Researches on berry composition in red grape: agronomical, biochemical and molecular approaches

It is well known that the best grape quality can occur only through the achievement of optimal source/sink ratio. Vine balance is in fact a key parameter in controlling berry sugar, acidity and secondary metabolites content (Howell, 2001; Vanden Heuvel et al., 2004). Despite yield reduction and quality improvement are not always strictly related, cluster thinning is considered a technique which could lead to improvement in grape sugar and anthocyanin composition (Dokoozlian and Hirschfelt, 1995; Guidoni et al., 2002). Among several microclimatic variables which may impact grape composition, the effect of cluster light exposure and temperature, which probably act in synergistic and complex way, has been widely explored showing positive even sometimes contradictory results (Spayd et al., 2001; Tarara et al., 2008). Pre-bloom and véraison defoliation are very efficient techniques in inducing cluster microclimatic modification. Furthermore pre-bloom defoliation inducing a lower berry set percentage On these basis the aim of the first experiment of the thesis was to verify in cv Sangiovese the effects on ripening and berry composition of management techniques which may increase source/sink ratio and /or promote light incidence on berries throughout grape ripening. An integrated agronomic, biochemical and microarray approach, aims to understand which mechanisms are involved in berry composition and may be conditioned in the berries during ripening in vines submitted to three treatments. In particular the treatments compared were: a) cluster thinning (increasing in source/sink ratio) b) leaf removal at véraison (increasing cluster light exposure) c) pre-bloom defoliation (increasing source sink ratio and cluster light exposure). Vine response to leaf removal at véraison was further evaluated in the second experiment on three different varieties (Cabernet Sauvignon, Nero d’Avola, Raboso Piave) chosen for their different genetic traits in terms of anthocyanin amount and composition. The integrated agronomic, biochemical and microarray approach, employed in order to understand those mechanisms involved in berry composition of Sangiovese vines submitted to management techniques which may increase source/sink ratio and induce microclimatic changes, bring to interesting results. This research confirmed the main role of source/sink ratio in conditioning sugars metabolism and revealed also that carbohydrates availability is a crucial issue in triggering anthocyanin biosynthesis. More complex is the situation of pre-bloom defoliation, where source/sink and cluster light increase effects are associated to determine final berry composition. It results that the application of pre-bloom defoliation may be risky, as too much dependent on seasonal conditions (rain and temperature) and physiological vine response (leaf area recovery, photosynthetic compensation, laterals regrowth). Early induced stress conditions could bring cluster at véraison in disadvantage to trigger optimal berry ripening processes compared to untreated vines. This conditions could be maintained until harvest, if no previously described physiological recovery occurs. Certainly, light exposure increase linked to defoliation treatments, showed a positive and solid effect on flavonol biosynthesis, as in our conditions temperature was not so different among treatments. Except the last aspects, that could be confirmed also for véraison defoliation, microclimatic changes by themselves seemed not able to induce any modification in berry composition. Further studies are necessary to understand if the peculiar anthocyanic and flavonols composition detected in véraison defoliation could play important role in both color intensity and stability of wines.

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.

Collective effects for the LHC injectors: non-ultrarelativistic approaches

The upgrade of the CERN accelerator complex has been planned in order to further increase the LHC performances in exploring new physics frontiers. One of the main limitations to the upgrade is represented by the collective instabilities. These are intensity dependent phenomena triggered by electromagnetic fields excited by the interaction of the beam with its surrounding. These fields are represented via wake fields in time domain or impedances in frequency domain. Impedances are usually studied assuming ultrarelativistic bunches while we mainly explored low and medium energy regimes in the LHC injector chain. In a non-ultrarelativistic framework we carried out a complete study of the impedance structure of the PSB which accelerates proton bunches up to 1.4 GeV. We measured the imaginary part of the impedance which creates betatron tune shift. We introduced a parabolic bunch model which together with dedicated measurements allowed us to point to the resistive wall impedance as the source of one of the main PSB instability. These results are particularly useful for the design of efficient transverse instability dampers. We developed a macroparticle code to study the effect of the space charge on intensity dependent instabilities. Carrying out the analysis of the bunch modes we proved that the damping effects caused by the space charge, which has been modelled with semi-analytical method and using symplectic high order schemes, can increase the bunch intensity threshold. Numerical libraries have been also developed in order to study, via numerical simulations of the bunches, the impedance of the whole CERN accelerator complex. On a different note, the experiment CNGS at CERN, requires high-intensity beams. We calculated the interpolating Hamiltonian of the beam for highly non-linear lattices. These calculations provide the ground for theoretical and numerical studies aiming to improve the CNGS beam extraction from the PS to the SPS.

