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Obesity is considered as a type of chronic inflammation. It enhances the risk of developing cardiovascular disease, diabetes, and some cancers. The key players in the induction of inflammation in adipose tissue are macrophages. However the mechanism of macrophage activation in obese fat tissue is still not fully understood. Elevated level of saturated fatty acids in adipose tissue promotes inflammation and insulin resistance. Exposure of macrophages to saturated fatty acids stimulates pro-inflammatory c-Jun N-terminal kinase (JNK), nuclear factor kappa B (NF-kB) signaling, and production of pro-inflammatory cytokines, such as IL-6, IL-8, IL-1β, and TNFα. Palmitate is a major saturated free fatty acid released by adipocytes. It activates inflammatory pathways through Toll-like receptors (TLR) 2 and 4, provokes endoplasmic reticulum (ER) stress and increases levels of diacylglycerols (DAGs) and ceramides. Saturated fatty acids also affect cellular oxidative metabolism. Thus, mitochondrial fatty acid oxidation reduces ER-stress and expression of inflammatory cytokines in palmitate-treated macrophages. On the other hand mitochondrial reactive oxygen species (ROS) promote palmitate-mediated pro-inflammatory cytokine production. Recently, mitochondrial functions were linked to their morphology. Mitochondrial fission has been reported in β-cells and myocytes in response to high levels of glucose and free fatty acids, and was associated with disruption of mitochondrial functions, increased ROS level, and cell death. The aim of this study was to investigate the role of mitochondrial fragmentation in palmitate-induced inflammation in human macrophages. In our settings fatty acids, independently of their saturation, affected mitochondrial morphology. Mixtures of long chain saturated and unsaturated fatty acids as well as triglyceride-rich lipoprotein lipolysis products promoted mitochondrial fission. Mitochondrial fragmentation in palmitate-treated macrophages revealed a time- and concentration-dependent character, and was reversible upon palmitate removal. This observation, together with unaltered levels of mitochondrial protein and DNA content, and intact mitochondrial respiration, suggested that mitochondria were not damaged and were functionally active. Mechanistically, palmitate-induced mitochondrial fragmentation was not regulated by ER stress or loss of mitochondrial membrane potential. However, inhibition of palmitate incorporation into mitochondrial membrane phospholipids decreased mitochondrial fragmentation. Other approach to prevent mitochondrial fission was the inhibition of dynamin-related protein 1 (DRP1) activity, which drives mitochondrial fission by forming ring- like structures around mitochondria and constricting mitochondrial membranes. Palmitate altered mitochondrial membrane lipid composition and promoted DRP1-oligomerization. The inhibition of palmitate-induced mitochondrial fragmentation enhanced mitochondrial ROS production, c-Jun phosphorylation, and upregulated expression of pro-inflammatory cytokines. Taken together, these results suggest that mitochondrial fragmentation is a protective mechanism attenuating palmitate-induced inflammatory responses. Future experiments will be required to investigate the role of mitochondrial fragmentation in obesity-associated diseases in vivo.
The Dodd Frank Act of 2010 (DFA) was the legislative response by the US Government to the Global Financial Crisis of 2007. DFA’s rescission of Rule 436 (g) of the Securities Act of 1933 - the exemption from liability clause - was the response to the post-crisis perception that credit rating agencies were insufficiently constrained by reputational risk considerations and consistently failed to provide high quality and accurate credit ratings as a consequence of the immunity they enjoyed and the regulatory reliance placed on ratings, as well as the conflicts of interest that they faced. This paper investigates whether the market failure event that occurred in the Asset Backed Securities market immediately after DFA was signed into law on July 21, 2010 was due to real economic concerns held by rating agencies about operating under a liability regime or whether it was merely an act of brinkmanship on the part of the rating agencies. The paper also predominantly examines US case law to identify the dilution of the freedom of speech defence in state courts, the conflict of interest issues and the legal challenges faced by plaintiffs when bringing a lawsuit against credit rating agencies, and proposes a novel co-pay and capped liability model to address the concerns of both credit rating agencies and investors.
Atmospheric nanoaerosols have extensive effects on the Earth’s climate and human health. This cumulative work focuses on the development and characterization of instrumentation for measuring various parameters of atmospheric nanoaerosols, and its use to understand new particle formation from organic precursors. The principal research question is, how the chemical composition of nanoaerosol particles can be measured and how atmospheric chemistry influences aerosol processes, especially new particle formation and growth. Therefore, nanoaerosols are investigated under various aspects. More specifically, an instrument is developed to analyze nanoparticles, and field as well as chamber studies are conducted.
The main project is the instrument development of the Thermal Desorption Differential Mobility Analyzer (TD-DMA, project 1, Wagner et al. (2018)). This instrument analyzes the chemical composition of small aerosol particles. By characterization and testing in chamber experiments, it is proven to be suitable for the analysis of freshly nucleated particles.
