@phdthesis{Beudert2024,
  author    = {Beudert, Matthias},
  title     = {Bioinspired Modification and Functionalization of Hydrogels for Applications in Biomedicine},
  doi       = {10.25972/OPUS-32288},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322887},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Over the years, hydrogels have been developed and used for a huge variety of different applications ranging from drug delivery devices to medical products. In this thesis, a poly(2-methyl-2-oxazoline) (POx) / poly(2-n-propyl-2-oxazine) (POzi) bioink was modified and analyzed for the use in biofabrication and targeted drug delivery. In addition, the protein fibrinogen (Fbg) was genetically modified for an increased stability towards plasmin degradation for its use as wound sealant. In Chapter 1, a thermogelling, printable POx/POzi-based hydrogel was modified with furan and maleimide moieties in the hydrophilic polymer backbone facilitating post-printing maturation of the constructs via Diels-Alder chemistry. The modification enabled long-term stability of the hydrogel scaffolds in aqueous solutions which is necessary for applications in biofabrication or tissue engineering. Furthermore, we incorporated RGD-peptides into the hydrogel which led to cell adhesion and elongated morphology of fibroblast cells seeded on top of the scaffolds. Additional printing experiments demonstrate that the presented POx/POzi system is a promising platform for the use as a bioink in biofabrication. Chapter 2 highlights the versatility of the POx/POzi hydrogels by adapting the system to a use in targeted drug delivery. We used a bioinspired approach for a bioorthogonal conjugation of insulin-like growth factor I (IGF-I) to the polymer using an omega-chain-end dibenzocyclooctyne (DBCO) modification and a matrix metalloprotease-sensitive peptide linker. This approach enabled a bioresponsive release of IGF-I from hydrogels as well as spatial control over the protein distribution in 3D printed constructs which makes the system a candidate for the use in personalized medicine. Chapter 3 gives a general overview over the necessity of wound sealants and the current generations of fibrin sealants on the market including advantages and challenges. Furthermore, it highlights trends and potential new strategies to tackle current problems and broadens the toolbox for future generations of fibrin sealants. Chapter 4 applies the concepts of recombinant protein expression and molecular engineering to a novel generation of fibrin sealants. In a proof-of-concept study, we developed a new recombinant fibrinogen (rFbg) expression protocol and a Fbg mutant that is less susceptible to plasmin degradation. Targeted lysine of plasmin cleavage sites in Fbg were exchanged with alanine or histidine in different parts of the molecule. The protein was recombinantly produced and restricted plasmin digest was analyzed using high resolution mass spectrometry. In addition to that, we developed a novel time resolved screening protocol for the detection of new potential plasmin cleavage sites for further amino acid exchanges in the fibrin sealant.},
  subject      = {Hydrogel},
  language  = {en}
}
@phdthesis{Dietrich2024,
  author    = {Dietrich, Oliver},
  title     = {Integrating single-cell multi-omics to decipher host-pathogen interactions},
  doi       = {10.25972/OPUS-36013},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-360138},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Interactions between host and pathogen determine the development, progression and outcomes of disease. Medicine benefits from better descriptions of these interactions through increased precision of prevention, diagnosis and treatment of diseases. Single-cell genomics is a disruptive technology revolutionizing science by increasing the resolution with which we study diseases. Cell type specific changes in abundance or gene expression are now routinely investigated in diseases. Meanwhile, detecting cellular phenotypes across diseases can connect scientific fields and fuel discovery. Insights acquired through systematic analysis of high resolution data will soon be translated into clinical practice and improve decision making. Therefore, the continued use of single-cell technologies and their application towards clinical samples will improve molecular interpretation, patient stratification, and the prediction of outcomes. In the past years, I was fortunate to participate in interdisciplinary research groups bridging biology, clinical research and data science. I was able to contribute to diverse projects through computational analysis and biological interpretation of sequencing data. Together, we were able to discover cellular phenotypes that influence disease progression and outcomes as well as the response to treatment. Here, I will present