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Tafazzin is an acyltransferase with key functions in remodeling of the mitochondrial phospholipid cardiolipin (CL) by exchanging single fatty acids species in CL. Tafazzin-mediated CL remodeling determines the actual CL compositions and has been implicated in mitochondrial morphology and function. Thus, any deficiency of tafazzin leads to altered fatty acid composition of CL which is directly associated with impaired mitochondrial respiration and ATP production. Mutations in the tafazzin encoding gene TAZ, are the cause of the severe X-linked genetic disease, BARTH syndrome (BTHS).
Previous work provided first hints on a linkage of CL composition and subsequent limitations in the cellular ATP levels which may contribute to the restriction of growth. However, in C6 cells ATP levels remained unaltered due to compensatory activation of glycolysis. Moreover, it has been demonstrated that the substantial changes in CL composition are similarly resulting from knocking down either cardiolipin synthase (CRLS) or TAZ. This has also been shown in C6 glioma cells. Most notably only the knock down of TAZ, but not that of CRLS, compromised proliferation of C6 glioma cells. Therefore, a CL- independent role of TAZ in regulating cell proliferation is postulated.
In this study, any linkage of the lack of tafazzin to cellular proliferation should be investigated in more detail to allow first insight into underlying mechanisms.
The results of the current study demonstrate that the tafazzin knockout in C6 glioma cells show changes in global gene expression by applying transcriptome analysis using the- microarray Clarion S rat Affymetrix array. Out of 22,076 total number of genes detected, 1,099 genes were differentially expressed in C6 knockout cells which were either ≥2 and ≥4 fold up or down regulated genes. Furthermore, expression of selected target genes was validated using RT-qPCR. We have hypothesised that the changes in TAZ dependent gene expression is via PPAR transcription factor. According to eukaryotic promoter database (EPD) for selected target genes, exhibited at least one putative binding site for PPARG and PPARA transcription factors. However, pioglitazone and LG100268, synthetic ligands of PPARG and RXR, could not show any effect on changes in gene expression in C6 TAZ cells. Another class of cellular lipids, oxylipins were found to occur in significantly higher amounts in C6 TAZ cells compared to C6 cells which makes them candidates for mediating cellular effects and regulating gene expression via PPARs. A computational tool CiiiDER was used to for the prediction of transcription factor binding site. The transcription factors enriched in TAZ- regulated genes were found to be HOXA5 and PAX2, binding sites of which could be detected in 100 % of TAZ- regulated genes (>2-fold). By applying IPA to the differentially expressed genes we could identify lipid metabolism, and cholesterol superpathway in particular as the most affected pathway in C6 TAZ cells. This pathway consists of 20 genes, of which all (20/20) appeared to be differentially regulated in C6 TAZ cells. Of all the 20 genes, 4 of the differentially expressed genes were selected for further validation by RT-qPCR. By IPA it was possible to identify the upstream regulators that might be responsible for the differential expression of genes in C6 deficient cells. Some of the genes ACACA, HMGCR, FASN, ACSL1, 3 and, 5 identified was decreased by predicted activation and inhibition of the regulators. Further we have analysed the levels of cellular cholesterol content in C6 and C6 TAZ (w/o Δ5 and FL) cells. In C6 cells cholesterol is present more in its free form. C6 TAZ cells have increased amount of cholesterol compared to C6 cells. However, Δ5 and FL expressed C6 TAZ cells showed less amount of cholesterol.
Previous work established that knockout of tafazzin in C6 cells showed decreased cell proliferation in the absence of any changes in ATP content. To understand this phenomenon cellular senescence associated β-galactosidase in C6 and C6 TAZ cells was performed. C6 TAZ cells showed increased percentage of β-gal positive cells compared to C6 cells. Moreover, senescent associated secretory phenotype (SASP) represented by e.g. CXCL1, IL6, and IL1α was determined using RT-qPCR. Gene expression of these SASP factors was significantly upregulated in C6 TAZ cells.
