly induces LTP in layer II/III of the visual cortex after theta burst stimulation (TBS). This potentiation in excitatory transmission is mediated by rapid decreases in the intrinsic excitability of PV regulated by reduced expressions of Kv3.1 and Kv3.2 mRNA. In addition, optoTrkB activation promotes the removal of perineuronal nets (PNNs) and shifts the PV and PNN networks into a plastic, immature configuration. Conversely, deleting TrkB from PV interneurons and using chronic fluoxetine treatment to pharmacologically induce plasticity prevented the effects of fluoxetine treatment. Our second aim was to identify the effects of optoTrkB activation expressed specifically in pyramidal neurons of the ventral hippocampus on the fear circuitry. We therefore directed the expression of optoTrkB to pyramidal neurons of the ventral hippocampus. During fear extinction optoTrkB was activated with light, and spontaneous recovery and fear renewal were tested one and three (remote memory) weeks after extinction training. We found that optoTrkB activation during extinction training promoted the erasure of remote fear memory. This effect was accompanied by increased LTP expression after brief TBS stimulation. Finally, fluoxetine and methylmercury (MeHg) are a common intervention and stressor, respectively, in our society, and exposure to either during pregnancy is known to impact brain development and functioning. An altered critical period can result in impairments that are retained into adulthood. Our aim was to understand how perinatal exposure to fluoxetine or MeHg affects the development of PV and PNNs, two well-established markers for the time course of critical periods, in the hippocampus and basolateral amygdala. We found that upon closure of the normal critical periods (P24) the number of PV and PNNs, and PV cell intensity increase. Perinatal fluoxetine treatment resulted in reduced expression of PNNs throughout critical periods, indicating a delayed closure. In contrast, perinatal MeHg exposure impaired the development of PV interneurons and PV expression at the onset of critical periods (P17), which were, however, restored upon critical period closure (P24), suggesting a delayed onset. Our results provide new evidence that TrkB activation in PV interneurons rapidly orchestrates cortical networks by reducing the intrinsic excitability of PV cells regulated by decreased expression of Kv3.1 and Kv3.2 channels, subsequently promoting excitatory transmission. In contrast, TrkB activation in pyramidal neurons of the ventral hippocampus also potentiates excitatory transmission. These opposite findings demonstrate that TrkB employs different mechanisms to increase the excitability of the neuronal network to induce plasticity. We propose that TrkB is a promising therapeutic target for the treatment of neuropsychiatric diseases that benefit from high plasticity modes. We further shed light on the effects of fluoxetine and MeHg exposure during pregnancy on the time course of the critical periods, which can help in developing better guidelines for the use and consumption of both during pregnancy.
  • Hedayati, Nasibeh (Helsingin yliopisto, 2019)
    The purpose of this study is to investigate morality in Iranian schools. In particular, the aim in this doctoral thesis is to explore morality and moral values as expressed in official documents of the Ministry of Education and two secondary schools. Thus, three main areas are addressed to raise awareness in this regard: (1) values in the official documents; (2) the life purposes of students; and (3) moral conflicts from the perspectives of stu-dents and teachers. This article-based thesis draws together the finding of four original studies. The following four main questions correspond with the results re-ported in the original studies: (1) What are the values in the Iranian educa-tional system, what kinds of teachers are desired for the Iranian educational system and what kind of citizens are teachers expected to educate? (2) What are the life purposes and purpose profiles of Iranian secondary school students? (3) What are the main themes of moral conflicts identified by Iranian students and teachers and how do the moral conflicts identified by students and teachers differ from each other? (4) What are the religious moral dilemmas that Iranian students and teachers identified? The first step in raising awareness of the values in this system was to study official documents such as The Theoretical Foundation of Transfor-mation in the Educational System of the Islamic Republic of Iran (TFFTES, 2011). This document presents the philosophy and goal of education in the Iranian educational system. Empirical data were also collected from two of Tehran’s secondary schools, one for females and the other for males, in 2016. The students were 12 to 16 years old and the teachers were 27 to 52 years old. First, data were gathered from students (female n = 174, male n = 163) through essays and questionnaires: they were asked to complete a survey that included questionnaires related to life purposes and open questions investigating moral conflicts, and they were given one hour to do so. Second, teachers (female n = 10, male n = 10) were interviewed and asked to narrate their stories about moral dilemmas. Thus, the empirical data included students’ essays, transcripts of interviews with teachers on moral conflicts, and stu-dents’ questionnaire responses on life purposes. The study framework combines qualitative and quantitative data analysis. The results of the study are reported in the original articles (Hedayati, Kuusisto, Gholami and Tirri, 2017a, 2017b, 2017c and 2019). Although, according to the findings of the study, values in the Iranian educational context reflect Islamic thinking, what is happening in schools in some areas conflicts with the values and goals promoted in the educational system. In some cases, however, the school context reflects the values in the official documents.