four studies that I have conducted in my PhD. First, we performed a case study of relapse from cell-based immunotherapy in Multiple Myeloma. We identified genomic deletion of the epitope as mechanism of immune escape and implicate heterozygosity or monosomy of the genomic locus at baseline as a potential risk factor. Second, we investigated the pathomechanisms of severe COVID-19 at the earliest stage of the COVID- 19 pandemic in Germany in March 2020. We discovered that profibrotic macrophages and lung fibrosis can be caused by SARS-CoV-2 infection. Third, we used a mouse model of chronic infection with Staphylococcus aureus that causes Osteomyelitis similar to the human disease. We were able to identify dysregulated immunometabolism associated with the generation of myeloid-derived suppressor cells (MDSC). Fourth, we investigated Salmonella infection of the human small intestine in an in vitro model and describe features of pathogen invasion and host response. Overall, I have been able to successfully employ single-cell sequencing to discover important aspects of diseases ranging from development to treatment and outcome. I analyzed samples from the clinics, human donors, mouse models and organoid models to investigate different aspects of diseases and managed to integrate data across sample types, technologies and diseases. Based on successful studies, we increased our efforts to combine data from multiple sources to build comprehensive references for the integration of large collections of clinical samples. Our findings exemplify how single-cell sequencing can improve clinical research and highlights the potential of mechanistic discoveries to drive precision medicine.},
  subject      = {Einzelzellanalyse},
  language  = {en}
}
@phdthesis{Yu2024,
  author    = {Yu, Yanying},
  title     = {Applied machine learning for the analysis of CRISPR-Cas systems},
  doi       = {10.25972/OPUS-32021},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-320219},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Among the defense strategies developed in microbes over millions of years, the innate adaptive CRISPR-Cas immune systems have spread across most of bacteria and archaea. The flexibility, simplicity, and specificity of CRISPR-Cas systems have laid the foundation for CRISPR-based genetic tools. Yet, the efficient administration of CRISPR-based tools demands rational designs to maximize the on-target efficiency and off-target specificity. Specifically, the selection of guide RNAs (gRNAs), which play a crucial role in the target recognition of CRISPR-Cas systems, is non-trivial. Despite the fact that the emerging machine learning techniques provide a solution to aid in gRNA design with prediction algorithms, design rules for many CRISPR-Cas systems are ill-defined, hindering their broader applications. CRISPR interference (CRISPRi), an alternative gene silencing technique using a catalytically dead Cas protein to interfere with transcription, is a leading technique in bacteria for functional interrogation, pathway manipulation, and genome-wide screens. Although the application is promising, it also is hindered by under-investigated design rules. Therefore, in this work, I develop a state-of-art predictive machine learning model for guide silencing efficiency in bacteria leveraging the advantages of feature engineering, data integration, interpretable AI, and automated machine learning. I first systematically investigate the influential factors that attribute to the extent of depletion in multiple CRISPRi genome-wide essentiality screens in Escherichia coli and demonstrate the surprising dominant contribution of gene-specific effects, such as gene expression level. These observations allowed me to segregate the confounding gene-specific effects using a mixed-effect random forest (MERF) model to provide a better estimate of guide efficiency, together with the improvement led by integrating multiple screens. The MERF model outperformed existing tools in an independent high-throughput saturating screen. I next interpret the predictive model to extract the design rules for robust gene silencing, such as the preference for cytosine and disfavoring for guanine and thymine within and around the protospacer adjacent motif (PAM) sequence. I further incorporated the MERF model in a web-based tool that is freely accessible at www.ciao.helmholtz-hiri.de. When comparing the MERF model with existing tools, the performance of the alternative gRNA design tool optimized for CRISPRi in eukaryotes when applied to bacteria was far from satisfying, questioning the robustness of prediction algorithms across organisms. In addition, the CRISPR-Cas systems exhibit diverse mechanisms albeit with some similarities. The captured predictive patterns from one dataset thereby are at risk of poor generalization when applied