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.

Multi-level models and infrastructures for simulating biological system development

The hierarchical organisation of biological systems plays a crucial role in the pattern formation of gene expression resulting from the morphogenetic processes, where autonomous internal dynamics of cells, as well as cell-to-cell interactions through membranes, are responsible for the emergent peculiar structures of the individual phenotype. Being able to reproduce the systems dynamics at different levels of such a hierarchy might be very useful for studying such a complex phenomenon of self-organisation. The idea is to model the phenomenon in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartment events determines the emergent behaviour resulting in the formation of spatial patterns. According to these premises the thesis proposes a review of the different approaches already developed in modelling developmental biology problems, as well as the main models and infrastructures available in literature for modelling biological systems, analysing their capabilities in tackling multi-compartment / multi-level models. The thesis then introduces a practical framework, MS-BioNET, for modelling and simulating these scenarios exploiting the potential of multi-level dynamics. This is based on (i) a computational model featuring networks of compartments and an enhanced model of chemical reaction addressing molecule transfer, (ii) a logic-oriented language to flexibly specify complex simulation scenarios, and (iii) a simulation engine based on the many-species/many-channels optimised version of Gillespie’s direct method. The thesis finally proposes the adoption of the agent-based model as an approach capable of capture multi-level dynamics. To overcome the problem of parameter tuning in the model, the simulators are supplied with a module for parameter optimisation. The task is defined as an optimisation problem over the parameter space in which the objective function to be minimised is the distance between the output of the simulator and a target one. The problem is tackled with a metaheuristic algorithm. As an example of application of the MS-BioNET framework and of the agent-based model, a model of the first stages of Drosophila Melanogaster development is realised. The model goal is to generate the early spatial pattern of gap gene expression. The correctness of the models is shown comparing the simulation results with real data of gene expression with spatial and temporal resolution, acquired in free on-line sources.

Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

Comparing Different Approaches for Clustering Categorical Data

There are different ways to do cluster analysis of categorical data in the literature and the choice among them is strongly related to the aim of the researcher, if we do not take into account time and economical constraints. Main approaches for clustering are usually distinguished into model-based and distance-based methods: the former assume that objects belonging to the same class are similar in the sense that their observed values come from the same probability distribution, whose parameters are unknown and need to be estimated; the latter evaluate distances among objects by a defined dissimilarity measure and, basing on it, allocate units to the closest group. In clustering, one may be interested in the classification of similar objects into groups, and one may be interested in finding observations that come from the same true homogeneous distribution. But do both of these aims lead to the same clustering? And how good are clustering methods designed to fulfil one of these aims in terms of the other? In order to answer, two approaches, namely a latent class model (mixture of multinomial distributions) and a partition around medoids one, are evaluated and compared by Adjusted Rand Index, Average Silhouette Width and Pearson-Gamma indexes in a fairly wide simulation study. Simulation outcomes are plotted in bi-dimensional graphs via Multidimensional Scaling; size of points is proportional to the number of points that overlap and different colours are used according to the cluster membership.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Analysis and development of ecologically based approaches to coastal defense

Climate-change related impacts, notably coastal erosion, inundation and flooding from sea level rise and storms, will increase in the coming decades enhancing the risks for coastal populations. Further recourse to coastal armoring and other engineered defenses to address risk reduction will exacerbate threats to coastal ecosystems. Alternatively, protection services provided by healthy ecosystems is emerging as a key element in climate adaptation and disaster risk management. I examined two distinct approaches to coastal defense on the base of their ecological and ecosystem conservation values. First, I analyzed the role of coastal ecosystems in providing services for hazard risk reduction. The value in wave attenuation of coral reefs was quantitatively demonstrated using a meta-analysis approach. Results indicate that coral reefs can provide wave attenuation comparable to hard engineering artificial defenses and at lower costs. Conservation and restoration of existing coral reefs are cost-effective management options for disaster risk reduction. Second, I evaluated the possibility to enhance the ecological value of artificial coastal defense structures (CDS) as habitats for marine communities. I documented the suitability of CDS to support native, ecologically relevant, habitat-forming canopy algae exploring the feasibility of enhancing CDS ecological value by promoting the growth of desired species. Juveniles of Cystoseira barbata can be successfully transplanted at both natural and artificial habitats and not affected by lack of surrounding adult algal individuals nor by substratum orientation. Transplantation success was limited by biotic disturbance from macrograzers on CDS compared to natural habitats. Future work should explore the reasons behind the different ecological functioning of artificial and natural habitats unraveling the factors and mechanisms that cause it. The comprehension of the functioning of systems associated with artificial habitats is the key to allow environmental managers to identify proper mitigation options and to forecast the impact of alternative coastal development plans.

