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A phagocyte-specific Irf8 gene enhancer establishes early conventional dendritic cell commitment
(2011)
Haematopoietic development is a complex process that is strictly hierarchically organized. Here, the phagocyte lineages are a very heterogeneous cell compartment with specialized functions in innate immunity and induction of adaptive immune responses. Their generation from a common precursor must be tightly controlled. Interference within lineage formation programs for example by mutation or change in expression levels of transcription factors (TF) is causative to leukaemia. However, the molecular mechanisms driving specification into distinct phagocytes remain poorly understood. In the present study I identify the transcription factor Interferon Regulatory Factor 8 (IRF8) as the specification factor of dendritic cell (DC) commitment in early phagocyte precursors. Employing an IRF8 reporter mouse, I showed the distinct Irf8 expression in haematopoietic lineage diversification and isolated a novel bone marrow resident progenitor which selectively differentiates into CD8α+ conventional dendritic cells (cDCs) in vivo. This progenitor strictly depends on Irf8 expression to properly establish its transcriptional DC program while suppressing a lineage-inappropriate neutrophile program. Moreover, I demonstrated that Irf8 expression during this cDC commitment-step depends on a newly discovered myeloid-specific cis-enhancer which is controlled by the haematopoietic transcription factors PU.1 and RUNX1. Interference with their binding leads to abrogation of Irf8 expression, subsequently to disturbed cell fate decisions, demonstrating the importance of these factors for proper phagocyte cell development. Collectively, these data delineate a transcriptional program establishing cDC fate choice with IRF8 in its center.
A systems biological approach towards the molecular basis of heterosis in Arabidopsis thaliana
(2011)
Heterosis is defined as the superiority in performance of heterozygous genotypes compared to their corresponding genetically different homozygous parents. This phenomenon is already known since the beginning of the last century and it has been widely used in plant breeding, but the underlying genetic and molecular mechanisms are not well understood. In this work, a systems biological approach based on molecular network structures is proposed to contribute to the understanding of heterosis. Hybrids are likely to contain additional regulatory possibilities compared to their homozygous parents and, therefore, they may be able to correctly respond to a higher number of environmental challenges, which leads to a higher adaptability and, thus, the heterosis phenomenon. In the network hypothesis for heterosis, presented in this work, more regulatory interactions are expected in the molecular networks of the hybrids compared to the homozygous parents. Partial correlations were used to assess this difference in the global interaction structure of regulatory networks between the hybrids and the homozygous genotypes. This network hypothesis for heterosis was tested on metabolite profiles as well as gene expression data of the two parental Arabidopsis thaliana accessions C24 and Col-0 and their reciprocal crosses. These plants are known to show a heterosis effect in their biomass phenotype. The hypothesis was confirmed for mid-parent and best-parent heterosis for either hybrid of our experimental metabolite as well as gene expression data. It was shown that this result is influenced by the used cutoffs during the analyses. Too strict filtering resulted in sets of metabolites and genes for which the network hypothesis for heterosis does not hold true for either hybrid regarding mid-parent as well as best-parent heterosis. In an over-representation analysis, the genes that show the largest heterosis effects according to our network hypothesis were compared to genes of heterotic quantitative trait loci (QTL) regions. Separately for either hybrid regarding mid-parent as well as best-parent heterosis, a significantly larger overlap between the resulting gene lists of the two different approaches towards biomass heterosis was detected than expected by chance. This suggests that each heterotic QTL region contains many genes influencing biomass heterosis in the early development of Arabidopsis thaliana. Furthermore, this integrative analysis led to a confinement and an increased confidence in the group of candidate genes for biomass heterosis in Arabidopsis thaliana identified by both approaches.
