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Sonstige beteiligte Institutionen
The acquired immunodeficiency syndrome (AIDS) is currently the most infectious disease worldwide. It is caused by the human immunodeficiency virus (HIV). At the moment there are ~33.3 million people infected with HIV. Sub-Saharan Africa, with ~22.5 million people infected accounts for 68% of the global burden. In most African countries antiretroviral therapy (ART) is administered in limited-resource settings with standardised first- and second-line ART regimens. During this study I analysed the therapy-naïve population of Cape Town, South Africa and Mwanza, Tanzania for any resistance associated mutations (RAMs) against protease inhibitors, nucleoside reverse transcriptase inhibitors and non-nucleoside reverse transcriptase inhibitors. My results indicate that HIV-1 subtype C accounts for ~95% of all circulating strains in Cape Town, South Africa. I could show that ~3.6% of the patient derived viruses had RAMs, despite patients being therapy-naïve. In Mwanza, Tanzania the HIV drug resistance (HIVDR) prevalence in the therapy-naïve population was 14.8% and significantly higher in the older population, >25 years. Therefore, the current WHO transmitted HIVDR (tHIVDR) survey that is solely focused on the transmission of HIVDR and that excludes patients over 25 years of age may result in substantial underestimation of the prevalence of HIVDR in the therapy-naïve population. Based on the prevalence rates of tHIVDR in the study populations it is recommended that all HIV-1 positive individuals undergo a genotyping resistance test before starting ART. I also characterized vif sequences from HIV-1 infected patients from Cape Town, South Africa as the Vif protein has been shown to counteract the antiretroviral activity of the cellular APOBEC3G/F cytidine deaminases. There is no selective pressure on the HIV-1 Vif protein from current ART regimens and vif sequences was used as an evolutionary control. As the majority of phenotypic resistance assays are still based on HIV-1 subtype B, I wanted to design an infectious HIV-1 subtype C proviral molecular clone that can be used for in vitro assays based on circulating strains in South Africa. Therefore, I characterized an early primary HIV-1 subtype C isolate from Cape Town, South Africa and created a new infectious subtype C proviral molecular clone (pZAC). The new pZAC virus has a significantly higher transient viral titer after transfection and replication rate than the previously published HIV-1 subtype C virus from Botswana. The optimized proviral molecular clone, pZAC could be used in future cell culture and phenotypic HIV resistance assays regarding HIV-1 subtype C.
The present work reviews the experimental literature on the acute effects of alcohol on human behaviour related to driving performance. A meta-analysis was conducted which includes studies published between 1954 and 2007 in order to provide a comprehensive knowledge of the substance alcohol. 450 studies reporting 5,300 findings were selected from over 12,000 references after applying certain in- and exclusion criteria. Thus, the present meta-analysis comprises far more studies than reviews on alcohol up to now. In the selected studies, different performance tests were conducted which were relevant for driving. The classification system used in this work assigns these tests to eight categories. The main categories consist of several sub categories classifying the tasks more precisely. The main categories were: (1) visual functions, (2) attention (including vigilance), (3) divided attention, (4) en-/decoding (including information processing and memory), (5) reaction time (including simple reaction time and choice reaction time), (6) psychomotor skills, (7) tracking and (8) driving. In addition to the performance aspect, the classification system takes into account mood and social behaviour variables related to driving safety like tiredness or aggression. Following the evaluation method of vote-counting, the number of significant findings and the number of non-significant findings were summarised per blood alcohol concentration (BAC) group. Thereby, a quantitative estimation of the effects of alcohol depending on the BAC was established, the so-called impairment function, which shows the percentage of significantly impaired findings. In order to provide a general overview of alcohol effects on driving-related performance, a global impairment function was established by aggregating all performance findings. The function is nearly linear with about 30% significant findings at a BAC of 0.05% and 50% significant findings at a BAC of 0.08%. In addition, more specific impairment functions considering only the findings of the single behavioural categories were calculated. The results revealed that impairment depends not only on the BAC, but also clearly differs between most of the performance categories. Tracking and driving performance were most affected by alcohol with impairment beginning at very low BACs of 0.02%. Also psychomotor skills were considerably affected by rather low BACs. Impairment of visual functions and information processing occurred at BACs of 0.04% and increased substantially with higher BACs. Impairment in memory tests could be found with very low BACs of 0.02%, but varied depending on the kind of memory. Performance decrements in divided attention tests could also be found with very low BACs in some studies. Attention started to be impaired at 0.04% BAC, but – as in vigilance tasks – considerable impairment only occurred at higher BACs. Choice reaction time was affected at lower BACs than simple reaction time, which was – together with the critical flicker fusion frequency – the least sensitive parameter to the effects of alcohol. To conclude, most skills which are relevant for the safe operation of a vehicle are clearly impaired by BACs of 0.05%, with motor functions being more affected than cognitive functions and complex tasks more than simple tasks. Generally, the results provided no evidence of a threshold effect for alcohol. There was no driving-related performance category for which a sudden transition from unimpaired to impaired occurred at a particular BAC level. In addition, a comparison was made between the present meta-analysis and two reviews of Moskowitz (Moskowitz & Fiorentino, 2000; Moskowitz & Robinson, 1988). Moskowitz reported much lower BACs at which performance was impaired. The reasons for this discrepancy lies in a different way to review scientific findings. On the one hand, Moskowitz focused on significant findings when selecting studies and findings for his reviews. On the other hand, the evaluation method used by Moskowitz ignored non-significant findings and counted each study once at the lowest BAC for which impairment was found. Those non-significant findings are as important as the significant ones in order to determine thresholds of impairment. Therefore, in contrast to Moskowitz, the present work describes the effects of alcohol with functions considering also the non-significant findings. The significance of the non-significant is emphasized with respect to the selection procedure as well as to the evaluation method.