Control of fruit postharvest diseases by thermotherapy: understanding the mechanisms of action by –omics approaches

In recent years the hot water treatment (HW) represents an effective and safe approach for managing postharvest decay. This study reported the effect of an HW (60°C for 60 s and 45°C for 10 min) on brown rot and blue mould respectively. Peaches was found more thermotolerant compared to apple fruit, otherwise Penicillium expansum was more resistant to heat with respect to Monilinia spp. In semi-commercial and commercial trials, the inhibition of brown rot in naturally infected peaches was higher than 78% after 6 days at 0°C and 3 days at 20°C. Moreover, in laboratory trials a 100% disease incidence reduction was obtained by treating artificially infected peaches at 6-12 h after inoculation revealing a curative effect of HW. The expression levels of some genes were evaluated by qRT-PCR. Specifically, the cell wall genes (β-GAL, PL, PG, PME) showed a general decrease of expression level whereas PAL, CHI, HSP70 and ROS-scavenging genes were induced in treated peaches compared to the control ones. Contrarily, HW applied on artificially infected fruit before the inoculum was found to increase brown rot susceptibility. This aspect might be due to an increase of fruit VOCs emission as revealed by PTR-ToF-MS analysis. In addition a microarray experiment was conducted to analyze molecular mechanisms underneath the apple response to heat. Our results showed a largest amount of induced Heat shock proteins (HSPs), Heat shock cognate proteins (HSCs), Heat shock transcription factors (HSTFs) genes found at 1 and 4 hours from the treatment. Those genes required for the thermotolerance process could be involved in induced resistance response. The hypothesis was confirmed by 30% of blue mold disease reduction in artificially inoculated apple after 1 and 4 hours from the treatment. In order to improve peaches quality and disease management during storage, an innovative tool was also used: Da-meter.

Using national FADN database to describe Italian farms and arable fields. A comparison of sustainability level between organic versus conventional regimes.

The study defines a new farm classification and identifies the arable land management. These aspects and several indicators are taken into account to estimate the sustainability level of farms, for organic and conventional regimes. The data source is Italian Farm Account Data Network (RICA) for years 2007-2011, which samples structural and economical information. An environmental data has been added to the previous one to better describe the farm context. The new farm classification describes holding by general informations and farm structure. The general information are: adopted regime and farm location in terms of administrative region, slope and phyto-climatic zone. The farm structures describe the presence of main productive processes and land covers, which are recorded by FADN database. The farms, grouped by homogeneous farm structure or farm typology, are evaluated in terms of sustainability. The farm model MAD has been used to estimate a list of indicators. They describe especially environmental and economical areas of sustainability. Finally arable lands are taken into account to identify arable land managements and crop rotations. Each arable land has been classified by crop pattern. Then crop rotation management has been analysed by spatial and temporal approaches. The analysis reports a high variability inside regimes. The farm structure influences indicators level more than regimes, and it is not always possible to compare the two regimes. However some differences between organic and conventional agriculture have been found. Organic farm structures report different frequency and geographical location than conventional ones. Also different connections among arable lands and farm structures have been identified.

