Analysis of ion channel stochastic signals for biosensing

In biological world, life of cells is guaranteed by their ability to sense and to respond to a large variety of internal and external stimuli. In particular, excitable cells, like muscle or nerve cells, produce quick depolarizations in response to electrical, mechanical or chemical stimuli: this means that they can change their internal potential through a quick exchange of ions between cytoplasm and the external environment. This can be done thanks to the presence of ion channels, proteins that span the lipid bilayer and act like switches, allowing ionic current to flow opening and shutting in a stochastic way. For a particular class of ion channels, ligand-gated ion channels, the gating processes is strongly influenced by binding between receptive sites located on the channel surface and specific target molecules. These channels, inserted in biomimetic membranes and in presence of a proper electronic system for acquiring and elaborating the electrical signal, could give us the possibility of detecting and quantifying concentrations of specific molecules in complex mixtures from ionic currents across the membrane; in this thesis work, this possibility is investigated. In particular, it reports a description of experiments focused on the creation and the characterization of artificial lipid membranes, the reconstitution of ion channels and the analysis of their electrical and statistical properties. Moreover, after a chapter about the basis of the modelling of the kinetic behaviour of ligand gated ion channels, a possible approach for the estimation of the target molecule concentration, based on a statistical analysis of the ion channel open probability, is proposed. The fifth chapter contains a description of the kinetic characterisation of a ligand gated ion channel: the homomeric α2 isoform of the glycine receptor. It involved both experimental acquisitions and signal analysis. The last chapter represents the conclusions of this thesis, with some remark on the effective performance that may be achieved using ligand gated ion channels as sensing elements.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Different approaches to identify markers for meat quality and production traits in pigs: analysis of the transcriptome in post mortem skeletal muscle and investigation of candidate genes

Due to the growing attention of consumers towards their food, improvement of quality of animal products has become one of the main focus of research. To this aim, the application of modern molecular genetics approaches has been proved extremely useful and effective. This innovative drive includes all livestock species productions, including pork. The Italian pig breeding industry is unique because needs heavy pigs slaughtered at about 160 kg for the production of high quality processed products. For this reason, it requires precise meat quality and carcass characteristics. Two aspects have been considered in this thesis: the application of the transcriptome analysis in post mortem pig muscles as a possible method to evaluate meat quality parameters related to the pre mortem status of the animals, including health, nutrition, welfare, and with potential applications for product traceability (chapters 3 and 4); the study of candidate genes for obesity related traits in order to identify markers associated with fatness in pigs that could be applied to improve carcass quality (chapters 5, 6, and 7). Chapter three addresses the first issue from a methodological point of view. When we considered this issue, it was not obvious that post mortem skeletal muscle could be useful for transcriptomic analysis. Therefore we demonstrated that the quality of RNA extracted from skeletal muscle of pigs sampled at different post mortem intervals (20 minutes, 2 hours, 6 hours, and 24 hours) is good for downstream applications. Degradation occurred starting from 48 h post mortem even if at this time it is still possible to use some RNA products. In the fourth chapter, in order to demonstrate the potential use of RNA obtained up to 24 hours post mortem, we present the results of RNA analysis with the Affymetrix microarray platform that made it possible to assess the level of expression of more of 24000 mRNAs. We did not identify any significant differences between the different post mortem times suggesting that this technique could be applied to retrieve information coming from the transcriptome of skeletal muscle samples not collected just after slaughtering. This study represents the first contribution of this kind applied to pork. In the fifth chapter, we investigated as candidate for fat deposition the TBC1D1 [TBC1 (tre-2/USP6, BUB2, cdc16) gene. This gene is involved in mechanisms regulating energy homeostasis in skeletal muscle and is associated with predisposition to obesity in humans. By resequencing a fragment of the TBC1D1 gene we identified three synonymous mutations localized in exon 2 (g.40A>G, g.151C>T, and g.172T>C) and 2 polymorphisms localized in intron 2 (g.219G>A and g.252G>A). One of these polymorphisms (g.219G>A) was genotyped by high resolution melting (HRM) analysis and PCR-RFLP. Moreover, this gene sequence was mapped by radiation hybrid analysis on porcine chromosome 8. The association study was conducted in 756 performance tested pigs of Italian Large White and Italian Duroc breeds. Significant results were obtained for lean meat content, back fat thickness, visible intermuscular fat and ham weight. In chapter six, a second candidate gene (tribbles homolog 3, TRIB3) is analyzed in a study of association with carcass and meat quality traits. The TRIB3 gene is involved in energy metabolism of skeletal muscle and plays a role as suppressor of adipocyte differentiation. We identified two polymorphisms in the first coding exon of the porcine TRIB3 gene, one is a synonymous SNP (c.132T> C), a second is a missense mutation (c.146C> T, p.P49L). The two polymorphisms appear to be in complete linkage disequilibrium between and within breeds. The in silico analysis of the p.P49L substitution suggests that it might have a functional effect. The association study in about 650 pigs indicates that this marker is associated with back fat thickness in Italian Large White and Italian Duroc breeds in two different experimental designs. This polymorphisms is also associated with lactate content of muscle semimembranosus in Italian Large White pigs. Expression analysis indicated that this gene is transcribed in skeletal muscle and adipose tissue as well as in other tissues. In the seventh chapter, we reported the genotyping results for of 677 SNPs in extreme divergent groups of pigs chosen according to the extreme estimated breeding values for back fat thickness. SNPs were identified by resequencing, literature mining and in silico database mining. analysis, data reported in the literature of 60 candidates genes for obesity. Genotyping was carried out using the GoldenGate (Illumina) platform. Of the analyzed SNPs more that 300 were polymorphic in the genotyped population and had minor allele frequency (MAF) >0.05. Of these SNPs, 65 were associated (P<0.10) with back fat thickness. One of the most significant gene marker was the same TBC1D1 SNPs reported in chapter 5, confirming the role of this gene in fat deposition in pig. These results could be important to better define the pig as a model for human obesity other than for marker assisted selection to improve carcass characteristics.

