Population projection for Namibia 2011-2020 - With an estimation of the impact of HIV/AIDS

This study presents a population projection for Namibia for years 2011–2020. In many countries of sub-Saharan Africa, including Namibia, the population growth is still continuing even though the fertility rates have declined. However, many of these countries suffer from a large HIV epidemic that is slowing down the population growth. In Namibia, the epidemic has been severe. Therefore, it is important to assess the effect of HIV/AIDS on the population of Namibia in the future. Demographic research on Namibia has not been very extensive, and data on population is not widely available. According to the studies made, fertility has been shown to be generally declining and mortality has been significantly increasing due to AIDS. Previous population projections predict population growth for Namibia in the near future, yet HIV/AIDS is affecting the future population developments. For the projection constructed in this study, data on population is taken from the two most recent censuses, from 1991 and 2001. Data on HIV is available from HIV Sentinel Surveys 1992–2008, which test pregnant women for HIV in antenatal clinics. Additional data are collected from different sources and recent studies. The projection is made with software (EPP and Spectrum) specially designed for developing countries with scarce data. The projection includes two main scenarios which have different assumptions concerning the development of the HIV epidemic. In addition, two hypothetical scenarios are made: the first considering the case where HIV epidemic would never have existed and the second considering the case where HIV treatment would never have existed. The results indicate population growth for Namibia. Population in the 2001 census was 1.83 million and is projected to result in 2.38/2.39 million in 2020 in the first two scenarios. Without HIV, population would be 2.61 million and without treatment 2.30 million in 2020. Urban population is growing faster than rural. Even though AIDS is increasing mortality, the past high fertility rates still keep young adult age groups quite large. The HIV epidemic shows to be slowing down, but it is still increasing the mortality of the working-aged population. The initiation of HIV treatment in 2004 in the public sector seems to have had an effect on many projected indicators, diminishing the impact of HIV on the population. For example, the rise of mortality is slowing down.

Dynamics of Finnish starlings in 1951-2005 : from monitoring to population modelling

Farmland bird species have been declining in Europe. Many declines have coincided with general intensification of farming practices. In Finland, replacement of mixed farming, including rotational pastures, with specialized cultivation has been one of the most drastic changes from the 1960s to the 1990s. This kind of habitat deterioration limits the persistence of populations, as has been previously indicated from local populations. Integrated population monitoring, which gathers species-specific information of population size and demography, can be used to assess the response of a population to environment changes also at a large spatial scale. I targeted my analysis at the Finnish starling (Sturnus vulgaris). Starlings are common breeders in farmland habitats, but severe declines of local populations have been reported from Finland in the 1970s and 1980s and later from other parts of Europe. Habitat deterioration (replacement of pasture and grassland habitats with specialized cultivation areas) limits reproductive success of the species. I analysed regional population data in order to exemplify the importance of agricultural change to bird population dynamics. I used nestling ringing and nest-card data from 1951 to 2005 in order to quantify population trends and per capita reproductive success within several geographical regions (south/north and west/east aspects). I used matrix modelling, acknowledging age-specific survival and fecundity parameters and density-dependence, to model population dynamics. Finnish starlings declined by 80% from the end of the 1960s up to the end of the 1980s. The observed patterns and the model indicated that the population decline was due to the decline of the carrying capacity of farmland habitats. The decline was most severe in north Finland where populations largely become extinct. However, habitat deterioration was most severe in the southern breeding areas. The deteriorations in habitat quality decreased reproduction, which finally caused the decline. I suggest that poorly-productive northern populations have been partly maintained by immigration from the highly-productive southern populations. As the southern populations declined, ceasing emigration caused the population extinction in north. This phenomenon was explained with source sink population dynamics, which I structured and verified on the basis of a spatially explicit simulation model. I found that southern Finnish starling population exhibits ten-year cyclic regularity, a phenomenon that can be explained with delayed density-dependence in reproduction.

