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Institute
- Graduate School of Life Sciences (59)
- Theodor-Boveri-Institut für Biowissenschaften (15)
- Institut für Psychologie (7)
- Institut für Informatik (5)
- Institut für Mathematik (5)
- Institut für Organische Chemie (5)
- Institut für Pharmazie und Lebensmittelchemie (5)
- Physikalisches Institut (5)
- Institut für Funktionsmaterialien und Biofabrikation (4)
- Institut für Physikalische und Theoretische Chemie (4)
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (3)
- Department of Mathematical Analysis, Faculty of Mathematics and Physics, Charles University in Prague (1)
- Deutsches Krebsforschungszentrum Heidelberg (1)
- Deutsches Zentrum für Luft- und Raumfahrt e.V. (1)
- European Space Agency (1)
- Experimental Physics V, University of Wuerzburg (1)
- Fraunhofer Insitut für Silicatforschung ISC (1)
- Fraunhofer-Institute for Silicate Research ISC (1)
- Helmholtz Institut für RNA-basierte Infektionsforschung (1)
- LMU München (1)
Over the years, hydrogels have been developed and used for a huge variety of different applications ranging from drug delivery devices to medical products. In this thesis, a poly(2-methyl-2-oxazoline) (POx) / poly(2-n-propyl-2-oxazine) (POzi) bioink was modified and analyzed for the use in biofabrication and targeted drug delivery. In addition, the protein fibrinogen (Fbg) was genetically modified for an increased stability towards plasmin degradation for its use as wound sealant.
In Chapter 1, a thermogelling, printable POx/POzi-based hydrogel was modified with furan and maleimide moieties in the hydrophilic polymer backbone facilitating post-printing maturation of the constructs via Diels-Alder chemistry. The modification enabled long-term stability of the hydrogel scaffolds in aqueous solutions which is necessary for applications in biofabrication or tissue engineering. Furthermore, we incorporated RGD-peptides into the hydrogel which led to cell adhesion and elongated morphology of fibroblast cells seeded on top of the scaffolds. Additional printing experiments demonstrate that the presented POx/POzi system is a promising platform for the use as a bioink in biofabrication.
Chapter 2 highlights the versatility of the POx/POzi hydrogels by adapting the system to a use in targeted drug delivery. We used a bioinspired approach for a bioorthogonal conjugation of insulin-like growth factor I (IGF-I) to the polymer using an omega-chain-end dibenzocyclooctyne (DBCO) modification and a matrix metalloprotease-sensitive peptide linker. This approach enabled a bioresponsive release of IGF-I from hydrogels as well as spatial control over the protein distribution in 3D printed constructs which makes the system a candidate for the use in personalized medicine.
Chapter 3 gives a general overview over the necessity of wound sealants and the current generations of fibrin sealants on the market including advantages and challenges. Furthermore, it highlights trends and potential new strategies to tackle current problems and broadens the toolbox for future generations of fibrin sealants.
Chapter 4 applies the concepts of recombinant protein expression and molecular engineering to a novel generation of fibrin sealants. In a proof-of-concept study, we developed a new recombinant fibrinogen (rFbg) expression protocol and a Fbg mutant that is less susceptible to plasmin degradation. Targeted lysine of plasmin cleavage sites in Fbg were exchanged with alanine or histidine in different parts of the molecule. The protein was recombinantly produced and restricted plasmin digest was analyzed using high resolution mass spectrometry. In addition to that, we developed a novel time resolved screening protocol for the detection of new potential plasmin cleavage sites for further amino acid exchanges in the fibrin sealant.
This thesis investigates the charged moments and the symmetry-resolved
entanglement entropy in the context of the AdS3/CFT2 duality. In the
first part, I focus on the holographic U(1) Chern-Simons-Einstein gravity,
a toy model of AdS3/CFT2 with U(1) Kac-Moody symmetry. I
start with the vacuum background with a single entangling interval. I
show that, apart from a partition function in the grand canonical ensemble,
the charged moments can also be interpreted as the two-point
function of vertex operators on the replica surface. For the holographic
description, I propose a duality between the bulk U(1) Wilson line and
the boundary vertex operators. I verify this duality by deriving the
effective action for the Chern-Simons fields and comparing the result
with the vertex correlator. In the twist field approach, I show that the
charged moments are given by the correlation function of the charged
twist operators and the additional background operators. To solve the
correlation functions involved, I prove the factorization of the U(1) extended
conformal block into a U(1) block and a Virasoro block. The
general expression for the U(1) block is derived by directly summing
over the current descendant states, and the result shows that it takes
an identical form as the vertex correlators. This leads to the conclusion
that the disjoint Wilson lines compute the neutral U(1) block. The final
result for the symmetry-resolved entanglement entropy shows that
it is always charge-independent in this model. In the second part, I
study charged moments in higher spin holography, where the boundary
theory is a CFT with W3 symmetry. I define the notion of the
higher spin charged moments by introducing a spin-3 modular charge
operator. Restricting to the vacuum background with a single entangling
interval, I employ the grand canonical ensemble interpretation
and calculate the charged moments via the known higher spin black
hole solution. On the CFT side, I perform a perturbative expansion for
the higher spin charged moments in terms of the connected correlation
functions of the spin-3 modular charge operators. Using the recursion
relation for the correlation functions of the W3 currents, I evaluate the
charged moments up to the quartic order of the chemical potential. The
final expression matches with the holographic result. My results both
for U(1) Chern-Simons Einstein gravity and W3 higher spin gravity
constitute novel checks of the AdS3/CFT2 correspondence.
Interactions between host and pathogen determine the development, progression and outcomes
of disease. Medicine benefits from better descriptions of these interactions through increased
precision of prevention, diagnosis and treatment of diseases. Single-cell genomics is a
disruptive technology revolutionizing science by increasing the resolution with which we study
diseases. Cell type specific changes in abundance or gene expression are now routinely investigated
in diseases. Meanwhile, detecting cellular phenotypes across diseases can connect
scientific fields and fuel discovery. Insights acquired through systematic analysis of high resolution
data will soon be translated into clinical practice and improve decision making. Therefore,
the continued use of single-cell technologies and their application towards clinical samples will
improve molecular interpretation, patient stratification, and the prediction of outcomes.
In the past years, I was fortunate to participate in interdisciplinary research groups bridging
biology, clinical research and data science. I was able to contribute to diverse projects through
computational analysis and biological interpretation of sequencing data. Together, we were
able to discover cellular phenotypes that influence disease progression and outcomes as well
as the response to treatment. Here, I will present four studies that I have conducted in my PhD.
First, we performed a case study of relapse from cell-based immunotherapy in Multiple Myeloma.
We identified genomic deletion of the epitope as mechanism of immune escape and implicate
heterozygosity or monosomy of the genomic locus at baseline as a potential risk factor. Second,
we investigated the pathomechanisms of severe COVID-19 at the earliest stage of the COVID-
19 pandemic in Germany in March 2020. We discovered that profibrotic macrophages and
lung fibrosis can be caused by SARS-CoV-2 infection. Third, we used a mouse model of chronic
infection with Staphylococcus aureus that causes Osteomyelitis similar to the human disease.
