Impacts of agriculture on amphibians at multiple scales

Agriculture-mediated habitat loss and degradation together with climate change are among the greatest global threats to species, communities, and ecosystem functioning. During the last century, more than 50% of the world's wetlands have been lost and agricultural activities have subjected wetland species to increased isolation and decreased quality of habitats. Likewise, as a part of agricultural intensification, the use of pesticides has increased notably, and pesticide residues occur frequently in wetlands making the exposure of wetland organisms to pesticides highly probable. In this thesis, a set of ecotoxicological and landscape ecological studies were carried out to investigate pesticide-effects on tadpoles, and species-habitat relationships of amphibians in agricultural landscapes. The results show that the fitness of R. temporaria tadpoles can be negatively affected by sublethal pesticide concentrations, and that pesticides may increase the costs of response to natural environmental stressors. However, tadpoles may also be able to compensate for some of the negative effects of pesticides. The results further demonstrate that both historic and current-day agricultural land use can negatively impact amphibians, but that in some cases the costs of living in agricultural habitats may only become apparent when amphibians face other environmental stressors, such as drought. Habitat heterogeneity may, however, increase the persistence of amphibians in agricultural landscapes. Hence, the results suggest that amphibians are likely to be affected by agricultural processes that operate at several spatial and temporal scales, and that it is probable that various processes related to current-day agriculture will affect both larval and adult amphibians. The results imply that maintaining dense wetland patterns could enhance persistence of amphibian populations in agricultural habitats, and indicate that heterogeneous landscapes may lower the risk of regional amphibian population declines under extreme weather perturbations.

Genetic analysis of chromosomal regions 2q33, 7q32 and 19q13 in multiple sclerosis susceptibility

Multiple sclerosis (MS) is an immune-mediated demyelinating disorder of the central nervous system (CNS) affecting 0.1-0.2% of Northern European descent population. MS is considered to be a multifactorial disease, both environment and genetics play a role in its pathogenesis. Despite several decades of intense research, the etiological and pathogenic mechanisms underlying MS remain still largely unknown and no curative treatment exists. The genetic architecture underlying MS is complex with multiple genes involved. The strongest and the best characterized predisposing genetic factors for MS are located, as in other immune-mediated diseases, in the major histocompatibility complex (MHC) on chromosome 6. In humans MHC is called human leukocyte antigen (HLA). Alleles of the HLA locus have been found to associate strongly with MS and remained for many years the only consistently replicable genetic associations. However, recently other genes located outside the MHC region have been proposed as strong candidates for susceptibility to MS in several studies. In this thesis a new genetic locus located on chromosome 7q32, interferon regulatory factor 5 (IRF5), was identified in the susceptibility to MS. In particular, we found that common variation of the gene was associated with the disease in three different populations, Spanish, Swedish and Finnish. We also suggested a possible functional role for one of the risk alleles with impact on the expression of the IRF5 locus. Previous studies have pointed out a possible role played by chromosome 2q33 in the susceptibility to MS and other autoimmune disorders. The work described here also investigated the involvement of this chromosomal region in MS predisposition. After the detection of genetic association with 2q33 (article-1), we extended our analysis through fine-scale single nucleotide polymorphism (SNP) mapping to define further the contribution of this genomic area to disease pathogenesis (article-4). We found a trend (p=0.04) for association to MS with an intronic SNP located in the inducible T-cell co-stimulator (ICOS) gene, an important player in the co-stimulatory pathway of the immune system. Expression analysis of ICOS revealed a novel, previously uncharacterized, alternatively spliced isoform, lacking the extracellular domain that is needed for ligand binding. The stability of the newly-identified transcript variant and its subcellular localization were analyzed. These studies indicated that the novel isoform is stable and shows different subcellular localization as compared to full-length ICOS. The novel isoform might have a regulatory function, but further studies are required to elucidate its function. Chromosome 19q13 has been previously suggested as one of the genomic areas involved in MS predisposition. In several populations, suggestive linkage signals between MS predisposition and 19q13 have been obtained. Here, we analysed the role of allelic variation in 19q13 by family based association analysis in 782 MS families collected from Finland. In this dataset, we were not able to detect any statistically significant associations, although several previously suggested markers were included to the analysis. Replication of the previous findings on the basis of linkage disequilibrium between marker allele and disease/risk allele appears notoriously difficult because of limitations such as allelic heterogeneity. Re-sequencing based approaches may be required for elucidating the role of chromosome 19q13 with MS. This thesis has resulted in the identification of a new MS susceptibility locus (IRF5) previously associated with other inflammatory or autoimmune disorders, such as SLE. IRF5 is one of the mediators of interferons biological function. In addition to providing new insight in the possible pathogenetic pathway of the disease, this finding suggests that there might be common mechanisms between different immune-mediated disorders. Furthermore the work presented here has uncovered a novel isoform of ICOS, which may play a role in regulatory mechanisms of ICOS, an important mediator of lymphocyte activation. Further work is required to uncover its functions and possible involvement of the ICOS locus in MS susceptibility.

Coherent quantum Boltzmann equations from cQPA

We reformulate and extend our recently introduced quantum kinetic theory for interacting fermion and scalar fields. Our formalism is based on the coherent quasiparticle approximation (cQPA) where nonlocal coherence information is encoded in new spectral solutions at off-shell momenta. We derive explicit forms for the cQPA propagators in the homogeneous background and show that the collision integrals involving the new coherence propagators need to be resummed to all orders in gradient expansion. We perform this resummation and derive generalized momentum space Feynman rules including coherent propagators and modified vertex rules for a Yukawa interaction. As a result we are able to set up self-consistent quantum Boltzmann equations for both fermion and scalar fields. We present several examples of diagrammatic calculations and numerical applications including a simple toy model for coherent baryogenesis.

