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This dissertation focuses on Mip (macrophage infectivity potentiator protein) inhibitors in response to increasing antibiotic resistance. The study follows an antivirulence approach, which aims to inhibit the non-essential Mip protein without exerting too much selective pressure. Three focus areas were (1) development and synthesis of a fluorescent probe for screening Mip inhibitors via fluorescence polarization; (2) design and synthesis of broad spectrum Mip inhibitors bearing a side chain; and (3) understanding the metabolism of Mip inhibitors and identification of active metabolites.
A sub-study addressed the biotinylation of anti-leishmanial compounds from Valeriana wallichii rhizomes, with three tracer molecules synthesized for future pull-down experiments.
Grasslands shape many landscapes of the earth as they cover about one-third of its surface. They are home and provide livelihood for billions of people and are mainly used as source of forage for animals. However, grasslands fulfill many additional ecosystem functions next to fodder production, such as storage of carbon, water filtration, provision of habitats and cultural values. They play a role in climate change (mitigation) and in preserving biodiversity and ecosystem functions on a global scale. The degree to what these ecosystem functions are present within grassland ecosystems is largely determined by the management. Individual management practices and the use intensity influence the species composition as well as functions, like carbon storage, while higher use intensities (e.g. high mowing frequencies) usually show a negative impact. Especially in Central European countries, like in Germany, the determining influence of grassland management on its physiognomy and ecosystem functions leads to a large variability and small-scale alternations of grassland parcels. Large-scale information on the management and use intensity of grasslands is not available. Consequently, estimations of grassland ecosystem functions are challenging which, however, would be required for large-scale assessments of the status of grassland ecosystems and optimized management plans for the future. The topic of this thesis tackles this gap by investigating the major grassland management practice in Germany, which is mowing, for multiple years, in high spatial resolution
and on a national scale.
Earth Observation (EO) has the advantage of providing information of the earth’s surface on multi-temporal time steps. An extensive literature review on the use of EO for grassland management and production analyses, which was part of this thesis, showed that in particular research on grasslands consisting of small parcels with a large variety of management and use intensity, like common in Central Europe, is underrepresented. Especially
the launch of the Sentinel satellites in the recent past now enables the analyses of such grasslands due to their high spatial and temporal resolution. The literature review specifically on the investigation of grassland mowing events revealed that most previous studies focused on small study areas, were exploratory, only used one sensor type and/or lacked a reference data set with a complete range of management options.
Within this thesis a novel framework to detect grassland mowing events over large areas is presented which was applied and validated for the entire area of Germany for multiple years (2018–2021). The potential of both sensor types, optical (Sentinel-2) and Synthetic Aperture Radar (SAR) (Sentinel-1) was investigated regarding grassland mowing event detection. Eight EO parameters were investigated, namely the Enhanced Vegetation Index (EVI), the backscatter intensity and the interferometric (InSAR) temporal coherence for both available polarization modes (VV and VH), and the polarimetric (PolSAR) decomposition parameters Entropy, K0 and K1. An extensive reference data set was generated based on daily images of webcams distributed in Germany which resulted in mowing information
for grasslands with the entire possible range of mowing frequencies – from one to six in Germany – and in 1475 reference mowing events for the four years of interest.
For the first time a observation-driven mowing detection approach including data from Sentinel-2 and Sentinel-1 and combining the two was developed, applied and validated on large scale. Based on a subset of the reference data (13 grassland parcels with 44 mowing events) from 2019 the EO parameters were investigated and the detection algorithm
developed and parameterized. This analysis showed that a threshold-based change detection approach based on EVI captured grassland mowing events best, which only failed during periods of clouds. All SAR-based parameters showed a less consistent behavior to mowing events, with PolSAR Entropy and InSAR Coherence VH, however, revealing the
highest potential among them. A second, combined approach based on EVI and a SARbased parameter was developed and tested for PolSAR Entropy and InSAR VH. To avoid additional false positive detections during periods in which mowing events are anyhow reliably detected using optical data, the SAR-based mowing detection was only initiated
during long gaps within the optical time series (< 25 days). Application and validation of
these approaches in a focus region revealed that only using EVI leads to the highest accuracies (F1-Score = 0.65) as combining this approach with SAR-based detection led to a strong increase in falsely detected mowing events resulting in a decrease of accuracies (EVI + PolSAR ENT F1-Score = 0.61; EVI + InSAR COH F1-Score = 0.61).
The mowing detection algorithm based on EVI was applied for the entire area of Germany for the years 2018-2021. It was revealed that the largest share of grasslands with high mowing frequencies (at least four mowing events) can be found in southern/south-eastern Germany. Extensively used grassland (mown up to two times) is distributed within the entire country with larger shares in the center and north-eastern parts of Germany. These patterns stay constant in general, but small fluctuations between the years are visible. Early mown grasslands can be found in southern/south-eastern Germany – in line with high mowing frequency areas – but also in central-western parts. The years 2019 and 2020 revealed higher accuracies based on the 1475 mowing events of the multi-annual validation data set
(F1-Scores of 0.64 and 0.63), 2018 and 2021 lower ones (F1-Score of 0.52 and 0.50).
Based on this new, unprecedented data set, potential influencing factors on the mowing dynamics were investigated. Therefore, climate, topography, soil data and information on conservation schemes were related to mowing dynamics for the year 2020, which showed a high number of valid observations and detection accuracy. It was revealed that there are no strong linear relationships between the mowing frequency or the timing of the first mowing event and the investigated variables. However, it was found that for intensive grassland usage certain climatic and topographic conditions have to be fulfilled, while extensive grasslands appear on the entire spectrum of these variables. Further, higher mowing frequencies occur on soils with influence of ground water and lower mowing frequencies in protected areas. These results show the complex interplay between grassland mowing dynamics and external influences and highlight the challenges of policies aiming to protect grassland ecosystem functions and their need to be adapted to regional circumstances.
DNA methylation acts as a major epigenetic modification in mammals, characterized by the transfer of a methyl group to a cytosine. DNA methylation plays a pivotal role in regulating normal development, and misregulation in cells leads to an abnormal phenotype as is seen in several cancers. Any mutations or expression anomalies of genes encoding regulators of DNA methylation may lead to abnormal expression of critical molecules. A comprehensive genomic study encompassing all the genes related to DNA methylation regulation in relation to breast cancer is lacking. We used genomic and transcriptomic datasets from the Cancer Genome Atlas (TGCA) Pan-Cancer Atlas, Genotype-Tissue Expression (GTEx) and microarray platforms and conducted in silico analysis of all the genes related to DNA methylation with respect to writing, reading and erasing this epigenetic mark. Analysis of mutations was conducted using cBioportal, while Xena and KMPlot were utilized for expression changes and patient survival, respectively. Our study identified multiple mutations in the genes encoding regulators of DNA methylation. The expression profiling of these showed significant differences between normal and disease tissues. Moreover, deregulated expression of some of the genes, namely DNMT3B, MBD1, MBD6, BAZ2B, ZBTB38, KLF4, TET2 and TDG, was correlated with patient prognosis. The current study, to our best knowledge, is the first to provide a comprehensive molecular and genetic profile of DNA methylation machinery genes in breast cancer and identifies DNA methylation machinery as an important determinant of the disease progression. The findings of this study will advance our understanding of the etiology of the disease and may serve to identify alternative targets for novel therapeutic strategies in cancer.
Testosterone deficiency in males is linked to various pathological conditions, including muscle and bone loss. This study evaluated the potential of different training modalities to counteract these losses in hypogonadal male rats. A total of 54 male Wistar rats underwent either castration (ORX, n = 18) or sham castration (n = 18), with 18 castrated rats engaging in uphill, level, or downhill interval treadmill training. Analyses were conducted at 4, 8, and 12 weeks postsurgery. Muscle force of the soleus muscle, muscle tissue samples, and bone characteristics were analyzed. No significant differences were observed in cortical bone characteristics. Castrated rats experienced decreased trabecular bone mineral density compared to sham-operated rats. However, 12 weeks of training increased trabecular bone mineral density, with no significant differences among groups. Muscle force measurements revealed decreased tetanic force in castrated rats at week 12, while uphill and downhill interval training restored force to sham group levels and led to muscle hypertrophy compared to ORX animals. Linear regression analyses showed a positive correlation between bone biomechanical characteristics and muscle force. The findings suggest that running exercise can prevent bone loss in osteoporosis, with similar bone restoration effects observed across different training modalities.
(1) Background: Metabolically healthy obesity (MHO) is a concept that applies to obese patients without any elements of metabolic syndrome (metS). In turn, metabolically unhealthy obesity (MUO) defines the presence of elements of metS in obese patients. The components of MUO can be divided into subgroups regarding the elements of inflammation, lipid and glucose metabolism and cardiovascular disease. MUO patients appear to be at greater risk of developing non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) compared to MHO patients. The aim of this study was to evaluate the influence of different MUO components on NAFLD and NASH in patients with morbid obesity undergoing bariatric surgery. (2) Methods: 141 patients undergoing bariatric surgery from September 2015 and October 2021 at RWTH Aachen university hospital (Germany) were included. Patients were evaluated pre-operatively for characteristics of metS and MUO (HbA1c, HOMA, CRP, BMI, fasting glucose, LDL, TG, HDL and the presence of arterial hypertension). Intraoperatively, a liver biopsy was taken from the left liver lobe and evaluated for the presence of NAFLD or NASH. In ordinal regression analyses, different factors were evaluated for their influence on NAFLD and NASH. (3) Results: Mean BMI of the patients was 52.3 kg/m\(^2\) (36–74.8, SD 8.4). Together, the parameters HbA1c, HOMA, CRP, BMI, fasting glucose, LDL, TG, HDL and the presence of arterial hypertension accounted for a significant amount of variance in the outcome, with a likelihood ratio of χ\(^2\) (9) = 41.547, p < 0.001, for predicting the presence of NASH. Only HOMA was an independent predictor of NASH (B = 0.102, SE = 0.0373, p = 0.007). Evaluation of steatosis showed a similar trend (likelihood ratio χ\(^2\) (9) = 40.272, p < 0.001). Independent predictors of steatosis were HbA1c (B = 0.833, SE = 0.343, p = 0.015) and HOMA (B = 0.136, SE = 0.039, p < 0.001). (4) Conclusions: The above-mentioned model, including components of MUO, was significant for diagnosing NASH in patients with morbid obesity undergoing bariatric surgery. Out of the different subitems, HOMA independently predicted the presence of NASH and steatosis, while HbA1c independently predicted steatosis and fibrosis. Taken together, the parameter of glucose metabolism appears to be more accurate for the prediction of NASH than the parameters of lipid metabolism, inflammation or the presence of cardiovascular disease.