In recent years high-throughput experiments provided a vast amount of data from all areas of molecular biology, including genomics, transcriptomics, proteomics and metabolomics. Its analysis using bioinformatics methods has developed accordingly, towards a systematic approach to understand how genes and their resulting proteins give rise to biological form and function. They interact with each other and with other molecules in highly complex structures, which are explored in network biology. The in-depth knowledge of genes and proteins obtained from high-throughput experiments can be complemented by the architecture of molecular networks to gain a deeper understanding of biological processes. This thesis provides methods and statistical analyses for the integration of molecular data into biological networks and the identification of functional modules, as well as its application to distinct biological data. The integrated network approach is implemented as a software package, termed BioNet, for the statistical language R. The package includes the statistics for the integration of transcriptomic and functional data with biological networks, the scoring of nodes and edges of these networks as well as methods for subnetwork search and visualisation. The exact algorithm is extensively tested in a simulation study and outperforms existing heuristic methods for the calculation of this NP-hard problem in accuracy and robustness. The variability of the resulting solutions is assessed on perturbed data, mimicking random or biased factors that obscure the biological signal, generated for the integrated data and the network. An optimal, robust module can be calculated using a consensus approach, based on a resampling method. It summarizes optimally an ensemble of solutions in a robust consensus module with the estimated variability indicated by confidence values for the nodes and edges. The approach is subsequently applied to two gene expression data sets. The first application analyses gene expression data for acute lymphoblastic leukaemia (ALL) and differences between the subgroups with and without an oncogenic BCR/ABL gene fusion. In a second application gene expression and survival data from diffuse large B-cell lymphomas are examined. The identified modules include and extend already existing gene lists and signatures by further significant genes and their interactions. The most important novelty is that these genes are determined and visualised in the context of their interactions as a functional module and not as a list of independent and unrelated transcripts. In a third application the integrative network approach is used to trace changes in tardigrade metabolism to identify pathways responsible for their extreme resistance to environmental changes and endurance in an inactive tun state. For the first time a metabolic network approach is proposed to detect shifts in metabolic pathways, integrating transcriptome and metabolite data. Concluding, the presented integrated network approach is an adequate technique to unite high-throughput experimental data for single molecules and their intermolecular dependencies. It is flexible to apply on diverse data, ranging from gene expression changes over metabolite abundances to protein modifications in a combination with a suitable molecular network. The exact algorithm is accurate and robust in comparison to heuristic approaches and delivers an optimal, robust solution in form of a consensus module with confidence values. By the integration of diverse sources of information and a simultaneous inspection of a molecular event from different points of view, new and exhaustive insights into biological processes can be acquired.
Computing Generic Causes of Revelation of the Quranic Verses Using Machine Learning Techniques
(2011)
Because many verses of the holy Quran are similar, there is high probability that, similar verses addressing same issues share same generic causes of revelation. In this study, machine learning techniques have been employed in order to automatically derive causes of revelation of Quranic verses. The derivation of the causes of revelation is viewed as a classification problem. Initially the categories are based on the verses with known causes of revelation, and the testing set consists of the remaining verses. Based on a computed threshold value, a naïve Bayesian classifier is used to categorize some verses. After that, using a decision tree classifier the remaining uncategorized verses are separated into verses that contain indicators (resultative connectors, causative expressions…), and those that do not. As for those verses having indicators, each one is segmented into its constituent clauses by identification of the linking indicators. Then a dominant clause is extracted and considered either as the cause of revelation, or post-processed by adding or subtracting some terms to form a causal clause that constitutes the cause of revelation. Concerning remaining unclassified verses without indicators, a naive Bayesian classifier is again used to assign each one of them to one of the existing classes based on features and topics similarity. As for verses that could not be classified so far, manual classification was made by considering each verse as a category on its own. The result obtained in this study is encouraging, and shows that automatic derivation of Quranic verses’ generic causes of revelation is achievable, and reasonably reliable for understanding and implementing the teachings of the Quran.