We were able to identify dysregulated immunometabolism associated with the generation of
myeloid-derived suppressor cells (MDSC). Fourth, we investigated Salmonella infection of the
human small intestine in an in vitro model and describe features of pathogen invasion and host
response.
Overall, I have been able to successfully employ single-cell sequencing to discover important
aspects of diseases ranging from development to treatment and outcome. I analyzed samples
from the clinics, human donors, mouse models and organoid models to investigate different
aspects of diseases and managed to integrate data across sample types, technologies and
diseases. Based on successful studies, we increased our efforts to combine data from multiple
sources to build comprehensive references for the integration of large collections of clinical
samples. Our findings exemplify how single-cell sequencing can improve clinical research and
highlights the potential of mechanistic discoveries to drive precision medicine.
African trypanosomes are unicellular parasites that cause nagana and sleeping sickness in livestock and man, respectively. The major pathogens for the animal disease include Trypanosoma vivax, T. congolense, and T. brucei brucei, whereas T. b. gambiense and T. b. rhodesiense are responsible for human infections. Given that the bloodstream form (BSF) of African trypanosomes is exclusively extracellular, its cell surface forms a critical boundary with the host environment. The cell surface of the BSF African trypanosomes is covered by a dense coat of immunogenic variant surface glycoproteins (VSGs). This surface protein acts as an impenetrable shield that protects the cells from host immune factors and is also involved in antibody clearance and antigenic variation, which collectively ensure that the parasite stays ahead of the host immune system. Gene expression in T. brucei is markedly different from other eukaryotes: most genes are transcribed as long polycistronic units, processed by trans-splicing a 39-nucleotide mini exon at the 5′ and polyadenylation at the 3′ ends of individual genes to generate the mature mRNA.
Therefore, gene expression in T. brucei is regulated post-transcriptionally, mainly by the action of RNA binding proteins (RBPs) and conserved elements in the 3′ untranslated regions (UTR) of transcripts. The expression of VSGs is highly regulated, and only a single VSG gene is expressed at a time from one of the ~15 subtelomeric domains termed bloodstream expression sites (BES). When cells are engineered to simultaneously express two VSGs, the total VSG mRNA do not exceed the wild type amounts. This suggests that a robust VSG mRNA balancing mechanism exists in T. brucei. The present study uses inducible and constitutive expression of ectopic VSG genes to show that the endogenous VSG mRNA is regulated only if the second VSG is properly targeted to the ER. Additionally, the endogenous VSG mRNA response is triggered when high amounts of the GFP reporter with a VSG 3′UTR is targeted to the ER. Further evidence that non-VSG ER import signals can efficiently target VSGs to the ER is presented. This study suggests that a robust trans-regulation of the VSG mRNA is elicited at the ER through a feedback loop to keep the VSG transcripts in check and avoid overshooting the secretory pathway capacity.
Further, it was shown that induction of expression of the T. vivax VSG ILDat1.2 in T. brucei causes a dual cell cycle arrest, with concomitant upregulation of the protein associated with differentiation (PAD1) expression. It could be shown that T. vivax VSG ILDat1.2 can only be sufficiently expressed in T. brucei after replacing its native GPI signal peptide with that of a T. brucei VSG. Taken together, these data indicate that inefficient VSG GPI anchoring and expression of low levels of the VSG protein can trigger differentiation from slender BSF to stumpy forms. However, a second T. vivax VSG, ILDat2.1, is not expressed in T. brucei even after similar modifications to its GPI signals. An X-ray crystallography approach was utilized to solve the N-terminal domain (NTD) structure of VSG ILDat1.2. This is first structure of a non-T. brucei VSG, and the first of a surface protein of T. vivax to be solved. VSG ILDat1.2 NTD maintains the three-helical bundle scaffold conserved in T. brucei surface proteins. However, it is likely that there are variations in the architecture of the membrane proximal region of the ILDat1.2 NTD and its CTD from T. brucei VSGs. The tractable T. brucei system is presented as a model that can be used to study surface proteins of related trypanosome species, thus creating avenues for further characterization of trypanosome surface coats.
Among the defense strategies developed in microbes over millions of years, the innate adaptive CRISPR-Cas immune systems have spread across most of bacteria and archaea. The flexibility, simplicity, and specificity of CRISPR-Cas systems have laid the foundation for CRISPR-based genetic tools. Yet, the efficient administration of CRISPR-based tools demands rational designs to maximize the on-target efficiency and off-target specificity. Specifically, the selection of guide RNAs (gRNAs), which play a crucial role in the target recognition of CRISPR-Cas systems, is non-trivial. Despite the fact that the emerging machine learning techniques provide a solution to aid in gRNA design with prediction algorithms, design rules for many CRISPR-Cas systems are ill-defined, hindering their broader applications.
CRISPR interference (CRISPRi), an alternative gene silencing technique using a catalytically dead Cas protein to interfere with transcription, is a leading technique in bacteria for functional interrogation, pathway manipulation, and genome-wide screens. Although the application is promising, it also is hindered by under-investigated design rules. Therefore, in this work, I develop a state-of-art predictive machine learning model for guide silencing efficiency in bacteria leveraging the advantages of feature engineering, data integration, interpretable AI, and automated machine learning. I first systematically investigate the influential factors that attribute to the extent of depletion in multiple CRISPRi genome-wide essentiality screens in Escherichia coli and demonstrate the surprising dominant contribution of gene-specific effects, such as gene expression level. These observations allowed me to segregate the confounding gene-specific effects using a mixed-effect random forest (MERF) model to provide a better estimate of guide efficiency, together with the improvement led by integrating multiple screens. The MERF model outperformed existing tools in an independent high-throughput saturating screen. I next interpret the predictive model to extract the design rules for robust gene silencing, such as the preference for cytosine and disfavoring for guanine and thymine within and around the protospacer adjacent motif (PAM) sequence. I further incorporated the MERF model in a web-based tool that is freely accessible at www.ciao.helmholtz-hiri.de.
When comparing the MERF model with existing tools, the performance of the alternative gRNA design tool optimized for CRISPRi in eukaryotes when applied to bacteria was far from satisfying, questioning the robustness of prediction algorithms across organisms. In addition, the CRISPR-Cas systems exhibit diverse mechanisms albeit with some similarities. The captured predictive patterns from one dataset thereby are at risk of poor generalization when applied across organisms and CRISPR-Cas techniques. To fill the gap, the machine learning approach I present here for CRISPRi could serve as a blueprint for the effective development of prediction algorithms for specific organisms or CRISPR-Cas systems of interest. The explicit workflow includes three principle steps: 1) accommodating the feature set for the CRISPR-Cas system or technique; 2) optimizing a machine learning model using automated machine learning; 3) explaining the model using interpretable AI. To illustrate the applicability of the workflow and diversity of results when applied across different bacteria and CRISPR-Cas systems, I have applied this workflow to analyze three distinct CRISPR-Cas genome-wide screens. From the CRISPR base editor essentiality screen in E. coli, I have determined the PAM preference and sequence context in the editing window for efficient editing, such as A at the 2nd position of PAM, A/TT/TG downstream of PAM, and TC at the 4th to 5th position of gRNAs. From the CRISPR-Cas13a screen in E. coli, in addition to the strong correlation with the guide depletion, the target expression level is the strongest predictor in the model, supporting it as a main determinant of the activation of Cas13-induced immunity and better characterizing the CRISPR-Cas13 system. From the CRISPR-Cas12a screen in Klebsiella pneumoniae, I have extracted the design rules for robust antimicrobial activity across K. pneumoniae strains and provided a predictive algorithm for gRNA design, facilitating CRISPR-Cas12a as an alternative technique to tackle antibiotic resistance.
