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Background and aims:
To succeed in competition, elite team and individual athletes often seek the development of both, high levels of muscle strength and power as well as cardiorespiratory endurance. In this context, concurrent training (CT) is a commonly applied and effective training approach. While being exposed to high training loads, youth athletes (≤ 18 years) are yet underrepresented in the scientific literature. Besides, immunological responses to CT have received little attention. Therefore, the aims of this work were to examine the acute (< 15min) and delayed (≥ 6 hours) effects of dif-ferent exercise order in CT on immunological stress responses, muscular fitness, metabolic response, and rating of perceived exertion (RPE) in highly trained youth male and female judo athletes.
Methods:
A total of twenty male and thirteen female participants, with an average age of 16 ± 1.8 years and 14.4 ± 2.1 years, respectively, were included in the study. They were randomly assigned to two CT sessions; power-endurance versus endurance-power (i.e., study 1), or strength-endurance versus endurance-strength (i.e., study 2). Markers of immune response (i.e., white-blood-cells, granulocytes, lymphocytes, mon-ocytes, and lymphocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index), muscular fitness (i.e., counter-movement jump [CMJ]), metabolic responses (i.e., blood lactate, glucose), and RPE were collected at different time points (i.e., PRE12H, PRE, MID, POST, POST6H, POST22H).
Results (study 1):
There were significant time*order interactions for white-blood-cells, lymphocytes, granulocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The power-endurance order resulted in significantly larger PRE-to-POST increases in white-blood-cells, monocytes, and lymphocytes while the endur-ance-power order resulted in significantly larger PRE-to-POST increases in the granu-locyte-lymphocyte-ratio and systemic-inflammation-index. Likewise, significantly larger increases from PRE-to-POST6H in white-blood-cells and granulocytes were observed following the power-endurance order compared to endurance-power. All markers of immune response returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. Following the endur-ance-power order, blood lactate and glucose increased from PRE-to-MID but not from PRE-to-POST. Meanwhile, in the power-endurance order blood lactate and glucose increased from PRE-to-POST but not from PRE-to-MID. A significant time*order inter-action was observed for CMJ-force with larger PRE-to-POST decreases in the endur-ance-power order compared to power-endurance order. Further, CMJ-power showed larger PRE-to-MID performance decreases following the power-endurance order, com-pared to the endurance-power order. Regarding RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endurance-power order and larger PRE-to-POST values following the power-endurance order.
Results (study 2):
There were significant time*order interactions for lymphocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The strength-endurance order resulted in significantly larger PRE-to-POST increases in lymphocytes while the endurance-strength order resulted in significantly larger PRE-to-POST increases in the granulocyte-lymphocyte-ratio and systemic-inflammation-index. All markers of the immune system returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. From PRE-to-MID, there was a significantly greater increase in blood lactate and glu-cose following the endurance-strength order compared to strength-endurance order. Meanwhile, from PRE-to-POST there was a significantly higher increase in blood glu-cose following the strength-endurance order compared to endurance-strength order. Regarding physical fitness, a significant time*order interaction was observed for CMJ-force and CMJ-power with larger PRE-to-MID increases following the endurance-strength order compared to the strength-endurance order. For RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endur-ance-power order and larger PRE-to-POST values following the power-endurance or-der.
Conclusions:
The primary findings from both studies revealed order-dependent effects on immune responses. In male youth judo athletes, the results demonstrated greater immunological stress responses, both immediately (≤ 15 min) and delayed (≥ 6 hours), following the power-endurance order compared to the endurance-power order. For female youth judo athletes, the results indicated higher acute, but not delayed, order-dependent changes in immune responses following the strength-endurance order compared to the endurance-strength order. It is worth noting that in both studies, all markers of immune system response returned to baseline levels within 22 hours. This suggests that successful recovery from the exercise-induced immune stress response was achieved within 22 hours. Regarding metabolic responses, physical fitness, and perceived exertion, the findings from both studies indicated acute (≤ 15 minutes) alterations that were dependent on the exercise order. These alterations were primarily influ-enced by the endurance exercise component. Moreover, study 1 provided substantial evidence suggesting that internal load measures, such as immune markers, may differ from external load measures. This indicates a disparity between immunological, perceived, and physical responses following both concurrent training orders. Therefore, it is crucial for practitioners to acknowledge these differences and take them into consideration when designing training programs.
