BACKGROUND: The complexity and scale of the knowledge in the biomedical domain has motivated research work towards mining heterogeneous data from both structured and unstructured knowledge bases. Towards this direction, it is necessary to combine facts in order to formulate hypotheses or draw conclusions about the domain concepts. This work addresses this problem by using indirect knowledge connecting two concepts in a knowledge graph to discover hidden relations between them. The graph represents concepts as vertices and relations as edges, stemming from structured (ontologies) and unstructured (textual) data. In this graph, path patterns, i.e. sequences of relations, are mined using distant supervision that potentially characterize a biomedical relation. RESULTS: It is possible to identify characteristic path patterns of biomedical relations from this representation using machine learning. For experimental evaluation two frequent biomedical relations, namely \'has target\', and \'may treat\', are chosen. Results suggest that relation discovery using indirect knowledge is possible, with an AUC that can reach up to 0.8, a result which is a great improvement compared to the random classification, and which shows that good predictions can be prioritized by following the suggested approach. CONCLUSIONS: Analysis of the results indicates that the models can successfully learn expressive path patterns for the examined relations. Furthermore, this work demonstrates that the constructed graph allows for the easy integration of heterogeneous information and discovery of indirect connections between biomedical concepts.

Spinal cord injury (SCI) triggers several lipid alterations in nervous tissue. It is characterized by extensive demyelination and the inflammatory response leads to accumulation of activated microglia/macrophages, which often transform into foam cells by accumulation of lipid droplets after engulfment of the damaged myelin sheaths. Using an experimental rat model, Raman microspectroscopy was applied to retrieve the modifications of the lipid distribution following SCI. Coherent anti-Stokes Raman scattering (CARS) and endogenous two-photon fluorescence (TPEF) microscopies were used for the detection of lipid-laden inflammatory cells. The Raman mapping of CH2 deformation mode intensity at 1440 cm−1 retrieved the lipid-depleted injury core. Preserved white matter and inflammatory regions with myelin fragmentation and foam cells were localized by specifically addressing the distribution of esterified lipids, i.e., by mapping the intensity of the carbonyl Raman band at 1743 cm−1, and were in agreement with CARS/TPEF microscopy. Principal component analysis revealed that the inflammatory regions are notably rich in saturated fatty acids. Therefore, Raman spectroscopy enabled to specifically detect inflammation after SCI and myelin degradation products.