Overall, this thesis presents an accurate prediction algorithm for CRISPRi guide efficiency in bacteria, providing insights into the determinants of efficient silencing and guide designs. The systematic exploration has led to a robust machine learning approach for effective model development in other bacteria and CRISPR-Cas systems. Applying the approach in the analysis of independent CRISPR-Cas screens not only sheds light on the design rules but also the mechanisms of the CRISPR-Cas systems. Together, I demonstrate that applied machine learning paves the way to a deeper understanding and a broader application of CRISPR-Cas systems.
Cognition refers to the ability to of animals to acquire, process, store and use vital information from the environment. Cognitive processes are necessary to predict the future and reduce the uncertainty of the ever-changing environment. Classically, research on animal cognition focuses on decisive cognitive tests to determine the capacity of a species by the testing the ability of a few individuals. This approach views variability between these tested key individuals as unwanted noise and is thus often neglected. However, inter-individual variability provides important insights to behavioral plasticity, cognitive specialization and brain modularity. Honey bees Apis mellifera are a robust and traditional model for the study of learning, memory and cognition due to their impressive capabilities and rich behavioral repertoire. In this thesis I have applied a novel view on the learning abilities of honey bees by looking explicitly at individual differences in a variety of learning tasks. Are some individual bees consistently smarter than some of her sisters? If so, will a smart individual always perform good independent of the time, the context and the cognitive requirements or do bees show distinct isolated ‘cognitive modules’?
My thesis presents the first comprehensive investigation of consistent individual differences in the cognitive abilities of honey bees. To speak of an individual as behaving consistently, a crucial step is to test the individual multiple times to examine the repeatability of a behavior. I show that free-flying bees remain consistent in a visual discrimination task for three consecutive days. Successively, I explored individual consistency in cognitive proficiency across tasks involving different sensory modalities, contexts and cognitive requirements. I found that free-flying bees show a cognitive specialization between visual and olfactory learning but remained consistent across a simple discrimination task and a complex concept learning task. I wished to further explore individual consistency with respect to tasks of different cognitive complexity, a question that has never been tackled before in an insect. I thus performed a series of four experiments using either visual or olfactory stimuli and a different training context (free-flying and restrained) and tested bees in a discrimination task, reversal learning and negative patterning. Intriguingly, across all these experiments I evidenced the same results: The bees’ performances were consistent across the discrimination task and reversal learning and negative patterning respectively. No association was evidenced between reversal learning and negative patterning. After establishing the existence of consistent individual differences in the cognitive proficiency of honey bees I wished to determine factors which could underlie these differences. Since genetic components are known to underlie inter-individual variability in learning abilities, I studied the effects of genetics on consistency in cognitive proficiency by contrasting bees originating from either from a hive with a single patriline (low genetic diversity) or with multiple patrilines (high genetic diversity). These two groups of bees showed differences in the patterns of individually correlated performances, indicating a genetic component accounts for consistent cognitive individuality. Another major factor underlying variability in learning performances is the individual responsiveness to sucrose solution and to visual stimuli, as evidenced by many studies on restrained bees showing a positive correlation between responsiveness to task relevant stimuli and learning performances. I thus tested whether these relationships between sucrose/visual responsiveness and learning performances are applicable for free-flying bees. Free-flying bees were again subjected to reversal learning and negative patterning and subsequently tested in the laboratory for their responsiveness to sucrose and to light. There was no evidence of a positive relationship between sucrose/visual responsiveness and neither performances of free-flying bees in an elemental discrimination, reversal learning and negative patterning. These findings indicate that relationships established between responsiveness to task relevant stimuli and learning proficiency established in the laboratory with restrained bees might not hold true for a completely different behavioral context i.e. for free-flying bees in their natural environment.
These results show that the honey bee is an excellent insect model to study consistency in cognitive proficiency and to identify the underlying factors. I mainly discuss the results with respect to the question of brain modularity in insects and the adaptive significance of individuality in cognitive abilities for honey bee colonies. I also provide a proposition of research questions which tie in this theme of consistent cognitive proficiency and could provide fruitful areas for future research.
In 2020, cancer was the leading cause of death worldwide, accounting for nearly 10 million deaths. Lung cancer was the most common cancer, with 2.21 million cases per year in both sexes. This non-homogeneous disease is further subdivided into small cell lung cancer (SCLC, 15%) and non-small cell lung cancer (NSCLC, 85%). By 2023, the American Cancer Society estimates that NSCLC will account for 13% of all new cancer cases and 21% of all estimated cancer deaths. In recent years, the treatment of patients with NSCLC has improved with the development of new therapeutic interventions and the advent of targeted and personalised therapies. However, these advances have only marginally improved the five-year survival rate, which remains alarmingly low for patients with NSCLC. This observation highlights the importance of having more appropriate experimental and preclinical models to recapitulate, identify and test novel susceptibilities in NSCLC. In recent years, the Trp53fl/fl KRaslsl-G12D/wt mouse model developed by Tuveson, Jacks and Berns has been the main in vivo model used to study NSCLC. This model mimics ADC and SCC to a certain extent. However, it is limited in its ability to reflect the genetic complexity of NSCLC. In this work, we use CRISPR/Cas9 genome editing with targeted mutagenesis and gene deletions to recapitulate the conditional model. By comparing the Trp53fl/fl KRaslsl- G12D/wt with the CRISPR-mediated Trp53mut KRasG12D, we demonstrated that both showed no differences in histopathological features, morphology, and marker expression. Furthermore, next-generation sequencing revealed a very high similarity in their transcriptional profile. Adeno-associated virus-mediated tumour induction and the modular design of the viral vector allow us to introduce additional mutations in a timely manner. CRISPR-mediated mutation of commonly mutated tumour suppressors in NSCLC reliably recapitulated the phenotypes described in patients in the animal model. Lastly, the dual viral approach could induce the formation of lung tumours not only in constitutive Cas9 expressing animals, but also in wildtype animals. Thus, the implementation of CRISPR genome editing can rapidly advance the repertoire of in vivo models for NSCLC research. Furthermore, it can reduce the necessity of extensive breeding.
Physical regimes characterized by low Mach numbers and steep stratifications pose severe challenges to standard finite volume methods. We present three new methods specifically designed to navigate these challenges by being both low Mach compliant and well-balanced. These properties are crucial for numerical methods to efficiently and accurately compute solutions in the regimes considered.
First, we concentrate on the construction of an approximate Riemann solver within Godunov-type finite volume methods. A new relaxation system gives rise to a two-speed relaxation solver for the Euler equations with gravity. Derived from fundamental mathematical principles, this solver reduces the artificial dissipation in the subsonic regime and preserves hydrostatic equilibria. The solver is particularly stable as it satisfies a discrete entropy inequality, preserves positivity of density and internal energy, and suppresses checkerboard modes.
