Antimicrobial capacity of plasma from anurans of the Atlantic Forest

The viability and interpretation of techniques for the evaluation of immunocompetence of animals in their natural environment has been largely debated. One of these methods is based on testing the antimicrobial capacity of the blood and/or plasma in vitro, which could rapidly and effectively assess the immunological conditions of natural populations. We tested the applicability of the antimicrobial capacity of plasma (ACP) assay in anuran amphibians from the Atlantic Forest. The assay was performed by measuring both the turbidity (in a spectrophotometer) and the colony forming units (CFU) of the remaining bacteria (Escherichia coli) following exposure to amphibian plasma. Although both assays were correlated, the ACP assay by spectrophotometry showed 10 times lower intra-assay variation. We also found interspecific variation in ACP, as well as the maintenance of ACP values in males from the same population, collected in different breeding seasons. Thus, the estimation of ACP by spectrophotometry provides a convenient and accurate method for evaluating innate immunocompetence in comparative and ecophysiological studies of anuran amphibians.

Isocyanates and Amines – Sampling and Analytical Procedures

This thesis covers sampling and analytical procedures for isocyanates (R-NCO) and amines (R-NH2), two kinds of chemicals frequently used in association with the polymeric material polyurethane (PUR). Exposure to isocyanates may result in respiratory disorders and dermal sensitisation, and they are one of the main causes of occupational asthma. Several of the aromatic diamines associated with PUR production are classified as suspected carcinogens. Hence, the presence of these chemicals in different exposure situations must be monitored. In the context of determining isocyanates in air, the methodologies included derivatisation with the reagent di-n-butylamine (DBA) upon collection and subsequent determination using liquid chromatography (LC) and mass spectrometric detection (MS). A user-friendly solvent-free sampler for collection of airborne isocyanates was developed as an alternative to a more cumbersome impinger-filter sampling technique. The combination of the DBA reagent together with MS detection techniques revealed several new exposure situations for isocyanates, such as isocyanic acid during thermal degradation of PUR and urea-based resins. Further, a method for characterising isocyanates in technical products used in the production of PUR was developed. This enabled determination of isocyanates in air for which pure analytical standards are missing. Tandem MS (MS/MS) determination of isocyanates in air below 10-6 of the threshold limit values was achieved. As for the determination of amines, the analytical methods included derivatisation into pentafluoropropionic amide or ethyl carbamate ester derivatives and subsequent MS analysis. Several amines in biological fluids, as markers of exposure for either the amines themselves or the corresponding isocyanates, were determined by LC-MS/MS at amol level. In aqueous extraction solutions of flexible PUR foam products, toluene diamine and related compounds were found. In conclusion, this thesis demonstrates the usefulness of well characterised analytical procedures and techniques for determination of hazardous compounds. Without reliable and robust methodologies there is a risk that exposure levels will be underestimated or, even worse, that relevant compounds will be completely missed.

Models and methods for power monolithic microwave integrated circuits

Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

Study of variability and genetic structure of European populations of Myotis emarginatus and Myotis capaccinii (Chiroptera, Vespertilionidae)

The Geoffroy’s bat Myotis emarginatus is mainly present in southern, south-eastern and central Europe (Červerný, 1999) and is often recorded from northern Spain (Quetglas, 2002; Flaquer et al., 2004). It has demonstrated the species’ preference for forest. Myotis capaccinii, confined to the Mediterranean (Guille´n, 1999), is classified as ‘vulnerable’ on a global scale (Hutson, Mickleburgh & Racey, 2001). In general, the species preferred calm waters bordered by well-developed riparian vegetation and large (> 5 m) inter-bank distances (Biscardi et al. 2007). In this study we present the first results about population genetic structure of these two species of genus Myotis. We used two methods of sampling: invasive and non-invasive techniques. A total of 323 invasive samples and a total of 107 non-invasive samples were collected and analyzed. For Myotis emarginatus we have individuated for the first time a set of 7 microsatellites, which can work on this species, started from a set developed on Myotis myotis (Castella et al. 2000). We developed also a method for analysis of non-invasive samples, that given a good percentage of positive analyzed samples. The results have highlighted for the species Myotis emarginatus the presence on the European territory of two big groups, discovered by using the microsatellites tracers. On this species, 33 haplotypes of Dloop have been identified, some of them are presented only in some colonies. We identified respectively 33 haplotypes of Dloop and 10 of cytB for Myotis emarginatus and 25 of dloop and 15 of cytB for Myotis capaccinii. Myotis emarginatus’ results, both microsatellites and mtDNA, show that there is a strong genetic flow between different colonies across Europe. The results achieved on Myotis capaccinii are very interesting, in this case either for the microsatellites or the mitochondrial DNA sequences, and it has been highlighted a big difference between different colonies.

