Biology and Molecular Markers of Malignant Gonadal Germ Cell Tumors

Germ cell tumors occur both in the gonads of both sexes and in extra-gonadal sites during adoles-cence and early adulthood. Malignant ovarian germ cell tumors are rare neoplasms accounting for less than 5% of all cases of ovarian malignancy. In contrast, testicular cancer is the most common malignancy among young males. Most of patients survive the disease. Prognostic factors of gonadal germ cell tumors include histology, clinical stage, size of the primary tumor and residua, and levels of tumor markers. Germ cell tumors include heterogeneous histological subgroups. The most common subgroup includes germinomas (ovarian dysgerminoma and testicular seminoma); other subgroups are yolk sac tumors, embryonal carcinomas, immature teratomas and mixed tumors. The origin of germ cell tumors is most likely primordial germ cells. Factors behind germ cell tumor development and differentiation are still poorly known. The purpose of this study was to define novel diagnostic and prognostic factors for malignant gonadal germ cell tumors. In addition, the aim was to shed further light into the molecular mechanisms regulating gonadal germ cell tumorigenesis and differentiation by studying the roles of GATA transcription factors, pluripotent factors Oct-3/4 and AP-2γ, and estrogen receptors. This study revealed the prognostic value of CA-125 in malignant ovarian germ cell tumors. In addition advanced age and residual tumor had more adverse outcome. Several novel markers for histological diagnosis were defined. In the fetal development transcription factor GATA-4 was expressed in early fetal gonocytes and in testicular carcinoma precursor cells. In addition, GATA-4 was expressed in both gonadal germinomas, thus it may play a role in the development and differentiation of the germinoma tumor subtype. Pluripotent factors Oct-3/4 and AP-2γ were expressed in dysgerminomas, thus they could be used in the differential diagnosis of the germ cell tumors. Malignant ovarian germ cell tumors expressed estrogen receptors and their co-regulator SNURF. In addition, estrogen receptor expression was up-regulated by estradiol stimulation. Thus, gonadal steroid hormone burst in puberty may play a role in germ cell tumor development in the ovary. This study shed further light in to the molecular pathology of malignant gonadal germ cell tumors. In addition, some novel diagnostic and prognostic factors were defined. This data may be used in the differential diagnosis of germ cell tumor patients.

X-ray and neutron scattering studies on some nanoscale structures in molecular biology

Scattering of X-rays and neutrons has been applied to the study of nanostructures with interesting biological functions. The systems studied were the protein calmodulin and its complexes, bacterial virus bacteriophage phi6, and the photosynthetic antenna complex from green sulfur bacteria, chlorosome. Information gathered using various structure determination methods has been combined to the low resolution information obtained from solution scattering. Conformational changes in calmodulin-ligand complex were studied by combining the directional information obtained from residual dipole couplings in nuclear magnetic resonance to the size information obtained from small-angle X-ray scattering from solution. The locations of non-structural protein components in a model of bacteriophage phi6, based mainly on electron microscopy, were determined by neutron scattering, deuterium labeling and contrast variation. New data are presented on the structure of the photosynthetic antenna complex of green sulfur bacteria and filamentous anoxygenic phototrophs, also known as the chlorosome. The X-ray scattering and electron cryomicroscopy results from this system are interpreted in the context of a new structural model detailed in the third paper of this dissertation. The model is found to be consistent with the results obtained from various chlorosome containing bacteria. The effect of carotenoid synthesis on the chlorosome structure and self-assembly are studied by carotenoid extraction, biosynthesis inhibition and genetic manipulation of the enzymes involved in carotenoid biosynthesis. Carotenoid composition and content are found to have a marked effect on the structural parameters and morphology of chlorosomes.

