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- Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie (8)
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (2)
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg (2)
- Anthropology Department University of Tennessee, Knoxville (1)
- Carl-Ludwig-Institut für Physiologie, Universität Leipzig (1)
- Chair of Experimental Biomedicine I (1)
- Deutsches Zentrum für Luft- und Raumfahrt (DLR) (1)
- EMBL Heidelberg (1)
- Evangelisches Studienwerk e.V. (1)
- Fachgebiet für Populationsgenomik bei Nutztieren, Universität Hohenheim (1)
- Forschungsverbund ForChange des Bayrischen Kultusministeriums (1)
Plexus injury often occurs after motor vehicle accidents and results in lifelong disability with severe neuropathic pain. Surgical treatment can partially restore motor functions, but sensory loss and neuropathic pain persist. Regenerative medicine concepts, such as cell replacement therapies for restoring dorsal root ganglia (DRG) function, set high expectations. However, up to now, it is unclear which DRG cell types are affected by nerve injury and can be targeted in regenerative medicine approaches.
This study followed the hypothesis that satellite glial cells (SGCs) might be a suitable endogenous cell source for regenerative medicine concepts in the DRG. SGCs originate from the same neural crest-derived cell lineage as sensory neurons, making them attractive for neural repair strategies in the peripheral nervous system. Our hypothesis was investigated on three levels of experimentation. First, we asked whether adult SGCs have the potential of sensory neuron precursors and can be reprogrammed into sensory neurons in vitro. We found that adult mouse DRG harbor SGC-like cells that can still dedifferentiate into progenitor-like cells. Surprisingly, expression of the early developmental transcription factors Neurog1 and Neurog2 was sufficient to induce neuronal and glial cell phenotypes. In the presence of nerve growth factor, induced neurons developed a nociceptor-like phenotype expressing functional nociceptor markers, such as the ion channels TrpA1, TrpV1 and NaV1.9. In a second set of experiments, we used a rat model for peripheral nerve injury to look for changes in the DRG cell composition. Using an unbiased deep learning-based approach for cell analysis, we found that cellular plasticity responses after nerve injury activate SGCs in the whole DRG. However, neither injury-induced neuronal death nor gliosis was observed. Finally, we asked whether a severe nerve injury changed the cell composition in the human DRG. For this, a cohort of 13 patients with brachial plexus injury was investigated. Surprisingly, in about half of all patients, the injury-affected DRG showed no characteristic DRG tissue. The complete entity of neurons, satellite cells, and axons was lost and fully replaced by mesodermal/connective tissue. In the other half of the patients, the basic cellular entity of the DRG was well preserved. Objective deep learning-based analysis of large-scale bioimages of the “intact” DRG showed no loss of neurons and no signs of gliosis.
This study suggests that concepts for regenerative medicine for restoring DRG function need at least two translational research directions: reafferentation of existing DRG units or full replacement of the entire multicellular DRG structure. For DRG replacement, SGCs of the adult DRG are an attractive endogenous cell source, as the multicellular DRG units could possibly be rebuilt by transdifferentiating neural crest-derived sensory progenitor cells into peripheral sensory neurons and glial cells using Neurog1 and Neurog2.
A closer look at long-established drugs: enantioselective protein binding and stability studies
(2023)
The aim of this work was to investigate older, established drugs. The extent of the protein binding of chiral ephedra alkaloids to AGP and of ketamine to albumin was determined. Since enantiomers of these drugs are individual available, the focus was on possible enantioselective binding and structural moieties involved in the binding.
Previously published work suggested that ephedrine and pseudoephedrine can bind stereoselectively to proteins other than albumin in serum. For the determination of the extent of protein binding, the established ultrafiltration with subsequent chiral CE analysis was used. To determine the influence of basicity on binding, the drugs methylephedrine and norephedrine were also analyzed. Drug binding to AGP increased with increasing basicity as follows: norephedrine < methylephedrine < ephedrine < pseudoephedrine. pKaff was determined both graphically using the Klotz plot and mathematical indicating a low affinity of the ephedra alkaloids to AGP. Using STD-NMR spectroscopy experiments the aromatic protons and the C-CH3 side chain were shown to be most strongly involved in binding, which could be confirmed by molecular docking experiments in more detail. For all drugs, van der Waals-, π π , cationic interactions, hydrogen bonds, and a formation of a salt bridge were observed. The individual enantiomers showed no significant differences and thus the binding of ephedra alkaloids to AGP is not significant.