Several human tafazzin isoforms exists due to alternate splicing. However, whether these isoforms differ in function and in CL remodelling activity or specificity, in particular, is unknown. The purpose of this work was to determine if specific isoforms, such as human isoform lacking exon 5 (Δ5), rat full length tafazzin (FL) and enzymatically dead full length tafazzin (H69L), can restore the wild type phenotype in terms of CL composition, cellular proliferation, and gene expression profile. Therefore, in the second part, it was demonstrated that expression of Δ5 to some extent and rat full length tafazzin can completely restore CL composition, in C6 TAZ cells which is naturally linked to the restoration of mitochondrial respiration. As expected, a comparable restoration of CL composition could not be seen after re-expressing an enzymatically dead full-length rat TAZ, (H69L; TAZ Mut). Furthermore, re-expression of the TAZ Mut largely failed to reverse the alterations in gene expression, in contrast re-expression of the TAZ FL and the Δ5 isoforms reversed gene expression to a larger extent. Moreover, only rat full length TAZ was able to reverse proliferation rate. Surprisingly, the expression of Δ5 in C6 TAZ cells did not promote proliferation of the wild type. Different effects of Δ5 and FL on CL composition and cell proliferation points to the specific and in part non-enzymatic functions of tafazzin isoforms, but this certainly requires further analysis.
Alternative splicing (AS) is a major mechanism for gene expression in eukaryotes, increasing proteome diversity but also regulating transcriptome abundance. High temperatures have a strong impact on the splicing profile of many genes and therefore AS is considered as an integral part of heat stress response. While many studies have established a detailed description of the diversity of the RNAome under heat stress in different plant species and stress regimes, little is known on the underlying mechanisms that control this temperature-sensitive process. AS is mainly regulated by the activity of splicing regulators. Changes in the abundance of these proteins through transcription and AS, post-translational modifications and interactions with exonic and intronic cis-elements and core elements of the spliceosomes modulate the outcome of pre-mRNA splicing. As a major part of pre-mRNAs are spliced co-transcriptionally, the chromatin environment along with the RNA polymerase II elongation play a major role in the regulation of pre-mRNA splicing under heat stress conditions. Despite its importance, our understanding on the regulation of heat stress sensitive AS in plants is scarce. In this review, we summarize the current status of knowledge on the regulation of AS in plants under heat stress conditions. We discuss possible implications of different pathways based on results from non-plant systems to provide a perspective for researchers who aim to elucidate the molecular basis of AS under high temperatures.
Liver diseases are important causes of morbidity and mortality worldwide. The aim of
this study was to identify differentially expressed microRNAs (miRNAs), target genes, and key
pathways as innovative diagnostic biomarkers in liver patients with different pathology and functional
state. We determined, using RT-qPCR, the expression of 472 miRNAs in 125 explanted livers from
subjects with six different liver pathologies and from control livers. ANOVA was employed to
obtain differentially expressed miRNAs (DEMs), and miRDB (MicroRNA target prediction database)
was used to predict target genes. A miRNA–gene differential regulatory (MGDR) network was
constructed for each condition. Key miRNAs were detected using topological analysis. Enrichment
analysis for DEMs was performed using the Database for Annotation, Visualization, and Integrated
Discovery (DAVID). We identified important DEMs common and specific to the different patient
groups and disease progression stages. hsa-miR-1275 was universally downregulated regardless
the disease etiology and stage, while hsa-let-7a*, hsa-miR-195, hsa-miR-374, and hsa-miR-378 were
deregulated. The most significantly enriched pathways of target genes controlled by these miRNAs
comprise p53 tumor suppressor protein (TP53)-regulated metabolic genes, and those involved in
regulation of methyl-CpG-binding protein 2 (MECP2) expression, phosphatase and tensin homolog
(PTEN) messenger RNA (mRNA) translation and copper homeostasis. Our findings show a novel
panel of deregulated miRNAs in the liver tissue from patients with different liver pathologies. These
miRNAs hold potential as biomarkers for diagnosis and staging of liver diseases.
The innate immune system relies on families of pattern recognition receptors (PRRs)
that detect distinct conserved molecular motifs from microbes to initiate antimicrobial responses.