  • Soikkeli, Maiju (Helsingin yliopisto, 2019)
    Magnetic resonance imaging (MRI) is one of the most important medical imaging methods due to its noninvasiveness, superior versatility and resolution. In order to improve the image quality and to make different tissues more distinguishable, MRI is often used together with contrast agents. Contrast agents are most commonly based on gadolinium. However, during recent decades, the group of metal-free contrast agents has become a major area of development. One striking group of potential metal-free contrast agents are the nitroxides, stable organic radicals. In this thesis, two fully organic, metal-free nitroxides were designed and synthesized. The compounds consisted of a nitroxide moiety bearing the contrast enhancing properties and a targeting moiety aimed to invoke specificity of the agent towards tumor tissue. Their stability and relaxation enhancing properties were determined in order to evaluate their potential as novel contrast agents for MRI. Both of the compounds proved to be highly stable by maintaining their contrast and relaxation enhancing properties for several hours is harsh conditions. Also, they displayed effective relaxation time shortening in MRI experiments. Therefore, these organic radical contrast agents are expected to bring a noteworthy addition to the established MRI-based diagnostics by joining the growing group of metal-free contrast agents for MRI. Another medical diagnostic method based on magnetic resonance is magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI). In the latter section of the thesis a novel organic marker for MRS and MRSI with no existing equivalent was developed. Although the phantom MRS studies seemed promising, unfortunately the in vivo animal studies did not give the desired outcome leaving place for improvement.
  • Ahonen, Lauri (Helsingin yliopisto, 2019)
    New particle formation (NPF) is a dominant source for atmospheric aerosol particles in terms of their number concentration, and a major contributor to the number of cloud con-densation nuclei globally. Atmospheric aerosol particles have impact on Earth’s climate via direct and indirect effects. In addition to climate, aerosol particles have impact on human health. In polluted environments, airborne pollutants, especially particulate matter, shorten the lifetime expectancy by several years. Understanding the processes of NPF is in a key role, for example, while identifying the most effective acts to improve the air quality in megacities or assessing the role of anthropogenic emissions in climate change. A NPF event consists of formation of molecular clusters and their subsequent growth into larger particle sizes by condensable vapors and/or coagulation In order to quantify NPF events, measurements of particle number size distribution close to the size where gas-to-particle conversion takes place are necessary. The gas-to-particle conversion takes place in the 1-2 nm size range, where there exist electrically charged and neutral molecular clusters. On one hand, in most of the environments such clusters are present also in the absence of NPF events. The growth of the small clusters to the 2-3 nm size range is, on the other hand, indicative of a NPF event. In this thesis, we gather knowledge on the concentration of sub-3 nm aerosol particles by conducting both long-term and campaign-like measure-ments with particle size magnifier (PSM; Airmodus Ltd.). Our results were compared with the other available PSM data, from sites around the world, and presented in compilation study. In all the sites the sub-3 nm particle concentration had a daytime maximum. Gener-ally, the highest concentrations were observed at the sites with the highest anthropogenic influence. In this thesis, we also conducted a campaign to observe particle formation in a cleanroom environment, where PSM was used for the first time to monitor concentration of nanoparticles in such an environment. The results showed that sub-2 nm clusters were observed to be always present in this clean room in relatively small concentrations. Short periods of high concentrations were observed during active manufacturing processes in the clean room. Instrumental development was one important aspect of this thesis. We experimented with the possibility of using two commercial condensation particle counters (CPCs), with nomi-nal lower limit close to 10 nm, for the detection of sub-3 nm particles. Optimized operating temperatures and flow rates were tested in laboratory conditions and by using simulation tools. We showed that commercially-available CPCs can be optimized down to sub-3 nm detection. In addition, a differential mobility particle sizer (DMPS) was specially built to measure particle number size distributions in the sub-10 nm size range using PSM and half-mini differential mobility analyzer (DMA). Due to the improved overall transmission of our system, the counting uncertainty compared to a harmonized DMPS was reduced to a half in the sub-10 nm size range. An ion mobility-mass spectrometry was utilized to investigate the structures and hydration of iodine pentoxide iodic acid clusters, similar to ones observed during coastal nucleation events. The number of water molecules in hydrated clusters was sufficient to convert io-dine pentoxide into iodic acid but the water sorption beyond this amount was limited.

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