Background: The American Thyroid Association (ATA) uses criteria to assess the risk for persistent disease in differentiated thyroid carcinoma (DTC) after radioiodine therapy (RAI). There are no data available showing that this classification can be adopted unadjusted by Germany. Aim: The aim of our study is to investigate whether the ATA classification can be applied to a German population for short-term prognosis. Furthermore, we investigated the influence of an age cutoff value. Methods: We retrospectively analyzed 121 patients who were referred to our tertiary referral center. Patients were classified into risk categories, and the therapy response was determined according to ATA. Results: A total of 73/83 (88%) ATA low-risk patients and 12/19 (63%) intermediate-risk patients showed an excellent response; 2/19 (11%) high-risk patients had a biochemical, and 6 (31%) had a structural incomplete response. Of all 39 patients ≥55 years, 84% had an excellent response. Using a cut off of 50 years, 50/62 (81%) of the older patients showed an excellent response. Conclusion: The ATA risk classification is able to estimate the response to RAI therapy in a German population. A shift from 55 to 50 years as an age cutoff value does not result in any relevant change in the treatment response.
This work presents a newly developed method for the epitaxial growth of the half-Heusler antiferromagnet CuMnSb. All necessary process steps, from buffer growth to the deposition of a protective layer, are presented in detail. Using structural, electrical, and magnetic characterization, the material parameters of the epitaxial CuMnSb layers are investigated.
The successful growth of CuMnSb by molecular beam epitaxy is demonstrated on InAs (001), GaSb (001), and InP (001) substrates. While CuMnSb can be grown pseudomorphically on InAs and GaSb, the significant lattice mismatch for growth on InP leads to relaxation already at low film thicknesses. Due to the lower conductivity of GaSb compared to InAs, GaSb substrates are particularly suitable for the fabrication of CuMnSb layers for lateral electrical transport experiments. However, by growing a high-resistive ZnTe interlayer below the CuMnSb layer, lateral transport experiments on CuMnSb layers grown on InAs can also be realized. Protective layers of Ru and Al2O3 have proven to be suitable for protecting the CuMnSb layers from the environment.
Structural characterization by high resolution X-ray diffraction (full width at half maximum of 7.7 ′′ of the rocking curve) and atomic force microscopy (root mean square surface roughness of 0.14 nm) reveals an outstanding crystal quality of the epitaxial CuMnSb layers. The half-Heusler crystal structure is confirmed by scanning transmission electron microscopy and the stoichiometric material composition by Rutherford backscattering spectrometry. In line with the high crystal quality, a new minimum value of the residual resistance of CuMnSb (𝜌0 = 35 μΩ ⋅ cm) could be measured utilizing basic electrical transport experiments.
An elaborate study of epitaxial CuMnSb grown on GaSb reveals a dependence of the vertical lattice parameter on the Mn/Sb flux ratio. This characteristic enables the growth of tensile, unstrained, and compressive strained CuMnSb layers on a single substrate material. Additionally, it is shown that the Néel temperature has a maximum of 62 K at stoichiometric material composition and thus can be utilized as a selection tool for stoichiometric CuMnSb samples. Mn-related defects are believed to be the driving force for these observations.
The magnetic characterization of the epitaxial CuMnSb films is performed by superconducting quantum interference device magnetometry. Magnetic behavior comparable to the bulk material is found, however, an additional complex magnetic phase appears in thin CuMnSb films and/or at low magnetic fields, which has not been previously reported for CuMnSb. This magnetic phase is believed to be localized at the CuMnSb surface and exhibits both superparamagnetic and spin-glass-like behavior. The exchange bias effect of CuMnSb is investigated in combination with different in- and out-of-plane ferromagnets. It is shown that the exchange bias effect can only be observed in combination with in-plane ferromagnets.
Finally, the first attempts at the growth of fully epitaxial CuMnSb/NiMnSb heterostructures are presented. Both magnetic and structural studies by secondary-ion mass spectrometry indicate the interdiffusion of Cu and Ni atoms between the two half-Heusler layers, however, an exchange bias effect can be observed for the CuMnSb/NiMnSb heterostructures. Whether this exchange bias effect originates from exchange interaction between the CuMnSb and NiMnSb layers, or from ferromagnetic inclusions in the antiferromagnetic layer can not be conclusively identified.
Depressive disorders represent one of the main sources for the loss of healthy years of life. One of the reasons for this circumstance is the recurrent course of these disorders, which can be interrupted by current therapeutic approaches, especially in the shortterm, but seem to be maintained at least in part in the long-term. Subsequently, on one hand, this thesis deals with methodological measurement issues in the longitudinal prediction of depressive courses. On the other hand, it addresses two currently discussed neuroscience-based treatment approaches, which are investigated experimentally in a basic-psychological manner and reviewed in the light of their potential to translate results to the application in patient care. These two approaches each address potential mechanisms that may negatively impact long-term disease trajectories: First, stable endophenotypes for vulnerability factors that could regain control over the organism and reactivate maladaptive experiences, or behaviors with increasing temporal distance from therapeutic methods are focused on. In the studies presented, these were influenced by a recently rediscovered method of neuromodulation (transcranial low-intensity focused ultrasound) which is discussed in light of its unique capability to address even deepest, subcortical regions at a high spatial resolution. Lastly, as a second approach, an experimental design for the use of reconsolidation interference is presented, which could provide a first insight into the applicability of corresponding protocols in the field of depressive disorders and thus contribute to the modification, instead of inhibition, of already mentioned endophenotypes. In sum, methodological considerations for monitoring and predicting long-term courses of depression are deducted before two approaches are discussed that could potentially exert positive influences on the recurrent nature of depressive symptoms on their own, in combination with each other, or as augmentation for existing therapeutic procedures.
One of the features that defines humans as extraordinarily social beings is their striking susceptibility to the gaze of others. The research reported in this dissertation was undertaken to advance our understanding of the role of gaze cues in low-level attentional and higher-order cognitive processes. In particular, effects of gaze were examined with regard to three aspects of human cognition: (1) social attention, (2) social interaction and (3) social understanding. Chapter 1 consists of three manuscripts that investigate the boundary conditions of attention capture by direct gaze and how gaze direction is integrated with facial context information. Manuscript 1 and 2 suggest two necessary requirements for attention capture by direct gaze: a meaningful holistic facial context and sharp foveal vision, respectively. Manuscript 3 shows approach/avoidance-congruency effects between gaze direction and emotion expression on attention. Chapter 2 of this dissertation explores the role of gaze in more naturalistic social scenarios. Manuscript 4 demonstrates that gaze behavior during a conversation shapes our perception of another person. Manuscript 5 builds on these findings by showing that these perceptions define our willingness to act in a prosocial way towards our interaction partner. Finally, chapter 3 adopts a broader perspective on social cognition research with a special focus on methodological aspects. Manuscript 6 is a review highlighting the significance of methodological aspects in social cognition research and stressing the importance of sophisticated decisions on task and stimulus materials. Manuscript 7 introduces a new instrument for the assessment of social understanding in adolescents. Initial application in a young sample group indicates that an understanding of another person’s mental states is a capacity that is still developing throughout adolescence. Both manuscripts of this final chapter include eye tracking data that suggest a relationship between gaze behavior and social understanding, a finding that further emphasizes the complex and multifaceted nature of social cognition. I conclude from the findings of this dissertation that research can benefit from adopting a broad view in terms of methodological as well as temporal aspects in order to capture human social cognition in its entirety.
Disentangling the Formation of PAHs in Extreme Environments by IR/UV Double Resonance Spectroscopy
(2023)
Polycyclic Aromatic Hydrocarbons (PAHs) are considered as key building blocks in the formation of carbonaceous particles such as soot. In our immediate surroundings, they are mainly generated in incomplete combustion processes and are further considered as carriers of the Unidentified Infrared Bands which are detected in a wide variety of astrophysical envelopes in the interstellar medium. Currently, astrochemical as well as combustion related models favour small resonance stabilized radicals (RSR) as major contributors to PAHs in sequential reactions. Therefore, we generated two RSR under well-defined conditions to investigate their contribution to PAH formation in a pyrolysis microreactor. The various reaction products were identified by IR/UV ion dip spectroscopy which combines the mass-selectivity of UV light with the structural sensitivity of IR radiation. Finally, we investigated the intermolecular interactions in azaphenanthrene dimers in combination with high-level theoretical calculations and found a preferential formation of pi-stacked van der Waals cluster in a molecular jet expansion.
The receptor activity-modifying proteins (RAMPs) are ubiquitously expressed membrane proteins that interact with several G protein-coupled receptors (GPCRs), the largest and pharmacologically most important family of cell surface receptors. RAMPs can regulate GPCR function in terms of ligand-binding, G-protein coupling, downstream signaling, trafficking, and recycling. The integrity of their interactions translates to many physiological functions or pathological conditions.
Regardless of numerous reports on its essential importance for cell biology and pivotal role in (patho-)physiology, the molecular mechanism of how RAMPs modulate GPCR activation remained largely elusive.
This work presents new insights that add to the common understanding of the allosteric regulation of receptor activation and will help interpret how accessory proteins - RAMPs - modulate activation dynamics and how this affects the fundamental aspects of cellular signaling. Using a prototypical class B GPCR, the parathyroid hormone 1 receptor (PTH1R) in the form of advanced genetically encoded optical biosensors, I examined RAMP's impact on the PTH1R activation and signaling in intact cells. A panel of single-cell FRET and confocal microscopy experiments as well canonical and non-canonical functional assays were performed to get a holistic picture of the signaling initiation and transduction of that clinically and therapeutically relevant GPCR. Finally, structural modeling was performed to add molecular mechanistic details to that novel art of modulation.
I describe here that RAMP2 acts as a specific allosteric modulator of PTH1R, shifting PTH1R to a unique pre-activated state that permits faster activation in a ligand-specific manner. Moreover, RAMP2 modulates PTH1R downstream signaling in an agonist-dependent manner, most notably increasing the PTH-mediated Gi3 signaling sensitivity and kinetics of cAMP accumulation. Additionally, RAMP2 increases PTH- and PTHrP-triggered β-arrestin2 recruitment to PTH1R and modulates cytosolic ERK1/2 phosphorylation. Structural homology modeling shows that structural motifs governing GPCR-RAMP interaction originate in allosteric hotspots and rationalize functional modulation. Moreover, to interpret the broader role of RAMP's modulation in GPCRs pharmacology, different fluorescent tools to investigate RAMP's spatial organization were developed, and novel conformational biosensors for class B GPCRs were engineered. Lastly, a high throughput assay is proposed and prototyped to expand the repertoire of RAMPs or other membrane protein interactors.
These data uncover the critical role of RAMPs in GPCR activation and signaling and set up a novel platform for studying GPCR modulation. Furthermore, these insights may provide a new venue for precise modulation of GPCR
function and advanced drug design.