Functional components and lipid quality assessment in vegetable foods: analytical and technological approaches

Lipids are important components that contribute very significantly to nutritional and technological quality of foods because they are the least stable macro-components in foods, due to high susceptibility to oxidation. When rancidity take place, it makes food unhealthy and unacceptable for consumers. Thus, the presence of antioxidants, naturally present of added to foods, is required to enhance shelf life of foods. Moreover, antioxidant like phenolic compounds play an important role in human health enhancing the functionality of foods. The aim of this PhD project was the study of lipid quality and lipid oxidation in different vegetable foods focusing on analytical and technological aspects in order to figure out the effects of lipid composition and bioactive compounds (phenolic compounds, omega-3 fatty acids and dietary fiber) addition on their shelf life. In addition, bioavailability and antioxidant effects of phenolic compounds in human and animals, respectively, were evaluated after consumption of vegetable foods. The first section of the work was focused on the evaluation of lipid quality impact on technological behaviour of vegetable foods. Because of that, cocoa butter with different melting point were evaluated by chromatographic techniques (GC, TLC) and the sample with the higher melting point showed the presence of fatty acids, triglycerides, 2-monoglycerides and FT-IR profile different from genuine cocoa butter, meaning an adding of foreign fat (lauric-fat) not allowed by the law. Looking at lipid quality of other vegetable foods, an accelerated shelf life test (OXITEST®), was used to evaluate of lipid stability to oxidation in tarallini snacks made up using different lipid matrices (sunflower oil, extravirgin olive oil and a blend of extravirgin olive oil and lard). The results showed a good ability of OXITEST® to discriminate between lipid unsaturation and different cooking times, without any samples fat extraction. In the second section, the role of bioactive compounds on cereal based food shelf life was studied in different bakeries by GC, spectrophotometric methods and capillary electrophoresis. It was examined the relationships between phenolic compounds, added with flour, and lipid oxidation of tarallini and frollini. Both products showed an increase in lipid oxidation during storage and antioxidant effects on lipid oxidation were not as expected. Furthermore, the influence of enrichment in polyunsaturated fatty acids on lipid oxidation of pasta was evaluated. The results proved that LC n-3 PUFA were not significantly implicated in the onset of oxidation in spaghetti stored under daylight and accelerated oxidation in a laboratory heater. The importance of phenolic compounds as antioxidant in humans and rats was also studied, by HPLC/MS in the latter section. For this purpose, apigenin and apigenin glycosides excretion was investigated in six women’s urine in a 24 hours study. After a single dose of steamed artichokes, both aglicone and glucuronide metabolites were recovered in 24 h urine. Moreover, the effect of whole grain durum wheat bread and whole grain Kamut® khorasan bread in rats were evaluated. Both cereals were good sources of antioxidants but Kamut® bread fed animals had a better response to stress than wheat durum fed, especially when a sourdough bread was supplied.