In contrast to the ephedra alkaloids, the possible enantioselective binding to albumin was investigated for R and S ketamine. Again, ultrafiltration followed by CE analysis was performed. The binding of ketamine to one main binding site could be identified. A non-linear fit was used for the determination of pKaff. Using the NMR methods STD-NMR, waterLOGSY-NMR, and CPMG-NMRspectroscopy: the aromatic protons as well as the protons of the NCH3 methyl group showed the largest signal intensity changes, while the cyclohexanone protons showed the smallest changes. pKaff was also determined by the change in the chemical shift at different drug-protein ratios. These obtained values confirm the values obtained from ultrafiltration. Based on this, ketamine is classified as a low-affinity ligand to albumin. There were no significant differences between the individual enantiomers and thus the binding of ketamine to albumin is not a stereoselective process.
Using statistical design of experiments an efficient chiral CE method for determining the extent of protein binding of R and S ketamine to albumin was developed and validated according to ICH Q2 (R1) guideline.
The stability of ketamine was also investigated because a yellowish discoloration of an aqueous solution of ketamine developed under heat. XRPD investigations showed the same crystal structure for all batches examined. An untargeted screening using LC HRMS as well as LC UV measurements showed no degradation of ketamine or the presence of impurities in stress and non-stressed ketamine solutions, confirming the stability of ketamine under the stress conditions investigated. The lower the quality of the water used in the stress tests, the more intense the yellow discoloration occurred. The impurity or the mechanism that causes the yellow discoloration could not be identified.
This work deals with the acceleration of cardiovascular MRI for the assessment
of functional information in steady-state contrast and for viability assessment
during the inversion recovery of the magnetization. Two approaches
are introduced and discussed in detail. MOCO-MAP uses an exponential
model to recover dynamic image data, IR-CRISPI, with its low-rank plus
sparse reconstruction, is related to compressed sensing.
MOCO-MAP is a successor to model-based acceleration of parametermapping
(MAP) for the application in the myocardial region. To this end, it
was augmented with a motion correction (MOCO) step to allow exponential
fitting the signal of a still object in temporal direction. Iteratively, this
introduction of prior physical knowledge together with the enforcement of
consistency with the measured data can be used to reconstruct an image
series from distinctly shorter sampling time than the standard exam (< 3 s
opposed to about 10 s). Results show feasibility of the method as well as
detectability of delayed enhancement in the myocardium, but also significant
discrepancies when imaging cardiac function and artifacts caused already by
minor inaccuracy of the motion correction.
IR-CRISPI was developed from CRISPI, which is a real-time protocol
specifically designed for functional evaluation of image data in steady-state
contrast. With a reconstruction based on the separate calculation of low-rank
and sparse part, it employs a softer constraint than the strict exponential
model, which was possible due to sufficient temporal sampling density via
spiral acquisition. The low-rank plus sparse reconstruction is fit for the use on
dynamic and on inversion recovery data. Thus, motion correction is rendered
unnecessary with it.
IR-CRISPI was equipped with noise suppression via spatial wavelet filtering.
A study comprising 10 patients with cardiac disease show medical
applicability. A comparison with performed traditional reference exams offer
insight into diagnostic benefits. Especially regarding patients with difficulty
to hold their breath, the real-time manner of the IR-CRISPI acquisition provides
a valuable alternative and an increase in robustness.
In conclusion, especially with IR-CRISPI in free breathing, a major acceleration
of the cardiovascular MR exam could be realized. In an acquisition
of less than 100 s, it not only includes the information of two traditional
protocols (cine and LGE), which take up more than 9.6 min, but also allows
adjustment of TI in retrospect and yields lower artifact level with similar
image quality.
