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Methicillin resistant Staphylococcus aureus (MRSA) is one of the most important antibiotic-resistant pathogens in hospitals and the community. Recently, a new generation of MRSA, the so called livestock associated (LA) MRSA, has emerged occupying food producing animals as a new niche. LA-MRSA can be regularly isolated from economically important live-stock species including corresponding meats. The present thesis takes a methodological approach to confirm the hypothesis that LA-MRSA are transmitted along the pork, poultry and beef production chain from animals at farm to meat on consumers` table. Therefore two new concepts were developed, adapted to differing data sets.
A mathematical model of the pig slaughter process was developed which simulates the change in MRSA carcass prevalence during slaughter with special emphasis on identifying critical process steps for MRSA transmission. Based on prevalences as sole input variables the model framework is able to estimate the average value range of both the MRSA elimination and contamination rate of each of the slaughter steps. These rates are then used to set up a Monte Carlo simulation of the slaughter process chain. The model concludes that regardless of the initial extent of MRSA contamination low outcome prevalences ranging between 0.15 and 1.15 % can be achieved among carcasses at the end of slaughter. Thus, the model demonstrates that the standard procedure of pig slaughtering in principle includes process steps with the capacity to limit MRSA cross contamination. Scalding and singeing were identified as critical process steps for a significant reduction of superficial MRSA contamination.
In the course of the German national monitoring program for zoonotic agents MRSA prevalence and typing data are regularly collected covering the key steps of different food production chains. A new statistical approach has been proposed for analyzing this cross sectional set of MRSA data with regard to show potential farm to fork transmission. For this purpose, chi squared statistics was combined with the calculation of the Czekanowski similarity index to compare the distributions of strain specific characteristics between the samples from farm, carcasses after slaughter and meat at retail. The method was implemented on the turkey and veal production chains and the consistently high degrees of similarity which have been revealed between all sample pairs indicate MRSA transmission along the chain.
As the proposed methods are not specific to process chains or pathogens they offer a broad field of application and extend the spectrum of methods for bacterial transmission assessment.
Forming as a result of the collision between the Adriatic and European plates, the Alpine orogen exhibits significant lithospheric heterogeneity due to the long history of interplay between these plates, other continental and oceanic blocks in the region, and inherited features from preceeding orogenies. This implies that the thermal and rheological configuration of the lithosphere also varies significantly throughout the region. Lithology and temperature/pressure conditions exert a first order control on rock strength, principally via thermally activated creep deformation and on the distribution at depth of the brittle-ductile transition zone, which can be regarded as the lower bound to the seismogenic zone. Therefore, they influence the spatial distribution of seismicity within a lithospheric plate. In light of this, accurately constrained geophysical models of the heterogeneous Alpine lithospheric configuration, are crucial in describing regional deformation patterns. However, despite the amount of research focussing on the area, different hypotheses still exist regarding the present-day lithospheric state and how it might relate to the present-day seismicity distribution.
This dissertaion seeks to constrain the Alpine lithospheric configuration through a fully 3D integrated modelling workflow, that utilises multiple geophysical techniques and integrates from all available data sources. The aim is therefore to shed light on how lithospheric heterogeneity may play a role in influencing the heterogeneous patterns of seismicity distribution observed within the region. This was accomplished through the generation of: (i) 3D seismically constrained, structural and density models of the lithosphere, that were adjusted to match the observed gravity field; (ii) 3D models of the lithospheric steady state thermal field, that were adjusted to match observed wellbore temperatures; and (iii) 3D rheological models of long term lithospheric strength, with the results of each step used as input for the following steps.
Results indicate that the highest strength within the crust (~ 1 GPa) and upper mantle (> 2 GPa), are shown to occur at temperatures characteristic for specific phase transitions (more felsic crust: 200 – 400 °C; more mafic crust and upper lithospheric mantle: ~600 °C) with almost all seismicity occurring in these regions. However, inherited lithospheric heterogeneity was found to significantly influence this, with seismicity in the thinner and more mafic Adriatic crust (~22.5 km, 2800 kg m−3, 1.30E-06 W m-3) occuring to higher temperatures (~600 °C) than in the thicker and more felsic European crust (~27.5 km, 2750 kg m−3, 1.3–2.6E-06 W m-3, ~450 °C). Correlation between seismicity in the orogen forelands and lithospheric strength, also show different trends, reflecting their different tectonic settings. As such, events in the plate boundary setting of the southern foreland correlate with the integrated lithospheric strength, occurring mainly in the weaker lithosphere surrounding the strong Adriatic indenter. Events in the intraplate setting of the northern foreland, instead correlate with crustal strength, mainly occurring in the weaker and warmer crust beneath the Upper Rhine Graben.
Therefore, not only do the findings presented in this work represent a state of the art understanding of the lithospheric configuration beneath the Alps and their forelands, but also a significant improvement on the features known to significantly influence the occurrence of seismicity within the region. This highlights the importance of considering lithospheric state in regards to explaining observed patterns of deformation.