Supramolecular approaches to organized luminescent nanostructures for sensing, labeling and imaging applications

The common thread of this thesis is the will of investigating properties and behavior of assemblies. Groups of objects display peculiar properties, which can be very far from the simple sum of respective components’ properties. This is truer, the smaller is inter-objects distance, i.e. the higher is their density, and the smaller is the container size. “Confinement” is in fact a key concept in many topics explored and here reported. It can be conceived as a spatial limitation, that yet gives origin to unexpected processes and phenomena based on inter-objects communication. Such phenomena eventually result in “non-linear properties”, responsible for the low predictability of large assemblies. Chapter 1 provides two insights on surface chemistry, namely (i) on a supramolecular assembly based on orthogonal forces, and (ii) on selective and sensitive fluorescent sensing in thin polymeric film. In chapters 2 to 4 confinement of molecules plays a major role. Most of the work focuses on FRET within core-shell nanoparticles, investigated both through a simulation model and through experiments. Exciting results of great applicative interest are drawn, such as a method of tuning emission wavelength at constant excitation, and a way of overcoming self-quenching processes by setting up a competitive deactivation channel. We envisage applications of these materials as labels for multiplexing analysis, and in all fields of fluorescence imaging, where brightness coupled with biocompatibility and water solubility is required. Adducts of nanoparticles and molecular photoswitches are investigated in the context of superresolution techniques for fluorescence microscopy. In chapter 5 a method is proposed to prepare a library of functionalized Pluronic F127, which gives access to a twofold “smart” nanomaterial, namely both (i)luminescent and (ii)surface-functionalized SCSSNPs. Focus shifts in chapter 6 to confinement effects in an upper size scale. Moving from nanometers to micrometers, we investigate the interplay between microparticles flowing in microchannels where a constriction affects at very long ranges structure and dynamics of the colloidal paste.

New molecular approaches to control rhabdomyosarcoma onset and metastasis in preclinical systems

Rhabdomyosarcoma is the most common soft tissue sarcoma of childhood. The aim of this study was to identify molecular events involved in rhabdomyosarcoma onset for the development of new therapeutic approaches against specific molecular targets. BALB-p53neu mice develop pelvic rhabdomyosarcoma and combines the activation of HER-2/neu oncogene with the inactivation of an allele of p53 oncosuppressor gene. Gene expression profiling led to the identification of genes potentially involved in rhabdomyosarcoma genesis and therefore of candidate targets. The pattern of expression of p53, HER-2/neu, CDKN2A/p19ARF and IGF-2 suggested that these alterations might be involved in gender-, site- and strain-specific development of rhabdomyosarcoma. Other genes such as CDKN1A/p21 might be involved. The role of IGF-2, CDKN2A/p19ARF and CDKN1A/p21 in tumor growth was investigated with siRNA in murine rhabdomyosarcoma cells. Silencing of p19ARF and p21 induced inhibition of growth and of migration ability, indicating a possible pro-tumor and pro-metastatic role in rhabdomyosarcoma in absence of p53. In addition the autocrine IGF-2/IGF-1R loop found in early phases of cancer progression strengthens its key role in sustaining rhabdomyosarcoma growth. As rhabdomyosarcoma displays defective myogenic differentiation, a therapeutic approach aimed at enhancing myogenic differentiation of rhabdomyosarcoma cells. Forced expression of myogenin was able to restore myogenic differentiation, significantly reduced cell motility and impaired tumor growth and metastatic spread. IL-4 treatment increased rhabdomyosarcoma cell growth, decreased myogenin expression and promoted migration of cells lacking myogenin. Another approach was based on small kinase inhibitors. Agents specifically targeting members of the HER family (Lapatinib), of the IGF system (NVP-AEW541) or downstream signal transducers (NVP-BEZ235) were investigated in vitro in human rhabdomyosarcoma cell lines as therapeutic anti-tumor and anti-metastatic tools. The major effects were obtained with NVP-BEZ235 treatment that was able to strongly inhibit cell growth in vitro and showed anti-metastatic effects in vivo.