The second project (Wagner et al. (2017)) applies a broad spectrum of aerosol measurement instruments for the characterization of aerosol particles produced by a skyscraper blasting. A comprehensive picture of the particle population emitted by the demolition is obtained.
Project 3 (K¨urten et al. (2016)) is also an ambient aerosol measurement, focusing of new particle formation in a rural area in central Germany, and the ability of a negative nitrate CI-APi-TOF to detect various substances in atmosphere. Project 4 (Heinritzi et al. (2016)) is a characterization of the negative nitrate CI-APi-TOF used in projects 1, 3, 5, 6, 7 and 8. The following projects focus on understanding new particle formation from atmospherically abundant organic precursors. Key instruments comprise the negative nitrate CI-APiTOF for gas-phase measurements of the nucleating species, and various sizing and counting instruments for quantifying the particle formation and growth. Project 5 (Kirkby et al. (2016)) shows that biogenic organic compounds formed from alpha-pinene can nucleate on their own without the influence of e.g. sulfuric acid. Project 6 (Tr¨ostl et al. (2016)) describe the subsequent growth of these particles. Project 7 (Stolzenburg et al. (2018)) covers the temperature dependence of this growth and in project 8 (Heinritzi et al. (2018)), the suppressing influence of isoprene on the new particle formation is assessed.
Das Standardmodell der Elementarteilchenphysik beschreibt nach aktuellem Kenntnisstand die Entstehung, den Aufbau und das Verhalten der Materie in unserem Universum am erfolgreichsten. Dennoch gibt es einige Phänomene, die sich nicht in dessen Rahmen beschreiben lassen, wie z. B. die Existenz von dunkler Materie und Energie, nicht-verschwindende Neutrinomassen oder die Baryonenasymmetrie. Speziell im Hinblick auf die starke Wechselwirkung, welche im Standardmodell durch die Quantenchromodynamik (QCD) beschrieben wird, gibt es noch immer viele offene Fragen.
Eine Umgebung, in der man die QCD experimentell ergründen kann, bieten vor allem Schwerionenkollisionen, die insbesondere am Large Hadron Collider (LHC) oder am Relativistic Heavy Ion Collider (RHIC) durchgeführt werden.
In dieser Arbeit soll ein Beitrag von theoretischer Seite aus hinsichtlich eines besseren Verständnisses dieser Schwerionenkollisionen und der zugrundeliegenden QCD erbracht werden. Der Fokus liegt dabei auf dem Isotropisierungsprozess unmittelbar nach der Kollision der beiden Kerne.
Neben etlichen effektiven Theorien, die sehr gute Ergebnisse in den entsprechenden Grenzbereichen liefern, ist die Beschreibung der QCD im Rahmen der Gittereichtheorie (Gitter-QCD) die am meisten etablierte. Diese beinhaltet in den meisten Fällen einen Übergang zur euklidischen Raumzeit, da somit ein Auswerten der hochdimensionalen Pfadintegrale mithilfe von Monte-Carlo-Simulation basierend auf dem sogenannten Importance Sampling ermöglicht wird. Aufgrund der Komplexwertigkeit der euklidischen Zeitkomponente ist man jedoch an das Studieren von statischen Observablen gebunden. Da wir aber gerade an einer Zeitentwicklung des Systems interessiert sind, sehen wir von dem Übergang zur euklidischen Raumzeit ab, was den Namen “real-time” im Titel der Arbeit erklärt.
Wir folgen dem sogenannten Hamilton-Ansatz und leiten damit Feldgleichungen in Form von partiellen Differentialgleichungen her, die wir dann mit den Methoden der Gitter-QCD numerisch lösen. Dabei bedienen wir uns der effektive Theorie des Farb-Glas-Kondensats (CGC, aus dem Englischen: “Color Glass Condensate”), um geeignete Anfangsbedingungen zu erhalten. Genauer gesagt basieren unsere Gitter-Anfangsbedingungen auf dem McLerran-Venugopalan-Modell (MV-Modell), das eine klassische Approximation in niedrigster Ordnung darstellt und nur Beiträge rein gluonischer Felder berücksichtigt.
Die klassische Näherung sowie das Vernachlässigen der fermionischen Felder wird insbesondere mit den hohen Besetzungszahlen der Feldmoden begründet. Einerseits dominieren Infrarot-Effekte, welche klassischer Natur sind, und andererseits ist dadurch der Einfluss der Fermionen, die dem Pauli-Prinzip gehorchen, unterdrückt. Gerade bei letzterer Aussage fehlt es jedoch an numerischen Belegen. Wir erweitern daher die klassische MV-Beschreibung durch stochastische Gitter-Fermionen, um diesem Punkt nachzugehen. Da sich Fermionen nicht klassisch beschreiben lassen, spricht man hierbei oft von einem semi-klassischen Ansatz.
