This dissertation studies (largely American) Science Fiction (SF) texts that are in some way “about” climate change or the anthropocene. While environmentally themed SF has received a significant amount of scholarly attention in the past decade, such academic Science Fiction studies tend to take for granted the political and literary value of writing this kind of SF, trained in scholarly reading practices that conceive of literary texts as imparting valuable knowledge. I propose that contemporary SF is largely written with an acute awareness of what academic readers “do” with such literature, and that academic readings of SF are in fact part of the same literary system as the studied SF itself, sharing the status of being “second-order observations”. In this dissertation I will therefore closely consider what readers and writers of (environmental) SF hope to “do with” texts, studying both how the genre community has defined itself and how two schools of literary analysis – the “suspicious” approach exemplified by Fredric Jameson, and the “post-critical” approach exemplified by Rita Felski – have conceived of the usefulness of literature; it will be my argument that a full analysis of environmental SF as a cultural object must be aware of the fact that such SF is, in turn, already aware of how academics read it. My other contribution to the theory of environmental SF literature will be to argue that more attention must be paid to the implied temporal gap between present and future in such fiction (chapter two). With this in mind, I will then read three moments in environmental SF. I will begin with the emergence of an environmental SF in the second half of the twentieth century, concurrent with the emergence of the environmental sciences and environmental non-fiction; particular attention will be given to science-fictional fantasies of overpopulation around the 1970s, which were used for political purposes by various writers and editors (chapter three). I will also re-read the rather canonical work of cyberpunk author William Gibson (written between 1981 and 2014), arguing that his fiction is not only disinterested in ecology, nature, and climate change, but in fact actively antiecological; written from the perspective of an “end of history”, catastrophic environmental degradation as a historical event becomes unimaginable for the cyberpunk of Gibson (chapter four). Thirdly, I will consider Kim Stanley Robinson’s recent Ministry for the Future (2020) as an example of an ecological SF that is written explicitly concerned both with the temporal gap between present and future, and with the question of how ecological fiction is supposed to effect political change in our non-fictional world (chapter five). In my concluding remarks, I will consider the prominent position of Rachel Carson’s environmental non-fiction text Silent Spring (1962) both in academic history of environmental SF and in two further recent works of environmental writing (chapter six).

This study investigates how social class differences are recontextualized into pedagogic practices in mathematics classrooms, shaping distinct social consciousnesses across different social groups, and ultimately perpetuating social insulation in subtle ways. The research is situated in secondary schools in Xi’an, the most developed city in Northwest China, in terms of population size and diversity of school types. Three school streams were selected to represent varying levels of social insulation.

The theoretical resource of this study is mainly drawn from Bernstein and Dowling. Bernstein’s theory of pedagogic discourse offers fundamental guidance that instructional discourse in pedagogic practices is governed by underlying regulative discourse like the principle of social class. His concepts like classification and framing, different values of knowledge, and a set of rules of pedagogic discourse, alongside Dowling’s Social Activity Method, which includes domains of practice and distributive strategies, offer concrete analytical instruments for examining the processes of recontextualization. Both quantitative and qualitative methods were used to address different research questions. Quantitative techniques were employed to investigate whether statistical class differences exhibited at the regional level where these samples were located, while qualitative analyses were conducted as tentative and exploratory study.

The thesis comprises three distinct but interconnected sub-studies, each representing a potential pathway of recontextualization. These pathways explore how class distinctions are transformed within pedagogic practices to legitimize and maintain social insulations. As a result, students are interpellated into accepting disparities in school achievements, which serve as indicators for their future roles within different divisions of labour and social positions.

The first part takes various forms of pedagogic communication as a possible way of recontextualization, which carries differentiated power relations. The quality of classroom interactions was extracted as a linking variable between forms of communication and differences in school achievement. The findings reveal that class differences transform into varying durations of peer interactions with a flatter hierarchy, prompting students’ engagement and autonomy. Therefore, social segregation is legitimized at the level of consciousness, as different social groups internalize these power relations through their engagement with specific forms of communication.

The second part explores pedagogic messages and the methods of their transmission by teachers as another pathway for recontextualization. By analyzing class differences in these two dimensions across different school streams, this exploratory study reveals that social class differences are converted in the range of esoteric mathematical knowledge conveyed and the methods used to transmit it. This process covertly legitimizes and reproduces social stratification.

The third part investigates the evaluation criteria contained in the content of teacher feedback and the way it is provided, serving as a further pathway for recontextualization. This sub-study found that class differences are translated in differentiated criteria for school success and in teachers’ perceptions of their students’ abilities, thereby legitimizing and reproducing social segregations through pedagogic practices.

Together, these three pathways provide evidence from different perspectives on how macro-level social class differences are recontextualized into micro-level mathematics pedagogic practices to achieve their legitimizing transmission. The contributions of this study are twofold: first, it extends the cross-cultural applicability of Bernstein and Dowling’s theories; second, it offers empirical support for how the principle of social class is transformed and legitimized in mathematics classrooms. These findings have implications for teacher training programs, particularly in integrating educational equity into three aspects: the arrangement of communication forms, the selection and organization of pedagogic tasks, and the provision of feedback, all aimed at narrowing the achievement gap between students from different social groups. Additionally, this thesis points forward to future research to explore other recontextualized pathways and the role of teachers’ personal backgrounds on the transmission of class differences.

The motion of salt water through the Earth's geomagnetic field generates characteristic electromagnetic (EM) signals. These ocean-induced EM signals can be observed from outside the ocean by space-borne satellite magnetometers. They depend on oceanic velocities and conductivity (i.e., temperature and salinity) and, therefore, could contribute to observing the ocean heat content or water mass transport. However, the identification of ocean-induced magnetic fields requires a separation from other geomagnetic field contributions (e.g., the core, lithosphere, and ionosphere). In contrast to tidal-induced EM signals, circulation-induced EM signals have not yet been identified in geomagnetic observations.

This thesis developed a novel Kalman-filter-based rescaling of EM signals (KREMS) to detect ocean-circulation-induced magnetic fields. The essential separation from other magnetic field contributions was achieved by predetermining the temporal behavior of the searched EM signal. KREMS was then used to locally rescale the amplitude of this predetermined EM signal by assimilating geomagnetic observations.

An observing system simulation experiment (OSSE) based on synthetic Swarm-like observations demonstrated that KREMS allowed for a global signal identification of circulation-induced EM signals regardless of their complex temporal behavior and low intensity. In an ideal scenario, the uncertainty of the rescaling could be reduced by 70% on average. The best detectability was found in the Indian Ocean basin and in parts of the Southern Ocean. In a more realistic scenario of the OSSE, KREMS performed comparably well as a least-squares approach. Moreover, it was shown that including spatial constraints in KREMS further improved signal identification.