Statistical analysis and simulation techniques in wall-bounded turbulence

The present work is devoted to the assessment of the energy fluxes physics in the space of scales and physical space of wall-turbulent flows. The generalized Kolmogorov equation will be applied to DNS data of a turbulent channel flow in order to describe the energy fluxes paths from production to dissipation in the augmented space of wall-turbulent flows. This multidimensional description will be shown to be crucial to understand the formation and sustainment of the turbulent fluctuations fed by the energy fluxes coming from the near-wall production region. An unexpected behavior of the energy fluxes comes out from this analysis consisting of spiral-like paths in the combined physical/scale space where the controversial reverse energy cascade plays a central role. The observed behavior conflicts with the classical notion of the Richardson/Kolmogorov energy cascade and may have strong repercussions on both theoretical and modeling approaches to wall-turbulence. To this aim a new relation stating the leading physical processes governing the energy transfer in wall-turbulence is suggested and shown able to capture most of the rich dynamics of the shear dominated region of the flow. Two dynamical processes are identified as driving mechanisms for the fluxes, one in the near wall region and a second one further away from the wall. The former, stronger one is related to the dynamics involved in the near-wall turbulence regeneration cycle. The second suggests an outer self-sustaining mechanism which is asymptotically expected to take place in the log-layer and could explain the debated mixed inner/outer scaling of the near-wall statistics. The same approach is applied for the first time to a filtered velocity field. A generalized Kolmogorov equation specialized for filtered velocity field is derived and discussed. The results will show what effects the subgrid scales have on the resolved motion in both physical and scale space, singling out the prominent role of the filter length compared to the cross-over scale between production dominated scales and inertial range, lc, and the reverse energy cascade region lb. The systematic characterization of the resolved and subgrid physics as function of the filter scale and of the wall-distance will be shown instrumental for a correct use of LES models in the simulation of wall turbulent flows. Taking inspiration from the new relation for the energy transfer in wall turbulence, a new class of LES models will be also proposed. Finally, the generalized Kolmogorov equation specialized for filtered velocity fields will be shown to be an helpful statistical tool for the assessment of LES models and for the development of new ones. As example, some classical purely dissipative eddy viscosity models are analyzed via an a priori procedure.

Study of Candidate Genes for production and carcass traits in Italian Heavy Pigs: identification of a new DNA Markers, Expression Studies and Association Analysis using Different Experimental Design

Heavy pig breeding in Italy is mainly oriented for the production of high quality processed products. Of particular importance is the dry cured ham production, which is strictly regulated and requires specific carcass characteristics correlated with green leg characteristics. Furthermore, as pigs are slaughtered at about 160 kg live weight, the Italian pig breeding sector faces severe problems of production efficiency that are related to all biological aspects linked to growth, feed conversion, fat deposition and so on. It is well known that production and carcass traits are in part genetically determined. Therefore, as a first step to understand genetic basis of traits that could have a direct or indirect impact on dry cured ham production, a candidate gene approach can be used to identify DNA markers associated with parameters of economic importance. In this thesis, we investigated three candidate genes for carcass and production traits (TRIB3, PCSK1, MUC4) in pig breeds used for dry cured ham production, using different experimental approaches in order to find molecular markers associated with these parameters.

