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Institute
- Graduate School of Life Sciences (103)
- Theodor-Boveri-Institut für Biowissenschaften (82)
- Institut für Informatik (46)
- Institut für Psychologie (43)
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Schriftenreihe
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (2)
- Interdisziplinäres Zentrum für Klinische Forschung (IZKF) (2)
- Klinische Studienzentrale (Universitätsklinikum) (2)
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg (2)
- Anthropology Department University of Tennessee, Knoxville (1)
- CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg (1)
- Carl-Ludwig-Institut für Physiologie, Universität Leipzig (1)
- Chair of Experimental Biomedicine I (1)
- Charles University, Faculty of Mathematics and Physics, Ke Karlovu 5, 121 16 Prague, Czech Republic (1)
- DATE Lab, KITE Research Insititute, University Health Network, Toronto, Canada (1)
Environmental issues have emerged especially since humans burned fossil fuels, which led to air pollution and climate change that harm the environment. These issues’ substantial consequences evoked strong efforts towards assessing the state of our environment.
Various environmental machine learning (ML) tasks aid these efforts. These tasks concern environmental data but are common ML tasks otherwise, i.e., datasets are split (training, validatition, test), hyperparameters are optimized on validation data, and test set metrics measure a model’s generalizability. This work focuses on the following environmental ML tasks: Regarding air pollution, land use regression (LUR) estimates air pollutant concentrations at locations where no measurements are available based on measured locations and each location’s land use (e.g., industry, streets). For LUR, this work uses data from London (modeled) and Zurich (measured). Concerning climate change, a common ML task is model output statistics (MOS), where a climate model’s output for a study area is altered to better fit Earth observations and provide more accurate climate data. This work uses the regional climate model (RCM) REMO and Earth observations from the E-OBS dataset for MOS. Another task regarding climate is grain size distribution interpolation where soil properties at locations without measurements are estimated based on the few measured locations. This can provide climate models with soil information, that is important for hydrology. For this task, data from Lower Franconia is used.
Such environmental ML tasks commonly have a number of properties: (i) geospatiality, i.e., their data refers to locations relative to the Earth’s surface. (ii) The environmental variables to estimate or predict are usually continuous. (iii) Data can be imbalanced due to relatively rare extreme events (e.g., extreme precipitation). (iv) Multiple related potential target variables can be available per location, since measurement devices often contain different sensors. (v) Labels are spatially often only sparsely available since conducting measurements at all locations of interest is usually infeasible. These properties present challenges but also opportunities when designing ML methods for such tasks.
In the past, environmental ML tasks have been tackled with conventional ML methods, such as linear regression or random forests (RFs). However, the field of ML has made tremendous leaps beyond these classic models through deep learning (DL). In DL, models use multiple layers of neurons, producing increasingly higher-level feature representations with growing layer depth. DL has made previously infeasible ML tasks feasible, improved the performance for many tasks in comparison to existing ML models significantly, and eliminated the need for manual feature engineering in some domains due to its ability to learn features from raw data. To harness these advantages for environmental domains it is promising to develop novel DL methods for environmental ML tasks.
This thesis presents methods for dealing with special challenges and exploiting opportunities inherent to environmental ML tasks in conjunction with DL. To this end, the proposed methods explore the following techniques: (i) Convolutions as in convolutional neural networks (CNNs) to exploit reoccurring spatial patterns in geospatial data. (ii) Posing the problems as regression tasks to estimate the continuous variables. (iii) Density-based weighting to improve estimation performance for rare and extreme events. (iv) Multi-task learning to make use of multiple related target variables. (v) Semi–supervised learning to cope with label sparsity. Using these techniques, this thesis considers four research questions: (i) Can air pollution be estimated without manual feature engineering? This is answered positively by the introduction of the CNN-based LUR model MapLUR as well as the off-the-shelf LUR solution OpenLUR. (ii) Can colocated pollution data improve spatial air pollution models? Multi-task learning for LUR is developed for this, showing potential for improvements with colocated data. (iii) Can DL models improve the quality of climate model outputs? The proposed DL climate MOS architecture ConvMOS demonstrates this. Additionally, semi-supervised training of multilayer perceptrons (MLPs) for grain size distribution interpolation is presented, which can provide improved input data. (iv) Can DL models be taught to better estimate climate extremes? To this end, density-based weighting for imbalanced regression (DenseLoss) is proposed and applied to the DL architecture ConvMOS, improving climate extremes estimation. These methods show how especially DL techniques can be developed for environmental ML tasks with their special characteristics in mind. This allows for better models than previously possible with conventional ML, leading to more accurate assessment and better understanding of the state of our environment.
The use of digital media by children and young people offers opportunities for communication, collaboration, and participation. However, to prepare them for the risks and challenges of media usage, promoting digital competencies of students and teachers is an indispensable goal for educational institutions. To meet this requirement, teacher education must be opened to innovative pedagogical concepts for initial teacher education that considers new technologies in a reflective, action-oriented way to promote competencies. Therefore, this work aims to promote the technological pedagogical content knowledge (TPACK) of prospective teachers that enables the purposeful integration of social virtual reality (social VR) into the classroom. Consequently, a pedagogical concept is developed and evaluated in an iterative research and development process following the design- based research approach (DBR) through four consecutive studies. The first study involved an analysis of the requirements of teachers and students for the effective use of social VR in the classroom. The second study examined how prospective teachers perceive teaching and learning activities within two theory-driven scenarios in social VR. The third study investigated the development of Technological Pedagogical Content Knowledge (TPACK) among students in social VR compared to video-based communication. Finally, the fourth study measured the development of TPACK in social VR using epistemic network analysis, finding that social VR can be an effective tool for teacher education, emphasizing the importance of authentic contexts and practical experiences for effective teaching in social VR. In the concluding chapter, appropriate implications for teacher education research and practice are derived from findings. For example, that a deeper understanding of TPACK as metacognitive awareness could enhance teacher education for media integration. It also highlights the need for digital literacy in seminars that address new technologies, emphasizing the importance of considering moral values and sustainability when using VR.
The holy grail of structural biology is to study a protein in situ, and this goal has been fast approaching since the resolution revolution and the achievement of atomic resolution. A cell's interior is not a dilute environment, and proteins have evolved to fold and function as needed in that environment; as such, an investigation of a cellular component should ideally include the full complexity of the cellular environment. Imaging whole cells in three dimensions using electron cryotomography is the best method to accomplish this goal, but it comes with a limitation on sample thickness and produces noisy data unamenable to direct analysis. This thesis establishes a novel workflow to systematically analyse whole-cell electron cryotomography data in three dimensions and to find and identify instances of protein complexes in the data to set up a determination of their structure and identity for success. Mycoplasma pneumoniae is a very small parasitic bacterium with fewer than 700 protein-coding genes, is thin enough and small enough to be imaged in large quantities by electron cryotomography, and can grow directly on the grids used for imaging, making it ideal for exploratory studies in structural proteomics. As part of the workflow, a methodology for training deep-learning-based particle-picking models is established.
As a proof of principle, a dataset of whole-cell Mycoplasma pneumoniae tomograms is used with this workflow to characterize a novel membrane-associated complex observed in the data. Ultimately, 25431 such particles are picked from 353 tomograms and refined to a density map with a resolution of 11 Å. Making good use of orthogonal datasets to filter search space and verify results, structures were predicted for candidate proteins and checked for suitable fit in the density map. In the end, with this approach, nine proteins were found to be part of the complex, which appears to be associated with chaperone activity and interact with translocon machinery.
Visual proteomics refers to the ultimate potential of in situ electron cryotomography: the comprehensive interpretation of tomograms. The workflow presented here is demonstrated to help in reaching that potential.