Novel matrix metalloproteinases in intestinal inflammation and in cancer of the gastrointestinal tract

Matrix metalloproteinases (MMPs) comprise a family of 23 zinc-dependent human endopeptidases that can degrade virtually all components of the extracellular matrix (ECM). They are classified into eight subgroups according to their structure and into six subgroups based on their substrate-specificity. MMPs have been implicated in inflammation, tissue destruction, cell migration, arthritis, vascular remodeling, angiogenesis, and tumor growth and invasion. MMPs are inhibited by their natural inhibitors, tissue inhibitors of metalloproteinases (TIMPs). Different MMPs function in the same tasks depending on the tissue or cancer subtype. I investigated the role of recently discovered MMPs, especially MMPs-19 and -26, in intestinal inflammation, in intestinal and cutaneous wound healing, and in intestinal cancer. Several MMPs and TIMPs were studied to determine their exact location at tissue level and to obtain information on possible functions of MMPs in such tissues and diseases as the healthy intestine, inflammatory bowel disease (IBD), neonatal necrotizing enterocolitis (NEC), pyoderma gangrenosum (PG), and colorectal as well as pancreatic cancers. In latent celiac disease (CD), I attempted to identify markers to predict later onset of CD in children and adolescents. The main methods used were immunohistochemistry, in situ hybridization, and Taqman RT-PCR. My results show that MMP-26 is important for re-epithelialization in intestinal and cutaneous wound healing. In colon and pancreatic cancers, MMP-26 seems to be a marker of invasive potential, although it is not itself expressed at the invasive front. MMP-21 is upregulated in pancreatic cancer and may be associated with tumor differentiation. MMPs-19 and -28 are associated with normal tissue turnover in the intestine, but they disappear in tumor progression as if they were protective markers . MMP-12 is an essential protease in intestinal inflammation and tissue destruction, as seen here in NEC and in previous CD studies. In patients with type 1 diabetes (T1D), MMPs-1, -3, and -12 were upregulated in the intestinal mucosa. Furthermore, MMP-7 was strongly elevated in NEC. In a model of aberrant wound repair, PG, MMPs-8, -9, and 10 and TNFα may promote ECM destruction, while absence of MMP-1 and MMP-26 from keratinocytes retards re-epithelialization. Based on my results, I suggest MMP-26 to be considered a putative marker for poor prognosis in pancreatic and colon cancer. However, since it functions differently in various tissues and tumor subtypes, this use cannot be generalized. Furthermore, MMP-26 is a beneficial marker for wound healing if expressed by migrating epithelial cells. MMP-12 expression in latent CD patients warrants research in a larger patient population to confirm its role as a specific marker for CD in pathologically indistinct cases. MMP-7 should be considered one of the most crucial proteases in NEC-associated tissue destruction; hence, specific inhibitors of this MMP are worth investigating. In PG, TNFα inhibitors are potential therapeutic agents, as shown already in clinical trials. In conclusion, studies of several MMPs in specific diseases and in healthy tissues are needed to elucidate their roles at the tissue level. MMPs and TIMPs are not exclusively destructive or reparative in tissues. They seem to function differently in different tissues. To identify selective MMP inhibitors, we must thoroughly understand the MMP profile (degradome) and their functions in various organs not to interfere with normal reparative functions during wound repair or beneficial host-response effects during cancer initiation and growth.