across organisms and CRISPR-Cas techniques. To fill the gap, the machine learning approach I present here for CRISPRi could serve as a blueprint for the effective development of prediction algorithms for specific organisms or CRISPR-Cas systems of interest. The explicit workflow includes three principle steps: 1) accommodating the feature set for the CRISPR-Cas system or technique; 2) optimizing a machine learning model using automated machine learning; 3) explaining the model using interpretable AI. To illustrate the applicability of the workflow and diversity of results when applied across different bacteria and CRISPR-Cas systems, I have applied this workflow to analyze three distinct CRISPR-Cas genome-wide screens. From the CRISPR base editor essentiality screen in E. coli, I have determined the PAM preference and sequence context in the editing window for efficient editing, such as A at the 2nd position of PAM, A/TT/TG downstream of PAM, and TC at the 4th to 5th position of gRNAs. From the CRISPR-Cas13a screen in E. coli, in addition to the strong correlation with the guide depletion, the target expression level is the strongest predictor in the model, supporting it as a main determinant of the activation of Cas13-induced immunity and better characterizing the CRISPR-Cas13 system. From the CRISPR-Cas12a screen in Klebsiella pneumoniae, I have extracted the design rules for robust antimicrobial activity across K. pneumoniae strains and provided a predictive algorithm for gRNA design, facilitating CRISPR-Cas12a as an alternative technique to tackle antibiotic resistance. Overall, this thesis presents an accurate prediction algorithm for CRISPRi guide efficiency in bacteria, providing insights into the determinants of efficient silencing and guide designs. The systematic exploration has led to a robust machine learning approach for effective model development in other bacteria and CRISPR-Cas systems. Applying the approach in the analysis of independent CRISPR-Cas screens not only sheds light on the design rules but also the mechanisms of the CRISPR-Cas systems. Together, I demonstrate that applied machine learning paves the way to a deeper understanding and a broader application of CRISPR-Cas systems.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@phdthesis{KuklovskyformerFinke2024,
  author    = {Kuklovsky [former Finke], Valerie},
  title     = {Are some bees smarter than others? An examination of consistent individual differences in the cognitive abilities of honey bees},
  doi       = {10.25972/OPUS-32301},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323012},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Cognition refers to the ability to of animals to acquire, process, store and use vital information from the environment. Cognitive processes are necessary to predict the future and reduce the uncertainty of the ever-changing environment. Classically, research on animal cognition focuses on decisive cognitive tests to determine the capacity of a species by the testing the ability of a few individuals. This approach views variability between these tested key individuals as unwanted noise and is thus often neglected. However, inter-individual variability provides important insights to behavioral plasticity, cognitive specialization and brain modularity. Honey bees Apis mellifera are a robust and traditional model for the study of learning, memory and cognition due to their impressive capabilities and rich behavioral repertoire. In this thesis I have applied a novel view on the learning abilities of honey bees by looking explicitly at individual differences in a variety of learning tasks. Are some individual bees consistently smarter than some of her sisters? If so, will a smart individual always perform good independent of the time, the context and the cognitive requirements or do bees show distinct isolated 'cognitive modules'? My thesis presents the first comprehensive investigation of consistent individual differences in the cognitive abilities of honey bees. To speak of an individual as behaving consistently, a crucial step is to test the individual multiple times to examine the repeatability of a behavior. I show that free-flying bees remain consistent in a visual discrimination task for three consecutive days. Successively, I explored individual consistency in cognitive proficiency across tasks involving different sensory modalities, contexts and cognitive requirements. I found that free-flying bees show a cognitive specialization between visual and olfactory learning but remained consistent across a simple discrimination task and a complex concept learning task. I wished to further explore individual consistency with respect to tasks of different cognitive complexity, a question that has never been tackled before in an insect. I thus performed a series of