Type 1 diabetes affects around 0.5% of the population in developed countries and the incidence rates have been rising over the years. The destruction of beta cells is irreversible and the current therapy available to patients only manages the symptoms and does not prevent the associated pathological manifestations. The patients need lifelong therapy and intensive research is being carried out to identify ways to eliminate autoimmune responses directed against pancreatic beta cells and to replace or regenerate beta cells. The work presented herein aimed at analyzing the role of the Th17 T cell subset, characterized by secretion of the pro- inflammatory cytokine IL-17A, in autoimmune diabetes and also at generating a beta cell reporter mouse line in the NOD background, the most widely- used mouse model for type 1 diabetes. We generated IL- 17A knockdown (KD) NOD mice, using RNAi in combination with lentiviral transgenesis. We analyzed diabetes frequency in IL-17A deficient mice and found that the loss of IL-17A did not protect the transgenic mice from diabetes. Based on these observations, we believe that Th17 cells do not play a critical role in type 1 diabetes through the IL-17A pathway, though they might still be involved in the disease process through alternate pathways. We also generated NOD and NOD-SCID mice with a transgene that drives the beta cell specific expression of a luciferase reporter gene. We used a lentiviral construct, which combined a luciferase sequence and a short- hairpin RNA (shRNA) expression cassette, allowing gene- knockdown under the beta cell specific rat insulin promoter (RIP). These mice will be of use in studying beta cell phenotypes resulting from the knockdown of target genes, using non- invasive bioimaging. We believe that the generation of these reporter mouse lines for diabetes studies will prove valuable in future investigations. Furthermore, the demonstration that the loss of IL-17A does not alter susceptibility to type 1 diabetes should help clarify the controversial involvement of Th17 cells in this disease.
Learning a book in general involves reading it, underlining important words, adding comments, summarizing some passages, and marking up some text or concepts. Once deeper understanding is achieved, one would like to organize and manage her/his knowledge in such a way that, it could be easily remembered and efficiently transmitted to others. This paper discusses about modeling religious texts using semantic XML markup based on frame-based knowledge representation, with the purpose of assisting understanding, retention, and sharing of knowledge they contain. In this study, books organized in terms of chapters made up of verses are considered as the source of knowledge to model. Some metadata representing the multiple perspectives of knowledge modeling are assigned to each chapter and verse. Chapters and verses with their metadata form a meta-model, which is represented using frames, and published on a web mashup. An XML-based annotation and visualization system equipped with user interfaces for creating static and dynamic metadata, annotating chapters’ contents according to user selected semantics, and templates for publishing generated knowledge on the Internet, has been developed. The system has been applied to the Quran, and the result obtained shows that multiple perspectives of information modeling can be successfully applied to religious texts, in order to support analysis, understanding, and retention of the texts.
Given a collection of diverging documents about some lost original text, any person interested in the text would try reconstructing it from the diverging documents. Whether it is eclecticism, stemmatics, or copy-text, one is expected to explicitly or indirectly select one of the documents as a starting point or as a base text, which could be emended through comparison with remaining documents, so that a text that could be designated as the original document is generated. Unfortunately the process of giving priority to one of the documents also known as witnesses is a subjective approach. In fact even Cladistics, which could be considered as a computer-based approach of implementing stemmatics, does not present or recommend users to select a certain witness as a starting point for the process of reconstructing the original document. In this study, a computational method using a rule-based Bayesian classifier is used, to assist text scholars in their attempts of reconstructing a non-existing document from some available witnesses. The method developed in this study consists of selecting a base text successively and collating it with remaining documents. Each completed collation cycle stores the selected base text and its closest witness, along with a weighted score of their similarities and differences. At the end of the collation process, a witness selected more often by majority of base texts is considered as the probable base text of the collection. Witnesses’ scores are weighted using a weighting system, based on effects of types of textual modifications on the process of reconstructing original documents. Users have the possibility to select between baseless and base text collation. If a base text is selected, the task is reduced to ranking the witnesses with respect to the base text, otherwise a base text as well as ranking of the witnesses with respect to the base text are computed and displayed on a bar diagram. Additionally this study includes a recursive algorithm for automatically reconstructing the original text from the identified base text and ranked witnesses.
The question of why the Quran structure does not follow its chronology of revelation is a recurring one. Some Islamic scholars such as [1] have answered the question using hadiths, as well as other philosophical reasons based on internal evidences of the Quran itself. Unfortunately till today many are still wondering about this issue. Muslims believe that the Quran is a summary and a copy of the content of a preserved tablet called Lawhul-Mahfuz located in the heaven. Logically speaking, this suggests that the arrangement of the verses and chapters is expected to be similar to that of the Lawhul-Mahfuz. As for the arrangement of the verses in each chapter, there is unanimity that it was carried out by the Prophet himself under the guidance of Angel Gabriel with the recommendation of God. But concerning the ordering of the chapters, there are reports about some divergences [3] among the Prophet’s companions as to which chapter should precede which one. This paper argues that Quranic chapters might have been arranged according to months and seasons of revelation. In fact, based on some verses of the Quran, it is defendable that the Lawhul-Mahfuz itself is understood to have been structured in terms of the months of the year. In this study, philosophical and mathematical arguments for computing chapters’ months of revelation are discussed, and the result is displayed on an interactive scatter plot.