Based on the these findings, KREMS was applied to seven years of real Swarm geomagnetic satellite observations. Compared to the OSSE, the Swarm assimilation results proved to be more ambiguous and strongly dependent on the presumed estimate of the circulation-induced EM signal. The rescaling remained highly uncertain and did not reveal a consistent spatial pattern. In some areas the signal-to-noise ratio turned out to be too low (e.g., the East Pacific Ocean), on others the rescaling indicates substantial discrepancies between the presumed and the true circulation-induced EM signal (e.g., the Southern Indian Ocean).

Finally, a purely observation-based detection of circulation-induced EM signals was considered by estimating the temporal behavior of the EM signal from satellite altimetry. This combination also indicated the potential of KREMS to correct water mass transport estimations (e.g., from satellite altimetry) and suggested the applicability of KREMS not only for examining the detectability of EM signals but also in a broader context of ocean observations.

Nanomaterials (NMs) can be manufactured to serve different industrial purposes by fine-tuning their physico-chemical properties. This results in a theoretically unlimited number of NM variants. Thereby, even small variations in the physico-chemical properties of a NM may have substantial influence on their uptake, toxicokinetics as well as (eco-)toxicity. Thus, in theory, risk assessment needs to be performed for all variants and all toxicological endpoint. As this is simply not feasible, grouping and read-across approaches which allow the transfer of information between sufficiently similar NMs are promising alternatives. However, establishing reliable grouping approaches for NMs is not trivial due to the current lack of understanding with respect to the relationship between individual physico-chemical properties and the toxicological profile of NMs. The overall aim of this thesis was to explore how machine learning (ML) approaches can be used to support NM grouping in finding such relationships or underlying patterns. As formulating a reliable grouping hypothesis may largely benefit from mechanistic understanding, the underlying modes-of-action (MoAs) for different NMs were also explored by investigating results from omics approaches. In the first study, the aim was to use ML for identifying the most important physico-chemical properties influencing the toxicity of NMs. Therefore, a dataset of eleven NMs with comprehensive description of their physico-chemical properties was used. These physico-chemical properties were then linked to available in vivo data obtained from short-term inhalation studies (STIS) and in vitro toxicity data measured with the so-called macrophage assay. In both cases, toxicity was represented as binary outcome variable indicating whether a NM was ‘active’ and ‘passive’ in the respective toxicity studies. Unsupervised and supervised ML approaches were trained on this dataset. In the unsupervised model, principal component analysis (PCA) was used to infer information on which physico-chemical properties have the strongest impact in the first two principal components (PCs). Afterwards, k-nearest neighbors (kNN) was applied to compare results to the defined activity levels. In the supervised counterpart, random forest (RF) analysis with and without recursive feature elimination (RFE) was performed. Toxicity classes were thereby directly used as labels in the model building process. Overall, the best model was obtained using RF with RFE. It reached a balanced accuracy of 0.82 and was built on the three parameters zeta potential, redox potential and dissolution rate. This study showed, how ML could support NM grouping approaches. At the same time, it was also obvious that predictive modeling based solely on physico-chemical properties has severe limitations. While this is widely accepted to date and also mentioned in various recommendations, this was not the case at the time of the study. Already with this small set of NMs 5 and compared to other studies a comprehensive description of physico-chemical properties, no perfect separation of ‘active’ and ‘passive’ NMs was possible. The second study, aimed at investigating the oxidative potential (OP) in addition to physico-chemical properties. Different assays for measuring the OP were evaluated with respect to their predictivity for NM toxicity. In addition, one goal was to find out whether or not OP assays could replace each other or whether results from different OP assay in different datasets could be combined. Within this study, four assays have been compared, namely the acellular surface reactivity assays electron spin resonance (ESR) spectroscopy using CPH spin probe and DMPO spin trap and the ferric reduction ability of serum (FRAS) assay as well as the cellular protein carbonylation assay as a marker for oxidative protein damage in NRK-52E cells. The comparison was based on a case study holding OP measurements for 35 NMs. For the four OP assays, mass-based doses were compared to surfacebased ones, correlations and clustering between assays were computed and their predictivity for the same outcome variables as in the first study was assessed for individual assays and all possible combinations of them in a logistic regression model. As a result of those comparisons, surface-based doses were shown to be more predictive than mass-based ones. In addition, correlations between the OP assays were only moderate. Within the logistic regression model, predictivity was highest for protein carbonylation or combinations of assays which include protein carbonylation. Thus, as expected, biological OP assays seem to predict the actual toxicity outcome more reliably. At the same time, combining datasets which used different OP assays for the purpose of building robust ML models based on large datasets is not easily possible as the assays are not highly correlated. Overall, OP seems to be very informative and relevant for NMs in general. However, also other toxicity mechanisms (not directly related to OP) may be triggered by NM treatment, which cannot be reflected by OP assays. The third study focused more generally on elucidating MoAs underlying NM toxicity. Here, proteomics data were to be explored for their potential to unravel MoAs of NMs to support NM grouping. However, as proteomics data for NMs are relatively scarce and interpretation is difficult due to missing reference data, the main idea was to integrate proteomics signatures observed for NMs with those from other traits like chemicals, drugs or diseases. As such meta-analyses are mainly hampered by the lack of standardization for proteomics data, a workflow for harmonized evaluation of public proteomics data and their integration in a meta-analysis setting was developed. The workflow PROTEOMAS aims to make proteomics data FAIR (findable, accessible, interoperable, reusable). In an initial case study, PROTEOMAS was tested on 25 proteomics datasets to investigate the toxicological effects of NMs in relation to those of other traits at the lung level. Proteomic 6 fingerprints and their similarities among the studied traits could be identified. PROTEOMAS was thus useful for meta-analysis of proteomic datasets. In the review article, an overview on the variety of ML models and omics approaches supporting NM grouping available in literature is provided. Corresponding models were collected and some overarching conclusions were drawn from these manuscripts. Especially, data availability and quality are a major concern preventing the development of robust ML models for NM toxicity prediction. In addition, measurements are usually not well-standardized and insufficient metadata is provided and thus datasets cannot be integrated. Overall, there is a strong need for FAIR data in the NM safety community which would then allow development of more reliable models and advancement of in silico tools in a regulatory context. It was also concluded, that recent developments in the field of AI may also greatly support data gap filling and improvement of metadata availability in NM databases as well as linked data concepts. Overall, ML models as well as omics methods were shown to be useful to support NM grouping approaches. However, data availability and standardization of methods are of utmost importance in order to be able to develop reliable models.