four experiments using either visual or olfactory stimuli and a different training context (free-flying and restrained) and tested bees in a discrimination task, reversal learning and negative patterning. Intriguingly, across all these experiments I evidenced the same results: The bees' performances were consistent across the discrimination task and reversal learning and negative patterning respectively. No association was evidenced between reversal learning and negative patterning. After establishing the existence of consistent individual differences in the cognitive proficiency of honey bees I wished to determine factors which could underlie these differences. Since genetic components are known to underlie inter-individual variability in learning abilities, I studied the effects of genetics on consistency in cognitive proficiency by contrasting bees originating from either from a hive with a single patriline (low genetic diversity) or with multiple patrilines (high genetic diversity). These two groups of bees showed differences in the patterns of individually correlated performances, indicating a genetic component accounts for consistent cognitive individuality. Another major factor underlying variability in learning performances is the individual responsiveness to sucrose solution and to visual stimuli, as evidenced by many studies on restrained bees showing a positive correlation between responsiveness to task relevant stimuli and learning performances. I thus tested whether these relationships between sucrose/visual responsiveness and learning performances are applicable for free-flying bees. Free-flying bees were again subjected to reversal learning and negative patterning and subsequently tested in the laboratory for their responsiveness to sucrose and to light. There was no evidence of a positive relationship between sucrose/visual responsiveness and neither performances of free-flying bees in an elemental discrimination, reversal learning and negative patterning. These findings indicate that relationships established between responsiveness to task relevant stimuli and learning proficiency established in the laboratory with restrained bees might not hold true for a completely different behavioral context i.e. for free-flying bees in their natural environment. These results show that the honey bee is an excellent insect model to study consistency in cognitive proficiency and to identify the underlying factors. I mainly discuss the results with respect to the question of brain modularity in insects and the adaptive significance of individuality in cognitive abilities for honey bee colonies. I also provide a proposition of research questions which tie in this theme of consistent cognitive proficiency and could provide fruitful areas for future research.},
  subject      = {Lernen},
  language  = {en}
}
@phdthesis{Hartmann2024,
  author    = {Hartmann, Oliver},
  title     = {Development of somatic modified mouse models of Non-Small cell lung cancer},
  doi       = {10.25972/OPUS-36340},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-363401},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {In 2020, cancer was the leading cause of death worldwide, accounting for nearly 10 million deaths. Lung cancer was the most common cancer, with 2.21 million cases per year in both sexes. This non-homogeneous disease is further subdivided into small cell lung cancer (SCLC, 15\%) and non-small cell lung cancer (NSCLC, 85\%). By 2023, the American Cancer Society estimates that NSCLC will account for 13\% of all new cancer cases and 21\% of all estimated cancer deaths. In recent years, the treatment of patients with NSCLC has improved with the development of new therapeutic interventions and the advent of targeted and personalised therapies. However, these advances have only marginally improved the five-year survival rate, which remains alarmingly low for patients with NSCLC. This observation highlights the importance of having more appropriate experimental and preclinical models to recapitulate, identify and test novel susceptibilities in NSCLC. In recent years, the Trp53fl/fl KRaslsl-G12D/wt mouse model developed by Tuveson, Jacks and Berns has been the main in vivo model used to study NSCLC. This model mimics ADC and SCC to a certain extent. However, it is limited in its ability to reflect the genetic complexity of NSCLC. In this work, we use CRISPR/Cas9 genome editing with targeted mutagenesis and gene deletions to recapitulate the conditional model. By comparing the Trp53fl/fl KRaslsl- G12D/wt with the CRISPR-mediated Trp53mut KRasG12D, we demonstrated that both showed no differences in histopathological features, morphology, and marker expression. Furthermore, next-generation sequencing revealed a very high similarity in their transcriptional profile. Adeno-associated virus-mediated tumour induction and the modular design of the viral vector allow us to introduce additional mutations in a timely manner. CRISPR-mediated mutation of commonly mutated tumour suppressors in NSCLC reliably recapitulated the phenotypes described in patients in the animal model. Lastly, the dual viral approach could induce the formation of lung tumours not only in constitutive Cas9 expressing animals, but also in wildtype animals. Thus, the implementation of CRISPR genome editing can rapidly advance the repertoire of in vivo models for NSCLC research. Furthermore, it can reduce the necessity of extensive breeding.},