Bees are subject to permanent threat from predators such as ants. Their nests with large quantities of brood, pollen and honey represent lucrative targets for attacks whereas foragers have to face rivalry at food sources. This thesis focused on the role of stingless bees as third party interactor on ant-aphid-associations as well as on the predatory potential represented by ants and defense mechanisms against this threat. Regular observations of an aphid infested Podocarpus for approaching stingless bees yielded no results. Another aim of this thesis was the observation of foraging habits of four native and one introduced ant species for assessment of their predatory potential to stingless bees. All species turned out to be dietary balanced generalists with one mostly carnivorous species and four species predominantly collecting nectar roughly according to optimal foraging theory. Two of the species monitored, Rhytidoponera metallica and Iridomyrmex rufoniger were considered potential nest robbers. As the name implies, stingless bees lack the powerful weapon of their distant relatives; hence they specialized on other defense strategies. Resin is an important, multipurpose resource for stingless bees that is used as material for nest construction, antibiotic and for defensive means. For the latter purpose highly viscous resin is either directly used to stick down aggressors or its terpenic compounds are included in the bees cuticular surface. In a feeding choice experiment, three ant species were confronted with the choice between two native bee species - Tetragonula carbonaria and Austroplebeia australis - with different cuticular profiles and resin collection habits. Two of the ant species, especially the introduced Tetramorium bicarinatum did not show any preferences. The carnivorous R. metallica predominantly took the less resinous A. australis as prey. The reluctance towards T. carbonaria disappeared when the resinous compounds on its cuticle had been washed off with hexane. To test whether the repulsive reactions were related to the stickiness of the resinous surface or to chemical substances, hexane extracts of bees’ cuticles, propolis and three natural tree resins were prepared. In the following assay responses of ants towards extract treated surfaces were observed. Except for one of the resin extracts, all tested substances had repellent effects to the ants. Efficacy varied with the type of extract and species. Especially to the introduced T. bicarinatum the cuticular extract had no effect. GCMS-analyses showed that some of the resinous compounds were also found in the cuticular profile of T. carbonaria which featured reasonable analogies to the resin of Corymbia torelliana that is highly attractive for stingless bees. The results showed that repellent effects were only partially related to the sticky quality of resin but were rather caused by chemical substances, presumably sesqui- and diterpenes. Despite its efficacy this defense strategy only provides short time repellent effects sufficient for escape and warning of nest mates to initiate further preventive measures.
Since the discovery of spin torque in 1996, independently by Berger and Slonczewski, and given its potential impact on information storage and communication technologies, (e.g. through the possibility of switching the magnetic configuration of a bit by current instead of a magnetic field, or the realization of high frequency spin torque oscillators (STO), this effect has been an important field of spintronics research. One aspect of this research focuses on ferromagnets with low damping. The lower the damping in a ferromagnet, the lower the critical current that is needed to induce switching of a spin valve or induce precession of its magnetization. In this thesis ferromagnetic resonance (FMR) studies of NiMnSb layers are presented along with experimental studies on various spin-torque (ST) devices using NiMnSb. NiMnSb, when crystallized in the half-Heusler structure, is a half-metal which is predicted to have 100% spin polarization, a consideration which further increases its potential as a candidate for memory devices based on the giant magnetoresistance (GMR) effect. The FMR measurements show an outstandingly low damping factor for NiMnSb, in low 10-3 range. This is about a factor of two lower than permalloy and well comparable to lowest damping for iron grown by molecular beam epitaxy (MBE). According to theory the 100% spin polarization properties of the bulk disappear at interfaces where the break in translational symmetry causes the gap in the minority spin band to collapse but can remain in other crystal symmetries such as (111). Consequently NiMnSb layers on (111)(In,Ga)As buffer are characterized in respect of anisotropies and damping. The FMR measurements on these samples indicates a higher damping that for the 001 samples, and a thickness dependent uniaxial in-plane anisotropy. Investigations of the material for device use is pursued by considering sub-micrometer sized elements of NiMnSb on 001 substrates, which were fabricated by electron-beam lithography and measured by ferromagnetic resonance. The damping remains in the low 10-3 range as determined directly by extracting the Gilbert damping from the line width. Additionally magnetostatic modes are observed in arrays of elements, which is further evidence of high material quality of the samples. By sputtering various metals on top of the NiMnSb, spin pumping from the ferromagnet into the non-magnetic layer is investigated. After these material investigations, pseudo-spin-valves using NiMnSb as one of the ferromagnet, in combination with Permalloy were fabricating using a self-aligned lithography process. These samples show a GMR ratio of 3.4% at room temperature and almost double at low temperature, comparing favourably to the best single stack GMR structures reported to date. Moreover, current induced switching measurements show promisingly low current densities are necessary to change the magnetic orientation of the free layer. These current densities compete with state-of-the-art GMR devices for metal based structures and almost with tunnel junction devices. The true potential of these devices however comes to light when they are operated as spin torque oscillators to emit high frequency, tunable, narrow spectrum electromagnetic waves. These Heusler based STOs show an outstanding q-factor of 4180, even when operating in the absence of an external field, a value which bests the highest value in the literature by more than an order of magnitude. While these devices currently still suffer from the same limited output power as all STO reported to date, their sub-micron lateral dimensions make the fabrication of an on-chip array of coupled oscillators, which is a promising path forward towards industrially relevant output power.