When animal rights activists enter farms or laboratories, they pose particular challenges for the law. How can the ethical motives of the activists be adequately taken into account in the legal assessment without giving them carte blanche for otherwise unlawful behaviour? This dissertation analyses, evaluates and compares the legislation and jurisprudence in Germany and other jurisdictions, particularly in the United States. In so doing, it incorporates the findings and methods of political theory alongside the legal assessment. The principles developed lay a foundation for a nuanced legal assessment of protest movements and methods on the limits of legality.

Die vorliegende Arbeit zeigt das komplexe Zusammenspiel der Geburtsmedizin und der Pränataldiagnostik, was eine personalisierte und risikoadaptierte Betreuung von Schwangeren ermöglicht. Es besteht ein breites Wissen über Risiken und mögliche Komplikationen. Die Demographie der Schwangeren hat sich durch das Hinzukommen von verschiedenen Risiken gewandelt: unter anderem steigendes Alter der Mütter, erhöhte Rate an Übergewicht und Adipositas sowie vermehrte Gewichtszunahme und Frauen mit einer Uterusnarbe, wie nach einem Kaiserschnitt und anderen Eingriffen. Die Vorsorge und die Beratung bei Schwangeren mit bestimmten Risikokonstellationen sollten angemessen und personalisiert erfolgen. Häufige Schwangerschaftskomplikationen wie der GDM können besser eingeschätzt und betreut werden, wenn bestimmte Eigenschaften berücksichtigt werden (zum Beispiel metabolische Typen). Die Schwangerenbetreuung geht Hand in Hand mit der Ultraschalldiagnostik. Zur Vorsorge gehören die drei Screeninguntersuchungen, die vom G BA vorgesehen sind. Zusätzlich kann eine weiterführende pränataldiagnostische Untersuchung angeboten werden: das Ersttrimesterscreening und die Feindiagnostik. Der differenzierte Ultraschall kann im ersten Trimester weiterführend dazu dienen, die fetale Anatomie und das Wachstum zu untersuchen, die Wahrscheinlichkeit für eine Trisomie 21, 13, 18 zu berechnen und mögliche Schwangerschaftsrisiken wie die Präeklampsie festzustellen. Bestimmte identifizierte Risiken wie die Präeklampsie können durch die 150 mg Gabe von Aspirin adressiert werden und erfahren damit eine Risikoreduktion. Zur differenzierten sonographischen Beurteilung stehen zahlreiche Möglichkeiten der 3D und 4D Sonographie zur Verfügung. Zusätzlich können Volumina mit Hilfe computerisierter automatischer Messung verarbeitet werden. Die KI basierte Anwendung kann Standardebenen generieren, die zur Beurteilung der relevanten Strukturen genutzt werden (zentrales Nervensystem, Echokardiographie, erstes Trimenon), was die Detektion von fetalen Anomalien erleichtert. Bei einer fetalen Fehlbildung werden weiterführende Untersuchungen angeboten, um eine mögliche Ursache zu klären. Zur Beurteilung des fetalen Karyotyps steht der NIPT zur Verfügung und kann zusätzlich nach Beratung angeboten werden. Die genetischen Untersuchungen erfolgen stufenweise und nach genetischer Beratung der werdenden Eltern: Karyotyp, ggf. Mikroarray, Trioexom. Mit jeder dieser Stufen können spezifische genetische Besonderheiten identifiziert werden: Aneuploidie, Strukturvarianten, monogene Erkrankungen. Welche Analysen durchgeführt werden, richtet sich nach dem fetalen Phänotyp und den Wünschen und Bedürfnissen der Eltern. Es existiert ein enormer Wissenszuwachs bezüglich seltener fetaler Erkrankungen und des entsprechenden fetalen Phänotyps und Genotyps. Auf dieser Grundlage können die werdenden Eltern hinsichtlich Prognose und Wiederholungswahrscheinlichkeit beraten werden. Um die Betreuung der Schwangeren und ihrer ungeborenen Kinder personalisiert und risikoadaptiert zu intensivieren und zu verbessern, steht eine Vielzahl an Untersuchungsmethoden zur Verfügung. Vor allem die Anwendung von komplexer genetischer Diagnostik und KI entwickelt sich rapide und ist aus der Schwangerenbetreuung nicht mehr wegzudenken.

Die Behandlung von Unterkieferfrakturen ist oft Teil eines komplexen Verletzungsmusters, das auch weitere Verletzungen des Viscerocraniums sowie anderer Körperregionen umfassen kann. Insbesondere bei polytraumatisierten Patienten, die häufig aus Verkehrsunfällen resultieren, steigt das Risiko für komplexe Gesichtsschädelverletzungen signifikant an. Eine vielversprechende Entwicklung in der Therapie von (Unterkiefer-)Frakturen ist die virtuelle computerassistierte präoperative Planung (CAPP) sowie die Durchführung virtueller Frakturrepositionen. Diese Methode hat das Potenzial, die Genauigkeit und Effizienz chirurgischer Eingriffe zu verbessern, indem sie das Verständnis des Frakturmusters fördert und individualisierte Behandlungsoptionen - wie die Erstellung und Fertigung von patientenspezifischen Implantaten - ermöglicht. Obwohl bereits vielversprechende Ergebnisse zu verschiedenen Ansätzen der virtuellen Frakturreposition vorliegen, wird die CAPP bisher hauptsächlich bei der Planung von elektiven Eingriffen im Kopf-Hals-Bereich eingesetzt. Um jedoch auch standardmäßig in der Traumatologie zum Einsatz zu kommen, sind derzeit noch Lösungen im Bereich der Softwareentwicklung zur (semi-) automatischen Frakturerkennung und -repositionierung erforderlich. Postoperative Komplikationen nach Unterkieferfrakturversorgung können von lokalen Wundinfektionen bis hin zu schweren Infektionen und beeinträchtigter Knochenheilung reichen. Zu den häufigsten Risikofaktoren für postoperative Komplikationen gehören Nikotin- und Alkoholabusus, das erhöhte Lebensalter, frakturspezifische Charakteristika aber auch Vorerkrankungen und die Patientencompliance. In unserer Untersuchung konnten wir feststellen, dass Männer ein signifikant höheres Risiko für postoperative Komplikationen aufweisen, was möglicherweise mit Unterschieden in der Knochenmorphologie sowie der Ätiologie der Fraktur zusammenhängt. Die Behandlung von Komplikationen erfordert oft Revisionseingriffe und stellt somit eine Belastung für das Gesundheitssystem sowie für Betroffene dar. Autologe Knochentransplantate sind zwar eine etablierte Methode zur Therapie von ossären Defekten, jedoch mit Nachteilen wie Hebedefektmorbidität verbunden. Alloplastische Implantate sind Gegenstand aktueller Forschungen und weisen materialspezifische Vor- und Nachteile auf. Poröse Implantate ermöglichen das Einwachsen des umliegenden Knochens wodurch eine bessere Integration und Stabilität erreicht werden soll. Neben der Mikroarchitektur beeinflusst die Nanoarchitektur von Implantatgerüsten die Knochenneubildung. Während bisher v.a. nicht-resorbierbare Materialien Anwendung fanden stellen resorbierbare Materialien vielversprechende Therapiestrategien dar.