  subject      = {CRISPR/Cas-Methode},
  language  = {en}
}
@phdthesis{Ramirez2024,
  author    = {Ramirez, Yesid A.},
  title     = {Structural basis of ubiquitin recognition and rational design of novel covalent inhibitors targeting Cdu1 from \(Chlamydia\) \(Trachomatis\)},
  doi       = {10.25972/OPUS-19168},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-191683},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {The WHO-designated neglected-disease pathogen Chlamydia trachomatis (CT) is a gram-negative bacterium responsible for the most frequently diagnosed sexually transmitted infection worldwide. CT infections can lead to infertility, blindness and reactive arthritis, among others. CT acts as an infectious agent by its ability to evade the immune response of its host, which includes the impairment of the NF-κB mediated inflammatory response and the Mcl1 pro-apoptotic pathway through its deubiquitylating, deneddylating and transacetylating enzyme ChlaDUB1 (Cdu1). Expression of Cdu1 is also connected to host cell Golgi apparatus fragmentation, a key process in CT infections. Cdu1 may this be an attractive drug target for the treatment of CT infections. However, a lead molecule for the development of novel potent inhibitors has been unknown so far. Sequence alignments and phylogenetic searches allocate Cdu1 in the CE clan of cysteine proteases. The adenovirus protease (adenain) also belongs to this clan and shares a high degree of structural similarity with Cdu1. Taking advantage of topological similarities between the active sites of Cdu1 and adenain, a target-hopping approach on a focused set of adenain inhibitors, developed at Novartis, has been pursued. The thereby identified cyano-pyrimidines represent the first active-site directed covalent reversible inhibitors for Cdu1. High-resolution crystal structures of Cdu1 in complex with the covalently bound cyano-pyrimidines as well as with its substrate ubiquitin have been elucidated. The structural data of this thesis, combined with enzymatic assays and covalent docking studies, provide valuable insights into Cdu1s activity, substrate recognition, active site pocket flexibility and potential hotspots for ligand interaction. Structure-informed drug design permitted the optimization of this cyano-pyrimidine based scaffold towards HJR108, the first molecule of its kind specifically designed to disrupt the function of Cdu1. The structures of potentially more potent and selective Cdu1 inhibitors are herein proposed. This thesis provides important insights towards our understanding of the structural basis of ubiquitin recognition by Cdu1, and the basis to design highly specific Cdu1 covalent inhibitors.},
  subject      = {Ubiquitin},
  language  = {en}
}
@phdthesis{Reissland2024,
  author    = {Reissland, Michaela},
  title     = {USP10 is a \(de\) \(novo\) tumour-specific regulator of β-Catenin and contributes to cancer stem cell maintenance and tumour progression},
  doi       = {10.25972/OPUS-31957},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-319579},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Colorectal Cancer (CRC) is the third most common cancer in the US. The majority of CRC cases are due to deregulated WNT-signalling pathway. These alterations are mainly caused by mutations in the tumour suppressor gene APC or in CTNNB1, encoding the key effector protein of this pathway, β-Catenin. In canonical WNT-signalling, β-Catenin activates the transcription of several target genes, encoding for proteins involved in proliferation, such as MYC, JUN and NOTCH. Being such a critical regulator of these proto-oncogenes, the stability of β-Catenin is tightly regulated by the Ubiquitin-Proteasome System. Several E3 ligases that ubiquitylate and degrade β-Catenin have been described in the past, but the antagonists, the deubiquitylases, are still unknown. By performing an unbiased siRNA screen, the deubiquitylase USP10 was identified as a de novo positive regulator of β-Catenin stability in CRC derived cells. USP10 has previously been shown in the literature to regulate both mutant and wild type TP53 stability, to deubiquitylate NOTCH1 in endothelial cells and to be involved in the regulation of AMPKα