Leaves exhibit cells with varying degrees of shape complexity along the proximodistal axis. Heterogeneities in growth directions within individual cells bring about such complexity in cell shape. Highly complex and interconnected gene regulatory networks and signaling pathways have been identified to govern these processes. In addition, the organization of cytoskeletal networks and cell wall mechanical properties greatly influences the regulation of cell shape. Research has shown that microtubules are involved in regulating cellulose deposition and direc-tion of cell growth. However, comprehensive analysis of the regulation of the actin cytoskele-ton in cell shape regulation has not been well studied.
This thesis provides evidence that actin regulates aspects of cell growth, division, and direction-al expansion that impacts morphogenesis of developing leaves. The jigsaw puzzle piece mor-phology of epidermal pavement cells further serves as an ideal system to investigate the com-plex process of morphogenetic processes occurring at the cellular level. Here we have em-ployed live cell based imaging studies to track the development of pavement cells in actin com-promised conditions. Genetic perturbation of two predominantly expressed vegetative actin genes ACTIN2 and ACTIN7 results in delayed emergence of the cellular protrusions in pave-ment cells. Perturbation of actin also impacted the organization of microtubule in these cells that is known to promote emergence of cellular protrusions. Further, live-cell imaging of actin or-ganization revealed a correlation with cell shape, suggesting that actin plays a role in influencing pavement cell morphogenesis.
In addition, disruption of actin leads to an increase in cell size along the leaf midrib, with cells being highly anisotropic due to reduced cell division. The reduction of cell division further im-pacted the morphology of the entire leaf, with the mutant leaves being more curved. These re-sults suggests that actin plays a pivotal role in regulating morphogenesis at the cellular and tis-sue scales thereby providing valuable insights into the role of the actin cytoskeleton in plant morphogenesis.
In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.
Many complex systems that we encounter in the world can be formalized using networks. Consequently, they have been in the focus of computer science for decades, where algorithms are developed to understand and utilize these systems.
Surprisingly, our theoretical understanding of these algorithms and their behavior in practice often diverge significantly. In fact, they tend to perform much better on real-world networks than one would expect when considering the theoretical worst-case bounds. One way of capturing this discrepancy is the average-case analysis, where the idea is to acknowledge the differences between practical and worst-case instances by focusing on networks whose properties match those of real graphs. Recent observations indicate that good representations of real-world networks are obtained by assuming that a network has an underlying hyperbolic geometry.
In this thesis, we demonstrate that the connection between networks and hyperbolic space can be utilized as a powerful tool for average-case analysis. To this end, we first introduce strongly hyperbolic unit disk graphs and identify the famous hyperbolic random graph model as a special case of them. We then consider four problems where recent empirical results highlight a gap between theory and practice and use hyperbolic graph models to explain these phenomena theoretically. First, we develop a routing scheme, used to forward information in a network, and analyze its efficiency on strongly hyperbolic unit disk graphs. For the special case of hyperbolic random graphs, our algorithm beats existing performance lower bounds. Afterwards, we use the hyperbolic random graph model to theoretically explain empirical observations about the performance of the bidirectional breadth-first search. Finally, we develop algorithms for computing optimal and nearly optimal vertex covers (problems known to be NP-hard) and show that, on hyperbolic random graphs, they run in polynomial and quasi-linear time, respectively.
Our theoretical analyses reveal interesting properties of hyperbolic random graphs and our empirical studies present evidence that these properties, as well as our algorithmic improvements translate back into practice.
