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Anxiety patients overgeneralize fear, also because of an inability to perceptually discriminate threat and safety signals. Therefore, some studies have developed discrimination training that successfully reduced the occurrence of fear generalization. The present work is the first to take a treatment-like approach by using discrimination training after generalization has occurred. Therefore, two studies were conducted with healthy participants using the same fear conditioning and generalization paradigm, with two faces as conditioned stimuli (CSs), and four facial morphs between CSs as generalization stimuli (GSs). Only one face (CS+) was followed by a loud scream (unconditioned stimulus, US). In Study 1, participants underwent either fear-relevant (discriminating faces) or fear-irrelevant discrimination training (discriminating width of lines) or a non-discriminative control training between the two generalization tests, each with or without feedback (n = 20 each). Generalization of US expectancy was reduced more effectively by fear-relevant compared to fear-irrelevant discrimination training. However, neither discrimination training was more effective than non-discriminative control training. Moreover, feedback reduced generalization of US expectancy only in discrimination training. Study 2 was designed to replicate the effects of the discrimination-training conditions in a large sample (N = 244) and examine their benefits in individuals at risk for anxiety disorders. Again, feedback reduced fear generalization particularly well for US expectancy. Fear relevance was not confirmed to be particularly fear-reducing in healthy participants, but may enhance training effects in individuals at risk of anxiety disorder. In summary, this work provides evidence that existing fear generalization can be reduced by discrimination training, likely involving several (higher-level) processes besides perceptual discrimination (e.g., motivational mechanisms in feedback conditions). Its use may be promising as part of individualized therapy for patients with difficulty discriminating similar stimuli.
RNA viruses rely entirely on the host machinery for their protein synthesis and harbor non-canonical translation mechanisms, such as alternative initiation and programmed –1 ribosomal frameshifting (–1PRF), to suit their specific needs. On the other hand, host cells have developed a variety of defensive strategies to safeguard their translational apparatus and at times transiently shut down global translation. An infection can lead to substantial translational remodeling in cells and translational control is critical during antiviral response. Due to their sheer diversity, this control is likely unique to each RNA virus and the intricacies of post-transcriptional regulation are unclear in certain viral species.
Here, we explored different aspects of translational regulation in virus-infected cells in detail. Using ribosome profiling, we extensively characterized the translational landscape in HIV-1 infected T cells, uncovering novel features of gene regulation in both host and virus. Additionally, we show that substantial pausing occurs prior to the frameshift site indicating complex regulatory mechanisms involving upstream viral RNA elements that can act as cis- regulators of frameshifting.
We also characterized the mechanistic details of trans- modulation of frameshifting by host- and virus-encoded proteins. Host antiviral protein ZAP-S binds to the SARS-CoV-2 frameshift site and destabilizes the stimulatory structure, leading to frameshift inhibition. On the other hand, EMCV 2A protein stabilizes the viral frameshift site, thereby, activating EMCV frameshifting. While both proteins were shown to be antagonistic in their mechanism, they interact with the host translational machinery. Furthermore, we showed that frameshifting can be regulated not just by proteins, but also by small molecules. High-throughput screening of natural and synthetic compounds identified two potent frameshift inhibitors that also impeded viral replication, namely trichangion and compound 25. Together, this work largely enhances our understanding of gene regulation mechanisms in virus-infected cells and further validates the druggability of viral –1 PRF site.
Background
Complex regional pain syndrome (CRPS) develops after injury and is characterized by disproportionate pain, oedema, and functional loss. CRPS has clinical signs of neuropathy as well as neurogenic inflammation. Here, we asked whether skin biopsies could be used to differentiate the contribution of these two systems to ultimately guide therapy. To this end, the cutaneous sensory system including nerve fibres and the recently described nociceptive Schwann cells as well as the cutaneous immune system were analysed.
Methods
We systematically deep-phenotyped CRPS patients and immunolabelled glabrous skin biopsies from the affected ipsilateral and non-affected contralateral finger of 19 acute (< 12 months) and 6 chronic (> 12 months after trauma) CRPS patients as well as 25 sex- and age-matched healthy controls (HC). Murine foot pads harvested one week after sham or chronic constriction injury were immunolabelled to assess intraepidermal Schwann cells.