Small bacterial regulatory RNAs (sRNAs) have been implicated in the regulation of numerous metabolic pathways. In most of these studies, sRNA-dependent regulation of mRNAs or proteins of enzymes in metabolic pathways has been predicted to affect the metabolism of these bacteria. However, only in a very few cases has the role in metabolism been demonstrated. Here, we performed a combined transcriptome and metabolome analysis to define the regulon of the sibling sRNAs NgncR_162 and NgncR_163 (NgncR_162/163) and their impact on the metabolism of Neisseria gonorrhoeae. These sRNAs have been reported to control genes of the citric acid and methylcitric acid cycles by posttranscriptional negative regulation. By transcriptome analysis, we now expand the NgncR_162/163 regulon by several new members and provide evidence that the sibling sRNAs act as both negative and positive regulators of target gene expression. Newly identified NgncR_162/163 targets are mostly involved in transport processes, especially in the uptake of glycine, phenylalanine, and branched-chain amino acids. NgncR_162/163 also play key roles in the control of serine-glycine metabolism and, hence, probably affect biosyntheses of nucleotides, vitamins, and other amino acids via the supply of one-carbon (C\(_1\)) units. Indeed, these roles were confirmed by metabolomics and metabolic flux analysis, which revealed a bipartite metabolic network with glucose degradation for the supply of anabolic pathways and the usage of amino acids via the citric acid cycle for energy metabolism. Thus, by combined deep RNA sequencing (RNA-seq) and metabolomics, we significantly extended the regulon of NgncR_162/163 and demonstrated the role of NgncR_162/163 in the regulation of central metabolic pathways of the gonococcus.
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
Enterococcus faecalis and Enterococcus faecium are major nosocomial pathogens. Despite their relevance to public health and their role in the development of bacterial antibiotic resistance, relatively little is known about gene regulation in these species. RNA–protein complexes serve crucial functions in all cellular processes associated with gene expression, including post-transcriptional control mediated by small regulatory RNAs (sRNAs). Here, we present a new resource for the study of enterococcal RNA biology, employing the Grad-seq technique to comprehensively predict complexes formed by RNA and proteins in E. faecalis V583 and E. faecium AUS0004. Analysis of the generated global RNA and protein sedimentation profiles led to the identification of RNA–protein complexes and putative novel sRNAs. Validating our data sets, we observe well-established cellular RNA–protein complexes such as the 6S RNA–RNA polymerase complex, suggesting that 6S RNA-mediated global control of transcription is conserved in enterococci. Focusing on the largely uncharacterized RNA-binding protein KhpB, we use the RIP-seq technique to predict that KhpB interacts with sRNAs, tRNAs, and untranslated regions of mRNAs, and might be involved in the processing of specific tRNAs. Collectively, these datasets provide departure points for in-depth studies of the cellular interactome of enterococci that should facilitate functional discovery in these and related Gram-positive species. Our data are available to the community through a user-friendly Grad-seq browser that allows interactive searches of the sedimentation profiles (https://resources.helmholtz-hiri.de/gradseqef/).
The present cumulative dissertation summarizes three clinical studies, which examine
subgroups of patients within the fibromyalgia syndrome (FMS). FMS entails chronic pain and
associated symptoms, and its pathophysiology is incompletely understood (1). Previous studies
show that there is a subgroup of patients with FMS with objective histological pathology of the
small nerve fibers of the peripheral nervous system (PNS). Another subgroup of FMS patients
does not show any signs of pathological changes of the small nerve fibers. The aim of this
dissertation was to compare FMS patients with healthy controls, and these two FMS subgroups
for differences in the central nervous system (CNS) in order to explore possible interactions
between PNS and the CNS. Regarding the CNS, differences of FMS patients with healthy
controls have already been found in studies with small sample sizes, but no subgroups have yet
been identified. Another aim of this thesis was to test whether the subgroups show a different
response to different classes of pain medication. The methods used in this thesis are structural
and functional magnetic resonance imaging (MRI), magnetic resonance diffusion imaging and
magnetic resonance spectroscopy. For the evaluation of clinical symptoms, we used
standardized questionnaires. The subgroups with and without pathologies of the PNS were
determined by skin biopsies of the right thigh and lower leg based on the intraepidermal nerve
fiber density (IENFD) of the small nerve fibers.
1) In the first MRI study, 43 female patients with the diagnosis of FMS and 40 healthy
control subjects, matched in age and body mass index, were examined with different MRI
sequences. Cortical thickness was investigated by structural T1 imaging, white matter integrity
by diffusion tensor imaging and functional connectivity within neuronal networks by functional
resting state MRI. Compared to the controls, FMS patients had a lower cortical volume in
bilateral frontotemporoparietal regions and the left insula, but a higher cortical volume in the
left pericalcarine cortex. Compared to the subgroup without PNS pathology, the subgroup with
PNS pathology had lower cortical volume in both pericalcarine cortices. Diffusion tensor
imaging revealed an increased fractional anisotropy (FA) of FMS patients in corticospinal
pathways such as the corona radiata, but also in regions of the limbic systems such as the fornix
and cingulum. Subgroup comparison again revealed lower mean FA values of the posterior
thalamic radiation and the posterior limb of the left internal capsule in the subgroup with PNS
pathology. In the functional connectivity analysis FMS patients, compared to controls, showed
a hypoconnectivity between the right median frontal gyrus and the posterior cerebellum and
the right crus cerebellum, respectively. In the subgroup comparisons, the subgroup with PNS
pathology showed a hyperconnectivity between both inferior frontal gyri, the right posterior
parietal cortex and the right angular gyrus. In summary, these results show that differences in
brain morphology and functional connectivity exist between FMS patients with and without
PNS pathology. These differences were not associated with symptom duration or severity and,
in some cases, have not yet been described in the context of FMS. The differences in brain
morphology and connectivity between subgroups could also lead to a differential response to
treatment with centrally acting drugs. Further imaging studies with FMS patients should take
into account this heterogeneity of FMS patient cohorts.
2) Following the results from the first MRI study, drug therapies of FMS patients and
their treatment response were compared between PNS subgroups. As there is no licensed drug
for FMS in Europe, the German S3 guideline recommends amitriptyline, duloxetine and
pregabalin for temporary use. In order to examine the current drug use in FMS patients in
Germany on a cross-sectional basis, 156 patients with FMS were systematically interviewed.
The drugs most frequently used to treat pain in FMS were non-steroidal anti-inflammatory
drugs (NSAIDs) (28.9%), metamizole (15.4%) and amitriptyline (8.8%). Pain relief assessed by
patients on a numerical rating scale from 0-10 averaged 2.2 points for NSAIDs, 2.0 for
metamizole and 1.5 for amitriptyline. Drugs that were discontinued for lack of efficacy and not
for side effects were acetaminophen (100%), flupirtine (91.7%), selective serotonin reuptake
inhibitors (81.8%), NSAIDs (83.7%) and weak opioids (74.1%). Patients were divided into
subgroups with and without PNS pathology as determined by skin biopsies. We found no
differences in drug use and effect between the subgroups. Taken together, these results show
that many FMS patients take medication that is not in accordance with the guidelines. The
reduction of symptoms was best achieved with metamizole and NSAIDs. Further longitudinal
studies on medication in FMS are necessary to obtain clearer treatment recommendations.
3) Derived from previous pharmacological and imaging studies (with smaller case
numbers), there is a hypothesis in the FMS literature that hyperreactivity of the insular cortex
may have an impact on FMS. The hyperreactivity seems to be due to an increased concentration
of the excitatory neurotransmitter glutamate in the insular cortex of FMS patients. The
hypothesis is supported by magnetic resonance spectroscopy studies with small number of
cases, as well as results from pharmacological studies with glutamate-inhibiting medication.
Studies from animal models have also shown that an artificially induced increase in glutamate
in the insular cortex can lead to reduced skin innervation. Therefore, the aim of this study was
to compare glutamate and GABA concentrations in the insular cortex of FMS patients with
those of healthy controls using magnetic resonance imaging. There was no significant
difference of both neurotransmitters between the groups. In addition, there was no correlation
between the neurotransmitter concentrations and the severity of clinical symptoms. There
were also no differences in neurotransmitter concentrations between the subgroups with and
without PNS pathology. In conclusion, our study could not show any evidence of a correlation
of glutamate and GABA concentrations with the symptoms of FMS or the pathogenesis of
subgroups with PNS pathologies.
