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ResearcherID
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Poly(A)-binding proteins (PABPs) regulate mRNA fate by controlling stability and translation through interactions with both the poly(A) tail and eIF4F complex. Many organisms have several paralogs of PABPs and eIF4F complex components and it is likely that different eIF4F/PABP complex combinations regulate distinct sets of mRNAs. Trypanosomes have five eIF4G paralogs, six of eIF4E and two PABPs, PABP1 and PABP2. Under starvation, polysomes dissociate and the majority of mRNAs, most translation initiation factors and PABP2 reversibly localise to starvation stress granules. To understand this more broadly we identified a protein interaction cohort for both T. brucei PABPs by cryo-mill/affinity purification-mass spectrometry. PABP1 very specifically interacts with the previously identified interactors eIF4E4 and eIF4G3 and few others. In contrast PABP2 is promiscuous, with a larger set of interactors including most translation initiation factors and most prominently eIF4G1, with its two partners TbG1-IP and TbG1-IP2. Only RBP23 was specific to PABP1, whilst 14 RNA-binding proteins were exclusively immunoprecipitated with PABP2. Significantly, PABP1 and associated proteins are largely excluded from starvation stress granules, but PABP2 and most interactors translocate to granules on starvation. We suggest that PABP1 regulates a small subpopulation of mainly small-sized mRNAs, as it interacts with a small and distinct set of proteins unable to enter the dominant pathway into starvation stress granules and localises preferentially to a subfraction of small polysomes. By contrast PABP2 likely regulates bulk mRNA translation, as it interacts with a wide range of proteins, enters stress granules and distributes over the full range of polysomes.
Semantic Fusion for Natural Multimodal Interfaces using Concurrent Augmented Transition Networks
(2018)
Semantic fusion is a central requirement of many multimodal interfaces. Procedural methods like finite-state transducers and augmented transition networks have proven to be beneficial to implement semantic fusion. They are compliant with rapid development cycles that are common for the development of user interfaces, in contrast to machine-learning approaches that require time-costly training and optimization. We identify seven fundamental requirements for the implementation of semantic fusion: Action derivation, continuous feedback, context-sensitivity, temporal relation support, access to the interaction context, as well as the support of chronologically unsorted and probabilistic input. A subsequent analysis reveals, however, that there is currently no solution for fulfilling the latter two requirements. As the main contribution of this article, we thus present the Concurrent Cursor concept to compensate these shortcomings. In addition, we showcase a reference implementation, the Concurrent Augmented Transition Network (cATN), that validates the concept’s feasibility in a series of proof of concept demonstrations as well as through a comparative benchmark. The cATN fulfills all identified requirements and fills the lack amongst previous solutions. It supports the rapid prototyping of multimodal interfaces by means of five concrete traits: Its declarative nature, the recursiveness of the underlying transition network, the network abstraction constructs of its description language, the utilized semantic queries, and an abstraction layer for lexical information. Our reference implementation was and is used in various student projects, theses, as well as master-level courses. It is openly available and showcases that non-experts can effectively implement multimodal interfaces, even for non-trivial applications in mixed and virtual reality.
Forest biodiversity conservation requires precise, area-wide information on the abundance and distribution of key habitat structures at multiple spatial scales. We combined airborne laser scanning (ALS) data with color-infrared (CIR) aerial imagery for identifying individual tree characteristics and quantifying multi-scale habitat requirements using the example of the three-toed woodpecker (Picoides tridactylus) (TTW) in the Bavarian Forest National Park (Germany). This bird, a keystone species of boreal and mountainous forests, is highly reliant on bark beetles dwelling in dead or dying trees. While previous studies showed a positive relationship between the TTW presence and the amount of deadwood as a limiting resource, we hypothesized a unimodal response with a negative effect of very high deadwood amounts and tested for effects of substrate quality. Based on 104 woodpecker presence or absence locations, habitat selection was modelled at four spatial scales reflecting different woodpecker home range sizes. The abundance of standing dead trees was the most important predictor, with an increase in the probability of TTW occurrence up to a threshold of 44–50 dead trees per hectare, followed by a decrease in the probability of occurrence. A positive relationship with the deadwood crown size indicated the importance of fresh deadwood. Remote sensing data allowed both an area-wide prediction of species occurrence and the derivation of ecological threshold values for deadwood quality and quantity for more informed conservation management.