signalling. Overall, however, its role in colorectal tumorigenesis remains controversial. By analysing publicly available protein and gene expression data from colorectal cancer patients, we have shown that USP10 is strongly upregulated or amplified upon transformation and that its expression correlates positively with CTNNB1 expression. In contrast, basal USP10 levels were found in non-transformed tissues, but surprisingly USP10 is upregulated in intestinal stem cells. Endogenous interaction studies in CRC-derived cell lines, with different extend of APCtruncation, revealed an APC-dependent mode of action for both proteins. Furthermore, by utilising CRISPR/Cas9, shRNA-mediated knock-down and overexpression of USP10, we could demonstrate a regulation of β-Catenin stability by USP10 in CRC cell lines. It is widely excepted that 2D cell culture systems do not reflect complexity, architecture and heterogeneity and are therefore not suitable to answer complex biological questions. To overcome this, we established the isolation, cultivation and genetically modification of murine intestinal organoids and utilised this system to study Usp10s role ex vivo. By performing RNA sequencing, dependent on different Usp10 levels, we were able to recapitulate the previous findings and demonstrated Usp10 as important regulator of β-dependent regulation of stem cell homeostasis. Since genetic depletion of USP10 resulted in down-regulation of β-Catenin-dependent transcription, therapeutic intervention of USP10 in colorectal cancer was also investigated. Commercial and newly developed inhibitors were tested for their efficacy against USP10, but failed to significantly inhibit USP10 activity in colorectal cancer cells. To validate the findings from this work also in vivo, development of a novel mouse model for colorectal cancer has begun. By combining CRISPR/Cas9 and classical genetic engineering with viral injection strategies, WT and genetically modified mice could be transformed and, at least in some animals, intestinal lesions were detectable at the microscopic level. The inhibition of USP10, which we could describe as a de novo tumour-specific regulator of β-Catenin, could become a new therapeutic strategy for colorectal cancer patients.},
  subject      = {Biomedizin},
  language  = {en}
}
@phdthesis{Gaballa2024,
  author    = {Gaballa, Abdallah Hatem Hassan Hosny Ahmed},
  title     = {PAF1c drives MYC-mediated immune evasion in pancreatic ductal adenocarcinoma},
  doi       = {10.25972/OPUS-36045},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-360459},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {The expression of the MYC proto-oncogene is elevated in a large proportion of patients with pancreatic ductal adenocarcinoma (PDAC). Previous findings in PDAC have shown that this increased MYC expression mediates immune evasion and promotes S-phase progression. How these functions are mediated and whether a downstream factor of MYC mediates these functions has remained elusive. Recent studies identifying the MYC interactome revealed a complex network of interaction partners, highlighting the need to identify the oncogenic pathway of MYC in an unbiased manner. In this work, we have shown that MYC ensures genomic stability during S-phase and prevents transcription-replication conflicts. Depletion of MYC and inhibition of ATR kinase showed a synergistic effect to induce DNA damage. A targeted siRNA screen targeting downstream factors of MYC revealed that PAF1c is required for DNA repair and S-phase progression. Recruitment of PAF1c to RNAPII was shown to be MYC dependent. PAF1c was shown to be largely dispensable for cell proliferation and regulation of MYC target genes. Depletion of CTR9, a subunit of PAF1c, caused strong tumor regression in a pancreatic ductal adenocarcinoma model, with long-term survival in a subset of mice. This effect was not due to induction of DNA damage, but to restoration of tumor immune surveillance. Depletion of PAF1c resulted in the release of RNAPII with transcription elongation factors, including SPT6, from the bodies of long genes, promoting full-length transcription of short genes. This resulted in the downregulation of long DNA repair genes and the concomitant upregulation of short genes, including MHC class I genes. These data demonstrate that a balance between long and short gene transcription is essential for tumor progression and that interference with PAF1c levels shifts this balance toward a tumor-suppressive transcriptional program. It also directly links MYC-mediated S-phase progression to immune evasion. Unlike MYC, PAF1c has a stable, known folded structure; therefore, the development of a small molecule targeting PAF1c may disrupt the immune evasive function of MYC while sparing its physiological functions in cellular growth.},
  subject      = {Myc},
  language  = {en}