Respiratory infections are a significant health concern worldwide, and the airway epithelium plays a crucial role in regulating airway function and modulating inflammatory processes. However, most studies on respiratory infections have used cell lines or animal models, which may not accurately reflect native physiological conditions, especially regarding human pathogens. We generated human nasal mucosa (hNM) and tracheobronchial mucosa (hTM) models to address this issue using primary human airway epithelial cells and fibroblasts. We characterised these human airway tissue models (hAM) using high speed video microscopy, single cell RNA sequencing, immunofluorescence staining,
and ultrastructural analyses that revealed their complexity and cellular heterogeneity. We demonstrated that Bordetella pertussis virulence factor adenylate cyclase toxin (CyaA) elevated the intracellular production of cyclic adenosine monophosphate (cAMP) and secretion of interleukin (IL) 6, IL 8, and human beta defensin 2 (HBD2). In addition, we compared the responses of the tissue models from two different anatomical sites (the upper and lower respiratory mucosa) and are the first to report such differential susceptibility towards CyaA using 3D primary airway cell derivedmodels. The effect of toxin treatment on the epithelial barrier integrity of the tissue models was assessed by measuring the flux of fluorescein isothiocyanate (FITC)-conjugated dextran across the models. Though we observed a cell type specific response with respect to intracellular cAMP production and IL 6, IL 8, and HBD2 secretion in the models treated with CyaA on the apical side, the epithelial membrane barrier integrity was not compromised. In addition to toxin studies, using these characterised models, we established viral infection studies for Influenza A (IAV), Respiratory Syncytial Virus subtype B (RSV), and severe acute respiratory syndrome coronavirus 2. We visualised the morphological consequences of the viral infection using ultrastructural analysis
and immunofluorescence. We verified the effective infection in hAM by measuring the viral RNA using RTqPCR and detected elevated cytokine levels in response to infection using biochemical assays. In contrast to cell lines, studies on viral infection using hAM demonstrated that infected areas were localized to specific regions. This led to the formation of infection hotspots, which were more likely to occur when models derived from different donors were infected separately with all three viruses. IAV infected tissue models replicate the clinical findings of H1N1 infection, such as mucus
hypersecretion, cytokine release, and infection-associated epithelial cell damage.Finally, we paved the steps towards understanding the impact of IAV infection on disease models. We generated hTM from biopsies obtained from chronic obstructive pulmonary disease (COPD) patients. As a model to study the impact of COPD on respiratory infections, considering the increase in COPD cases in the past decade and the continued predicted increase in the future. We established the IAV infection
protocol to capture the early infection signatures in non-COPD and COPD conditions using scRNA-seq. We investigated the infection kinetics of IAV (H1N1-clinical isolate) in hTM and found that viruses were actively released approximately 24 hours post infection. The scRNA-seq data from the hTM derived from non-COPD and COPD patients, revealed lower levels of SCGB1A1 (club cell marker) gene expression in the COPD-control group compared to the non-COPD control group, consistent with previous clinical studies. Furthermore, we observed that IAV infection elevated SCGB1A1 gene expression especially in secretory cells of both the COPD and non COPD groups. This may imply the role of club cells as early responders during IAV infection providing epithelial repair, regeneration, and resistance to spread of infection. This is the first study to address the molecular diversity in COPD and non-COPD disease models infected with IAV investigating the early response (6 h) of specific cell types in the human lower airways towards infection using scRNA-seq. These findings
highlight the potential interplay between COPD, IAV infection, and altered vulnerability to other viral infections and respiratory illnesses making the hAM applicable for addressing more specific research questions and validating potential targets, such as SCGB1A1 targeted therapy for chronic lung diseases. Our findings demonstrate the potential of the hNM and hTM for investigating respiratory infections, innate immune responses, and trained immunity in non-immune cells. Our experiments show that hAM may represent a more accurate representation of the native physiological condition and improve our understanding of the disease mechanisms. Furthermore, these models promote non-animal research as they replicate clinical findings. We can further increase their complexity by incorporating dynamic flow systems and immune cells catered to the research question.
Post-transcriptional RNA modification methods are in high demand for site-specific RNA labelling and analysis of RNA functions. In vitro-selected ribozymes are attractive tools for RNA research and have the potential to overcome some of the limitations of chemoenzymatic approaches with repurposed methyltransferases. Here we report an alkyltransferase ribozyme that uses a synthetic, stabilized S-adenosylmethionine (SAM) analogue and catalyses the transfer of a propargyl group to a specific adenosine in the target RNA. Almost quantitative conversion was achieved within 1 h under a wide range of reaction conditions in vitro, including physiological magnesium ion concentrations. A genetically encoded version of the SAM analogue-utilizing ribozyme (SAMURI) was expressed in HEK293T cells, and intracellular propargylation of the target adenosine was confirmed by specific fluorescent labelling. SAMURI is a general tool for the site-specific installation of the smallest tag for azide-alkyne click chemistry, which can be further functionalized with fluorophores, affinity tags or other functional probes.
This thesis, first, is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints, subsequently, as well as constrained structured optimization problems featuring a composite objective function and set-membership constraints. It is then concerned to convergence and rate-of-convergence analysis of proximal gradient methods for the composite optimization problems in the presence of the Kurdyka--{\L}ojasiewicz property without global Lipschitz assumption.
Deep learning enables enormous progress in many computer vision-related tasks. Artificial Intel- ligence (AI) steadily yields new state-of-the-art results in the field of detection and classification. Thereby AI performance equals or exceeds human performance. Those achievements impacted many domains, including medical applications.
One particular field of medical applications is gastroenterology. In gastroenterology, machine learning algorithms are used to assist examiners during interventions. One of the most critical concerns for gastroenterologists is the development of Colorectal Cancer (CRC), which is one of the leading causes of cancer-related deaths worldwide. Detecting polyps in screening colonoscopies is the essential procedure to prevent CRC. Thereby, the gastroenterologist uses an endoscope to screen the whole colon to find polyps during a colonoscopy. Polyps are mucosal growths that can vary in severity.
This thesis supports gastroenterologists in their examinations with automated detection and clas- sification systems for polyps. The main contribution is a real-time polyp detection system. This system is ready to be installed in any gastroenterology practice worldwide using open-source soft- ware. The system achieves state-of-the-art detection results and is currently evaluated in a clinical trial in four different centers in Germany.
The thesis presents two additional key contributions: One is a polyp detection system with ex- tended vision tested in an animal trial. Polyps often hide behind folds or in uninvestigated areas. Therefore, the polyp detection system with extended vision uses an endoscope assisted by two additional cameras to see behind those folds. If a polyp is detected, the endoscopist receives a vi- sual signal. While the detection system handles the additional two camera inputs, the endoscopist focuses on the main camera as usual.
The second one are two polyp classification models, one for the classification based on shape (Paris) and the other on surface and texture (NBI International Colorectal Endoscopic (NICE) classification). Both classifications help the endoscopist with the treatment of and the decisions about the detected polyp.
The key algorithms of the thesis achieve state-of-the-art performance. Outstandingly, the polyp detection system tested on a highly demanding video data set shows an F1 score of 90.25 % while working in real-time. The results exceed all real-time systems in the literature. Furthermore, the first preliminary results of the clinical trial of the polyp detection system suggest a high Adenoma Detection Rate (ADR). In the preliminary study, all polyps were detected by the polyp detection system, and the system achieved a high usability score of 96.3 (max 100). The Paris classification model achieved an F1 score of 89.35 % which is state-of-the-art. The NICE classification model achieved an F1 score of 81.13 %.
Furthermore, a large data set for polyp detection and classification was created during this thesis. Therefore a fast and robust annotation system called Fast Colonoscopy Annotation Tool (FastCAT) was developed. The system simplifies the annotation process for gastroenterologists. Thereby the
i
gastroenterologists only annotate key parts of the endoscopic video. Afterward, those video parts are pre-labeled by a polyp detection AI to speed up the process. After the AI has pre-labeled the frames, non-experts correct and finish the annotation. This annotation process is fast and ensures high quality. FastCAT reduces the overall workload of the gastroenterologist on average by a factor of 20 compared to an open-source state-of-art annotation tool.
The N,C-coupled naphthylisoquinoline alkaloid ancistrocladinium A belongs to a novel class of natural products with potent antiprotozoal activity. Its effects on tumor cells, however, have not yet been explored. We demonstrate the antitumor activity of ancistrocladinium A in multiple myeloma (MM), a yet incurable blood cancer that represents a model disease for adaptation to proteotoxic stress. Viability assays showed a potent apoptosis-inducing effect of ancistrocladinium A in MM cell lines, including those with proteasome inhibitor (PI) resistance, and in primary MM cells, but not in non-malignant blood cells. Concomitant treatment with the PI carfilzomib or the histone deacetylase inhibitor panobinostat strongly enhanced the ancistrocladinium A-induced apoptosis. Mass spectrometry with biotinylated ancistrocladinium A revealed significant enrichment of RNA-splicing-associated proteins. Affected RNA-splicing-associated pathways included genes involved in proteotoxic stress response, such as PSMB5-associated genes and the heat shock proteins HSP90 and HSP70. Furthermore, we found strong induction of ATF4 and the ATM/H2AX pathway, both of which are critically involved in the integrated cellular response following proteotoxic and oxidative stress. Taken together, our data indicate that ancistrocladinium A targets cellular stress regulation in MM and improves the therapeutic response to PIs or overcomes PI resistance, and thus may represent a promising potential therapeutic agent.
The Essential Climate Variable (ECV) Permafrost is currently undergoing strong changes due to rising ground and air temperatures. Surface movement, forming characteristic landforms such as rock glaciers, is one key indicator for mountain permafrost. Monitoring this movement can indicate ongoing changes in permafrost; therefore, rock glacier velocity (RGV) has recently been added as an ECV product. Despite the increased understanding of rock glacier dynamics in recent years, most observations are either limited in terms of the spatial coverage or temporal resolution. According to recent studies, Sentinel-1 (C-band) Differential SAR Interferometry (DInSAR) has potential for monitoring RGVs at high spatial and temporal resolutions. However, the suitability of DInSAR for the detection of heterogeneous small-scale spatial patterns of rock glacier velocities was never at the center of these studies. We address this shortcoming by generating and analyzing Sentinel-1 DInSAR time series over five years to detect small-scale displacement patterns of five high alpine permafrost environments located in the Central European Alps on a weekly basis at a range of a few millimeters. Our approach is based on a semi-automated procedure using open-source programs (SNAP, pyrate) and provides East-West displacement and elevation change with a ground sampling distance of 5 m. Comparison with annual movement derived from orthophotos and unpiloted aerial vehicle (UAV) data shows that DInSAR covers about one third of the total movement, which represents the proportion of the year suited for DInSAR, and shows good spatial agreement (Pearson R: 0.42–0.74, RMSE: 4.7–11.6 cm/a) except for areas with phase unwrapping errors. Moreover, the DInSAR time series unveils spatio-temporal variations and distinct seasonal movement dynamics related to different drivers and processes as well as internal structures. Combining our approach with in situ observations could help to achieve a more holistic understanding of rock glacier dynamics and to assess the future evolution of permafrost under changing climatic conditions.
