Search for single top quark production in pp̅ collisions at √s=1.96 TeV in the missing transverse energy plus jets topology

We report a search for single top quark production with the CDF II detector using 2.1 fb-1 of integrated luminosity of pbar p collisions at sqrt{s}=1.96 TeV. The data selected consist of events characterized by large energy imbalance in the transverse plane and hadronic jets, and no identified electrons and muons, so the sample is enriched in W -> tau nu decays. In order to suppress backgrounds, additional kinematic and topological requirements are imposed through a neural network, and at least one of the jets must be identified as a b-quark jet. We measure an excess of signal-like events in agreement with the standard model prediction, but inconsistent with a model without single top quark production by 2.1 standard deviations (sigma), with a median expected sensitivity of 1.4 sigma. Assuming a top quark mass of 175 GeV/c2 and ascribing the excess to single top quark production, the cross section is measured to be 4.9+2.5-2.2(stat+syst)pb, consistent with measurements performed in independent datasets and with the standard model prediction.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Molecular epidemiology of human rhinoviruses

The first part of this work investigates the molecular epidemiology of a human enterovirus (HEV), echovirus 30 (E-30). This project is part of a series of studies performed in our research team analyzing the molecular epidemiology of HEV-B viruses. A total of 129 virus strains had been isolated in different parts of Europe. The sequence analysis was performed in three different genomic regions: 420 nucleotides (nt) in the VP4/VP2 capsid protein coding region, the entire VP1 capsid protein coding gene of 876 nt, and 150 nt in the VP1/2A junction region. The analysis revealed a succession of dominant sublineages within a major genotype. The temporally earlier genotypes had been replaced by a genetically homogenous lineage that has been circulating in Europe since the late 1970s. The same genotype was found by other research groups in North America and Australia. Globally, other cocirculating genetic lineages also exist. The prevalence of a dominant genotype makes E-30 different from other previously studied HEVs, such as polioviruses and coxsackieviruses B4 and B5, for which several coexisting genetic lineages have been reported. The second part of this work deals with molecular epidemiology of human rhinoviruses (HRVs). A total of 61 field isolates were studied in the 420-nt stretch in the capsid coding region of VP4/VP2. The isolates were collected from children under two years of age in Tampere, Finland. Sequences from the clinical isolates clustered in the two previously known phylogenetic clades. Seasonal clustering was found. Also, several distinct serotype-like clusters were found to co-circulate during the same epidemic season. Reappearance of a cluster after disappearing for a season was observed. The molecular epidemiology of the analyzed strains turned out to be complex, and we decided to continue our studies of HRV. Only five previously published complete genome sequences of HRV prototype strains were available for analysis. Therefore, all designated HRV prototype strains (n=102) were sequenced in the VP4/VP2 region, and the possibility of genetic typing of HRV was evaluated. Seventy-six of the 102 prototype strains clustered in HRV genetic group A (HRV-A) and 25 in group B (HRV-B). Serotype 87 clustered separately from other HRVs with HEV species D. The field strains of HRV represented as many as 19 different genotypes, as judged with an approximate demarcation of a 20% nt difference in the VP4/VP2 region. The interserotypic differences of HRV were generally similar to those reported between different HEV serotypes (i.e. about 20%), but smaller differences, less than 10%, were also observed. Because some HRV serotypes are genetically so closely related, we suggest that the genetic typing be performed using the criterion "the closest prototype strain". This study is the first systematic genetic characterization of all known HRV prototype strains, providing a further taxonomic proposal for classification of HRV. We proposed to divide the genus Human rhinoviruses into HRV-A and HRV-B. The final part of the work comprises a phylogenetic analysis of a subset (48) of HRV prototype strains and field isolates (12) in the nonstructural part of the genome coding for the RNA-dependent RNA polymerase (3D). The proposed division of the HRV strains in the species HRV-A and HRV-B was also supported by 3D region. HRV-B clustered closer to HEV species B, C, and also to polioviruses than to HRV-A. Intraspecies variation within both HRV-A and HRV-B was greater in the 3D coding region than in the VP4/VP2 coding region, in contrast to HEV. Moreover, the diversity of HRV in 3D exceeded that of HEV. One group of HRV-A, designated HRV-A', formed a separate cluster outside other HRV-A in the 3D region. It formed a cluster also in the capsid region, but located within HRV-A. This may reflect a different evolutionary history of distinct genomic regions among HRV-A. Furthermore, the tree topology within HRV-A in the 3D region differed from that in the VP4/VP2, suggesting possible recombination events in the evolution of the strains. No conflicting phylogenies were observed in any of the 12 field isolates. Possible recombination was further studied using the Similarity and Bootscanning analyses of the complete genome sequences of HRV available in public databases. Evidence for recombination among HRV-A was found, as HRV2 and HRV39 showed higher similarity in the nonstructural part of the genome. Whether HRV2 and HRV39 strains - and perhaps also some other HRV-A strains not yet completely sequenced - are recombinants remains to be determined.