Monte Carlo Simulations of Molecular Clusters in Nucleation

A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

Molecular line and continuum studies of the early stages of star formation

New stars form in dense interstellar clouds of gas and dust called molecular clouds. The actual sites where the process of star formation takes place are the dense clumps and cores deeply embedded in molecular clouds. The details of the star formation process are complex and not completely understood. Thus, determining the physical and chemical properties of molecular cloud cores is necessary for a better understanding of how stars are formed. Some of the main features of the origin of low-mass stars, like the Sun, are already relatively well-known, though many details of the process are still under debate. The mechanism through which high-mass stars form, on the other hand, is poorly understood. Although it is likely that the formation of high-mass stars shares many properties similar to those of low-mass stars, the very first steps of the evolutionary sequence are unclear. Observational studies of star formation are carried out particularly at infrared, submillimetre, millimetre, and radio wavelengths. Much of our knowledge about the early stages of star formation in our Milky Way galaxy is obtained through molecular spectral line and dust continuum observations. The continuum emission of cold dust is one of the best tracers of the column density of molecular hydrogen, the main constituent of molecular clouds. Consequently, dust continuum observations provide a powerful tool to map large portions across molecular clouds, and to identify the dense star-forming sites within them. Molecular line observations, on the other hand, provide information on the gas kinematics and temperature. Together, these two observational tools provide an efficient way to study the dense interstellar gas and the associated dust that form new stars. The properties of highly obscured young stars can be further examined through radio continuum observations at centimetre wavelengths. For example, radio continuum emission carries useful information on conditions in the protostar+disk interaction region where protostellar jets are launched. In this PhD thesis, we study the physical and chemical properties of dense clumps and cores in both low- and high-mass star-forming regions. The sources are mainly studied in a statistical sense, but also in more detail. In this way, we are able to examine the general characteristics of the early stages of star formation, cloud properties on large scales (such as fragmentation), and some of the initial conditions of the collapse process that leads to the formation of a star. The studies presented in this thesis are mainly based on molecular line and dust continuum observations. These are combined with archival observations at infrared wavelengths in order to study the protostellar content of the cloud cores. In addition, centimetre radio continuum emission from young stellar objects (YSOs; i.e., protostars and pre-main sequence stars) is studied in this thesis to determine their evolutionary stages. The main results of this thesis are as follows: i) filamentary and sheet-like molecular cloud structures, such as infrared dark clouds (IRDCs), are likely to be caused by supersonic turbulence but their fragmentation at the scale of cores could be due to gravo-thermal instability; ii) the core evolution in the Orion B9 star-forming region appears to be dynamic and the role played by slow ambipolar diffusion in the formation and collapse of the cores may not be significant; iii) the study of the R CrA star-forming region suggests that the centimetre radio emission properties of a YSO are likely to change with its evolutionary stage; iv) the IRDC G304.74+01.32 contains candidate high-mass starless cores which may represent the very first steps of high-mass star and star cluster formation; v) SiO outflow signatures are seen in several high-mass star-forming regions which suggest that high-mass stars form in a similar way as their low-mass counterparts, i.e., via disk accretion. The results presented in this thesis provide constraints on the initial conditions and early stages of both low- and high-mass star formation. In particular, this thesis presents several observational results on the early stages of clustered star formation, which is the dominant mode of star formation in our Galaxy.