Zebrafish as a model of Parkinson's disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease among the elderly. Its etiology is unknown and no disease-modifying drugs are available. Thus, more information concerning its pathogenesis is needed. Among other genes, mutated PTEN-induced kinase 1 (PINK1) has been linked to early-onset and sporadic PD, but its mode of action is poorly understood. Most animal models of PD are based on the use of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). MPTP is metabolized to MPP+ by monoamine oxidase B (MAO B) and causes cell death of dopaminergic neurons in the substantia nigra in mammals. Zebrafish has been a widely used model organism in developmental biology, but is now emerging as a model for human diseases due to its ideal combination of properties. Zebrafish are inexpensive and easy to maintain, develop rapidly, breed in large quantities producing transparent embryos, and are readily manipulated by various methods, particularly genetic ones. In addition, zebrafish are vertebrate animals and results derived from zebrafish may be more applicable to mammals than results from invertebrate genetic models such as Drosophila melanogaster and Caenorhabditis elegans. However, the similarity cannot be taken for granted. The aim of this study was to establish and test a PD model using larval zebrafish. The developing monoaminergic neuronal systems of larval zebrafish were investigated. We identified and classified 17 catecholaminergic and 9 serotonergic neuron populations in the zebrafish brain. A 3-dimensional atlas was created to facilitate future research. Only one gene encoding MAO was found in the zebrafish genome. Zebrafish MAO showed MAO A-type substrate specificity, but non-A-non-B inhibitor specificity. Distribution of MAO in larval and adult zebrafish brains was both diffuse and distinctly cellular. Inhibition of MAO during larval development led to markedly elevated 5-hydroxytryptamine (serotonin, 5-HT) levels, which decreased the locomotion of the fish. MPTP exposure caused a transient loss of cells in specific aminergic cell populations and decreased locomotion. MPTP-induced changes could be rescued by the MAO B inhibitor deprenyl, suggesting a role for MAO in MPTP toxicity. MPP+ affected only one catecholaminergic cell population; thus, the action of MPP+ was more selective than that of MPTP. The zebrafish PINK1 gene was cloned in zebrafish, and morpholino oligonucleotides were used to suppress its expression in larval zebrafish. The functional domains and expression pattern of zebrafish PINK1 resembled those of other vertebrates, suggesting that zebrafish is a feasible model for studying PINK1. Translation inhibition resulted in cell loss of the same catecholaminergic cell populations as MPTP and MPP+. Inactivation of PINK1 sensitized larval zebrafish to subefficacious doses of MPTP, causing a decrease in locomotion and cell loss in one dopaminergic cell population. Zebrafish appears to be a feasible model for studying PD, since its aminergic systems, mode of action of MPTP, and functions of PINK1 resemble those of mammalians. However, the functions of zebrafish MAO differ from the two forms of MAO found in mammals. Future studies using zebrafish PD models should utilize the advantages specific to zebrafish, such as the ability to execute large-scale genetic or drug screens.

Periodontitis and peri-implantitis biomarkers in human oral fluids and the null-allele mouse model

Tissue destruction associated with the periodontal disease progression is caused by a cascade of host and microbial factors and proteolytic enzymes. Aberrant laminin-332 (Ln-332), human beta defensin (hBD), and matrix metalloproteinase (MMP) functions have been found in oral inflammatory diseases. The null-allele mouse model appears as the next step in oral disease research. The MMP-8 knock-out mouse model allowed us to clarify the involvement of MMP-8 in vivo in oral and related inflammatory diseases where MMP-8 is suggested to play a key role in tissue destruction. The cleaved Ln-332 γ2-chain species has been implicated in the apical migration of sulcular epithelial cells during the formation of periodontal pockets. We demonstrated that increased Ln-332 fragment levels in gingival crevicular fluid (GCF) are strongly associated with the severity of inflammation in periodontitis. Porphyromonas gingivalis trypsin-like proteinase can cleave an intact Ln-332 γ2-chain into smaller fragments and eventually promote the formation of periodontal pockets. hBDs are components of an innate mucosal defense against pathogenic microbes. Our results suggest that P. gingivalis trypsin-like proteinase can degrade hBD and thus reduce the innate immune response. Elevated levels and the increased activity of MMPs have been detected in several pathological tissue-destructive conditions where MMPs are shown to cleave extracellular matrix (ECM) and basement membrane (BM) molecules and to facilitate tissue destruction. Elevated levels of MMP-8 have been reported in many inflammatory diseases. In periodontitis, MMP-8 levels in gingival crevicular fluid (GCF) and in peri-implant sulcular fluid (PISF) are elevated at sites of active inflammation, and the increased levels of MMP-8 are mainly responsible for collagenase activity, which leads to tissue destruction. MMP-25, expressed by neutrophils, is involved in inflammatory diseases and in ECM turnover. MMP-26 can degrade ECM components and serve as an activator of other MMP enzymes. We further confirmed that increased levels and activation of MMP-8, -25, and -26 in GCF, PISF, and inflamed gingival tissue are associated with the severity of periodontal/peri-implant inflammation. We evaluated the role of MMP-8 in P. gingivalis-induced periodontitis by comparing MMP-8 knock-out (MMP8-/-) and wild-type mice. Surprisingly, MMP-8 significantly attenuated P. gingivalis-induced site-specific alveolar bone loss. We also evaluated systemic changes in serum immunoglobulin and lipoprotein profiles among these mouse groups. P. gingivalis infection increased HDL/VLDL particle size in the MMP-8-/- mice, which is an indicator of lipoprotein responses during systemic inflammation. Serum total LPS and IgG antibody levels were enhanced in both mice groups. P. gingivalis-induced periodontitis, especially in MMP-8-/- mice, is associated with severe alveolar bone loss and with systemic inflammatory and lipoprotein changes that are likely to be involved in early atherosclerosis.