For the differentiation of a embryonic stem cells (ESCs) to neuronal cells (NCs) a complex and coordinated gene regulation program is needed. One important control element for neuronal differentiation is the repressor element 1 silencing transcription factor (REST) complex, which represses neuronal gene expression in non-neuronal cells. Crucial effector proteins of the REST complex are small phosphatases such as the CTDSPs (C-terminal domain small phosphatases) that regulate polymerase II activity by dephosphorylating the C-terminal domain of the polymerase, thereby repressing target genes. The stepwise inactivation of REST, including the CTDSPs, leads to the induction of a neuron-specific gene program, which ultimately induces the formation of neurons. The spatio-temporal control of REST and its effector components is therefore a crucial step for neurogenesis.
In zebrafish it was shown that the REST-associated CTDSP2 is negatively regulated by the micro RNA (miR) -26b. Interestingly, the miR-26b is encoded in an intron of the primary transcript of CTDSP2. This gives the fundament of an intrinsic regulatory negative feedback loop, which is essential for the proceeding of neurogenesis. This feedback loop is active during neurogenesis, but inactive in non-neuronal cells. The reason for this is that the maturation of the precursor miR (pre-miR) to the mature miR-26 is arrested in non neuronal cells, but not in neurons. As only mature miRs are actively repressing genes, the regulation of miR-26 processing is an essential step in neurogenesis.
In this study, the molecular basis of miR-26 processing regulation in the context of neurogenesis was addressed. The mature miR is processed from two larger precursors: First the primary transcript is cleaved by the enzyme DROSHA in the nucleus to form the pre-miR. The pre-miR is exported from the nucleus and processed further through the enzyme DICER to yield the mature miR. The mature miR can regulate gene expression in association with the RNA-induced silencing complex (RISC).
Multiple different scenarios in which miR processing was regulated were proposed and experimentally tested. Microinjection studies using Xenopus leavis oocytes showed that slowdown or blockage of the nucleo-cytoplasmic transport are not the reason for delayed pre-miR-26 processing. Moreover, in vitro and in vivo miR-processing assays showed that maturation is most likely regulated through a in trans acting factor, which blocks processing in non neuronal cells.
Through RNA affinity chromatographic assays using zebrafish and murine lysates I was able to isolate and identify proteins that interact specifically with pre-miR-26 and could by this influence its biogenesis. Potential candidates are FMRP/FXR1/2, ZNF346 and Eral1, whose functional characterisation in the context of miR-biogenesis could now be addressed.
The second part of my thesis was executed in close colaboration with the laboratory of Prof. Albrecht Müller. The principal question was addressed how miR-26 influences neuronal gene expression and which genes are primarily affected. This research question could be addressed by using a cell culture model system, which mimics ex vivo the differentiation of ESCs to NCs via neuronal progenitor.
For the functional analysis of miR-26 knock out cell lines were generated by the CRISPR/Cas9 technology. miR-26 deficient ESC keep their pluripotent state and are able to develop NPC, but show major impairment in differentiating to NCs. Through RNA deep sequencing the miR-26 induced transcriptome differences could be analysed.
On the level of mRNAs it could be shown, that the expression of neuronal gene is downregulated in miR-26 deficient NCs. Interestingly, the deletion of miR-26 leads to selectively decreased levels of miRs, which on one hand regulate the REST complex and on the other hand are under transcriptional control by REST themself. This data and the discovery that induction of miR-26 leads to enrichment of other REST regulating miRs indicates that miR-26 initiates neurogenesis through stepwise inactivation of the REST complex.
This work is concerned with the numerical approximation of solutions to models that are used to describe atmospheric or oceanographic flows. In particular, this work concen- trates on the approximation of the Shallow Water equations with bottom topography and the compressible Euler equations with a gravitational potential. Numerous methods have been developed to approximate solutions of these models. Of specific interest here are the approximations of near equilibrium solutions and, in the case of the Euler equations, the low Mach number flow regime. It is inherent in most of the numerical methods that the quality of the approximation increases with the number of degrees of freedom that are used. Therefore, these schemes are often run in parallel on big computers to achieve the best pos- sible approximation. However, even on those big machines, the desired accuracy can not be achieved by the given maximal number of degrees of freedom that these machines allow. The main focus in this work therefore lies in the development of numerical schemes that give better resolution of the resulting dynamics on the same number of degrees of freedom, compared to classical schemes.
This work is the result of a cooperation of Prof. Klingenberg of the Institute of Mathe- matics in Wu¨rzburg and Prof. R¨opke of the Astrophysical Institute in Wu¨rzburg. The aim of this collaboration is the development of methods to compute stellar atmospheres. Two main challenges are tackled in this work. First, the accurate treatment of source terms in the numerical scheme. This leads to the so called well-balanced schemes. They allow for an accurate approximation of near equilibrium dynamics. The second challenge is the approx- imation of flows in the low Mach number regime. It is known that the compressible Euler equations tend towards the incompressible Euler equations when the Mach number tends to zero. Classical schemes often show excessive diffusion in that flow regime. The here devel- oped scheme falls into the category of an asymptotic preserving scheme, i.e. the numerical scheme reflects the behavior that is computed on the continuous equations. Moreover, it is shown that the diffusion of the numerical scheme is independent of the Mach number.