The second scheme is designed to solve the equations of ideal MHD and combines different approaches. In order to deal with low Mach numbers, it makes use of a low-dissipation version of the HLLD solver and a partially implicit time discretization to relax the CFL time step constraint. A Deviation Well-Balancing method is employed to preserve a priori known magnetohydrostatic equilibria and thereby reduces the magnitude of spatial discretization errors in strongly stratified setups.
The third scheme relies on an IMEX approach based on a splitting of the MHD equations. The slow scale part of the system is discretized by a time-explicit Godunov-type method, whereas the fast scale part is discretized implicitly by central finite differences. Numerical dissipation terms and CFL time step restriction of the method depend solely on the slow waves of the explicit part, making the method particularly suited for subsonic regimes. Deviation Well-Balancing ensures the preservation of a priori known magnetohydrostatic equilibria.
The three schemes are applied to various numerical experiments for the compressible Euler and ideal MHD equations, demonstrating their ability to accurately simulate flows in regimes with low Mach numbers and strong stratification even on coarse grids.
The WHO-designated neglected-disease pathogen Chlamydia trachomatis (CT) is a gram-negative bacterium responsible for the most frequently diagnosed sexually transmitted infection worldwide. CT infections can lead to infertility, blindness and reactive arthritis, among others. CT acts as an infectious agent by its ability to evade the immune response of its host, which includes the impairment of the NF-κB mediated inflammatory response and the Mcl1 pro-apoptotic pathway through its deubiquitylating, deneddylating and transacetylating enzyme ChlaDUB1 (Cdu1). Expression of Cdu1 is also connected to host cell Golgi apparatus fragmentation, a key process in CT infections.
Cdu1 may this be an attractive drug target for the treatment of CT infections. However, a lead molecule for the development of novel potent inhibitors has been unknown so far. Sequence alignments and phylogenetic searches allocate Cdu1 in the CE clan of cysteine proteases. The adenovirus protease (adenain) also belongs to this clan and shares a high degree of structural similarity with Cdu1. Taking advantage of topological similarities between the active sites of Cdu1 and adenain, a target-hopping approach on a focused set of adenain inhibitors, developed at Novartis, has been pursued. The thereby identified cyano-pyrimidines represent the first active-site directed covalent reversible inhibitors for Cdu1. High-resolution crystal structures of Cdu1 in complex with the covalently bound cyano-pyrimidines as well as with its substrate ubiquitin have been elucidated. The structural data of this thesis, combined with enzymatic assays and covalent docking studies, provide valuable insights into Cdu1s activity, substrate recognition, active site pocket flexibility and potential hotspots for ligand interaction. Structure-informed drug design permitted the optimization of this cyano-pyrimidine based scaffold towards HJR108, the first molecule of its kind specifically designed to disrupt the function of Cdu1. The structures of potentially more potent and selective Cdu1 inhibitors are herein proposed.
This thesis provides important insights towards our understanding of the structural basis of ubiquitin recognition by Cdu1, and the basis to design highly specific Cdu1 covalent inhibitors.
This dissertation explores the development and assessment of inhibitory control – a crucial component of executive functions – in young children. Inhibitory control, defined as the ability to suppress inappropriate responses (Verbruggen & Logan, 2008), is essential for adaptable and goal-oriented behavior. The rapid and non-linear development of this cognitive function in early childhood presents unique challenges for accurate assessment. As children age, they often exhibit a ceiling effect in terms of response accuracy (Petersen et al., 2016), underscoring the need to consider response latency as well. Ideally, combining response latency with accuracy could yield a more precise measure of inhibitory control (e.g., Magnus et al., 2019), facilitating a detailed tracking of developmental changes in inhibitory control across a wider age spectrum. The three studies of this dissertation collectively aim to clarify the relationship between response accuracy, response latency, and inhibitory control across different stages of child development. Each study utilizes a computerized Pointing Stroop Task (Berger et al., 2000) to measure inhibitory control, examining the task's validity and the integration of dual metrics for a more comprehensive evaluation.
The first study focuses on establishing the validity of using both response accuracy and latency as indicators of inhibitory control. Utilizing the framework of explanatory item-response modeling (De Boeck & Wilson, 2004), the study revealed how the task characteristics congruency and item position influence both the difficulty level and timing aspects in young children’s responses in the computerized Pointing Stroop task. Further, this study found that integrating response accuracy with latency, even in a basic manner, provides additional insights. Building upon these findings, the second study investigates the nuances of integrating response accuracy and latency, examining whether this approach can account for age-related differences in inhibitory control. It also explores whether response latencies may contain different information depending on the age and proficiency of the children. The study leverages novel and established methodological perspectives to integrate response accuracy and latency into a single metric, showing the potential applicability of different approaches for assessing inhibitory control development. The third study extends the investigation to a longitudinal perspective, exploring the dynamic relationship between response accuracy, latency, and inhibitory control over time. It assesses whether children who achieve high accuracy at an earlier age show faster improvement in response latency, suggesting a non-linear maturation pathway of inhibitory control. The study also examines if the predictive value of early response latency for later fluid intelligence is dependent on the response accuracy level.
Together, these empirical studies contribute to a more robust understanding of the complex interaction between inhibitory control, response accuracy, and response latency, facilitating valid evaluations of cognitive capabilities in children. Moreover, the findings may have practical implications for designing educational strategies and clinical interventions that address the developmental trajectory of inhibitory control. The nuanced approach advocated in this dissertation suggests prioritizing accuracy in assessment and interventions during the early stages of children's cognitive development, gradually shifting the focus to response latency as children mature and secure their inhibitory control abilities.
The focus of this thesis is on analysing a linear stochastic partial differential equation (SPDE) with a bounded domain. The first part of the thesis commences with an examination of a one-dimensional SPDE. In this context, we construct estimators for the parameters of a parabolic SPDE based on discrete observations of a solution in time and space on a bounded domain. We establish central limit theorems for a high-frequency asymptotic regime, showing substantially smaller asymptotic variances compared to existing estimation methods. Moreover, asymptotic confidence intervals are directly feasible. Our approach builds upon realized volatilities and their asymptotic illustration as the response of a log-linear model with a spatial explanatory variable. This yields efficient estimators based on realized volatilities with optimal rates of convergence and minimal variances. We demonstrate our results by Monte Carlo simulations.
Extending this framework, we analyse a second-order SPDE model in multiple space dimensions in the second part of this thesis and develop estimators for the parameters of this model based on discrete observations in time and space on a bounded domain. While parameter estimation for one and two spatial dimensions was established in recent literature, this is the first work that generalizes the theory to a general, multi-dimensional framework. Our methodology enables the construction of an oracle estimator for volatility within the underlying model. For proving central limit theorems, we use a high-frequency observation scheme. To showcase our results, we conduct a Monte Carlo simulation, highlighting the advantages of our novel approach in a multi-dimensional context.
Two-dimensional lattices are in the focus of research in modern solid state physics due to their novel and exotic electronic properties with tremendous potential for seminal future applications. Of particular interest within this research field are quantum spin Hall insulators which are characterized by an insulating bulk with symmetry-protected metallic edge states. For electrons within these one-dimensional conducting channels, spin-momentum locking enables dissipationless transport - a property which promises nothing short of a revolution for electronic devices. So far, however, quantum spin Hall materials require enormous efforts to be realized such as cryogenic temperatures or ultra-high vacuum. A potential candidate to overcome these shortcomings are two-dimensional lattices of the topological semi-metal antimony due to their potential to host the quantum spin Hall effect while offering improved resilience against oxidation.