This Thesis puts its focus on the physics of neutron stars and its description with methods of numerical relativity. In the first step, a new numerical framework the Whisky2D code will be developed, which solves the relativistic equations of hydrodynamics in axisymmetry. Therefore we consider an improved formulation of the conserved form of these equations. The second part will use the new code to investigate the critical behaviour of two colliding neutron stars. Considering the analogy to phase transitions in statistical physics, we will investigate the evolution of the entropy of the neutron stars during the whole process. A better understanding of the evolution of thermodynamical quantities, like the entropy in critical process, should provide deeper understanding of thermodynamics in relativity. More specifically, we have written the Whisky2D code, which solves the general-relativistic hydrodynamics equations in a flux-conservative form and in cylindrical coordinates. This of course brings in 1/r singular terms, where r is the radial cylindrical coordinate, which must be dealt with appropriately. In the above-referenced works, the flux operator is expanded and the 1/r terms, not containing derivatives, are moved to the right-hand-side of the equation (the source term), so that the left hand side assumes a form identical to the one of the three-dimensional (3D) Cartesian formulation. We call this the standard formulation. Another possibility is not to split the flux operator and to redefine the conserved variables, via a multiplication by r. We call this the new formulation. The new equations are solved with the same methods as in the Cartesian case. From a mathematical point of view, one would not expect differences between the two ways of writing the differential operator, but, of course, a difference is present at the numerical level. Our tests show that the new formulation yields results with a global truncation error which is one or more orders of magnitude smaller than those of alternative and commonly used formulations. The second part of the Thesis uses the new code for investigations of critical phenomena in general relativity. In particular, we consider the head-on-collision of two neutron stars in a region of the parameter space where two final states a new stable neutron star or a black hole, lay close to each other. In 1993, Choptuik considered one-parameter families of solutions, S[P], of the Einstein-Klein-Gordon equations for a massless scalar field in spherical symmetry, such that for every P > P⋆, S[P] contains a black hole and for every P < P⋆, S[P] is a solution not containing singularities. He studied numerically the behavior of S[P] as P → P⋆ and found that the critical solution, S[P⋆], is universal, in the sense that it is approached by all nearly-critical solutions regardless of the particular family of initial data considered. All these phenomena have the common property that, as P approaches P⋆, S[P] approaches a universal solution S[P⋆] and that all the physical quantities of S[P] depend only on |P − P⋆|. The first study of critical phenomena concerning the head-on collision of NSs was carried out by Jin and Suen in 2007. In particular, they considered a series of families of equal-mass NSs, modeled with an ideal-gas EOS, boosted towards each other and varied the mass of the stars, their separation, velocity and the polytropic index in the EOS. In this way they could observe a critical phenomenon of type I near the threshold of black-hole formation, with the putative solution being a nonlinearly oscillating star. In a successive work, they performed similar simulations but considering the head-on collision of Gaussian distributions of matter. Also in this case they found the appearance of type-I critical behaviour, but also performed a perturbative analysis of the initial distributions of matter and of the merged object. Because of the considerable difference found in the eigenfrequencies in the two cases, they concluded that the critical solution does not represent a system near equilibrium and in particular not a perturbed Tolmann-Oppenheimer-Volkoff (TOV) solution. In this Thesis we study the dynamics of the head-on collision of two equal-mass NSs using a setup which is as similar as possible to the one considered above. While we confirm that the merged object exhibits a type-I critical behaviour, we also argue against the conclusion that the critical solution cannot be described in terms of equilibrium solution. Indeed, we show that, in analogy with what is found in, the critical solution is effectively a perturbed unstable solution of the TOV equations. Our analysis also considers fine-structure of the scaling relation of type-I critical phenomena and we show that it exhibits oscillations in a similar way to the one studied in the context of scalar-field critical collapse.