Eines der Hauptziele dieser Arbeit liegt darin, den Isotropisierungsprozess, der bislang noch viele Fragen aufwirft, aber unter anderem Voraussetzung für das Anwenden von hydrodynamischen Modellen ist, zu studieren. Wir legen dabei einen besonderen Fokus auf die systematische Untersuchung der verschiedenen Parameter, die durch die CGC-Anfangsbedingungen in unsere Beschreibung einfließen, und deren Auswirkungen auf etwa die Gesamtenergiedichte des Systems oder die zugehörigen Isotropisierungszeiten. Währenddessen überprüfen wir zudem den Einfluss von unphysikalischen Gitter-Artefakten und präsentieren eine eichinvariante Methode zur Analyse der Güte unserer klassischen Näherung. Die Zeitentwicklung des Systems betrachten wir dabei sowohl in einer statischen Box als auch in einem expandierenden Medium, wobei Letzteres durch sogenannte comoving Koordinaten beschrieben wird. Zudem liefern wir einen Vergleich von der realistischen SU(3)-Eichgruppe und der rechentechnisch ökonomischeren SU(2)-Eichgruppe.
Mit unseren numerischen Ergebnissen zeigen wir, dass das System hochempfindlich auf die verschiedenen Modellparameter reagiert, was das Treffen quantitativer Aussagen in dieser Formulierung deutlich erschwert, insbesondere da einige dieser Parameter rein technischer Natur sind und somit keine zugehörigen physikalisch motivierten Größen, die den Definitionsbereich einschränken könnten, vorhanden sind. Es ist jedoch möglich, die Anzahl der freien Parameter zu reduzieren, indem man ihren Einfluss auf die Gesamtenergie des Systems analysiert und sich diesen zunutze macht. Dadurch gelingt es uns mithilfe von Konturdiagrammen einige Abhängigkeiten zu definieren und somit die Unbestimmtheit des Systems einzuschränken. Des Weiteren finden wir dynamisch generierte Filamentierungen in der Ortsdarstellung der Energiedichte, die ein starkes Indiz für die Präsenz von sogenannten chromo-Weibel-Instabilitäten sind. Unsere Studie des fermionischen Einflusses auf den Isotropisierungsprozess des CGC-Systems weist auf, dass dieser bei kleiner Kopplung vernachlässigbar ist. Bei hinreichend großen Werten für die Kopplungskonstante sehen wir allerdings einen starken Effekt hinsichtlich der Isotropisierungszeiten, was ein bemerkenswertes Resultat ist.
Whereas many writers across all times and cultures have written about the potential aesthetic effects of music experiences which could be labeled as absorption, only limited empirical research has been done on the state aspects of this fascinating aspect of human involvement. What is more, there are still few tested models which explain how people can be absorbed by a piece of music as well as continue to be third-person observers monitoring and even reflecting on that same musical experience (cf. Bryant & Veroff, 2007; Dewey, 2005; Wolf, 2013).
Adopting a dual process approach (Dietrich, 2004; Evans & Stanovich, 2013; Lewis, Tamborini & Weber, 2014; Mukhopadhyay, 2014; Schwarz, 2011; Smith & Neumann, 2005) – in which human thinking, emotion, and routes to appraisal are defined in terms of an interplay between two distinct systems of psychological processing – this thesis aimed to examine a) the cognitive mechanisms underlying the essential yet poorly understood paradox of losing oneself in the music on the one hand, and the act of meta-awareness (i.e., rational and controlled sense of self) on the other, b) its corresponding psycho-phenomenological profile(s) when listening intentionally to self-chosen music, and c) the different potential of state and trait aspects of absorption and meta-awareness in predicting three indicators of the aesthetic response to music: enjoyment (a purely pleasurable response), lasting impression (a meaningful response related to mixed emotion), and behavioral intention (future-planned seeking/ avoidance response). Moreover, a dynamically-conceived conceptualization of absorption was proposed in terms of a temporary phase taking place amidst a variety of other cognitive responses to music, including concentration, mind wandering, and mindfulness. Finally, a questionnaire commonly-used for assessing alterations in consciousness (Phenomenology of Consciousness Inventory; Pekala, 1991) was evaluated in the context of music listening, before using it in the development of a self-report questionnaire aimed at measuring absorptive states in or by music. To this end, a quantitative empirical research method (state and trait questionnaires) was employed in a series of online surveys, using self-selected music as well as pre-determined music by the researcher as stimulus, together approaching a naturalistic listening setting.