Early detection of type 2 diabetes mellitus in Chinese and Indian adult population

Objectives of this study were to determine secular trends of diabetes prevalence in China and develop simple risk assessment algorithms for screening individuals with high-risk for diabetes or with undiagnosed diabetes in Chinese and Indian adults. Two consecutive population based surveys in Chinese and a prospective study in Mauritian Indians were involved in this study. The Chinese surveys were conducted in randomly selected populations aged 20-74 years in 2001-2002 (n=14 592) and 35-74 years in 2006 (n=4416). A two-step screening strategy using fasting capillary plasma glucose (FCG) as first-line screening test followed by standard 2-hour 75g oral glucose tolerance tests (OGTTs) was applied to 12 436 individuals in 2001, while OGTTs were administrated to all participants together with FCG in 2006 and to 2156 subjects in 2002. In Mauritius, two consecutive population based surveys were conducted in Mauritian Indians aged 20-65 years in 1987 and 1992; 3094 Indians (1141 men), who were not diagnosed as diabetes at baseline, were reexamined with OGTTs in 1992 and/or 1998. Diabetes and pre-diabetes was defined following 2006 World Health Organization/ International Diabetes Federation Criteria. Age-standardized, as well as age- and sex-specific, prevalence of diabetes and pre-diabetes in adult Chinese was significantly increased from 12.2% and 15.4% in 2001 to 16.0% and 21.2% in 2006, respectively. A simple Chinese diabetes risk score was developed based on the data of Chinese survey 2001-2002 and validated in the population of survey 2006. The risk scores based on β coefficients derived from the final Logistic regression model ranged from 3 – 32. When the score was applied to the population of survey 2006, the area under operating characteristic curve (AUC) of the score for screening undiagnosed diabetes was 0.67 (95% CI, 0.65-0.70), which was lower than the AUC of FCG (0.76 [0.74-0.79]), but similar to that of HbA1c (0.68 [0.65-0.71]). At a cut-off point of 14, the sensitivity and specificity of the risk score in screening undiagnosed diabetes was 0.84 (0.81-0.88) and 0.40 (0.38-0.41). In Mauritian Indian, body mass index (BMI), waist girth, family history of diabetes (FH), and glucose was confirmed to be independent risk predictors for developing diabetes. Predicted probabilities for developing diabetes derived from a simple Cox regression model fitted with sex, FH, BMI and waist girth ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, the AUC of the predicted probabilities was 0.62 (95% CI, 0.56-0.68) in men and 0.64(0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity was 0.72(0.71-0.74) and 0.47(0.45-0.49) in men; and 0.77(0.75-0.78) and 0.50(0.48-0.52) in women, respectively. In conclusion, there was a rapid increase in prevalence of diabetes in Chinese adults from 2001 to 2006. The simple risk assessment algorithms based on age, obesity and family history of diabetes showed a moderate discrimination of diabetes from non-diabetes, which may be used as first line screening tool for diabetes and pre-diabetes, and for health promotion purpose in Chinese and Indians.

Statistical analysis of the associations of hereditary factors with the risk of Type 1 diabetes and Diabetic Nephropathy based on the familial data collected through ascertaiment from population-based registers

In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.