Local Earthquake Tomography by trans-dimensional Monte Carlo Sampling

In this study a new, fully non-linear, approach to Local Earthquake Tomography is presented. Local Earthquakes Tomography (LET) is a non-linear inversion problem that allows the joint determination of earthquakes parameters and velocity structure from arrival times of waves generated by local sources. Since the early developments of seismic tomography several inversion methods have been developed to solve this problem in a linearized way. In the framework of Monte Carlo sampling, we developed a new code based on the Reversible Jump Markov Chain Monte Carlo sampling method (Rj-McMc). It is a trans-dimensional approach in which the number of unknowns, and thus the model parameterization, is treated as one of the unknowns. I show that our new code allows overcoming major limitations of linearized tomography, opening a new perspective in seismic imaging. Synthetic tests demonstrate that our algorithm is able to produce a robust and reliable tomography without the need to make subjective a-priori assumptions about starting models and parameterization. Moreover it provides a more accurate estimate of uncertainties about the model parameters. Therefore, it is very suitable for investigating the velocity structure in regions that lack of accurate a-priori information. Synthetic tests also reveal that the lack of any regularization constraints allows extracting more information from the observed data and that the velocity structure can be detected also in regions where the density of rays is low and standard linearized codes fails. I also present high-resolution Vp and Vp/Vs models in two widespread investigated regions: the Parkfield segment of the San Andreas Fault (California, USA) and the area around the Alto Tiberina fault (Umbria-Marche, Italy). In both the cases, the models obtained with our code show a substantial improvement in the data fit, if compared with the models obtained from the same data set with the linearized inversion codes.

Application of innovative methods of source apportionment in air contamination assessment

In this work, new tools in atmospheric pollutant sampling and analysis were applied in order to go deeper in source apportionment study. The project was developed mainly by the study of atmospheric emission sources in a suburban area influenced by a municipal solid waste incinerator (MSWI), a medium-sized coastal tourist town and a motorway. Two main research lines were followed. For what concerns the first line, the potentiality of the use of PM samplers coupled with a wind select sensor was assessed. Results showed that they may be a valid support in source apportionment studies. However, meteorological and territorial conditions could strongly affect the results. Moreover, new markers were investigated, particularly focusing on the processes of biomass burning. OC revealed a good biomass combustion process indicator, as well as all determined organic compounds. Among metals, lead and aluminium are well related to the biomass combustion. Surprisingly PM was not enriched of potassium during bonfire event. The second research line consists on the application of Positive Matrix factorization (PMF), a new statistical tool in data analysis. This new technique was applied to datasets which refer to different time resolution data. PMF application to atmospheric deposition fluxes identified six main sources affecting the area. The incinerator’s relative contribution seemed to be negligible. PMF analysis was then applied to PM2.5 collected with samplers coupled with a wind select sensor. The higher number of determined environmental indicators allowed to obtain more detailed results on the sources affecting the area. Vehicular traffic revealed the source of greatest concern for the study area. Also in this case, incinerator’s relative contribution seemed to be negligible. Finally, the application of PMF analysis to hourly aerosol data demonstrated that the higher the temporal resolution of the data was, the more the source profiles were close to the real one.

Coarse-graining methods and polymer dynamics

This thesis studies molecular dynamics simulations on two levels of resolution: the detailed level of atomistic simulations, where the motion of explicit atoms in a many-particle system is considered, and the coarse-grained level, where the motion of superatoms composed of up to 10 atoms is modeled. While atomistic models are capable of describing material specific effects on small scales, the time and length scales they can cover are limited due to their computational costs. Polymer systems are typically characterized by effects on a broad range of length and time scales. Therefore it is often impossible to atomistically simulate processes, which determine macroscopic properties in polymer systems. Coarse-grained (CG) simulations extend the range of accessible time and length scales by three to four orders of magnitude. However, no standardized coarse-graining procedure has been established yet. Following the ideas of structure-based coarse-graining, a coarse-grained model for polystyrene is presented. Structure-based methods parameterize CG models to reproduce static properties of atomistic melts such as radial distribution functions between superatoms or other probability distributions for coarse-grained degrees of freedom. Two enhancements of the coarse-graining methodology are suggested. Correlations between local degrees of freedom are implicitly taken into account by additional potentials acting between neighboring superatoms in the polymer chain. This improves the reproduction of local chain conformations and allows the study of different tacticities of polystyrene. It also gives better control of the chain stiffness, which agrees perfectly with the atomistic model, and leads to a reproduction of experimental results for overall chain dimensions, such as the characteristic ratio, for all different tacticities. The second new aspect is the computationally cheap development of nonbonded CG potentials based on the sampling of pairs of oligomers in vacuum. Static properties of polymer melts are obtained as predictions of the CG model in contrast to other structure-based CG models, which are iteratively refined to reproduce reference melt structures. The dynamics of simulations at the two levels of resolution are compared. The time scales of dynamical processes in atomistic and coarse-grained simulations can be connected by a time scaling factor, which depends on several specific system properties as molecular weight, density, temperature, and other components in mixtures. In this thesis the influence of molecular weight in systems of oligomers and the situation in two-component mixtures is studied. For a system of small additives in a melt of long polymer chains the temperature dependence of the additive diffusion is predicted and compared to experiments.