Mammalian embryonic development is subject to complex biological relationships that need to be understood. However, before the whole structure of development can be put together, the individual building blocks must first be understood in more detail. One of these building blocks is the second cell fate decision and describes the differentiation of cells of the inner cell mass of the embryo into epiblast and primitive endoderm cells. These cells then spatially segregate and form the subsequent bases for the embryo and yolk sac, respectively. In organoids of the inner cell mass, these two types of progenitor cells are also observed to form, and to some extent to spatially separate. This work has been devoted to these phenomena over the past three years. Plenty of studies already provide some insights into the basic mechanics of this cell differentiation, such that the first signs of epiblast and primitive endoderm differentiation, are the expression levels of transcription factors NANOG and GATA6. Here, cells with low expression of GATA6 and high expression of NANOG adopt the epiblast fate. If the expressions are reversed, a primitive endoderm cell is formed. Regarding the spatial segregation of the two cell types, it is not yet clear what mechanism leads to this. A common hypothesis suggests the differential adhesion of cell as the cause for the spatial rearrangement of cells. In this thesis however, the possibility of a global cell-cell communication is investigated. The approach chosen to study these phenomena follows the motto "mathematics is biology's next microscope". Mathematical modeling is used to transform the central gene regulatory network at the heart of this work into a system of equations that allows us to describe the temporal evolution of NANOG and GATA6 under the influence of an external signal. Special attention is paid to the derivation of new models using methods of statistical mechanics, as well as the comparison with existing models. After a detailed stability analysis the advantages of the derived model become clear by the fact that an exact relationship of the model parameters and the formation of heterogeneous mixtures of two cell types was found. Thus, the model can be easily controlled and the proportions of the resulting cell types can be estimated in advance. This mathematical model is also combined with a mechanism for global cell-cell communication, as well as a model for the growth of an organoid. It is shown that the global cell-cell communication is able to unify the formation of checkerboard patterns as well as engulfing patterns based on differently propagating signals. In addition, the influence of cell division and thus organoid growth on pattern formation is studied in detail. It is shown that this is able to contribute to the formation of clusters and, as a consequence, to breathe some randomness into otherwise perfectly sorted patterns.
Aging is known to be a risk factor for structural abnormalities and functional decline in the nervous system. Characterizing age-related changes is important to identify putative pathways to overcome deleterious effects and improve life quality for the elderly. In this study, the peripheral nervous system of 24-month-old aged C57BL/6 mice has been investigated and compared to 12-month-old adult mice. Aged mice showed pathological alterations in their peripheral nerves similar to nerve biopsies from elderly human individuals, with nerve fibers showing demyelination and axonal damage. Such changes were lacking in nerves of adult 12-month-old mice and adult, non-aged humans. Moreover, neuromuscular junctions of 24-month-old mice showed increased denervation compared to adult mice. These alterations were accompanied by elevated numbers of macrophages in the peripheral nerves of aged mice. The neuroinflammatory conditions were associated with impaired myelin integrity and with a decline of nerve conduction properties and muscle strength in aged mice.
To determine the pathological impact of macrophages in the aging mice, macrophage depletion was performed in mice by oral administration of CSF-1R specific kinase (c-FMS) inhibitor PLX5622 (300 mg/kg body weight), which reduced the number of macrophages in the peripheral nerves by 70%. The treated mice showed attenuated demyelination, less muscle denervation and preserved muscle strength. This indicates that macrophage-driven inflammation in the peripheral nerves is partially responsible for the age-related neuropathy in mice.
Based on previous observations that systemic inflammation can accelerate disease progression in mouse models of neurodegenerative diseases, it was hypothesized that systemic inflammation can exacerbate the peripheral neuropathy found in aged mice. To investigate this hypothesis, aged C57BL/6 mice were intraperitoneally injected with a single dose of lipopolysaccharide (LPS; 500 μg/kg body weight) to induce systemic inflammation by mimicking bacterial infection, mostly via activation of Toll-like receptors (TLRs). Altered endoneurial macrophage activation, highlighted by Trem2 downregulation, was found in LPS injected aged mice one month after injection. This was accompanied by a so far rarely observed form of axonal perturbation, i.e., the occurrence of “dark axons” characterized by a damaged cytoskeleton and an increased overall electron density of the axoplasm. At the same time, however, LPS injection reduced demyelination and muscle denervation in aged mice. Interestingly, TREM2 deficiency in aged mice led to similar changes to LPS injection. This suggests that LPS injection likely mitigates aging-related demyelination and muscle denervation via Trem2 downregulation.