Situated within an overarching neurocognitive model for music engagement and consistent with several aesthetic theories converging (Benson, 1993; Dewey, 2005; Wolf, 2013), aesthetic absorption was conceptualized as, and later confirmed to be, structured by experiential and meta-consciousness or – in terms of dual process terminology – intuitive type I and reflective type II processing. Two forms of music absorption were empirically identified and labeled as zoning in and tuning in (cf. Schooler, 2007). These experience profiles distinguished themselves significantly in terms of the degree in which a music listener maintained his or her meta-awareness, assessed via volitional control, rationality, self-awareness, and memory of the previous event. The overall pattern of consciousness parameters of both types of absorbed listening are suggestive of a unique interchanging between brain networks for intuitive processing and areas related to self-reference, -awareness and -control. The distinction between zoning in and tuning in was further found to be strongly related to the quality of affective state (i.e., positive vs. mixed emotions). These emotions modulate the experiential intensity of absorption, suggesting this experience to be an affect-biased type of attention. Based on the feelings-as-information theory (Schwarz, 2011), postulating that positive emotions (e.g., happiness) are differently processed than negatively-tinted types of emotions (e.g., nostalgia), it was concluded that music-induced rumination (a negatively-valenced experience related to the self and represented by the feeling of sadness) ‘competes’ with higher-order functions relevant to meta-awareness. From this perspective, the two found absorption types match conceptually with the positively-tinged self-reflection and negatively-tinged self-rumination as two different types of self-focused introspection (Takano & Tanno, 2009; Trapnell & Campbell, 1999). Further examining the construct’s latent structure, it was shown that being absorbed by music is a continuous phenomenon; a matter of ‘more-or-less’ involvement rather than a ‘unique state of mind’. This finding cautions against subtyping absorption experiences as being qualitatively distinct, and assuming it to be guided by ‘special’ mechanisms. Consequently, determining ‘music absorbers’ is a matter of imprecise estimation rather than being marked by a clear observable onset. Finally, as expected, an absorbed state of mind – operationalized here as a multidimensional bifactor model – completely mediated the effect of trait absorption, and was a good predictor for enjoyment, lasting impression, and behavioral intention. Whereas absorption and enjoyment were found to have a mutual positive effect on each other, absorption and meta-awareness were found to be unrelated to each other. Also, meta-awareness contributed little to aesthetic appreciation. The results confirm the need for a dynamic approach to the relationship between state absorption and enjoyment; the one-directional approach common in many research reports does not seem to fully capture the relationship between them. Future research should examine whether the same applies for absorption and meta-awareness, preferably making use of more advanced measures for the latter.
Taken together, this dissertation shows the potential of including the interplay between the trait and state constructs of absorption and meta-awareness in order to better understand the mechanisms underlying aesthetic experiences with music. The present work demonstrated that these two constructs should not be conflated, but, in terms of dual processing, that they represent different levels of consciousness. Moreover, this thesis underlined the power of absorption not only to evoke short-lived pleasurable experiences, but also to stimulate long-lasting impressions. Knowing more about absorbed listening and its potential effects, learning to consciously recognize it as it happens, and perhaps regulate and maintain its positive consequences (i.e., savoring), could further improve the way we engage ourselves with music or other aesthetic objects. Only then could we engage in behavior that we’re sure would make us happy rather than seeking out experiences which we hope would make us happy.
Finally, dual process approach and measures provided by research on altered-states-of-consciousness (ASC) experiences offer new and fruitful perspectives to conceptualize aesthetic absorption and examine its mechanisms. Several major research questions lie ahead in understanding the phenomenological experience and aesthetic role of absorption, including the future comparison between subjective experiences of ASCs across varying music and non-music induction methods (e.g., hypnosis), listening conditions (e.g., live concert experience), and musical ‘cultures’ (human societies, musical styles, classes).
Whereas many writers across all times and cultures have written about the potential aesthetic effects of music experiences which could be labeled as absorption, only limited empirical research has been done on the state aspects of this fascinating aspect of human involvement. What is more, there are still few tested models which explain how people can be absorbed by a piece of music as well as continue to be third-person observers monitoring and even reflecting on that same musical experience.
Adopting a dual process approach – in which human thinking, emotion, and routes to appraisal are defined in terms of an interplay between two distinct systems of psychological processing – this thesis aimed to examine a) the cognitive mechanisms underlying the paradox of losing oneself in the music on the one hand, and meta-awareness on the other, b) its corresponding psychophenomenological profile(s) when listening intentionally to self-chosen music, and c) the different potential of state and trait aspects of absorption and meta-awareness in predicting three indicators of the aesthetic response to music: enjoyment, lasting impression, and behavioral intention.
To this end, a quantitative empirical research method (state and trait questionnaires) was employed in a series of online surveys, using self-selected music as well as pre-determined music by the researcher as stimulus, together approaching a naturalistic listening setting.Aesthetic absorption was confirmed to be structured– in terms of dual process terminology – by intuitive type I and reflective type II processing. Two forms of music absorption were empirically
identified and labeled as zoning in and tuning in. These experience profiles distinguished themselves significantly in terms of the degree in which a music listener maintained his or her meta-awareness, assessed via volitional control, rationality, self-awareness, and memory of the previous event. The overall pattern of consciousness parameters of both types of absorbed listening are suggestive of a unique interchanging between brain networks for intuitive processing and areas related to self-reference, -awareness and -control. The distinction between zoning in and tuning in was further found to be strongly related to the quality of affective state.
These emotions modulate the experiential intensity of absorption, suggesting this experience to be an affect-biased type of attention. Based on the feelings-as-information theory, postulating that positive emotions are differently processed than negatively-tinted types of emotions, it was
concluded that music-induced rumination ‘competes’ with higher-order functions relevant to meta-awareness. From this perspective, the two found absorption types match conceptually with the positively-tinged self-reflection and negatively-tinged self-rumination as two different types of self-focused introspection. It was also shown that being absorbed by music is a continuous phenomenon; a matter of ‘more-or-less’ involvement rather than a ‘unique state of mind’. Consequently, determining ‘music absorbers’ is a matter of imprecise estimation rather than being marked by a clear observable onset. Finally, as expected, an absorbed state of mind - operationalized here as a multidimensional bifactor model – completely mediated the effect of trait absorption, and was a good predictor for enjoyment, lasting impression, and behavioral intention.
Whereas absorption and enjoyment were found to have a mutual positive effect on each other, absorption and meta-awareness were found to be unrelated to each other. Also, meta-awareness contributed little to aesthetic appreciation. The results confirm the need for a dynamic approach to the relationship between state absorption and enjoyment; the one-directional approach common in many research reports does not seem to fully capture the relationship between them. Taken together, this dissertation shows the potential of including the interplay between the trait and state constructs of absorption and meta-awareness in order to better understand the mechanisms underlying aesthetic experiences with music. The present work demonstrated that these two constructs should not be conflated. Moreover, this thesis underlined the power of absorption not only to evoke short-lived pleasurable experiences, but also to stimulate longlasting impressions. Knowing more about absorbed listening and its potential effects, learning to consciously recognize it as it happens, and perhaps regulate and maintain its positive consequences (i.e., savoring), could further improve the way we engage ourselves with music or other aesthetic objects. Only then could we engage in behavior that we’re sure would make us happy rather than seeking out experiences which we hope would make us happy.
With the discovery of light beyond human visibility, scientists strove to extend the range of observation to invisible parts of the light’s spectrum. Realising that light of all frequencies is part the same physical phenomenon, brought a leap in understanding about electromagnetic waves. With the development of more advanced technology, detectors with higher sensitivity for adjacent frequencies to the visible were built. From this, with each new observable wavelength, more insight into otherwise invisible processes and phenomenons were observed. Hand in hand with this went the enhancement of the output power of corresponding sources. This has lead to higher sensitivity setups throughout the spectrum, leading to observations which have given a deeper understanding in various fields of science. Nowadays, detectors and emitters in many different regions of the invisible electro magnetic spectrum have found their way in our every day life. Innovations in technology has lead to practical applications such as X-rays in medicine, motion sensors and remote controls using infrared light, distance sensors and data transmission using radar and radio devices. The frequency regions above infrared are optically generated and below radar can be produced using electric methods. There is no straight line that separates these frequencies. There rather is a whole intermediate region known as the terahertz (THz) regime. Due to the lack of sensitive detectors and efficient sources, the THz frequency region has not been exploited for application use on a widespread basis so far. It combines properties from the surrounding frequency ranges which make it an ideal spectrum for various applications. Consequently, THz radiation and THz imaging are active fields of research.
The work presented in this thesis consists of the development and testing of novel THz imaging concepts, which uses a THz antenna coupled field effect transistor (TeraFET) detector. Two detection principles are applied using two different optical setups. The first uses a pulsed optical parametric oscillator (OPO) THz source where the optical output power is detected. The source relies on a nonlinear effect of a lithium niobate crystal to generate tunable THz pulses from a Q-switched pump laser. The THz signal is detected and amplified by a double stage operational amplifier for monitoring the real time 20 ns pulses on an oscilloscope where a signal to noise ratio (SNR) of ⇠ 25 at a frequency range from 0.75 to 1.1 THz is reached. Imaging of the area of interest with a resolution of 1.2 mm is achieved through raster scanning of the THz pulses. Also spectroscopy with a frequency resolution of ⇠ 50 GHz is demonstrated using a para-aminobenzoic acid sample. The second setup utilises two synchronised electronic multiplier chain sources where their output is mixed on the detector. To form a heterodyne detection setup, the intermediate frequency is fed to a lock-in amplifier which then amplifies the so called beat signal from the TeraFET detector. One source is fixed relative to the detector even through scanning to ensure a stable signal. This detection method allows for amplitude and phase detection for every scanning position, making numerical light field propagation and object reconstruction possible. Numerical focussing is a key feature achieving a lateral resolution of the input transmittance of ⇡ 2 mm.
After the introduction, the second chapter describes the setup, measurement results and challenges which arise using a TeraFET together with the pulsed THz source “Firefly-THz”. In the description of the setup, special attention is given to the shielding of the detector and the electronics. General findings discuss first the overall performance and later spectroscopy and imaging as application examples. Another subsection continues with potential noise sources before the chapter is concluded. Chapter three expands on the topic of Fourier optics from a theoretical point of view. First, parts of the theory of the Fourier Transform (FT) are set out for the reader and how the Fast Fourier Transform (FFT) results from the Discrete Fourier Transform (DFT). This approach is used for theoretical considerations and the implementation of a Fourier optic script that allows for numerical investigations on electro magnetic field propagation through an optical system. The boundary conditions are chosen to be practical relevant to make predictions on measurements presented in chapter four. The following fourth chapter describes the realisation of a heterodyne THz detection setup. Before the measurement results are presented, the setup and its electric configuration are shown. The results come close to the analytical predictions so that the same algorithm which propagates the field from an object to the Fourier plane is used to propagate the measured field back to the object. The influence of phase noise on the measurement results are discussed before simulation and measurement is compared. The last chapter in this thesis concludes on the findings in the pulsed THz detection and the heterodyne THz Fourier imaging and gives an outlook for both configurations.
The present study aimed to assess the tissue response to the SYMBIOS® resorbable collagen membrane SR, which is derived from bovine Achilles tendon, and compare it to the physiological wound healing of a sham operation as a control.
An ex vivo analysis was performed using injectable platelet-rich fibrin (i-PRF), that is gained by the centrifugation of human venous blood and contains fibrin, leukocytes and platelets, to elucidate the membrane permeability and interactions with human cells and plasma proteins. In the in vivo study, a subcutaneous implantation model was established in Wistar rats to evaluate the cellular reactions for up to 30 days after membrane implantation. Histochemical, immunohistochemical and histomorphometric analyses were performed to assess the cellular inflammatory response, vascularization pattern and cell infiltration capacity.
In the ex vivo study, i-PRF components including fibrin, leukocytes and platelets penetrated the membrane after just 15 minutes. Within the observation period, the cellular reaction in the early phase, which included the first 3 days, produced only mononuclear cells. From 10 to 30 days , the formation of multinucleated giant cells (MNGCs) was induced by the collagen membrane. CD-68 positive cells (macrophages) occurred in a high number on day 3, and the number decreased over time up to day 30. Along with the reduction in the number of CD-68 positive cells, the number of MNGCs increased significantly. The presence of MNGCs was accompanied by significantly increased vascularization within the central region of the membrane, and only mononuclear cells (MNCs) did not produce vascularization. In contrast, the accumulated MNGCs were located on the membrane surface. The control group reflected the physiological process of wound healing, as MNGCs did not form over the 30 day period, and a significantly lower level of vascularization was observed compared with the test group.
This finding showed dynamic changes in the cellular reaction, which indicated a relationship between macrophage fusion and MNGC formation, and vascularization of the collagen membrane is circumstantial evidence of a reaction to a foreign body. However, the collagen membrane was able to maintain its structure and integrity over time, showing no signs of premature breakdown and disintegration due to the specific porosity of its membrane structure.
Therefore, we questioned whether the biomaterial-induced formation of MNGCs should be accepted as a biomaterial-induced cellular reaction that is able to restore vascularization or as an adverse reaction. Therefore, extensive preclinical and clinical studies are needed to investigate the type of MNGCs that form in response to the membrane material studied here.
Due to the resurrection of data-hungry models (such as deep convolutional neural nets), there is an increasing demand for large-scale labeled datasets and benchmarks in the computer vision fields (CV). However, collecting real data across diverse scene contexts along with high-quality annotations is often expensive and time-consuming, especially for detailed pixel-level label prediction tasks such as semantic segmentation, etc. To address the scarcity of real-world training sets, recent works have proposed the use of computer graphics (CG) generated data to train and/or characterize performance of modern CV systems. CG based virtual worlds provide easy access to ground truth annotations and control over scene states. Most of these works utilized training data simulated from video games and pre-designed virtual environments and demonstrated promising results. However, little effort has been devoted to the systematic generation of massive quantities of sufficiently complex synthetic scenes for training scene understanding algorithms. In this work, we develop a full pipeline for simulating large-scale datasets along with per-pixel ground truth information. Our simulation pipeline constitutes of mainly two components: (a) a stochastic scene generative model that automatically synthesizes traffic scene layouts by using marked point processes coupled with 3D CAD objects and factor potentials, (b) an annotated-image rendering tool that renders the sampled 3D scene as RGB image with a chosen rendering method along with pixel-level annotations such as semantic labels, depth, surface normals etc. This pipeline is capable of automatically generating and rendering a potentially infinite variety of outdoor traffic scenes that can be used to train convolutional neural nets (CNN).
However, several recent works, including our own initial experiments demonstrated that the CV models that are trained naively on simulated data lack generalization capabilities to real-world scenes. This opens up several fundamental questions about what is it lacking in simulated data compared to real data and how to use it effectively. Furthermore, there has been a long debate since 1980’s on the usefulness of CG generated data for tuning CV systems. Primarily, the impact of modeling errors and computational rendering approximations, due to various choices in the rendering pipeline, on trained CV systems generalization performance is still not clear. In this thesis, we take a case study in the context of traffic scenarios to empirically analyze the performance degradations when CV systems trained with virtual data are transferred to real data. We first explore system performance tradeoffs due to the choice of the rendering engine (e.g., Lambertian shader (LS), ray-tracing (RT), and Monte-Carlo path tracing (MCPT)) and their parameters. A CNN architecture, DeepLab, that performs semantic segmentation, is chosen as the CV system being evaluated. In our case study, involving traffic scenes, a CNN trained with CG data samples generated with photorealistic rendering methods (such as RT or MCPT), shows already a reasonably good performance on real-world testing data from CityScapes benchmark. Use of samples from an elementary rendering method, i.e., LS, degraded the performance of CNN by nearly 20%. This result conveys that training data must be photorealistic enough for better generalizability of the trained CNN models. Furthermore, the use of physics-based MCPT rendering improved the performance by 6% but at the cost of more than three times the rendering time. This MCPT generated dataset when augmented with just 10% of real-world training data from CityScapes dataset, the performance levels achieved are comparable to that of training CNN with the complete CityScapes dataset.
The next aspect we study in the thesis involves the impact of choice of parameter settings of scene generation model on the generalization performance of CNN models trained with the generated data. Towards this end, we first propose an algorithm to estimate our scene generation model parameters given an unlabeled real world dataset from the target domain. This unsupervised tuning approach utilizes the concept of generative adversarial training, which aims at adapting the generative model by measuring the discrepancy between generated and real data in terms of their separability in the space of a deep discriminatively-trained classifier. Our method involves an iterative estimation of the posterior density of prior distributions for the generative graphical model used in the simulation. Initially, we assume uniform distributions as priors over parameters of a scene described by our generative graphical model. As iterations proceed the uniform prior distributions are updated sequentially to distributions for the simulation model parameters that leads to simulated data with statistics that are closer to the distributions of the unlabeled target data.
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Microsporidia are a group of parasites that infect a wide range of species, many of which play important roles in agriculture and human disease. At least 14 microsporidian species have been confirmed to cause potentially lifethreatening infectious diseases in both immunocompromised and immunocompetent humans. Approximately 1,400 species of microsporidia have been described. Depending on their host and habitat they are classified into three groups, the aquasporidia, the terresporidia and the marinosporidia.
Microsporidia were originally classified as fungi by Naegeli (1857). However, their lack of typical eukaryotic components – such as mitochondria, Golgi bodies or peroxisomes – suggested to place the microsporidia together with other amitochondriate protists within the Archezoa kingdom. This "microsporidia-early" hypothesis was further supported by molecular phylogenies inferred from individual genes. Despite this evidence, the placement of microsporidia as an early branching eukaryote remained a topic for debate. The phylogeny of microsporidia is prone to suffer from biases in their reconstruction. The high evolutionary rate of microsporidian proteins tends to place these proteins together with other fast evolving lineages, a phenomenon known as long-branch attraction. In 1996, the first molecular phylogenetic studies placed the microsporidia inside the fungi.
Subsequently, several further studies located the microsporidia at different positions inside the fungal clade. Since then, microsporidia have been considered as members of the Ascomycota, Zygomycota, Cryptomycota, or as a sister group to the Ascomycota and Basidiomycota, or even as the sister group of all fungi.
The difficulties in determining the evolutionary origin of microsporidia are not only caused by their lack of several cellular components but also by their reduced genomes and metabolism. Being obligate intracellular parasites, microsporidia successfully reduced their genome sizes, down to the range of bacteria. As the smallest eukaryotic genome described so far, the genome of Encephalitozoon intestinalis is just 2.3 Mbp, about half the size of the one of Escherichia coli. Due to their low number of protein coding genes (less than 4,000), microsporidia are thought to retain only genes essential for their survival and development. Furthermore, several key metabolic pathways are missing in the microsporidia, such as the citric acid cycle, oxidative phosphorylation, or the de novo biosynthesis of nucleotides. As a result they are in an obligatory dependence on many primary metabolites from the hosts. However, the presence of hsp70 protein suggests a more complex genome of the microsporidian ancestor. Consequently, the small microsporidian genomes and the reduced metabolism would be consequences of a secondary loss process that molded the contemporary microsporidia from a functionally more complex ancestral species. However, it remains unclear whether the last common ancestor (LCA) of the microsporidia was already reduced, or whether the genome compaction was lineage-specific and started from a more complex LCA.
We investigated the evolutionary history of the contemporary microsporidia through the reconstruction and analysis of their LCA. As a first step in our analysis, we have developed and implemented a software facilitating an intuitive data analysis of the large presence absence-patterns resulting from the tracing of microsporidian proteins in gene sets of many different species. These so called phylogenetic profiles can now be dynamically visualized and explored with PhyloProfile. The software allows the integration of other additional information layers into the phylogenetic profile, such as the similarity of feature architecture (FAS) between the protein under study and its orthologs. The FAS score can be displayed along the presence-absence pattern, which can help to identify orthologs that have likely diverged in function. PhyloProfile closes the methodological gap that existed between tools to generate large phylogenetic profiles to delineate the evolutionary history and the contemporary distribution of large – and ultimately complete – gene sets, and the more function-oriented analysis of individual protein. In the next step we tackled the problem of how to transfer functional annotation from one protein to another. We have developed HamFAS that integrates a targeted ortholog search based on the HaMStR algorithm with a weighted assessment of feature architecture similarities (FAS) between orthologs. In brief, for a seed protein we identify orthologs in reference species in which proteins have been functionally annotated based on manually curated assignments to KEGG Ortholog (KO) groups. The FAS scores between the orthologs and seed proteins are calculated. Subsequently, we compute pairwise FAS scores for all reference proteins within a KO group. A group's mean FAS score serves then as cutoff that must be exceeded to warrant transfer of its KO identifier to the seed. A benchmark using a manually curated yeast protein set showed that HamFAS yields the best precision (98.5%) when compared with two state-of-the-art annotation tools, KAAS and BlastKOALA. Furthermore, HamFAS achieves a higher sensitivity. On average HamFAS annotates almost 50% more proteins than KAAS or BlastKOALA.
With this extended bioinformatics toolbox at hand, we aimed at reconstructing the evolutionary history of the microsporidia. We generated a robust phylogeny of microsporidia using a phylogenomics approach. As a data basis, we identified a set of microsporidian proteins encoded by 80 core genes with one-to-one orthologs. A maximum likelihood analysis of this data
with 48 fungi and additionally in 13 species from more distantly related such as animals and plants combined in a supermatrix strongly supported the hypothesis that microsporidia form the sister group of the fungi. We confirmed that the data explains this microsporidia-fungi relationship significantly better than any other of the previously proposed phylogenetic hypotheses.
On the basis of this phylogeny, and of the phylogenetic profiles of microsporidian proteins, we then focused on reconstructing the dynamics microsporidian genome evolution. Between 2% of the proteins in the compact microsporidia Encephalitozoon intestinalis and up to 49% of the proteins of Edhazardia aedis are private for individual microsporidian species. A comparison of the sequence characteristics of these proteins to that of proteins with orthologs in other microsporidian species revealed individual differences. Yet, without further evidences it remains unclear whether these private genes are indeed lineage-specific innovations contributing to the adaptation of each microsporidium to its host, or whether these are artifacts introduced in the process of gene annotation. A total of 14,410 microsporidian proteins could then be grouped into 1605 orthologous groups that can be traced back to the last common ancestor of the microsporidia (LCA set). We found that 94% of the microsporidian LCA proteins could be tracked back to the last eukaryotic common ancestor. The high evolutionary age of these proteins, together with the resistance against gene loss in the microsporidia suggests that the corresponding functions are essential for eukaryotic life. Further 3% of the LCA proteins could be dated to the common ancestor microsporidia share with the fungi. Only 3% of the LCA proteins appear as microsporidia specific inventions. These proteins are potentially of importance for the evolutionary of the obligate parasitic lifestyle nowadays shared by all microsporidia.
The functional annotation and metabolic pathway analysis of the microsporidian LCA protein set gave us more insight into the adaptation of the microsporidia to their parasitic lifestyle and the origin of the microsporidian genome reduction. The presence of E1 and E3 components of the pyruvate dehydrogenase complex and the mitochondrial hsp70 protein support an ancestral presence of mitochondria in the ancestral microsporidia. In addition, several ancient proteins that complement gapped metabolic pathways were found in the microsporidian LCA. They suggested a more complex genome and metabolism in the LCA. However, our reconstruction of the metabolic network of the microsporidian LCA still lacks many main pathways. For example, the TCA cycle for effective energy production, and key enzymes that are required for in vivo synthesis of critical metabolites like purines and pyrimidines appear absent. We therefore find that the parasitic lifestyle and the genome reduction already occurred in the microsporidian LCA. This ancestral state was followed by further losses and gains during the evolution of each individual microsporidian lineage.