Animal model and molecular interactions of Cln5

Neuronal ceroid lipofuscinoses (NCLs) are a family of inherited pediatric neurodegenerative disorders, leading to retinal degeneration, death of selective neuronal populations and accumulation of autofluorscent ceroid-lipopigments. The clinical manifestations are generally similar in all forms. The Finnish variant late infantile neuronal ceroid lipofuscinosis (vLINCLFin) is a form of NCL, especially enriched in the Finnish population. The aim of this thesis was to analyse the brain pathology of vLINCLFin utilising the novel Cln5-/- mouse model. Gene expression profiling of the brains of already symptomatic Cln5-/- mice revealed that inflammation, neurodegeneration and defects in myelinization are the major characteristics of the later stages of the disease. Histological characterization of the brain pathology confirmed that the thalamocortical system is affected in Cln5-/- mice, similarly to the other NCL mouse models. However, whereas the brain pathology in all other analyzed NCL mice initiate in the thalamus and spread only months later to the cortex, we observed that the sequence of events is uniquely reversed in Cln5-/- mice; beginning in the cortex and spreading to the thalamus only months later. We could also show that even though neurodegeneration is inititated in the cortex, reactive gliosis and loss of myelin are evident in specific nuclei of the thalamus already in the 1 month old brain. To obtain a deeper insight into the disturbed metabolic pathways, we performed gene expression profiling of presymptomatic mouse brains. We validated these findings with immunohistological analyses, and could show that cytoskeleton and myelin were affected in Cln5-/- mice. Comparison of gene expression profiling results of Cln5-/- and Cln1-/- mice, further highlighted that these two NCL models share a common defective pathway, leading to disturbances in the neuronal growth cone and cytoskeleton. Encouraged by the evidence of this defected pathway, we analyzed the molecular interactions of NCL-proteins and observed that Cln5 and Cln1/Ppt1 proteins interact with each other. Furthermore, we demonstrated that Cln5 and Cln1/Ppt1 share an interaction partner, the F1-ATP synthase, potentially linking both vLINCLFIN and INCL diseases to disturbed lipid metabolism. In addition, Cln5 was shown to interact with other NCL proteins; Cln2, Cln3, Cln6 and Cln8, implicating a central role for Cln5 in the NCL pathophysiology. This study is the first to describe the brain pathology and gene expression changes in the Cln5-/- mouse. Together the findings presented in this thesis represent novel information of the disease processes and the molecular mechanisms behind vLINCLFin and have highlighted that vLINCLFin forms a very important model to analyze the pathophysiology of NCL diseases.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Conceptual and statistical modelling of environmental effects in population dynamics

Population dynamics are generally viewed as the result of intrinsic (purely density dependent) and extrinsic (environmental) processes. Both components, and potential interactions between those two, have to be modelled in order to understand and predict dynamics of natural populations; a topic that is of great importance in population management and conservation. This thesis focuses on modelling environmental effects in population dynamics and how effects of potentially relevant environmental variables can be statistically identified and quantified from time series data. Chapter I presents some useful models of multiplicative environmental effects for unstructured density dependent populations. The presented models can be written as standard multiple regression models that are easy to fit to data. Chapters II IV constitute empirical studies that statistically model environmental effects on population dynamics of several migratory bird species with different life history characteristics and migration strategies. In Chapter II, spruce cone crops are found to have a strong positive effect on the population growth of the great spotted woodpecker (Dendrocopos major), while cone crops of pine another important food resource for the species do not effectively explain population growth. The study compares rate- and ratio-dependent effects of cone availability, using state-space models that distinguish between process and observation error in the time series data. Chapter III shows how drought, in combination with settling behaviour during migration, produces asymmetric spatially synchronous patterns of population dynamics in North American ducks (genus Anas). Chapter IV investigates the dynamics of a Finnish population of skylark (Alauda arvensis), and point out effects of rainfall and habitat quality on population growth. Because the skylark time series and some of the environmental variables included show strong positive autocorrelation, the statistical significances are calculated using a Monte Carlo method, where random autocorrelated time series are generated. Chapter V is a simulation-based study, showing that ignoring observation error in analyses of population time series data can bias the estimated effects and measures of uncertainty, if the environmental variables are autocorrelated. It is concluded that the use of state-space models is an effective way to reach more accurate results. In summary, there are several biological assumptions and methodological issues that can affect the inferential outcome when estimating environmental effects from time series data, and that therefore need special attention. The functional form of the environmental effects and potential interactions between environment and population density are important to deal with. Other issues that should be considered are assumptions about density dependent regulation, modelling potential observation error, and when needed, accounting for spatial and/or temporal autocorrelation.