According to a changing environment it is crucial for animals to make experience and learn about it. Sensing, integrating and learning to associate different kinds of modalities enables animals to expect future events and to adjust behavior in the way, expected as the most profitable. Complex processes as memory formation and storage make it necessary to investigate learning and memory on different levels. In this context Drosophila melanogaster represents a powerful model organism. As the adult brain of the fly is still quite complex, I chose the third instar larva as model - the more simple the system, the easier to isolate single, fundamental principles of learning. In this thesis I addressed several kinds of questions on different mechanism of olfactory associative and synaptic plasiticity in Drosophila larvae. I focused on short-term memory throughout my thesis. First, investigating larval learning on behavioral level, I developed a one-odor paradigm for olfactory associative conditioning. This enables to estimate the learnability of single odors, reduces the complexity of the task and simplify analyses of "learning mutants". It further allows to balance learnability of odors for generalization-type experiments to describe the olfactory "coding space". Furthermore I could show that innate attractiveness and learnability can be dissociated and found finally that paired presentation of a given odor with reward increase performance, whereas unpaired presentations of these two stimuli decrease performance, indicating that larva are able to learn about the presence as well as about the absence of a reward. Second, on behavioral level, together with Thomas Niewalda and colleagues we focussed on salt processing in the context of choice, feeding and learning. Salt is required in several physiological processes, but can neither be synthesized nor stored. Various salt concentrations shift the valence from attraction to repulsion in reflexive behaviour. Interestingly, the reinforcing effect of salt in learning is shifted by more than one order of magnitude toward higher concentrations. Thus, the input pathways for gustatory behavior appear to be more sensitive than the ones supporting gustatory reinforcement, which is may be due to the dissociation of the reflexive and the reinforcing signalling pathways of salt. Third, in cooperation with Michael Schleyer we performed a series of behavioral gustatory, olfactory preference tests and larval learning experiments. Based on the available neuroanatomical and behavioral data we propose a model regarding chemosensory processing, odor-tastant memory trace formation and the 'decision' like process. It incorporates putative sites of interaction between olfactory and gustatory pathways during the establishment as well as behavioral expression of odor-tastant memory. We claim that innate olfactory behavior is responsive in nature and suggest that associative conditioned behavior is not a simple substitution like process, but driven more likely by the expectation of its outcome. Fourth, together with Birgit Michels and colleagues we investigated the cellular site and molecular mode of Synapsin, an evolutionarily conserved, presynaptic vesicular phosphoprotein and its action in larval learning. We confirmed a previously described learning impairment upon loss of Synapsin. We localized this Synapsin dependent memory trace in the mushroom bodies, a third-order "cortical" brain region, and could further show on molecular level, that Synapsin is as a downstream element of the AC-cAMP-PKA signalling cascade. This study provides a comprehensive chain of explanation from the molecular level to an associative behavioral change. Fifth, in the main part of my thesis I focused on molecular level on another synaptic protein, the Synapse associated protein of 47kDa (Sap47) and its role in larval behavior. As a member of a phylogenetically conserved gene family of hitherto unknown function. It is localized throughout the whole neuropil of larval brains and associated with presynaptic vesicles. Upon loss of Sap47 larvae exhibit normal sensory detection of the to-be-associated stimuli as well as normal motor performance and basic synaptic transmission. Interestingly, short-term plasticity is distorted and odorant–tastant associative learning ability is reduced. This defect in associative function could be rescued by restoring Sap47 expression. Therefore, this report is the first to suggest a function for Sap47 and specifically argues that Sap47 is required for synaptic as well as for behavioral plasticity in Drosophila larva. This prompts the question whether its homologs are required for synaptic and behavioral plasticity also in other species. Further in the last part of my thesis I contributed to the study of Ayse Yarali. Her central topic was the role of the White protein in punishment and relief learning in adult flies. Whereas stimuli that precede shock during training are subsequently avoided as predictors for punishment, stimuli that follow shock during training are later on approached, as they predict relief. Concerning the loss of White we report that pain-relief learning as well as punishment learning is changed. My contribution was a comparison between wild type and the white1118 mutant larvae in odor-reward learning. It turned out that a loss of White has no effect on larval odorant-tastant learning. This study, regarding painrelief learning provides the very first hints concerning the genetic determinants of this form of learning.