Taken together, this study reveals the role of macrophage-driven inflammation as a pathogenic mediator in age-related peripheral neuropathy, and that targeting macrophages might be an option to mitigate peripheral neuropathies in aging individuals. Furthermore, this study shows that systemic inflammation may be an ambivalent modifier of age-related nerve damage, leading to a distinct type of axonal perturbation, but in addition to functionally counteracting, dampened demyelination and muscle denervation. Translationally, it is plausible to assume that tipping the balance of macrophage polarization to one direction or the other may determine the functional outcome in the aging peripheral nervous system of the elderly.
Recent computing advances are driving the integration of artificial intelligence (AI)-based systems into nearly every facet of our daily lives. To this end, AI is becoming a frontier for enabling algorithmic decision-making by mimicking or even surpassing human intelligence. Thereupon, these AI-based systems can function as decision support systems (DSSs) that assist experts in high-stakes use cases where human lives are at risk. All that glitters is not gold, due to the accompanying complexity of the underlying machine learning (ML) models, which apply mathematical and statistical algorithms to autonomously derive nonlinear decision knowledge. One particular subclass of ML models, called deep learning models, accomplishes unsurpassed performance, with the drawback that these models are no longer explainable to humans. This divergence may result in an end-user’s unwillingness to utilize this type of AI-based DSS, thus diminishing the end-user’s system acceptance.
Hence, the explainable AI (XAI) research stream has gained momentum, as it develops techniques to unravel this black-box while maintaining system performance. Non-surprisingly, these XAI techniques become necessary for justifying, evaluating, improving, or managing the utilization of AI-based DSSs. This yields a plethora of explanation techniques, creating an XAI jungle from which end-users must choose. In turn, these techniques are preliminarily engineered by developers for developers without ensuring an actual end-user fit. Thus, it renders unknown how an end-user’s mental model behaves when encountering such explanation techniques.
For this purpose, this cumulative thesis seeks to address this research deficiency by investigating end-user perceptions when encountering intrinsic ML and post-hoc XAI explanations. Drawing on this, the findings are synthesized into design knowledge to enable the deployment of XAI-based DSSs in practice. To this end, this thesis comprises six research contributions that follow the iterative and alternating interplay between behavioral science and design science research employed in information systems (IS) research and thus contribute to the overall research objectives as follows: First, an in-depth study of the impact of transparency and (initial) trust on end-user acceptance is conducted by extending and validating the unified theory of acceptance and use of technology model. This study indicates both factors’ strong but indirect effects on system acceptance, validating further research incentives. In particular, this thesis focuses on the overarching concept of transparency. Herein, a systematization in the form of a taxonomy and pattern analysis of existing user-centered XAI studies is derived to structure and guide future research endeavors, which enables the empirical investigation of the theoretical trade-off between performance and explainability in intrinsic ML algorithms, yielding a less gradual trade-off, fragmented into three explainability groups. This includes an empirical investigation on end-users’ perceived explainability of post-hoc explanation types, with local explanation types performing best. Furthermore, an empirical investigation emphasizes the correlation between comprehensibility and explainability, indicating almost significant (with outliers) results for the assumed correlation. The final empirical investigation aims at researching XAI explanation types on end-user cognitive load and the effect of cognitive load on end-user task performance and task time, which also positions local explanation types as best and demonstrates the correlations between cognitive load and task performance and, moreover, between cognitive load and task time. Finally, the last research paper utilizes i.a. the obtained knowledge and derives a nascent design theory for XAI-based DSSs. This design theory encompasses (meta-) design requirements, design principles, and design features in a domain-independent and interdisciplinary fashion, including end-users and developers as potential user groups. This design theory is ultimately tested through a real-world instantiation in a high-stakes maintenance scenario.
From an IS research perspective, this cumulative thesis addresses the lack of research on perception and design knowledge for an ensured utilization of XAI-based DSS. This lays the foundation for future research to obtain a holistic understanding of end-users’ heuristic behaviors during decision-making to facilitate the acceptance of XAI-based DSSs in operational practice.