The monarch butterfly (Danaus plexippus) performs one of the most astonishing behaviors in the animal kingdom: every fall millions of these butterflies leave their breeding grounds in North Amerika and migrate more than 4.000 km southwards until they reach their overwintering habitat in Central Mexico. To maintain their migratory direction over this enormous distance, the butterflies use a time-compensated sun compass. Beside this, skylight polarization, the Earth’s magnetic field and specific mountain ranges seem to guide the butterflies as well the south. In contrast to this fascinating orientation ability, the behavior of the butterflies in their non-migratory state received less attention. Although they do not travel long distances, they still need to orient themselves to find food, mating partners or get away from competitors. The aim of the present doctoral thesis was to investigate use of visual cues for orientation in migrating as well as non-migrating monarch butterflies. For this, field experiments investigating the migration of the butterflies in Texas (USA) were combined with experiments testing the orientation performance of non-migratory butterflies in Germany.
In the first project, I recorded the heading directions of tethered butterflies during their annual fall migration. In an outdoor flight simulator, the butterflies maintained a southwards direction as long as they had a view of the sun’s position. Relocating the position of the sun by 180° using a mirror, revealed that the sun is the animals’ main orientation reference. Furthermore, I demonstrated that when the sun is blocked and a green light stimulus (simulated sun) is introduced, the animals interpreted this stimulus as the ‘real’ sun. However, this cue was not sufficient to set the migratory direction when simulated as the only visual cue in indoor experiments. When I presented the butterflies a linear polarization pattern additionally to the simulated sun, the animals headed in the correct southerly direction showing that multiple skylight cues are required to guide the butterflies during their migration.
In the second project, I, furthermore, demonstrated that non-migrating butterflies are able to maintain a constant direction with respect to a simulated sun. Interestingly, they ignored the spectral component of the stimulus and relied on the intensity instead. When a panoramic skyline was presented as the only orientation reference, the butterflies maintained their direction only for short time windows probably trying to stabilize their flight based on optic-flow information. Next, I investigated whether the butterflies combine celestial with local cues by simulating a sun stimulus together with a panoramic skyline. Under this conditions, the animals’ directedness was increased demonstrating that they combine multiple visual cues for spatial orientation.
Following up on the observation that a sun stimulus resulted in a different behavior than the panoramic skyline, I investigated in my third project which orientation strategies the butterflies use by presenting different simulated cues to them. While a bright stripe on a dark background elicited a strong attraction of the butterflies steering in the direction of the stimulus, the inverted version of the stimulus was used for flight stabilization. In contrast to this, the butterflies maintained arbitrary directions with a high directedness with respect to a simulated sun. In an ambiguous scenery with two identical stimuli (two bright stripes, two dark stripes, or two sun stimuli) set 180° apart, a constant flight course was only achieved when two sun stimuli were displayed suggesting an involvement of the animals’ internal compass. In contrast, the butterflies used two dark stripes for flight stabilization and were alternatingly attracted by two bright stripes. This shows that monarch butterflies use stimulus-dependent orientation strategies and gives the first evidence for different neuronal pathways controlling the output behavior.
Acknowledgements
(2023)
Beyond the four canonical nucleosides as primary building blocks of RNA, posttranscriptional modifications give rise to the epitranscriptome as a second layer of genetic information. In eukaryotic mRNA, the most abundant posttranscriptional modification is N6-methyladenosine (m6A), which is involved in the regulation of cellular processes. Throughout this thesis, the concept of atomic mutagenesis was employed to gain novel mechanistic insights into the substrate recognition by human m6A reader proteins as well as in the oxidative m6A demethylation by human demethylase enzymes. Non-natural m6A atomic mutants featuring distinct steric and electronic properties were synthesized and incorporated into RNA oligonucleotides. Fluorescence anisotropy measurements using these modified oligonucleotides revealed the impact of the atomic mutagenesis on the molecular recognition by the human m6A readers YTHDF2, YTHDC1 and YTHDC2 and allowed to draw conclusions about structural prerequisites for substrate recognition. Furthermore, substrate recognition and demethylation mechanism of the human m6A demethylase enzymes FTO and ALKBH5 were analyzed by HPLC-MS and PAGE-based assays using the modified oligonucleotides synthesized in this work.
Modified nucleosides not only expand the genetic alphabet, but are also extensively researched as drug candidates. In this thesis, the antiviral mechanism of the anti-SARS-CoV-2 drug remdesivir was investigated, which causes delayed stalling of the viral RNA-dependent RNA polymerase (RdRp). Novel remdesivir phosphoramidite building blocks were synthesized and used to construct defined RNA-RdRp complexes for subsequent studies by cryogenic electron microscopy (cryo-EM). It was found that the 1'-cyano substituent causes Rem to act as a steric barrier of RdRp translocation. Since this translocation barrier can eventually be overcome by the polymerase, novel derivatives of Rem with potentially improved antiviral properties were designed.
A New International
(2023)
Contributors
(2023)
Can cultural studies attend to the problems of our globalized world? Or is this project of “engaged scholarship” too deeply rooted in the parochial terrain of the national?
This collection of essays – the first volume in the new JMU Cultural Studies publication series – attends to this vital yet difficult question. Based on joint seminars bringing together emerging scholars from Germany and India, the contributions confront “classic texts” from US-American, British, and Indian cultural studies with the specific concerns and contemporary perspectives of the authors.
The collection thus tests the potentials of the tradition to speak to the transnational as well as the national environments of the very present. Emphasis is placed on Marxist and feminist legacies, which are then projected into the domains of contemporary disability, food, and film studies.
Pulmonary artery embolism (PE) is a common condition and an even more common clinical suspect. The computed tomography pulmonary angiogram (CTPA) is the main medical imaging tool used to diagnose a suspected case of PE. To gain a better impression of the effects of a PE on the perfusion and hence the gas exchange, a functional imaging method is beneficial. One approach for functional imaging using radiation exposure is the generation of color-coded iodine perfusion maps acquired by Dual-Energy Computed Tomography (DECT), which enable the detection of perfusion defects in the pulmonary parenchyma. In contrast to the existing approach of DECT with iodine color-coded maps, the SElf-gated Non-Contrast-Enhanced FUnctional Lung (SENCEFUL) MRI technique offers the possibility to interpret perfusion maps without any radiation exposure or application of contrast agents. The measurement in SENCEFUL MRI can be performed during conditions of free breathing and without electrocardiogram triggering.
The purpose of this study was to determine whether PE can be diagnosed on the basis of visible perfusion defects in the perfusion maps of SENCEFUL MRI and in the iodine-coded maps of DECT and to compare the diagnostic performance of these methods. Both SENCEFUL-MRI and iodine distribution maps from DECT have been compared with the CTPA of ten patients with PE. Additionally, the functional images were compared with each other on a per-patient basis.
The iodine perfusion maps of DECT had a sensitivity of 84.2 % and specificity of 65.2 % for the diagnosis of PE. The SENCEFUL technique in MRI showed a sensitivity of 78.9 % and a specificity of 26.1 %. When comparing the whole lung depicted in both series of functional images, the main perfusion defect location matched in four of ten patients (40 %).
In conclusion, this work found that DECT iodine maps have higher sensitivity and specificity in the diagnosis of pulmonary embolism compared with SENCEFUL MRI.
Coxiella burnetii, a Gram negative obligate intracellular bacterium, is the causative
agent of Q fever. It has a world wide distribution and has been documented to
be capable of causing infections in several domestic animals, livestock species,
and human beings. Outbreaks of Q fever are still being observed in livestock
across animal farms in Europe, and primary transmission to humans still oc-
curs especially in animal handlers. Public health authorities in some countries
like Germany are required by law to report human acute cases denoting the
significance of the challenge posed by C. burnetii to public health.
In this thesis, I have developed a platform alongside methods to address the
challenges of genomic analyses of C. burnetii for typing purposes. Identification
of C. burnetii isolates is an important task in the laboratory as well as in the
clinics and genotyping is a reliable method to identify and characterize known
and novel isolates. Therefore, I designed and implemented several methods
to facilitate the genotyping analyses of C. burnetii genomes in silico via a web
platform. As genotyping is a data intensive process, I also included additional
features such as visualization methods and databases for interpretation and
storage of obtained results. I also developed a method to profile the resistome
of C. burnetii isolates using a machine learning approach. Data about antibiotic
resistance in C. burnetii are scarce majorly due to its lifestyle and the difficulty
of cultivation in laboratory media. Alternative methods that rely on homology
identification of resistance genes are also inefficient in C. burnetii, hence, I
opted for a novel approach that has been shown to be promising in other
bacteria species. The applied method relied on an artificial neural network as
well as amino acid composition of position specific scoring matrix profile for
feature extraction. The resulting model achieved an accuracy of ≈ 0.96 on test
data and the overall performance was significantly higher in comparison to
existing models. Finally, I analyzed two new C. burnetii isolates obtained from
an outbreak in Germany, I compared the genome to the RSA 493 reference
isolate and found extensive deletions across the genome landscape.