Agrofood chain analysis: production, commercialisation and consumption of healthy food for population at risk of poverty in Italy

Italy registers a fast increase of low income population. Academics and policy makers consider income inequalities as a key determinant for low or inadequate healthy food consumption. Thus the objective is to understand how to overcome the agrofood chain barriers towards healthy food production, commercialisation and consumption for population at risk of poverty (ROP) in Italy. The study adopts a market oriented food chain approach, focusing the research ambit on ROP consumers, processing industries and retailers. The empirical investigation adopts a qualitative methodology with an explorative approach. The actors are investigated through 4 focus groups for consumers and carrying out 27 face to face semi-structured interviews for industries and retailers’ representatives. The results achieved provide the perceptions of each actor integrated into an overall chain approach. The analysis shows that all agrofood actors lack of an adequate level of knowledge towards healthy food definition. Food industries and retailers also show poor awareness about ROP consumers’ segment. In addition they perceive that the high costs for producing healthy food conflict with the low economic performances expected from ROP consumers’ segment. These aspects induce a scarce interest in investing on commercialisation strategies for healthy food for ROP consumers. Further ROP consumers show other notable barriers to adopt healthy diets caused, among others, by a personal strong negative attitude and lack of motivation. The personal barriers are also negatively influenced by several external socio-economic factors. The solutions to overcome the barriers shall rely on the improvement of the agrofood chain internal relations to identify successful strategies for increasing interest on low cost healthy food. In particular the focus should be on improved collaboration on innovation adoption and marketing strategies, considering ROP consumers’ preferences and needs. An external political intervention is instead necessary to fill the knowledge and regulations’ gaps on healthy food issues.

Top-quark pair production at hadron colliders

In this thesis we investigate several phenomenologically important properties of top-quark pair production at hadron colliders. We calculate double differential cross sections in two different kinematical setups, pair invariant-mass (PIM) and single-particle inclusive (1PI) kinematics. In pair invariant-mass kinematics we are able to present results for the double differential cross section with respect to the invariant mass of the top-quark pair and the top-quark scattering angle. Working in the threshold region, where the pair invariant mass M is close to the partonic center-of-mass energy sqrt{hat{s}}, we are able to factorize the partonic cross section into different energy regions. We use renormalization-group (RG) methods to resum large threshold logarithms to next-to-next-to-leading-logarithmic (NNLL) accuracy. On a technical level this is done using effective field theories, such as heavy-quark effective theory (HQET) and soft-collinear effective theory (SCET). The same techniques are applied when working in 1PI kinematics, leading to a calculation of the double differential cross section with respect to transverse-momentum pT and the rapidity of the top quark. We restrict the phase-space such that only soft emission of gluons is possible, and perform a NNLL resummation of threshold logarithms. The obtained analytical expressions enable us to precisely predict several observables, and a substantial part of this thesis is devoted to their detailed phenomenological analysis. Matching our results in the threshold regions to the exact ones at next-to-leading order (NLO) in fixed-order perturbation theory, allows us to make predictions at NLO+NNLL order in RG-improved, and at approximate next-to-next-to-leading order (NNLO) in fixed order perturbation theory. We give numerical results for the invariant mass distribution of the top-quark pair, and for the top-quark transverse-momentum and rapidity spectrum. We predict the total cross section, separately for both kinematics. Using these results, we analyze subleading contributions to the total cross section in 1PI and PIM originating from power corrections to the leading terms in the threshold expansions, and compare them to previous approaches. We later combine our PIM and 1PI results for the total cross section, this way eliminating uncertainties due to these corrections. The combined predictions for the total cross section are presented as a function of the top-quark mass in the pole, the minimal-subtraction (MS), and the 1S mass scheme. In addition, we calculate the forward-backward (FB) asymmetry at the Tevatron in the laboratory, and in the ttbar rest frames as a function of the rapidity and the invariant mass of the top-quark pair at NLO+NNLL. We also give binned results for the asymmetry as a function of the invariant mass and the rapidity difference of the ttbar pair, and compare those to recent measurements. As a last application we calculate the charge asymmetry at the LHC as a function of a lower rapidity cut-off for the top and anti-top quarks.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Secondary Microseisms Characterization and Green’s Function Extraction at the Larderello-Travale Geothermal Field (Italy)

Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.