Glioblastoma (GB) is the most aggressive malignant adult brain tumour with a median survival rate of only 15 months. GB tumours are characterized by necrotic and hypoxic core, which leads to nutrient deficient areas contributing to invasive, diffuseinfiltrative and angiogenic nature of these tumours. Cells exposed to nutrient deficient conditions and are known to reprogram their metabolism to produce or procure macro molecules from their environment. This makes cancer cells uniquely dependent on transcriptional regulators and a window of opportunity to target them. Sterol regulatory element binding protein 1 (SREBP1) is a transcriptional regulator of de-novo fatty acid synthesis in cells. The aim of this thesis was to investigate if SREBP1 was involved in restructuring the transcriptional regulation of genes involved in fatty acid biosynthesis upon low serum condition, in mediating interaction with other cell types in the tumour bulk such as endothelial cells, in regulating cancer stem like cells and finally to study its upstream regulation in GB. Global transcriptional analysis on GB cells exposed to low serum conditions revealed that SREBP1 regulated several fatty acid biosynthesis and phospholipid metabolic processes. PLA2G3 was identified as a novel target of SREBP1 in GB that was uniquely regulated in low serum condition. Analysis of total fatty acid and lipid species revealed that loss of SREBP1 in low serum condition changes the proportion of saturated, MUFAs and PUFAs. These changes were not specific to loss of PLA2G3 but as a result of downregulation of many genes regulated by SREBP1 in the fatty acid biosynthetic pathway. Next, treatment of HUVEC’s (endothelial cells) with condition medium from SREBP1-silenced U87 cells inhibited sprouting and tube formation capacity compared to the control condition, emphasizing the role of SREBP1 in angiogenesis and release of signalling mediators. Further, SREBP1 was shown to be important for proliferation of patient derived stem like cells and becomes indispensable for forming neurospheres in long term cultures, indicating its role in maintaining stemness. Also, inhibition of SREBP function by blocking the esterification of cholesterol using inhibitors targeting SOAT1 showed impairment in the viability of GB cells exposed to serum-depleted condition. Overall, SREBP1 plays an important role in maintaining tumour growth in nutrient deficient conditions and help in interaction with tumour microenvironment contributing to the aggressiveness of this tumour and poses itself as an attractive and unique target for GB treatment
In all the projects presented, it is evident that the selection of suitable separation conditions is only one side of the coin. Equally crucial in the development of methods for the quality assessment of APIs/drugs is the right detection system.
The application of CAD as an alternative to UV detection at low wavelength of the two weak chromophore main degradation products of the very polar, zwitterionic API carbocisteine requires the volatility of the mobile phase. Therefore, as a substitute for the non-volatile ion pairing reagent tetrabutylammonium hydroxide (TBAOH), six different volatile alkylamines as well as a RP/SAX mixed-mode column were evaluated. The best selectivity and separation performance comparable to TBAOH was achieved with the RP/SAX column and a mixture of formic acid and trifluoroacetic acid. For the simultaneous optimisation of the evaporation temperature of the CAD as a function of two chromatographic parameters, a central composite design was chosen and the “desirability function” was subsequently applied for modelling. In addition, column bleeding was investigated with a second RP/SAX column (different batch) with the result that the acetonitrile percentage had to be adjusted and preconditioning by injection of concentrated samples is essential. The final mixed-mode method was finally validated with both columns according to the ICH Q2 (R1) guideline.
Based on this, an MS-compatible method was developed with little effort using an identical RP/SAX column in UPLC dimension for the untargeted analysis by HRMS of two carbocisteine-containing prototype syrup formulations. For a comprehensive characterisation, HRMS and MS/HRMS data were recorded simultaneously by information dependent acquisition mode. Based on the exact masses, isotope patterns and an in silico plausibility check of the fragment spectra, the prediction of the structures of the unknown impurities was possible. In both syrup samples, which had been stored for nine months at 40 °C and 75 % r.h., two additional impurities of carbocisteine (i.e. lactam of the sulfoxides and disulphide between cysteine and thioglycolic acid) were identified by comparison with the corresponding prototype placebo samples using general unknown comparative screening. In addition, the formation of Maillard products by binary mixtures with 13C-labelled sugars was revealed in the sucrose-containing formulation.
For the promising hyphenation of the UV detector with the CAD for the simultaneous detection of all UV-active impurities of the cholesterol-lowering drug simvastatin and the only weak chromophore dihydrosimvastatin, the Ph. Eur. method had to be adapted. Besides replacing phosphoric acid with trifluoroacetic acid, the gradient also had to be adjusted and a third critical peak pair was observed. Based on validation experiments (according to the ICH Q2 (R1) guideline), the suitability of the CAD for sensitive detection (LOQ = 0.0175 % m/m) was proven.