Bustle behind the scenes of action : nemosis as a model for fibroblast inflammatory activation

Wound healing is a complex process that requires an interplay between several cell types. Classically, fibroblasts have been viewed as producers of extracellular matrix, but more recently they have been recognized as orchestrators of the healing response, promoting and directing, inflammation and neovascularization processes. Compared to those from healthy tissue, inflammation-associated fibroblasts display a dramatically altered phenotype and have been described as sentinel cells, able to switch to an immunoregulatory profile on cue. However, the activation mechanism still remains largely uncharacterized. Nemosis is a model for stromal fibroblast activation. When normal human primary fibroblasts are deprived of growth support they cluster, forming multicellular spheroids. Clustering results in upregulation of proinflammatory markers such as cyclooxygenase-2 and secretion of prostaglandins, proteinases, cytokines, and growth factors. Fibroblasts in nemosis induce wound healing and tumorigenic responses in many cell types found in inflammatory and tumor microenvironments. This study investigated the effect of nemotic fibroblasts on two components of the vascular system, leukocytes and endothelium, and characterized the inflammation-promoting responses that arose in these cell types. Fibroblasts in nemosis were found to secrete an array of chemotactic cytokines and attract leukocytes, as well as promote their adhesion to the endothelium. Nuclear factor-kB, the master regulator of many inflammatory responses, is activated in nemotic fibroblasts. Nemotic fibroblasts are known to produce large amounts of hepatocyte growth factor, a motogenic and angiogenic factor. Also, as shown in this study, they produce vascular endothelial growth factor. These two factors induced migratory and sprouting responses in endothelial cells, both required for neovascularization. Nemotic fibroblasts also caused a decrease in the expression of adherens and tight junction components on the surface of endothelial cells. The results allow the conclusion that fibroblasts in nemosis share many similarities with inflammation-associated fibroblasts. Both inflammation and stromal fibroblasts are known to be involved in tumorigenesis and tumor progression. Nemosis may be viewed as a model for stromal fibroblast activation, or it may correlate with cell-cell interactions between adjacent fibroblasts in vivo. Nevertheless, due to nemosis-derived production of proinflammatory cytokines and growth factors, fibroblast nemosis may have therapeutic potential as an inducer of controlled tissue repair. Knowledge of stromal fibroblast activation gained through studies of nemosis, could provide new strategies to control unwanted inflammation and tumor progression.

Habitat use and population dynamics of brown bears (Ursus arctos) in Scandinavia

Large carnivore populations are currently recovering from past extirpation efforts and expanding back into their original habitats. At the same time human activities have resulted in very few wilderness areas left with suitable habitats and size large enough to maintain populations of large carnivores without human contact. Consequently the long-term future of large carnivores depends on their successful integration into landscapes where humans live. Thus, understanding their behaviour and interaction with surrounding habitats is of utmost importance in the development of management strategies for large carnivores. This applies also to brown bears (Ursus arctos) that were almost exterminated from Scandinavia and Finland at the turn of the century, but are now expanding their range with the current population estimates being approximately 2600 bears in Scandinavia and 840 in Finland. This thesis focuses on the large-scale habitat use and population dynamics of brown bears in Scandinavia with the objective to develop modelling approaches that support the management of bear populations. Habitat analysis shows that bear home ranges occur mainly in forested areas with a low level of human influence relative to surrounding areas. Habitat modelling based on these findings allows identification and quantification of the potentially suitable areas for bears in Scandinavia. Additionally, this thesis presents novel improvements to home range estimation that enable realistic estimates of the effective area required for the bears to establish a home range. This is achieved through fitting to the radio-tracking data to establish the amount of temporal autocorrelation and the proportion of time spent in different habitat types. Together these form a basis for the landscape-level management of the expanding population. Successful management of bears requires also assessment of the consequences of harvest on the population viability. An individual-based simulation model, accounting for the sexually selected infanticide, was used to investigate the possibility of increasing the harvest using different hunting strategies, such as trophy harvest of males. The results indicated that the population can sustain twice the current harvest rate. However, harvest should be changed gradually while carefully monitoring the population growth as some effects of increased harvest may manifest themselves only after a time-delay. The results and methodological improvements in this thesis can be applied to the Finnish bear population and to other large carnivores. They provide grounds for the further development of spatially-realistic management-oriented models of brow bear dynamics that can make projections of the future distribution of bears while accounting for the development of human activities.