Background/ aims: Growing evidence suggests a critical role of distinct gut microbially produced metabolites in developing cardiometabolic and -vascular diseases. The amino-acid-derived metabolite imidazole propionate (ImP) is increased in patients with pre- and type 2 diabetes. However, its impact on endothelial cell physiology and vascular disease has not been examined so far. Here, the effects of ImP were studied on endothelial cell function and inflammatory activation, as well as on endothelial regeneration after injury and development of atherosclerosis in atheroprone Apoe-/- mice.

Methods/ results: Cell culture experiments, next-generation sequencing, western blotting, and immunostaining were performed to identify the potential underlying mechanism of ImP-mediated effects on primary human aortic endothelial cells (HAECs). Transcriptomic profiling of HAECs revealed altered regulation of several genes involved in angiogenesis in ImP-treated cells. In particular, decreased PI3K/ AKT signaling was found upon pre-treatment of ImP, followed by insulin receptor stimulation with IGF-1, which led to an increase in FOXO1 protein expression as well as nuclear accumulation of FOXO1 in HAECs. Consequently, ImP impaired migratory and angiogenetic properties of endothelial cells assessed by scratch wound healing and Matrigel tube formation assay. Moreover, ImP promoted inflammatory activation of endothelial cells, leading to increased expression of pro-inflammatory cell adhesion molecules (VCAM-1, ICAM-1, and E-selectin) and, finally, to increased adhesion of monocytes under flow conditions. In an in vitro rescue experiment, the ImP-mediated pro-inflammatory phenotype was abrogated by targeted gene silencing of FOXO1 in endothelial cells. Vascular regeneration in vivo was analyzed using a carotid artery injury model (CI) in C57BL/6J mice treated with ImP or vehicle for three weeks via drinking water. Re-endothelialization was determined by Evans blue staining three days post-CI. The results showed that treatment with ImP significantly impaired wound healing compared to control animals. Finally, atherosclerotic plaque formation was analyzed in vivo using apolipoprotein E knockout (Apoe-/-) mice fed a standard chow diet (SCD) or high-fat diet (HFD) and simultaneously treated with vehicle or ImP in drinking water for 6 and 12 weeks. Oil red O staining displayed increased atherosclerotic plaque formation in en face aortic arch and aortic root sections upon ImP treatment. CD68 expression was also enhanced in murine atherosclerotic lesions in response to ImP treatment, indicative of increased macrophage accumulation.

Conclusion: The gut microbially produced metabolite ImP impairs the insulin receptor signaling pathway via PI3K/ AKT/ FOXO1 in endothelial cells, thereby affecting their functional properties such as migration, proliferation and angiogenic capacity. Moreover, ImP promotes inflammatory activation of endothelial cells leading to increased monocyte adhesion. These effects result in impaired vascular healing after injury and increased atherosclerosis in atheroprone Apoe-/- mice.

In der vorliegenden Habilitationsschrift werden neue Aspekte der periazetabulären Osteotomie (PAO) zur Behandlung der Hüftdysplasie untersucht. Im Fokus stehen intraoperative Modifikationen, perioperative Maßnahmen und postoperative Ergebnisse.

Intraoperativ wurden alternative Fixationstechniken evaluiert, insbesondere die Stabilität der Schraubenfixation mit und ohne horizontale Schraube sowie einer schraubenlosen K-Draht-Fixation. Ziel war die Analyse von Fixationsstabilität, Komplikationsraten und klinischen Ergebnissen über einen 5-Jahres-Zeitraum.

Perioperativ wurde der Einsatz eines Regionalverfahren als schmerztherapeutische Maßnahme untersucht, um den intraoperativen Opioidverbrauch zu reduzieren.

Postoperativ standen die Rückkehr zum präoperativen Aktivitätsniveau, Anpassungen der sportlichen Aktivität sowie die Auswirkungen der PAO auf Schwangerschaft und Geburtsweg im Vordergrund. Die Ergebnisse sollen die Entscheidungsfindung für Patient:innen und Behandler:innen erleichtern und die Therapie der Hüftdysplasie optimieren.

Die häufigsten malignen Tumoren des Pankreas sind exokrine Pankreaskarzinome. Betroffene Patient:innen haben nach wie vor eine stark eingeschränkte Prognose und lediglich ein Bruchteil ist zum Zeitpunkt der Diagnosestellung operabel. Die operative Resektion stellt weiterhin die einzige kurative Therapiemöglichkeit dar. Auch nach erfolgreicher onkologischer Resektion bleibt die Prognose der betroffenen Patient:innen stark eingeschränkt. Innerhalb der Gruppe resektabler Pankreaskarzinome besteht jedoch eine prognostische Heterogenität. Im Rahmen multimodaler Therapiekonzepte bildet eine prognostische Risikostratifikation die Grundlage für die Wahl des geeigneten Therapiekonzeptes. Die Präzisierung dieser Risikostratifikation bildet somit eine potentielle Grundlage für eine exaktere Indikationsstellung des geeigneten Therapiekonzeptes. Im Kontext der stark eingeschränkten Prognose des exokrinen Pankreaskarzinoms und der Morbidität onkologischer Resektionen ist die exakte prognostische Risikostratifikation essenziel für die bestmögliche Behandlung betroffener Patient:innen. Ziel der vorliegenden Arbeit ist die Herausarbeitung von Merkmalen prognostischer Heterogenität sowie die Präzisierung ihrer Identifizierung und somit die Weiterentwicklung dieser prognostischen Risikostratifikation bei Patient:innen mit resektablem exokrinen Pankreaskarzinom.