Structural analysis of the major lightharvesting complex II by electron paramagnetic resonance (EPR) : comparison between monomers and trimers

Der Haupt-Lichtsammenkomplex II (LHCII) höherer Pflanzen ist das häufigsternMembranprotein der Welt und in die chloroplastidäre Thylakoidmembran integriert. DerrnLHCII kann als Modellsystem genutzt werden, um die Funktionsweise vonrnMembranproteinen besser zu verstehen, da 96 % seiner Struktur kristallografisch aufgelöstrnist und er in rekombinanter Form in vitro rückgefaltet werden kann. Hierbei entsteht einrnvoll funktionaler Protein-Pigment.Komplex, der nahezu identisch mit der in vivo Varianternist.rnElektronenparamagnetischen Resonanz (EPR) Spektroskopie ist eine hoch sensitive undrnideal geeignete Methode, um die Strukturdynamik von Proteinen zu untersuchen. Hierzurnist eine ortsspezifische Markierung mit Spinsonden notwendig, die kovalent an Cysteinernbinden. Möglich wird dies, indem sorgfältig ausgewählte Aminosäuren gegen Cysteinerngetauscht werden, ohne dass die Funktionsweise des LHCII beeinträchtigt wird.rnIm Rahmen dieser Arbeit wurden die Stabilität des verwendeten Spinmarkers und diernProbenqualität verbessert, indem alle Schritte der Probenpräparation untersucht wurden.rnMithilfe dieser Erkenntnisse konnte sowohl die Gefahr einer Proteinaggregation als auchrnein Verlust des EPR Signals deutlich vermindert werden. In Kombination mit derrngleichzeitigen Etablierung des Q-Band EPR können nun deutlich geringer konzentrierternProben zuverlässig vermessen werden. Darüber hinaus wurde eine reproduzierbarernMethode entwickelt, um heterogene Trimere herzustellen. Diese bestehen aus einemrndoppelt markierten Monomer und zwei unmarkierten Monomeren und erlauben es, diernkristallografisch unvollständig aufgelöste N-terminale Domäne im monomeren undrntrimeren Assemblierungsgrad zu untersuchen. Die Ergebnisse konnten einerseits diernVermutung bestätigen, dass diese Domäne im Vergleich zum starren Proteinkern sehrrnflexibel ist und andererseits, dass sie in Monomeren noch mobiler ist als in Trimeren.rnZudem wurde die lumenale Schleifenregion bei unterschiedlichen pH Werten undrnvariierender Pigmentzusammensetzung untersucht, da dieser Bereich sehr kontroversrndiskutiert wird. Die Messergebnisse offenbarten, dass diese Region starre und flexiblerernSektionen aufweist. Während der pH Wert keinen Einfluss auf die Konformation hatte,rnzeigte sich, dass die Abwesenheit von Neoxanthin zu einer Änderung der Konformationrnführt. Weiterführende Analysen der strukturellen Dynamik des LHCII in einerrnLipidmembran konnten hingegen nicht durchgeführt werden, da dies eine gerichteternInsertion des rückgefalteten Proteins in Liposomen erfordert, was trotz intensiverrnVersuche nicht zum Erfolg führte.

Regulatory T cell-mediated suppression of Th9 cell development and effector function

T helper (Th) 9 cells are an important subpopulation of the CD4+ T helper cells. Due to their ability to secrete Interleukin-(IL-)9, Th9 cells essentially contribute to the expulsion of parasitic helminths from the intestinal tract but they play also an immunopathological role in the course of asthma. Recently, a beneficial function of Th9 cells in anti-tumor immune responses was published. In a murine melanoma tumor model Th9 cells were shown to enhance the anti-melanoma immune response via the recruitment of CD8+ T cells, dendritic cells and mast cells. In contrast to Th9 effector cells regulatory T cells (Tregs) are able to control an immune response with the aid of different suppressive mechanisms. Based on their ability to suppress an immune response Tregs are believed to be beneficial in asthma by diminishing excessive allergic reactions. However, concerning cancer they can have a detrimental function because Tregs inhibit an effective anti-tumor immune reaction. Thus, the analysis of Th9 suppression by Tregs is of central importance concerning the development of therapeutic strategies for the treatment of cancer and allergic diseases and was therefore the main objective of this PhD thesis.rnIn general it could be demonstrated that the development of Th9 cells can be inhibited by Tregs in vitro. The production of the lineage-specific cytokine IL-9 by developing Th9 cells was completely suppressed at a Treg/Th9 ratio of 1:1 on the transcriptional (qRT-PCR) as well as on the translational level (ELISA). In contrast, the expression of IRF4 that was found to strongly promote Th9 development was not reduced in the presence of Tregs, suggesting that IRF4 requires additional transcription factors to induce the differentiation of Th9 cells. In order to identify such factors, which regulate Th9 development and therefore represent potential targets for Treg-mediated suppressive mechanisms, a transcriptome analysis using “next-generation sequencing” was performed. The expression of some genes which were found to be up- or downregulated in Th9 cells in the presence of Tregs was validated with qRT-PCR. Time limitations prevented a detailed functional analysis of these candidate genes. Nevertheless, the analysis of the suppressive mechanisms revealed that Tregs probably suppress Th9 cells via the increase of the intracellular cAMP concentration. In contrast, IL-9 production by differentiated Th9 cells was only marginally affected by Tregs in vitro and in vivo analysis (asthma, melanoma model). Hence, Tregs represent very effective inhibitors of Th9 development whereas they have only a minimal suppressive influence on differentiated Th9 cells.rn

