DWI – Leibniz Institute for Interactive Materials
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Comparing the electrical performance of commercial sodium-ion and lithium-iron-phosphate batteries
No full textDeveloping a Simplified Linear-Elastic Material Model for Carbon Paper Applied in the Rough Rail–Wheel Contact
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Optimizing thermo-mechanical and shape-memory properties in nanofibrous yarns through twist variation and core–shell structure
No full textConcept and development of a telemedical supervision system for anesthesiology in operating rooms using the interoperable communication standard ISO/IEEE 11073 SDC
No full textAutomation, miniaturization, and parallelization of isotopic labeling experiments for the advanced analysis of microbial systems
No full textThe generation and optimization of bioprocesses and strains for industrial application as well as the investigation of fundamental biological research hypotheses require adequate phenotyping experiments. Generally, there is a trade-off between informativeness and experimental throughput which became ever more relevant as the creation of genetic diversity and cultivation of mutant strain variants was increasingly accelerated. Isotopic labeling experiments are located at the extreme of high informativeness and low throughput with the additional limitation of significant associated costs per experiment. Commonly, they are conducted in lab-scale bioreactors, shakingflasks, and as the result of recent advances in mini-bioreactors at a scale ranging from liters to milliliters. In the present dissertation, an automated, miniaturized, and parallelized experimental setup taking advantage of modern liquid handling robots and microbioreactors is established and validated. The development of an automated quenching method for this workflow enables the analysis of labeling patterns from free amino acids and intermediates of the central carbon metabolism, even at a microliter scale. It is then embedded into an overarching integrated pipeline for isotopic labeling experiments and applied to biological case studies. In order to realize such a pipeline, multiple Python programs are constructed and most notably the open source package PeakPerformance using an innovative peak fitting approach by Bayesian inference is developed and utilized for the evaluation of chromatographic peak data. For the first application study, a novel bioprocess modelling approach for estimating intracellular metabolite pool sizes based on 13C-labeling data is developed and demonstrated in Corynebacterium glutamicum. Thereby, the pool sizes of multiple amino acids the synthesis pathways of which are branching from the glycolysis were identified with a relatively high certainty. For the second study, the first ever automated isotopically non-stationary 13C-metabolic flux analysis is conducted at an unprecedented microliter scale to elucidate the fluxome of the evolved strain C. glutamicum WT_EtOH-Evo grown on ethanol as the sole carbon source. Since no fluxome of C. glutamicum grown exclusively on ethanol had been published prior, new insight regarding the pertaining pathway usage was generated, in particular an increased glyoxylate shunt activity compared to other substrates entering the central carbon metabolism via acetyl-CoA
Konzentrationen von endogenen immunvermittelten Biomarkern in prä- und postoperativen Liquorproben bei Patienten mit degenerativer zervikaler Myelopathie
No full textIn degenerative cervical myelopathy (DCM), degenerative changes in the cervical spine lead to repetitive microtrauma to the cervical spinal cord. Prevalence rates vary widely across different studies, but overall suggest significant health-economic implications. Mechanical damage to the spinal cord induces ischemia and neuroinflammation at the molecular level. The resulting inflammatory pathways in DCM are not fully understood. Thus, the aim of this study was to compare biomarkers in cerebrospinal fluid (CSF) of DCM patients with a neurologically healthy control group to capture a characteristic spectrum of biomarkers. Ultimately, it is noted that this objective was partially achieved. Cytokines were investigated due to their suspected involvement in the pathogenesis of DCM based on pathophysiological parallels with other neuroinflammatory, neurodegenerative, and ischemic diseases. These cytokines included Eotaxin-1, several interleukins, MCP-1, MIF, RAGE, TREM-2, and YKL-40. To address the central question, a patient cohort with DCM (n=47) and a neurologically healthy control group (n=48) were recruited at the University Hospital Aachen. A structured medical history was obtained, comprehensive neurological examination conducted and clinical scores were assessed. CSF was collected from DCM patients preoperatively and three months postoperatively through lumbar puncture. CSF was collected from the neurologically healthy control cohort once via routinely placed lumbar drainages. The cytokines were analyzed using multiplex assays, a specialized form of enzyme-linked immunosorbent assay (ELISA). Statistical analysis was performed using IBM SPSS 28.0. Statistical analysis confirmed significant pathological values for the typical clinical symptoms of DCM and clinical scores in the patient group (p < 0.001). There was also a postoperative improvement of pain and daily functioning of these patients. For the biomarkers Eotaxin-1, RAGE, and TREM-2, preoperative values were significantly elevated in the DCM group (p < 0.001), while YKL-40 concentration was significantly decreased (p < 0.001). There was also a significant increase in Eotaxin-1 postoperatively (p = 0.02). In the discussion and interpretation of results, Eotaxin-1 and TREM-2 emerged as biomarkers that could be characteristic of DCM and could have prognostic and therapeutic potential