To define frailty in older cancer patients, the aim of this study was to assess the geriatric status and quality of life (QoL) aspects in patients suffering from recurrent/metastatic head and neck squamous cell carcinoma (r/m HNSCC) under palliative treatment. A comprehensive geriatric assessment (CGA) was performed on 21 r/m HNSCC patients at two defined assessments, and the QoL aspects and the impact of descriptive data were evaluated. The Kolmogorov–Smirnov test, Spearman’s rho correlation, and two-way mixed ANOVA were used for statistical analysis. All patients were found to be “frail”. Pain, fatigue, and the burden of illness were the highest-rated symptoms. Oral function and orofacial appearance were highly impaired. A significant impact of descriptive data on the CGA and QoL results was found (all p ≤ 0.05). Thus, the CGA results revealed high frailty, severe comorbidities, and high impairments in QoL aspects. The CGA and QoL results were negatively affected by the primary HNSCC treatment approach, the need for prosthetic treatment, and worse oral functional capacity. Therefore, frailty in r/m HNSCC patients seems to be multidimensional. The evaluation of the CGA and QoL aspects in r/m HNSCC patients can be recommended to detect special needs, organize aftercare, and improve the support for frail and vulnerable cancer patients to create a multidisciplinary treatment approach.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) imposes a significant burden on Westernized regions. The Western diet, high in salt intake, significantly contributes to disease development. However, there are a lack of data on salt literacy and salt intake among MASLD patients in Germany. Our study aims to analyze daily salt intake and salt-intake-related behavior in MASLD patients. Methods: 234 MASLD patients were prospectively included. Daily salt intake and salt-intake-related behavior were assessed via a food frequency questionnaire (FFQ—DEGS) and a salt questionnaire (SINU). Statistical analyses were performed using SPSS. Results: Mean daily salt intake was higher in men than in women (7.3 ± 5 g/d vs. 5.3 ± 4 g/d; p < 0.001). There was significant agreement between increased daily salt intake (6 g/d) and the behavioral salt index (SI) (p < 0.001). Men exhibited higher SI scores compared to women, indicating lower awareness of salt in everyday life. Multivariate analysis identified specific salt-intake-related behaviors impacting daily salt consumption. Conclusions: Our study reveals a strong link between daily salt intake and salt-intake-related behavior, highlighting sex-specific differences in an MASLD cohort. To enhance patient care in high-cardiovascular-risk populations, specific behavioral approaches may be considered, including salt awareness, to improve adherence to lifestyle changes, particularly in male patients.
In heart failure and atrial fibrillation, a persistent Na\(^+\) current (I\(_{NaL}\)) exerts detrimental effects on cellular electrophysiology and can induce arrhythmias. We have recently shown that Na\(_V\)1.8 contributes to arrhythmogenesis by inducing a I\(_{NaL}\). Genome-wide association studies indicate that mutations in the SCN10A gene (Na\(_V\)1.8) are associated with increased risk for arrhythmias, Brugada syndrome, and sudden cardiac death. However, the mediation of these Na\(_V\)1.8-related effects, whether through cardiac ganglia or cardiomyocytes, is still a subject of controversial discussion. We used CRISPR/Cas9 technology to generate homozygous atrial SCN10A-KO-iPSC-CMs. Ruptured-patch whole-cell patch-clamp was used to measure the I\(_{NaL}\) and action potential duration. Ca\(^{2+}\) measurements (Fluo 4-AM) were performed to analyze proarrhythmogenic diastolic SR Ca\(^{2+}\) leak. The I\(_{NaL}\) was significantly reduced in atrial SCN10A KO CMs as well as after specific pharmacological inhibition of Na\(_V\)1.8. No effects on atrial APD\(_{90}\) were detected in any groups. Both SCN10A KO and specific blockers of Na\(_V\)1.8 led to decreased Ca\(^{2+}\) spark frequency and a significant reduction of arrhythmogenic Ca\(^{2+}\) waves. Our experiments demonstrate that Na\(_V\)1.8 contributes to I\(_{NaL}\) formation in human atrial CMs and that Na\(_V\)1.8 inhibition modulates proarrhythmogenic triggers in human atrial CMs and therefore Na\(_V\)1.8 could be a new target for antiarrhythmic strategies.
The use of bone-cement-enforced osteosynthesis is a growing topic in trauma surgery. In this context, drillability is a desirable feature for cements that can improve fracture stability, which most of the available cement systems lack. Therefore, in this study, we evaluated a resorbable and drillable magnesium-phosphate (MgP)-based cement paste considering degradation behavior and biocompatibility in vivo. Two different magnesium-phosphate-based cement (MPC) pastes with different amounts of phytic acid (IP 6) as setting retarder (MPC 22.5 and MPC 25) were implanted in an orthotopic defect model of the lateral femoral condyle of New Zealand white rabbits for 6 weeks. After explantation, their resorption behavior and material characteristics were evaluated by means of X-ray diffraction (XRD), porosimetry measurement, histological staining, peripheral quantitative computed tomography (pQCT), cone-beam computed tomography (CBCT) and biomechanical load-to-failure tests. Both cement pastes displayed comparable results in mechanical strength and resorption kinetics. Bone-contact biocompatibility was excellent without any signs of inflammation. Initial resorption and bone remodeling could be observed. MPC pastes with IP 6 as setting retardant have the potential to be a valuable alternative in distinct fracture patterns. Drillability, promising resorption potential and high mechanical strength confirm their suitability for use in clinical routine.
In March 2020, Germany imposed a nationwide lockdown to curb the spread of COVID-19, prompting questions about the impact on the incidence of common fractures. This study examined 15 fracture types in pre-outbreak (2010–2019) and post-outbreak (2020–2021) periods, using data categorized by age (18–64 years, 65 years) and sex (male, female). Linear regression assessed annual growth rates, and mean fracture numbers were compared across periods for significant differences. Results indicated a positive correlation between fracture incidence rates and time for various types, such as cervical, thoracic, lumbar, and pelvic spine fractures, rib fractures, femoral neck, pertrochanteric femur, femoral shaft, and ankle fractures. Frequencies of proximal humerus, distal radius, femoral neck, pertrochanteric femur, femoral shaft, and ankle fractures in 2020 and 2021 were within predicted ranges from previous years. However, rib fractures and spinal fractures (cervical, thoracic, lumbar, and pelvic spine) occurred less frequently during this time. Notably, this study found a consistent decline in most fracture types for individuals aged 18–64 after the pandemic’s onset, while the fracture incidence of hip fractures, often referred to as fragility fractures, for those over 65 remained unchanged. Fibula fractures showed the most considerable decrease in both age groups. In conclusion, the COVID-19 pandemic substantially impacted fracture incidence, with lower rates among individuals under 65 and unchanged fragility fractures in the elderly population.
Background and objectives: Cartilage surgery constitutes a standard intervention in foot and ankle procedures. Currently, there is a lack of epidemiological data on its frequency, age distribution, and surgical options for cartilage surgery. This study aimed to investigate the current landscape of cartilage surgery in Germany and identify the most common procedures from an epidemiological standpoint. Materials and methods: Medical billing and reporting data from the Federal Statistical Office of Germany, encompassing the period 2006–2020, was examined, including all foot and ankle cartilage surgical procedures (summarized under OPS codes 5-812 and 5-801). The dataset incorporated information on the affected joint, patient age and sex, and surgery type. Each surgical procedure was categorized as “debridement”, “regeneration” or “refixation”. Linear and nonlinear regression analyses were employed, with a statistical significance threshold of 0.05. Results: From the total of 136,501 procedures conducted during the study period, the most frequently performed interventions were microfracture (58,252) and chondroplasty (56,135), and thus, debridement procedures were in the leading position. The use of acellular membranes was the most used regenerative technique (n = 11,414). At the ankle joint, interventions were mostly arthroscopic and in men, while foot cartilage surgeries were preferably performed via open surgery and mostly in women. Age distribution analysis revealed two primary peaks: the first in the 20–25-year-old group (ankle and foot) and the second in the 45–50-year-old group (ankle) and 55–60-year-old group (foot). Refixation and regenerative procedures were more frequent among younger individuals, while debriding procedures were more frequent among older individuals. Regenerative procedures, particularly in the ankle, significantly increased over time. Conclusions: Cartilage surgery of the foot and ankle was common, with two primary age groups predominantly affected. Notably, recent years have witnessed a considerable rise in cartilage regenerative procedures.
In this study, we examined the conditional indirect and direct relations of pain-related cognitions to depression. Subjective helplessness was included as presumably mediating the relations of catastrophizing and thought suppression to depression due to motivational deficits. In addition, moderating effects of dispositional action versus state orientation were analyzed, whereby state orientation indicates volitional deficits in coping with distress. The study was based on self-report data from 536 patients with chronic non-specific low back pain at the beginning of inpatient rehabilitation. Moderated mediation analyses were performed. The indirect catastrophizing- and thought suppression-depression relations were (partially) mediated by subjective helplessness; and moderated by failure-related action versus state orientation. Moreover, action versus state orientation moderated the direct relation of thought suppression to depression. Results suggest that catastrophizing, thought suppression, and subjective helplessness do not lead to depression unless associated with self-regulatory inability (i.e., state orientation). In contrast, action-oriented patients more effectively self-regulate pain-related emotions, disengage from rumination, and distract from pain and thus better avoid the debilitating effects of negative pain-related cognitions on depression. Future research and treatment may more strongly focus on the role of motivational and volitional deficits underlying learned helplessness and depression in chronic pain.
Mammalian phoshoglycolate phosphatase (PGP, also known as AUM) belongs to the ubiquitous HAD superfamily of phosphatases. As several other members of HAD phosphatases, the Mg2+-dependent dephosphorylation is conducted via a nucleophilic attack from a conserved aspartate residue in the catalytic cleft. The protein structure of PGP could not yet be solved entirely. Only a hybrid consisting of the PGP cap and the PDXP core (pyridoxal phosphatase, closest enzyme paralog) was crystallizable so far. PGP is able to efficiently dephosphorylate 2-phosphoglycolate, 2-phospho-L-lactate, 4-phospho-D-erythronate, and glycerol-3-phosphate in vitro which makes them likely physiological substrates. The first three substrates can be derived from metabolic side reactions (during glycolysis) and inhibit key enzymes in glycolysis and pentose phosphate pathway, the latter is situated at the intersection between glycolysis and lipogenesis. 2-phosphoglycolate can also be released in the context of repair of oxidative DNA damage. The activity of purified PGP can be reversibly inhibited by oxidation - physiologically likely in association with epidermal growth factor (EGF) signal transduction. In fact, an association between persistently lacking PGP activity (via downregulation) and the presence of hyperphosphorylated proteins after EGF stimulation has been identified. Reversible oxidation and transient inactivation of PGP may be particularly important for short-term and feedback regulatory mechanisms (as part of the EGF signaling). Furthermore, cellular proliferation in PGP downregulated cells is constantly reduced. Whole-body PGP inactivation in mice is embryonically lethal. Despite the many well-known features and functions, the knowledge about PGP is still incomplete.
