Methods and tools for mass spectrometric lipidome analysis

The analysis of lipid compositions from biological samples has become increasingly important. Lipids have a role in cardiovascular disease, metabolic syndrome and diabetes. They also participate in cellular processes such as signalling, inflammatory response, aging and apoptosis. Also, the mechanisms of regulation of cell membrane lipid compositions are poorly understood, partially because a lack of good analytical methods. Mass spectrometry has opened up new possibilities for lipid analysis due to its high resolving power, sensitivity and the possibility to do structural identification by fragment analysis. The introduction of Electrospray ionization (ESI) and the advances in instrumentation revolutionized the analysis of lipid compositions. ESI is a soft ionization method, i.e. it avoids unwanted fragmentation the lipids. Mass spectrometric analysis of lipid compositions is complicated by incomplete separation of the signals, the differences in the instrument response of different lipids and the large amount of data generated by the measurements. These factors necessitate the use of computer software for the analysis of the data. The topic of the thesis is the development of methods for mass spectrometric analysis of lipids. The work includes both computational and experimental aspects of lipid analysis. The first article explores the practical aspects of quantitative mass spectrometric analysis of complex lipid samples and describes how the properties of phospholipids and their concentration affect the response of the mass spectrometer. The second article describes a new algorithm for computing the theoretical mass spectrometric peak distribution, given the elemental isotope composition and the molecular formula of a compound. The third article introduces programs aimed specifically for the analysis of complex lipid samples and discusses different computational methods for separating the overlapping mass spectrometric peaks of closely related lipids. The fourth article applies the methods developed by simultaneously measuring the progress curve of enzymatic hydrolysis for a large number of phospholipids, which are used to determine the substrate specificity of various A-type phospholipases. The data provides evidence that the substrate efflux from bilayer is the key determining factor for the rate of hydrolysis.

Estimation of cutting volume with three inventory methods for harvest planning in Canadian boreal forests.

Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.

Methods and applications for improving parameter prediction models for stand structures in Finland

This thesis report attempts to improve the models for predicting forest stand structure for practical use, e.g. forest management planning (FMP) purposes in Finland. Comparisons were made between Weibull and Johnson s SB distribution and alternative regression estimation methods. Data used for preliminary studies was local but the final models were based on representative data. Models were validated mainly in terms of bias and RMSE in the main stand characteristics (e.g. volume) using independent data. The bivariate SBB distribution model was used to mimic realistic variations in tree dimensions by including within-diameter-class height variation. Using the traditional method, diameter distribution with the expected height resulted in reduced height variation, whereas the alternative bivariate method utilized the error-term of the height model. The lack of models for FMP was covered to some extent by the models for peatland and juvenile stands. The validation of these models showed that the more sophisticated regression estimation methods provided slightly improved accuracy. A flexible prediction and application for stand structure consisted of seemingly unrelated regression models for eight stand characteristics, the parameters of three optional distributions and Näslund s height curve. The cross-model covariance structure was used for linear prediction application, in which the expected values of the models were calibrated with the known stand characteristics. This provided a framework to validate the optional distributions and the optional set of stand characteristics. Height distribution is recommended for the earliest state of stands because of its continuous feature. From the mean height of about 4 m, Weibull dbh-frequency distribution is recommended in young stands if the input variables consist of arithmetic stand characteristics. In advanced stands, basal area-dbh distribution models are recommended. Näslund s height curve proved useful. Some efficient transformations of stand characteristics are introduced, e.g. the shape index, which combined the basal area, the stem number and the median diameter. Shape index enabled SB model for peatland stands to detect large variation in stand densities. This model also demonstrated reasonable behaviour for stands in mineral soils.