This work has provided a new digital infrastructure to analyze and character-
ize C. burnetii genomes that was not in existence before and it has also made a
significant contribution to the existing information about antibiotic resistance
genes in C. burnetii.
The discovery, heterologous expression, and characterization of channelrhodopsin-2 (ChR2) – a light-sensitive cation channel found in the green alga Chlamydomonas reinhardtii – led to the success of optogenetics as a powerful technology, first in neuroscience. ChR2 was employed to induce action potentials by blue light in genetically modified nerve cells. In optogenetics, exogenous photoreceptors are expressed in cells to manipulate cellular activity. These photoreceptors were in the beginning mainly microbial opsins. During nearly two decades, many microbial opsins and their mutants were explored for their application in neuroscience. Until now, however, the application of optogenetics to plant studies is limited to very few reports. Several optogenetic strategies for plant research were demonstrated, in which most attempts are based on non-opsin optogenetic tools. Opsins need retinal (vitamin A) as a cofactor to generate the functional protein, the rhodopsin. As most animals have eyes that contain animal rhodopsins, they also have the enzyme - a 15, 15'-Dioxygenase - for retinal production from food-supplied provitamin A (beta-carotene). However, higher plants lack a similar enzyme, making it difficult to express functional rhodopsins successfully in plants. But plant chloroplasts contain plenty of beta-carotene. I introduced a gene, coding for a 15, 15'-Dioxygenase with a chloroplast target peptide, to tobacco plants. This enzyme converts a molecule of β-carotene into two of all-trans-retinal. After expressing this enzyme in plants, the concentration of all-trans-retinal was increased greatly. The increased retinal concentration led to increased expression of several microbial opsins, tested in model higher plants. Unfortunately, most opsins were observed intracellularly and not in the plasma membrane. To improve their localization in the plasma membrane, some reported signal peptides were fused to the N- or C-terminal end of opsins. Finally, I helped to identify three microbial opsins -- GtACR1 (a light-gated anion channel), ChR2 (a light-gated cation channel), PPR (a light-gated proton pump) which express and work well in the plasma membrane of plants. The transgene plants were grown under red light to prevent activation of the expressed opsins. Upon illumination with blue or green light, the activation of these opsins then induced the expected change of the membrane potential, dramatically changing the phenotype of plants with activated rhodopsins.
This study is the first which shows the potential of microbial opsins for optogenetic research in higher plants, using the ubq10 promoter for ubiquitous expression. I expect this to be just the beginning, as many different opsins and tissue-specific promoters for selective expression now can be tested for their usefulness. It is further to be expected that the here established method will help investigators to exploit more optogenetic tools and explore the secrets, kept in the plant kingdom.
This thesis examines the electronic properties of two materials that promise the realization and observation of novel exotic quantum phenomena. For this purpose, angle-resolved photoemission forms the experimental basis for the investigation of the electronic properties. Furthermore, the magnetic order is investigated utilizing X-ray dichroism measurements.
First, the bulk and surface electronic structure of epitaxially grown HgTe in its three-dimensional topological insulator phase is investigated. In this study, synchrotron radiation is used to address the three-dimensional band structure and orbital composition of the bulk states by employing photon-energy-dependent and polarization-dependent measurements, respectively. In addition, the topological surface state is examined on in situ grown samples using a laboratory photon source. The resulting data provide a means to experimentally localize the bulk band inversion in momentum space and to evidence the momentum-dependent change in the orbital character of the inverted bulk states.
Furthermore, a rather new series of van der Waals compounds, (MnBi\(_2\)Te\(_4\))(Bi\(_2\)Te\(_3\))\(_n\), is investigated. First, the magnetic properties of the first two members of the series, MnBi\(_2\)Te\(_4\) and MnBi\(_4\)Te\(_7\), are studied via X-ray absorption-based techniques. The topological surface state on the two terminations of MnBi\(_4\)Te\(_7\) is analyzed using circular dichroic, photon-energy-dependent, and spin-resolved photoemission. The topological state on the (MnBi\(_2\)Te\(_4\))-layer termination shows a free-standing Dirac cone with its Dirac point located in the bulk band gap. In contrast, on the (Bi\(_2\)Te\(_3\))-layer termination the surface state hybridizes with the bulk valences states, forming a spectral weight gap, and exhibits a Dirac point that is buried within the bulk continuum. Lastly, the lack of unambiguous evidence in the literature showing a temperature-dependent mass gap opening in these magnetic topological insulators is discussed through MnBi\(_2\)Te\(_4\).
Monarch butterflies are famous for their annual long-distance migration. Decreasing temperatures and reduced daylight induce the migratory state in the autumn generation of monarch butterflies. Not only are they in a reproductive diapause, they also produce fat deposits to be prepared for the upcoming journey: Driven by their instinct to migrate, they depart from their eclosion grounds in the northern regions of the North American continent and start their southern journey to their hibernation spots in Central Mexico. The butterflies cover a distance of up to 4000 km across the United States. In the next spring, the same butterflies invert their preferred heading direction due to seasonal changes and start their northward spring migration. The spring migration is continued by three consecutive butterfly generations, until the animals repopulate the northern regions in North America as non-migratory monarch butterflies. The monarch butterflies’ migratory state is genetically and epigenetically regulated, including the directed flight behavior. Therefore, the insect’s internal compass system does not only have to encode the butterflies preferred, but also its current heading direction. However, the butterfly’s internal heading representation has to be matched to external cues, to avoid departing from its initial flight path and increasing its risk of missing its desired destination. During the migratory flight, visual cues provide the butterflies with reliable orientation information. The butterflies refer to the sun as their main orientation cue. In addition to the sun, the butterflies likely use the polarization pattern of the sky for orientation. The sky compass signals are processed within a region in the brain, termed the central complex (CX). Previous research on the CX neural circuitry of the monarch butterflies demonstrated that tangential central complex neurons (TL) carry the visual input information into the CX and respond to a simulated sun and polarized light. However, whether these cells process additional visual cues like the panoramic skyline is still unknown. Furthermore, little is known about how the migratory state affects visual cue processing. In addition to this, most experiments studying the monarch butterfly CX focused on how neurons process single visual cues. However, how combined visual stimuli are processed in the CX is still unknown.
This thesis is investigating the following questions:
1) How does the migratory state affect visual cue processing in the TL cells within the monarch butterfly brain?
2) How are multiple visual cues integrated in the TL cells?
3) How is compass information modulated in the CX?
To study these questions, TL neurons from both animal groups (migratory and non-migratory) were electrophysiologically characterized using intracellular recordings while presenting different simulated celestial cues and visual sceneries. I showed that the TL neurons of migratory butterflies are more narrowly tuned to the sun, possibly helping them in keeping a directed flight course during migration. Furthermore, I found that TL cells encode a panoramic skyline, suggesting that the CX network combines celestial and terrestrial information. Experiments with combined celestial stimuli revealed that the TL cells combine both cue information linearly. However, if exposing the animals to a simulated visual scenery containing a panoramic skyline and a simulated sun, the single visual cues are weighted differently. These results indicate that the CX’s input region can flexibly adapt to different visual cue conditions. Furthermore, I characterize a previously unknown neuron in the monarch butterfly CX which responds to celestial stimuli and connects the CX with other brain neuropiles. How this cell type affects heading direction encoding has yet to be determined.