To further investigate the robustness of the adapted method and CAD, a Plackett-Burman design was chosen. None of the factors had a statistically significant effect on the S/N of the CAD in the ranges tested. Regarding the three critical peak pairs, on the other hand, the factors to be controlled were statistically established, so that a targeted correction is possible if the system suitability test is not passed. The idea of employing a hyphenated UV-CAD system was finally applied to the structurally closely related lovastatin and its specified impurity dihydrolovastatin. Here, the CAD showed a significantly better S/N compared to the compendial UV detection at 200 nm.
The suitability of CAD for the analysis of non-volatile fatty acids in polysorbate 80 (PS80) as favourable alternative to the Ph. Eur. GC method (no time-consuming, error-prone and toxic derivatisation) has already been demonstrated. The aim of this project was therefore to develop a robust method with a focus on the AQbD principles, which can be used for the analysis of other excipients with similar fatty acid composition. After the definition of the analytical target profile and a risk assessment by means of an Ishikawa diagram, a suitable C18 column and the chromatographic framework conditions (formic acid concentration and initial/final gradient conditions) were selected after only few preliminary runs. The remaining critical method parameters were then investigated with the help of DoE and RSM. Using the obtained model equations, Monte Carlo simulations were performed to create the method operable design region as a region of theoretical robustness. After validation according to ICH Q2 (R1), the fatty acid composition of a magnesium stearate batch was successfully analysed as a further application example in addition to PS80.
The CAD was able to prove its potential in all the issues investigated in the context of this doctoral thesis. As a cost-effective alternative compared to MS instruments, it thus closes a gap in the quality assessment of APIs or excipients without a suitable chromophore. The easy method transfer to (HR)MS instruments also allows for a unique degree of sample characterisation through untargeted approaches in case of new impurities. For resource- and time-efficient work, the possibilities and limitations of software tools for method development and data evaluation as well as the application of risk-based approaches such as AQbD should also be considered.
Dietary fatty acids serve as objective biomarkers for the estimation of habitual diet mainly because biomarkers are free of memory bias or inaccuracies of food databases. The aim of the present work encompassed the implementation of a gas chromatographical method coupled with a mass spectrometrical and flame-ionization detector for analysis of fatty acid biomarkers in human biospecimens, their analytical determination and statistical evaluation in two different study populations and different biospecimens as well as the elaboration of adverse reactions to food ingredients with special focus on food allergies and food intolerances in the context of a possible implementation into an application for consumer health. The first aim was the identification of potential influence of fatty acid biomarkers on desaturase and elongase indexes (Δ9DI, Δ6DI, Δ5DI and ELOVLI5), which are factors in type 2 diabetes risk, in breast adipose tissue from healthy women. Influence of further variables on respective indexes was also investigated. 40 samples were investigated and potential variables were either collected by questionnaire or determined. Principle component analysis was applied for fatty acid biomarkers (PCdiet1, PCdiet2 and PCdiet3 representative for the dietary intake of vegetable oils/nuts, fish and partially hydrogenated vegetable oils), endogenous estrogens (PCE1) and oxysterols (PCOxy1). Multiple linear regression models were applied. Δ9DI and Δ6DI were influenced non-significantly and significantly negatively by PCdiet2 supporting a putative beneficial effect of vegetable oils and nuts on type 2 diabetes risk factors. ELOVLI5 and Δ5DI were influenced significantly and non-significantly positively by PCdiet1 supporting a putative beneficial effect of fish consumption on type 2 diabetes risk factors. On the other hand, PCdiet1 also significantly and non-significantly positively influenced Δ9DI and Δ6DI supporting a putative adverse effect of fish biomarkers on type 2 diabetes risk factors. The opposing influences of PCdiet1 suggesting an ambivalent role of dietary intake of fish on investigated indexes. Δ6DI was significantly positively influenced by PCdiet3 and number of pregnancies supporting a putative adverse effect of partially hydrogenated vegetable oils and pregnancies on type 2 diabetes risk factors. Lifestyle factors like smoking significantly and non-significantly influenced Δ9DI and Δ6DI putatively adversely. Δ5DI was influenced significantly positively by estrogen active drugs suggesting a putative beneficial effect on type 2 diabetes risk factors. It must be considered that a variation coefficient of up to 0.44 only explained 