Results
Intraepidermal Schwann cells were detected in human skin of the finger—but their density was much lower compared to mice. Acute and chronic CRPS patients suffered from moderate to severe CRPS symptoms and corresponding pain. Most patients had CRPS type I in the warm category. Their cutaneous neuroglial complex was completely unaffected despite sensory plus signs, e.g. allodynia and hyperalgesia. Cutaneous innate sentinel immune cells, e.g. mast cells and Langerhans cells, infiltrated or proliferated ipsilaterally independently of each other—but only in acute CRPS. No additional adaptive immune cells, e.g. T cells and plasma cells, infiltrated the skin.
Conclusions
Diagnostic skin punch biopsies could be used to diagnose individual pathophysiology in a very heterogenous disease like acute CRPS to guide tailored treatment in the future. Since numbers of inflammatory cells and pain did not necessarily correlate, more in-depth analysis of individual patients is necessary.
African trypanosomes are unicellular parasites that cause nagana and sleeping sickness in livestock and man, respectively. The major pathogens for the animal disease include Trypanosoma vivax, T. congolense, and T. brucei brucei, whereas T. b. gambiense and T. b. rhodesiense are responsible for human infections. Given that the bloodstream form (BSF) of African trypanosomes is exclusively extracellular, its cell surface forms a critical boundary with the host environment. The cell surface of the BSF African trypanosomes is covered by a dense coat of immunogenic variant surface glycoproteins (VSGs). This surface protein acts as an impenetrable shield that protects the cells from host immune factors and is also involved in antibody clearance and antigenic variation, which collectively ensure that the parasite stays ahead of the host immune system. Gene expression in T. brucei is markedly different from other eukaryotes: most genes are transcribed as long polycistronic units, processed by trans-splicing a 39-nucleotide mini exon at the 5′ and polyadenylation at the 3′ ends of individual genes to generate the mature mRNA.
Therefore, gene expression in T. brucei is regulated post-transcriptionally, mainly by the action of RNA binding proteins (RBPs) and conserved elements in the 3′ untranslated regions (UTR) of transcripts. The expression of VSGs is highly regulated, and only a single VSG gene is expressed at a time from one of the ~15 subtelomeric domains termed bloodstream expression sites (BES). When cells are engineered to simultaneously express two VSGs, the total VSG mRNA do not exceed the wild type amounts. This suggests that a robust VSG mRNA balancing mechanism exists in T. brucei. The present study uses inducible and constitutive expression of ectopic VSG genes to show that the endogenous VSG mRNA is regulated only if the second VSG is properly targeted to the ER. Additionally, the endogenous VSG mRNA response is triggered when high amounts of the GFP reporter with a VSG 3′UTR is targeted to the ER. Further evidence that non-VSG ER import signals can efficiently target VSGs to the ER is presented. This study suggests that a robust trans-regulation of the VSG mRNA is elicited at the ER through a feedback loop to keep the VSG transcripts in check and avoid overshooting the secretory pathway capacity.
Further, it was shown that induction of expression of the T. vivax VSG ILDat1.2 in T. brucei causes a dual cell cycle arrest, with concomitant upregulation of the protein associated with differentiation (PAD1) expression. It could be shown that T. vivax VSG ILDat1.2 can only be sufficiently expressed in T. brucei after replacing its native GPI signal peptide with that of a T. brucei VSG. Taken together, these data indicate that inefficient VSG GPI anchoring and expression of low levels of the VSG protein can trigger differentiation from slender BSF to stumpy forms. However, a second T. vivax VSG, ILDat2.1, is not expressed in T. brucei even after similar modifications to its GPI signals. An X-ray crystallography approach was utilized to solve the N-terminal domain (NTD) structure of VSG ILDat1.2. This is first structure of a non-T. brucei VSG, and the first of a surface protein of T. vivax to be solved. VSG ILDat1.2 NTD maintains the three-helical bundle scaffold conserved in T. brucei surface proteins. However, it is likely that there are variations in the architecture of the membrane proximal region of the ILDat1.2 NTD and its CTD from T. brucei VSGs. The tractable T. brucei system is presented as a model that can be used to study surface proteins of related trypanosome species, thus creating avenues for further characterization of trypanosome surface coats.