Regional climate models (RCMs) are tools used to project future climate change at a regional scale. Despite their high horizontal resolution, RCMs are characterized by systematic biases relative to observations, which can result in unrealistic interpretations of future climate change signals. On the other hand, bias correction (BC) is a popular statistical post-processing technique applied to improve the usability of output from climate models. Like every other statistical technique, BC has its strengths and weaknesses. Hence, within the regional context of Germany, and for temperature and precipitation, this study is dedicated to the assessment of the impact of different BC techniques on the RCM output. The focuses are on the impact of BC on the RCM’s statistical characterization, and physical consistency defined as the spatiotemporal consistency between the bias-corrected variable and the simulated physical mechanisms governing the variable, as well as the correlations between the bias-corrected variable and other (simulated) climate variables. Five BC techniques were applied in adjusting the systematic biases in temperature and precipitation RCM outputs. The BC techniques are linear scaling, empirical quantile mapping, univariate quantile delta mapping, multivariate quantile delta mapping that considers inter-site dependencies, and multivariate quantile delta mapping that considers inter-variable dependencies (MBCn). The results show that each BC technique adds value in reducing the biases in the statistics of the RCM output, though the added value depends on several factors such as the temporal resolution of the data, choice of RCM, climate variable, region, and the metric used in evaluating the BC technique. Further, the raw RCMs reproduced portions of the observed modes of atmospheric circulation in Western Europe, and the observed temperature, and precipitation meteorological patterns in Germany. After the BC, generally, the spatiotemporal configurations of the simulated meteorological patterns as well as the governing large-scale mechanisms were reproduced.
However, at a more localized spatial scale for the individual meteorological patterns, the BC changed the simulated co-variability of some grids, especially for precipitation. Concerning the co-variability among the variables, a physically interpretable positive correlation was found between temperature and precipitation during boreal winter in both models and observations. For most grid boxes in the study domain and on average, the BC techniques that do not adjust inter-variable dependency did not notably change the simulated correlations between the climate variables. However, depending on the grid box, the (univariate) BC techniques tend to degrade the simulated temporal correlations between temperature and precipitation. Further, MBCn which adjusts biases in inter-variable dependency has the skill to improve the correlations between the simulated variables towards observations.
Characterization of binding properties of ephedrine derivatives to human alpha-1-acid glycoprotein
(2023)
Most drugs, especially those with acidic or neutral moieties, are bound to the plasma protein albumin, whereas basic drugs are preferentially bound to human alpha-1-acid glycoprotein (AGP). The protein binding of the long-established drugs ephedrine and pseudoephedrine, which are used in the treatment of hypotension and colds, has so far only been studied with albumin. Since in a previous study a stereoselective binding of ephedrine and pseudoephedrine to serum but not to albumin was observed, the aim of this study was to check whether the enantioselective binding behavior of ephedrine and pseudoephedrine, in addition to the derivatives methylephedrine and norephedrine, is due to AGP and to investigate the influence of their different substituents and steric arrangement. Discontinuous ultrafiltration was used for the determination of protein binding. Characterization of ligand-protein interactions of the drugs was obtained by saturation transfer difference nuclear magnetic resonance spectroscopy. Docking experiments were performed to analyze possible ligand-protein interactions. The more basic the ephedrine derivative is, the higher is the affinity to AGP. There was no significant difference in the binding properties between the individual enantiomers and the diastereomers of ephedrine and pseudoephedrine.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ∼ 0.20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Non-aureus staphylococci (NAS) are ubiquitous bacteria in livestock-associated environments where they may act as reservoirs of antimicrobial resistance (AMR) genes for pathogens such as Staphylococcus aureus. Here, we tested whether housing conditions in pig farms could influence the overall AMR-NAS burden. Two hundred and forty porcine commensal and environmental NAS isolates from three different farm types (conventional, alternative, and organic) were tested for phenotypic antimicrobial susceptibility and subjected to whole genome sequencing. Genomic data were analysed regarding species identity and AMR gene carriage. Seventeen different NAS species were identified across all farm types. In contrast to conventional farms, no AMR genes were detectable towards methicillin, aminoglycosides, and phenicols in organic farms. Additionally, AMR genes to macrolides and tetracycline were rare among NAS in organic farms, while such genes were common in conventional husbandries. No differences in AMR detection existed between farm types regarding fosfomycin, lincosamides, fusidic acid, and heavy metal resistance gene presence. The combined data show that husbandry conditions influence the occurrence of resistant and multidrug-resistant bacteria in livestock, suggesting that changing husbandry practices may be an appropriate means of limiting the spread of AMR bacteria on farms.
Aim
Global warming is assumed to restructure mountain insect communities in space and time. Theory and observations along climate gradients predict that insect abundance and richness, especially of small‐bodied species, will increase with increasing temperature. However, the specific responses of single species to rising temperatures, such as spatial range shifts, also alter communities, calling for intensive monitoring of real‐world communities over time.
Location
German Alps and pre‐alpine forests in south‐east Germany.
Methods
We empirically examined the temporal and spatial change in wild bee communities and its drivers along two largely well‐protected elevational gradients (alpine grassland vs. pre‐alpine forest), each sampled twice within the last decade.
Results
We detected clear abundance‐based upward shifts in bee communities, particularly in cold‐adapted bumble bee species, demonstrating the speed with which mobile organisms can respond to climatic changes. Mean annual temperature was identified as the main driver of species richness in both regions. Accordingly, and in large overlap with expectations under climate warming, we detected an increase in bee richness and abundance, and an increase in small‐bodied species in low‐ and mid‐elevations along the grassland gradient. Community responses in the pre‐alpine forest gradient were only partly consistent with community responses in alpine grasslands.
Main Conclusion
In well‐protected temperate mountain regions, small‐bodied bees may initially profit from warming temperatures, by getting more abundant and diverse. Less severe warming, and differences in habitat openness along the forested gradient, however, might moderate species responses. Our study further highlights the utility of standardized abundance data for revealing rapid changes in bee communities over only one decade.
Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist searches for polyps. However, there is a potential risk of polyps being missed by the gastroenterologist. Automated detection of polyps helps to assist the gastroenterologist during a colonoscopy. There are already publications examining the problem of polyp detection in the literature. Nevertheless, most of these systems are only used in the research context and are not implemented for clinical application. Therefore, we introduce the first fully open-source automated polyp-detection system scoring best on current benchmark data and implementing it ready for clinical application. To create the polyp-detection system (ENDOMIND-Advanced), we combined our own collected data from different hospitals and practices in Germany with open-source datasets to create a dataset with over 500,000 annotated images. ENDOMIND-Advanced leverages a post-processing technique based on video detection to work in real-time with a stream of images. It is integrated into a prototype ready for application in clinical interventions. We achieve better performance compared to the best system in the literature and score a F1-score of 90.24% on the open-source CVC-VideoClinicDB benchmark.
Cancer is one of the leading causes of death worldwide, with currently assessed chances to develop at least one cancer in a lifetime for about 20%. High cases rates and mortality require the development of new anticancer therapies and treatment strategies. Another important concern is toxicity normally associated with conventional therapy methods, such as chemo- and radiotherapy. Among many proposed antitumoral agents, oncolytic viruses are still one of the promising and fast-developing fields of research with almost a hundred studies published data on over 3000 patients since the beginning of the new millennia.
Among all oncolytic viruses, the Vaccinia virus is arguably one of the safest, with an extremely long and prominent history of use, since it was the one and only vaccine used in the Smallpox Eradication Program in the 1970s. Interestingly enough, it was the first oncolytic virus proven to have tumor tropism in vitro and in vivo in laboratory settings, and this year we can celebrate an unofficial 100th anniversary since the publication of the fact. While being highly immunogenic, Vaccinia virus DNA replication takes place in the cytoplasm of the infected cell, and virus genes never integrate into the host genome. Another advantage of using Vaccinia as an oncolytic agent is its high genome capacity, which allows inserting up to 25 kbps of exogenous genes, thus allowing to additionally arm the virus against the tumor.
Oncolytic virus action consists of two major parts: direct oncolysis and immune activation against the tumor, with the latter being the key to successful treatment. To this moment, preclinical research data are mostly generated in immunocompromised xenograft models, which have hurdles to be properly translated for clinical use. In the first part of the current study, fourteen different recombinant Vaccinia virus strains were tested in two different murine tumor cell lines and corresponding immunocompetent animal models. We found, that Copenhagen backbone Vaccinia viruses while being extremely effective in cell culture, do not show significant oncolytic efficacy in animals. In contrast, several of the LIVP backbone viruses tested (specifically, IL-2 expressing ones) have little replication ability when compared to the Copenhagen strain, but are able to significantly delay tumor growth and prolong survival of the treated animals. We have also noted cytokine related toxicity of the animals to be mouse strain specific.
