Retrospektive Analyse der Lateralität von Hauttumoren an einer saarländischen Kohorte

Die Lateralität der Hauttumore bzw. die signifikante Ungleichverteilung dieser Tumore stellt ein in letzter Zeit vermehrt untersuchtes Phänomen dar. Nachdem dieses bereits in amerikanischen, sowie in Multicenter- Studien für einzelne Tumore betrachtet wurde, beschäftigt sich diese Studie mit der Lateralität der Hauttumore an einer saarländischen Kohorte. Hierzu wurden insgesamt 441 Hauttumore von Patienten der Klinik für Dermatologie und Venerologie des Universitätsklinikums des Saarlandes hinsichtlich ihrer Lateralität, sowie genauen Lokalisation untersucht. Die Studie schloss dazu 293 maligne Hauttumore ein. Als eine Kontrollgruppe fungierten 148 benigne Tumore. Die malignen Tumore konnten in Merkelzellkarzinome, Plattenepithelkarzinome, maligne Melanome und Sarkome unterteilt werden. Des Weiteren konnten die malignen Melanome noch in die Untergruppen des superfiziell spreitenden-, des akrolentiginösen- und des nodulären malignen Melanoms untergliedert werden. Die Auswertung der Ergebnisse erfolgte über Chi-Quadrat-Test, bei ordinalskalierten Daten wurde der Kruskal-Wallis bzw. der Man-Witney-U-Test verwendet. Für die benignen Tumore konnte in der Auswertung keine Präferenz für eine Körperlateralität bzw. einvermehrtes Auftreten an einer bestimmten Körperstelle festgestellt werden. Sowohl die MCCs als auchdie Plattenepithelkarzinome zeigten eine signifikante linksseitige Häufung, bei den PECAs konnte diese Häufung weiterhin vermehrt auf UV-expositionierter Haut nachgewiesen werden. Für die Melanome ergab sich keine signifikante Ungleichverteilung in ihrer Lateralität und nur das nodulär maligne Melanom zeigte hierbei überhaupt eine linksseitige Tendenz. Auch für die Sarkome fand sich kein signifikant vermehrt linksseitiges Auftreten, es konnte lediglich eine linksseitige Tendenz gefunden werden. Die genauen Gründe für diesen Trend bleiben bis zu diesem Zeitpunkt unbekannt. Die oft angeführte Hypothese, dass dieses Phänomen durch eine ungleiche UV-Bestrahlung während des Autofahrens hervorgerufen wird, ist allerdings anzuzweifeln. Eine embryologische Hypothese, die sichauf die ungleiche Verteilung der Zellen während der Entwicklung beruft, scheint zur Zeit plausibler zu sein. Für die abschließende Klärung sind allerdings weitere Studien angezeigt.The laterality of skin tumors or rather the significantly disproportionate appearance of skin tumors on one side of the body, is a phenomenon that has gotten more attention in recent years. After this phenomenon had already been described for various tumors by american-, as well as other multicenter studies, this study aims to examine the laterality of skin tumors on a cohort comprised of participants of the german region of the Saarland. For this purpose 441 skin tumors from patients of the department for dermatology and venerology of the Saarland university clinical center were examined for their laterality and exact location on the body. This study included 293 malign skin tumors, as well as 148 benign tumors, that acted as a control group. The malign tumors included merkelcellcarzinom, squamous cell carcinoma, malignant melanoma and sarcoma of the skin. Malignant melanomas were further subdivided into superficially spreading-, acrolentigular- and nodular malignant melanoma. Statistical analysis of the acquired data was done by using chi-square test or Kruskal-Wallis/Man-Whitney-U test for ordinally scaled variables. No preference for any side or location on the body could be found for the benigne skin tumors. For the merkelcellcarcinomas as well as for the squamous cell carcinomas a statistically significant left-sided excess could be found. Squamous cell carcinoma furthermore showed this excess on chronically UV-exposed skin. This left sides excess however could not be found in the malignant melanoma. Here only the nodular melanoma even showed a left-sided trend. The same was found for sarcomas where no significant left sided excess could be found, only a left sided trend was observed. At this point in time, it is not yet clear what causes this tendency for skin tumors to appear on the left more often than on the right side of the body. The often stated hypothesis that this phenomenon is caused by unequal exposure to UV-radiation while driving remains unsatisfactory and has slowly been abandoned in recent years. An embyolocical explanation, that focusses on the uneven distributionof cells during development is, at this time, more likely to be the cause of the phenomenon. For a conclusive answer however more studies will have to be conducted

De Asyndeti natura et apud Aeschylum usu

tradidit auctor Gustavus BromigZugl.: Göttingen, Univ., Phil. Diss., 187

Wie kann das Gymnasium den Sinn für Kunst wecken?