Fluid-rock interaction is a fundamental process in the earth system, capable of altering the chemical and physical properties of wall rocks, which in turn significantly influences the large-scale exposure of fluid-altered rock, geophysical observations and hydrothermal ore deposits. Greisenization represents such a fluid-rock interaction characterized by the replacement of biotite + feldspar by quartz + white mica ± topaz ± fluorite, which links fluid-rock interaction to the ore formation, particularly facilitating significant enrichments in W, Sn, and Li. However, the factors controlling greisen variation and the fluid evolution are not well understood. In this dissertation, I integrate natural sample analysis and a reactive transport model to investigate the greisenization process. The results indicate that the initial fluid composition, particularly F concentration and pH value, governs the variation of greisen. Additionally, boiling may serve as a mechanism to introduce F-rich fluid. Further, fluorine content in topaz is a probe to the F concentration change of fluid. This thesis emphasizes a novel perspective on how F influences the process of greisenization from natural observations to numerical modeling, which further contributes to a better understanding of greisen-related ore formation and F-related processes.

The first scientific section presents work on the Zinnwald/Cínovec quartz-topaz greisen, a typical example of fluid-rock interactions involving F-rich fluids. A transect with a width of 12 cm from this deposit presents a sequence of quartz-topaz greisen and weakly altered rhyolite. Mass balance calculation for this transect indicates a net gain of F, Si, etc. during greisenization. Fluid inclusions evidence suggests that boiling occurred during or before greisenization. To explain the observation, I propose a two-stage greisenization model. Initially, fluid boiling induces the phase separation of HF-rich vapor and brine. The vapor reacts with feldspar and biotite to form quartz and topaz, while mineral replacement creates significant transient porosity, which is then filled by brine and later sealed by the precipitation of quartz and fluorite due to oversaturation. This study underscores that fluid boiling, which introduces F-rich fluids, is essential for the formation of quartz-topaz-rich greisen.

Observations on Zinnwald/Cínovec quartz-topaz greisen reveal that the process of boiling introduces the F-rich fluid. However, the evolution of fluid composition is equally crucial to the mobility of metals of interest (e.g., W, Sn). In this case, topaz, a key F-bearing phase in quartz-topaz greisen, can be used to trace the fluid evolution, especially in terms of F content. In the second scientific section, I performed measurements of Raman spectrometry on topaz crystals collected from different locations. The results reveal that the distances of Raman bands shifts around 155 and 562 cm⁻¹ correlate with F concentration by a linear correlation (y = 0.329x – 113.6, where y represents F concentration and x the distance of Raman bands shifts around 155 and 562 cm⁻¹). Two types of topazes from the Zinnwald/Cínovec greisen profile were recognized based on CL imaging. The systematic F concentration difference of 0.4 wt. % among these two types of greisen indicates the F content change in the fluid equilibrated with greisen. This approach provides a newly practical method to determine F concentration in topaz, which could be used to trace the temporal (and/or spatial) evolution of aqueous F content during greisenization.

The case study of Zinnwald/Cínovec quartz-topaz greisen offers valuable insights into the formation of quartz-topaz greisen. However, the factors controlling the variation between quartz-topaz and quartz-mica greisen are not well understood. Based on the natural sample study, the third section of this dissertation introduces a reactive transport model to constrain the parameters governing the development of distinct greisen assemblages. The infiltrating fluid with a lower pH value and lower F concentration result in the formation of greisen characterized by a sequence of quartz-topaz and quartz-mica. In contrast, acdic fluid enriched in F (>0.015 mol/kg), lead to mica-free greisen formation. Additionally, the results of the numerical modeling suggest that quartz-topaz greisen has a higher porosity (14 %) compared to quartz-mica greisen (8 %), allowing that larger fluid volumes to pass through quartz-topaz greisen. These findings enhance our understanding of greisen variation and fluid evolution, which are critical to studying greisen-related ore formation.

In conclusion, the comprehensive study emphasizes the significance of quartz-topaz greisen in greisen systems, particularly its F-rich environment, which provides potential for rare metal enrichment. By examining processes from the mineral to the bulk rock scale, this work demonstrates that F plays a critical role in greisen systems. The novel method of determining F concentration in topaz through Raman spectroscopy enables the precise measurement. Moreover, the reactive transport model offers detailed constraints on fluid evolution during greisenization, improving the understanding of both greisen formation and associated ore deposits, such as those of W, Nb, and Ta. This dissertation covers a wide spectrum of greisen, providing valuable insights into the greisenization process.

Intra-tumor heterogeneity describes the coexistence of multiple genetically distinct subclones within the tumor of a patient resulting from somatic evolution, clonal diversification, and selection. It is a main causal driver of therapy resistance in the clinic by already containing subclones that are resistant to therapy or by subclones acquiring resistance to therapy. Therefore, the understanding of intra-tumor heterogeneity and tumor development may lead to new approaches and targets for treatment. In this thesis, I developed a method for the integrated analysis of bulk and single-cell DNA sequencing data of core-binding factor acute myeloid leukemia patients, which is defined by the presence of a RUNX1-RUNX1T1 or CBFB-MYH11 fusion gene. I generated a combined bulk and single-cell dataset of 9 core-binding factor acute myeloid leukemia patients with samples at diagnosis, complete remission and relapse. Using this method, I was able to reconstruct tumor development including somatic variants, somatic copy-number alterations and fusion genes from a single tumor sample and, if available, from merged diagnosis and relapse samples showing tumor evolution under the pressure of chemotherapy. I performed an in-depth analysis of small-scale and large-scale genomic alterations of leukemia patients and, moreover, demonstrate that my developed method can detect subclonal copy-number alterations with a higher resolution as compared to current methods.