We have also tested the virus with the highest therapeutic benefit in combination with romidepsin and cyclophosphamide. While the combination with histone deacetylase inhibitor romidepsin did not result in therapeutic benefit in our settings, the addition of cyclophosphamide significantly improved the efficacy of the treatment, at the same time reducing cytokine-associated toxicity of the IL-2 expressing virus.
In the second part of the work, we analyzed the ability of adipose-derived mesenchymal stem cells to serve as a carrier for the oncolytic Vaccinia virus. We showed for the first time that the cells can be infected with the virus and can generate virus progeny. They are also able to survive for a substantially long time and, when injected into the bloodstream of tumor-bearing animals, produce the virus that is colonizing the tumor. Analysis of the systemic distribution of the cells after injection revealed that infected and uninfected cells are not distributed in the same manner, possibly suggesting that infected cells are getting recognized and cleared by an impaired immune system of athymic mice faster than non-infected cells. Despite this, injection of virus-loaded adipose-derived mesenchymal stem cells to human A549 tumor-bearing xenograft mice resulted in rapid tumor regression and reduced virus-related side effects of the treatment when compared to injection of the naked virus.
In conclusion, we have tested two different approaches to augmenting oncolytic Vaccinia virus therapy. First, the combination of recombinant Vaccinia virus expressing IL-2 and cyclophosphamide showed promising results in a syngeneic mouse model, despite the low permissivity of murine cells to the virus. Second, we loaded the oncolytic Vaccinia virus into mesenchymal stem cells and have proven that they can potentially serve as a vehicle for the virus.
In a recent study, we showed in an in vitro murine cerebellar microvascular endothelial cell (cerebEND) model as well as in vivo in rats that Tumor-Treating Fields (TTFields) reversibly open the blood–brain barrier (BBB). This process is facilitated by delocalizing tight junction proteins such as claudin-5 from the membrane to the cytoplasm. In investigating the possibility that the same effects could be observed in human-derived cells, a 3D co-culture model of the BBB was established consisting of primary microvascular brain endothelial cells (HBMVEC) and immortalized pericytes, both of human origin. The TTFields at a frequency of 100 kHz administered for 72 h increased the permeability of our human-derived BBB model. The integrity of the BBB had already recovered 48 h post-TTFields, which is earlier than that observed in cerebEND. The data presented herein validate the previously observed effects of TTFields in murine models. Moreover, due to the fact that human cell-based in vitro models more closely resemble patient-derived entities, our findings are highly relevant for pre-clinical studies.
Physicians play an important role in adapting to and mitigating the adverse health effects of the unfolding climate and ecological crises. To fully harness this potential, future physicians need to acquire knowledge, values, skills, and leadership attributes to care for patients presenting with environmental change-related conditions and to initiate and propel transformative change in healthcare and other sectors of society including, but not limited to, the decarbonization of healthcare systems, the transition to renewable energies and the transformation of transport and food systems. Despite the potential of Planetary Health Education (PHE) to support medical students in becoming agents of change, best-practice examples of mainstreaming PHE in medical curricula remain scarce both in Germany and internationally. The process of revising and updating the Medical Licensing Regulations and the National Competency-based Catalog of Learning Objectives for Medical Education in Germany provided a window of opportunity to address this implementation challenge. In this article, we describe the development and content of national Planetary Health learning objectives for Germany. We anticipate that the learning objectives will stimulate the development and implementation of innovative Planetary Health teaching, learning and exam formats in medical schools and inform similar initiatives in other health professions. The availability of Planetary Health learning objectives in other countries will provide opportunities for cross-country and interdisciplinary exchange of experiences and validation of content, thus supporting the consolidation of Planetary Health learning objectives and the improvement of PHE for all health professionals globally.
Honeybees (Apis mellifera) need their fine sense of taste to evaluate nectar and pollen sources. Gustatory receptors (Grs) translate taste signals into electrical responses. In vivo experiments have demonstrated collective responses of the whole Gr-set. We here disentangle the contributions of all three honeybee sugar receptors (AmGr1-3), combining CRISPR/Cas9 mediated genetic knock-out, electrophysiology and behaviour. We show an expanded sugar spectrum of the AmGr1 receptor. Mutants lacking AmGr1 have a reduced response to sucrose and glucose but not to fructose. AmGr2 solely acts as co-receptor of AmGr1 but not of AmGr3, as we show by electrophysiology and using bimolecular fluorescence complementation. Our results show for the first time that AmGr2 is indeed a functional receptor on its own. Intriguingly, AmGr2 mutants still display a wildtype-like sugar taste. AmGr3 is a specific fructose receptor and is not modulated by a co-receptor. Eliminating AmGr3 while preserving AmGr1 and AmGr2 abolishes the perception of fructose but not of sucrose. Our comprehensive study on the functions of AmGr1, AmGr2 and AmGr3 in honeybees is the first to combine investigations on sugar perception at the receptor level and simultaneously in vivo. We show that honeybees rely on two gustatory receptors to sense all relevant sugars.
Covalent crosslinking of DNA strands provides a useful tool for medical, biochemical and DNA nanotechnology applications. Here we present a light-induced interstrand DNA crosslinking reaction using the modified nucleoside 5-phenylethynyl-2’-deoxyuridine (\(^{Phe}\)dU). The crosslinking ability of \(^{Phe}\)dU was programmed by base pairing and by metal ion interaction at the Watson-Crick base pairing site. Rotation to intrahelical positions was favored by hydrophobic stacking and enabled an unexpected photochemical alkene-alkyne [2+2] cycloaddition within the DNA duplex, resulting in efficient formation of a \(^{Phe}\)dU-dimer after short irradiation times of a few seconds. A \(^{Phe}\)dU dimer-containing DNA was shown to efficiently bind a helicase complex, but the covalent crosslink completely prevented DNA unwinding, suggesting possible applications in biochemistry or structural biology.
[\(^{223}\)Ra]RaCl\(_2\) and [\(^{224}\)Ra]RaCl\(_2\) are bone seekers, emitting high LET, and short range (< 100 μm) alpha-particles. Both radionuclides show similar decay properties; the total alpha energies are comparable (\(^{223}\)Ra: ≈28 MeV, \(^{224}\)Ra: ≈26 MeV). [\(^{224}\)Ra]RaCl\(_2\) has been used from the mid-1940s until 1990 for treating different bone and joint diseases with activities of up to approximately 50 MBq [\(^{224}\)Ra]RaCl\(_2\). In 2013 [\(^{223}\)Ra]RaCl\(_2\) obtained marketing authorization by the FDA and by the European Union for the treatment of metastatic prostate cancer with an activity to administer of 0.055 MBq per kg body weight for six cycles. For intravenous injections in humans a model calculation using the biokinetic model of ICRP67 shows a ratio of organ absorbed dose coefficients (\(^{224}\)Ra:\(^{223}\)Ra) between 0.37 (liver) and 0.97 except for the kidneys (2.27) and blood (1.57). For the red marrow as primary organ-at-risk, the ratio is 0.57. The differences are mainly caused be the differing half-lives of the decay products of both radium isotopes. Both radionuclides show comparable DNA damage patterns in peripheral blood mononuclear cells after internal ex-vivo irradiation. Data on the long-term radiation-associated side effects are only available for treatment with [\(^{224}\)Ra]RaCl\(_2\). Two epidemiological studies followed two patient groups treated with [\(^{224}\)Ra]RaCl\(_2\) for more than 25 years. One of them was the “Spiess study”, a cohort of 899 juvenile patients who received several injections of [\(^{224}\)Ra]RaCl\(_2\) with a mean specific activity of 0.66 MBq/kg. Another patient group of ankylosing spondylitis patients was treated with 10 repeated intravenous injections of [\(^{224}\)Ra]RaCl\(_2\), 1 MBq each, 1 week apart. In total 1,471 of these patients were followed-up in the “Wick study”. In both studies, an increased cancer mortality by leukemia and solid cancers was observed. Similar considerations on long-term effects likely apply to [\(^{223}\)Ra]RaCl\(_2\) as well since the biokinetics are similar and the absorbed doses in the same range. However, this increased risk will most likely not be observed due to the much shorter life expectancy of prostate cancer patients treated with [\(^{223}\)Ra]RaCl\(_2\).