Response of nutrient cycles of an old-growth montane forest in Ecuador to experimental low-level nutrient amendments

Atmospheric nitrogen (N) and phosphorus (P) depositions are expected to increase in the tropicsrnas a consequence of increasing human activities in the next decades. Furthermore, a possiblernshortened El Niño Southern Oscillation cycle might come along with more frequent calcium (Ca)rndepositions on the eastern slope of the Ecuadorian Andes originating from Saharan dust. It isrncrucial to understand the response of the old-growth montane forest in Ecuador to increasedrnnutrient deposition to predict the further development of this megadiverse ecosystem.rnI studied experimental additions of N, P, N+P and Ca to the forest and an untreatedrncontrol, all in a fourfold replicated randomized block design. These experiments were conductedrnin the framework of a collaborative research effort, the NUtrient Manipulation EXperimentrn(NUMEX). I collected litter leachate, mineral soil solution (0.15 and 0.30 m depths), throughfallrnand fine litterfall samples and determined N, P and Ca concentrations and fluxes. This approachrnalso allowed me to assess whether N, P and/or Ca are limiting nutrients for forest growth.rnFurthermore, I evaluated the response of fine root biomass, leaf area index, leaf area and specificrnleaf area, tree diameter growth and basal area increment contributed from a cooperating group inrnthe Ca applied and control treatments.rnDuring the observation period of 16 months after the first fertilizer application, less thanrn10, 1 and 5% of the applied N, P and Ca, respectively, leached below the organic layer whichrncontained almost all roots but no significant leaching losses occurred to the deeper mineral soil.rnDeposited N, P and Ca from the atmosphere in dry and wet form were, on balance, retained in therncanopy in the control treatment. Retention of N, P and Ca in the canopy in their respectiverntreatments was reduced resulting in higher concentrations and fluxes of N, P and Ca inrnthroughfall and litterfall. Up to 2.5% of the applied N and 2% of the applied P and Ca werernrecycled to the soil with throughfall. Fluxes of N, P and Ca in throughfall+litterfall were higher inrnthe fertilized treatments than in the control; up to 20, 5 and 25% of the applied N, P and Ca,rnrespectively, were recycled to the soil with throughfall+litterfall.rnIn the Ca-applied plots, fine root biomass decreased significantly. Also the leaf area of thernfour most common tree species tended to decrease and the specific leaf area increasedrnsignificantly in Graffenrieda emarginata Triana, the most common tree species in the study area.rnThese changes are known plant responses to reduced nutrient stress. Reduced aluminium (Al)rntoxicity as an explanation of the Ca effect was unlikely, because of almost complete organocomplexationrnof Al and molar Ca:Al concentration ratios in solution above the toxicity threshold.rnThe results suggest that N, P and Ca co-limit the forest ecosystem functioning in thernnorthern Andean montane forests in line with recent assumptions in which different ecosystemrncompartments and even different phenological stages may show different nutrient limitationsrn(Kaspari et al. 2008). I conclude that (1) the expected elevated N and P deposition will bernretained in the ecosystem, at least in the short term and hence, quality of river water will not bernendangered and (2) increased Ca input will reduce nutrient stress of the forest.