The goal of this thesis is to study the topological and algebraic properties of the quasiconformal automorphism groups of simply and multiply connected domains in the complex plain, in which the quasiconformal automorphism groups are endowed with the supremum metric on the underlying domain. More precisely, questions concerning central topological properties such as (local) compactness, (path)-connectedness and separability and their dependence on the boundary of the corresponding domains are studied, as well as completeness with respect to the supremum metric. Moreover, special subsets of the quasiconformal automorphism group of the unit disk are investigated, and concrete quasiconformal automorphisms are constructed. Finally, a possible application of quasiconformal unit disk automorphisms to symmetric cryptography is presented, in which a quasiconformal cryptosystem is defined and studied.
Defensive behaviors in response to threats are key factors in maintaining mental and physical health, but their phenomenology remains poorly understood. Prior work reported an inhibition of oculomotor activity in response to avoidable threat in humans that reminded of freezing behaviors in rodents. This notion of a homology between defensive responding in rodents and humans was seconded by concomitant heart rate decrease and skin conductance increase. However, several aspects of this presumed defense state remained ambiguous. For example, it was unclear whether the observed oculomotor inhibition would 1) robustly occur during preparation for threat-avoidance irrespective of task demands, 2) reflect a threat-specific defensive state, 3) be related to an inhibition of somatomotor activity as both motion metrics have been discussed as indicators for freezing behaviors in humans, and 4) manifest in unconstrained settings.
We thus embarked on a series of experiments to unravel the robustness, threat-specificity, and validity of previously observed (oculo)motor and autonomic dynamics upon avoidable threat in humans. We provided robust evidence for reduced gaze dispersion, significantly predicting the speed of subsequent motor reactions across a wide range of stimulus contexts. Along this gaze pattern, we found reductions in body movement and showed that the temporal profiles between gaze and body activity were positively related within individuals, suggesting that both metrics reflect the same construct. A simultaneous activation of the parasympathetic (i.e., heart rate deceleration) and sympathetic (i.e., increased skin conductance and pupil dilation) nervous system was present in both defensive and appetitive contexts, suggesting that these autonomic dynamics are not only sensitive to threat but reflecting a more general action-preparatory mechanism. We further gathered evidence for two previously proposed defensive states involving a decrease of (oculo)motor activity in a naturalistic, unconstrained virtual reality environment. Specifically, we observed a state consisting of a cessation of ongoing behaviors and orienting upon relatively distal, ambiguous threat (Attentive Immobility) while an entire immobilization and presumed allocation of attention to the threat stimulus became apparent upon approaching potential threat (Immobility under Attack).
Taken together, we provided evidence for specific oculomotor and autonomic dynamics upon increasing levels of threat that may inspire future translational work in rodents and humans on shared mechanisms of threat processing, ultimately supporting the development of novel therapeutic approaches.
The cystine/glutamate antiporter xCT is an important source of cysteine for cancer cells. Once taken up, cystine is reduced to cysteine and serves as a building block for the synthesis of glutathione, which efficiently protects cells from oxidative damage and prevents ferroptosis. As melanomas are particularly exposed to several sources of oxidative stress, we investigated the biological role of cysteine and glutathione supply by xCT in melanoma. xCT activity was abolished by genetic depletion in the Tyr::CreER; Braf\(^{CA}\); Pten\(^{lox/+}\) melanoma model and by acute cystine withdrawal in melanoma cell lines. Both interventions profoundly impacted melanoma glutathione levels, but they were surprisingly well tolerated by murine melanomas in vivo and by most human melanoma cell lines in vitro. RNA sequencing of human melanoma cells revealed a strong adaptive upregulation of NRF2 and ATF4 pathways, which orchestrated the compensatory upregulation of genes involved in antioxidant defence and de novo cysteine biosynthesis. In addition, the joint activation of ATF4 and NRF2 triggered a phenotypic switch characterized by a reduction of differentiation genes and induction of pro-invasive features, which was also observed after erastin treatment or the inhibition of glutathione synthesis. NRF2 alone was capable of inducing the phenotypic switch in a transient manner. Together, our data show that cystine or glutathione levels regulate the phenotypic plasticity of melanoma cells by elevating ATF4 and NRF2.
