Nachweis und Lokalisation von Photosensibilisatoren bei der photodynamischen Inaktivierung von Candida albicans

Eine neue Methode zur Bekämpfung mikrobieller Erkrankungen wie Mykosen der oralen Schleimhaut ist die antimikrobielle, photodynamische Therapie (aPDT). TMPyP, Methylenblau, Toluidinblau und Flavin 7 sind häufig verwendete Photosensibilisatoren (PS) in der Photodynamik. Das Ziel dieser Arbeit war es, die Wirkeffizienz dieser PS gegen Candida albicans zu untersuchen und festzustellen in welchem Maße die PS an die Zielzellen binden. Hierfür wurden Phototoxizitäts- und Uptakeuntersuchungen durchgeführt. Nur TMPyP zeigte sich in der Lage die koloniebildenden Einheiten (KBE) von Candida albicans nach Bestrahlung um 3log10-Stufen zu reduzieren. Die Aufnahme von TMPyP durch Candida albicans lag bei über 30%. Im zweiten Teil der Arbeit wurde die Lokalisation von TMPyP innerhalb der Pilzzelle vor und nach Bestrahlung untersucht, um daraus Informationen über den Wirkmechanismus der aPDT zu erhalten. Unmittelbar nach Inkubation von Candida albicans mit TMPyP zeigte sich im Fluoreszenzmikroskop eine ringförmige Anordnung des PS im Bereich der Zellhülle. Die Co-Inkubation mit dem Zellwandmarker Wheat Germ Agglutinin konnte die Zellwand als primären Lokalisationsort von TMPyP bestätigen. Nach Bestrahlung der Proben mit sichtbarem Licht lag das rot fluoreszierende TMPyP über die ganze Zelle verteilt vor, was auf einen Schaden an der Zellwand mit anschließendem Eindringen des PS in die Zelle schließen lässt. Während der Fluoreszenzmikroskopie nahm die Intensität von TMPyP aufgrund von Photobleaching deutlich ab

Assessment of the GW Approximation using Hubbard Chains

We investigate the performance of the GW approximation by comparison to exact results for small model systems. The role of the chemical potentials in Dyson's equation as well as the consequences of numerical resonance broadening are examined, and we show how a proper treatment can improve computational implementations of many-body perturbation theory in general. GW and exchange-only calculations are performed over a wide range of fractional band fillings and correlation strengths. We thus identify the physical situations where these schemes are applicable

Das Motivationspotenzial von Spielen erschließen. Künstliche Intelligenz als Lotse im Prozess der kreativen Gestaltung von motivierenden Lerngelegenheiten

Spiele bergen ein großes Motivationspotenzial. Sie zeigen, dass Menschen sich nicht nur freiwillig, sondern begeistert mit schwierigen Problemen auseinandersetzen können. Übertragen auf den Bildungskontext könnte dieses Potenzial auch das Lernen beflügeln. Der große Möglichkeitsraum des Spieldesigns überfordert Lehrende und Lernende jedoch oftmals, wenn sie ihn auf Lerngelegenheiten übertragen wollen. Künstliche Intelligenz (KI) kann einen solchen kreativen Gestaltungsprozess unterstützen. Als Teil eines methodischen Vorgehens kann sie den schwer überschaubaren Fundus spielerischer Elemente zugänglich machen. Auch ohne Spieldesignerfahrung können Lehrende und Lernende so das Potenzial von Spielen nutzen, um motivierende Lerngelegenheiten zu gestalten. Dafür haben wir in einen bereits erprobten, kreativen Arbeitsprozess, mit dem Nutzer:innen die Motivation in spielfremden Kontexten analysieren und weiterentwickeln können, eine KI eingebunden und Studierende damit in einem Seminar arbeiten lassen. Als Auftragnehmer hatten sie die Aufgabe Lerngelegenheiten motivierender zu gestalten. Anhand von Fokusgruppeninterviews haben wir explorativ untersucht, ob und wie die KI ihre Kreativität unterstützen konnte. (DIPF/Orig.)Games hold great motivational potential. They show that people can deal with difficult problems not only voluntarily but also enthusiastically. This potential could be used to inspire learning in educational contexts. However, the large number of possible structures provided by game design tends to overwhelm both teachers and learners when they try to transfer them to the context of learning. Artificial intelligence (AI) can support this creative design process. As part of a methodical approach, it can make the pool of game elements accessible. Even without any prior experience in game design, teachers, and learners can thus use the potential of games to create motivating learning opportunities. In a seminar with students, we integrated an AI into a tested creative workflow, where users analyze and develop motivation in non-game contexts. Using focus group interviews, we explored whether and how it could support the users’ creativity. The results show that the students used the AI to validate their ideas, and that it was predominantly perceived as supporting their creativity. (DIPF/Orig.