In the present work the influence of reactive oxygen species (ROS) on PGP activity in cells und a possible connection between oxidative stress and the proliferation deficit of PGP downregulated cells was investigated. For the experiments, a spermatogonial cell line was used (due to the high PGP expression in testis). PGP activity can be reversibly inhibited in cellular lysates by H2O2 (as a ROS representative). Reversible oxidation could thus indeed be physiologically important. More oxidative DNA damage (by bleomycin) showed no PGP-dependent effects here. EGF stimulation (as an inducer of transient and well-controlled ROS production), low concentrations of menadione (as an oxidant) and N-acetylcysteine (as an antioxidant) were able to approximate the proliferation rate in PGP downregulated cells to that of control cells. The redox regulation of PGP could thus have an influence on cellular proliferation as a feedback mechanism - a mechanism that could not take place in PGP downregulated cells. However, the connections are probably even more complex and cannot be elucidated by a sole examination of the proliferation rate. The present results can thus only be regarded as preliminary experiments.
For a better understanding of the features and functions of PGP, this work then focused on specific regulation of enzyme activity by pharmacologically applicable small molecules. Four potent inhibitors had previously been identified in a screening campaign. In this work, three of these four inhibiting compounds could be further characterized in experiments with highly purified, recombinant murine and human PGP. Compounds #2 and #9 showed competitive inhibition properties with a markedly rising KM value with little or no change in vmax. The results were consistent for all tested protein variants: the murine and the human PGP as well as a PGP/PDXP hybrid protein. Compound #1 was the most potent and interesting PGP-inhibitory molecule: less change in KM and a constant decrease in vmax as well as a lower impact on the PGP/PDXP hybrid hint at a mixed mode of inhibition as a combination of competitive and non-competitive inhibition. The characterization of the potential inhibitors can serve as a basis for further structural analysis and studies on the complex physiological role of PGP.
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.
Serverless computing is an emerging cloud computing paradigm that offers a highlevel
application programming model with utilization-based billing. It enables the
deployment of cloud applications without managing the underlying resources or
worrying about other operational aspects. Function-as-a-Service (FaaS) platforms
implement serverless computing by allowing developers to execute code on-demand
in response to events with continuous scaling while having to pay only for the
time used with sub-second metering. Cloud providers have further introduced
many fully managed services for databases, messaging buses, and storage that also
implement a serverless computing model. Applications composed of these fully
managed services and FaaS functions are quickly gaining popularity in both industry
and in academia.
However, due to this rapid adoption, much information surrounding serverless
computing is inconsistent and often outdated as the serverless paradigm evolves.
This makes the performance engineering of serverless applications and platforms
challenging, as there are many open questions, such as: What types of applications
is serverless computing well suited for, and what are its limitations? How should
serverless applications be designed, configured, and implemented? Which design
decisions impact the performance properties of serverless platforms and how can
they be optimized? These and many other open questions can be traced back to an
inconsistent understanding of serverless applications and platforms, which could
present a major roadblock in the adoption of serverless computing.
In this thesis, we address the lack of performance knowledge surrounding serverless
applications and platforms from multiple angles: we conduct empirical studies
to further the understanding of serverless applications and platforms, we introduce
automated optimization methods that simplify the operation of serverless applications,
and we enable the analysis of design tradeoffs of serverless platforms by
extending white-box performance modeling.
After the discovery of three-dimensional topological insulators (TIs), such as tetradymite chalcogenides Bi$_2$Se$_3$, Bi$_2$Te$_3$ and Sb$_2$Te$_3$ – a new class of quantum materials characterized by their unique surface electronic properties – the solid state community got focused on topological states that are driven by strong electronic correlations and magnetism. An important material class is the magnetic TI (MTI) exhibiting the quantum anomalous Hall (QAH) effect, i.e. a dissipationless quantized edge-state transport in the absence of external magnetic field, originating from the interplay between ferromagnetism and a topologically non-trivial band structure. The unprecedented opportunities offered by these new exotic materials open a new avenue for the development of low-dissipation electronics, spintronics, and quantum computation. However, the major concern with QAH effect is its extremely low onset temperature, limiting its practical application. To resolve this problem, a comprehensive understanding of the microscopic origin of the underlying ferromagnetism is necessary.
V- and Cr-doped (Bi,Sb)$_2$Te$_3$ are the two prototypical systems that have been widely studied as realizations of the QAH state. Finding microscopic differences between the strongly correlated V and Cr impurities would help finding a relevant model of ferromagnetic coupling and eventually provide better control of the QAH effect in these systems. Therefore, this thesis first focuses on the V- and Cr-doped (Bi,Sb)$_2$Te$_3$ systems, to better understand these differences. Exploiting the unique capabilities of x-ray absorption spectroscopy and magnetic circular dichroism (XAS/XMCD), combined with advanced modeling based on multiplet ligand-field theory (MLFT), we provide a detailed microscopic insight into the local electronic and magnetic properties of these systems and determine microscopic parameters crucial for the comparison with theoretical models, which include the $d$-shell filling, spin and orbital magnetic moments. We find a strongly covalent ground state, dominated by the superposition of one and two Te-ligand-hole configurations, with a negligible contribution from a purely ionic 3+ configuration. Our findings indicate the importance of the Te $5p$ states for the ferromagnetism in (Bi, Sb)$_2$Te$_3$ and favor magnetic coupling mechanisms involving $pd$-exchange. Using state-of-the-art density functional theory (DFT) calculations in combination with XMCD and resonant photoelectron spectroscopy (resPES), we reveal the important role of the $3d$ impurity states in mediating magnetic exchange coupling. Our calculations illustrate that the kind and strength of the exchange coupling varies with the impurity $3d$-shell occupation. We find a weakening of ferromagnetic properties upon the increase of doping concentration, as well as with the substitution of Bi at the Sb site. Finally, we qualitatively describe the origin of the induced magnetic moments at the Te and Sb sites in the host lattice and discuss their role in mediating a robust ferromagnetism based on a $pd$-exchange interaction scenario. Our findings reveal important clues to designing higher $T_{\text{C}}$ MTIs.
Rare-earth ions typically exhibit larger magnetic moments than transition-metal ions and thus promise the opening of a wider exchange gap in the Dirac surface states of TIs, which is favorable for the realization of the high-temperature QAH effect. Therefore, we have further focused on Eu-doped Bi$_2$Te$_3$ and scrutinized whether the conditions for formation of a substantial gap in this system are present by combining spectroscopic and bulk characterization methods with theoretical calculations. For all studied Eu doping concentrations, our atomic multiplet analysis of the $M_{4,5}$ x-ray absorption and magnetic circular dichroism spectra reveals a Eu$^{2+}$ valence, unlike most other rare earth elements, and confirms a large magnetic moment. At temperatures below 10 K, bulk magnetometry indicates the onset of antiferromagnetic ordering. This is in good agreement with DFT results, which predict AFM interactions between the Eu impurities due to the direct overlap of the impurity wave functions. Our results support the notion of antiferromagnetism coexisting with topological surface states in rare-earth doped Bi$_2$Te$_3$ and corroborate the potential of such doping to result in an antiferromagnetic TI with exotic quantum properties.
The doping with impurities introduces disorder detrimental for the QAH effect, which may be avoided in stoichiometric, well-ordered magnetic compounds. In the last part of the thesis we have investigated the recently discovered intrinsic magnetic TI (IMTI) MnBi$_6$Te$_{10}$, where we have uncovered robust ferromagnetism with $T_{\text{C}} \approx 12$ K and connected its origin to the Mn/Bi intermixing. Our measurements reveal a magnetically intact surface with a large moment, and with FM properties similar to the bulk, which makes MnBi$_6$Te$_{10}$ a promising candidate for the QAH effect at elevated temperatures. Moreover, using an advanced ab initio MLFT approach we have determined the ground-state properties of Mn and revealed a predominant contribution of the $d^5$ configuration to the ground state, resulting in a $d$-shell electron occupation $n_d = 5.31$ and a large magnetic moment, in excellent agreement with our DFT calculations and the bulk magnetometry data. Our results together with first principle calculations based on the DFT-GGA$+U$, performed by our collaborators, suggest that carefully engineered intermixing plays a crucial role in achieving a robust long-range FM order and therefore could be the key for achieving enhanced QAH effect properties.
We expect our findings to aid better understanding of MTIs, which is essential to help increasing the temperature of the QAH effect, thus facilitating the realization of low-power electronics in the future.
For formative evaluations of user experience (UX) a variety of methods have been developed over the years. However, most techniques require the users to interact with the study as a secondary task. This active involvement in the evaluation is not inclusive of all users and potentially biases the experience currently being studied. Yet there is a lack of methods for situations in which the user has no spare cognitive resources. This condition occurs when 1) users' cognitive abilities are impaired (e.g., people with dementia) or 2) users are confronted with very demanding tasks (e.g., air traffic controllers). In this work we focus on emotions as a key component of UX and propose the new structured observation method Proxemo for formative UX evaluations. Proxemo allows qualified observers to document users' emotions by proxy in real time and then directly link them to triggers. Technically this is achieved by synchronising the timestamps of emotions documented by observers with a video recording of the interaction.
In order to facilitate the documentation of observed emotions in highly diverse contexts we conceptualise and implement two separate versions of a documentation aid named Proxemo App. For formative UX evaluations of technology-supported reminiscence sessions with people with dementia, we create a smartwatch app to discreetly document emotions from the categories anger, general alertness, pleasure, wistfulness and pride. For formative UX evaluations of prototypical user interfaces with air traffic controllers we create a smartphone app to efficiently document emotions from the categories anger, boredom, surprise, stress and pride. Descriptive case studies in both application domains indicate the feasibility and utility of the method Proxemo and the appropriateness of the respectively adapted design of the Proxemo App.
The third part of this work is a series of meta-evaluation studies to determine quality criteria of Proxemo. We evaluate Proxemo regarding its reliability, validity, thoroughness and effectiveness, and compare Proxemo's efficiency and the observers' experience to documentation with pen and paper. Proxemo is reliable, as well as more efficient, thorough and effective than handwritten notes and provides a better UX to observers. Proxemo compares well with existing methods where benchmarks are available.