Activation of PRRs triggers a series of signaling cascades, leading to the release of pro-inflammatory
cytokines, chemokines and antimicrobials, thereby contributing to the early host defense against
microbes and regulating adaptive immunity. Additionally, PRRs can detect perturbation of cellular
homeostasis caused by pathogens and fine-tune the immune responses. Among PRRs, nucleotide
binding oligomerization domain (NOD)-like receptors (NLRs) have attracted particular interest in the
context of cellular stress-induced inflammation during infection. Recently, mechanistic insights into
the monitoring of cellular homeostasis perturbation by NLRs have been provided. We summarize
the current knowledge about the disruption of cellular homeostasis by pathogens and focus on NLRs
as innate immune sensors for its detection. We highlight the mechanisms employed by various
pathogens to elicit cytoskeleton disruption, organelle stress as well as protein translation block, point
out exemplary NLRs that guard cellular homeostasis during infection and introduce the concept of
stress-associated molecular patterns (SAMPs). We postulate that integration of information about
microbial patterns, danger signals, and SAMPs enables the innate immune system with adequate
plasticity and precision in elaborating responses to microbes of variable virulence.
Neutrophils in Tuberculosis: Cell Biology, Cellular Networking and Multitasking in Host Defense
(2021)
Neutrophils readily infiltrate infection foci, phagocytose and usually destroy microbes. In
tuberculosis (TB), a chronic pulmonary infection caused by Mycobacterium tuberculosis (Mtb),
neutrophils harbor bacilli, are abundant in tissue lesions, and their abundances in blood correlate
with poor disease outcomes in patients. The biology of these innate immune cells in TB is complex.
Neutrophils have been assigned host-beneficial as well as deleterious roles. The short lifespan of
neutrophils purified from blood poses challenges to cell biology studies, leaving intracellular
biological processes and the precise consequences of Mtb–neutrophil interactions ill-defined. The
phenotypic heterogeneity of neutrophils, and their propensity to engage in cellular cross-talk and
to exert various functions during homeostasis and disease, have recently been reported, and such
observations are newly emerging in TB. Here, we review the interactions of neutrophils with Mtb,
including subcellular events and cell fate upon infection, and summarize the cross-talks between
neutrophils and lung-residing and -recruited cells. We highlight the roles of neutrophils in TB
pathophysiology, discussing recent findings from distinct models of pulmonary TB, and emphasize
technical advances that could facilitate the discovery of novel neutrophil-related disease
mechanisms and enrich our knowledge of TB pathogenesis
Simple Summary
Paratuberculosis is a disease which affects ruminants worldwide. Many countries have implemented certification and monitoring systems to control the disease, particularly in dairy herds. Monitoring herds certified as paratuberculosis non-suspect is an important component of paratuberculosis herd certification programs. The challenge is to detect the introduction or reintroduction of the infectious agent as early as possible with reasonable efforts but high certainty. In our study, we evaluated different low-cost testing schemes in herds where the share of infected animals was low, resulting in a low within-herd prevalence of animals shedding the bacteria that causes paratuberculosis in their feces. The test methods used were repeated pooled milk samples and fecal samples from the barn environment. Our study showed that numerous repetitions of different samples are necessary to monitor such herds with sufficiently high certainty. In the case of herds with a very low prevalence, our study showed that a combination of different sampling approaches is required.
Abstract
An easy-to-use and affordable surveillance system is crucial for paratuberculosis control. The use of environmental samples and milk pools has been proven to be effective for the detection of Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds, but not for monitoring dairy herds certified as MAP non-suspect. We aimed to evaluate methods for the repeated testing of large dairy herds with a very low prevalence of MAP shedders, using different sets of environmental samples or pooled milk samples, collected monthly over a period of one year in 36 herds with known MAP shedder prevalence. Environmental samples were analyzed by bacterial culture and fecal PCR, and pools of 25 and 50 individual milk samples were analyzed by ELISA for MAP-specific antibodies. We estimated the cumulative sensitivity and specificity for up to twelve sampling events by adapting a Bayesian latent class model and taking into account the between- and within-test correlation. Our study revealed that at least seven repeated samplings of feces from the barn environment are necessary to achieve a sensitivity of 95% in herds with a within-herd shedder prevalence of at least 2%. The detection of herds with a prevalence of less than 2% is more challenging and, in addition to numerous repetitions, requires a combination of different samples.
Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.