In this work new fluorinated and non-fluorinated mono- and bifunctional trithiocarbonates of the structure Z-C(=S)-S-R and Z-C(=S)-S-R-S-C(=S)-Z were synthesized for the use as chain transfer agents (CTAs) in the RAFT-process. All newly synthesized CTAs were tested for their efficiency to moderate the free radical polymerization process by polymerizing styrene (M3). Besides characterization of the homopolymers by GPC measurements, end- group analysis of the synthesized block copolymers via 1H-, 19F-NMR, and in some cases also UV-vis spectroscopy, were performed attaching suitable fluorinated moieties to the Z- and/or R-groups of the CTAs. Symmetric triblock copolymers of type BAB and non-symmetric fluorine end- capped polymers were accessible using the RAFT process in just two or one polymerization step. In particular, the RAFT-process enabled the controlled polymerization of hydrophilic monomers such as N-isopropylacrylamide (NIPAM) (M1) as well as N-acryloylpyrrolidine (NAP) (M2) for the A-blocks and of the hydrophobic monomers styrene (M3), 2-fluorostyrene (M4), 3-fluorostyrene (M5), 4-fluorostyrene (M6) and 2,3,4,5,6-pentafluorostyrene (M7) for the B-blocks. The properties of the BAB-triblock copolymers were investigated in dilute, concentrated and highly concentrated aqueous solutions using DLS, turbidimetry, 1H- and 19F-NMR, rheology, determination of the CMC, foam height- and surface tension measurements and microscopy. Furthermore, their ability to stabilize emulsions and microemulsions and the wetting behaviour of their aqueous solutions on different substrates was investigated. The behaviour of the fluorine end-functionalized polymers to form micelles was studied applying DLS measurements in diluted organic solution. All investigated BAB-triblock copolymers were able to form micelles and show surface activity at room temperature in dilute aqueous solution. The aqueous solutions displayed moderate foam formation. With different types and concentrations of oils, the formation of emulsions could be detected using a light microscope. A boosting effect in microemulsions could not be found adding BAB-triblock copolymers. At elevated polymer concentrations, the formation of hydrogels was proved applying rheology measurements.
The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches.
Corvino, Corvino and Schoen, Chruściel and Delay have shown the existence of a large class of asymptotically flat vacuum initial data for Einstein's field equations which are static or stationary in a neighborhood of space-like infinity, yet quite general in the interior. The proof relies on some abstract, non-constructive arguments which makes it difficult to calculate such data numerically by using similar arguments. A quasilinear elliptic system of equations is presented of which we expect that it can be used to construct vacuum initial data which are asymptotically flat, time-reflection symmetric, and asymptotic to static data up to a prescribed order at space-like infinity. A perturbation argument is used to show the existence of solutions. It is valid when the order at which the solutions approach staticity is restricted to a certain range. Difficulties appear when trying to improve this result to show the existence of solutions that are asymptotically static at higher order. The problems arise from the lack of surjectivity of a certain operator. Some tensor decompositions in asymptotically flat manifolds exhibit some of the difficulties encountered above. The Helmholtz decomposition, which plays a role in the preparation of initial data for the Maxwell equations, is discussed as a model problem. A method to circumvent the difficulties that arise when fast decay rates are required is discussed. This is done in a way that opens the possibility to perform numerical computations. The insights from the analysis of the Helmholtz decomposition are applied to the York decomposition, which is related to that part of the quasilinear system which gives rise to the difficulties. For this decomposition analogous results are obtained. It turns out, however, that in this case the presence of symmetries of the underlying metric leads to certain complications. The question, whether the results obtained so far can be used again to show by a perturbation argument the existence of vacuum initial data which approach static solutions at infinity at any given order, thus remains open. The answer requires further analysis and perhaps new methods.
Most of the microelectronic circuits fabricated today are synchronous, i.e. they are driven by one or several clock signals. Synchronous circuit design faces several fundamental challenges such as high-speed clock distribution, integration of multiple cores operating at different clock rates, reduction of power consumption and dealing with voltage, temperature, manufacturing and runtime variations. Asynchronous or clockless design plays a key role in alleviating these challenges, however the design and test of asynchronous circuits is much more difficult in comparison to their synchronous counterparts. A driving force for a widespread use of asynchronous technology is the availability of mature EDA (Electronic Design Automation) tools which provide an entire automated design flow starting from an HDL (Hardware Description Language) specification yielding the final circuit layout. Even though there was much progress in developing such EDA tools for asynchronous circuit design during the last two decades, the maturity level as well as the acceptance of them is still not comparable with tools for synchronous circuit design. In particular, logic synthesis (which implies the application of Boolean minimisation techniques) for the entire system's control path can significantly improve the efficiency of the resulting asynchronous implementation, e.g. in terms of chip area and performance. However, logic synthesis, in particular for asynchronous circuits, suffers from complexity problems. Signal Transitions Graphs (STGs) are labelled Petri nets which are a widely used to specify the interface behaviour of speed independent (SI) circuits - a robust subclass of asynchronous circuits. STG decomposition is a promising approach to tackle complexity problems like state space explosion in logic synthesis of SI circuits. The (structural) decomposition of STGs is guided by a partition of the output signals and generates a usually much smaller component STG for each partition member, i.e. a component STG with a much smaller state space than the initial specification. However, decomposition can result in component STGs that in isolation have so-called irreducible CSC conflicts (i.e. these components are not SI synthesisable anymore) even if the specification has none of them. A new approach is presented to avoid such conflicts by introducing internal communication between the components. So far, STG decompositions are guided by the finest output partitions, i.e. one output per component. However, this might not yield optimal circuit implementations. Efficient heuristics are presented to determine coarser partitions leading to improved circuits in terms of chip area. For the new algorithms correctness proofs are given and their implementations are incorporated into the decomposition tool DESIJ. The presented techniques are successfully applied to some benchmarks - including 'real-life' specifications arising in the context of control resynthesis - which delivered promising results.