Molecular dynamics studies of nanoparticle impacts

This thesis concerns the dynamics of nanoparticle impacts on solid surfaces. These impacts occur, for instance, in space, where micro- and nanometeoroids hit surfaces of planets, moons, and spacecraft. On Earth, materials are bombarded with nanoparticles in cluster ion beam devices, in order to clean or smooth their surfaces, or to analyse their elemental composition. In both cases, the result depends on the combined effects of countless single impacts. However, the dynamics of single impacts must be understood before the overall effects of nanoparticle radiation can be modelled. In addition to applications, nanoparticle impacts are also important to basic research in the nanoscience field, because the impacts provide an excellent case to test the applicability of atomic-level interaction models to very dynamic conditions. In this thesis, the stopping of nanoparticles in matter is explored using classical molecular dynamics computer simulations. The materials investigated are gold, silicon, and silica. Impacts on silicon through a native oxide layer and formation of complex craters are also simulated. Nanoparticles up to a diameter of 20 nm (315000 atoms) were used as projectiles. The molecular dynamics method and interatomic potentials for silicon and gold are examined in this thesis. It is shown that the displacement cascade expansionmechanism and crater crown formation are very sensitive to the choice of atomic interaction model. However, the best of the current interatomic models can be utilized in nanoparticle impact simulation, if caution is exercised. The stopping of monatomic ions in matter is understood very well nowadays. However, interactions become very complex when several atoms impact on a surface simultaneously and within a short distance, as happens in a nanoparticle impact. A high energy density is deposited in a relatively small volume, which induces ejection of material and formation of a crater. Very high yields of excavated material are observed experimentally. In addition, the yields scale nonlinearly with the cluster size and impact energy at small cluster sizes, whereas in macroscopic hypervelocity impacts, the scaling 2 is linear. The aim of this thesis is to explore the atomistic mechanisms behind the nonlinear scaling at small cluster sizes. It is shown here that the nonlinear scaling of ejected material yield disappears at large impactor sizes because the stopping mechanism of nanoparticles gradually changes to the same mechanism as in macroscopic hypervelocity impacts. The high yields at small impactor size are due to the early escape of energetic atoms from the hot region. In addition, the sputtering yield is shown to depend very much on the spatial initial energy and momentum distributions that the nanoparticle induces in the material in the first phase of the impact. At the later phases, the ejection of material occurs by several mechanisms. The most important mechanism at high energies or at large cluster sizes is atomic cluster ejection from the transient liquid crown that surrounds the crater. The cluster impact dynamics detected in the simulations are in agreement with several recent experimental results. In addition, it is shown that relatively weak impacts can induce modifications on the surface of an amorphous target over a larger area than was previously expected. This is a probable explanation for the formation of the complex crater shapes observed on these surfaces with atomic force microscopy. Clusters that consist of hundreds of thousands of atoms induce long-range modifications in crystalline gold.

Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

Tests of a Roman Pot Prototype for the TOTEM Experiment

The TOTEM collaboration has developed and tested the first prototype of its Roman Pots to be operated in the LHC. TOTEM Roman Pots contain stacks of 10 silicon detectors with strips oriented in two orthogonal directions. To measure proton scattering angles of a few microradians, the detectors will approach the beam centre to a distance of 10 sigma + 0.5 mm (= 1.3 mm). Dead space near the detector edge is minimised by using two novel "edgeless" detector technologies. The silicon detectors are used both for precise track reconstruction and for triggering. The first full-sized prototypes of both detector technologies as well as their read-out electronics have been developed, built and operated. The tests took place first in a fixed-target muon beam at CERN's SPS, and then in the proton beam-line of the SPS accelerator ring. We present the test beam results demonstrating the successful functionality of the system despite slight technical shortcomings to be improved in the near future.

Identifying Genetic Risk Factors in Canine Autoimmune Disorders

Autoimmune diseases are more common in dogs than in humans and are already threatening the future of some highly predisposed dog breeds. Susceptibility to autoimmune diseases is controlled by environmental and genetic factors, especially the major histocompatibility complex (MHC) gene region. Dogs show a similar physiology, disease presentation and clinical response as humans, making them an excellent disease model for autoimmune diseases common to both species. The genetic background of canine autoimmune disorders is largely unknown, but recent annotation of the dog genome and subsequent development of new genomic tools offer a unique opportunity to map novel autoimmune genes in various breeds. Many autoimmune disorders show breed-specific enrichment, supporting a strong genetic background. Furthermore, the presence of hundreds of breeds as genetic isolates facilitates gene mapping in complex autoimmune disorders. Identification of novel predisposing genes establishes breeds as models and may reveal novel candidate genes for the corresponding human disorders. Genetic studies will eventually shed light on common biological functions and interactions between genes and the environment. This study aimed to identify genetic risk factors in various autoimmune disorders, including systemic lupus erythematosus (SLE)-related diseases, comprising immune-mediated rheumatic disease (IMRD) and steroid-responsive meningitis arteritis (SMRA) as well as Addison s disease (AD) in Nova Scotia Duck Tolling Retrievers (NSDTRs) and chronic superficial keratitis (CSK) in German Shepherd dogs (GSDs). We used two different approaches to identify genetic risk factors. Firstly, a candidate gene approach was applied to test the potential association of MHC class II, also known as a dog leukocyte antigen (DLA) in canine species. Secondly, a genome-wide association study (GWAS) was performed to identify novel risk loci for SLE-related disease and AD in NSDTRs. We identified DLA risk haplotypes for an IMRD subphenotype of SLE-related disease, AD and CSK, but not in SMRA, and show that the MHC class II gene region is a major genetic risk factor in canine autoimmune diseases. An elevated risk was found for IMRD in dogs that carried the DLA-DRB1*00601/DQA1*005011/DQB1*02001 haplotype (OR = 2.0, 99% CI = 1.03-3.95, p = 0.01) and for ANA-positive IMRD dogs (OR = 2.3, 99% CI = 1.07-5.04, p-value 0.007). We also found that DLA-DRB1*01502/DQA*00601/DQB1*02301 haplotype was significantly associated with AD in NSDTRs (OR = 2.1, CI = 1.0-4.4, P = 0.044) and the DLA-DRB1*01501/DQA1*00601/DQB1*00301 haplotype with the CSK in GSDs (OR=2.67, CI=1.17-6.44, p= 0.02). In addition, we found that homozygosity for the risk haplotype increases the risk for each disease phenotype and that an overall homozygosity for the DLA region predisposes to CSK and AD. Our results have enabled the development of genetic tests to improve breeding practices by avoiding the production of puppies homozygous for risk haplotypes. We also performed the first successful GWAS for a complex disease in dogs. With less than 100 cases and 100 controls, we identified five risk loci for SLE-related disease and AD and found strong candidate genes involved in a novel T-cell activation pathway. We show that an inbred dog population has fewer risk factors, but each of them has a stronger genetic risk. Ongoing studies aim to identify the causative mutations and bring new knowledge to help diagnostics, treatment and understanding of the aetiology of SLE-related diseases.