44% of variance of the respective indexes, suggesting other influencing factors might play a role. The second aim was the implementation of a gas chromatographical method coupled with a mass spectrometrical and flame-ionization detector for analysis of fatty acid biomarkers in human biospecimens. The method was optimized for separation and detection of 40 fatty acids. Mean recovery for tridecanoic acid was x(tridecanoic acid) = 90.51% and for nonadecanoic acid x(nonadecanoic acid) = 96.21%. Thus, there was no significant loss of fatty acids with shorter and longer carbon chains over the extraction process to be expected. Limit of detections were calculated in adipose tissue samples and ranged from 0.007 to 0.077% of the proportion of the respective fatty acid to total fatty acids. The third aim was the investigation if differentiation between breast glandular and adipose tissue had a relevant impact on the analysis of dietary fatty acid biomarkers or if contamination of breast glandular with breast adipose tissue and vice versa was neglectable for the analysis of dietary fatty acid biomarkers. No statistical significant differences were observed for all investigated fatty acid biomarkers (pentadecanoic-, heptadecanoic-, trans palmitoleic-, eicosapentaenoic-, docosahexaenoic-, linoleic and α-linolenic acid) between breast glandular and adipose tissue. Thus, differentiation between breast glandular and adipose tissue seems not to be necessary for the analysis of fatty acids serving as biomarkers for the intake of specific food groups. Potential influence of mixed breast tissue on fatty acid biomarkers analysis seems to be neglectable. The fourth aim was the determination of fatty acid biomarkers in adipose tissue in another study population from healthy participants. 27 adipose tissue samples were analyzed. Milk and ruminant fat biomarkers exhibited proportions of 0.47% for pentadecanoic acid, 0.34% for heptadecanoic acid and 0.25% for trans palmitoleic acid. Fish fatty acid biomarkers revealed proportions of 0.034% for eicosapentaenoic acid and 0.061% for docosahexaenoic acid. The mean proportion of vegetable oils and nuts biomarkers were 9.58% for linoleic acid and 0.48% for α-linolenic acid in all adipose tissues. Principle component analysis was applied for the fatty acid biomarkers to provide objective markers of habitual diet for this study population. PCdiet1 was mainly characterized by pentadecanoic acid, heptadecanoic acid and trans palmitoleic acid and therefore served as a principle component for the dietary intake of milk and ruminant fat. PCdiet2 and PCdiet3 only exhibited pattern for ω3 and ω6 fatty acids but not for dietary intake of specific food groups and could therefore not used as objective marker. PCdiet1, 2 and 3 explained 82.76% of variance. The last aim of this thesis was the elaboration of adverse reactions to food ingredients with special focus on food allergies and food intolerances in the context of a possible implementation into an application for consumer health. Scientific information on adverse reactions to food ingredients and trigger substances was provided in this thesis and possible implementation strategies were evaluated. For food allergens, which have regulatory requirements in the context of labelling, a strategy was elaborated, where it is necessary to provide information on the list of ingredients, the nexus ’contain’ and the respective food allergen as well as information on the name of the product. For food intolerances, which do not have regulatory requirements, limits were shown in the context of the application. If the elaborated food intolerances shall be implemented into the application, a professional dietary concept has to be developed for every food intolerance because of the complexity of the implementation.
In this thesis, we are interested in numerically preserving stationary solutions of balance laws. We start by developing finite volume well-balanced schemes for the system of Euler equations and the system of MHD equations with gravitational source term. Since fluid models and kinetic models are related, this leads us to investigate AP schemes for kinetic equations and their ability to preserve stationary solutions. Kinetic models typically have a stiff term, thus AP schemes are needed to capture good solutions of the model. For such kinetic models, equilibrium solutions are reached after large time. Thus we need a new technique to numerically preserve stationary solutions for AP schemes. We find a criterion for SP schemes for kinetic equations which states, that AP schemes under a particular discretization are also SP. In an attempt to mimic our result for kinetic equations in the context of fluid models, for the isentropic Euler equations we developed an AP scheme in the limit of the Mach number going to zero. Our AP scheme is proven to have a SP property under the condition that the pressure is a function of the density and the latter is obtained as a solution of an elliptic equation. The properties of the schemes we developed and its criteria are validated numerically by various test cases from the literature.