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Magnetresonanztomographie (MRT) ist eine nichtinvasive Bildgebungsmethode, die in der Medizin sowie in der Forschung eingesetzt wird und auf der magnetischen Kernresonanz beruht. Die Erforschung der Ultrahochfeld (UHF) MRT ab Magnetfeldstärken von 7.0 Tesla und darüber ist durch einen intrinsischen Signalgewinn hin zu hohen Magnetfeldstärken motiviert und beschäftigt sich mit den dabei auftretenden physikalischen Effekten ebenso wie mit den dazu notwendigen neuartigen Technologien. Die vorliegende Arbeit untersucht Mehrkanalantennen zur Anregung der magnetischen Kernresonanz sowie zum Empfang des resultierenden Signals bei 7.0 T. Für die magnetische Kernresonanz von Protonen ergibt sich eine Resonanzfrequenz von 300 MHz. Die zugehörige Wellenlänge in menschlichem Gewebe verlässt in diesem Frequenzbereich im Verhältnis zu den Körperabmessungen den quasistatischen Bereich. Die sich ergebende Wellenausbreitung hat Interferenzmuster in den erzeugten Bildern zur Folge, die zu klinisch nicht verwertbaren Bildinformationen führen können. Vor diesem Hintergrund wurden in dieser Arbeit Mehrkanalantennen mit 4, 8 und 16 unabhängigen Elementen zur Signalanregung und zum Empfang konzipiert, aufgebaut und untersucht. Die Erkenntnisse mündeten in der erfolgreichen Implementierung der weltweit ersten 32-Kanal Antenne zur kardiovaskulären Bildgebung bei 7.0 T. Darüber hinaus wurde eine Antenne entwickelt, welche die ersten auf der Natriumkonzentration beruhenden bewegten MRT Bilder des menschlichen Herzens bei 7.0 T ermöglichte. Der Zusammenhang zwischen Natriumkonzentration und Zellintegrität ermöglicht direkte und ortsaufgelöste Einblicke in physiologische Prozesse. Die Ergebnisse dieser Arbeit belegen die breite Anwendbarkeit von Mehrkanalantennen in der UHF MRT zur Protonen-und Natriumbildgebung und bilden eine solide technologische Basis für breitere klinische Studien, um die Ultrahochfeld MRT reif für den routinemäßigen Einsatz im Gesundheitswesen zu machen. / Magnetic resonance imaging (MRI) is a non-invasive imaging method based on the effect of nuclear magnetic resonance. It is used in healthcare as well as in research. MRI at magnetic field strengths of 1.5 Tesla and 3 Tesla is well established. The gain in signal-to-noise ratio (SNR) intrinsic to higher magnetic field strength fuels the vigorous research field of Ultrahigh field (UHF) MRI at 7.0 T and above. Nevertheless for MRI based upon proton imaging the wavelength of the transmitted electro-magnetic fields slowly departs from the semi-static regime and reaches the dimension of the transection of the human body at 7.0 T. This gives rise to constructive and destructive interferences that potentially render image quality non-diagnostic for clinical use. Therefore is work proposes the worlds’ first 32 channel antenna array for cardiovascular MRI at 7.0 T. Electro-magnetic field simulations are utilized to study the capabilities of multi-channel RF antenna arrays to mitigate destructive interferences and provided the basis for a workflow towards homogenization of the electromagnetic radio-frequency field. Pre-clinical studies showed the capabilities and limits of translating the SNR gain of UHF MRI into clinical beneficial numbers, namely increased spatial or temporal resolution or scan time shortening. To make further use of the benefits of UHR MRI and to make a step towards first-hand spatial resolved information of biological processes in human tissue sodium imaging of the human heart was enabled with the design of a tailored antenna array. The results were reconstructed into the first movies of the human heart at 7.0 T based on sodium signal. This profound technological basis for radio frequency excitation and reception in UHF MRI can be expected to pave the way for broader clinical studies at 7.0 T with the ultimate goal to improve the quality and the earliness of treatment decisions in future clinical practice.

Description Logics (DLs) belong to a successful family of knowledge representation formalisms with two key assets: formally well-defined semantics which allows to represent knowledge in an unambiguous way and automated reasoning which allows to infer implicit knowledge from the one given explicitly. This thesis investigates various reasoning techniques for tractable DLs in the EL family which have been implemented in the CEL system. It suggests that the use of the lightweight DLs, in which reasoning is tractable, is beneficial for ontology design and maintenance both in terms of expressivity and scalability. The claim is supported by a case study on the renown medical ontology SNOMED CT and extensive empirical evaluation on several large-scale biomedical ontologies.

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As dental caries is one of the most common diseases, the early and noninvasive detection of carious lesions plays an important role in public health care. Optical coherence tomography (OCT) with its ability of depth-resolved, high-resolution, noninvasive, fast imaging has been previously recognized as a promising tool in dentistry. Additionally, polarization sensitive imaging provides quantitative measures on the birefringent tissue properties and can be utilized for imaging dental tissue, especially enamel and dentin. By imaging three exemplary tooth samples ex vivo with proximal white spot, brown spot, and cavity, we show that the combination of polarization sensitive OCT and the degree of polarization uniformity (DOPU) algorithm is a promising approach for the detection of proximal carious lesions due to the depolarization contrast of demineralized tissue. Furthermore, we investigate different sizes of the DOPU evaluation kernel on the resulting contrast and conclude a suitable value for this application. We propose that DOPU provides an easy to interpret image representation and appropriate contrast for possible future screening applications in early caries diagnostics.

Description Logics (DLs) belong to a successful family of knowledge representation formalisms with two key assets: formally well-defined semantics which allows to represent knowledge in an unambiguous way and automated reasoning which allows to infer implicit knowledge from the one given explicitly. This thesis investigates various reasoning techniques for tractable DLs in the EL family which have been implemented in the CEL system. It suggests that the use of the lightweight DLs, in which reasoning is tractable, is beneficial for ontology design and maintenance both in terms of expressivity and scalability. The claim is supported by a case study on the renown medical ontology SNOMED CT and extensive empirical evaluation on several large-scale biomedical ontologies.

No description available.