Positional cloning and pathway analysis of the asthma susceptibility gene, NPSR1

In the present study, we identified a novel asthma susceptibility gene, NPSR1 (neuropeptide S receptor 1) on chromosome 7p14.3 by the positional cloning strategy. An earlier significant linkage mapping result among Finnish Kainuu asthma families was confirmed in two independent cohorts: in asthma families from Quebec, Canada and in allergy families from North Karelia, Finland. The linkage region was narrowed down to a 133-kb segment by a hierarchial genotyping method. The observed 77-kb haplotype block showed 7 haplotypes and a similar risk and nonrisk pattern in all three populations studied. All seven haplotypes occur in all three populations at frequences > 2%. Significant elevated relative risks were detected for elevated total IgE (immunoglobulin E) or asthma. Risk effects of the gene variants varied from 1.4 to 2.5. NPSR1 belongs to the G protein-coupled receptor (GPCR) family with a topology of seven transmembrane domains. NPSR1 has 9 exons, with the two main transcripts, A and B, encoding proteins of 371 and 377 amino acids, respectively. We detected a low but ubiquitous expression level of NPSR1-B in various tissues and endogenous cell lines while NPSR1-A has a more restricted expression pattern. Both isoforms were expressed in the lung epithelium. We observed aberrant expression levels of NPSR1-B in smooth muscle in asthmatic bronchi as compared to healthy. In an experimental mouse model, the induced lung inflammation resulted in elevated Npsr1 levels. Furthermore, we demonstrated that the activation of NPSR1 with its endogenous agonist, neuropeptide S (NPS), resulted in a significant inhibition of the growth of NPSR1-A overexpressing stable cell lines (NPSR1-A cells). To determine which target genes were regulated by the NPS-NPSR1 pathway, NPSR1-A cells were stimulated with NPS, and differentially expressed genes were identified using the Affymetrix HGU133Plus2 GeneChip. A total of 104 genes were found significantly up-regulated and 42 down-regulated 6 h after NPS administration. The up-regulated genes included many neuronal genes and some putative susceptibility genes for respiratory disorders. By Gene Ontology enrichment analysis, the biological process terms, cell proliferation, morphogenesis and immune response were among the most altered. The expression of four up-regulated genes, matrix metallopeptidase 10 (MMP10), INHBA (activin A), interleukin 8 (IL8) and EPH receptor A2 (EPHA2), were verified and confirmed by quantitative reverse-transcriptase-PCR. In conclusion, we identified a novel asthma susceptibility gene, NPSR1, on chromosome 7p14.3. NPS-NPSR1 represents a novel pathway that regulates cell proliferation and immune responses, and thus may have functional relevance in the pathogenesis of asthma.

Observation of single top quark production and measurement of |Vtb| with CDF

We report the observation of electroweak single top quark production in 3.2  fb-1 of pp̅ collision data collected by the Collider Detector at Fermilab at √s=1.96  TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3-0.5+0.6(stat+sys)  pb, extract the value of the Cabibbo-Kobayashi-Maskawa matrix element |Vtb|=0.91-0.11+0.11(stat+sys)±0.07  (theory), and set a lower limit |Vtb|>0.71 at the 95% C.L., assuming mt=175  GeV/c2.