Business Process Management (BPM) emerged as a means to control, analyse, and optimise business operations. Conceptual models are of central importance for BPM. Most prominently, process models define the behaviour that is performed to achieve a business value. In essence, a process model is a mapping of properties of the original business process to the model, created for a purpose. Different modelling purposes, therefore, result in different models of a business process. Against this background, the misalignment of process models often observed in the field of BPM is no surprise. Even if the same business scenario is considered, models created for strategic decision making differ in content significantly from models created for process automation. Despite their differences, process models that refer to the same business process should be consistent, i.e., free of contradictions. Apparently, there is a trade-off between strictness of a notion of consistency and appropriateness of process models serving different purposes. Existing work on consistency analysis builds upon behaviour equivalences and hierarchical refinements between process models. Hence, these approaches are computationally hard and do not offer the flexibility to gradually relax consistency requirements towards a certain setting. This thesis presents a framework for the analysis of behaviour consistency that takes a fundamentally different approach. As a first step, an alignment between corresponding elements of related process models is constructed. Then, this thesis conducts behavioural analysis grounded on a relational abstraction of the behaviour of a process model, its behavioural profile. Different variants of these profiles are proposed, along with efficient computation techniques for a broad class of process models. Using behavioural profiles, consistency of an alignment between process models is judged by different notions and measures. The consistency measures are also adjusted to assess conformance of process logs that capture the observed execution of a process. Further, this thesis proposes various complementary techniques to support consistency management. It elaborates on how to implement consistent change propagation between process models, addresses the exploration of behavioural commonalities and differences, and proposes a model synthesis for behavioural profiles.
Business process models are used within a range of organizational initiatives, where every stakeholder has a unique perspective on a process and demands the respective model. As a consequence, multiple process models capturing the very same business process coexist. Keeping such models in sync is a challenge within an ever changing business environment: once a process is changed, all its models have to be updated. Due to a large number of models and their complex relations, model maintenance becomes error-prone and expensive. Against this background, business process model abstraction emerged as an operation reducing the number of stored process models and facilitating model management. Business process model abstraction is an operation preserving essential process properties and leaving out insignificant details in order to retain information relevant for a particular purpose. Process model abstraction has been addressed by several researchers. The focus of their studies has been on particular use cases and model transformations supporting these use cases. This thesis systematically approaches the problem of business process model abstraction shaping the outcome into a framework. We investigate the current industry demand in abstraction summarizing it in a catalog of business process model abstraction use cases. The thesis focuses on one prominent use case where the user demands a model with coarse-grained activities and overall process ordering constraints. We develop model transformations that support this use case starting with the transformations based on process model structure analysis. Further, abstraction methods considering the semantics of process model elements are investigated. First, we suggest how semantically related activities can be discovered in process models-a barely researched challenge. The thesis validates the designed abstraction methods against sets of industrial process models and discusses the method implementation aspects. Second, we develop a novel model transformation, which combined with the related activity discovery allows flexible non-hierarchical abstraction. In this way this thesis advocates novel model transformations that facilitate business process model management and provides the foundations for innovative tool support.