Loading of itraconazole into porous silica and silicon microparticles: characterization and dissolution tests

Most new drug molecules discovered today suffer from poor bioavailability. Poor oral bioavailability results mainly from poor dissolution properties of hydrophobic drug molecules, because the drug dissolution is often the rate-limiting event of the drug’s absorption through the intestinal wall into the systemic circulation. During the last few years, the use of mesoporous silica and silicon particles as oral drug delivery vehicles has been widely studied, and there have been promising results of their suitability to enhance the physicochemical properties of poorly soluble drug molecules. Mesoporous silica and silicon particles can be used to enhance the solubility and dissolution rate of a drug by incorporating the drug inside the pores, which are only a few times larger than the drug molecules, and thus, breaking the crystalline structure into a disordered, amorphous form with better dissolution properties. Also, the high surface area of the mesoporous particles improves the dissolution rate of the incorporated drug. In addition, the mesoporous materials can also enhance the permeability of large, hydrophilic drug substances across biological barriers. T he loading process of drugs into silica and silicon mesopores is mainly based on the adsorption of drug molecules from a loading solution into the silica or silicon pore walls. There are several factors that affect the loading process: the surface area, the pore size, the total pore volume, the pore geometry and surface chemistry of the mesoporous material, as well as the chemical nature of the drugs and the solvents. Furthermore, both the pore and the surface structure of the particles also affect the drug release kinetics. In this study, the loading of itraconazole into mesoporous silica (Syloid AL-1 and Syloid 244) and silicon (TOPSi and TCPSi) microparticles was studied, as well as the release of itraconazole from the microparticles and its stability after loading. Itraconazole was selected for this study because of its highly hydrophobic and poorly soluble nature. Different mesoporous materials with different surface structures, pore volumes and surface areas were selected in order to evaluate the structural effect of the particles on the loading degree and dissolution behaviour of the drug using different loading parameters. The loaded particles were characterized with various analytical methods, and the drug release from the particles was assessed by in vitro dissolution tests. The results showed that the loaded drug was apparently in amorphous form after loading, and that the loading process did not alter the chemical structure of the silica or silicon surface. Both the mesoporous silica and silicon microparticles enhanced the solubility and dissolution rate of itraconazole. Moreover, the physicochemical properties of the particles and the loading procedure were shown to have an effect on the drug loading efficiency and drug release kinetics. Finally, the mesoporous silicon particles loaded with itraconazole were found to be unstable under stressed conditions (at 38 qC and 70 % relative humidity).

Monte Carlo simulations of molecular clusters in nucleation

A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.