Multiple Perspectives on Networks: Conceptual Development, Application and Integration in an Entrepreneurial Context

Multiple Perspectives on Networks: Conceptual Development, Application and Integration in an Entrepreneurial Context. The purpose of this thesis is to enhance cross-fertilization between three different approaches to network research. The business network approach may contribute in terms of how relationships are created, developed and how tie content changes within ties, not only between them. The social network approach adds to the discussion by offering concepts of structural change on a network level. The network approach in entrepreneurship contributes by emphasizing network content, governance and structure as a way of understanding and capturing networks. This is discussed in the conceptual articles, Articles 2 and 3. The ultimate purpose of this thesis is to develop a theoretical and empirical understanding of network development processes. This is fulfilled by presenting a theoretical framework, which offers multiple views on process as a developmental outcome. The framework implies that change ought to be captured both within and among relationships over time in the firm as well as in the network. Consequently, changes in structure and interaction taking place simultaneously need to be included when doing research on network development. The connection between micro and macro levels is also stressed. Therefore, the entrepreneur or firm level needs to be implemented together with the network level. The surrounding environment impacts firm and network development and vice versa and hence needs to be integrated. Further, it is necessary to view network development not only as a way forward but to include both progression and regression as inevitable parts of the process. Finally, both stability and change should be taken into account as part of network development. Empirical results in Article 1 show support for a positive impact of networks on SME internationalization. Article 4 compares networks of novice, serial and portfolio entrepreneurs but the empirical results show little support for differences in the networks by type of entrepreneur. The results demonstrate that network interaction and structure is not directly impacted by type of entrepreneur involved. It indicates instead that network structure and interaction is more impacted by the development phase of the firm. This in turn is in line with the theoretical implications, stating that the development of the network and the firm impacts each other, as they co-evolve.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Studies on Causes of Multiple Sclerosis : From Genes to Transcriptome

Multiple sclerosis (MS) is the most common cause of neurological disability in young adults, affecting more than two million people worldwide. It manifests as a chronic inflammation in the central nervous system (CNS) and causes demyelination and neurodegeneration. Depending on the location of the demyelinated plaques and axonal loss, a variety of symptoms can be observed including deficits in vision, coordination, balance and movement. With a typical age of onset at 20-40 years, the social and economic impacts of MS on lives of the patients and their families are considerable. Unfortunately the current treatments are relatively inefficient and the development of more effective treatments has been impeded by our limited understanding of the causes and pathogenesis of MS. Risk of MS is higher in biological relatives of MS patients than in the general population. Twin and adoption studies have shown that familial clustering of MS is explained by shared genetic factors rather than by shared familial environment. While the involvement of the human leukocyte antigen (HLA) genes was first discovered four decades ago, additional genetic risk factors have only recently been identified through genome-wide association studies (GWAS). Current evidence suggests that MS is a highly polygenic disease with perhaps hundreds of common variants with relatively modest effects contributing to susceptibility. Despite extensive research, the majority of these risk factors still remain to be identified. In this thesis the aim was to identify novel genes and pathways involved in MS. Using genome-wide microarray technology, gene expression levels in peripheral blood mononuclear cells (PBMC) from 12 MS patients and 15 controls were profiled and more than 600 genes with altered expression in MS were identified. Three of five selected findings, DEFA1A3, LILRA4 and TNFRSF25, were successfully replicated in an independent sample. Increased expression of DEFA1A3 in MS is a particularly interesting observation, because its elevated levels have previously been reported also in several other autoimmune diseases. A systematic review of seven microarray studies was then performed leading to identification of 229 genes, in which either decreased or increased expression in MS had been reported in at least two studies. In general there was relatively little overlap across the experiments: 11 of the 229 genes had been reported in three studies and only HSPA1A in four studies. Nevertheless, these 229 genes were associated with several immunological pathways including interleukin pathways related to type 2 and type 17 helper T cells and regulatory T cells. However, whether these pathways are involved in causing MS or related to secondary processes activated after disease onset remains to be investigated. The 229 genes were also compared with loci identified in published MS GWASs. Single nucleotide polymorphisms (SNP) in 17 of the 229 loci had been reported to be associated with MS with P-value less than 0.0001 including variants in CXCR4 and SAPS2, which were the only loci where evidence for correlation between the associated variant and gene expression was found. The CXCR4 variant was further tested for association with MS in a large case-control sample and the previously reported suggestive association was replicated (P-value is 0.0004). Finally, common genetic variants in candidate genes, which had been selected on the basis of showing association with other autoimmune diseases (MYO9B) or showing differential expression in MS in our study (DEFA1A3, LILRA4 and TNFRSF25), were tested for association with MS, but no evidence of association was found. In conclusion, through a systematic review of genome-wide expression studies in MS we have identified several promising candidate genes and pathways for future studies. In addition, we have replicated a previously suggested association of a SNP variant upstream of CXCR4 with MS. Keywords: autoimmune disease, common variant, CXCR4, DEFA1A3, HSPA1A,gene expression, genetic association, GWAS, MS, multiple sclerosis, systematic review