Self-similar sets with the open set condition, the linear objects of fractal geometry, have been considered mainly for crystallographic data. Here we introduce new symmetry classes in the plane, based on rotation by irrational angles. Examples without characteristic directions, with strong connectedness and small complexity, were found in a computer-assisted search. They are surprising since the rotations are given by rational matrices, and the proof of the open set condition usually requires integer data. We develop a classification of self-similar sets by symmetry class and algebraic numbers. Examples are given for various quadratic number fields.
Universal products provide an axiomatic framework to study noncommutative independences general enough to include, besides the well known "single-faced" case (i.e., tensor, free, Boolean, monotone and antimonotone independence), also more recent "multi-faced" examples like bifree independence. Questions concerning classification have been fully answered in the single-faced case, but are in general still open in the multi-faced case. In this thesis we discuss how one can use insights in the relation between universal products and their associated moment-cumulant formula as a starting point towards a combinatorial approach to (multi-faced) universal products. We define certain classes of partitions and discuss why the defining axioms are sufficient to associate to each of them a multi-faced universal product. For the two-faced case we present our result that every positive and symmetric universal product can be produced in this fashion and we outline how these results might contribute to a classification of positive and symmetric universal products.
A lot of research data has become available since the outbreak of the COVID-19
pandemic in 2019. Connecting this data is essential for the understanding of the
SARS-CoV-2 virus and the fight against the pandemic.
Amongst biological and biomedical research data, computational models targeting
COVID-19 have been emerging and their number is growing constantly. They are a
central part of the field of Systems Biology, which aims to understand the mechanisms
and behaviour of biological systems. Model predictions help to understand the
mechanisms of the novel coronavirus and the life-threatening disease it is causing.
Both biomedical research data and modelling data regarding COVID-19 have
previously been stored in separated domain-specific graph databases. MaSyMoS,
short for Management System for Models and Simulations, is a graph database for
storing simulation studies of biological and biochemical systems. The CovidGraph
project integrates research data regarding COVID-19 and the coronavirus family
from various data resources in a knowledge graph.
In this thesis, we integrate simulation models from MaSyMoS, including models
targeting COVID-19, into the CovidGraph. Therefore, we present a concept for
the integration of simulation studies and the linkage through ontology terms and
reference publications in the CovidGraph. Ultimately, we connect data from the field
of systems biology and biomedical research data in a graph database.
Simple Summary
Monitoring animal behavior provides an indicator of their health and welfare. For this purpose, video surveillance is an important method to get an unbiased insight into behavior, as animals often show different behavior in the presence of humans. However, manual analysis of video data is costly and time-consuming. For this reason, we present a method for automated analysis using computer vision—a method for teaching the computer to see like a human. In this study, we use computer vision to detect red foxes and their body posture (lying, sitting, or standing). With this data we are able to monitor the animals, determine their activity, and identify their behavior.
Abstract
The behavior of animals is related to their health and welfare status. The latter plays a particular role in animal experiments, where continuous monitoring is essential for animal welfare. In this study, we focus on red foxes in an experimental setting and study their behavior. Although animal behavior is a complex concept, it can be described as a combination of body posture and activity. To measure body posture and activity, video monitoring can be used as a non-invasive and cost-efficient tool. While it is possible to analyze the video data resulting from the experiment manually, this method is time consuming and costly. We therefore use computer vision to detect and track the animals over several days. The detector is based on a neural network architecture. It is trained to detect red foxes and their body postures, i.e., ‘lying’, ‘sitting’, and ‘standing’. The trained algorithm has a mean average precision of 99.91%. The combination of activity and posture results in nearly continuous monitoring of animal behavior. Furthermore, the detector is suitable for real-time evaluation. In conclusion, evaluating the behavior of foxes in an experimental setting using computer vision is a powerful tool for cost-efficient real-time monitoring.
Geometric T-Duality
(2022)
From a physicists point of view T-duality is a relation connecting string
theories on different spacetimes. Mathematically speaking, T-duality should be a symmetric relation on
the space of toroidal string backgrounds. Such a background consists of: a smooth manifold M; a torus bundle E over M - the total space modelling spacetime; a Riemannian metric g on E - modelling the field of gravity; a U(1)-bundle gerbe G with connection over E - modelling the Kalb-
Ramond field.