Seasonal outbreaks of Influenza A virus (IAV) infections repeatedly challenge the immune system, which is in charge of controlling viral replication and facilitating clearance and subsequently recovery. T cells, which are part of the adaptive immune system, provide a highly specific response towards IAV during the acute infection phase that supports viral clearance. For that, activated effector T cells migrate from the lung-draining lymph nodes (drLN) to the side of infection, where they induce cell death of infected cells. Besides effector function in the lung, the follicular T helper cell subset provides help to B cells in drLN thereby supporting plasma cell differentiation and production of neutralizing antibodies. Furthermore, memory T cells reside long term in the body and serve as protection against re-infections. Although the T cell response is crucial for virus control, it has to be tightly regulated as T cell induced immunopathology and collateral tissue damage is disadvantageous. The protein T cell activation inhibitor, mitochondrial (TCAIM) was previously found to interfere with effector T cell differentiation and function. Yet, TCAIM overexpressing T cells were able to respond to activating stimuli by entering the proliferation cycle and reduced cytokine production. Thus, within the scope of this work, the question was addressed, if the degree of T cell activation and differentiation in TCAIM overexpressing mice is sufficient to facilitate viral clearance and to support establishment of a protective memory T cell pool. Furthermore, no in vivo data are available for TCAIM deficient T cells, but previous in vitro work showed an advantage in T cell activation under sub-optimal stimulation conditions. This raises the question, whether viral control is improved in TCAIM deficient mice. The here presented data show an impaired lung infiltration of TCAIM overexpressing T cells upon IAV infection, which is linked to the failure to modulate CD44 and CD62L receptor expression and upregu-lation of genes involved in migration and effector T cell differentiation. As a functional consequence cytokine production was diminished and viral clearance delayed. Nevertheless, TCAIM overexpressing mice did recover from IAV infection and were able to respond to infection induced activation stimuli seen in undisturbed type I interferon (IFN) signalling and T cell expansion within drLN. Importantly, reduced T cell response at the side of infection prevented T cell induced immunopathology since TCAIM overexpressing mice only slightly lost weight. Surprisingly, although generation of lung homing effector and tissue resident memory T cells was impaired, neutralizing antibodies were formed which might serve as protection during re-infection. TCAIM deficient T cells were found to predominantly accumulate at the side of infection. Early upregulation of Ifng and genes involved in T cell activation however did not translate into increased IFN-γ production at the peak of infection and improved viral control. VI In conclusion, the data within this work highlight the impact of TCAIM on T cell migration and the prevention of T cell induced immunopathology thereby proposing a beneficial role during IAV infections.

The field of highly frustrated magnetism harbors a wide variety of exotic phases that sustain interest in the field with no end in sight. Competing interactions yield models that often remain highly fluctuating down to zero temperature, have long-range entangled ground states, or exhibit fractionalized excitations. The study of these frustrated models presents a challenge for experimental and theoretical methods alike, driving their development in the process. As a contribution to the field, this thesis both further develops the pseudo-fermion functional renormalization group and applies the method in collaborative studies involving complementary methods to reveal low-temperature properties of a selection of frustrated spin models with relevance to spin compound families of recent interest.

In the first chapters of the thesis, the pseudo-fermion functional renormalization group is extended to enable the treatment of spin models with broken time-reversal symmetry. Newly accessible applications include models with finite magnetic fields in the form of site-dependent Zeeman terms. While previous formulations of the method could investigate magnetically ordered models only in their paramagnetic regime, often achieved by a finite renormalization group parameter in the model, the new scheme further allows the study of magnetic phases in absence of this parameter. In an exploratory study across a selection of Heisenberg and XXZ models, magnetic order parameters and magnetization plateaus will be compared with literature results to reveal for which newly accessible applications the method is best suited.

In addition to method development, a major emphasis of the thesis is placed on the study of nearest-neighbor spin models on the pyrochlore lattice. It is argued that the S = 1/2 and S = 1 Heisenberg models assume nematic ground states that break either only C3, or both C3 and lattice inversion symmetry. Quantum and classical phase diagrams of the model with Heisenberg and Dzyaloshinskii-Moriya interactions, and of non-Kramers pyrochlores are computed as well. In this context, an in-depth study of the so-called Γ5 phase will resolve subtle order-by-disorder selections from quantum or thermal fluctuations at both zero and critical temperatures. Furthermore, a model contained in both phase diagrams will be presented that exhibits a temperature-dependent spin liquid to spin liquid transition driven by entropic selections between ground state submanifolds in the case of classical spins. While the intermediate-temperature spin liquid can be described by coexisting vector and matrix gauge fields, spin degrees of freedom associated with the matrix gauge field depopulate as the temperature is lowered, realizing a spin-ice phase in the process. Emphasis is put on the study of the corresponding quantum model and its vicinity in the phase diagrams. This model is found to be best described in analogy to the intermediate-temperature classical spin liquid.

In the last part of the thesis, the pseudo-fermion functional renormalization group is applied in collaboration with classical Monte Carlo and inelastic neutron scattering to resolve the low-temperature behavior and magnetic order of the three-dimensional tetra-trillium compound and spin liquid candidate K2Ni2(SO4)3. The phase diagram of a Heisenberg model on the tetra-trillium lattice contextualizes the strongly fluctuating behavior of K2Ni2(SO4)3 by hosting a large paramagnetic region close to the density functional theory model of K2Ni2(SO4)3. In a broader scope, this region establishes compounds of the langbeinite family, which are described by Heisenberg models on the tetra-trillium lattice, as a promising platform in the future search for three-dimensional quantum spin-liquid phases.

Universal quantum computing is a coveted goal in the current technological landscape. This thesis presents a theoretical study of qubit arrays, the basic system for processing quantum information, tackling three important problems using results from Lie groups and algebras. Since every real system is subject to decoherence, it is crucial to find quantum devices capable of fast dynamics. The quantum speed limit of a system serves as a measure of the minimum time in which a given unitary evolution can be performed, depending on its controls and qubit couplings. A new method for its estimation is introduced in this thesis. Furthermore, the estimator is extended to determine the quantum speed limit of state-to-state transfers and quantum gates acting on a logical subspace of the total Hilbert space. The number and type of controls and qubit couplings in the system also determine whether all operations in the system are feasible, i.e. whether the system is controllable. Controllability is a necessary property for universality. The thesis presents two controllability tests, which are particularly tailored to the case of qubit arrays: A classical test based on notions from graph theory and a hybrid quantum-classical algorithm that employs parametric quantum circuits. These tests greatly expand the number of cases that can be studied. Finally, a method for designing arbitrarily large controllable qubit arrays is presented. This is achieved by juxtaposing smaller controllable arrays and connecting them via tunable couplings. The modular architecture allows the construction of larger devices that are in principle suitable for universal quantum computing, even if the controllability of the overall system cannot be directly determined by previous tests. The concepts shown here introduce an arsenal of tools that can provide valuable information for the study and development of systems with the aim of bringing quantum technologies closer to universal quantum computing.

The aim of this research is to historically reconstruct the main features of the processes of disciplinary professionalisation and renewal of forms, contents and methodologies that urbanism, photography and design experienced, both in Germany and Argentina, during the first half of the 20th century. The hypothesis poses that the figure of empathy and the experience of vision towards the end of the 19th century contributed to the foundation of a new paradigm of perception through which it is possible to jointly reinterpret the historical circulation of modernist ideas during the 20th century. Thus, the syntax of empathic and visual perception constitutes the focus of analysis that will shed light on three highly significant experiences of this global historical process in order to demonstrate how each of them contributed to a common way of perceiving space and forms.