Global and regional sea level variations in the recent past and future: insight from observations and modeling

This work is focused on the analysis of sea–level change (last century), based mainly on instrumental observations. During this period, individual components of sea–level change are investigated, both at global and regional scales. Some of the geophysical processes responsible for current sea-level change such as glacial isostatic adjustments and current melting terrestrial ice sources, have been modeled and compared with observations. A new value of global mean sea level change based of tide gauges observations has been independently assessed in 1.5 mm/year, using corrections for glacial isostatic adjustment obtained with different models as a criterion for the tide gauge selection. The long wavelength spatial variability of the main components of sea–level change has been investigated by means of traditional and new spectral methods. Complex non–linear trends and abrupt sea–level variations shown by tide gauges records have been addressed applying different approaches to regional case studies. The Ensemble Empirical Mode Decomposition technique has been used to analyse tide gauges records from the Adriatic Sea to ascertain the existence of cyclic sea-level variations. An Early Warning approach have been adopted to detect tipping points in sea–level records of North East Pacific and their relationship with oceanic modes. Global sea–level projections to year 2100 have been obtained by a semi-empirical approach based on the artificial neural network method. In addition, a model-based approach has been applied to the case of the Mediterranean Sea, obtaining sea-level projection to year 2050.

Engineering in Transition. Approaches, strategies and technologies for implementing system innovation towards sustainability

With the aim to provide people with sustainable options, engineers are ethically required to hold the safety, health and welfare of the public paramount and to satisfy society's need for sustainable development. The global crisis and related sustainability challenges are calling for a fundamental change in culture, structures and practices. Sustainability Transitions (ST) have been recognized as promising frameworks for radical system innovation towards sustainability. In order to enhance the effectiveness of transformative processes, both the adoption of a transdisciplinary approach and the experimentation of practices are crucial. The evolution of approaches towards ST provides a series of inspiring cases which allow to identify advances in making sustainability transitions happen. In this framework, the thesis has emphasized the role of Transition Engineering (TE). TE adopts a transdisciplinary approach for engineering to face the sustainability challenges and address the risks of un-sustainability. With this purpose, a definition of Transition Technologies is provided as a valid instruments to contribute to ST. In the empirical section, several transition initiatives have been analysed especially at the urban level. As a consequence, the model of living-lab of sustainability has crucially emerged. Living-labs are environments in which innovative technologies and services are co-created with users active participation. In this framework, university can play a key role as learning organization. The core of the thesis has concerned the experimental application of transition approach within the School of Engineering and Architecture of University of Bologna at Terracini Campus. The final vision is to realize a living-lab of sustainability. Particularly, a Transition Team has been established and several transition experiments have been conducted. The final result is not only the improvement of sustainability and resilience of the Terracini Campus, but the demonstration that university can generate solutions and strategies that tackle the complex, dynamic factors fuelling the global crisis.

Laserspektroskopie der Grundzustands-Hyperfeinstruktur des lithiumähnlichen 209 Bi 80+