von Gustav BromigProgr.-Nr. 74

Vergleichung der Komödien Aulularia des Plautus und l'Avare des Molière

von Oberlehrer BromigIn Fraktu

Accelerated Adaptive Laboratory Evolution by Automated Repeated Batch Processes in Parallelized Bioreactors

Adaptive laboratory evolution (ALE) is a valuable complementary tool for modern strain development. Insights from ALE experiments enable the improvement of microbial cell factories regarding the growth rate and substrate utilization, among others. Most ALE experiments are conducted by serial passaging, a method that involves large amounts of repetitive manual labor and comes with inherent experimental design flaws. The acquisition of meaningful and reliable process data is a burdensome task and is often undervalued and neglected, but also unfeasible in shake flask experiments due to technical limitations. Some of these limitations are alleviated by emerging automated ALE methods on the μL and mL scale. A novel approach to conducting ALE experiments is described that is faster and more efficient than previously used methods. The conventional shake flask approach was translated to a parallelized, L scale stirred-tank bioreactor system that runs controlled, automated, repeated batch processes. The method was validated with a growth optimization experiment of E. coli K-12 MG1655 grown with glycerol minimal media as a benchmark. Off-gas analysis enables the continuous estimation of the biomass concentration and growth rate using a black-box model based on first principles (soft sensor). The proposed method led to the same stable growth rates of E. coli with the non-native carbon source glycerol 9.4 times faster than the traditional manual approach with serial passaging in uncontrolled shake flasks and 3.6 times faster than an automated approach on the mL scale. Furthermore, it is shown that the cumulative number of cell divisions (CCD) alone is not a suitable timescale for measuring and comparing evolutionary progress

Understanding biochemical design principles with ensembles of canonical non-linear models.

Systems biology applies concepts from engineering in order to understand biological networks. If such an understanding was complete, biologists would be able to design ad hoc biochemical components tailored for different purposes, which is the goal of synthetic biology. Needless to say that we are far away from creating biological subsystems as intricate and precise as those found in nature, but mathematical models and high throughput techniques have brought us a long way in this direction. One of the difficulties that still needs to be overcome is finding the right values for model parameters and dealing with uncertainty, which is proving to be an extremely difficult task. In this work, we take advantage of ensemble modeling techniques, where a large number of models with different parameter values are formulated and then tested according to some performance criteria. By finding features shared by successful models, the role of different components and the synergies between them can be better understood. We will address some of the difficulties often faced by ensemble modeling approaches, such as the need to sample a space whose size grows exponentially with the number of parameters, and establishing useful selection criteria. Some methods will be shown to reduce the predictions from many models into a set of understandable "design principles" that can guide us to improve or manufacture a biochemical network. Our proposed framework formulates models within standard formalisms in order to integrate information from different sources and minimize the dimension of the parameter space. Additionally, the mathematical properties of the formalism enable a partition of the parameter space into independent subspaces. Each of these subspaces can be paired with a set of criteria that depend exclusively on it, thus allowing a separate sampling/screening in spaces of lower dimension. By applying tests in a strict order where computationally cheaper tests are applied first to each subspace and applying computationally expensive tests to the remaining subset thereafter, the use of resources is optimized and a larger number of models can be examined. This can be compared to a complex database query where the order of the requests can make a huge difference in the processing time. The method will be illustrated by analyzing a classical model of a metabolic pathway with end-product inhibition. Even for such a simple model, the method provides novel insight

Control of parallelized bioreactors II: probabilistic quantification of carboxylic acid reductase activity for bioprocess optimization

Autonomously operated parallelized mL-scale bioreactors are considered the key to reduce bioprocess development cost and time. However, their application is often limited to products with very simple analytics. In this study, we investigated enhanced protein expression conditions of a carboxyl reductase from Nocardia otitidiscaviarum in E. coli. Cells were produced with exponential feeding in a L-scale bioreactor. After the desired cell density for protein expression was reached, the cells were automatically transferred to 48 mL-scale bioreactors operated by a liquid handling station where protein expression studies were conducted. During protein expression, the feed rate and the inducer concentration was varied. At the end of the protein expression phase, the enzymatic activity was estimated by performing automated whole-cell biotransformations in a deep-well-plate. The results were analyzed with hierarchical Bayesian modelling methods to account for the biomass growth during the biotransformation, biomass interference on the subsequent product assay, and to predict absolute and specific enzyme activities at optimal expression conditions. Lower feed rates seemed to be beneficial for high specific and absolute activities. At the optimal investigated expression conditions an activity of [Formula: see text] was estimated with a [Formula: see text] credible interval of [Formula: see text] . This is about 40-fold higher than the highest published data for the enzyme under investigation. With the proposed setup, 192 protein expression conditions were studied during four experimental runs with minimal manual workload, showing the reliability and potential of automated and digitalized bioreactor systems