But as of now no complete model for T-duality exists. The three most notable
approaches for T-duality are given by the differential approaches by Buscher in the form of the Buscher rules and by Bouwknegt, Evslin and Mathai in the form of T-duality with H-flux on the one hand, and by the topological approach given by Bunke, Rumpf and Schick which is known as topological T-duality. In this thesis we combine these different approaches to form the first model for T-duality over complete geometric toroidal string backgrounds and we will introduce an example for this geometric T-duality inspired by the Hopf bundle.
Discovering Latent Structure in High-Dimensional Healthcare Data: Toward Improved Interpretability
(2022)
This cumulative thesis describes contributions to the field of interpretable machine learning in the healthcare domain. Three research articles are presented that lie at the intersection of biomedical and machine learning research. They illustrate how incorporating latent structure can provide a valuable compression of the information hidden in complex healthcare data.
Methodologically, this thesis gives an overview of interpretable machine learning and the discovery of latent structure, including clusters, latent factors, graph structure, and hierarchical structure. Different workflows are developed and applied to two main types of complex healthcare data (cohort study data and time-resolved molecular data). The core result builds on Bayesian networks, a type of probabilistic graphical model. On the application side, we provide accurate predictive or discriminative models focusing on relevant medical conditions, related biomarkers, and their interactions.
Spatial variation in survival has individual fitness consequences and influences population dynamics. It proximately and ultimately impacts space use including migratory connectivity. Therefore, knowing spatial patterns of survival is crucial to understand demography of migrating animals. Extracting information on survival and space use from observation data, in particular dead recovery data, requires explicitly identifying the observation process. The main aim of this work is to establish a modeling framework which allows estimating spatial variation in survival, migratory connectivity and observation probability using dead recovery data. We provide some biological background on survival and migration and a short methodological overview of how similar situations are modeled in literature.
Afterwards, we provide REML-like estimators for discrete space and show identifiability of all three parameters using the characteristics of the multinomial distribution. Moreover, we formulate a model in continuous space using mixed binomial point processes. The continuous model assumes a constant recovery probability over space. To drop this strict assumption, we develop an optimization procedure combining the discrete and continuous space model. Therefore, we use penalized M-splines. In simulation studies we demonstrate the performance of the estimators for all three model approaches. Furthermore, we apply the models to real-world data sets of European robins \textit{Erithacus rubecula} and ospreys \textit{Pandion haliaetus}.
We discuss how this study can be embedded in the framework of animal movement and the capture mark recapture/recovery methodology. It can be seen as a contribution and an extension to distance sampling, local stationary everyday movement and dispersal. We emphasize the importance of having a mathematically clearly formulated modeling framework for applied methods. Moreover, we comment on model assumptions and their limits. In the future, it would be appealing to extend this framework to the full annual cycle and carry-over effects.
Anaplasma phagocytophilum and Anaplasma ovis–Emerging Pathogens in the German Sheep Population
(2021)
Knowledge on the occurrence of pathogenic tick-borne bacteria Anaplasma phagocytophilum and Anaplasma ovis is scarce in sheep from Germany. In 2020, owners from five flocks reported ill thrift lambs and ewes with tick infestation. Out of 67 affected sheep, 55 animals were clinically examined and hematological values, blood chemistry and fecal examinations were performed to investigate the underlying disease causes. Serological tests (cELISA, IFAT) and qPCR were applied to all affected sheep to rule out A. phagocytophilum and A. ovis as a differential diagnosis. Ticks were collected from selected pastures and tested by qPCR. Most animals (n = 43) suffered from selenium deficiency and endoparasites were detected in each flock. Anaplasma spp. antibodies were determined in 59% of examined sheep. Seventeen animals tested positive for A. phagocytophilum by qPCR from all flocks and A. phagocytophilum was also detected in eight pools of Ixodes ricinus. Anaplasma phagocytophilum isolates from sheep and ticks were genotyped using three genes (16S rRNA, msp4 and groEL). Anaplasma ovis DNA was identified in six animals from one flock. Clinical, hematological and biochemical changes were not significantly associated with Anaplasma spp. infection. The 16S rRNA analysis revealed known variants of A. phagocytophilum, whereas the msp4 and groEL showed new genotypes. Further investigations are necessary to evaluate the dissemination and health impact of both pathogens in the German sheep population particularly in case of comorbidities.