Computational Methods for Studies of Quantum Dots and Boson Condensates

This thesis presents ab initio studies of two kinds of physical systems, quantum dots and bosons, using two program packages of which the bosonic one has mainly been developed by the author. The implemented models, \emph{i.e.}, configuration interaction (CI) and coupled cluster (CC) take the correlated motion of the particles into account, and provide a hierarchy of computational schemes, on top of which the exact solution, within the limit of the single-particle basis set, is obtained. The theory underlying the models is presented in some detail, in order to provide insight into the approximations made and the circumstances under which they hold. Some of the computational methods are also highlighted. In the final sections the results are summarized. The CI and CC calculations on multiexciton complexes in self-assembled semiconductor quantum dots are presented and compared, along with radiative and non-radiative transition rates. Full CI calculations on quantum rings and double quantum rings are also presented. In the latter case, experimental and theoretical results from the literature are re-examined and an alternative explanation for the reported photoluminescence spectra is found. The boson program is first applied on a fictitious model system consisting of bosonic electrons in a central Coulomb field for which CI at the singles and doubles level is found to account for almost all of the correlation energy. Finally, the boson program is employed to study Bose-Einstein condensates confined in different anisotropic trap potentials. The effects of the anisotropy on the relative correlation energy is examined, as well as the effect of varying the interaction potential.}

Chemical Characterization of Urban Background Aerosol Using Online And Filter Methods

In order to evaluate the influence of ambient aerosol particles on cloud formation, climate and human health, detailed information about the concentration and composition of ambient aerosol particles is needed. The dura-tion of aerosol formation, growth and removal processes in the atmosphere range from minutes to hours, which highlights the need for high-time-resolution data in order to understand the underlying processes. This thesis focuses on characterization of ambient levels, size distributions and sources of water-soluble organic carbon (WSOC) in ambient aerosols. The results show that in the location of this study typically 50-60 % of organic carbon in fine particles is water-soluble. The amount of WSOC was observed to increase as aerosols age, likely due to further oxidation of organic compounds. In the boreal region the main sources of WSOC were biomass burning during the winter and secondary aerosol formation during the summer. WSOC was mainly attributed to a fine particle mode between 0.1 - 1 μm, although different size distributions were measured for different sources. The WSOC concentrations and size distributions had a clear seasonal variation. Another main focus of this thesis was to test and further develop the high-time-resolution methods for chemical characterization of ambient aerosol particles. The concentrations of the main chemical components (ions, OC, EC) of ambient aerosol particles were measured online during a year-long intensive measurement campaign conducted on the SMEAR III station in Southern Finland. The results were compared to the results of traditional filter collections in order to study sampling artifacts and limitations related to each method. To achieve better a time resolution for the WSOC and ion measurements, a particle-into-liquid sampler (PILS) was coupled with a total organic carbon analyzer (TOC) and two ion chromatographs (IC). The PILS-TOC-IC provided important data about diurnal variations and short-time plumes, which cannot be resolved from the filter samples. In summary, the measurements made for this thesis provide new information on the concentrations, size distribu-tions and sources of WSOC in ambient aerosol particles in the boreal region. The analytical and collection me-thods needed for the online characterization of aerosol chemical composition were further developed in order to provide more reliable high-time-resolution measurements.

Development of radiosynthesis methods for 18F-labelled radiopharmaceuticals : General considerations and production of a dopamine transporter radioligand