Numerical and analytical approaches to strongly correlated electron systems

In this thesis we consider three different models for strongly correlated electrons, namely a multi-band Hubbard model as well as the spinless Falicov-Kimball model, both with a semi-elliptical density of states in the limit of infinite dimensions d, and the attractive Hubbard model on a square lattice in d=2. In the first part, we study a two-band Hubbard model with unequal bandwidths and anisotropic Hund's rule coupling (J_z-model) in the limit of infinite dimensions within the dynamical mean-field theory (DMFT). Here, the DMFT impurity problem is solved with the use of quantum Monte Carlo (QMC) simulations. Our main result is that the J_z-model describes the occurrence of an orbital-selective Mott transition (OSMT), in contrast to earlier findings. We investigate the model with a high-precision DMFT algorithm, which was developed as part of this thesis and which supplements QMC with a high-frequency expansion of the self-energy. The main advantage of this scheme is the extraordinary accuracy of the numerical solutions, which can be obtained already with moderate computational effort, so that studies of multi-orbital systems within the DMFT+QMC are strongly improved. We also found that a suitably defined Falicov-Kimball (FK) model exhibits an OSMT, revealing the close connection of the Falicov-Kimball physics to the J_z-model in the OSM phase. In the second part of this thesis we study the attractive Hubbard model in two spatial dimensions within second-order self-consistent perturbation theory. This model is considered on a square lattice at finite doping and at low temperatures. Our main result is that the predictions of first-order perturbation theory (Hartree-Fock approximation) are renormalized by a factor of the order of unity even at arbitrarily weak interaction (U->0). The renormalization factor q can be evaluated as a function of the filling n for 00, the q-factor vanishes, signaling the divergence of self-consistent perturbation theory in this limit. Thus we present the first asymptotically exact results at weak-coupling for the negative-U Hubbard model in d=2 at finite doping.

Integrating new and traditional approaches for the estimate of slip-rates of active faults: examples from the Mw 6.3, 2009 L’Aquila earthquake area, Central Italy

This thesis is based on the integration of traditional and innovative approaches aimed at improving the normal faults seimogenic identification and characterization, focusing mainly on slip-rate estimate as a measure of the fault activity. The L’Aquila Mw 6.3 April 6, 2009 earthquake causative fault, namely the Paganica - San Demetrio fault system (PSDFS), was used as a test site. We developed a multidisciplinary and scale‐based strategy consisting of paleoseismological investigations, detailed geomorphological and geological field studies, as well as shallow geophysical imaging and an innovative application of physical properties measurements. We produced a detailed geomorphological and geological map of the PSDFS, defining its tectonic style, arrangement, kinematics, extent, geometry and internal complexities. The PSDFS is a 19 km-long tectonic structure, characterized by a complex structural setting and arranged in two main sectors: the Paganica sector to the NW, characterized by a narrow deformation zone, and the San Demetrio sector to SE, where the strain is accommodated by several tectonic structures, exhuming and dissecting a wide Quaternary basin, suggesting the occurrence of strain migration through time. The integration of all the fault displacement data and age constraints (radiocarbon dating, optically stimulated luminescence (OSL) and tephrochronology) helped in calculating an average Quaternary slip-rate representative for the PSDFS of 0.27 - 0.48 mm/yr. On the basis of its length (ca. 20 km) and slip per event (up to 0.8 m) we also estimated a max expected Magnitude of 6.3-6.8 for this fault. All these topics have a significant implication in terms of surface faulting hazard in the area and may contribute also to the understanding of the PSDFS seismic behavior and of the local seismic hazard.

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.

Insights in the maturation of pathogenic bacteria vaccine candidates using mass spectrometry based approaches

The study of the maturation process that occurs to a protein is of pivotal importance for the understanding of its function. This is true also in the vaccine field but in this case is also important to evaluate if inappropriate protein conformation and maturation play roles in the impairment of the functional immunogenicity of protein vaccines. Mass spectrometry (MS) is the method of choice for the study of the maturation process since each modification that occurs during the maturation will lead to a change in the mass of the entire protein. Therefore the aim of my thesis is the development of mass spectrometry-based approaches to study the maturation of proteins and the application of these methods to proteic vaccine candidates. The thesis is divided in two main parts. In the first part, I focused my attention on the study of the maturation of different vaccine candidates using native mass spectrometry. The analyses in this case have been performed using recombinant proteins produced in E. coli. In the second part I applied different MS strategies for the identification of unknown PTMs on pathogenic bacteria surface proteins since modified surface proteins are now considered for vaccine candidate selection.