Deep Learning (DL) models are trained on a downstream task by feeding (potentially preprocessed) input data through a trainable Neural Network (NN) and updating its parameters to minimize the loss function between the predicted and the desired output. While this general framework has mainly remained unchanged over the years, the architectures of the trainable models have greatly evolved. Even though it is undoubtedly important to choose the right architecture, we argue that it is also beneficial to develop methods that address other components of the training process. We hypothesize that utilizing domain knowledge can be helpful to improve DL models in terms of performance and/or efficiency. Such model-agnostic methods can be applied to any existing or future architecture. Furthermore, the black box nature of DL models motivates the development of techniques to understand their inner workings. Considering the rapid advancement of DL architectures, it is again crucial to develop model-agnostic methods.
In this thesis, we explore six principles that incorporate domain knowledge to understand or improve models. They are applied either on the input or output side of the trainable model. Each principle is applied to at least two DL tasks, leading to task-specific implementations. To understand DL models, we propose to use Generated Input Data coming from a controllable generation process requiring knowledge about the data properties. This way, we can understand the model’s behavior by analyzing how it changes when one specific high-level input feature changes in the generated data. On the output side, Gradient-Based Attribution methods create a gradient at the end of the NN and then propagate it back to the input, indicating which low-level input features have a large influence on the model’s prediction. The resulting input features can be interpreted by humans using domain knowledge.
To improve the trainable model in terms of downstream performance, data and compute efficiency, or robustness to unwanted features, we explore principles that each address one of the training components besides the trainable model. Input Masking and Augmentation directly modifies the training input data, integrating knowledge about the data and its impact on the model’s output. We also explore the use of Feature Extraction using Pretrained Multimodal Models which can be seen as a beneficial preprocessing step to extract useful features. When no training data is available for the downstream task, using such features and domain knowledge expressed in other modalities can result in a Zero-Shot Learning (ZSL) setting, completely eliminating the trainable model. The Weak Label Generation principle produces new desired outputs using knowledge about the labels, giving either a good pretraining or even exclusive training dataset to solve the downstream task. Finally, improving and choosing the right Loss Function is another principle we explore in this thesis. Here, we enrich existing loss functions with knowledge about label interactions or utilize and combine multiple task-specific loss functions in a multitask setting.
We apply the principles to classification, regression, and representation tasks as well as to image and text modalities. We propose, apply, and evaluate existing and novel methods to understand and improve the model. Overall, this thesis introduces and evaluates methods that complement the development and choice of DL model architectures.
Dipolar merocyanines are very attractive supramolecular building blocks, as they combine interesting functional properties with strong, directional intermolecular interactions. The pyridine dioxocyano-pyridine (PYOP) chromophore (Chapter 2.2), used in this thesis, stands out because of its exceptionally high ground state dipole moment (g ~ 17 D), in combination with the option to retain good solubility also in unpolar solvents, by decoration with solubilizing groups.
The reliable binding motif of anti-parallel -stacking due to dipole-dipole interactions has allowed the design of molecular building blocks that form assemblies of predictable geometry. The intense unstructured charge transfer UV/Vis absorption band (eg ~ 10.7 D) is a result of the dominant contribution of the zwitterionic resonance structure which brings the PYOP chromophore just beyond the cyanine limit in solvents of low polarity (c2 = 0.60, 1,4 dioxane). The high sensitivity of the S0 – S1 UV/Vis absorption band to the environment manifests itself in a pronounced negative solvatochromism and strong H-type exciton coupling within -stacked PYOP assemblies. In accordance with the classical molecular exciton theory, an increasing hypsochromic shift of the dominant absorption band of these H aggregates can be observed as the stack size increases up to about six chromophores, where it levels out at about max ~ 440 nm (CHCl3). This allows a uniquely simple estimation of the number of interacting chromophores within the self-assembled structure from a single UV/Vis absorption spectrum of an aggregate.