With Proxemo we contribute a validated structured observation method that has shown to meet requirements formative UX evaluations in the extreme contexts of users with cognitive impairments or high task demands. Proxemo is agnostic regarding researchers' theoretical approaches and unites reductionist and holistic perspectives within one method.
Future work should explore the applicability of Proxemo for further domains and extend the list of audited quality criteria to include, for instance, downstream utility. With respect to basic research we strive to better understand the sources leading observers to empathic judgments and propose reminisce and older adults as model environment for investigating mixed emotions.
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.
Facing Enemies. Modulation of Revenge Interactions based on Opponent State Indicators of Suffering
(2023)
Research on revenge often treats vengeful acts as singular one-way experiences, an approach which fails to account for the social nature and functions of revenge. This dissertation aims to integrate emotional punishment reactions into dynamic revenge sequences to investigate the affective and cognitive consequences of revenge within a social interaction.
Exacting revenge can evoke intense affective consequences, from feelings of guilt to the genuine enjoyment of the suffering of others. In Chapter 2, affective responses towards suffering opponents and the regulation of aggression based on the appraisal of distinct suffering indicators were investigated. Results indicate that the observation of opponent pain evokes positive affect (measured via facial muscle contractions during the observation), which is followed by a downregulation of subsequent punishment. Both, positive affective reactions and the downregulation of punishment, were only observed following pain and not sadness expressions. Empathic distress, indexed by negative affective reactions, was only present following the observation of pain in non-provoking opponents. Showcasing the modulation of empathy related processes due to provocation and competition.
In Chapter 3, a significant escalation of punishment, when being confronted with Schadenfreude, was observed. Results are interpreted as supporting the assumption that opponent monitoring processes inform subsequent action selection. The observation of opponent smiles led to imitation behavior (facial mimicry), which was partially attenuated due to previous provocation. The different functions of smile mimicry in the context of the aggressive competitive setting are discussed as containing simulation aspects (to aid in opponent understanding) and as a potential mirroring of dominance gestures, to avoid submission.
In an additional series of studies, which are presented in Chapter 4, changes in memory of opponent faces following vengeful encounters were measured. Based on provocation, and punishment outcomes (pain & anger), face memory was distorted, resulting in more positive representations of opponents that expressed pain. These results are discussed as evidence of the impact of outcome appraisals in the formation of opponent representations and are theorized to aid empathy avoidance in future interactions.
The comparison of desired and observed opponent states, is theorized to result in appraisals of the punishment outcomes, which evoke affective states, inform the action selection of subsequent punishments, and are integrated into the representation of the opponent in memory.
Overall, the results indicate that suffering cues that are congruent with the chosen punishment action are appraised as positive, evoking an increase in positive affect. The emergence of positive affect during the observation of successful aggressive actions supports recent theories about the chronification of aggressive behavior based on reinforcement learning. To allow positive affect to emerge, affective empathic responses, such as distress, are theorized to be suppressed to facilitate the goal attainment process. The suffering of the opponent constitutes the proximate goal during revenge taking, which highlights the importance of a theoretical differentiation of proximate and ultimate goals in revenge to allow for a deeper understanding of the underlying motives of complex revenge behavior.
Proton‐coupled electron‐transfer (PCET) processes play a key role in biocatalytic energy conversion and storage, for example, photosynthesis or nitrogen fixation. Here, we report a series of bipyridine‐containing di‐ to tetranuclear Ru(bda) macrocycles 2 C–4 C (bda: 2,2′‐bipyridine‐6,6′‐dicarboxylate) to promote O−O bond formation. In photocatalytic water oxidation under neutral conditions, all complexes 2 C–4 C prevail in a folded conformation that support the water nucleophilic attack (WNA) pathway with remarkable turnover frequencies of up to 15.5 s\(^{−1}\) per Ru unit respectively. Single‐crystal X‐ray analysis revealed an increased tendency for intramolecular π‐π stacking and preorganization of the proximal bases close to the active centers for the larger macrocycles. H/D kinetic isotope effect studies and electrochemical data demonstrate the key role of the proximal bipyridines as proton acceptors in lowering the activation barrier for the crucial nucleophilic attack of H\(_{2}\)O in the WNA mechanism.
Isolated 2‐phenylallyl radicals (2‐PA), generated by pyrolysis from a nitrite precursor, have been investigated by IR/UV ion dip spectroscopy using free electron laser radiation. 2‐PA is a resonance‐stabilized radical that is considered to be involved in the formation of polycyclic aromatic hydrocarbons (PAH) in combustion, but also in interstellar space. The radical is identified based on its gas‐phase IR spectrum. Furthermore, a number of bimolecular reaction products are identified, showing that the self‐reaction as well as reactions with unimolecular decomposition products of 2‐PA form several PAH efficiently. Possible mechanisms are discussed and the chemistry of 2‐PA is compared with the one of the related 2‐methylallyl and phenylpropargyl radicals.
To study coisotropic reduction in the context of deformation quantization we introduce constraint manifolds and constraint algebras as the basic objects encoding the additional information needed to define a reduction. General properties of various categories of constraint objects and their compatiblity with reduction are examined. A constraint Serre-Swan theorem, identifying constraint vector bundles with certain finitely generated projective constraint modules, as well as a constraint symbol calculus are proved. After developing the general deformation theory of constraint algebras, including constraint Hochschild cohomology and constraint differential graded Lie algebras, the second constraint Hochschild cohomology for the constraint algebra of functions on a constraint flat space is computed.
Despite accounting for only a small proportion of all skin cancers, malignant melanoma
displays a serious health risk with increasing incidence and high mortality rate. Fortunately,
advances in the treatment of malignant melanoma now prolong survival and enhance response
and treatment efficacy. Established biomarkers help evaluate disease progression and
facilitate choosing appropriate and individual treatment options. However, the need for easily
accessible and reliable biomarkers is rising to predict patient-specific clinical outcome.
Eosinophil infiltration into the tumor and high peripheral eosinophil counts prior and during
treatment have been associated with better response in patients for various cancer entities,
including melanoma. An analysis of a heterogeneous study cohort reported high serum ECP
levels in non-responders. Hence, eosinophil frequency and serum ECP as a soluble
eosinophil-secreted mediator were suggested as prognostic biomarkers in melanoma. We
examined whether melanoma patients treated with first-line targeted therapy could also benefit
from the effects of eosinophils. In total, 243 blood and serum samples from patients with
advanced melanoma were prospectively and retrospectively collected before and after drug
initiation. To link eosinophil function to improved clinical outcome, soluble serum markers and
peripheral blood counts were used for correlative studies using a homogeneous study cohort.
In addition, functional and phenotypical characterizations provided insights into the expression
profile and activity of freshly isolated eosinophils, including comparisons between patients and
healthy donors.
Our data showed a significant correlation between high pre-treatment blood eosinophil counts
and improved response to targeted therapy and by trend to combinatorial immunotherapy in
patients with metastatic melanoma. In accordance with previous studies our results links
eosinophil blood counts to better response in melanoma patients. High pre-treatment ECP
serum concentration correlated with response to immunotherapy but not to targeted therapy.
Eosinophils from healthy donors and patients showed functional and phenotypical similarities.
Functional assays revealed a strong cytotoxic potential of blood eosinophils towards
melanoma cells in vitro, inducing apoptosis and necrosis. In addition, in vitro cytotoxicity was
an active process of peripheral eosinophils and melanoma cells with bidirectional features and
required close cell-cell interaction. The extent of cytotoxicity was dose-dependent and showed
susceptibility to changes in physical factors like adherence. Importantly, we provide evidence
of an additive tumoricidal function of eosinophils and combinatorial targeted therapy in vitro. In
summary, we give valuable insights into the complex and treatment-dependent role of
eosinophils in melanoma. As a result, our data support the suggestion of eosinophils and their
secreted mediators as potential prognostic biomarkers. It will take additional studies to
examine the molecular mechanisms that underlie our findings.
The great progress in organic photovoltaics (OPV) over the past few years has been largely achieved by the development of non‐fullerene acceptors (NFAs), with power conversion efficiencies now approaching 20%. To further improve device performance, loss mechanisms must be identified and minimized. Triplet states are known to adversely affect device performance, since they can form energetically trapped excitons on low‐lying states that are responsible for non‐radiative losses or even device degradation. Halogenation of OPV materials has long been employed to tailor energy levels and to enhance open circuit voltage. Yet, the influence on recombination to triplet excitons has been largely unexplored. Using the complementary spin‐sensitive methods of photoluminescence detected magnetic resonance and transient electron paramagnetic resonance corroborated by transient absorption and quantum‐chemical calculations, exciton pathways in OPV blends are unravelled employing the polymer donors PBDB‐T, PM6, and PM7 together with NFAs Y6 and Y7. All blends reveal triplet excitons on the NFA populated via non‐geminate hole back transfer and, in blends with halogenated donors, also by spin‐orbit coupling driven intersystem crossing. Identifying these triplet formation pathways in all tested solar cell absorber films highlights the untapped potential for improved charge generation to further increase plateauing OPV efficiencies.
For decades autonomy has been utilised as a concept in various social sciences, like sociology, political science, law and philosophy. Certain concepts of autonomy have always reflected the needs of the respective disciplines that made use of the term, but also ever infringed on the interpretation of autonomy in other disciplines. Most notably, conceptualisations of international and constitutional law have found their way into bordering sciences, like political science. The result: a legal positivist view prevailing in the conceptualisations of autonomy within political and administrative sciences. As this working paper points out, this perspective does not do justice to the complex phenomenon autonomy is or may be in social and political reality. Hence, the paper argues for a differentiated concept of autonomy, splitting it into autonomy claims, actors, process, rights and powers, regimes, and their institutions. The empirical world suggests a salience of formally and informally lived types of autonomy, especially in Latin America, due to the region’s indigenous population often living outside of, or within the limited reach of the state. Therefore, the paper aims to incorporate the dimension of informality – lacking in previous legal positivist approaches. Autonomy regimes could be entrenched in international, constitutional, or secondary law, or they could be tolerated by the state or seized by autonomy claimants by force. From a theoretical or conceptual perspective, the dimension of (in)formality facilitates the incorporation of autonomy into the discussion on governance and government, mostly on the local or regional level. Thus, the paper establishes autonomy regimes as a concept located at the verges of (self-)government and (self-)governance.