Objectives
Although the vast majority of COVID-19 cases are treated in primary care, patients' experiences during home isolation have been little studied. This study aimed to explore the experiences of patients with acute COVID-19 and to identify challenges after the initial adaptation of the German health system to the pandemic (after first infection wave from February to June 2020).
Methods
A mixed-method convergent design was used to gain a holistic insight into patients experience. The study consisted of a cross-sectional survey, open survey answers and semi-structured telephone interviews. Descriptive analysis was performed on quantitative survey answers. Between group differences were calculated to explore changes after the first infection wave. Qualitative thematic analysis was conducted on open survey answers and interviews. The results were then compared within a triangulation protocol.
Results
A total of 1100 participants from all German states were recruited by 145 general practitioners from August 2020 to April 2021, 42 additionally took part in qualitative interviews. Disease onset varied from February 2020 to April 2021. After the first infection wave, more participants were tested positive during the acute disease (88.8%; 95.2%; P < 0.001). Waiting times for tests (mean 4.5 days, SD 4.1; 2.7days, SD 2.6, P < 0.001) and test results (mean 2.4 days, SD 1.9; 1.8 days, SD 1.3, P < 0.001) decreased. Qualitative results indicated that the availability of repeated testing and antigen tests reduced insecurities, transmission and related guilt. Although personal consultations at general practices increased (6.8%; 15.5%, P < 0.001), telephone consultation remained the main mode of consultation (78.5%) and video remained insignificant (1.9%). The course of disease, the living situation and social surroundings during isolation, access to health care, personal resilience, spirituality and feelings of guilt and worries emerged as themes influencing the illness experience. Challenges were contact management and adequate provision of care during home isolation. A constant contact person within the health system helped against feelings of care deprivation, uncertainty and fear.
Conclusions
Our study highlights that home isolation of individuals with COVID-19 requires a holistic approach that considers all aspects of patient care and effective coordination between different care providers.
Two-dimensional (2D) topological insulators are a new class of materials with properties that are
promising for potential future applications in quantum computers. For example, stanene represents
a possible candidate for a topological insulator made of Sn atoms arranged in a hexagonal
lattice. However, it has a relatively fragile low-energy spectrum and sensitive topology. Therefore,
to experimentally realize stanene in the topologically non-trivial phase, a suitable substrate
that accommodates stanene without compromising these topological properties must be found.
A heterostructure consisting of a SiC substrate with a buffer layer of adsorbed group-III elements
constitutes a possible solution for this problem. In this work, 2D adatom systems of Al and In
were grown epitaxially on SiC(0001) and then investigated structurally and spectroscopically by
scanning tunneling microscopy (STM) and photoelectron spectroscopy.
Al films in the high coverage regime \( (\Theta_{ML}\approx2\) ML\( ) \) exhibit unusually large, triangular- and
rectangular-shaped surface unit cells. Here, the low-energy electron diffraction (LEED)
pattern is brought into accordance with the surface topography derived from STM. Another Al
reconstruction, the quasi-one-dimensional (1D) Al phase, exhibits a striped surface corrugation,
which could be the result of the strain imprinted by the overlayer-substrate lattice mismatch.
It is suggested that Al atoms in different surface areas can occupy hexagonal close-packed and
face-centered cubic lattice sites, respectively, which in turn lead to close-packed transition regions
forming the stripe-like corrugations. On the basis of the well-known herringbone reconstruction
from Au(111), a first structural model is proposed, which fits well to the structural data from
STM. Ultimately, however, thermal treatments of the sample could not generate lower coverage
phases, i.e. in particular, a buffer layer structure.
Strong metallic signatures are found for In high coverage films \( (\Theta_{ML}\approx3\) to \(2\) ML\() \) by
scanning tunneling spectroscopy (STS) and angle-resolved photoelectron spectroscopy (ARPES),
which form a \( (7\times7) \), \( (6\times4\sqrt{3}) \), and \( (4\sqrt{3}\times4\sqrt{3}) \) surface reconstruction. In all these In phases
electrons follow the nearly-free electron model. Similar to the Al films, thermal treatments could
not obtain the buffer layer system.
Surprisingly, in the course of this investigation a triangular In lattice featuring a \( (1\times1) \)
periodicity is observed to host massive Dirac-like bands at \( K/K^{\prime} \) in ARPES. Based on this
strong electronic similarity with graphene at the Brillouin zone boundary, this new structure is
referred to as \textit{indenene}. An extensive theoretical analysis uncovers the emergence of an electronic
honeycomb network based on triangularly arranged In \textit{p} orbitals. Due to strong atomic spin-orbit
coupling and a comparably small substrate-induced in-plane inversion symmetry breaking this
material system is rendered topologically non-trivial. In indenene, the topology is intimately
linked to a bulk observable, i.e., the energy-dependent charge accumulation sequence within the
surface unit cell, which is experimentally exploited in STS to confirm the non-trivial topological
character. The band gap at \( K/K^{\prime} \), a signature of massive Dirac fermions, is estimated by
ARPES to approximately 125 meV. Further investigations by X-ray standing wave, STM, and
LEED confirm the structural properties of indenene. Thus, this thesis presents the growth and
characterization of the novel quantum spin Hall insulator material indenene.
In this in-vitro study, teeth were imaged using photoacoustic tomography (PAT), cone-beam computed tomography (CBCT), and micro-computed tomography (µ-CT). The study had aim: to identify the best wavelength for PAT images to determine the accuracy of the three imaging methods, and to determine whether PAT images of teeth can achieve acceptable reconstruction quality.
Aging is known to be a risk factor for structural abnormalities and functional decline in the nervous system. Characterizing age-related changes is important to identify putative pathways to overcome deleterious effects and improve life quality for the elderly. In this study, the peripheral nervous system of 24-month-old aged C57BL/6 mice has been investigated and compared to 12-month-old adult mice. Aged mice showed pathological alterations in their peripheral nerves similar to nerve biopsies from elderly human individuals, with nerve fibers showing demyelination and axonal damage. Such changes were lacking in nerves of adult 12-month-old mice and adult, non-aged humans. Moreover, neuromuscular junctions of 24-month-old mice showed increased denervation compared to adult mice. These alterations were accompanied by elevated numbers of macrophages in the peripheral nerves of aged mice. The neuroinflammatory conditions were associated with impaired myelin integrity and with a decline of nerve conduction properties and muscle strength in aged mice.
To determine the pathological impact of macrophages in the aging mice, macrophage depletion was performed in mice by oral administration of CSF-1R specific kinase (c-FMS) inhibitor PLX5622 (300 mg/kg body weight), which reduced the number of macrophages in the peripheral nerves by 70%. The treated mice showed attenuated demyelination, less muscle denervation and preserved muscle strength. This indicates that macrophage-driven inflammation in the peripheral nerves is partially responsible for the age-related neuropathy in mice.
Based on previous observations that systemic inflammation can accelerate disease progression in mouse models of neurodegenerative diseases, it was hypothesized that systemic inflammation can exacerbate the peripheral neuropathy found in aged mice. To investigate this hypothesis, aged C57BL/6 mice were intraperitoneally injected with a single dose of lipopolysaccharide (LPS; 500 μg/kg body weight) to induce systemic inflammation by mimicking bacterial infection, mostly via activation of Toll-like receptors (TLRs). Altered endoneurial macrophage activation, highlighted by Trem2 downregulation, was found in LPS injected aged mice one month after injection. This was accompanied by a so far rarely observed form of axonal perturbation, i.e., the occurrence of “dark axons” characterized by a damaged cytoskeleton and an increased overall electron density of the axoplasm. At the same time, however, LPS injection reduced demyelination and muscle denervation in aged mice. Interestingly, TREM2 deficiency in aged mice led to similar changes to LPS injection. This suggests that LPS injection likely mitigates aging-related demyelination and muscle denervation via Trem2 downregulation.