Geothermal Potential of the Brenner Base Tunnel—Initial Evaluations

Increasing demands on mobility and transport, but limited space above ground, lead to new traffic routes being built, even more underground in the form of tunnels. In addition to improving the traffic situation, tunnels offer the possibility of contributing to climate-friendly heating by indirectly serving as geothermal power plants. In this study, the geothermal potential of the future longest railway tunnel in the world, the Brenner Base Tunnel, was evaluated. At the Brenner Base Tunnel, warm water naturally flows from the apex of the tunnel towards the city of Innsbruck, Austria. In order to estimate its geothermal potential, hydrological data of discharge rates and temperatures were investigated and analyzed. The investigations indicated the highest geothermal potential in the summertime, while the lowest occurs during winter. It could be shown that these variations were a result of cooling during discharge through areas of low overburden (mid mountain range), where the tunnel atmosphere is increasingly influenced by the air temperatures outside the tunnel. Nevertheless, the calculations showed that there will be a usable potential after completion of the tunnel

Compensating asynchrony effects in the calculation of financial correlations

We present a method to compensate statistical errors in the calculation of correlations on asynchronous time series. The method is based on the assumption of an underlying time series. We set up a model and apply it to financial data to examine the decrease of calculated correlations towards smaller return intervals (Epps effect). We show that this statistical effect is a major cause of the Epps effect. Hence, we are able to quantify and to compensate it using only trading prices and trading times.Comment: 13 pages, 7 figure

Wearable full-body motion tracking of activities of daily living predicts disease trajectory in Duchenne muscular dystrophy

Artificial intelligence has the potential to revolutionize healthcare, yet clinical trials in neurological diseases continue to rely on subjective, semiquantitative and motivation-dependent endpoints for drug development. To overcome this limitation, we collected a digital readout of whole-body movement behavior of patients with Duchenne muscular dystrophy (DMD) (n = 21) and age-matched controls (n = 17). Movement behavior was assessed while the participant engaged in everyday activities using a 17-sensor bodysuit during three clinical visits over the course of 12 months. We first defined new movement behavioral fingerprints capable of distinguishing DMD from controls. Then, we used machine learning algorithms that combined the behavioral fingerprints to make cross-sectional and longitudinal disease course predictions, which outperformed predictions derived from currently used clinical assessments. Finally, using Bayesian optimization, we constructed a behavioral biomarker, termed the KineDMD ethomic biomarker, which is derived from daily-life behavioral data and whose value progresses with age in an S-shaped sigmoid curve form. The biomarker developed in this study, derived from digital readouts of daily-life movement behavior, can predict disease progression in patients with muscular dystrophy and can potentially track the response to therapy

Effect of short-range electron correlations in dynamic transport in a Luttinger liquid

The density operator in the Luttinger model consists of two components, one of which describes long-wave fluctuations and the other is related to the rapid oscillations of the charge-density-wave (CDW) type, caused by short-range electron correlations. It is commonly believed that the conductance is determined by the long-wave component. The CDW component is considered only when an impurity is present. We investigate the contribution of this component to the dynamic density response of a Luttinger liquid free from impurities. We show that the conventional form of the CDW density operator does not conserve the number of particles in the system. We propose the corrected CDW density operator devoid of this shortcoming and calculate the dissipative conductance in the case when the one-dimensional conductor is locally disturbed by a conducting probe. The contribution of the CDW component to conductance is found to dominate over that of the long-wave component in the low-frequency regime.Comment: 6 pages, 4 figures; updated to the published versio