In this work, two-dimensional lattices of antimony on different substrates, namely Ag(111), InSb(111) and SiC(0001), are investigated regarding their atomic structure and electronic properties with complimentary surface sensitive techniques. In addition, a systematic oxidation study compares the stability of Sb-SiC(0001) with that of the two-dimensional topological insulators bismuthene-SiC(0001) and indenene-SiC(0001).
A comprehensive experimental analysis of the \((\sqrt{3}\times\sqrt{3})R30^\circ\) Sb-Ag(111) surface, including X-ray standing wave measurements, disproves the proclaimed formation of a buckled antimonene lattice in literature. The surface lattice can instead be identified as a metallic Ag\(_2\)Sb surface alloy.
Antimony on InSb(111) shows an unstrained Volmer-Weber island growth due to its large lattice mismatch to the substrate. The concomitant moir\'{e} situation at the interface imprints mainly in a periodic height corrugation of the antimony islands which as observed with scanning tunneling microscopy. On islands with various thicknesses, quasiparticle interference patterns allow to trace the topological surface state of antimony down to the few-layer limit.
On SiC(0001), two different two-dimensional antimony surface reconstructions are identified. Firstly, a metallic triangular $1\times1$ lattice which constitutes the antimony analogue to the topological insulator indenene. Secondly, an insulating asymmetric kagome lattice which represents the very first realized atomic surface kagome lattice.
A comparative, systematic oxidation study of elemental (sub-)monolayer materials on SiC(0001) reveals a high sensitivity of indenene and bismuthene to small dosages of oxygen. An improved resilience is found for Sb-SiC(0001) which, however, oxidizes nevertheless if exposed to oxygen. These surface lattices are therefore not suitable for future applications without additional protective measures.
In this thesis, a variety of Fokker--Planck (FP) optimal control problems are investigated. Main emphasis is put on a first-- and second--order analysis of different optimal control problems, characterizing optimal controls, establishing regularity results for optimal controls, and providing a numerical analysis for a Galerkin--based numerical scheme.
The Fokker--Planck equation is a partial differential equation (PDE) of linear parabolic type deeply connected to the theory of stochastic processes and stochastic differential equations. In essence, it describes the evolution over time of the probability distribution of the state of an object or system of objects under the influence of both deterministic and stochastic forces.
The FP equation is a cornerstone in understanding and modeling phenomena ranging from the diffusion and motion of molecules in a fluid to the fluctuations in financial markets.
Two different types of optimal control problems are analyzed in this thesis. On the one hand, Fokker--Planck ensemble optimal control problems are considered that have a wide range of applications in controlling a system of multiple non--interacting objects. In this framework, the goal is to collectively drive each object into a desired state.
On the other hand, tracking--type control problems are investigated, commonly used in parameter identification problems or stemming from the field of inverse problems.
In this framework, the aim is to determine certain parameters or functions of the FP equation, such that the resulting probability distribution function takes a desired form, possibly observed by measurements.
In both cases, we consider FP models where the control functions are part of the drift, arising only from the deterministic forces of the system. Therefore, the FP optimal control problem has a bilinear control structure.
Box constraints on the controls may be present, and the focus is on time--space dependent controls for ensemble--type problems and on only time--dependent controls for tracking--type optimal control problems.
In the first chapter of the thesis, a proof of the connection between the FP equation and stochastic differential equations is provided. Additionally, stochastic optimal control problems, aiming to minimize an expected cost value, are introduced, and the corresponding formulation within a deterministic FP control framework is established.
For the analysis of this PDE--constrained optimal control problem, the existence, and regularity of solutions to the FP problem are investigated. New $L^\infty$--estimates for solutions are established for low space dimensions under mild assumptions on the drift. Furthermore, based on the theory of Bessel potential spaces, new smoothness properties are derived for solutions to the FP problem in the case of only time--dependent controls. Due to these properties, the control--to--state map, which associates the control functions with the corresponding solution of the FP problem, is well--defined, Fréchet differentiable and compact for suitable Lebesgue spaces or Sobolev spaces.
The existence of optimal controls is proven under various assumptions on the space of admissible controls and objective functionals. First--order optimality conditions are derived using the adjoint system. The resulting characterization of optimal controls is exploited to achieve higher regularity of optimal controls, as well as their state and co--state functions.
Since the FP optimal control problem is non--convex due to its bilinear structure, a first--order analysis should be complemented by a second--order analysis.
Therefore, a second--order analysis for the ensemble--type control problem in the case of $H^1$--controls in time and space is performed, and sufficient second--order conditions are provided. Analogous results are obtained for the tracking--type problem for only time--dependent controls.
The developed theory on the control problem and the first-- and second--order optimality conditions is applied to perform a numerical analysis for a Galerkin discretization of the FP optimal control problem. The main focus is on tracking-type problems with only time--dependent controls. The idea of the presented Galerkin scheme is to first approximate the PDE--constrained optimization problem by a system of ODE--constrained optimization problems. Then, conditions on the problem are presented such that the convergence of optimal controls from one problem to the other can be guaranteed.
For this purpose, a class of bilinear ODE--constrained optimal control problems arising from the Galerkin discretization of the FP problem is analyzed. First-- and second--order optimality conditions are established, and a numerical analysis is performed. A discretization with linear finite elements for the state and co--state problem is investigated, while the control functions are approximated by piecewise constant or piecewise quadratic continuous polynomials. The latter choice is motivated by the bilinear structure of the optimal control problem, allowing to overcome the discrepancies between a discretize--then--optimize and optimize--then--discretize approach. Moreover, second--order accuracy results are shown using the space of continuous, piecewise quadratic polynomials as the discrete space of controls. Lastly, the theoretical results and the second--order convergence rates are numerically verified.