As a result of CMOS scaling, radiation-induced Single-Event Effects (SEEs) in electronic circuits became a critical reliability issue for modern Integrated Circuits (ICs) operating under harsh radiation conditions. SEEs can be triggered in combinational or sequential logic by the impact of high-energy particles, leading to destructive or non-destructive faults, resulting in data corruption or even system failure. Typically, the SEE mitigation methods are deployed statically in processing architectures based on the worst-case radiation conditions, which is most of the time unnecessary and results in a resource overhead. Moreover, the space radiation conditions are dynamically changing, especially during Solar Particle Events (SPEs). The intensity of space radiation can differ over five orders of magnitude within a few hours or days, resulting in several orders of magnitude fault probability variation in ICs during SPEs. This thesis introduces a comprehensive approach for designing a self-adaptive fault resilient multiprocessing system to overcome the static mitigation overhead issue. This work mainly addresses the following topics: (1) Design of on-chip radiation particle monitor for real-time radiation environment detection, (2) Investigation of space environment predictor, as support for solar particle events forecast, (3) Dynamic mode configuration in the resilient multiprocessing system. Therefore, according to detected and predicted in-flight space radiation conditions, the target system can be configured to use no mitigation or low-overhead mitigation during non-critical periods of time. The redundant resources can be used to improve system performance or save power. On the other hand, during increased radiation activity periods, such as SPEs, the mitigation methods can be dynamically configured appropriately depending on the real-time space radiation environment, resulting in higher system reliability. Thus, a dynamic trade-off in the target system between reliability, performance and power consumption in real-time can be achieved. All results of this work are evaluated in a highly reliable quad-core multiprocessing system that allows the self-adaptive setting of optimal radiation mitigation mechanisms during run-time. Proposed methods can serve as a basis for establishing a comprehensive self-adaptive resilient system design process. Successful implementation of the proposed design in the quad-core multiprocessor shows its application perspective also in the other designs.
Pichia pastoris (syn. Komagataella phaffi) is a distinguished expression system widely used in industrial production processes. Recent molecular research has focused on numerous approaches to increase recombinant protein yield in P. pastoris. For example, the design of expression vectors and synthetic genetic elements, gene copy number optimization, or co-expression of helper proteins
(transcription factors, chaperones, etc.). However, high clonal variability of transformants and low screening throughput have hampered significant success.
To enhance screening capacities, display-based methodologies inherit the potential for efficient isolation of producer clones via fluorescence-activated cell sorting (FACS). Therefore, this study focused on developing a novel clone selection method that is based on the non-covalent attachment of Fab fragments on the P. pastoris cell surface to be applicable for FACS.
Initially, a P. pastoris display system was developed, which is a prerequisite for the surface capture of secreted Fabs. A Design of Experiments approach was applied to analyze the influence of various genetic elements on antibody fragment display. The combined P. pastoris formaldehyde dehydrogenase promoter (PFLD1), Saccharomyces cerevisiae invertase 2 signal peptide (ScSUC2), - agglutinin (ScSAG1) anchor protein, and the ARS of Kluyveromyces lactis (panARS) conferred highest display levels.
Subsequently, eight single-chain variable fragments (scFv) specific for the constant part of the Fab heavy or light chain were individually displayed in P. pastoris. Among the tested scFvs, the anti-human CH1 IgG domain scFv allowed the most efficient Fab capture detected by flow cytometry.
Irrespective of the Fab sequence, exogenously added as well as simultaneously secreted Fabs were successfully captured on the cell surface. Furthermore, Fab secretion capacities were shown to correlate to the level of surface-bound Fabs as demonstrated for characterized producer clones.