Performance studies of the CMS distributed analysis system in the associated Higgs boson production with top quarks

L'obiettivo di questa tesi è studiare la fattibilità dello studio della produzione associata ttH del bosone di Higgs con due quark top nell'esperimento CMS, e valutare le funzionalità e le caratteristiche della prossima generazione di toolkit per l'analisi distribuita a CMS (CRAB versione 3) per effettuare tale analisi. Nel settore della fisica del quark top, la produzione ttH è particolarmente interessante, soprattutto perchè rappresenta l'unica opportunità di studiare direttamente il vertice t-H senza dover fare assunzioni riguardanti possibili contributi dalla fisica oltre il Modello Standard. La preparazione per questa analisi è cruciale in questo momento, prima dell'inizio del Run-2 dell'LHC nel 2015. Per essere preparati a tale studio, le implicazioni tecniche di effettuare un'analisi completa in un ambito di calcolo distribuito come la Grid non dovrebbero essere sottovalutate. Per questo motivo, vengono presentati e discussi un'analisi dello stesso strumento CRAB3 (disponibile adesso in versione di pre-produzione) e un confronto diretto di prestazioni con CRAB2. Saranno raccolti e documentati inoltre suggerimenti e consigli per un team di analisi che sarà eventualmente coinvolto in questo studio. Nel Capitolo 1 è introdotta la fisica delle alte energie a LHC nell'esperimento CMS. Il Capitolo 2 discute il modello di calcolo di CMS e il sistema di analisi distribuita della Grid. Nel Capitolo 3 viene brevemente presentata la fisica del quark top e del bosone di Higgs. Il Capitolo 4 è dedicato alla preparazione dell'analisi dal punto di vista degli strumenti della Grid (CRAB3 vs CRAB2). Nel capitolo 5 è presentato e discusso uno studio di fattibilità per un'analisi del canale ttH in termini di efficienza di selezione.