Exploring the Relationship Between Social Movement Organizations and the State in Latin America
(2023)
Under conditions of weak statehood, societal actors are supposed to assume functions usually attributed to the state. Social self-organization is expected to emerge when the state leaves important social problems unattended. Should social self-organization, therefore, be regarded as a reaction to state weakness and as compensation for state failure in the provision of basic services? Does society organize itself on its own in areas where the state is absent or ineffective? By the example of two Latin American social movements, this article aims to show that social self-organization—at least on a larger scale—is not independent of the state, but rather a result of a dynamic interaction with the state. The two examples this article explores are the middle-class Venezuelan neighborhood movement and the Argentine piquetero movement of unemployed workers. Both movements emerged as reactions to the state’s failure and retreat from essential social functions and both developed into extensive and influential social actors. For that reason, they can be regarded as crucial cases for observing the patterns and conditions of social self-organization and autonomous collective action within the specific Latin American context. Despite their different backgrounds and social bases, the two cases reveal remarkable similarities. They show that the emergence and development of self-organized social groups cannot be conceived simply as a reaction to state weakness, but rather should be viewed as a dynamic interaction with the state.
The nervous system relies on an orchestrated assembly of complex cellular entities called neurons, which are specifically committed to information management and transmission. Inter-neuronal communication takes place via synapses, membrane-membrane junctions which ensure efficient signal transfer. Synaptic neurotransmission involves release of presynaptic neurotransmitters and their reception by cognate receptors at postsynaptic terminals. Inhibitory neurotransmission is primarily mediated by the release of neurotransmitters GABA (γ-Aminobutyric acid) and glycine, which are precisely sensed by GABA type-A receptors (GABAARs) and glycine receptors (GlyRs), respectively. GABAAR assembly and maintenance is coordinated by various postsynaptic neuronal factors including the scaffolding protein gephyrin, the neuronal adaptor collybistin (CB) and cell adhesion proteins of the neuroligin (NL) family, specifically NL2 and NL4.
At inhibitory postsynaptic specializations, gephyrin has been hypothesized to form extended structures underneath the plasma membrane, where its interaction with the receptors leads to their stabilization and impedes their lateral movement. Gephyrin mutations have been associated with various brain disorders, including autism, schizophrenia, Alzheimer’s disease, and epilepsy. Furthermore, gephyrin loss is lethal and causes mice to die within the first post-natal day. Gephyrin recruitment from intracellular deposits to postsynaptic membranes primarily relies on the adaptor protein CB.
As a moonlighting protein, CB, a guanine nucleotide exchange factor (GEF), also catalyzes a nucleotide exchange reaction, thereby regenerating the GTP-bound state of the small GTPase Cdc42 from its GDP-bound form. The CB gene undergoes alternative splicing with the majority of CB splice variants featuring an N-terminal SH3 domain followed by tandem Dbl-homology (DH) and pleckstrin-homology (PH) domains. Previous studies demonstrated that the most widely expressed, SH3-domain containing splice variant (CB2SH3+) preferentially adopts a closed conformation, in which the N-terminally located SH3 domain forms intra-molecular interaction with the DH-PH domain tandem. Previous cell-based studies indicated that SH3 domain-encoding CB variants remain untargeted and colocalize with intracellular gephyrin deposits and hence require additional factors which interact with the SH3 domain, thus inducing an open or active conformation. The SH3 domain-deficient CB isoform (CB2SH3-), on the contrary, adopts an open conformation, which possess enhanced postsynaptic gephyrin-clustering and also effectively replenishes the GTP-bound small GTPase-Cdc42 from its GDP-bound state.
Despite the fundamental role of CB as a neuronal adaptor protein maintaining the proper function of inhibitory GABAergic synapses, its interactions with the neuronal scaffolding protein gephyrin and other post synaptic neuronal factors remain poorly understood. Moreover, CB interaction studies with the small GTPase Cdc42 and TC10, a closely related member of Cdc42 subfamily, remains poorly characterized. Most importantly, the roles of the neuronal factors and small GTPases in CB conformational activation have not been elucidated.
This PhD dissertation primarily focuses on delineating the molecular basis of the interactions between CB and postsynaptic neuronal factors. During the course of my PhD dissertation, I engineered a series of CB FRET (Förster Resonance Energy Transfer) sensors to characterize the CB interaction with its binding partners along with outlining their role in CB conformational activation. Through the aid of these CB FRET sensors, I analyzed the gephyrin-CB interaction, which, due to technical limitations remained unaddressed for more than two decades (refer Chapter 2 for more details). Subsequently, I also unraveled the molecular basis of the interactions between CB and the neuronal cell adhesion factor neuroligin 2 (refer chapter 2) and the small GTPases Cdc42 and TC10 (refer chapter 3) and describe how these binding partners induce a conformational activation of CB.
In summary, this PhD dissertation provides strong evidence of a closely knit CB communication network with gephyrin, neuroligin and the small GTPase TC10, wherein CB activation from closed/inactive to open/active states is effectively triggered by these ligands.
The present study discusses money and conflicts and anxiety over money in late Ming vernacular stories and contextualizes these stories in the contemporary society of economic prosperity and rapid changes. The high monetization and extensive use of silver and copper cash as currency brought both wealth and conflicts in various aspects of society. Eleven vernacular stories from several collections are adopted as source materials for the close examination, including Jingshi tongyan (Stories to Caution the World, 1624) and Xingshi hengyan (Stories to Awaken the World, 1627) by Feng Menglong (1574-1646) and the two Pai’an jingqi (Slapping the Table in Amazement, 1628 and 1632) collections by Ling Mengchu (1580-1644), etc. The analysis then focuses on the relationship between money and four topics, the late Ming context, social relations, gender ideals, and religion. Multiple voices and various viewpoints in these narratives show human beings’ struggles in taming and dominating money, the increasingly familiar and essential object in everyday life. Generally, when people cannot control money properly, there is a fear of its detrimental power to humans and social relations within and beyond families. On the contrary, characters, who are able to control money, are praised.
Insights;
(2023)
The cluster of texts assembled here were imagined, crafted, and brought together as a collaborative writing project that emerged from the seminar titled "Words Matter Worlds: Activist Scholarship and Literary Praxis," which convened over the course of the 2021/22 winter semester as an offering of the American Studies department of the Julius-Maximilians-Universität Würzburg. Like the seminar that nurtured the considerations that evolve here, these contributions engage with how scholarly writing practices in general, and literary and cultural studies in particular, can remake the world.
Mammalian embryonic development is subject to complex biological relationships that need to be understood. However, before the whole structure of development can be put together, the individual building blocks must first be understood in more detail. One of these building blocks is the second cell fate decision and describes the differentiation of cells of the inner cell mass of the embryo into epiblast and primitive endoderm cells. These cells then spatially segregate and form the subsequent bases for the embryo and yolk sac, respectively. In organoids of the inner cell mass, these two types of progenitor cells are also observed to form, and to some extent to spatially separate. This work has been devoted to these phenomena over the past three years. Plenty of studies already provide some insights into the basic mechanics of this cell differentiation, such that the first signs of epiblast and primitive endoderm differentiation, are the expression levels of transcription factors NANOG and GATA6. Here, cells with low expression of GATA6 and high expression of NANOG adopt the epiblast fate. If the expressions are reversed, a primitive endoderm cell is formed. Regarding the spatial segregation of the two cell types, it is not yet clear what mechanism leads to this. A common hypothesis suggests the differential adhesion of cell as the cause for the spatial rearrangement of cells. In this thesis however, the possibility of a global cell-cell communication is investigated. The approach chosen to study these phenomena follows the motto "mathematics is biology's next microscope". Mathematical modeling is used to transform the central gene regulatory network at the heart of this work into a system of equations that allows us to describe the temporal evolution of NANOG and GATA6 under the influence of an external signal. Special attention is paid to the derivation of new models using methods of statistical mechanics, as well as the comparison with existing models. After a detailed stability analysis the advantages of the derived model become clear by the fact that an exact relationship of the model parameters and the formation of heterogeneous mixtures of two cell types was found. Thus, the model can be easily controlled and the proportions of the resulting cell types can be estimated in advance. This mathematical model is also combined with a mechanism for global cell-cell communication, as well as a model for the growth of an organoid. It is shown that the global cell-cell communication is able to unify the formation of checkerboard patterns as well as engulfing patterns based on differently propagating signals. In addition, the influence of cell division and thus organoid growth on pattern formation is studied in detail. It is shown that this is able to contribute to the formation of clusters and, as a consequence, to breathe some randomness into otherwise perfectly sorted patterns.
Plexus injury often occurs after motor vehicle accidents and results in lifelong disability with severe neuropathic pain. Surgical treatment can partially restore motor functions, but sensory loss and neuropathic pain persist. Regenerative medicine concepts, such as cell replacement therapies for restoring dorsal root ganglia (DRG) function, set high expectations. However, up to now, it is unclear which DRG cell types are affected by nerve injury and can be targeted in regenerative medicine approaches.
This study followed the hypothesis that satellite glial cells (SGCs) might be a suitable endogenous cell source for regenerative medicine concepts in the DRG. SGCs originate from the same neural crest-derived cell lineage as sensory neurons, making them attractive for neural repair strategies in the peripheral nervous system. Our hypothesis was investigated on three levels of experimentation. First, we asked whether adult SGCs have the potential of sensory neuron precursors and can be reprogrammed into sensory neurons in vitro. We found that adult mouse DRG harbor SGC-like cells that can still dedifferentiate into progenitor-like cells. Surprisingly, expression of the early developmental transcription factors Neurog1 and Neurog2 was sufficient to induce neuronal and glial cell phenotypes. In the presence of nerve growth factor, induced neurons developed a nociceptor-like phenotype expressing functional nociceptor markers, such as the ion channels TrpA1, TrpV1 and NaV1.9. In a second set of experiments, we used a rat model for peripheral nerve injury to look for changes in the DRG cell composition. Using an unbiased deep learning-based approach for cell analysis, we found that cellular plasticity responses after nerve injury activate SGCs in the whole DRG. However, neither injury-induced neuronal death nor gliosis was observed. Finally, we asked whether a severe nerve injury changed the cell composition in the human DRG. For this, a cohort of 13 patients with brachial plexus injury was investigated. Surprisingly, in about half of all patients, the injury-affected DRG showed no characteristic DRG tissue. The complete entity of neurons, satellite cells, and axons was lost and fully replaced by mesodermal/connective tissue. In the other half of the patients, the basic cellular entity of the DRG was well preserved. Objective deep learning-based analysis of large-scale bioimages of the “intact” DRG showed no loss of neurons and no signs of gliosis.
This study suggests that concepts for regenerative medicine for restoring DRG function need at least two translational research directions: reafferentation of existing DRG units or full replacement of the entire multicellular DRG structure. For DRG replacement, SGCs of the adult DRG are an attractive endogenous cell source, as the multicellular DRG units could possibly be rebuilt by transdifferentiating neural crest-derived sensory progenitor cells into peripheral sensory neurons and glial cells using Neurog1 and Neurog2.