Positron emission tomography (PET) is a molecular imaging technique that utilises radiopharmaceuticals (radiotracers) labelled with a positron-emitting radionuclide, such as fluorine-18 (18F). Development of a new radiotracer requires an appropriate radiosynthesis method: the most common of which with 18F is nucleophilic substitution with [18F]fluoride ion. The success of the labelling reaction is dependent on various factors such as the reactivity of [18F]fluoride, the structure of the target compound in addition to the chosen solvent. The overall radiosynthesis procedure must be optimised in terms of radiochemical yield and quality of the final product. Therefore, both quantitative and qualitative radioanalytical methods are essential in developing radiosynthesis methods. Furthermore, biological properties of the tracer candidate need to be evaluated by various pre-clinical studies in animal models. In this work, the feasibility of various nucleophilic 18F-fluorination strategies were studied and a labelling method for a novel radiotracer, N-3-[18F]fluoropropyl-2beta-carbomethoxy-3beta-4-fluorophenyl)nortropane ([18F]beta-CFT-FP), was optimised. The effect of solvent was studied by labelling a series of model compounds, 4-(R1-methyl)benzyl R2-benzoates. 18F-Fluorination reactions were carried out both in polar aprotic and protic solvents (tertiary alcohols). Assessment of the 18F-fluorinated products was studied by mass spectrometry (MS) in addition to conventional radiochromatographic methods, using radiosynthesis of 4-[18F]fluoro-N-[2-[1-(2-methoxyphenyl)-1-piperazinyl]ethyl-N-2-pyridinyl-benzamide (p-[18F]MPPF) as a model reaction. Labelling of [18F]beta-CFT-FP was studied using two 18F-fluoroalkylation reagents, [18F]fluoropropyl bromide and [18F]fluoropropyl tosylate, as well as by direct 18F-fluorination of sulfonate ester precursor. Subsequently, the suitability of [18F]beta-CFT-FP for imaging dopamine transporter (DAT) was evaluated by determining its biodistribution in rats. The results showed that protic solvents can be useful co-solvents in aliphatic 18F-fluorinations, especially in the labelling of sulfonate esters. Aromatic 18F-fluorination was not promoted in tert-alcohols. Sensitivity of the ion trap MS was sufficient for the qualitative analysis of the 18F-labelled products; p-[18F]MPPF was identified from the isolated product fraction with a mass-to-charge (m/z) ratio of 435 (i.e. protonated molecule [M+H]+). [18F]beta-CFT-FP was produced most efficiently via [18F]fluoropropyl tosylate, leading to sufficient radiochemical yield and specific radioactivity for PET studies. The ex vivo studies in rats showed fast kinetics as well as the specific uptake of [18F]beta-CFT-FP to the DAT rich brain regions. Thus, it was concluded that [18F]beta-CFT-FP has potential as a radiotracer for imaging DAT by PET.

Molecular methods for the epidemiological analysis of methicillin-resistant Staphylococcus aureus (MRSA) and Streptococcus pneumoniae

Methicillin-resistant Staphylococcus aureus (MRSA) and Streptococcus pneumoniae are major health problems worldwide, both found in symptomless carriage but also causing even life-threatening infections. The aim of this thesis was to characterise MRSA and S. pneumoniae in detail by using several molecular typing methods for various epidemiological purposes: clonality analysis, epidemiological surveillance, outbreak investigation, and virulence factor analysis. The characteristics of MRSA isolates from the strain collection of the Finnish National Infectious Disease Register (NIDR) and pneumococcal isolates collected from military recruits and children with acute otitis media (AOM) were analysed using various typing techniques. Antimicrobial susceptibility testing, pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), spa typing, staphylococcal cassette chromosome mec (SCCmec) typing, and the detection of Panton-Valentine leukocidin (PVL) genes were performed for MRSA isolates. Pneumococcal isolates were analysed using antimicrobial susceptibility testing, serotyping, MLST, and by detecting pilus islet 1 (PI-1) and 2 (PI-2) genes. Several international community- and hospital-associated MRSA clones were recognised in Finland. The genetic diversity among MRSA FIN-4 isolates and among FIN-16 isolates was low. Overall, MRSA blood isolates from 1997 to 2006 were genetically diverse. spa typing was found to be a highly discriminatory, rapid and accurate typing method and it also qualifies as the primary typing method in countries with a long history of PFGE-based MRSA strain nomenclature. However, additional typing by another method, e.g. PFGE, is needed in certain situations to be able to provide adequate discrimination for epidemiological surveillance and outbreak investigation. An outbreak of pneumonia was associated with one pneumococcal strain among military recruits, previously healthy young men living in a crowded setting. The pneumococcal carriage rate after the outbreak was found to be exceptionally high. PI-1 genes were detected at a rather low prevalence among pneumococcal isolates from children with AOM. However, the study demonstrated that PI-1 has existed among pneumococcal isolates prior to pneumococcal conjugate vaccine and the increased antimicrobial resistance era. Moreover, PI-1 was found to associate with the serotype rather than the genotype. This study adds to our understanding of the molecular epidemiology of MRSA strains in Finland and the importance of an appropriate genotyping method to be able to perform high-level laboratory-based surveillance of MRSA. Epidemiological and molecular analyses of S. pneumoniae add to our knowledge of the characteristics of pneumococcal strains in Finland.