Die Bedeutung von molekularem Sauerstoff für die Evolution des genetischen Codes

Die Entstehung und Evolution des genetischen Codes, der die Nukleotidsequenz der mRNA in die Aminosäuresequenz der Proteine übersetzt, zählen zu den größten Rätseln der Biologie. Die ersten Organismen, die vor etwa 3,8 Milliarden Jahren auf der Erde auftraten, nutzten einen ursprünglichen genetischen Code, der vermutlich ausschließlich abiotisch verfügbare Aminosäuren terrestrischer oder extraterrestrischer Herkunft umfasste. Neue Aminosäuren wurden sukzessive biosynthetisiert und selektiv in den Code aufgenommen, welcher in der modernen Form aus bis zu 22 Aminosäuren besteht. Die Ursachen für die Selektion und die Chronologie ihrer Aufnahme sind bis heute unbekannt und sollten im Rahmen der vorliegenden Arbeit erforscht werden. Auf Grundlage quanten-chemischer Berechnungen konnte in dieser Arbeit zunächst ein Zusammenhang zwischen der HOMO-LUMO-Energiedifferenz (H-L-Distanz), die ein inverses quanten-chemisches Korrelat für allgemeine chemische Reaktivität darstellt, und der chronologischen Aufnahme der Aminosäuren in den genetischen Code aufgezeigt werden. Demnach sind ursprüngliche Aminosäuren durch große H-L-Distanzen und neue Aminosäuren durch kleine H-L-Distanzen gekennzeichnet. Bei einer Analyse des Metabolismus von Tyrosin und Tryptophan, bei denen es sich um die beiden jüngsten Standard-Aminosäuren handelt, wurde ihre Bedeutung als Vorläufer von Strukturen ersichtlich, die sich durch eine hohe Redox-Aktivität auszeichnen und deren Synthese gleichzeitig molekularen Sauerstoff erfordert. Aus diesem Grund wurden die Redox-Aktivitäten der 20 Standard-Aminosäuren gegenüber Peroxylradikalen und weiteren Radikalen getestet. Die Untersuchungen ergaben eine Korrelation zwischen evolutionärem Auftreten und chemischer Reaktivität der jeweiligen Aminosäure, die sich insbesondere in der effizienten Reaktion zwischen Tryptophan bzw. Tyrosin und Peroxylradikalen widerspiegelte. Dies indizierte eine potentielle Bedeutung reaktiver Sauerstoffspezies (ROS) bei der Konstituierung des genetischen Codes. Signifikante Mengen an ROS wurden erst zu Beginn der Oxygenierung der Geobiosphäre, die als Great Oxidation Event (GOE) bezeichnet wird und vor circa 2,3 Milliarden Jahren begann, gebildet und müssen zur oxidativen Schädigung vulnerabler, zellulärer Strukturen geführt haben. Aus diesem Grund wurde das antioxidative Potential von Aminosäuren beim Prozess der Lipidperoxidation untersucht. Es konnte gezeigt werden, dass lipophile Derivate von Tryptophan und Tyrosin befähigt sind, die Peroxidation von Rattenhirnmembranen zu verhindern und humane Fibroblasten vor oxidativem Zelltod zu schützen. Daraus gründete sich das in dieser Arbeit aufgestellte Postulat eines Selektionsvorteils primordialer Organismen während des GOEs, die Tryptophan und Tyrosin als redox-aktive Aminosäuren in Membranproteine einbauen konnten und somit vor Oxidationsprozessen geschützt waren. Demzufolge wurde die biochemische Reaktivität als Selektionsparameter sowie oxidativer Stress als prägender Faktor der Evolution des genetischen Codes identifiziert.

Single meson production in proton diffraction at 190 GeV/c at COMPASS

The quark model successfully describes all ground state bary-ons as members of $SU(N)$ flavour multiplets. For excited baryon states the situation is totally different. There are much less states found in the experiment than predicted in most theoretical calculations. This fact has been known for a long time as the 'missing resonance problem'. In addition, many states found in experiments are only poorly measured up to now. Therefore, further experimental efforts are needed to clarify the situation.rnrnAt mbox{COMPASS}, reactions of a $190uskgigaeVperclight$ hadron beam impinging on a liquid hydrogen target are investigated.rnThe hadron beam contains different species of particles ($pi$, $K$, $p$). To distinguish these particles, two Cherenkov detectors are used. In this thesis, a new method for the identification of particles from the detector information is developed. This method is based on statistical approaches and allows a better kaon identification efficiency with a similar purity compared to the method, which was used before.rnrnThe reaction $pprightarrow ppX$ with $X=(pi^0,~eta,~omega,~phi)$ is used to study different production mechanisms. A previous analysis of $omega$ and $phi$ mesons is extended to pseudoscalar mesons. As the resonance contributions in $peta$ are smaller than in $ppi^0$ a different behaviour of these two final states is expected as a function of kinematic variables. The investigation of these differences allows to study different production mechanisms and to estimate the size of the resonant contribution in the different channels.rnrnIn addition, the channel $pprightarrow ppX$ allows to study baryon resonances in the $pX$ system.rnIn the mbox{COMPASS} energy regime, the reaction is dominated by Pomeron exchange. As a Pomeron carries vacuum quantum numbers, no isospin is transferred between the target proton and the beam proton. Therefore, the $pX$ final state has isospin $textstylefrac{1}{2}$ and all baryon resonances in this channel are $N^ast$ baryons. This offers the opportunity to do spectroscopy without taking $Delta$ resonances into account. rnrnTo disentangle the contributions of different resonances a partial wave analysis (PWA) is used. Different resonances have different spin and parity $J^parity$, which results in different angular distributions of the decay particles. These angular distributions can be calculated from models and then be fitted to the data. From the fit the contributions of the single resonances as well as resonance parameters -- namely the mass and the width -- can be extracted. In this thesis, two different approaches for a partial wave analysis of the reaction $pprightarrow pppi^0$ are developed and tested.