}
@phdthesis{Glueck2024,
  author    = {Gl{\"u}ck, Valentina},
  title     = {Habitual avoidance in trait anxiety and anxiety disorders},
  doi       = {10.25972/OPUS-36022},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-360227},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Maladaptive avoidance behaviors can contribute to the maintenance of fear, anxiety, and anxiety disorders. It has been proposed that, throughout anxiety disorder progression, extensively repeated avoidance may become a habit (i.e., habitual avoidance) instead of being controlled by internal threat-related goals (i.e., goal-directed avoidance). However, the process of the acquisition of habitual avoidance in anxiety disorders is not yet well understood. Accordingly, the current thesis aimed to investigate experimentally whether trait anxiety and anxiety disorders are associated with an increased shift from goal-directed to habitual avoidance. The aim of Study 1 was to develop an experimental operationalization of maladaptive habitual avoidance. To this end, we adapted a commonly used action control task, the outcome devaluation paradigm. In this task, habitual avoidance was operationalized as persistent responses after extensive training to avoid an unpleasant stimulus when the aversive outcome was devalued, i.e., when individuals knew the aversive outcome could not occur anymore. We included indicators for costly and low-cost habitual avoidance, whereby habitual avoidance was associated with a monetary cost, while low-cost habitual avoidance was not associated with monetary costs. In Experiment 1 of Study 1, a pronounced costly and non-costly outcome devaluation effect was observed. However, this result may have partly resulted from trial-and-error learning or a better-safe-than-sorry strategy since not instructions about the stimulus-response-outcome contingencies after the outcome devaluation procedure had been provided to the participants. In Experiment 2 of Study 1, instructions on these stimulus-response-outcome contingencies were included to prevent the potential confounders. As a result, we observed no indicators for costly habitual avoidance, but evidence for low-cost habitual avoidance, potentially because competing goal-directed responses could easily be implemented and inhibited costly habitual avoidance tendencies. In Study 2, the strength of habitual avoidance acquisition was compared between participants with and without anxiety disorders, using the experimental task of Experiment 1 in Study 1. The results indicated that costly and low-cost habitual avoidance was not more pronounced in participants with anxiety disorders than in the healthy control group. However, in an exploratory subgroup comparison, panic disorder predicted more substantial habitual avoidance acquisition than social anxiety disorder. In Study 3, we investigated whether trait anxiety as a risk factor for anxiety disorders is associated with a specific increased shift from goal-directed to habitual avoidance and approach. The task from the Experiment 1 of Study 1 was adapted to include parallel versions for operationalizing habitual avoidance and habitual approach responses. Using a within-subjects design, the individuals - pre-screened for high and low trait anxiety - took part in the approach and the avoidance outcome devaluation task version. The results suggested stronger non-costly habitual responses in more highly trait-anxious individuals independent of the task version, and suggested a tendency towards an impact of trait anxiety on costly habitual approach rather than on costly habitual avoidance. In summary, individuals with high trait anxiety or anxiety disorders did not develop habitual avoidance more readily than individuals with low trait anxiety or without anxiety disorders. Therefore, this thesis does not support the assumption that an increased tendency to acquire habitual avoidance contributes to persistent maladaptive avoidance in anxiety disorders. The thesis also contributes to the discourse on the validity of outcome devaluation studies in general by highlighting the impact of task features, such as the instructions after the outcome devaluation procedure or the task difficulty in the test phase, on the experimental results. Such validity issues may partly explain the heterogeneity of findings in research with the outcome devaluation paradigm. We suggest ways towards more valid operationalizations of habitual avoidance in future studies.},
  subject      = {Gewohnheit},
  language  = {en}
}
@phdthesis{Amini2024,
  author    = {Amini, Emad},
  title     = {How central and peripheral clocks and the neuroendocrine system interact to time eclosion behavior in \(Drosophila\) \(melanogaster\)},
