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The highly polymorphic human cytochrome P450 2D6 enzyme is involved in the metabolism of up to 25% of all marketed drugs and accounts for significant individual differences in response to CYP2D6 substrates. Because of the differences in the multiplicity and substrate specificity of CYP2D family members among species, it is difficult to predict pathways of human CYP2D6-dependent drug metabolism on the basis of animal studies. To create animal models that reflect the human situation more closely and that allow an in vivo assessment of the consequences of differential CYP2D6 drug metabolism, we have developed a novel straightforward approach to delete the entire murine Cyp2d gene cluster and replace it with allelic variants of human CYP2D6. By using this approach, we have generated mouse lines expressing the two frequent human protein isoforms CYP2D6.1 and CYP2D6.2 and an as yet undescribed variant of this enzyme, as well as a Cyp2d cluster knockout mouse. We demonstrate that the various transgenic mouse lines cover a wide spectrum of different human CYP2D6 metabolizer phenotypes. The novel humanization strategy described here provides a robust approach for the expression of different CYP2D6 allelic variants in transgenic mice and thus can help to evaluate potential CYP2D6-dependent interindividual differences in drug response in the context of personalized medicine.
Compared with rodents and many other animal species, the human cytochrome P450 (P450) Cyp2c gene cluster varies significantly in the multiplicity of functional genes and in the substrate specificity of its enzymes. As a consequence, the use of wild-type animal models to predict the role of human CYP2C enzymes in drug metabolism and drug-drug interactions is limited. Within the human CYP2C cluster CYP2C9 is of particular importance, because it is one of the most abundant P450 enzymes in human liver, and it is involved in the metabolism of a wide variety of important drugs and environmental chemicals. To investigate the in vivo functions of cytochrome P450 Cyp2c genes and to establish a model for studying the functions of CYP2C9 in vivo, we have generated a mouse model with a deletion of the murine Cyp2c gene cluster and a corresponding humanized model expressing CYP2C9 specifically in the liver. Despite the high number of functional genes in the mouse Cyp2c cluster and the reported roles of some of these proteins in different biological processes, mice deleted for Cyp2c genes were viable and fertile but showed certain phenotypic alterations in the liver. The expression of CYP2C9 in the liver also resulted in viable animals active in the metabolism and disposition of a number of CYP2C9 substrates. These mouse lines provide a powerful tool for studying the role of Cyp2c genes and of CYP2C9 in particular in drug disposition and as a factor in drug-drug interaction.
In humans, 75% of all drugs are metabolized by the cytochrome P450-dependent monooxygenase system. Enzymes encoded by the CYP2C, CYP2D, and CYP3A gene clusters account for ∼80% of this activity. There are profound species differences in the multiplicity of cytochrome P450 enzymes, and the use of mouse models to predict pathways of drug metabolism is further complicated by overlapping substrate specificity between enzymes from different gene families. To establish the role of the hepatic and extrahepatic P450 system in drug and foreign chemical disposition, drug efficacy, and toxicity, we created a unique mouse model in which 30 cytochrome P450 genes from the Cyp2c, Cyp2d, and Cyp3a gene clusters have been deleted. Remarkably, despite a wide range of putative important endogenous functions, Cyp2c/2d/3a KO mice were viable and fertile, demonstrating that these genes have evolved primarily as detoxification enzymes. Although there was no overt phenotype, detailed examination showed Cyp2c/2d/3a KO mice had a smaller body size (15%) and larger livers (20%). Changes in hepatic morphology and a decreased blood glucose (30%) were also noted. A five-drug cocktail of cytochrome P450 isozyme probe substrates were used to evaluate changes in drug pharmacokinetics; marked changes were observed in either the pharmacokinetics or metabolites formed from Cyp2c, Cyp2d, and Cyp3a substrates, whereas the metabolism of the Cyp1a substrate caffeine was unchanged. Thus, Cyp2c/2d/3a KO mice provide a powerful model to study the in vivo role of the P450 system in drug metabolism and efficacy, as well as in chemical toxicity.
Dexamethasone (DEX) is a potent and widely used anti-inflammatory and immunosuppressant glucocorticoid. It can bind and activate the pregnane X receptor (PXR), which plays a critical role as xenobiotic sensor in mammals to induce the expression of many enzymes, including cytochromes P450 in the CYP3A family. This induction results in its own metabolism. We have used a series of transgenic mouse lines, including a novel, improved humanized PXR line, to compare the induction profile of PXR-regulated drug-metabolizing enzymes after DEX administration, as well as looking at hepatic responses to rifampicin (RIF). The new humanized PXR model has uncovered further intriguing differences between the human and mouse receptors in that RIF only induced Cyp2b10 in the new humanized model. DEX was found to be a much more potent inducer of Cyp3a proteins in wild-type mice than in mice humanized for PXR. To assess whether PXR is involved in the detoxification of DEX in the liver, we analyzed the consequences of high doses of the glucocorticoid on hepatotoxicity on different PXR genetic backgrounds. We also studied these effects in an additional mouse model in which functional mouse Cyp3a genes have been deleted. These strains exhibited different sensitivities to DEX, indicating a protective role of the PXR and CYP3A proteins against the hepatotoxicity of this compound.