Evidence synthesis findings depend on the assumption that the included studies follow good clinical practice and results are not fabricated or false. Studies which are problematic due to scientific misconduct, poor research practice, or honest error may distort evidence synthesis findings. Authors of evidence synthesis need transparent mechanisms to identify and manage problematic studies to avoid misleading findings. As evidence synthesis authors of the Cochrane COVID-19 review on ivermectin, we identified many problematic studies in terms of research integrity and regulatory compliance. Through iterative discussion, we developed a research integrity assessment (RIA) tool for randomized controlled trials for the update of this Cochrane review. In this paper, we explain the rationale and application of the RIA tool in this case study. RIA assesses six study criteria: study retraction, prospective trial registration, adequate ethics approval, author group, plausibility of methods (e.g., randomization), and plausibility of study results. RIA was used in the Cochrane review as part of the eligibility check during screening of potentially eligible studies. Problematic studies were excluded and studies with open questions were held in awaiting classification until clarified. RIA decisions were made independently by two authors and reported transparently. Using the RIA tool resulted in the exclusion of >40% of studies in the first update of the review. RIA is a complementary tool prior to assessing “Risk of Bias” aiming to establish the integrity and authenticity of studies. RIA provides a platform for urgent development of a standard approach to identifying and managing problematic studies.
Background
Ischemic stroke immediately evokes a strong neuro-inflammatory response within the vascular compartment, which contributes to primary infarct development under vessel occlusion as well as further infarct growth despite recanalization, referred to as ischemia/reperfusion injury. Later, in the subacute phase of stroke (beyond day 1 after recanalization), further inflammatory processes within the brain parenchyma follow. Whether this second wave of parenchymal inflammation contributes to an additional/secondary increase in infarct volumes and bears the potential to be pharmacologically targeted remains elusive. We addressed the role of the NLR-family pyrin domain-containing protein 3 (NLRP3) inflammasome in the subacute phase of ischemic stroke.
Methods
Focal cerebral ischemia was induced in C57Bl/6 mice by a 30-min transient middle cerebral artery occlusion (tMCAO). Animals were treated with the NLRP3 inhibitor MCC950 therapeutically 24 h after or prophylactically before tMCAO. Stroke outcome, including infarct size and functional deficits as well as the local inflammatory response, was assessed on day 7 after tMCAO.
Results
Infarct sizes on day 7 after tMCAO decreased about 35% after delayed and about 60% after prophylactic NLRP3 inhibition compared to vehicle. Functionally, pharmacological inhibition of NLRP3 mitigated the local inflammatory response in the ischemic brain as indicated by reduction of infiltrating immune cells and reactive astrogliosis.
Conclusions
Our results demonstrate that the NLRP3 inflammasome continues to drive neuroinflammation within the subacute stroke phase. NLRP3 inflammasome inhibition leads to a better long-term outcome—even when administered with a delay of 1 day after stroke induction, indicating ongoing inflammation-driven infarct progression. These findings may pave the way for eagerly awaited delayed treatment options in ischemic stroke.
Empathy, the act of sharing another person’s affective state, is a ubiquitous driver for helping others and feeling close to them. These experiences are integral parts of human behavior and society. The studies presented in this dissertation aimed to investigate the sustainability and stability of social closeness and prosocial decision-making driven by empathy and other social motives. In this vein, four studies were conducted in which behavioral and neural indicators of empathy sustainability were identified using model-based functional magnetic resonance imaging (fMRI).
Applying reinforcement learning, drift-diffusion modelling (DDM), and fMRI, the first two studies were designed to investigate the formation and sustainability of empathy-related social closeness (study 1) and examined how sustainably empathy led to prosocial behavior (study 2). Using DDM and fMRI, the last two studies investigated how empathy combined with reciprocity, the social norm to return a favor, on the one hand and empathy combined with the motive of outcome maximization on the other hand altered the behavioral and neural social decision process.
The results showed that empathy-related social closeness and prosocial decision tendencies persisted even if empathy was rarely reinforced. The sustainability of these empathy effects was related to recalibration of the empathy-related social closeness learning signal (study 1) and the maintenance of a prosocial decision bias (study 2). The findings of study 3 showed that empathy boosted the processing of reciprocity-based social decisions, but not vice versa. Study 4 revealed that empathy-related decisions were modulated by the motive of outcome maximization, depending on individual differences in state empathy.
Together, the studies strongly support the concept of empathy as a sustainable driver of social closeness and prosocial behavior.
Metallic nanostructures possess the ability to support resonances in the visible wavelength regime which are related to localized surface plasmons. These create highly enhanced electric fields in the immediate vicinity of metal surfaces. Nanoparticles with dipolar resonance also radiate efficiently into the far-field and hence serve as antennas for light. Such optical antennas have been explored during the last two decades, however, mainly as standalone units illuminated by external laser beams and more recently as electrically driven point sources, yet merely with basic antenna properties. This work advances the state of the art of locally driven optical antenna systems. As a first instance, the electric driving scheme including inelastic electron tunneling over a nanometer gap is merged with Yagi-Uda theory. The resulting antenna system consists of a suitably wired feed antenna, incorporating a tunnel junction, as well as several nearby parasitic elements whose geometry is optimized using analytical and numerical methods. Experimental evidence of unprecedented directionality of light emission from a nanoantenna is provided. Parallels in the performance between radiofrequency and optical Yagi-Uda arrays are drawn. Secondly, a pair of electrically connected antennas with dissimilar resonances is harnessed as electrodes in an organic light emitting nanodiode prototype. The organic material zinc phthalocyanine, exhibiting asymmetric injection barriers for electrons and holes, in conjunction with the electrode resonances, allows switching and controlling the emitted peak wavelength and directionality as the polarity of the applied voltage is inverted. In a final study, the near-field based transmission-line driving of rod antenna systems is thoroughly explored. Perfect impedance matching, corresponding to zero back-reflection, is achieved when the antenna acts as a generalized coherent perfect absorber at a specific frequency. It thus collects all guided, surface-plasmon mediated input power and transduces it to other nonradiative and radiative dissipation channels. The coherent interplay of losses and interference effects turns out to be of paramount importance for this delicate scenario, which is systematically obtained for various antenna resonances. By means of the here developed semi-analytical toolbox, even more complex nanorod chains, supporting topologically nontrivial localized edge states, are studied. The results presented in this work facilitate the design of complex locally driven antenna systems for optical wireless on-chip communication, subwavelength pixels, and loss-compensated integrated plasmonic nanocircuitry which extends to the realm of topological plasmonics.
Various types of cancer involve aberrant cell cycle regulation. Among the pathways responsible for tumor growth, the YAP oncogene, a key downstream effector of the Hippo pathway, is responsible for oncogenic processes including cell proliferation, and metastasis by controlling the expression of cell cycle genes. In turn, the MMB multiprotein complex (which is formed when B-MYB binds to the MuvB core) is a master regulator of mitotic gene expression, which has also been associated with cancer. Previously, our laboratory identified a novel crosstalk between the MMB-complex and YAP. By binding to enhancers of MMB target genes and promoting B-MYB binding to promoters, YAP and MMB co-regulate a set of mitotic and cytokinetic target genes which promote cell proliferation. This doctoral thesis addresses the mechanisms of YAP and MMB mediated transcription, and it characterizes the role of YAP regulated enhancers in transcription of cell cycle genes.
The results reported in this thesis indicate that expression of constitutively active, oncogenic YAP5SA leads to widespread changes in chromatin accessibility in untransformed human MCF10A cells. ATAC-seq identified that newly accessible and active regions include YAP-bound enhancers, while the MMB-bound promoters were found to be already accessible and remain open during YAP induction. By means of CRISPR-interference (CRISPRi) and chromatin immuniprecipitation (ChIP), we identified a role of YAP-bound enhancers in recruitment of CDK7 to MMB-regulated promoters and in RNA Pol II driven transcriptional initiation and elongation of G2/M genes. Moreover, by interfering with the YAP-B-MYB protein interaction, we can show that binding of YAP to B-MYB is also critical for the initiation of transcription at MMB-regulated genes. Unexpectedly, overexpression of YAP5SA also leads to less accessible chromatin regions or chromatin closing. Motif analysis revealed that the newly closed regions contain binding motifs for the p53 family of transcription factors. Interestingly, chromatin closing by YAP is linked to the reduced expression and loss of chromatin-binding of the p53 family member Np63. Furthermore, I demonstrate that downregulation of Np63 following expression of YAP is a key step in driving cellular migration.
Together, the findings of this thesis provide insights into the role of YAP in the chromatin changes that contribute to the oncogenic activities of YAP. The overexpression of YAP5SA not only leads to the opening of chromatin at YAP-bound enhancers which together with the MMB complex stimulate the expression of G2/M genes, but also promotes the closing of chromatin at ∆Np63 -bound regions in order to lead to cell migration.
Development, Simulation and Evaluation of Mobile Wireless Networks in Industrial Applications
(2023)
Manyindustrialautomationsolutionsusewirelesscommunicationandrelyontheavail-
ability and quality of the wireless channel. At the same time the wireless medium is
highly congested and guaranteeing the availability of wireless channels is becoming
increasingly difficult. In this work we show, that ad-hoc networking solutions can be
used to provide new communication channels and improve the performance of mobile
automation systems. These ad-hoc networking solutions describe different communi-
cation strategies, but avoid relying on network infrastructure by utilizing the Peer-to-
Peer (P2P) channel between communicating entities.
This work is a step towards the effective implementation of low-range communication
technologies(e.g. VisibleLightCommunication(VLC), radarcommunication, mmWave
communication) to the industrial application. Implementing infrastructure networks
with these technologies is unrealistic, since the low communication range would neces-
sitate a high number of Access Points (APs) to yield full coverage. However, ad-hoc
networks do not require any network infrastructure. In this work different ad-hoc net-
working solutions for the industrial use case are presented and tools and models for
their examination are proposed.
The main use case investigated in this work are Automated Guided Vehicles (AGVs)
for industrial applications. These mobile devices drive throughout the factory trans-
porting crates, goods or tools or assisting workers. In most implementations they must
exchange data with a Central Control Unit (CCU) and between one another. Predicting
if a certain communication technology is suitable for an application is very challenging
since the applications and the resulting requirements are very heterogeneous.
The proposed models and simulation tools enable the simulation of the complex inter-
action of mobile robotic clients and a wireless communication network. The goal is to
predict the characteristics of a networked AGV fleet.
Theproposedtoolswereusedtoimplement, testandexaminedifferentad-hocnetwork-
ing solutions for industrial applications using AGVs. These communication solutions
handle time-critical and delay-tolerant communication. Additionally a control method
for the AGVs is proposed, which optimizes the communication and in turn increases the
transport performance of the AGV fleet. Therefore, this work provides not only tools
for the further research of industrial ad-hoc system, but also first implementations of
ad-hoc systems which address many of the most pressing issues in industrial applica-
tions.