The defined and well investigated PYOP dimer formation was employed in this thesis to probe the applicability and limitations of concentration-, temperature-, and solvent-dependent self-assembly studies (Chapter 3). Straightforward theoretical models to evaluate datasets of concentration-, temperature-, and solvent-dependent UV/Vis absorption by nonlinear regression analysis were derived for the case of dimer formation (Chapter 2.1). Although the dimer model is well known and widely applied in literature, this detailed derivation is helpful to understand assumptions and potential problems of the different approaches for the determination of thermodynamic parameters. This helps to decide on the most appropriate method to analyse a system of interest. In this regard it should be noted that covering a large portion of the self-assembly process with the experimental data is a prerequisite for the accuracy of the analysis. Additionally, many of the insights can also be transferred to other self-assembly systems like supramolecular polymerization or host-guest interactions.
The concentration-dependent analysis is the most straightforward method to investigate self-assembly equilibria. No additional assumptions, besides mass balance and mass action law, are required. Since it includes the least number of parameters (only K, if M/D are known), it is the most, or even only, reliable method, to elucidate the self-assembly mechanism of an unknown system by model comparison. To cover a large concentration range, however, the compound must be soluble enough and generally sample amounts at least in the low mg scale must be available.
The temperature-dependent analysis has the advantage that all thermodynamic parameters G0, H0 and S0 can be obtained from a single sample in one automated measurement. However, the accessible temperature-range is experimentally often quite limited and dependent on the solvent. For systems which do not show the transition from monomer to aggregate in a narrow temperature range, as given for, e.g., cooperative aggregation or processes with a high entropy contribution, often not the entire self-assembly process can be monitored. Furthermore, the assumptions of temperature-independent extinction coefficients of the individual species as well as temperature-independent H0 and S0 must be met. Monte Carlo simulations of data sets demonstrated that even minor changes in experimental data can significantly impact the optimized values for H0 and S0. This is due to the redundancy of these two parameters within the model framework and even small thermochromic effects can significantly influence the results. The G0 value, calculated from H0 and S0, is, however, still rather reliable.
Solvent-dependent studies can often cover the entire self-assembly process from monomeric (agg = 0) to the fully aggregated state (agg = 1). However, for dyes with strong solvatochromic effects, such as the dipolar merocyanines investigated in this thesis, the results are affected. Also, the assumption of a linear relation of the binding energy G0 and the fraction of denaturating solvent f, which is based on linear free energy relationships between G0 and the solvent polarity, can lead to errors. Especially when specific solvent effects are involved.
For the evaluation of experimental data by nonlinear regression, general data analysis software can be used, where user-defined fit models and known parameters can be implemented as desired. Alternatively, multiple specialized programs for analysing self-assembly data are available online. While the latter programs are usually more user-friendly, they have the disadvantage of being a “black box” where only pre-implemented models can be used without the option for the user to adapt models or parameters for a specific system.
In Chapter 3 comprehensive UV/Vis absorption datasets are presented for the dimerization of merocyanine derivative 1 in 1,4-dioxane, which allowed for the first time a direct comparison of the results derived from concentration-, temperature-, and solvent-dependent self-assembly studies.
The results for the binding constant K and corresponding G0 from the concentration- and temperature-dependent analysis were in very good agreement, also in comparison to the results from ITC. For the temperature-dependent analysis, though, multiple datasets of samples with different concentration had to be evaluated simultaneously to cover a meaningful part of the self-assembly process. Furthermore, a significant dependence of the optimized parameters H0 and S0 on the wavelength chosen for the analysis was observed. This can be rationalized by the small thermochromic shifts of both the monomer and the dimer UV/Vis absorption band. The results from the solvent-dependent evaluation showed the largest deviation, as expected for the highly solvatochromic merocyanine dye.