Development of models and methods to simulate peptide-assisted nucleation and growth of calcium-minerals

In den vergangenen Jahren wurden einige bislang unbekannte Phänomene experimentell beobachtet, wie etwa die Existenz unterschiedlicher Prä-Nukleations-Strukturen. Diese haben zu einem neuen Verständnis von Prozessen, die auf molekularer Ebene während der Nukleation und dem Wachstum von Kristallen auftreten, beigetragen. Die Auswirkungen solcher Prä-Nukleations-Strukturen auf den Prozess der Biomineralisation sind noch nicht hinreichend verstanden. Die Mechanismen, mittels derer biomolekulare Modifikatoren, wie Peptide, mit Prä-Nukleations-Strukturen interagieren und somit den Nukleationsprozess von Mineralen beeinflussen könnten, sind vielfältig. Molekulare Simulationen sind zur Analyse der Formation von Prä-Nukleations-Strukturen in Anwesenheit von Modifikatoren gut geeignet. Die vorliegende Arbeit beschreibt einen Ansatz zur Analyse der Interaktion von Peptiden mit den in Lösung befindlichen Bestandteilen der entstehenden Kristalle mit Hilfe von Molekular-Dynamik Simulationen.rnUm informative Simulationen zu ermöglichen, wurde in einem ersten Schritt die Qualität bestehender Kraftfelder im Hinblick auf die Beschreibung von mit Calciumionen interagierenden Oligoglutamaten in wässrigen Lösungen untersucht. Es zeigte sich, dass große Unstimmigkeiten zwischen etablierten Kraftfeldern bestehen, und dass keines der untersuchten Kraftfelder eine realistische Beschreibung der Ionen-Paarung dieser komplexen Ionen widerspiegelte. Daher wurde eine Strategie zur Optimierung bestehender biomolekularer Kraftfelder in dieser Hinsicht entwickelt. Relativ geringe Veränderungen der auf die Ionen–Peptid van-der-Waals-Wechselwirkungen bezogenen Parameter reichten aus, um ein verlässliches Modell für das untersuchte System zu erzielen. rnDas umfassende Sampling des Phasenraumes der Systeme stellt aufgrund der zahlreichen Freiheitsgrade und der starken Interaktionen zwischen Calciumionen und Glutamat in Lösung eine besondere Herausforderung dar. Daher wurde die Methode der Biasing Potential Replica Exchange Molekular-Dynamik Simulationen im Hinblick auf das Sampling von Oligoglutamaten justiert und es erfolgte die Simulation von Peptiden verschiedener Kettenlängen in Anwesenheit von Calciumionen. Mit Hilfe der Sketch-Map Analyse konnten im Rahmen der Simulationen zahlreiche stabile Ionen-Peptid-Komplexe identifiziert werden, welche die Formation von Prä-Nukleations-Strukturen beeinflussen könnten. Abhängig von der Kettenlänge des Peptids weisen diese Komplexe charakteristische Abstände zwischen den Calciumionen auf. Diese ähneln einigen Abständen zwischen den Calciumionen in jenen Phasen von Calcium-Oxalat Kristallen, die in Anwesenheit von Oligoglutamaten gewachsen sind. Die Analogie der Abstände zwischen Calciumionen in gelösten Ionen-Peptid-Komplexen und in Calcium-Oxalat Kristallen könnte auf die Bedeutung von Ionen-Peptid-Komplexen im Prozess der Nukleation und des Wachstums von Biomineralen hindeuten und stellt einen möglichen Erklärungsansatz für die Fähigkeit von Oligoglutamaten zur Beeinflussung der Phase des sich formierenden Kristalls dar, die experimentell beobachtet wurde.

The sensitivity of the photostationary state of NOx and its implication for the oxidation capacity in a semi-rural and boreal forest region