The Casimir-Polder interaction between a single neutral atom and a nearby surface, arising from the (quantum and thermal) fluctuations of the electromagnetic field, is a cornerstone of cavity quantum electrodynamics (cQED), and theoretically well established. Recently, Bose-Einstein condensates (BECs) of ultracold atoms have been used to test the predictions of cQED. The purpose of the present thesis is to upgrade single-atom cQED with the many-body theory needed to describe trapped atomic BECs. Tools and methods are developed in a second-quantized picture that treats atom and photon fields on the same footing. We formulate a diagrammatic expansion using correlation functions for both the electromagnetic field and the atomic system. The formalism is applied to investigate, for BECs trapped near surfaces, dispersion interactions of the van der Waals-Casimir-Polder type, and the Bosonic stimulation in spontaneous decay of excited atomic states. We also discuss a phononic Casimir effect, which arises from the quantum fluctuations in an interacting BEC.
Non-mycorrhizal fungal endophytes are able to colonize internally roots without causing visible disease symptoms establishing neutral or mutualistic associations with plants. These fungi known as non-clavicipitaceous endophytes have a broad host range of monocot and eudicot plants and are highly diverse. Some of them promote plant growth and confer increased abiotic-stress tolerance and disease resistance. According to such possible effects on host plants, it was aimed to isolate and to characterize native fungal root endophytes from tomato (Lycopersicon esculentum Mill.) and to analyze their effects on plant development, plant resistance and fruit yield and quality together with the model endophyte Piriformospora indica. Fifty one new fungal strains were isolated from desinfected tomato roots of four different crop sites in Colombia. These isolates were roughly characterized and fourteen potential endophytes were further analyzed concerning their taxonomy, their root colonization capacity and their impact on plant growth. Sequencing of the ITS region from the ribosomal RNA gene cluster and in-depth morphological characterisation revealed that they correspond to different phylogenetic groups among the phylum Ascomycota. Nine different morphotypes were described including six dark septate endophytes (DSE) that did not correspond to the Phialocephala group. Detailed confocal microscopy analysis showed various colonization patterns of the endophytes inside the roots ranging from epidermal penetration to hyphal growth through the cortex. Tomato pot experiments under glass house conditions showed that they differentially affect plant growth depending on colonization time and inoculum concentration. Three new isolates (two unknown fungal endophyte DSE48, DSE49 and one identified as Leptodontidium orchidicola) with neutral or positiv effects were selected and tested in several experiments for their influence on vegetative growth, fruit yield and quality and their ability to diminish the impact of the pathogen Verticillium dahliae on tomato plants. Although plant growth promotion by all three fungi was observed in young plants, vegetative growth parameters were not affected after 22 weeks of cultivation except a reproducible increase of root diameter by the endophyte DSE49. Additionally, L. orchidicola increased biomass and glucose content of tomato fruits, but only at an early date of harvest and at a certain level of root colonization. Concerning bioprotective effects, the endophytes DSE49 and L. orchidicola decreased significantly disease symptoms caused by the pathogen V. dahliae, but only at a low dosis of the pathogen. In order to analyze, if the model root endophytic fungus Piriformospora indica could be suitable for application in production systems, its impact on tomato was evaluated. Similarly to the new fungal isolates, significant differences for vegetative growth parameters were only observable in young plants and, but protection against V. dahliae could be seen in one experiment also at high dosage of the pathogen. As the DSE L. orchidicola, P. indica increased the number and biomass of marketable tomatoes only at the beginning of fruit setting, but this did not lead to a significant higher total yield. If the effects on growth are due to a better nutrition of the plant with mineral element was analyzed in barley in comparison to the arbuscular mycorrhizal fungus Glomus mosseae. While the mycorrhizal fungus increased nitrogen and phosphate uptake of the plant, no such effect was observed for P. indica. In summary this work shows that many different fungal endophytes can be also isolated from roots of crops and, that these isolates can have positive effects on early plant development. This does, however, not lead to an increase in total yield or in improvement of fruit quality of tomatoes under greenhouse conditions.