Co-Signaling by Neurotrophic Factors and the Extracellular Matrix for Axonal Growth and Neuronal Survival

Neurotrophic factors (NTFs) and the extracellular matrix (ECM) are important regulators of axonal growth and neuronal survival in mammalian nervous system. Understanding of the mechanisms of this regulation is crucial for the development of posttraumatic therapies and drug intervention in the injured nervous system. NTFs act as soluble, target-derived extracellular regulatory molecules for a wide range of physiological functions including axonal guidance and the regulation of programmed cell death in the nervous system. The ECM determines cell adhesion and regulates multiple physiological functions via short range cell-matrix interactions. The present work focuses on the mechanisms of the action of NTFs and the ECM on axonal growth and survival of cultured sensory neurons from dorsal root ganglia (DRG). We first examined signaling mechanisms of the action of the glial cell line-derived neurotrophic factor (GDNF) family ligands (GFLs) on axonal growth. GDNF, neurturin (NRTN) and artemin (ART) but not persephin (PSPN) promoted axonal initiation in cultured DRG neurons from young adult mice. This effect required Src family kinase (SFK) activity. In neurons from GFRalpha2-deficient mice, NRTN did not significantly promote axonal initiation. GDNF and NRTN induced extensive lamellipodia formation on neuronal somata and growth cones. This study suggested that GDNF, NRTN and ARTN may serve as stimulators of nerve regeneration under posttraumatic conditions. Consequently we studied the convergence of signaling pathways induced by NTFs and the ECM molecule laminin in the intracellular signaling network that regulates axonal growth. We demonstrated that co-stimulation of DRG neurons with NTFs (GDNF, NRTN or nerve growth factor (NGF)) and laminin leads to axonal growth that requires activation of SFKs. A different, SFK-independent signaling pathway evoked axonal growth on laminin in the absence of the NTFs. In contrast, axonal branching was regulated by SFKs both in the presence and in the absence of NGF. We proposed and experimentally verified a Boolean model of the signaling network triggered by NTFs and laminin. Our results put forward an approach for predictable, Boolean logics-driven pharmacological manipulation of a complex signaling network. Finally we found that N-syndecan, the receptor for the ECM component HB-GAM was required for the survival of neonatal sensory neurons in vitro. We demonstrated massive cell death of cultured DRG neurons from mice deficient in the N-syndecan gene as compared to wild type controls. Importantly, this cell death could not be prevented by NGF the neurotrophin which activates multiple anti-apoptotic cascades in DRG neurons. The survival deficit was observed during first postnatal week. By contrast, DRG neurons from young adult N-syndecan knock-out mice exhibited normal survival. This study identifies a completely new syndecan-dependent type of signaling that regulates cell death in neurons.

Microsurgical Aneurysm Model in Rats and Mice: Development of Endovascular Treatment and Optimization of Magnetic Resonance Imaging

The rupture of a cerebral artery aneurysm causes a devastating subarachnoid hemorrhage (SAH), with a mortality of almost 50% during the first month. Each year, 8-11/100 000 people suffer from aneurysmal SAH in Western countries, but the number is twice as high in Finland and Japan. The disease is most common among those of working age, the mean age at rupture being 50-55 years. Unruptured cerebral aneurysms are found in 2-6% of the population, but knowledge about the true risk of rupture is limited. The vast majority of aneurysms should be considered rupture-prone, and treatment for these patients is warranted. Both unruptured and ruptured aneurysms can be treated by either microsurgical clipping or endovascular embolization. In a standard microsurgical procedure, the neck of the aneurysm is closed by a metal clip, sealing off the aneurysm from the circulation. Endovascular embolization is performed by packing the aneurysm from the inside of the vessel lumen with detachable platinum coils. Coiling is associated with slightly lower morbidity and mortality than microsurgery, but the long-term results of microsurgically treated aneurysms are better. Endovascular treatment methods are constantly being developed further in order to achieve better long-term results. New coils and novel embolic agents need to be tested in a variety of animal models before they can be used in humans. In this study, we developed an experimental rat aneurysm model and showed its suitability for testing endovascular devices. We optimized noninvasive MRI sequences at 4.7 Tesla for follow-up of coiled experimental aneurysms and for volumetric measurement of aneurysm neck remnants. We used this model to compare platinum coils with polyglycolic-polylactic acid (PGLA) -coated coils, and showed the benefits of the latter in this model. The experimental aneurysm model and the imaging methods also gave insight into the mechanisms involved in aneurysm formation, and the model can be used in the development of novel imaging techniques. This model is affordable, easily reproducible, reliable, and suitable for MRI follow-up. It is also suitable for endovascular treatment, and it evades spontaneous occlusion.