Für das Vermögen der Atmosphäre sich selbst zu reinigen spielen Stickstoffmonoxid (NO) und Stickstoffdioxid (NO2) eine bedeutende Rolle. Diese Spurengase bestimmen die photochemische Produktion von Ozon (O3) und beeinflussen das Vorkommen von Hydroxyl- (OH) und Nitrat-Radikalen (NO3). Wenn tagsüber ausreichend Solarstrahlung und Ozon vorherrschen, stehen NO und NO2 in einem schnellen photochemischen Gleichgewicht, dem „Photostationären Gleichgewichtszustand“ (engl.: photostationary state). Die Summe von NO und NO2 wird deshalb als NOx zusammengefasst. Vorhergehende Studien zum photostationären Gleichgewichtszustand von NOx umfassen Messungen an unterschiedlichsten Orten, angefangen bei Städten (geprägt von starken Luftverschmutzungen), bis hin zu abgeschiedenen Regionen (geprägt von geringeren Luftverschmutzungen). Während der photochemische Kreislauf von NO und NO2 unter Bedingungen erhöhter NOx-Konzentrationen grundlegend verstanden ist, gibt es in ländlicheren und entlegenen Regionen, welche geprägt sind von niedrigeren NOx-Konzetrationen, signifikante Lücken im Verständnis der zugrundeliegenden Zyklierungsprozesse. Diese Lücken könnten durch messtechnische NO2-Interferenzen bedingt sein - insbesondere bei indirekten Nachweismethoden, welche von Artefakten beeinflusst sein können. Bei sehr niedrigen NOx-Konzentrationen und wenn messtechnische NO2-Interferenzen ausgeschlossen werden können, wird häufig geschlussfolgert, dass diese Verständnislücken mit der Existenz eines „unbekannten Oxidationsmittels“ (engl.: unknown oxidant) verknüpft ist. Im Rahmen dieser Arbeit wird der photostationäre Gleichgewichtszustand von NOx analysiert, mit dem Ziel die potenzielle Existenz bislang unbekannter Prozesse zu untersuchen. Ein Gasanalysator für die direkte Messung von atmosphärischem NO¬2 mittels laserinduzierter Fluoreszenzmesstechnik (engl. LIF – laser induced fluorescence), GANDALF, wurde neu entwickelt und während der Messkampagne PARADE 2011 erstmals für Feldmessungen eingesetzt. Die Messungen im Rahmen von PARADE wurden im Sommer 2011 in einem ländlich geprägten Gebiet in Deutschland durchgeführt. Umfangreiche NO2-Messungen unter Verwendung unterschiedlicher Messtechniken (DOAS, CLD und CRD) ermöglichten einen ausführlichen und erfolgreichen Vergleich von GANDALF mit den übrigen NO2-Messtechniken. Weitere relevante Spurengase und meteorologische Parameter wurden gemessen, um den photostationären Zustand von NOx, basierend auf den NO2-Messungen mit GANDALF in dieser Umgebung zu untersuchen. Während PARADE wurden moderate NOx Mischungsverhältnisse an der Messstelle beobachtet (10^2 - 10^4 pptv). Mischungsverhältnisse biogener flüchtige Kohlenwasserstoffverbindungen (BVOC, engl.: biogenic volatile organic compounds) aus dem umgebenden Wald (hauptsächlich Nadelwald) lagen in der Größenordnung 10^2 pptv vor. Die Charakteristiken des photostationären Gleichgewichtszustandes von NOx bei niedrigen NOx-Mischungsverhältnissen (10 - 10^3 pptv) wurde für eine weitere Messstelle in einem borealen Waldgebiet während der Messkampagne HUMPPA-COPEC 2010 untersucht. HUMPPA–COPEC–2010 wurde im Sommer 2010 in der SMEARII-Station in Hyytiälä, Süd-Finnland, durchgeführt. Die charakteristischen Eigenschaften des photostationären Gleichgewichtszustandes von NOx in den beiden Waldgebieten werden in dieser Arbeit verglichen. Des Weiteren ermöglicht der umfangreiche Datensatz - dieser beinhaltet Messungen von relevanten Spurengasen für die Radikalchemie (OH, HO2), sowie der totalen OH-Reaktivität – das aktuelle Verständnis bezüglich der NOx-Photochemie unter Verwendung von einem Boxmodell, in welches die gemessenen Daten als Randbedingungen eingehen, zu überprüfen und zu verbessern. Während NOx-Konzentrationen in HUMPPA-COPEC 2010 niedriger sind, im Vergleich zu PARADE 2011 und BVOC-Konzentrationen höher, sind die Zyklierungsprozesse von NO und NO2 in beiden Fällen grundlegend verstanden. Die Analyse des photostationären Gleichgewichtszustandes von NOx für die beiden stark unterschiedlichen Messstandorte zeigt auf, dass potenziell unbekannte Prozesse in keinem der beiden Fälle vorhanden sind. Die aktuelle Darstellung der NOx-Chemie wurde für HUMPPA-COPEC 2010 unter Verwendung des chemischen Mechanismus MIM3* simuliert. Die Ergebnisse der Simulation sind konsistent mit den Berechnungen basierend auf dem photostationären Gleichgewichtszustand von NOx.

Selective inferior petrosal sinus sampling without venous outflow diversion in the detection of a pituitary adenoma in Cushing's syndrome

Conventional MRI may still be an inaccurate method for the non-invasive detection of a microadenoma in adrenocorticotropin (ACTH)-dependent Cushing's syndrome (CS). Bilateral inferior petrosal sinus sampling (BIPSS) with ovine corticotropin-releasing hormone (oCRH) stimulation is an invasive, but accurate, intervention in the diagnostic armamentarium surrounding CS. Until now, there is a continuous controversial debate regarding lateralization data in detecting a microadenoma. Using BIPSS, we evaluated whether a highly selective placement of microcatheters without diversion of venous outflow might improve detection of pituitary microadenoma.