Abstract
Cellular stress has been associated with inflammation, yet precise underlying mechanisms remain elusive. In this study, various unrelated stress inducers were employed to screen for sensors linking altered cellular homeostasis and inflammation. We identified the intracellular pattern recognition receptors NOD1/2, which sense bacterial peptidoglycans, as general stress sensors detecting perturbations of cellular homeostasis. NOD1/2 activation upon such perturbations required generation of the endogenous metabolite sphingosine‐1‐phosphate (S1P). Unlike peptidoglycan sensing via the leucine‐rich repeats domain, cytosolic S1P directly bound to the nucleotide binding domains of NOD1/2, triggering NF‐κB activation and inflammatory responses. In sum, we unveiled a hitherto unknown role of NOD1/2 in surveillance of cellular homeostasis through sensing of the cytosolic metabolite S1P. We propose S1P, an endogenous metabolite, as a novel NOD1/2 activator and NOD1/2 as molecular hubs integrating bacterial and metabolic cues.
Phytopathogenic Verticillia cause Verticillium wilt on numerous economically important crops. Plant infection begins at the roots, where the fungus is confronted with rhizosphere inhabiting bacteria. The effects of different fluorescent pseudomonads, including some known biocontrol agents of other plant pathogens, on fungal growth of the haploid Verticillium dahliae and/or the amphidiploid Verticillium longisporum were compared on pectin-rich medium, in microfluidic interaction channels, allowing visualization of single hyphae, or on Arabidopsis thaliana roots. We found that the potential for formation of bacterial lipopeptide syringomycin resulted in stronger growth reduction effects on saprophytic Aspergillus nidulans compared to Verticillium spp. A more detailed analyses on bacterial-fungal co-cultivation in narrow interaction channels of microfluidic devices revealed that the strongest inhibitory potential was found for Pseudomonas protegens CHA0, with its inhibitory potential depending on the presence of the GacS/GacA system controlling several bacterial metabolites. Hyphal tip polarity was altered when V. longisporum was confronted with pseudomonads in narrow interaction channels, resulting in a curly morphology instead of straight hyphal tip growth. These results support the hypothesis that the fungus attempts to evade the bacterial confrontation. Alterations due to co-cultivation with bacteria could not only be observed in fungal morphology but also in fungal transcriptome. P. protegens CHA0 alters transcriptional profiles of V. longisporum during 2 h liquid media co-cultivation in pectin-rich medium. Genes required for degradation of and growth on the carbon source pectin were down-regulated, whereas transcripts involved in redox processes were up-regulated. Thus, the secondary metabolite mediated effect of Pseudomonas isolates on Verticillium species results in a complex transcriptional response, leading to decreased growth with precautions for self-protection combined with the initiation of a change in fungal growth direction. This interplay of bacterial effects on the pathogen can be beneficial to protect plants from infection, as shown with A. thaliana root experiments. Treatment of the roots with bacteria prior to infection with V. dahliae resulted in a significant reduction of fungal root colonization. Taken together we demonstrate how pseudomonads interfere with the growth of Verticillium spp. and show that these bacteria could serve in plant protection.
Diese Dissertation untersucht Zusammenhänge der spieltheoretischen Begriffe des Nash- und Stackelberg-Gleichgewichts in Differenialspielen im N-Spieler-Fall. Weiterhin werden drei verschiedene Lösungskonzepte für das Finden von Gleichgewichten in 2-Spieler-Differentialspielen vorgestellt. Direkte Methoden aus der nichtlinearen Optimierung, der globalen Optimierung und der optimalen Steuerung werden verwendet, um Nash- und Stackelberg-Gleichgewichte in 2-Spieler-Differentialspielen zu finden. Anhand von Anwendungsbeispielen werden die Methoden getestet, analysiert und ausgewertet. Eine Erweiterung des Verfolgungsspiels von Isaacs auf Beschleunigungskomponenten wird betrachtet. Ein bisher unbekanntes Stackelberg-Gleichgewicht wird im Kapitalismusspiel nach Lancaster numerisch berechnet. Zuletzt wird ein Problem aus der Fischerei modelliert und anhand der eingeführten Methoden gelöst.