In chapter 3, an HLL-type approximate Riemann solver is adapted for simulations of the Shallow Water equations with bottom topography to develop a well-balanced scheme. In the literature, most schemes only tackle the equilibria when the fluid is at rest, the so called Lake at rest solutions. Here a scheme is developed to accurately capture all the equilibria of the Shallow Water equations. Moreover, in contrast to other works, a second order extension is proposed, that does not rely on an iterative scheme inside the reconstruction procedure, leading to a more efficient scheme.
In chapter 4, a Suliciu relaxation scheme is adapted for the resolution of hydrostatic equilibria of the Euler equations with a gravitational potential. The hydrostatic relations are underdetermined and therefore the solutions to that equations are not unique. However, the scheme is shown to be well-balanced for a wide class of hydrostatic equilibria. For specific classes, some quadrature rules are computed to ensure the exact well-balanced property. Moreover, the scheme is shown to be robust, i.e. it preserves the positivity of mass and energy, and stable with respect to the entropy. Numerical results are presented in order to investigate the impact of the different quadrature rules on the well-balanced property.
In chapter 5, a Suliciu relaxation scheme is adapted for the simulations of low Mach number flows. The scheme is shown to be asymptotic preserving and not suffering from excessive diffusion in the low Mach number regime. Moreover, it is shown to be robust under certain parameter combinations and to be stable from an Chapman-Enskog analysis.
Numerical results are presented in order to show the advantages of the new approach.
In chapter 6, the schemes developed in the chapters 4 and 5 are combined in order to investigate the performance of the numerical scheme in the low Mach number regime in a gravitational stratified atmosphere. The scheme is shown the be well-balanced, robust and stable with respect to a Chapman-Enskog analysis. Numerical tests are presented to show the advantage of the newly proposed method over the classical scheme.
In chapter 7, some remarks on an alternative way to tackle multidimensional simulations are presented. However no numerical simulations are performed and it is shown why further research on the suggested approach is necessary.
Abstract
Despite multidisciplinary local and systemic therapeutic approaches, the prognosis for most patients with brain metastases is still dismal. The role of adaptive and innate anti-tumor response including the Human Leukocyte Antigen (HLA) machinery of antigen presentation is still unclear. We present data on the HLA class II-chaperone molecule CD74 in brain metastases and its impact on the HLA peptidome complexity.
We analyzed CD74 and HLA class II expression on tumor cells in a subset of 236 human brain metastases, primary tumors and peripheral metastases of different entities in association with clinical data including overall survival. Additionally, we assessed whole DNA methylome profiles including CD74 promoter methylation and differential methylation in 21 brain metastases. We analyzed the effects of a siRNA mediated CD74 knockdown on HLA-expression and HLA peptidome composition in a brain metastatic melanoma cell line.
We observed that CD74 expression on tumor cells is a strong positive prognostic marker in brain metastasis patients and positively associated with tumor-infiltrating T-lymphocytes (TILs). Whole DNA methylome analysis suggested that CD74 tumor cell expression might be regulated epigenetically via CD74 promoter methylation. CD74\(^{high}\) and TIL\(^{high}\) tumors displayed a differential DNA methylation pattern with highest enrichment scores for antigen processing and presentation. Furthermore, CD74 knockdown in vitro lead to a reduction of HLA class II peptidome complexity, while HLA class I peptidome remained unaffected.
In summary, our results demonstrate that a functional HLA class II processing machinery in brain metastatic tumor cells, reflected by a high expression of CD74 and a complex tumor cell HLA peptidome, seems to be crucial for better patient prognosis.
To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolution annotations is challenging, time consuming, and requires numerous steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-seq and differential RNA-seq and predicts and annotates numerous features, including small noncoding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.
Purpose: Prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) imaging has become commonly utilized in patients with prostate cancer (PCa). The PSMA reporting and data system version 1.0 (PSMA-RADS version 1.0) categorizes lesions on the basis of the likelihood of PCa involvement, with PSMA-RADS-3A (soft tissue) and PSMA-RADS-3B (bone) lesions being indeterminate for the presence of disease. We retrospectively reviewed the imaging follow-up of such lesions to determine the rate at which they underwent changes suggestive of underlying PCa.