Epimutations in Germ-Cell and Embryo Development: Possible Consequences for Assisted Reproduction
(2011)
Assisted reproductive technologies (ART) emerged in the late 1970’s as a therapy for human infertility. Up till now more than 3 million babies have been conceived through ART, demonstrating the safety and efficiency of the technique. Published reports showed an increase in the rate of imprinting disorders (Beckwith Wiedemann Syndrome, Angelman Syndrome, etc.) in babies born after ART. What are the effects imposed through ART and should researchers reassess its safety and implications on the future offspring? Throughout this thesis, I analyzed the methylation patterns of germ cells and embryos to determine whether in vitro maturation and in vitro fertilization have a negative impact on the epigenetic patterns. Furthermore, DNA methylation was compared between sperm of infertile and presumably fertile controls in order to understand whether epigenetic disturbances lead to infertility at the first place. The occurrence of methylation aberrations in germ cells of infertile patients could be transmitted to new-borns and then cause epigenetic disorders. In order to elucidate the imprinting status within single cells, I developed a new technique based on limiting dilution where bisulfite treated DNA is distributed across several wells before amplification. This allowed methylation measurement at the single allele level as well parent of origin detection. In a total of 141 sperm samples from couples undergoing in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) including 106 with male factor or combined infertility and 28 with female infertility, I detected a significant correlation between lower quality of semen parameters (sperm count, percentage of abnormal sperm, and percentage of motile sperm) and the rate of imprinting errors. ALU repeats displayed a higher methylation in sperm DNA of patients leading to a pregnancy and live birth, compared to patients in which pregnancy was not achieved or a spontaneous abortion occurred. A discriminant analysis based on ALU methylation allowed correct classification of >70% of cases. Preliminary data from illumina methylation arrays where more than 27,000 CpGs were analyzed determined that only a single CpG site from the open reading frame C14orf93 was significantly different between the infertile and presumably fertile control group. However, further improvements on data normalization might permit detection of other differentially methylated regions. Comparison of embryos after natural conception, in vitro fertilized embryos from superovulated oocytes, and embryos achieved through fertilization of in vitro cultured oocytes revealed no dramatic effect on the imprinting patterns of Igf2r, H19, and Snrpn. Oocyte cryotop vitrification did not result in a dramatic increase of imprinting mutations in oocytes even though the rate of sporadic methylation errors in single Snrpn CpGs were higher within the in-vitrified group. Collectively, the results I will present within this thesis suggest an increase in the rate of imprinting errors within the germ cells of infertile patients, in addition to a decrease in genome wide methylation of ALU repetitive elements. I did not observe a detrimental effect on the methylation patterns of oocytes and the resulting embryos using in vitro maturation of oocytes and/or standard IVF with in vivo grown superovulated oocytes.
The present work investigated the neural mechanisms underlying cognitive inhibition/thought suppression in Anderson’s and Green’s Think/No-Think paradigm (TNT), as well as different variables influencing these mechanisms at the cognitive, the neurophysiological, the electrophysiological and the molecular level. Neurophysiological data collected with fNIRS and fMRI have added up to the existing evidence of a fronto-hippocampal network interacting during the inhibition of unwanted thoughts. Some evidence has been presented suggesting that by means of external stimulation of the right dlPFC through iTBS thought suppression might be improved, providing further evidence for an implication of this region in the TNT. A combination of fNIRS with ERP has delivered evidence of a dissociation of early condition-independent attentional and later suppression-specific processes within the dlPFC, both contributing to suppression performance. Due to inconsistencies in the previous literature it was considered how stimulus valence would influence thought suppression by manipulating the emotional content of the to-be-suppressed stimuli. Findings of the current work regarding the ability to suppress negative word or picture stimuli have, however, been inconclusive as well. It has been hypothesized that performance in the TNT might depend on the combination of valence conditions included in the paradigm. Alternatively, it has been suggested that inconsistent findings regarding the suppression of negative stimuli or suppression at all might be due to certain personality traits and/or genetic variables, found in the present work to contribute to thought inhibition in the TNT. Rumination has been shown to be a valid predictor of thought suppression performance. Increased ruminative tendencies led to worse suppression performance which, in the present work, has been linked to less effective recruitment of the dlPFC and in turn less effective down-regulation of hippocampal activity during suppression trials. Trait anxiety has also been shown to interrupt thought suppression despite higher, however, inefficient recruitment of the dlPFC. Complementing the findings regarding ruminative tendencies and decreased thought inhibition a functional polymorphism in the KCNJ6 gene, encompassing a G-to-A transition, has been shown to disrupt thought suppression despite increased activation of the dlPFC. Through the investigation of thought suppression at different levels, the current work adds further evidence to the idea that the TNT reflects an executive control mechanism, which is sensitive to alterations in stimulus valence to some extent, neurophysiological functioning as indicated by its sensitivity to iTBS, functional modulations at the molecular level and personality traits, such as rumination and trait anxiety.
In this thesis a systematic analysis of the correlation effects between lattice dynamics and magnetism in the Multiferroic Manganites RMnO3 with Pnma structure was conducted. For this task, Raman and FT-IR Spectroscopy were employed for an investigation of all optically accessible lattice vibrations, i.e. phonons. To study the correlation effects as well as their specific connections to symmetry and compositional properties of the Multiferroic Manganites, the polarisation and temperature dependence of the phonons were considered explicitly. In combination with lattice dynamical calculations based on Density Functional Theory, two coupling effects - Spin-Phonon Coupling and Electromagnon-Phonon Coupling - were systematically analysed.
Honeybees (Apis mellifera) forage on a great variety of plant species, navigate over large distances to crucial resources, and return to communicate the locations of food sources and potential new nest sites to nest mates using a symbolic dance language. In order to achieve this, honeybees have evolved a rich repertoire of adaptive behaviours, some of which were earlier believed to be restricted to vertebrates. In this thesis, I explore the mechanisms involved in honeybee learning, memory, numerical competence and navigation. The findings acquired in this thesis show that honeybees are not the simple reflex automats they were once believed to be. The level of sophistication I found in the bees’ memory, their learning ability, their time sense, their numerical competence and their navigational abilities are surprisingly similar to the results obtained in comparable experiments with vertebrates. Thus, we should reconsider the notion that a bigger brain automatically indicates higher intelligence.