Repetitive negative thinking (RNT) is a problematic thinking style that encompasses rumination and worry. RNT is characterized by continuously dwelling on negative content, such as problems or unpleasant experiences. RNT is associated with negative affect and various psychopathological symptoms, and it even predicts the onset of these symptoms, making it a transdiagnostic risk factor for psychopathology. This qualifies RNT as an ideal candidate for interventions because its reduction can help avoid worsened affect and symptoms, and may even prevent psychopathology. Mindfulness interventions are promising to reduce RNT because mindfulness teaches us to become aware of experiences (e.g., thoughts and feelings) and approach these experiences in an observing and non-judgmental way instead of getting stuck in negativity. Previous findings suggest that mindfulness interventions may indeed be helpful to reduce RNT and symptoms, and to improve affect. However, it remains largely unanswered whether brief mindfulness interventions in daily life lead to immediate benefits for RNT and affect. Two randomized controlled trials were conducted as part of this dissertation to answer this question. In both studies, participants completed brief audio-guided mindfulness interventions multiple times per day over several days. Immediately after each intervention, participants reported their RNT and affect via experience sampling method (ESM). STUDY 1 investigated the effects of a mindfulness intervention in N = 91 non-clinical participants. Over 10 days, participants were randomized at each assessment to complete either a mindfulness intervention or an active control task consisting of listening to neutral background sounds. Results of STUDY 1 showed that participants reported less RNT and less negative affect after completing the mindfulness intervention as compared to the control condition. However, the associations between RNT and negative affect were not impacted by the mindfulness intervention. STUDY 2 investigated the effects of a detached mindfulness intervention in N = 100 participants with elevated trait RNT. The study consisted of a 5-day baseline phase with only ESM assessments and a 5-day intervention phase, where participants additionally engaged in either a detached mindfulness or an active control task, depending on which group they were randomized to. The control task was matched to the mindfulness intervention except for the mindfulness instructions and corresponded to a guided imagery task. Results of STUDY 2 showed that participants of both groups reported stronger reductions in RNT and in negative affect, and stronger improvements in positive affect during the intervention phase compared to the non-intervention baseline phase. However, there were no differences between the groups. The integration of the studies’ findings allows to draw conclusions about the effectiveness of mindfulness interventions and about the mechanisms causing benefits. Effectiveness. Findings suggest that detecting an effect of the mindfulness interventions depended on the control condition used as a comparison. Our guided mindfulness interventions led to less RNT and negative affect compared to both (i) not engaging in any task (STUDY 2) and (ii) listening to neutral background sounds (STUDY 1). However, the mindfulness intervention was equally effective as a matched control task that excluded mindfulness instructions (i.e., guided imagery; STUDY 2). Mechanisms. The studies of this dissertation do not allow us to conclusively determine which mechanisms caused the benefits across both mindfulness interventions and the guided imagery task. It could be that experiencing momentary mindfulness led to lower RNT and better affect. However, other mindfulness-unspecific mechanisms, such as expectations about the helpfulness of the tasks or distraction from current RNT and affect, may also have been (partly) responsible for the observed benefits. Overall, findings of this dissertation indicate that brief guided mindfulness interventions and guided imagery tasks are helpful to immediately reduce RNT and improve affect in daily life. Whether these tasks caused benefits by increasing momentary mindfulness or via other mechanisms remains to be elucidated.

The steady increase in urbanization presents several challenges for humans, as they are forced to adapt to an environment that differs from the natural habitats in which they evolved. Consequently, studying the effects of this environmental shift on psychological well-being has become increasingly important. Especially the influences of environmental sounds seem understudied. Previous research has demonstrated that exposure to natural sounds can improve cognitive performance and positive affect while exposure to urban sounds was found to be detrimental. In order to facilitate the benefits of natural sound exposure, a deeper understanding of the underlying psychological and neural mechanisms is essential. The current dissertation sought to provide insights into these mechanisms by investigating the brain’s response to environmental sounds via magnetic resonance imaging (MRI) and sub-clinical assessment of mental well-being. In Paper I (Stobbe et al., 2023), the impact of exposure to natural versus urban soundscapes on brain activity during cognitive performance was assessed. It was found that performance gains in a working memory task were associated with a reduction of activity in the medial prefrontal cortex (mPFC) proposing facilitated information processing in a subregion of the frontal executive network following exposure to a natural soundscape. Moreover, the reduction of negative emotions was linked to reduced activity in the inferior parietal lobule (IPL), a region that is part of the cognitive control network, suggesting that cognitive processes required less effort and elicited fewer negative emotions following the exposure to the natural soundscape condition. In Paper II (Stobbe et al., 2024), the effects of natural versus urban sounds on brain entropy (BEN) and functional connectivity (FC) during the sound exposure was examined. It was demonstrated, that the brain’s signal complexity, or BEN, in the posterior cingulate cortex (PCC) was significantly higher while participants listened to the urban soundscape. The increased BEN was found to be associated with a reduction of positive emotions in the urban soundscape condition, suggesting that the dislike of urban sounds might be represented by high signal complexity within the PCC. Additionally, it was discovered that FC in the auditory brain network was greater during exposure to natural soundscape compared to urban soundscape. This increment of FC was found to be associated with a performance gain on two working memory tasks, indicating that exposure to natural sounds could facilitate the brain’s processing efficiency via increased FC within a task relevant network. xii In Paper III (Stobbe et al., 2022), the influence of birdsongs versus traffic noise on depressive, anxious and paranoid states was investigated. It was found that while traffic noise exposure heightened the depressive states of healthy participants, exposure to birdsongs alleviated anxious and paranoid states in the same sample. These results suggest a possible explanation for the high prevalence of mental illness in urban areas while they simultaneously provide insights into how natural sounds such as birdsong could potentially be utilized to prevent the emergence mental illness. In conclusion, the present dissertation complements the debate on whether exposure to natural sounds can lead to improvements with respect to cognition and mental well-being and provides insights into possible mechanisms that underlie these benefits. These insights could contribute to more effective natural sound interventions and highlight the potential hazards of urban noise pollution.