However, even here by evaluation at 491 and 549 nm the deviation for G0 was only 2.5 kJ mol1 (9%) with respect to the results from the concentration-dependent analysis (G0 = 29.1 kJ mol1). Thus, despite the strong solvatochromism of the dipolar chromophore, it can still be considered a reliable method for estimating the binding strength. Furthermore, multiple repetitions of the concentration-, temperature-, and solvent-dependent studies provided insight into the reproducibility of the results and possible sources of experimental errors. In all cases, the deviations of the results were small (G0 < 0.4 kJ mol1) and within the same range as the fit error from the nonlinear regression analysis.
The insights from these studies were an important basis for the in-depth investigation of a more complex supramolecular system in Chapter 4, as a single method is often not enough to capture the full picture of a more complicated self-assembly process. To elucidate the anti-cooperative self-assembly of the chiral merocyanine 2, a combination of multiple techniques had to be applied.
Solvent-dependent UV/Vis absorption studies in CH2Cl2/MCH mixtures showed the step-wise assembly of the merocyanine monomer (max(M) = 549 nm, CH2Cl2) to first a dimer (max(D) = 498 nm, CH2Cl2/MCH 15:85) by dipole-dipole interactions, and then a -stacked higher aggregate (max(H) = 477 nm, MCH), with pronounced H-type coupling.
The thermodynamic evaluation of this data, however, suffered from the severe solvatochromism, especially of the monomeric species (max(M, CH2Cl2) = 549 nm, max(M, MCH) = 596 nm). Therefore, concentration-dependent studies were performed at three different temperatures (298, 323, 353 K) to elucidate the self-assembly mechanism and determine reliable thermodynamic parameters. The studies at elevated temperatures were hereby necessary, to obtain experimental data over a larger agg--range. Due to the pronounced difference in the thermodynamic driving force for dimerization and higher aggregate formation (KD/K5 = 6500) a concentration range exists in MCH where almost exclusively the dimer species of 2 is present, before further self-assembly by dispersion interactions occurs. Therefore, the data could be evaluated independently for the two self-assembly steps. The self-assembly of dimers into the higher aggregate could not be described by the isodesmic model but was fitted satisfactorily to a pentamer model. This rather small size of about ten -stacked PYOP chromophores was, furthermore, consistently indicated by AFM, VPO and DOSY NMR measurements. Based on 1D and 2D NMR data as well as the strong bisignate CD signal of the higher aggregate in combination with TD-DFT calculations, a P-helical stack is proposed as its structure. The small size can be rationalized by the anti-cooperative self-assembly mechanism and the sterical demand of the solubilizing trialkoxyphenyl and the chiral tetralin substituents. Additionally, the aliphatic shell formed by the solubilizing chains around the polar chromophore stack, can account for the exceptionally high solubility of 2 in MCH (> 15 mg mL1). These combined studies of the self-assembly process enabled the identification of suitable conditions for the investigation of fluorescence properties of the individual aggregate species. Aggregation-induced emission enhancement was observed for the almost non-emissive monomer (Fl(M) = 0.23%), which can be rationalized by the increasing rigidification within the dimer (Fl(D) = 2.3%) and the higher aggregate (Fl(H) = 4.5%). The helical chirality of the PYOP decamer stack, furthermore, gave rise to a strong CPL signal with a large glum value of 0.011.
The important conclusion of this thesis is that the temperature- and solvent-dependent analyses are valid alternatives to the classical concentration-dependent analysis to determine thermodynamic parameters of self-assembly equilibria. Although, for a specific supramolecular system, one approach might be favourable over the others for a variety of reasons. The experimental limitations often demand a combination of techniques to fully elucidate a self-assembly process and to gain insights in the aggregate structure. The anti-cooperative merocyanine self-assembly, which was described here for the first time for the PYOP merocyanine 2, is no exception. Besides the interest in the merocyanine assemblies from a structural and functional point of view, the insights gained from the presented studies can also be transferred to other self-assembly systems and be a guide to find the most appropriate analysis technique.
Theory and simulation of ultrafast autodetachment dynamics and nonradiative relaxation in molecules
(2024)
In this thesis, theoretical approaches for the simulation of electron detachment processes in molecules following vibrational or electronic excitation are developed and applied. These approaches are based on the quantum-classical surface-hopping methodology, in which nuclear motion is treated classically as an ensemble of trajectories in the potential of quantum-mechanically described electronic degrees of freedom.