Attention-deficit/hyperactivity disorder (ADHD) is a genetically complex childhood onset neurodevelopmental disorder which is highly persistent into adulthood. Several chromo-somal regions associated with this disorder were identified previously in genome-wide linkage scans, association (GWA) and copy number variation (CNV) studies. In this work the results of case-control and family-based association studies using a can-didate gene approach are presented. For this purpose, possible candidate genes for ADHD have been finemapped using mass array-based SNP genotyping. The genes KCNIP4, CDH13 and DIRAS2 have been found to be associated with ADHD and, in addition, with cluster B and cluster C personality disorders (PD) which are known to be related to ADHD. Most of the associations found in this work would not withstand correction for multiple testing. However, a replication in several independent populations has been achieved and in conjunction with previous evidence from linkage, GWA and CNV studies, it is assumed that there are true associations between those genes and ADHD. Further investigation of DIRAS2 by quantitative real-time PCR (qPCR) revealed expression in the hippocampus, cerebral cortex and cerebellum of the human brain and a significant increase in Diras2 expression in the mouse brain during early development. In situ hybrid-izations on murine brain slices confirmed the results gained by qPCR in the human brain. Moreover, Diras2 is expressed in the basolateral amygdala, structures of the olfactory system and several other brain regions which have been implicated in the psychopatholo-gy of ADHD. In conclusion, the results of this work provide further support to the existence of a strong genetic component in the pathophysiology of ADHD and related disorders. KCNIP4, CDH13 and DIRAS2 are promising candidates and need to be further examined to get more knowledge about the neurobiological basis of this common disease. This knowledge is essential for understanding the molecular mechanisms underlying the emergence of this disorder and for the development of new treatment strategies.
During the last decades the standard model of particle physics has evolved to one of the most precise theories in physics, describing the properties and interactions of fundamental particles in various experiments with a high accuracy. However it lacks on some shortcomings from experimental as well as from theoretical point of view: There is no approved mechanism for the generation of masses of the fundamental particles, in particular also not for the light, but massive neutrinos. In addition the standard model does not provide an explanation for the observance of dark matter in the universe. Moreover the gauge couplings of the three forces in the standard model do not unify, implying that a fundamental theory combining all forces can not be formulated. Within this thesis we address supersymmetric models as answers to these various questions, but instead of focusing on the most simple supersymmetrization of the standard model, we consider basic extensions, namely the next-to-minimal supersymmetric standard model (NMSSM), which contains an additional singlet field, and R-parity violating models. R-parity is a discrete symmetry introduced to guarantee the stability of the proton. Using lepton number violating terms in the context of bilinear R-parity violation and the munuSSM we are able to explain neutrino physics intrinsically supersymmetric, since those terms induce a mixing between the neutralinos and the neutrinos. Since 2009 the Large Hadron Collider (LHC) at CERN explores the new energy regime of Tera-electronvolt, allowing the production of potentially existing heavy particles by the collision of protons. Thus the near future might provide answers to the open questions of mass generation in the standard model and show hints towards physics beyond the standard model. Therefore this thesis works out the phenomenology of the supersymmetric models under consideration and tries to point out differences to the well-known features of the simplest supersymmetric realization of the standard model. In case of the R-parity violating models the decays of the light neutralinos can result in displaced vertices. In combination with a light singlet state these displaced vertices might offer a rich phenomenology like non-standard Higgs decays into a pair of singlinos decaying with displaced vertices. Within this thesis we present some calculations at next order of perturbation theory, since one-loop corrections provide possibly large contributions to the tree-level masses and decay widths. We are using an on-shell renormalization scheme to calculate the masses of neutralinos and charginos including the neutrinos and leptons in case of the R-parity violating models at one-loop level. The discussion shows the similarities and differences to existing calculations in another renormalization scheme, namely the DRbar scheme. Moreover we consider two-body decays of the form chi_j^0 -> chi_l^\pm W^\mp involving a heavy gauge boson in the final state at one-loop level. Corrections are found to be large in case of small or vanishing tree-level decay widths and also for the R-parity violating decay of the lightest neutralino chi_1^0 -> l^\pm W^\mp. An interesting feature of the models based on bilinear R-parity violation is the correlation between the branching ratios of the lightest neutralino decays and the neutrino mixing angles. We discuss these relations at tree-level and for two-body decays chi_1^0 -> l^\pm W^\mp also at one-loop level, since only the full one-loop corrections result in the tree-level expected behavior. The appendix describes the two programs MaCoR and CNNDecays being developed for the analysis carried out in this thesis. MaCoR allows for the calculation of mass matrices and couplings in the models under consideration and CNNDecays is used for the one-loop calculations of neutralino and chargino mass matrices and the two-body decay widths.