Flow-sorted clones presenting high amounts of Fabs showed an increase in median Fab titers (factor of 21 to 49) compared to unsorted clones when screened in deep-well plates. For selected candidates, improved functional Fab yields of sorted cells vs. unsorted cells were confirmed in an upscaled shake flask production. Since the scFv capture matrix was encoded on an episomal plasmid with inherently unstable autonomously replicating sequences (ARS), efficient plasmid curing was observed after removing the selective pressure. Hence, sorted clones could be immediately used for production without the need to modify the expression host or vector. The resulting switchable display/secretion system provides a streamlined approach for the isolation of Fab producers and subsequent Fab production.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
The emerging threat of antibiotic-resistant bacteria has become a global challenge in the last decades, leading to a rising demand for alternative treatments for bacterial infections. One approach is to target the bacterial cell envelope, making understanding its biophysical properties crucial. Specifically, bacteriophages use the bacterial envelope as an entry point to initiate infection, and they are considered important building blocks of new antibiotic strategies against drug-resistant bacteria.. Depending on the structure of the cell wall, bacteria are classified as Gram-negative and Gram-positive. Gram-negative bacteria are equipped with a complex cell envelope composed of two lipid membranes enclosing a rigid peptidoglycan layer. The synthesis machinery of the Gram-negative cell envelope is the target of antimicrobial agents, including new physical sanitizing procedures addressing the outer membrane (OM). It is therefore very important to study the biophysical properties of the Gram-negative bacterial cell envelope. The high complexity of the Gram-negative OM sets the demand for a model system in which the contribution of individual components can be evaluated separately. In this respect, giant unilamellar vesicles (GUVs) are promising membrane systems to study membrane properties while controlling parameters such as membrane composition and surrounding medium conditions.
The aim of this work was to develop methods and approaches for the preparation and characterization of a GUV-based membrane model that mimics the OM of the Gram-negative cell envelope. A major component of the OM is the lipopolysaccharide (LPS) on the outside of the OM heterobilayer. The vesicle model was designed to contain LPS in the outer leaflet and lipids in the inner leaflet. Furthermore, the interaction of the prepared LPS-GUVs with bacteriophages was tested. LPS containing GUVs were prepared by adapting the inverted emulsion technique to meet the challenging properties of LPS, namely their high self-aggregation rate in aqueous solutions. Notably, an additional emulsification step together with the adaption of solution conditions was employed to asymmetrically incorporate LPS containing long polysaccharide chains into the artificial membranes. GUV membrane asymmetry was verified with a fluorescence quenching assay. Since the necessary precautions for handling the quenching agent sodium dithionite are often underestimated and poorly described, important parameters were tested and identified to obtain a stable and reproducible assay. In the context of varied LPS incorporation, a microscopy-based technique was introduced to determine the LPS content on individual GUVs and to directly compare vesicle properties and LPS coverage. Diffusion coefficient measurements in the obtained GUVs showed that increasing LPS concentrations in the membranes resulted in decreased diffusivity.
Employing LPS-GUVs we could demonstrate that a Salmonella bacteriophage bound with high specificity to its LPS receptor when presented at the GUV surface, and that the number of bound bacteriophages scaled with the amount of presented LPS receptor. In addition to binding, the bacteriophages were able to eject their DNA into the vesicle lumen. LPS-GUVs thus provide a starting platform for bottom-up approaches for the generation of more complex membranes, in which the effects of individual components on the membrane properties and the interaction with antimicrobial agents such as bacteriophages could be explored.
"Il Gattopardo" nella DDR
(2023)
Sulla base di materiale d'archivio inedito si ripercorre l'avvincente storia della prima edizione del Gattopardo nella DDR (1961). È qui analizzata la corsa ad ostacoli del romanzo tra congruenze ed eccezioni che assume i tratti di un giallo letterario. L'opera di un principe defunto scavalca il Muro grazie ad Alfred Kurella, potente funzionario della SED. Nella sua postfazione Il Gattopardo non è canto della decadenza, ma preannuncio di una nuova epoca, manifesto dello Stato in procinto di entrare nell'era socialista. La chiave di lettura è un unicum con una marcata impronta ideologica che ne determina prima la fortuna e poi l'isolamento. Al Gattopardo nella Germania Est Bernardina Rago dà per la prima volta voce.