Observation of single top quark production and measurement of |Vtb| with CDF

We report the observation of electroweak single top quark production in 3.2 fb-1 of ppbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3+0.6-0.5(stat+sys) pb, extract the CKM matrix element value |Vtb|=0.91+0.11-0.11 (stat+sys)+-0.07(theory), and set a lower limit |Vtb|>0.71 at the 95% confidence level, assuming m_t=175 GeVc^2.

Spatial ecology of food webs : herbivore-parasitoid communities on the pedunculate oak

Herbivorous insects, their host plants and natural enemies form the largest and most species-rich communities on earth. But what forces structure such communities? Do they represent random collections of species, or are they assembled by given rules? To address these questions, food webs offer excellent tools. As a result of their versatile information content, such webs have become the focus of intensive research over the last few decades. In this thesis, I study herbivore-parasitoid food webs from a new perspective: I construct multiple, quantitative food webs in a spatially explicit setting, at two different scales. Focusing on food webs consisting of specialist herbivores and their natural enemies on the pedunculate oak, Quercus robur, I examine consistency in food web structure across space and time, and how landscape context affects this structure. As an important methodological development, I use DNA barcoding to resolve potential cryptic species in the food webs, and to examine their effect on food web structure. I find that DNA barcoding changes our perception of species identity for as many as a third of the individuals, by reducing misidentifications and by resolving several cryptic species. In terms of the variation detected in food web structure, I find surprising consistency in both space and time. From a spatial perspective, landscape context leaves no detectable imprint on food web structure, while species richness declines significantly with decreasing connectivity. From a temporal perspective, food web structure remains predictable from year to year, despite considerable species turnover in local communities. The rate of such turnover varies between guilds and species within guilds. The factors best explaining these observations are abundant and common species, which have a quantitatively dominant imprint on overall structure, and suffer the lowest turnover. By contrast, rare species with little impact on food web structure exhibit the highest turnover rates. These patterns reveal important limitations of modern metrics of quantitative food web structure. While they accurately describe the overall topology of the web and its most significant interactions, they are disproportionately affected by species with given traits, and insensitive to the specific identity of species. As rare species have been shown to be important for food web stability, metrics depicting quantitative food web structure should then not be used as the sole descriptors of communities in a changing world. To detect and resolve the versatile imprint of global environmental change, one should rather use these metrics as one tool among several.

Playing Games on Sets and Models

The most prominent objective of the thesis is the development of the generalized descriptive set theory, as we call it. There, we study the space of all functions from a fixed uncountable cardinal to itself, or to a finite set of size two. These correspond to generalized notions of the universal Baire space (functions from natural numbers to themselves with the product topology) and the Cantor space (functions from natural numbers to the {0,1}-set) respectively. We generalize the notion of Borel sets in three different ways and study the corresponding Borel structures with the aims of generalizing classical theorems of descriptive set theory or providing counter examples. In particular we are interested in equivalence relations on these spaces and their Borel reducibility to each other. The last chapter shows, using game-theoretic techniques, that the order of Borel equivalence relations under Borel reduciblity has very high complexity. The techniques in the above described set theoretical side of the thesis include forcing, general topological notions such as meager sets and combinatorial games of infinite length. By coding uncountable models to functions, we are able to apply the understanding of the generalized descriptive set theory to the model theory of uncountable models. The links between the theorems of model theory (including Shelah's classification theory) and the theorems in pure set theory are provided using game theoretic techniques from Ehrenfeucht-Fraïssé games in model theory to cub-games in set theory. The bottom line of the research declairs that the descriptive (set theoretic) complexity of an isomorphism relation of a first-order definable model class goes in synch with the stability theoretical complexity of the corresponding first-order theory. The first chapter of the thesis has slightly different focus and is purely concerned with a certain modification of the well known Ehrenfeucht-Fraïssé games. There we (me and my supervisor Tapani Hyttinen) answer some natural questions about that game mainly concerning determinacy and its relation to the standard EF-game