Taken together, this study reveals the role of macrophage-driven inflammation as a pathogenic mediator in age-related peripheral neuropathy, and that targeting macrophages might be an option to mitigate peripheral neuropathies in aging individuals. Furthermore, this study shows that systemic inflammation may be an ambivalent modifier of age-related nerve damage, leading to a distinct type of axonal perturbation, but in addition to functionally counteracting, dampened demyelination and muscle denervation. Translationally, it is plausible to assume that tipping the balance of macrophage polarization to one direction or the other may determine the functional outcome in the aging peripheral nervous system of the elderly.
As central components of life, DNA and RNA encode the genetic information. However, RNA performs several functions that exceed the competences stated in the ‘central dogma of life‘. RNAs undergo extensive post-transcriptional processing like chemical modifications. Among all classes of RNA, tRNAs are the most extensively modified. Their modifications are chemically diverse and vary from simple methylations (e.g. m3C, m6A) to more complex residues, like isopentenyl group (e.g. i6A, hypermodifications: e.g. ms2i6A) or even amino acids (e.g. t6A). Depending on their location within the overall structure, modifications can have an impact on tRNA stability and structure, as well as affinity for the ribosome and translation efficiency and fidelity. Given the importance of tRNA modifications new tools are needed for their detection and to study their recognition by proteins and enzymatic transformations.
The chemical synthesis of these naturally occurring tRNA modifications as phosphoramidite building blocks is a prerequisite to incorporate the desired modification via solid-phase synthesis into oligonucleotides. With the help of the m3C, (ms2)i6A, and t6A oligonucleotides, the importance and impact of tRNA modifications was investigated in this thesis. To this end, the role of METTL8 as the methyltransferase responsible for the installation of the methyl group at C32 for mt-tRNAThr and mt-tRNASer(UCN) was resolved. Thereby, the respective adenosine modification on position 37 is essential for the effectiveness of the enzyme. Besides, by means of NMR analysis, CD spectroscopy, thermal denaturation experiments, and native page separation, the impact of m3C32 on the structure of the tRNA ASLs was shown. The modification appeared to fine-tune the tRNA structure to optimize mitochondrial translation. To investigate the regulation of the dynamic modification pathway of m3C, demethylation assays were performed with the modified tRNA-ASLs and the (α-KG)- and Fe(II)-dependent dioxygenase ALKBH1 and ALKHB3. A demethylation activity of ALKBH3 on the mt-tRNAs was observed, even though it has so far only been described as a cytoplasmic enzyme. Whether this is physiologically relevant and ALKBH3 present a mitochondrial localization needs further validation. In addition, ALKBH1 was confirmed to not be able to demethylate m3C on mt-tRNAs, but indications for a deprenylation and exonuclease activity were found. Furthermore, the aforementioned naturally occurring modifications were utilized to find analytical tools that can determine the modification levels by DNAzymes, which cleave RNA in the presence of a specific modification. Selective DNA enzymes for i6A, as well as the three cytidine isomers m3C, m4C, and m5C have been identified and characterized.
Besides the naturally occurring tRNA modifications, the investigation on artificially modified nucleosides is also part of this thesis. Nucleosides with specific properties for desired applications can be created by modifying the scaffold of native nucleosides.
During the pandemic, the potential of antiviral nucleoside analogues was highlighted for the treatment of the SARS-CoV-2 infection. For examinations of the potential drug-candidate Molnupiravir, the N4-hydroxycytidine phosphoramidite building block was synthesized and incorporated into several RNA oligonucleotides. A two-step model for the NHC-induced mutagenesis of SARS-CoV-2 was proposed based on RNA elongation, thermal denaturation, and cryo-EM experiments using the modified RNA strands with the recombinant SARS-CoV-2 RNA-dependent RNA polymerase. Two tautomeric forms of NHC enable base pairing with guanosine in the amino and with adenosine in the imino form, leading to error catastrophe after the incorporation into viral RNA. These findings were further corroborated by thermal melting curve analysis and NMR spectroscopy of the NHC-containing Dickerson Drew sequence. In conclusion, the anti-amino form in the NHC-G base pair was assigned by NMR analysis using a 15N-labeld NHC building block incorporated into the Dickerson Drew sequence.
This thesis also addressed the synthesis of a 7-deazaguanosine crosslinker with a masked aldehyde as a diol linker for investigations of DNA-protein interactions. The diol functional group can be unmasked to release the reactive aldehyde, which can specifically form a covalent bond with amino acids Lys or Arg within the protein complex condensin. The incorporation of the synthesized phosphoramidite and triphosphate building blocks were shown and the functionality of the PCR product containing the crosslinker was demonstrated by oxidation and the formation of a covalent bond with a fluorescein label.
The development of assays that detect changes in this methylation pattern of m6A could provide new insights into important biological processes. In the last project of this thesis, the influence of RNA methylation states on the structural properties of RNA was analyzed and a fluorescent nucleoside analog (8-vinyladenosine) as molecular tools for such assays was developed. Initial experiments with the fluorescent nucleoside analog N6-methyl-8-vinyladenosine (m6v8A) were performed and revealed a strong fluorescence enhancement of the free m6v8A nucleoside by the installation of the vinyl moiety at position 8.
Overall, this thesis contributes to various research topics regarding the application of naturally occurring and artificial nucleoside analogues. Starting with the chemical synthesis of RNA and DNA modifications, this thesis has unveiled several open questions regarding the dynamic (de-)methylation pathway of m3C and the mechanism of action of molnupiravir through in-depth analysis and provided the basis for further investigations of the protein complex condensin, and a new fluorescent nucleoside analog m6v8A.
Ibrutinib serves as an efficient second-line therapy in relapsed/refractory mantle cell lymphoma. However, resistance to the BTK inhibitor results in a poor prognosis for patients. Since the mechanisms leading to resistance in initially responding tumor cells are poorly understood, this work aimed to decipher acquired features in ibrutinib-surviving cells of a sensitive mantle cell lymphoma cell line and evaluate these potential therapeutic targets in ibrutinib-treated mantle cell lymphoma.
Time-resolved single-cell RNA sequencing was performed to track the transcriptomic evolution of REC-1 cells across 6 and 48 hours of treatment. Single-cell analysis uncovered a subpopulation of REC-1 with potentially greater aggressiveness and survival advantage by benefiting from interaction with the tumor microenvironment. Upregulation of B-cell receptor genes, elevated surface antigen expression of CD52 and metabolic rewiring to higher dependence on oxidative phosphorylation were identified as further potential resistance features of ibrutinib-surviving cells. RNA sequencing after prolonged incubation corroborated the increase in CD52 and oxidative phosphorylation as dominant characteristics of the cells surviving the 4-day treatment, highlighting their potential as therapeutic targets in combination with ibrutinib treatment. Concomitant use of ibrutinib and the oxidative phosphorylation inhibitor IACS-010759 increased toxicity compared to ibrutinib monotherapy due to higher apoptosis and greater inhibition of proliferation. For anti-CD52 therapy, a consecutive approach with ibrutinib pretreatment followed by incubation of surviving cells with a CD52 monoclonal antibody and human serum yielded a synergistic effect, as ibrutinib-surviving mantle cell lymphoma cells were rapidly depleted by complement-dependent cytotoxicity. Regarding the effects on primary tumor cells from mantle cell lymphoma patients, ibrutinib induced upregulation of CD52 in some cases, and increased toxicity of anti-CD52 therapy was observed in ibrutinib-sensitive patient samples after pretreatment with the BTK inhibitor. The likely favorable in vivo efficacy of an anti-CD52 therapy might therefore be restricted to a subgroup of mantle cell lymphoma patients, also in view of the associated side effects.
Given the need for new therapeutic options in mantle cell lymphoma to overcome resistance to ibrutinib, this work highlights the potentially beneficial use of an oxidative phosphorylation inhibitor as add-on therapy. In addition, the findings suggest to further assess the value of anti-CD52 therapy as consolidation to ibrutinib in ibrutinib-sensitive patients with elevated CD52 surface levels on tumor cells to target resistant clones and minimize risk of minimal residual disease and relapse.