  doi       = {10.25972/OPUS-36130},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-361309},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {To grow larger, insects must shed their old rigid exoskeleton and replace it with a new one. This process is called molting and the motor behavior that sheds the old cuticle is called ecdysis. Holometabolic insects have pupal stages in between their larval and adult forms, during which they perform metamorphosis. The pupal stage ends with eclosion, i.e., the emergence of the adult from the pupal shell. Insects typically eclose at a specific time during the day, likely when abiotic conditions are at their optimum. A newly eclosed insect is fragile and needs time to harden its exoskeleton. Hence, eclosion is regulated by sophisticated developmental and circadian timing mechanisms. In Drosophila melanogaster, eclosion is limited to a daily time window in the morning, regarded as the "eclosion gate". In a population of laboratory flies entrained by light/dark cycles, most of the flies eclose around lights on. This rhythmic eclosion pattern is controlled by the circadian clock and persists even under constant conditions. Developmental timing is under the control of complex hormonal signaling, including the steroid ecdysone, insulin-like peptides, and prothoracicotropic hormone (PTTH). The interactions of the central circadian clock in the brain and a peripheral clock in the prothoracic gland (PG) that produces ecdysone are important for the circadian timing of eclosion. These two clocks are connected by a bilateral pair of peptidergic PTTH neurons (PTTHn) that project to the PG. Before each molt, the ecdysone level rises and then falls shortly before ecdysis. The falling ecdysone level must fall below a certain threshold value for the eclosion gate to open. The activity of PTTHn is inhibited by short neuropeptide F (sNPF) from the small ventrolateral neurons (sLNvs) and inhibition is thought to lead to a decrease in ecdysone production. The general aim of this thesis is to further the understanding of how the circadian clock and neuroendocrinal pathways are coordinated to drive eclosion rhythmicity and to identify when these endocrinal signaling pathways are active. In Chapter I, a series of conditional PTTHn silencing-based behavioral assays, combined with neuronal activity imaging techniques such as non-invasive ARG-Luc show that PTTH signaling is active and required shortly before eclosion and may serve to phase-adjust the activity of the PG at the end of pupal development. Trans-synaptic anatomical stainings identified the sLNvs, dorsal neurons 1 (DN1), dorsal neurons 2 (DN2), and lateral posterior neurons (LPNs) clock neurons as directly upstream of the PTTHn. Eclosion motor behavior is initiated by Ecdysis triggering hormone (ETH) which activates a pair of ventromedial (Vm) neurons to release eclosion hormone (EH) which positively feeds back to the source of ETH, the endocrine Inka cells. In Chapter II trans-synaptic tracing showed that most clock neurons provide input to the Vm and non-canonical EH neurons. Hence, clock can potentially influence the ETH/EH feedback loop. The activity profile of the Inka cells and Vm neurons before eclosion is described. Vm and Inka cells are active around seven hours before eclosion. Interestingly, all EH neurons appear to be exclusively peptidergic. In Chapter III, using chemoconnectomics, PTTHns were found to express receptors for sNPF, allatostatin A (AstA), allatostatin C (AstC), and myosuppressin (Ms), while EH neurons expressed only Ms and AstA receptors. Eclosion assays of flies with impaired AstA, AstC, or Ms signaling do not show arrhythmicity under constant conditions. However, optogenetic activation of the AstA neurons strongly suppresses eclosion. Chapter IV focuses on peripheral ventral' Tracheal dendrite (v'Td) and class IV dendritic arborization (C4da) neurons. The C4da neurons mediate larval light avoidance through endocrine PTTH signaling. The v'Td neurons mainly receive O2/CO2 input from the trachea and are upstream of Vm neurons but are not required for eclosion rhythmicity. Conditional ablation of the C4da neurons or torso (receptor of PTTH) knock-out in the C4da neurons impaired eclosion rhythmicity. Six to seven hours before eclosion, PTTHn, C4da, and Vm neurons are active based on ARG-Luc imaging. Thus, C4da neurons may indirectly connect the PTTHn to the Vm neurons. In summary, this thesis advances our knowledge of the temporal activity and role of PTTH signaling during pupal development and rhythmic eclosion. It further provides a comprehensive characterization of the synaptic and peptidergic inputs from clock neurons to PTTHn and EH neurons. AstA, AstC, and Ms are identified as potential modulators of eclosion circuits and suggest an indirect effect of PTTH signaling on EH signaling via the peripheral sensory C4da neurons.},
  subject      = {Neuroendokrines System},
  language  = {en}
}