Die theoretische und experimentelle Untersuchung von wasserstoffähnlichen Systemen hat in den letzten hundert Jahren immer wieder sowohl die experimentelle als auch die theoretische Physik entscheidend vorangebracht. Formulierung und Test der Quantenelektrodynamik (QED) standen und stehen in engen Zusammenhang mit der Untersuchung wasserstoffähnlicher Systeme. Gegenwärtig sind besonders wasserstoffähnliche Systeme schwerer Ionen von Interesse, um die QED in den extrem starken Feldern in Kernnähe zu testen. Laserspektroskopische Messungen der Hyperfeinstrukturaufspaltung des Grundzustandes bieten eine hohe Genauigkeit, ihre Interpretation wird jedoch durch die Unsicherheit in der Größe der Kernstruktureffekte erschwert. Beseitigt werden können diese durch die Kombination der Aufspaltung in wasserstoff- und lithiumähnlichen Ionen des gleichen Nuklids. In den letzten zwei Jahrzehnten scheiterten mehrere dadurch motivierte Versuche, den HFS-Übergang in lithiumähnlichen 209Bi80+ zu finden. Im Rahmen dieser Arbeit wurde kollineare Laserspektroskopie bei etwa 70% der Lichtgeschwindigkeit an 209Bi82+ und 209Bi80+ -Ionen im Experimentier- Speicherring an der GSI in Darmstadt durchgeführt. Dabei wurde der Übergang im lithiumähnlichen Bismut erstmals beobachtet und dessen Übergangswellenlänge zu 1554,74(74) nm bestimmt. Ein eigens für dieses Experiment optimiertes Fluoreszenz-Nachweissystem stellte dabei die entscheidende Verbesserung gegenüber den gescheiterten Vorgängerexperimenten dar. Der Wellenlängenfehler ist dominiert von der Unsicherheit der Ionengeschwindigkeit, die für die Transformation in das Ruhesystem der Ionen entscheidend ist. Für deren Bestimmung wurden drei Ansätze verfolgt: Die Geschwindigkeit wurde aus der Elektronenkühlerspannung bestimmt, aus dem Produkt von Orbitlänge und Umlauffrequenz und aus dem relativistischen Dopplereffekt unter Annahme der Korrektheit des früher bestimmten Überganges in wasserstoffähnlichen Bismut. Die Spannungskalibration des Elektronenkühlers wurde im Rahmen dieser Arbeit erstmals kritisch evaluiert und bislang unterschätzte systematische Unsicherheiten aufgezeigt, die derzeit einen aussagekräftigen QED-Test verhindern. Umgekehrt konnte unter Verwendung der QED-Berechnungen eine Ionengeschwindigkeit berechnet werden, die ein genaueres und konsistenteres Resultat für die Übergangswellenlängen beider Ionenspezies liefert. Daraus ergibt sich eine Diskrepanz zu dem früher bestimmten Wert des Überganges in wasserstoffähnlichen Bismut, die es weiter zu untersuchen gilt.