Modelling the stable, nocturnal boundary layer: different approaches to turbulence closure problem

Il lavoro è dedicato all'analisi fisica e alla modellizzazione dello strato limite atmosferico in condizioni stabili. L'obiettivo principale è quello di migliorare i modelli di parametrizzazione della turbulenza attualmente utilizzati dai modelli meteorologici a grande scala. Questi modelli di parametrizzazione della turbolenza consistono nell' esprimere gli stress di Reynolds come funzioni dei campi medi (componenti orizzontali della velocità e temperatura potenziale) usando delle chiusure. La maggior parte delle chiusure sono state sviluppate per i casi quasi-neutrali, e la difficoltà è trattare l'effetto della stabilità in modo rigoroso. Studieremo in dettaglio due differenti modelli di chiusura della turbolenza per lo strato limite stabile basati su assunzioni diverse: uno schema TKE-l (Mellor-Yamada,1982), che è usato nel modello di previsione BOLAM (Bologna Limited Area Model), e uno schema sviluppato recentemente da Mauritsen et al. (2007). Le assunzioni delle chiusure dei due schemi sono analizzate con dati sperimentali provenienti dalla torre di Cabauw in Olanda e dal sito CIBA in Spagna. Questi schemi di parametrizzazione della turbolenza sono quindi inseriti all'interno di un modello colonnare dello strato limite atmosferico, per testare le loro predizioni senza influenze esterne. Il confronto tra i differenti schemi è effettuato su un caso ben documentato in letteratura, il "GABLS1". Per confermare la validità delle predizioni, un dataset tridimensionale è creato simulando lo stesso caso GABLS1 con una Large Eddy Simulation. ARPS (Advanced Regional Prediction System) è stato usato per questo scopo. La stratificazione stabile vincola il passo di griglia, poichè la LES deve essere ad una risoluzione abbastanza elevata affinchè le tipiche scale verticali di moto siano correttamente risolte. Il confronto di questo dataset tridimensionale con le predizioni degli schemi turbolenti permettono di proporre un insieme di nuove chiusure atte a migliorare il modello di turbolenza di BOLAM. Il lavoro è stato compiuto all' ISAC-CNR di Bologna e al LEGI di Grenoble.

Inferences on earthquake kinematic properties from data inversion: two different approaches

During my PhD, starting from the original formulations proposed by Bertrand et al., 2000 and Emolo & Zollo 2005, I developed inversion methods and applied then at different earthquakes. In particular large efforts have been devoted to the study of the model resolution and to the estimation of the model parameter errors. To study the source kinematic characteristics of the Christchurch earthquake we performed a joint inversion of strong-motion, GPS and InSAR data using a non-linear inversion method. Considering the complexity highlighted by superficial deformation data, we adopted a fault model consisting of two partially overlapping segments, with dimensions 15x11 and 7x7 km2, having different faulting styles. This two-fault model allows to better reconstruct the complex shape of the superficial deformation data. The total seismic moment resulting from the joint inversion is 3.0x1025 dyne.cm (Mw = 6.2) with an average rupture velocity of 2.0 km/s. Errors associated with the kinematic model have been estimated of around 20-30 %. The 2009 Aquila sequence was characterized by an intense aftershocks sequence that lasted several months. In this study we applied an inversion method that assumes as data the apparent Source Time Functions (aSTFs), to a Mw 4.0 aftershock of the Aquila sequence. The estimation of aSTFs was obtained using the deconvolution method proposed by Vallée et al., 2004. The inversion results show a heterogeneous slip distribution, characterized by two main slip patches located NW of the hypocenter, and a variable rupture velocity distribution (mean value of 2.5 km/s), showing a rupture front acceleration in between the two high slip zones. Errors of about 20% characterize the final estimated parameters.

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.