This work presents the first ILT observations of high redshift blazars and their study in terms of jet evolution, morphology, and interaction with the surrounding medium. Each of these represents a highly topical area of astronomywith a large number of open questions. To better understand Active Galactic Nuclei (AGN) and their fundamental inner workings, new techniques are needed to exploit the full potential of the next generation of radio interferometers. Some of these tools are presented here and applied to one of the latest generation of software radio telescopes. A major focus of the studies presented is on the unification model, where the observed blazars are discussed for their properties to be rotated counterparts of Fanaroff-Riley Class II (FR-II) radio galaxies, when classified as Flat Spectrum Radio Quasars (FSRQs). In addition, multiwavelength information has been included in the analysis. Both studies are feasibility studies that will serve as a basis for future similar studies. The characteristics discussed and their interpretation do not allow conclusions to be drawn for their respective populations. However, by applying them to a larger number of targets, population studies will be possible. The first chapters introduce the necessary topics, AGN, principles of radio observations and ILT, in the necessary depth to provide the reader with a solid knowledge base. They are particularly important for understanding the current limits and influences of uncertainties in the observation, calibration and imaging process. But they also shed light on realistic future improvements. A particular focus is on the development and evolution of the LOw-Frequency ARray (LOFAR)-Very Long Baseline Interferometry (VLBI) pipeline. With the tools at hand, the first study addresses the high redshift blazar S5 0836+710 $(z=2.218)$, which has been observed at various wavelengths and resolutions. It has a disrupted one-sided jet with an associated extended region further out. Despite the excellent wavelength coverage, only the additional ILT observations provided a complete picture of the source. With the data, the extended region could be classified as a hotspot moving at slightly relativistic speeds.. With the ILT data it was also possible to extract the flux of the core region of the AGN, and in projection to reveal the mixed counter-hotspot behind it. This also allowed constraints on jet parameters and environmental properties to be modelled, which were previously inconclusive. Technically, this study shows that the ILT can be used as an effective VLBI array for compact sources with small angular scales. However, the detection of faint components beyond redshifts of $z=2$ may require the capabilities of the Square Kilometre Array (SKA) to provide a significant number of detections to enable statistical conclusions. The second study uses a much improved calibration pipeline to analyse the high redshift blazar GB1508+5714 $(z=4.30)$. The ILT data revealed a previously unseen component in the eastern direction. A spectral index map was generated from the Karl G. Jansky Very Large Array (VLA) data, showing spectral index values of $-1.2_{-0.2}^{+0.4}$ for the western component, steeper than $-1.1$ for the eastern region, and $0.023 \pm 0.007$ for the core. Using the information provided by the ILT observation, as well as multi-wavelength information from other observations ranging from the long radio wavelengths to the $\gamma$ regime, four models were developed to interpret the observed flux with different emission origins. This also allowed to test a proposed interaction channel of the electrons provided by the jet, to cool off via inverse compton scattering with the Cosmic Microwave Background (CMB) photons, rather than by the usual synchrotron emission. This is referred to as cmb quenching in the literature, which could be shown in the study, to be necessary in any case. Finally, one of the four models was considered in which the hotspots in the detected components are unresolved and mixed by the lobe emission, with the X-ray emission coming from the lobes and partially mixed by the bright core region. The results of this preferred model are consistent with hotspots in a state of equipartition and lobes almost so. The study shows that high redshift blazars can be studied with the ILT, and expanding the sample of high redshift blazars resolved at multiple frequencies will allow a statistical study of the population. Finally, this work successfully demonstrates the powerful capabilities of the ILT to address questions that were previously inaccessible. The current state of the LOFAR-VLBI pipeline, when properly executed, allows work on the most challenging objects and will only improve in the future. In particular, this gives a glimpse of the possibilities that SKA will bring to astronomy.
Helically Twisted Graphene Nanoribbons: Bottom-up Stereospecific Synthesis and Characterization
(2024)
Over the past decade, substantial progress has been made in synthesizing atomically precise carbon nanostructures, with a focus on graphene nanoribbons (NRs) through advanced synthetic techniques. Despite these advancements, precise control over the stereochemistry of twisted NRs remains challenging. This thesis introduces a strategic approach to achieve absolute control over the single-handed helical conformation in a cove-edged NR, utilizing enantiopure [n]helicenes as a molecular wrench to intricately dictate the overall conformation of the NR.
Enantiopure [7]helicenes were stitched to the terminal K-regions of a conjugated pyrene NR using a stereospecific and site-selective palladium(II)-catalyzed annulative π-extension (APEX) reaction, resulting in a helically twisted NR with an end-to-end twist of 171°, the second-largest twist reported so far in the literature for twistacenes. The helical end-to-end twist increases with each addition of benzene ring to the central acene core, suggesting that the extra strain induced by the terminal [7]helicenes maintains such a high level of twist.
The quantum chemical calculations were conducted to investigate the impact of twisting on the conformational population. At room temperature, the central backbone of the nanoribbon adopts the twisted helicity opposite to that of the attached [7]helicene, constituting around 99% of the molecular population. For instance, (P)-[7]helicenes produce a left-handed helical nanoribbon, while (M)-[7]helicenes produce a right-handed helical nanoribbon. In the presence of helicenes of opposite chirality, the nanoribbon adopts a waggling conformation. The helically twisted nanoribbons are conformationally robust, as variable temperature chiroptical measurements showed no change in CD and CPL spectra. The proposed strategy, involving the late-stage addition of [n]helicene units through the APEX reaction, appears promising for streamlining the synthesis of diverse cove edge NR variants with desired conformations.
In addition to single-handed helically twisted nanoribbons, the symmetry-based functional properties of C2 and C1 symmetric pyrene-fused single and double [n]helicene compounds were studied. Owing to its higher structural rigidity, the C1 symmetric heptagonal ring-containing molecules exhibited exceptional configurational stability along with remarkable chiroptical properties compared to their C2 symmetric as well as pristine helicene congeners.
The goal of this thesis was to investigate the influence of rotational restriction between individual parts and of the varying electron density in the bridging unit of D B A systems on the exchange interaction 2J, and thus the electronic coupling between a donor state and an acceptor state. A better understanding of how to influence the underlaying spin dynamics in such donor acceptor systems can open up the door to new technologies, such as modern molecular electronics or optoelectronic devices.
Therefore, three series of molecules consisting of a TAA electron donor, a TTC or ATC bridging unit and a PDI electron acceptor were studied. To investigate the influence of rotational restriction on 2J and the electronic coupling, a series of four rotationally hindered triads (chapter 6) was synthesised. The dihedral angle between the TAA and the TTC as well as between the TTC and the PDI was restricted by ortho methyl groups at the phenylene linkers of the connecting ends to the TTC bridge, producing a twist around the linking single bond which minimises the π overlap. The triads exhibit varying numbers of ortho methyl groups and therefore different degrees of rotational restriction. In order to shine light on the influence of varying electron density on 2J and the electronic coupling, a series of four substituted triptycene triads (chapter 7) was synthesised. The electron density in the TTC bridging unit was varied by electron donating and electron withdrawing groups in 12,13 position of the TTC bridging unit and thus varying its HOMO/LUMO energy. The last series of two anthracene bridge triads (chapter 8) connected both approaches by restricting the rotation with ortho methyl groups and simultaneously by varying the bridge energies.
In order to obtain the electronic properties, steady state absorption and emission spectra of all triads were investigated (chapter 4). Here, all triads show spectral features associated with the separate absorption bands of TAA and the PDI moiety. The reduced QYs, compared to the unsubstituted PDI acceptor, indicate a non radiative quenching mechanism in all triads. The CV data (chapter 5) were used to calculate the energies of possible CSSs and those results were used to assign the CR dynamics into the different Marcus regions. fs TA measurements reveal that all triads form a CSS upon excitation of the PDI moiety. The lifetimes of the involved states and the rate constants were determined by global exponential fits and global target analysis. The CR dynamics upon depopulation of the CSSs were investigated using external magnetic field dependent ns TA spectroscopy. The ns TA maps show that all triads recombine via CRT pathway populating the local 3PDI state in toluene and provided the respective lifetimes. The approximate QYs of triplet formation were determined using actinometry. The magnetic field dependent ns TA data reveal the exchange interaction 2J between singlet and triplet CSS for each triad. Those magnetic field dependent ns TA data in toluene were furthermore treated using a quantum mechanical simulation (done by U.E. Steiner) to extract the rate constants kT and kS for CRT and CRS, respectively. However, the error margins of kS were rather wide. Finally, the electronic couplings between the donor and the acceptor states were obtained by combining the aforementioned experimental results of the rate constants and applying the Bixon Jortner theoretical description of diabatic ET and Andersons perturbative theory of the exchange coupling. Therefore, the experimentally determined values of 2J and the calculated values of kCS and kT were used. The rate constant kS was calculated based on the electronic coupling V1CSS 1S0.