Common Infrastructure for Finite-State Based Methods and Linguistics Descriptions

Finite-state methods have been adopted widely in computational morphology and related linguistic applications. To enable efficient development of finite-state based linguistic descriptions, these methods should be a freely available resource for academic language research and the language technology industry. The following needs can be identified: (i) a registry that maps the existing approaches, implementations and descriptions, (ii) managing the incompatibilities of the existing tools, (iii) increasing synergy and complementary functionality of the tools, (iv) persistent availability of the tools used to manipulate the archived descriptions, (v) an archive for free finite-state based tools and linguistic descriptions. Addressing these challenges contributes to building a common research infrastructure for advanced language technology.

Periglasiaalisten ilmiöiden alueellinen mallintaminen subarktisessa ympäristössä

Periglacial processes act on cold, non-glacial regions where the landscape deveploment is mainly controlled by frost activity. Circa 25 percent of Earth's surface can be considered as periglacial. Geographical Information System combined with advanced statistical modeling methods, provides an efficient tool and new theoretical perspective for study of cold environments. The aim of this study was to: 1) model and predict the abundance of periglacial phenomena in subarctic environment with statistical modeling, 2) investigate the most import factors affecting the occurence of these phenomena with hierarchical partitioning, 3) compare two widely used statistical modeling methods: Generalized Linear Models and Generalized Additive Models, 4) study modeling resolution's effect on prediction and 5) study how spatially continous prediction can be obtained from point data. The observational data of this study consist of 369 points that were collected during the summers of 2009 and 2010 at the study area in Kilpisjärvi northern Lapland. The periglacial phenomena of interest were cryoturbations, slope processes, weathering, deflation, nivation and fluvial processes. The features were modeled using Generalized Linear Models (GLM) and Generalized Additive Models (GAM) based on Poisson-errors. The abundance of periglacial features were predicted based on these models to a spatial grid with a resolution of one hectare. The most important environmental factors were examined with hierarchical partitioning. The effect of modeling resolution was investigated with in a small independent study area with a spatial resolution of 0,01 hectare. The models explained 45-70 % of the occurence of periglacial phenomena. When spatial variables were added to the models the amount of explained deviance was considerably higher, which signalled a geographical trend structure. The ability of the models to predict periglacial phenomena were assessed with independent evaluation data. Spearman's correlation varied 0,258 - 0,754 between the observed and predicted values. Based on explained deviance, and the results of hierarchical partitioning, the most important environmental variables were mean altitude, vegetation and mean slope angle. The effect of modeling resolution was clear, too coarse resolution caused a loss of information, while finer resolution brought out more localized variation. The models ability to explain and predict periglacial phenomena in the study area were mostly good and moderate respectively. Differences between modeling methods were small, although the explained deviance was higher with GLM-models than GAMs. In turn, GAMs produced more realistic spatial predictions. The single most important environmental variable controlling the occurence of periglacial phenomena was mean altitude, which had strong correlations with many other explanatory variables. The ongoing global warming will have great impact especially in cold environments on high latitudes, and for this reason, an important research topic in the near future will be the response of periglacial environments to a warming climate.