Methods: PET/CT imaging with \(^{18}\)F-DCFPyL was carried out in 110 patients with PCa and lesions were categorized according to PSMA-RADS Version 1.0. 56/110 (50.9%) patients were determined to have indeterminate PSMA-RADS-3A or PSMA-RADS-3B lesions and 22/56 (39.3%) patients had adequate follow-up to be included in the analysis. The maximum standardized uptake values (SUV\(_{max}\)) of the lesions were obtained and the ratios of SUV\(_{max}\) of the lesions to SUV\(_{mean}\) of blood pool (SUV\(_{max}\)-lesion/SUV\(_{mean}\)-bloodpool) were calculated. Pre-determined criteria were used to evaluate the PSMA-RADS-3A and PSMA-RADS-3B lesions on follow-up imaging to determine if they demonstrated evidence of underlying malignancy.
Results: A total of 46 lesions in 22 patients were considered indeterminate for PCa (i.e. PSMA-RADS-3A (32 lesions) or PSMA-RADS-3B (14 lesions)) and were evaluable on follow-up imaging. 27/46 (58.7%) lesions demonstrated changes on follow-up imaging consistent with the presence of underlying PCa at baseline. These lesions included 24/32 (75.0%) PSMA-RADS-3A lesions and 3/14 (21.4%) lesions categorized as PSMA-RADS-3B. The ranges of SUVmax and SUVmax-lesion/SUVmean-bloodpool overlapped between those lesions demonstrating changes consistent with malignancy on follow-up imaging and those lesions that remained unchanged on follow-up.
Conclusion: PSMA-RADS-3A and PSMA-RADS-3B lesions are truly indeterminate in that proportions of findings in both categories demonstrate evidence of malignancy on follow-up imaging. Overall, PSMA-RADS-3A lesions are more likely than PSMA-RADS-3B lesions to represent sites of PCa and this information should be taken into when guiding patient therapy.
The HECT-type ubiquitin ligase HECT, UBA and WWE Domain Containing 1, (HUWE1) regulates key cancer-related pathways, including the Myc oncogene. It affects cell proliferation, stress and immune signaling, mitochondria homeostasis, and cell death. HUWE1 is evolutionarily conserved from Caenorhabditis elegance to Drosophila melanogaster and Humans. Here, we report that the Drosophila ortholog, dHUWE1 (CG8184), is an essential gene whose loss results in embryonic lethality and whose tissue-specific disruption establishes its regulatory role in larval salivary gland development. dHUWE1 is essential for endoreplication of salivary gland cells and its knockdown results in the inability of these cells to replicate DNA. Remarkably, dHUWE1 is a survival factor that prevents premature activation of JNK signaling, thus preventing the disintegration of the salivary gland, which occurs physiologically during pupal stages. This function of dHUWE1 is general, as its inhibitory effect is observed also during eye development and at the organismal level. Epistatic studies revealed that the loss of dHUWE1 is compensated by dMyc proeitn expression or the loss of dmP53. dHUWE1 is therefore a conserved survival factor that regulates organ formation during Drosophila development.
Background:
Until now there has been a reported lack of systematic reports and scientific evaluations of rescue missions during terror attacks. This however is urgently required in order to improve the performance of emergency medical services and to be able to compare different missions with each other. Aim of the presented work was to report the systematic evaluation and the lessons learned from the response to a terror attack that happened in Wuerzburg, Germany in 2016.
Methods:
A team of 14 experts developed a template of quality indicators and operational characteristics, which allow for the description, assessment and comparison of civil emergency rescue missions during mass killing incidents. The entire systematic evaluation process consisted of three main steps. The first step was the systematic data collection according to the quality indicators and operational characteristics. Second was the systematic stratification and assessment of the data. The last step was the prioritisation of the identified weaknesses and the definition of the lessons learned.
Results:
Five important “lessons learned” have been defined. First of all, a comprehensive concept for rescue missions during terror attacks is essential. Furthermore, the establishment of a defined high priority communication infrastructure between the different dispatch centres (“red phone”) is vital. The goal is to secure the continuity of information between a few well-defined individuals. Thirdly, the organization of the incident scene needs to be commonly decided and communicated between police, medical services and fire services during the mission. A successful mission tactic requires continuous flux of reports to the on-site command post. Therefore, a predefined and common communication infrastructure for all operational forces is a crucial point. Finally, all strategies need to be extensively trained before the real life scenario hits.
Conclusion:
According to a systematic evaluation, we defined the lessons learned from a terror attack in 2016. Further systematic reports and academic work surrounding life threatening rescue missions and mass killing incidents are needed in order to ultimately improve such mission outcomes. In the future, a close international collaboration might help to find the best database to report and evaluate major incidents but also mass killing events.