The rotationally hindered triads (chapter 6) show a strong influence of the degree of rotational restriction on the lifetimes and rate constants of the CS processes. The rate constants of CS are increasing with increasing rotational freedom. The magnetic field dependent decay data show that the exchange interactions increase with increasing rotational freedom. Based on the CR dynamics, the calculated electronic couplings of the ET processes reflect the same trend along the series. Here, only singlet couplings turned out to be strongly influenced while the triplet couplings are not. Therefore, this series shows that the ET dynamics of donor acceptor systems can strongly be influenced by restricting the rotational freedom.
In the substituted triptycene triads (chapter 7), decreasing electron density in the bridging unit causes a decrease of the CS rate constants. The magnetic field dependent decay data show that with decreasing electron density in the bridge the exchange interaction decreases. The CR dynamics-based rate constants and the electronic couplings follow the same trend as the exchange interaction. This series shows that varying the HOMO/LUMO levels of the connecting bridge between donor and acceptor strongly influences the ET processes.
In the anthracene bridge triads (chapter 8), the CS process is slow in both triads. The CR was fast in the anthracene triad and is slowed down in the methoxy substituted anthracene bridge triad. The increase of the exchange interaction with increasing electron density in the bridge was more pronounced than in the substituted triptycene triads. Thus, the variation of electron density in the bridge strongly influences the ET processes even though the rotation is restricted.
In this thesis, it was shown that the influence of the rotational hindrance as well as the electron density in a connecting bridge have strong influence on all ET processes and the electronic coupling in donor acceptor systems. These approaches can therefore be used to modify magnetic properties of new materials.
In a world of constant change, uncertainty has become a daily challenge for businesses. Rapidly shifting market conditions highlight the need for flexible responses to unforeseen events. Operations Management (OM) is crucial for optimizing business processes, including site planning, production control, and inventory management. Traditionally, companies have relied on theoretical models from microeconomics, game theory, optimization, and simulation. However, advancements in machine learning and mathematical optimization have led to a new research field: data-driven OM.
Data-driven OM uses real data, especially time series data, to create more realistic models that better capture decision-making complexities. Despite the promise of this new research area, a significant challenge remains: the availability of extensive historical training data. Synthetic data, which mimics real data, has been used to address this issue in other machine learning applications.
Therefore, this dissertation explores how synthetic data can be leveraged to improve decisions for data-driven inventory management, focusing on the single-period newsvendor problem, a classic stochastic optimization problem in inventory management.
The first article, "A Meta Analysis of Data-Driven Newsvendor Approaches", presents a standardized evaluation framework for data-driven prescriptive approaches, tested through a numerical study. Findings suggest model performance is not robust, emphasizing the need for a standardized evaluation process.
The second article, "Application of Generative Adversarial Networks in Inventory Management", examines using synthetic data generated by Generative Adversarial Networks (GANs) for the newsvendor problem. This study shows GANs can model complex demand relationships, offering a promising alternative to traditional methods.
The third article, "Combining Synthetic Data and Transfer Learning for Deep Reinforcement Learning in Inventory Management", proposes a method using Deep Reinforcement Learning (DRL) with synthetic and real data through transfer learning. This approach trains a generative model to learn demand distributions, generates synthetic data, and fine-tunes a DRL agent on a smaller real dataset. This method outperforms traditional approaches in controlled and practical settings, though further research is needed to generalize these findings.
Plants are able to sense mechanical forces in order to defend themselves against predators,
for instance by synthesizing repellent compounds. Very few plants evolved extremely sensitive
tactile abilities that allow them to perceive, interpret and respond by rapid movement in the
milliseconds range. One such rarity is the charismatic Venus flytrap (Dionaea muscipula) - a
carnivorous plant which relies on its spectacular active trapping strategy to catch its prey. The
snapping traps are equipped with touch-specialised trigger hairs, that upon bending elicit an
action potential (AP). This electrical signal originates within the trigger hairs’ mechanosensory
cells and further propagates throughout the whole trap, alerting the plant of potential prey.
Two APs triggered within thirty seconds will set off the trap and more than five APs will
initiate the green stomach formation for prey decomposition and nutrient uptake. Neither
the molecular components of the plant’s AP nor the Venus flytrap’s fast closure mechanism
have been fully elucidated yet. Therefore, the general objective of this study is to expound
on the molecular basis of touch perception: from AP initiation to trap closure and finally to
stomach formation.
The typical electrical signal in plants lasts for minutes and its shape is determined by the
intensity of the mechanical force applied. In contrast, the Venus flytrap’s one-second AP is of
all-or-nothing type, similar in shape to the animal AP. In order to gain more insight into the
molecular components that give rise to the Venus flytrap’s emblematic AP, the transcriptomic
landscape of its unique mechanotransducer - the trigger hair – was compared to the rest
of the non-specialised tissues and organs. Additionally, the transcriptome of the electrically
excitable fully-developed adult trap was compared to non-excitable juvenile traps that are
unable to produce sharp APs. Together, the two strategies helped with the identification of
electrogenic channels and pumps for each step of the AP as follows: (1) the most specific to
the trigger hair was the mechanosensitive channel DmMSL10, making up the best candidate for
the initial AP depolarization phase, (2) the K+ outward rectifier DmSKOR could be responsible
for repolarisation, (3) further, the proton pump DmAHA4, might kick in during repolarisation
and go on with hyperpolarisation and (4) the hyperpolarization- and acid-activated K+ inward
rectifier KDM1 might contribute to the re-establishment of electrochemical gradient and
the resting potential. Responsible for the AP-associated Ca2+ wave and electrical signal
propagation, the glutamate-like receptor DmGLR3.6 was also enriched in the trigger hairs.
Together, these findings suggest that the reuse of genes involved in electrical signalling in
ordinary plants can give rise to the Venus flytrap’s trademark AP.
The Venus flytrap has been cultivated ever since its discovery, generating more than one
hundred cultivars over the years. Among them, indistinguishable from a normal Venus flytrap
at first sight, the ’ERROR’ cultivar exhibits a peculiar behaviour: it is unable to snap its traps
upon two APs. Nevertheless, it is still able to elicit normal APs. To get a better understanding
of the key molecular mechanisms and pathways that are essential for a successful trap closure,
the ’ERROR’ mutant was compared to the functional wild type.
