Electrocardiographic repolarization variables in detecting myocardial infarction and ischemic injury : From body surface potential mapping to a single lead

The aim of the studies was to improve the diagnostic capability of electrocardiography (ECG) in detecting myocardial ischemic injury with a future goal of an automatic screening and monitoring method for ischemic heart disease. The method of choice was body surface potential mapping (BSPM), containing numerous leads, with intention to find the optimal recording sites and optimal ECG variables for ischemia and myocardial infarction (MI) diagnostics. The studies included 144 patients with prior MI, 79 patients with evolving ischemia, 42 patients with left ventricular hypertrophy (LVH), and 84 healthy controls. Study I examined the depolarization wave in prior MI with respect to MI location. Studies II-V examined the depolarization and repolarization waves in prior MI detection with respect to the Minnesota code, Q-wave status, and study V also with respect to MI location. In study VI the depolarization and repolarization variables were examined in 79 patients in the face of evolving myocardial ischemia and ischemic injury. When analyzed from a single lead at any recording site the results revealed superiority of the repolarization variables over the depolarization variables and over the conventional 12-lead ECG methods, both in the detection of prior MI and evolving ischemic injury. The QT integral, covering both depolarization and repolarization, appeared indifferent to the Q-wave status, the time elapsed from MI, or the MI or ischemia location. In the face of evolving ischemic injury the performance of the QT integral was not hampered even by underlying LVH. The examined depolarization and repolarization variables were effective when recorded in a single site, in contrast to the conventional 12-lead ECG criteria. The inverse spatial correlation of the depolarization and depolarization waves in myocardial ischemia and injury could be reduced into the QT integral variable recorded in a single site on the left flank. In conclusion, the QT integral variable, detectable in a single lead, with optimal recording site on the left flank, was able to detect prior MI and evolving ischemic injury more effectively than the conventional ECG markers. The QT integral, in a single-lead or a small number of leads, offers potential for automated screening of ischemic heart disease, acute ischemia monitoring and therapeutic decision-guiding as well as risk stratification.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Farmland birds and habitat heterogeneity in intensively cultivated boreal agricultural landscapes

The biodiversity of farmland ecosystems has decreased remarkably during the latter half of the 20th century, and this development is due to intensive farming with its various environmental effects. In the countries of the EU the Common Agricultural Policy (CAP) is the main determinant affecting farmland biodiversity, since the agricultural policy defines guidelines of agricultural practices. In addition to policies promoting intensive farming, CAP also includes national agri-environment schemes (AES), in which a part of subsidies paid to farmers is directed to acts that are presumed to promote environmental protection and biodiversity. In order to shape AES into relevant and powerful tools for biodiversity protection, detailed studies on the effects of agriculture on species and species assemblages are needed. In my thesis I investigated the importance of habitat heterogeneity and effects of different habitat and landscape characteristics on farmland bird abundance and diversity in typical cereal cultivation-dominated southern Finnish agricultural environments. The extensive data used were collected by territory mapping. My two main study species were the drastically declined ortolan bunting (Emberiza hortulana) and the phenomenally increased tree sparrow (Passer montanus); in addition I studied assemblages of 20 species breeding in open arable and edge/bush habitats. In light of my results I discuss whether the Finnish AES take into account the habitat needs of farmland birds, and I provide suggestions for improvement of the future AES. My results show that heterogeneity of both uncultivated and cultivated habitats increases abundance and species richness among farmland birds, but in this respect the amount and diversity of uncultivated habitats are essential. Ditches in particular are a keystone structure for farmland birds in boreal landscapes. Ditches lined by trees or bushes increased ortolan bunting abundance. Loss of that kind of ditches (and clearance of forest and bush patches), reduced breeding ortolan buntings, mainly by decreasing availability of song-posts that are important for the breeding groups of the species. Heterogeneity of uncultivated habitats, most importantly open ditches and the habitat patch richness, increased densities and species richnesses of species assemblages of open arable and edge/bush habitats. Human impact (winter-feeding, nest-boxes) affected favourably the tree sparrow s rapid range expansion in southern Finland, but any habitat types had no significant effects. At the moment the Finnish agri-environmental policy does not conserve farmland ditches as a habitat type. Instead, sub-surface drainage is financially promoted. This is a fatal mistake as far as farmland biodiversity is concerned. In addition to the maintenance of ditches, at least the following aspects should be included more than is done previously in the measures of the future AES: 1) promotion of diverse crop rotation (especially by promoting animal husbandry), 2) maintenance of tree and bush vegetation in islets and along ditches, 3) promotion of organic farming.