Indirect Search for Dark Matter in the Universe - the Multiwavelength and Multiobject Approach
(2011)
Cold dark matter constitutes a basic tenet of modern cosmology, essential for our understanding of structure formation in the Universe. Since its first discovery by means of spectroscopic observations of the dynamics of the Coma cluster some 80 years ago, mounting evidence of its gravitational pull and its impact on the geometry of space-time has build up across a wide range of scales, from galaxies to the entire Hubble flow. The apparent lack of electromagnetic coupling and independent measurements of the energy density of baryonic matter from the primordial abundances of light elements show the non-baryonic nature of dark matter, and its clustering properties prove that it is cold, i.e. that it has a temperature lower than its mass during the time of radiation-matter equality. A generic particle candidate for cold dark matter are weakly interacting massive particles at the electroweak symmetry-breaking scale, such as the neutralinos in R-parity conserving supersymmetry. Such particles would naturally freeze-out with a cosmologically relevant relic density at early times in the expanding Universe. Subsequent clustering of matter would recover annihilation interactions between the dark matter particles to some extent and thus lead to potentially observable high-energy emission from the decaying unstable secondaries produced in annihilation events. The spectra of the secondaries would permit a determination of the mass and annihilation cross section, which are crucial for the microphysical identification of the dark matter. This the central motivation for indirect dark matter searches. However, presently neither the indirect searches, nor the complementary direct searches based on the detection of elastic scattering events, nor the production of candidate particles in collider experiments, has yet provided unequivocal evidence for dark matter. This does not come as a surprise, since the dark matter particles interact only through weak interactions and therefore the corresponding secondary emission must be extremely faint. It turns out that even for the strongest mass concentrations in the Universe, the dark matter annihilation signal is expected to not exceed the level of competing astrophysical sources. Thus, the discrimination of the putative dark matter annihilation signal from the signals of the astrophysical inventory has become crucial for indirect search strategies. In this thesis, a novel search strategy will be developed and exemplified in which target selection across a wide range of masses, astrophysical background estimation, and multiwavelength signatures play the key role. It turns out that the uncertainties regarding the halo profile and the boost due to surviving substructure are bigger for halos at the lower end of the observed mass scales, i.e. in the regime of dwarf galaxies and below, while astrophysical backgrounds tend to become more severe for massive dark matter halos such as clusters of galaxies. By contrast, the uncertainties due to unknown details of particle physics are invariant under changes of the halo mass. Therefore, the different scaling behaviors can be employed to significantly cut down on the uncertainties in observations of different targets covering a major part of the involved mass scales. This strategical approach was implemented in the scientific program carried out with the MAGIC telescope system. Observations of dwarf galaxies and the Virgo- and Perseus clusters of galaxies have been carried out and, at the time of writing, result in some of the most stringent constraints on weakly interacting massive particles from indirect searches. Here, the low-threshold design of the MAGIC telescope system plays a crucial role, since the bulk of the high-energy photons, produced with a high multiplicity during the fragmentation of unstable dark matter annihilation products, are emitted at energies well below the dark matter mass scale. The upper limits severely constrain less generic, but more prolific scenarios characterized by extraordinarily high annihilation efficiencies.
The subject of this thesis are mathematical programs with complementarity conditions (MPCC). At first, an economic example of this problem class is analyzed, the problem of effort maximization in asymmetric n-person contest games. While an analytical solution for this special problem could be derived, this is not possible in general for MPCCs. Therefore, optimality conditions which might be used for numerical approaches where considered next. More precisely, a Fritz-John result for MPCCs with stronger properties than those known so far was derived together with some new constraint qualifications and subsequently used to prove an exact penalty result. Finally, to solve MPCCs numerically, the so called relaxation approach was used. Besides improving the results for existing relaxation methods, a new relaxation with strong convergence properties was suggested and a numerical comparison of all methods based on the MacMPEC collection conducted.
The charge transport in disordered organic bulk heterojunction (BHJ) solar cells is a crucial process affecting the power conversion efficiency (PCE) of the solar cell. With the need of synthesizing new materials for improving the power conversion efficiency of those cells it is important to study not only the photophysical but also the electrical properties of the new material classes. Thereby, the experimental techniques need to be applicable to operating solar cells. In this work, the conventional methods of transient photoconductivity (also known as "Time-of-Flight" (TOF)), as well as the transient charge extraction technique of "Charge Carrier Extraction by Linearly Increasing Voltage" (CELIV) are performed on different organic blend compositions. Especially with the latter it is feasible to study the dynamics, i.e. charge transport and charge carrier recombination, in bulk heterojunction (BHJ) solar cells with active layer thicknesses of 100-200 nm. For a well performing organic BHJ solar cells the morphology is the most crucial parameter finding a trade-off between an efficient photogeneration of charge carriers and the transport of the latter to the electrodes. Besides the morphology, the nature of energetic disorder of the active material blend and its influence on the dynamics are discussed extensively in this work. Thereby, the material system of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61 butyric acid methyl ester (PC61BM) serves mainly as a reference material system. New promising donor or acceptor materials and their potential for application in organic photovoltaics are studied in view of charge dynamics and compared with the reference system. With the need for commercialization of organic solar cells the question of the impact of environmental conditions on the PCE of the solar cells raises. In this work, organic BHJ solar cells exposed to synthetic air for finite duration are studied in view of the charge carrier transport and recombination dynamics. Finally, within the framework of this work the technique of photo-CELIV is improved. With the modified technique it is now feasible to study the mobility and lifetime of charge carriers in organic solar cells under operating conditions.