Die Expression und Regulation der CYP3A in menschlicher Haut

In Leber und Dünndarm bauen CYP3A-Enzyme eine Vielzahl von Fremdstoffen ab, die in den Körper gelangt sind. Zudem aber sind diese Enzyme auch in anderen Organen, wie der Haut exprimiert. Doch weder die genaue Zusammensetzung der CYP3A-Isozyme noch deren physiologische Rolle in der Haut sind bisher bekannt. Basierend auf begrenzten in vitro-Daten ist eine Rolle der CYP3A in der kutanen Vitamin D-Synthese denkbar. Auf der anderen Seite könnten die kutanen CYP3A auch lokal oder systemisch verabreichte Medikamente in der Haut verstoffwechseln und so zur Entstehung immunologischer und nicht-immunologischer unerwünschter Arzneimittelwirkungen beitragen, von denen sich bis zu 45 % in der Haut manifestieren.rnDie Arbeitshypothese dieses Projekts war, dass die CYP3A die kutane Synthese von Vitamin D regulieren. In dieser Funktion wurden sie zur Vermeidung von Vitamin D-Mangel-Erkrankungen wie Rachitis oder Osteomalazie in Europäern negativ selektiert. rnDie Expression und Regulation der CYP3A wurde in Hautbiopsien, einer Zelllinie epidermalen Ursprungs und primären Hautzellen wie auch in transgenen Mäusen untersucht. Die metabolische Aktivität der CYP3A gegenüber den kutanen Vitamin D-Vorstufen wurde mit Hilfe rekombinant exprimierter Enzyme untersucht. CYP3A5-mRNA war die häufigste der CYP3A in humanen Hautproben und überstieg die von CYP3A4 um das Dreifache, die von CYP3A7 um das 130-Fache. Damit entsprach diese 1,3 %, 0,01 % bzw. 0,01 % der jeweiligen hepatischen Genexpression. Die Expression von CYP3A43 war zu vernachlässigen. CYP3A5 zeigte eine bimodale Expression sowohl auf mRNA- als auch auf Proteinebene. So zeigten Träger der Wildtyp-Allels *1 eine 3,3-fach höhere mRNA- und 1,8-fach höhere Proteinmenge als homozygote Träger des Nullallels *3. CYP3A4/7- und CYP3A5-Protein wurde v. a. in den Keratinozyten der Epidermis und den Talgdrüsen, also den Bereichen der kutanen Vitamin D-Synthese lokalisiert. Die CYP3A5-Expression wurde ferner in der Haut transgener Mäusen gezeigt, die das Reportergen Luziferase unter Kontrolle des humanen CYP3A5-Promoters exprimieren. Verglichen mit der Leber war die kutane Expression des Vitamin D-Rezeptors (VDR) 100-fach höher, die der Xenosensoren CAR und PXR vergleichbar bzw. zu vernachlässigen. Dementsprechend erhöhte die Behandlung mit 1,25-Dihydroxyvitamin D, dem aktiven Vitamin D-Hormon, und dessen Vorstufen außer 7-Dehydrocholesterol, jedoch nicht der PXR-Ligand Rifampicin, die Expression der CYP3A. Wie in Zwei-Hybrid-Experimenten gezeigt, wurden die Effekte des 1,25-Dihydroxyvitamin D und dessen Vorstufen alleinig durch VDR vermittelt. Die Effektstärke hingegen war abhängig von Zellspender, Zellpassage und Zelltypus. Alle drei CYP3A-Isozyme metabolisieren Vitamin D zu einem oder mehreren unbekannten Metaboliten, jedoch nicht zu 25-Hydroxyvitamin D, dem direkten Vorläufer des aktiven Vitamin D. rnZusammengefasst legen die Daten nahe, dass die kutanen CYP3A, allen voran CYP3A5, die Vitamin D-Homöostase durch VDR-vermittelte Induktion des Abbaus von Vitamin D-Vorstufen regulieren. Dies zusammen mit Sequenzdaten liefert starke Indizien für Vitamin D als treibende Kraft der Selektion des CYP3A-Lokus in Europäern. Der Einfluss der CYP3A-Expression auf selektiv wirksame, klinisch relevante Knochenveränderungen wie Rachitis oder Osteomalazie müssen folgen.rn

Elevated level of metabotropic glutamate receptor 2/3 in the prefrontal cortex in major depression

Clinical, postmortem and preclinical research strongly implicates dysregulation of glutamatergic neurotransmission in major depressive disorder (MDD). Recently, metabotropic glutamate receptors (mGluRs) have been proposed as attractive targets for the discovery of novel therapeutic approaches against depression. The aim of this study was to examine mGluR2/3 protein levels in the prefrontal cortex (PFC) from depressed subjects. In addition, to test whether antidepressants influence mGluR2/3 expression we also studied levels of mGluR2/3 in fluoxetine-treated monkeys. Postmortem human prefrontal samples containing Brodmann's area 10 (BA10) were obtained from 11 depressed and 11 psychiatrically healthy controls. Male rhesus monkeys were treated chronically with fluoxetine (dose escalated to 3mg/kg, p.o.; n=7) or placebo (n=6) for 39 weeks. The mGluR2/3 immunoreactivity was investigated using Western blot method. There was a robust (+67%) increase in the expression of the mGlu2/3 protein in the PFC of depressed subjects relative to healthy controls. The expression of mGlu2/3 was unchanged in the PFC of monkeys treated with fluoxetine. Our findings provide the first evidence that mGluR2/3 is elevated in the PFC in MDD. This observation is consistent with reports showing that mGluR2/3 antagonists exhibit antidepressant-like activity in animal models and demonstrates that these receptors are promising targets for the discovery of novel antidepressants.

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.

Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches

Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.