The Baikal Archaeology Project (BAP: https://baikalproject.artsrn.ualberta.ca/) is a long-term, multidisciplinary research initiative that has brought together experts from the fields of archaeology, bioarchaeology, ethnoarchaeology, genetics, bio- and geochemistry, and palaeoecology for over two decades to explore the lifeways of prehistoric hunter-gatherer cultures in Northern Eurasia. The focus of the project is on investigating the cultural diversity, change, stability, and resilience of foraging cultures in response to changing environmental conditions in the Lake Baikal Region (LBR) in southern Siberia and the Lake Onega Region (LOR) in Karelia, eastern Fennoscandia. High-resolution continuous sediment sequences from lakes and peatbogs serve as valuable environmental archives, ideally suited for detailed reconstructions of past human-environment relationships in the respective study areas. This dissertation presents robustly dated, high-resolution palynological records and pollen-based biome reconstructions from both BAP regions, providing detailed insights into the climatic and environmental histories and how they may have influenced the hunter-gatherer cultures studied within the BAP. A pollen record from a 135-cm-long, radiocarbon-dated sediment core from Lake Kamenistoe (67°30'31.4" N, 34°38'53.3" E) provides important insights into the vegetation and climate dynamics of the central Kola Peninsula over the last ca. 13 ka BP. The results improve existing reconstructions of the retreat of the Scandinavian Ice Sheet at the end of the last glacial period, indicating that the region was already ice-free by 13 ka BP. The palaeoenvironmental record, integrated with existing archaeological data, suggests that the initial spread of early Mesolithic hunter-gatherer groups into the region took place no later than 10 ka BP and coincided with the expansion of the boreal forest and a phase of continuous warming. These changes likely prompted the northward migration of reindeer, which were a crucial resource for Mesolithic hunter-gatherers, facilitating the habitation of this region. The palaeoenvironmental study in the LOR is based on an 885-cm-long sediment core from Razlomnoe Peat (62°27'53" N, 34°26'4" E), composed of continuous deposits from the last ca. 11.8 ka BP. The results of the palynological analysis allowed detailed reconstruction of Lateglacial–Holocene environmental changes and their possible impacts on hunter-gatherer societies in the region. The findings show rapid postglacial afforestation and highlight the sensitivity of the regional vegetation to climatic changes, such as during the 8.2 ka BP and 4.2 ka BP events, which mark the beginning of the Middle and Late Holocene, respectively. The 8.2 ka BP event is characterised by a substantial spread of birch at the expense of pine, indicating markedly cooler winters and an increase in wildfire frequency. These abrupt changes coincide with the peak of use of the Yuzhniy Oleniy Ostrov burial ground (ca. 8250–8000 a BP), suggesting an adaptive response of hunter-gatherer communities to less favourable environmental conditions. The 4.2 ka BP event, often associated with drought in other regions, coincides in the LOR with wetter conditions, which led to the expansion of wetlands and the opening of the landscape. In a third study, records of pollen and microscopic charcoal particles from sediment cores from Lake Ochaul (54°13’58.4” N, 106°27’53.8” E) in Cis-Baikal and Lake Kotokel (52°47’ N, 108°07’ E) in Trans-Baikal were analysed to reconstruct and compare the vegetation and fire history of the last 32 ka BP in the two regions. In addition to information about the complex relationship between climate, vegetation, and fire activity, these records, in combination with archaeological data, also provide new insights into the activities of hunter-gatherer communities and their impact on the natural environment. Under the cold and dry conditions during the peak (32–18.2 ka BP) of the last glacial period, both records show minimal fire activity, likely due to sparse vegetation cover. The onset of deglaciation around 18.2 ka BP is marked by a gradual spread of woody plants, accompanied by a slight increase in fire activity. Significant differences in the fire records between the two study regions become evident at the end of the Lateglacial. The peak in fire activity in Cis-Baikal is dated to the Early Holocene (9.5–8 ka BP), while in Trans-Baikal, the peak occurred during the Middle Holocene (6–5 ka BP). These differences are likely primarily due to variations in vegetation composition and landscape openness. Charcoal concentrations in both sediment cores show low values during the so-called “cultural hiatus” in the Middle Neolithic (ca. 6660–6060 a BP), suggesting a population decline throughout the LBR. The spread of Late Bronze and Iron Age cultures from 3.5 ka BP onwards is likely related to the recorded increase in fire frequency around Lake Kotokel.

The AHR is a ligand dependent transcription factor, which belongs to the bHLH-PAS superfamily of proteins. Originally, the AHR was discovered for mediating the toxicity of environmental toxicants like TCDD and different PAHs. Advanced research showed that the AHR can be bound and activated by a wide range of agonists, including various exogenous and endogenous compounds. According to the classical description of the AHR pathway, the AHR is mainly located in the cytoplasm prior to ligandbinding. Most ligands own hydrophobic characteristics allowing them to enter the cell via diffusion.Ligand-binding to the AHR triggers a nuclear import followed by building a dimer with a protein called ARNT. This heterodimer recruits many co-factors, thereby getting access and subsequently binding to a special sequence in the DNA, the XRE. The AHR/ARNT complex bound to XRE induces the expression of xenobiotic metabolizing enzymes, including phase I and phase II enzymes, thus pointing to a key role of the AHR in xenobiotic metabolism. Examining the intracellular distribution of the AHR in living cells reveals that the AHR undergoes a shuttling between cytoplasm and nucleus. This shuttling occurs continuously and does not lead to any activation. Despite the huge number of studies examining the AHR, the localization remains scarcely investigated. In this thesis, the localization of the AHR was investigated thoroughly after transient transfection of EYFP-AHR leading to expression of a fluorescent fusion protein that can be detected in real-time in living cells. I validated this system by comparing the localization of the overexpressed AHR fusion protein with the endogenous AHR with and without the presence of ligands. First of all, in depth mutagenesis analyses on the crucial amino acids to dimerize with ARNT and bind to XRE were carried out. This aimed to characterize if these two significant steps might have an impact on maintaining the activated AHR in the nucleus after ligand-binding or generally affect its nucelo-cytoplasmic translocation in the basal state. Later, the regulatory motive responsible for intracellular distribution and nuclear import, namely NLS, was characterized using point mutations. Thereby, the intracellular distribution of the AHR variants that carry an impaired NLS was detected in the basal state or after ligand treatment. My results demonstrated that neither ARNT dimerization nor DNA binding have an impact on stabilizing the AHR in the nucleus prior or post ligand-binding. Moreover, the sequence of NLS was identified as (13RKRRK17) and (37KR-R40), whereby the first part represents the main regulator, while the second one has only a supportive and complementary role. Besides that, I examined both nuclear import processes of the AHR: basal and ligand-induced. Thereafter, the effect of novel import inhibitors IPZ and IVM was tested on the mentioned nuclear import of the AHR. I found that ligand induced import can occur when the basal import is diminished. At the same time, trying to block the nuclear import using import inhibitors showed comparable influence on both import pathways. My results proposed that ligand-induced and basal import happen autonomously and independent of each other, but they rely on the same particular mechanism. Taken together, this thesis expressed novel findings on the AHR’s sequence and the molecular components involved in its nucleo-cytoplasmic translocation using advanced methods.