Mice that have been genetically humanized for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging and promising in vivo models for an improved prediction of the pharmacokinetic, drug–drug interaction and safety characteristics of compounds in humans. The specific advantages and disadvantages of these models should be carefully considered when using them for studies in drug discovery and development. Here, an overview on the corresponding genetically humanized and chimeric liver humanized mouse models described to date is provided and illustrated with examples of their utility in drug metabolism and toxicity studies. We compare the strength and weaknesses of the two different approaches, give guidance for the selection of the appropriate model for various applications and discuss future trends and perspectives.
1. Drug metabolizing enzymes and transporters play important roles in the absorption, metabolism, tissue distribution and excretion of various compounds and their metabolites and thus can significantly affect their efficacy and safety. Furthermore, they can be involved in drug–drug interactions which can result in adverse responses, life-threatening toxicity or impaired efficacy. Significant species differences in the interaction of compounds with drug metabolizing enzymes and transporters have been described.
2. In order to overcome the limitation of animal models in accurately predicting human responses, a large variety of mouse models humanized for drug metabolizing enzymes and to a lesser extent drug transporters have been created.
3. This review summarizes the literature describing these mouse models and their key applications in studying the role of drug metabolizing enzymes and transporters in drug bioavailability, tissue distribution, clearance and drug–drug interactions as well as in human metabolite testing and risk assessment.
4. Though such humanized mouse models have certain limitations, there is great potential for their use in basic research and for testing and development of new medicines. These limitations and future potentials will be discussed.
We present a new Min-Max theorem for an optimization problem closely connected to matchings and vertex covers in balanced hypergraphs. The result generalizes Kőnig’s Theorem (Berge and Las Vergnas in Ann N Y Acad Sci 175:32–40, 1970; Fulkerson et al. in Math Progr Study 1:120–132, 1974) and Hall’s Theorem (Conforti et al. in Combinatorica 16:325–329, 1996) for balanced hypergraphs.
Biodiversity and the coexistence of species have puzzled and fascinated biologists since decades and is a hotspot in todays’ natural sciences. Preserving this biodiversity is a great challenge as habitats and environments underlying tremendous changes like climate change and the loss of natural habitats, which are mainly due to anthropogenic influences. The coexistence of numerous species even in homogeneous environments is a stunning feature of natural communities and has been summarized under the term ‘paradox of plankton’. Up to now, there are several mechanisms discussed, which may contribute to local and global diversity of organisms. Several interspecific trade offs have been identified maintaining the coexistence of species like their abilities regarding competition and predator avoidance, their capability to disperse in space and time, and their ability to exploit variable resources. Further, micro-evolutionary dynamics supporting the coexistence of species have been added to our knowledge, and deriving from theoretical deterministic models, non-linear dynamics which describe the temporal fluctuation of abundances of organisms. Whereas competition and predation seem to be clue structural elements within interacting organisms, the intrinsic dynamic behavior – by means of temporal changes in abundance - plays an important role regarding coexistence within a community. The present work sheds light on different factors affecting the coexistence of species using experimental microbial model systems consisting of a bacterivorous ciliate as the predator and two bacteria strains as prey organism. Additionally, another experimental setup consisting of two up to five bacteria species competing for one limiting resource was investigated. Highly controllable chemostat systems were established to exclude extrinsic disturbances. According to theoretical analyses I was able to show - experimentally and theoretically - that phenotypic plasticity of one species within a microbial one-predator-two-prey food web enlarges the range of possible coexistence of all species under different dynamic conditions, compared to a food web without phenotypic plasticity. This was accompanied by non-linear (chaotic) population dynamics within all experimental systems showing phenotypic plasticity. The experiments on the interplay of competition, predation and invasion showed that all aspects have an influence on species coexistence. Under undisturbed controlled conditions all aspects were analyzed in detail and in combination. Populations showed oscillations which were shown by quasi-chaotic attractors in phase space diagrams. Competition experiments with two up to five bacteria species competing for one limiting resource showed that all organisms were able to coexist which was mediated by species oscillations entering a regime of chaos. Besides that fact it was found, that the productivity (biomass) as well as the total cell numbers – under the same nutrition supply – increased by an increasing number of species in the experimental systems. Up to now, the occurrence of non-linear dynamics in well controlled experimental studies has been recognized several times and this phenomenon seemed to be more common in natural systems than generally assumed.
In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog’s forward-search DT planning algorithm, these formulas are evaluated in order to find the agent’s optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.
In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human–robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents.