Techniques and Methods for a multi-scale analysis of neuromuscular fatigue

This thesis proposes an integrated holistic approach to the study of neuromuscular fatigue in order to encompass all the causes and all the consequences underlying the phenomenon. Starting from the metabolic processes occurring at the cellular level, the reader is guided toward the physiological changes at the motorneuron and motor unit level and from this to the more general biomechanical alterations. In Chapter 1 a list of the various definitions for fatigue spanning several contexts has been reported. In Chapter 2, the electrophysiological changes in terms of motor unit behavior and descending neural drive to the muscle have been studied extensively as well as the biomechanical adaptations induced. In Chapter 3 a study based on the observation of temporal features extracted from sEMG signals has been reported leading to the need of a more robust and reliable indicator during fatiguing tasks. Therefore, in Chapter 4, a novel bi-dimensional parameter is proposed. The study on sEMG-based indicators opened a scenario also on neurophysiological mechanisms underlying fatigue. For this purpose, in Chapter 5, a protocol designed for the analysis of motor unit-related parameters during prolonged fatiguing contractions is presented. In particular, two methodologies have been applied to multichannel sEMG recordings of isometric contractions of the Tibialis Anterior muscle: the state-of-the-art technique for sEMG decomposition and a coherence analysis on MU spike trains. The importance of a multi-scale approach has been finally highlighted in the context of the evaluation of cycling performance, where fatigue is one of the limiting factors. In particular, the last chapter of this thesis can be considered as a paradigm: physiological, metabolic, environmental, psychological and biomechanical factors influence the performance of a cyclist and only when all of these are kept together in a novel integrative way it is possible to derive a clear model and make correct assessments.

Obsessed With Work: A multi-causal and multi-rater approach to workaholism

Workaholism is defined as the combination of two underlying dimensions: working excessively and working compulsively. The present thesis aims at achieving the following purposes: 1) to test whether the interaction between environmental and personal antecedents may enhance workaholism; 2) to develop a questionnaire aimed to assess overwork climate in the workplace; 3) to contrast focal employees’ and coworkers’ perceptions of employees’ workaholism and engagement. Concerning the first purpose, the interaction between overwork climate and person characteristics (achievement motivation, perfectionism, conscientiousness, self-efficacy) was explored on a sample of 333 Dutch employees. The results of moderated regression analyses showed that the interaction between overwork climate and person characteristics is related to workaholism. The second purpose was pursued with two interrelated studies. In Study 1 the Overwork Climate Scale (OWCS) was developed and tested using a principal component analysis (N = 395) and a confirmatory factor analysis (N = 396). Two overwork climate dimensions were distinguished, overwork endorsement and lacking overwork rewards. In Study 2 the total sample (N = 791) was used to explore the association of overwork climate with two types of working hard: work engagement and workaholism. Lacking overwork rewards was negatively associated with engagement, whereas overwork endorsement showed a positive association with workaholism. Concerning the third purpose, using a sample of 73 dyads composed by focal employees and their coworkers, a multitrait-multimethod matrix and a correlated trait-correlated method model, i.e. the CT-C(M–1) model, were examined. Our results showed a considerable agreement between raters on focal employees' engagement and workaholism. In contrast, we observed a significant difference concerning the cognitive dimension of workaholism, working compulsively. Moreover, we provided further evidence for the discriminant validity between engagement and workaholism. Overall, workaholism appears as a negative work-related state that could be better explained by assuming a multi-causal and multi-rater approach.

LPS-induced modifications in spontaneous network activity causes neuronal apoptosis in neonatal cerebral cortex

During the perinatal period the developing brain is most vulnerable to inflammation. Prenatal infection or exposure to inflammatory factors can have a profound impact on fetal neurodevelopment with long-term neurological deficits, such as cognitive impairment, learning deficits, perinatal brain damage and cerebral palsy. Inflammation in the brain is characterized by activation of resident immune cells, especially microglia and astrocytes whose activation is associated with a variety of neurodegenerative disorders like Alzheimer´s disease and Multiple sclerosis. These cell types express, release and respond to pro-inflammatory mediators such as cytokines, which are critically involved in the immune response to infection. It has been demonstrated recently that cytokines also directly influence neuronal function. Glial cells are capable of releaseing the pro-inflammatory cytokines MIP-2, which is involved in cell death, and tumor necrosis factor alpha (TNFalpha), which enhances excitatory synaptic function by increasing the surface expression of AMPA receptors. Thus constitutively released TNFalpha homeostatically regulates the balance between neuronal excitation and inhibition in an activity-dependent manner. Since TNFalpha is also involved in neuronal cell death, the interplay between neuronal activity MIP-2 and TNFalpha may control the process of cell death and cell survival in developing neuronal networks. An increasing body of evidence suggests that neuronal activity is important in the regulation of neuronal survival during early development, e.g. programmed cell death (apoptosis) is augmented when neuronal activity is blocked. In our study we were interested on the impact of inflammation on neuronal activity and cell survival during early cortical development. To address this question, we investigated the impact of inflammation on neuronal activity and cell survival during early cortical development in vivo and in vitro. Inflammation was experimentally induced by application of the endotoxin lipopolysaccharide (LPS), which initiates a rapid and well-characterized immune response. I studied the consequences of inflammation on spontaneous neuronal network activity and cell death by combining electrophysiological recordings with multi-electrode arrays and quantitative analyses of apoptosis. In addition, I used a cytokine array and antibodies directed against specific cytokines allowing the identification of the pro-inflammatory factors, which are critically involved in these processes. In this study I demonstrated a direct link between inflammation-induced modifications in neuronal network activity and the control of cell survival in a developing neuronal network for the first time. Our in vivo and in vitro recordings showed a fast LPS-induced reduction in occurrence of spontaneous oscillatory activity. It is indicated that LPS-induced inflammation causes fast release of proinflammatory factors which modify neuronal network activity. My experiments with specific antibodies demonstrate that TNFalpha and to a lesser extent MIP-2 seem to be the key mediators causing activity-dependent neuronal cell death in developing brain. These data may be of important clinical relevance, since spontaneous synchronized activity is also a hallmark of the developing human brain and inflammation-induced alterations in this early network activity may have a critical impact on the survival of immature neurons.

Identity dynamics and the emergence of new organizational arrangements: A multi-level study

Organizational and institutional scholars have advocated the need to examine how processes originating at an individual level can change organizations or even create new organizational arrangements able to affect institutional dynamics (Chreim et al., 2007; Powell & Colyvas, 2008; Smets et al., 2012). Conversely, research on identity work has mainly investigated the different ways individuals can modify the boundaries of their work in actual occupations, thus paying particular attention to ‘internal’ self-crafting (e.g. Wrzesniewski & Dutton, 2001). Drawing from literatures on possible and alternative self and on positive organizational scholarship (e.g., Obodaru, 2012; Roberts & Dutton, 2009), my argument is that individuals’ identity work can go well beyond the boundaries of internal self-crafting to the creation of new organizational arrangements. In this contribution I analyze, through multiple case studies, healthcare professionals who spontaneously participated in the creation of new organizational arrangements, namely health structures called Community Hospitals. The contribution develops this form of identity work by building a grounded model. My findings disclose the process that leads from the search for the enactment of different self-concepts to positive identities, through the creation of a new organizational arrangement. I contend that this is a particularly complex form of collective identity work because it requires, to be successful, concerted actions of several internal, external and institutional actors, and it also requires balanced tensions that – at the same time - enable individuals’ aspirations and organizational equilibrium. I name this process organizational collective crafting. Moreover I inquire the role of context in supporting the triggering power of those unrealized selves. I contribute to the comprehension of the consequences of self-comparisons, organizational identity variance, and positive identity. The study bears important insights on how identity work originating from individuals can influence organizational outcomes and larger social systems.

Methodologies for Synthesizable Programmable Devices based on Multi-Stage Switching Networks

Nowadays the rise of non-recurring engineering (NRE) costs associated with complexity is becoming a major factor in SoC design, limiting both scaling opportunities and the flexibility advantages offered by the integration of complex computational units. The introduction of embedded programmable elements can represent an appealing solution, able both to guarantee the desired flexibility and upgradabilty and to widen the SoC market. In particular embedded FPGA (eFPGA) cores can provide bit-level optimization for those applications which benefits from synthesis, paying on the other side in terms of performance penalties and area overhead with respect to standard cell ASIC implementations. In this scenario this thesis proposes a design methodology for a synthesizable programmable device designed to be embedded in a SoC. A soft-core embedded FPGA (eFPGA) is hence presented and analyzed in terms of the opportunities given by a fully synthesizable approach, following an implementation flow based on Standard-Cell methodology. A key point of the proposed eFPGA template is that it adopts a Multi-Stage Switching Network (MSSN) as the foundation of the programmable interconnects, since it can be efficiently synthesized and optimized through a standard cell based implementation flow, ensuring at the same time an intrinsic congestion-free network topology. The evaluation of the flexibility potentialities of the eFPGA has been performed using different technology libraries (STMicroelectronics CMOS 65nm and BCD9s 0.11μm) through a design space exploration in terms of area-speed-leakage tradeoffs, enabled by the full synthesizability of the template. Since the most relevant disadvantage of the adopted soft approach, compared to a hardcore, is represented by a performance overhead increase, the eFPGA analysis has been made targeting small area budgets. The generation of the configuration bitstream has been obtained thanks to the implementation of a custom CAD flow environment, and has allowed functional verification and performance evaluation through an application-aware analysis.

Prozessevaluation einer kognitiv-verhaltenstherapeutischen Gruppentherapie bei Diabetes und Depression : Entwicklung und Validierung der Patienten- und Therapeuten- Gruppentherapiestundenbögen (GTS-P, GTS-T, GTS-TP) zur Vorhersage des Therapieerfolgs

Untersucht werden Prozess-Ergebnis-Zusammenhänge einer kognitiv-verhaltenstherapeutischen Gruppentherapie für Diabetes und Depression im Rahmen der DAD-Studie. rnAufgrund des Mangels an geeigneten Erhebungsinstrumenten der validen, ökonomischen und komplementären Sitzungsbewertung von Gruppenpatienten und -therapeuten wurden angelehnt an einen Patienten- (GTS-P) zwei Therapeutenstundenbögen entwickelt: der GTS-T zur Bewertung der Gesamtgruppe und der GTS-TP zur Bewertung einzelner Patienten. Die GTS-Bögen zeigen bei der Überprüfung der Testgüte insgesamt gute Itemparameter und Reliabilitäten. Das in den exploratorischen Faktorenanaylsen des GTS-P identifizierte zweifaktorielle Modell (1. wahrgenommene Zuversicht hinsichtlich der Gruppentherapie, 2. wahrgenommene persönliche Beteiligung) kann in den konfirmatorischen Faktorenanalysen bestätigt werden. Dazu wurden GTS-P-Daten aus einer Untersuchung mit Patienten mit somatoformen Störungen (Schulte, 2001) einbezogen. Den Ergebnissen der Item- und Faktorenanalysen folgend, wurden zwei Items des GTS-P und zwei weitere Items des GTS-T aus den Instrumenten ausgeschlossen. Für den GTS-T zeigt sich eine einfaktorielle, für den GTS-TP eine zum GTS-P parallele zweifaktorielle Struktur. rnIn den Mehrebenenanalysen zur Vorhersage des Therapieergebnisses (Post-Depressionssymptomatik) zeigt sich die Skala Zuversicht des GTS-P zu Therapiebeginn (1.-4. Sitzung) kontrolliert an der Skala Beteiligung und der Prä-Symptomatik, als valider Prädiktor. Das Item 5 „Anregungen“ (Skala Zuversicht) und Item 2 „Aktive Mitwirkung“ (Skala Beteiligung) sind am stärksten an diesem Effekt beteiligt, da diese Itemkombination das Therapieergebnis ebenfalls valide vorhersagen kann. Die Prognose ist schon durch die Werte der ersten Gruppentherapiesitzungen in der Remoralisierungsphase (Howard et al., 1993) möglich und verbessert sich nicht bei Berücksichtigung aller 10 Gruppensitzungen. Die Therapeutenbögen zeigen keine prädiktive Validität. Bedeutsame Zusammenhänge der Patienten- und Therapeutenbewertungen finden sich lediglich für den GTS-P und GTS-TP. Weitere Prädiktoren, wie der Diabetestyp, Diabeteskomplikationen und die Adhärenz, konnten nicht zur Verbesserung der Vorhersage beitragen. Für sekundär überprüfte Kriterien gelang die Prognose lediglich für ein weiteres Maß der Depressionssymptomatik und für eine Gesamtbewertung der Gruppentherapie durch die Patienten zu Therapieende. Bei der deskriptiven Betrachtung der Prozessqualität der DAD-Gruppentherapien zeigen sich positive, über den Verlauf der Gruppe zunehmende und nach Therapiephasen differenzierbare Bewertungsverläufe. rnDie Ergebnisse der Studie sprechen für die Relevanz von unspezifischen Wirkfaktoren für das Therapieergebnis von kognitiv-behavioralen Gruppentherapien. Die von den Gruppenpatienten wahrgenommene Zuversicht und Beteiligung als Zeichen der Ansprechbarkeit auf die Therapie sollte mit Hilfe von Stundenbögen, wie den GTS-Bögen, von Gruppentherapeuten zur Prozessoptimierung und Prävention von Therapieabbrüchen und Misserfolgen beachtet werden. rn

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.

Experimentelle Untersuchung von Phasenübergängen im kolloidalen Modellsystem harter Kugeln

Die vorliegende Arbeit behandelt den fluid-kristallinen Phasenübergang sowie den Glasübergang anhand von kolloidalen Hart-Kugel(HK)-Modellsystemen. Die Untersuchungen erfolgen dabei im Wesentlichen mit unterschiedlichen Lichtstreumethoden und daher im reziproken Raum. rnDie Analyse der Kristallisationskinetik zeigt, dass es bei der Kristallisation zu signifikanten Abweichungen vom Bild der klassischen Nukleationstheorie (CNT) kommt. Diese geht von einem einstufigen Nukleationsprozess aus, wohingegen bei den hier durchgeführten Experimenten ein mehrstufiger Prozess beobachtet wird. Vor der eigentlichen Kristallisation kommt es zunächst zur Nukleation einer metastabilen Zwischenphase, sogenannter Precursor. In einer zweiten Stufe erfolgt innerhalb der Precursor die eigentliche Nukleation der Kristallite. rnDurch weitere Analyse und den Vergleich des Kristallisations- und Verglasungsszenarios konnte das Konzept der Precursornukleation auf den Vorgang der Verglasung erweitert werden. Während die Kristallnukleation oberhalb des Glasübergangspunktes zum Erliegen kommt, bleibt der Prozess der Precursornukleation auch bei verglasenden Proben erhalten. Ein Glas erstarrt somit in einem amorphen Zustand mit lokalen Precursorstrukturen. Die Korrelation der gemessenen zeitlichen Entwicklung der strukturellen sowie der dynamischen Eigenschaften zeigt darüber hinaus, dass das bisher unverstandene Ageing-Phänomen von HK-Gläsern mit der Nukleation von Precursorn zusammenhängt.rnEin solches mehrstufiges Szenario wurde bereits in früheren Veröffentlichungen beobachtet. Die im Rahmen dieser Arbeit durchgeführten Messungen ermöglichten erstmals die Bestimmung von Kristallnukleationsratendichten (Kristall-NRD) und Ratendichten für die Precursornukleation bis über den Glasübergangspunkt hinaus. Die Kristall-NRD bestätigen die Resultate aus anderen experimentellen Arbeiten. Die weiteren Analysen der Kristall-NRD belegen, dass die fluid-kristalline Grenzflächenspannung bei der Nukleation entgegen den Annahmen der CNT nicht konstant ist, sondern mit ansteigendem Volumenbruch linear zunimmt. Die Erweiterung der CNT um eine linear zunehmende Grenzflächenspannung ermöglichte eine quantitative Beschreibung der gemessenen Kristall- sowie der Precursor-NRD, was den Schluss zulässt, dass es sich in beiden Fällen um einen Boltzmann-aktivierten Prozess handelt. rnUm die beobachteten Abweichungen des Nukleationsprozesses vom Bild der CNT näher zu untersuchen, wurden die kollektiven Partikeldynamiken in stabilen Fluiden und metastabilen Schmelzen analysiert. Im klassischen Bild wird angenommen, dass die kollektive Partikeldynamik beim Vorgang der Nukleation keine Rolle spielt. Anhand der Resultate zeigen sich Abweichungen in der Dynamik stabiler Fluide und metastabiler Schmelzen. Während die kollektive Partikeldynamik in der stabilen Schmelze von der Struktur entkoppelt ist, tritt oberhalb des Phasenübergangspunktes eine Kopplung von Struktur und Dynamik auf. Dabei treten die Abweichungen zunächst in der Umgebung des ersten Strukturfaktormaximums und somit bei den am stärksten besetzten Moden auf. Mit steigender Unterkühlung nehmen die Anzahl der abweichenden Moden sowie die Stärke der Abweichungen zu. Dieses Phänomen könnte einen signifikanten Einfluss auf den Nukleationsprozess und somit auf die Kristallisationskinetik haben. Die Analyse der Dynamik im stabilen Fluid zeigt darüber hinaus Hinweise auf eine Singularität bei Annäherung an den fluid-kristallinen Phasenübergangspunkt.rnDes Weiteren wurden im Rahmen der vorliegenden Arbeit erstmals Ratendichten für die heterogene Nukleation eines HK-Systems an einer flachen Wand mittels statischer Lichtstreuung (SLS) bestimmt. Die Ergebnisse der Messung zeigen, dass die Nukleationsbarriere der heterogenen Nukleation annähernd Null ist und folglich eine vollständige Benetzung der Wand mit einer kristallinen Monolage vorliegt. Die Erweiterung der Untersuchungen auf gekrümmte Oberflächen in Form von sphärischen Partikeln (Seeds) stellt die erste experimentelle Arbeit dar, die den Einfluss eines Ensembles von Seeds auf die Kristallisationskinetik in HK-Systemen untersucht. Die Kristallisationskinetik und die Mikrostruktur werden abhängig von Größe und Anzahldichte der Seed-Partikel signifikant beeinflusst. In Übereinstimmung mit konfokalmikroskopischen Experimenten und Simulationen spielt dabei das Radienverhältnis der Majoritäts- zur Minoritätskomponente eine entscheidende Rolle.

Hunting for warped extra dimensions via loop-induced processes

This thesis is on loop-induced processes in theories with warped extra dimensions where the fermions and gauge bosons are allowed to propagate in the bulk, while the Higgs sector is localized on or near the infra-red brane. These so-called Randall-Sundrum (RS) models have the potential to simultaneously explain the hierarchy problem and address the question of what causes the large hierarchies in the fermion sector of the Standard Model (SM). The Kaluza-Klein (KK) excitations of the bulk fields can significantly affect the loop-level processes considered in this thesis and, hence, could indirectly indicate the existence of warped extra dimensions. The analytical part of this thesis deals with the detailed calculation of three loop-induced processes in the RS models in question: the Higgs production process via gluon fusion, the Higgs decay into two photons, and the flavor-changing neutral current b → sγ. A comprehensive, five-dimensional (5D) analysis will show that the amplitudes of the Higgs processes can be expressed in terms of integrals over 5D propagators with the Higgs-boson profile along the extra dimension, which can be used for arbitrary models with a compact extra dimension. To this end, both the boson and fermion propagators in a warped 5D background are derived. It will be shown that the seemingly contradictory results for the gluon fusion amplitude in the literature can be traced back to two distinguishable, not smoothly-connected incarnations of the RS model. The investigation of the b → sγ transition is performed in the KK decomposed theory. It will be argued that summing up the entire KK tower leads to a finite result, which can be well approximated by a closed, analytical expression.rnIn the phenomenological part of this thesis, the analytic results of all relevant Higgs couplings in the RS models in question are compared with current and in particular future sensitivities of the Large Hadron Collider (LHC) and the planned International Linear Collider. The latest LHC Higgs data is then used to exclude significant portions of the parameter space of each RS scenario. The analysis will demonstrate that especially the loop-induced Higgs couplings are sensitive to KK particles of the custodial RS model with masses in the multi tera-electronvolt range. Finally, the effect of the RS model on three flavor observables associated with the b → sγ transition are examined. In particular, we study the branching ratio of the inclusive decay B → X_s γ

High precision tools for slepton pair production processes at hadron colliders

In this thesis, we develop high precision tools for the simulation of slepton pair production processes at hadron colliders and apply them to phenomenological studies at the LHC. Our approach is based on the POWHEG method for the matching of next-to-leading order results in perturbation theory to parton showers. We calculate matrix elements for slepton pair production and for the production of a slepton pair in association with a jet perturbatively at next-to-leading order in supersymmetric quantum chromodynamics. Both processes are subsequently implemented in the POWHEG BOX, a publicly available software tool that contains general parts of the POWHEG matching scheme. We investigate phenomenological consequences of our calculations in several setups that respect experimental exclusion limits for supersymmetric particles and provide precise predictions for slepton signatures at the LHC. The inclusion of QCD emissions in the partonic matrix elements allows for an accurate description of hard jets. Interfacing our codes to the multi-purpose Monte-Carlo event generator PYTHIA, we simulate parton showers and slepton decays in fully exclusive events. Advanced kinematical variables and specific search strategies are examined as means for slepton discovery in experimentally challenging setups.

High-mass Drell-Yan cross-section and search for new phenomena in multi-electron/positron final states with the ATLAS detector

The Standard Model of particle physics is a very successful theory which describes nearly all known processes of particle physics very precisely. Nevertheless, there are several observations which cannot be explained within the existing theory. In this thesis, two analyses with high energy electrons and positrons using data of the ATLAS detector are presented. One, probing the Standard Model of particle physics and another searching for phenomena beyond the Standard Model.rnThe production of an electron-positron pair via the Drell-Yan process leads to a very clean signature in the detector with low background contributions. This allows for a very precise measurement of the cross-section and can be used as a precision test of perturbative quantum chromodynamics (pQCD) where this process has been calculated at next-to-next-to-leading order (NNLO). The invariant mass spectrum mee is sensitive to parton distribution functions (PFDs), in particular to the poorly known distribution of antiquarks at large momentum fraction (Bjoerken x). The measurementrnof the high-mass Drell-Yan cross-section in proton-proton collisions at a center-of-mass energy of sqrt(s) = 7 TeV is performed on a dataset collected with the ATLAS detector, corresponding to an integrated luminosity of 4.7 fb-1. The differential cross-section of pp -> Z/gamma + X -> e+e- + X is measured as a function of the invariant mass in the range 116 GeV < mee < 1500 GeV. The background is estimated using a data driven method and Monte Carlo simulations. The final cross-section is corrected for detector effects and different levels of final state radiation corrections. A comparison isrnmade to various event generators and to predictions of pQCD calculations at NNLO. A good agreement within the uncertainties between measured cross-sections and Standard Model predictions is observed.rnExamples of observed phenomena which can not be explained by the Standard Model are the amount of dark matter in the universe and neutrino oscillations. To explain these phenomena several extensions of the Standard Model are proposed, some of them leading to new processes with a high multiplicity of electrons and/or positrons in the final state. A model independent search in multi-object final states, with objects defined as electrons and positrons, is performed to search for these phenomenas. Therndataset collected at a center-of-mass energy of sqrt(s) = 8 TeV, corresponding to an integrated luminosity of 20.3 fb-1 is used. The events are separated in different categories using the object multiplicity. The data-driven background method, already used for the cross-section measurement was developed further for up to five objects to get an estimation of the number of events including fake contributions. Within the uncertainties the comparison between data and Standard Model predictions shows no significant deviations.

Molecular mechanisms of shikonin and its derivatives in cancer therapy

The identification of molecular processes involved in cancer development and prognosis opened avenues for targeted therapies, which made treatment more tumor-specific and less toxic than conventional therapies. One important example is the epidermal growth factor receptor (EGFR) and EGFR-specific inhibitors (i.e. erlotinib). However, challenges such as drug resistance still remain in targeted therapies. Therefore, novel candidate compounds and new strategies are needed for improvement of therapy efficacy. Shikonin and its derivatives are cytotoxic constituents in traditional Chinese herbal medicine Zicao (Lithospermum erythrorhizin). In this study, we investigated the molecular mechanisms underlying the anti-cancer effects of shikonin and its derivatives in glioblastoma cells and leukemia cells. Most of shikonin derivatives showed strong cytotoxicity towards erlotinib-resistant glioblastoma cells, especially U87MG.ΔEGFR cells which overexpressed a deletion-activated EGFR (ΔEGFR). Moreover, shikonin and some derivatives worked synergistically with erlotinib in killing EGFR-overexpressing cells. Combination treatment with shikonin and erlotinib overcame the drug resistance of these cells to erlotinib. Western blotting analysis revealed that shikonin inhibited ΔEGFR phosphorylation and led to corresponding decreases in phosphorylation of EGFR downstream molecules. By means of Loewe additivity and Bliss independence drug interaction models, we found erlotinb and shikonin or its derivatives corporately suppressed ΔEGFR phosphorylation. We believed this to be a main mechanism responsible for their synergism in U87MG.ΔEGFR cells. In leukemia cells, which did not express EGFR, shikonin and its derivatives exhibited even greater cytotoxicity, suggesting the existence of other mechanisms. Microarray-based gene expression analysis uncovered the transcription factor c-MYC as the commonly deregulated molecule by shikonin and its derivatives. As validated by Western blotting analysis, DNA-binding assays and molecular docking, shikonin and its derivatives bound and inhibited c-MYC. Furthermore, the deregulation of ERK, JNK MAPK and AKT activity was closely associated with the reduction of c-MYC, indicating the involvement of these signaling molecules in shikonin-triggered c-MYC inactivation. In conclusion, the inhibition of EGFR signaling, synergism with erlotinib and targeting of c-MYC illustrate the multi-targeted feature of natural naphthoquinones such as shikonin and derivatives. This may open attractive possibilities for their use in a molecular targeted cancer therapy.

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.

The transcriptional regulator megakaryoblastic leukemia-1 mediates serum response factor-independent activation of tenascin-C transcription by mechanical stress

The extracellular matrix protein tenascin-C (TNC) is up-regulated in processes influenced by mechanical stress, such as inflammation, tissue remodeling, wound healing, and tumorigenesis. Cyclic strain-induced TNC expression depends on RhoA-actin signaling, the pathway that regulates transcriptional activity of serum response factor (SRF) by its coactivator megakaryoblastic leukemia-1 (MKL1). Therefore, we tested whether MKL1 controls TNC transcription. We demonstrate that overexpression of MKL1 strongly induces TNC expression in mouse NIH3T3 fibroblasts and normal HC11 and transformed 4T1 mammary epithelial cells. Part of the induction was dependant on SRF and a newly identified atypical CArG box in the TNC promoter. Another part was independent of SRF but required the SAP domain of MKL1. An MKL1 mutant incapable of binding to SRF still strongly induced TNC, while induction of the SRF target c-fos was abolished. Cyclic strain failed to induce TNC in MKL1-deficient but not in SRF-deficient fibroblasts, and strain-induced TNC expression strongly depended on the SAP domain of MKL1. Promoter-reporter and chromatin immunoprecipitation experiments unraveled a SAP-dependent, SRF-independent interaction of MKL1 with the proximal promoter region of TNC, attributing for the first time a functional role to the SAP domain of MKL1 in regulating gene expression.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.