Timelapse photography led to the observation that the ’ERROR’ mutants were able to leisurely
half close their traps when repeated mechanostimulation was applied (10 minutes after 20
APs, 0.03 Hz). As a result of touch or wounding in non-carnivorous plants, jasmonic acid
(JA) is synthesized, alerting the plants of potential predators. Curiously, the JA levels were reduced upon mechanostimulation and completely impaired upon wounding in the ’ERROR’
mutant. In search of genes accountable for the ’ERROR’ mutant’s defects, the transcriptomes
of the two phenotypes were compared before and after mechanostimulation (1h after 10
APs, 0.01 Hz). The overall dampened response of the mutant compared to the wild type,
was reflected at transcriptomic level as well. Only about 50% of wild type’s upregulated
genes after touch stimulation were differentially expressed in ’ERROR’ and they manifested
only half of the wild type’s expression amplitude. Among unresponsive functional categories
of genes in ’ERROR’ phenotype, there were: cell wall integrity surveilling system, auxin
biosynthesis and stress-related transcription factors from the ethylene-responsive AP2/ERF and
C2H2-ZF families. Deregulated Ca2+-decoding as well as redox-related elements together with
JA-pathway components might also contribute to the malfunctioning of the ’ERROR’ mutant. As
the mutant does not undergo full stomach formation after mechanical treatment, these missing
processes represent key milestones that might mediate growth-defence trade-offs under JA
signalling. This confirms the idea that carnivory has evolved by recycling the already available
molecular machineries of the ubiquitous plant immune system.
To better understand the mutant’s defect in the trap snapping mechanism, the ground states
(unstimulated traps) of the two phenotypes were compared. In this case, many cell wall-related
genes (e.g. expansins) were downregulated in the ’ERROR’ mutant. For the first time, these
data point to the importance of a special cell wall architecture of the trap, that might confer
the mechanical properties needed for a functional buckling system - which amplifies the speed
of the trap closure.
This study provides candidate channels for each of the AP phases that give rise to and shape
the sharp Venus flytrap-specific AP. It further underlines the possible contribution of the cell
wall architecture to the metastable ready-to-snap configuration of the trap before stimulation
- which might be crucial for the buckling-dependent snapping. And finally, it highlights
molecular milestones linked to defence responses that ensure trap morphing into a green
stomach after mechanostimulation. Altogether, these processes prove to be interdependent
and essential for a successful carnivorous lifestyle.
Colorectal Cancer (CRC) is the third most common cancer in the US. The majority of CRC cases are due to deregulated WNT-signalling pathway. These alterations are mainly caused by mutations in the tumour suppressor gene APC or in CTNNB1, encoding the key effector protein of this pathway, β-Catenin. In canonical WNT-signalling, β-Catenin activates the transcription of several target genes, encoding for proteins involved in proliferation, such as MYC, JUN and NOTCH. Being such a critical regulator of these proto-oncogenes, the stability of β-Catenin is tightly regulated by the Ubiquitin-Proteasome System. Several E3 ligases that ubiquitylate and degrade β-Catenin have been described in the past, but the antagonists, the deubiquitylases, are still unknown. By performing an unbiased siRNA screen, the deubiquitylase USP10 was identified as a de novo positive regulator of β-Catenin stability in CRC derived cells. USP10 has previously been shown in the literature to regulate both mutant and wild type TP53 stability, to deubiquitylate NOTCH1 in endothelial cells and to be involved in the regulation of AMPKα signalling. Overall, however, its role in colorectal tumorigenesis remains controversial. By analysing publicly available protein and gene expression data from colorectal cancer patients, we have shown that USP10 is strongly upregulated or amplified upon transformation and that its expression correlates positively with CTNNB1 expression. In contrast, basal USP10 levels were found in non-transformed tissues, but surprisingly USP10 is upregulated in intestinal stem cells. Endogenous interaction studies in CRC-derived cell lines, with different extend of APCtruncation, revealed an APC-dependent mode of action for both proteins. Furthermore, by utilising CRISPR/Cas9, shRNA-mediated knock-down and overexpression of USP10, we could demonstrate a regulation of β-Catenin stability by USP10 in CRC cell lines. It is widely excepted that 2D cell culture systems do not reflect complexity, architecture and heterogeneity and are therefore not suitable to answer complex biological questions. To overcome this, we established the isolation, cultivation and genetically modification of murine intestinal organoids and utilised this system to study Usp10s role ex vivo. By performing RNA sequencing, dependent on different Usp10 levels, we were able to recapitulate the previous findings and demonstrated Usp10 as important regulator of β-dependent regulation of stem cell homeostasis. Since genetic depletion of USP10 resulted in down-regulation of β-Catenin-dependent transcription, therapeutic intervention of USP10 in colorectal cancer was also investigated. Commercial and newly developed inhibitors were tested for their efficacy against USP10, but failed to significantly inhibit USP10 activity in colorectal cancer cells. To validate the findings from this work also in vivo, development of a novel mouse model for colorectal cancer has begun. By combining CRISPR/Cas9 and classical genetic engineering with viral injection strategies, WT and genetically modified mice could be transformed and, at least in some animals, intestinal lesions were detectable at the microscopic level. The inhibition of USP10, which we could describe as a de novo tumour-specific regulator of β-Catenin, could become a new therapeutic strategy for colorectal cancer patients.
In this thesis, a model system of a magnetic topological heterostructure is studied, namely a heterosystem consisting of a single ferromagnetic septuple-layer (SL) of \(MnBi_2Te_4\) on the surface of the three-dimensional topological insulator \(Bi_2Te_3\).
Using MBE and developing a specialized experimental setup, the first part of this thesis deals with the growth of \(Bi_2Te_3\) and thin films of \(MnBi_2Te_4\) on \(BaF_2\)-substrates by the co-evaporation of its binary constituents. The structural analysis is conducted along several suitable probes such as X-ray diffraction (XRD, XRR), AFM and scanning tunnelling electron microscopy (STEM). It is furthermore found that the growth of a single septuple-layer of \(MnBi_2Te_4\) on the surface of \(Bi_2Te_3\) can be facilitated.
By using X-ray absorption and circular magnetic dichroism (XAS, XMCD), the magnetic properties of \(MnBi_2Te_4\) are explored down to the monolayer limit. The layered nature of the vdW crystal and a strong uniaxial magnetocrystalline anisotropy establish stable out-of plane magnetic order at the surface of \(MnBi_2Te_4\), which is stable even down to the 2D limit. Pushing the material system to there, i.e. a single SL \(MnBi_2Te_4\) further allows to study the phase transition of this 2D ferromagnet and extract its critical behaviour with \(T_c \, = \, 14.89~k\) and \(\beta \, = \, 0.484\).
Utilizing bulk crystals of the ferromagnetic \(Fe_3GeTe_2\) as substrate allows to influence, enhance and bias the magnetism in the single SL of \(MnBi_2Te_4\). By growing heterostructures of the type \(MnBi_2Te_4\) -- n layer \(Bi_2Te_3\) -- \(Fe_3GeTe_2\)for n between 0 and 2, it is shown, that a considerable magnetic coupling can be introduced between the \(MnBi_2Te_4\) top-layer and the substrate.
Finally the interplay between topology and magnetism in the ferromagnetic extension is studied directly by angle-resolved photoemission spectroscopy. The heterostructure is found to host a linearly dispersing TSS at the centre of the Brillouin zone. Using low temperature and high-resolution ARPES a large magnetic gap opening of \(\sim\) 35 meV is found at the Dirac point of the TSS. By following its temperature evolution, it is apparent that the scaling behaviour coincides with the magnetic order parameter of the modified surface.