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.

Development of new therapeutic approaches in the treatments of Inflammatory Bowel Diseases: functional food and nutraceuticals vs synthetic peptides based vaccines

Inflammatory Bowel Diseases (IBD) are intestinal chronic relapsing diseases which ethiopathogenesis remains uncertain. Several group have attempted to study the role of factors involved such as genetic susceptibility, environmental factors such as smoke, diet, sex, immunological factors as well as the microbioma. None of the treatments available satisfy several criteria at the same time such as safety, long-term remission, histopatological healing, and specificity. We used two different approaches for the development of new therapeutic treatment for Inflammatory Bowel Disease. The first is focused on the understanding of the potential role of functional food and nutraceuticals nutrients in the treatment of IBD. To do so, we investigated the role of Curcuma longa in the treatment of chemical induced colitis in mice model. Since Curcma Longa has been investigated for its antinflammatory role related to the TNFα pathway as well investigators have reported few cases of patients with ulcerative colites treated with this herbs, we harbored the hypothesis of a role of Curcuma Longa in the treatment f IBD as well as we decided to assess its role in intestinal motility. The second part is based on an immunological approach to develop new drugs to induce suppression in Crohn’s disease or to induce mucosa immunity such as in colonrectal tumor. The main idea behind this approach is that we could manipulate relevant cell-cell interactions using synthetic peptides. We demonstrated the role of the unique interaction between molecules expressed on intestinal epithelial cells such as CD1d and CEACAM5 and on CD8+ T cells. In normal condition this interaction has a role for the expansion of the suppressor CD8+ T cells. Here, we characterized this interaction, we defined which are the epitope involved in the binding and we attempted to develop synthetic peptides from the N domain of CEACAM5 in order to manipulate it.

Effects of Global Warming on Berry Composition of cv. Sangiovese: Biochemical and Molecular Aspects and Agronomical Adaptation Approaches

Wine grape must deal with serious problems due to the unfavorable climatic conditions resulted from global warming. High temperatures result in oxidative damages to grape vines. The excessive elevated temperatures are critical for grapevine productivity and survival and contribute to degradation of grape and wine quality and yield. Elevated temperature can negatively affect anthocyanin accumulation in red grape. Particularly, cv. Sangiovese was identified to be very sensitive to such condition. The quantitative real-time PCR analysis showed that flavonoid biosynthetic genes were slightly repressed by high temperature. Also, the heat stress repressed the expression of the transcription factor “VvMYBA1” that activates the expression of UFGT. Moreover, high temperatures had repressing effects on the activity of the flavonoids biosynthetic enzymes “PAL” and “UFGT”.Anthocyanin accumulation in berry skin is due to the balance between its synthesis and oxidation. In grape cv. Sangiovese, the gene transcription and activity of peroxidases enzyme was elevated by heat stress as a defensive mechanism of ROS-scavenging. Among many isoforms of peroxidases genes, one gene (POD 1) was induced in Sangiovese under thermal stress condition. This gene was isolated and evaluated via the technique of genes transformation from grape to Petunia. Reduction in anthocyanins concentration and higher enzymatic activity of peroxidase was observed in POD 1 transformed Petunia after heat shock compared to untrasformed control. Moreover, in wine producing regions, it is inevitable for the grape growers to adopt some adaptive strategies to alleviate grape damages to abiotic stresses. Therefore, in this thesis, the technique of post veraison trimming was done to improve the coupling of phenolic and sugar ripening in Vitis vinifera L. cultivar Sangiovese. Trimming after veraison showed to be executable to slow down the rate of sugar accumulation in grape (to decrease the alcohol potential in wines) without evolution of the main berry flavonoids compounds.

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.

Role of new molecular approaches for the early diagnosis of bladder cancer in clinical practice

There is an urgent need to improve the performance of urine cytology for the diagnosis of bladder cancer. In preliminary studies, telomerase activity evaluated by telomeric repeat amplification protocol (TRAP) assay and chromosomal aneuploidy detected by fluorescence in situ hybridization (FISH) in the diagnosis of bladder cancer have produced important results. Urine cell-free (UCF) DNA has also been proposed as a potential marker for early bladder cancer diagnosis. In the first study the diagnostic performance of TRAP assay and FISH analysis was assessed, while the second study evaluated the potential role of UCF DNA integrity in early bladder cancer diagnosis. In the first cross-sectional study, 289 consecutive patients who presented with urinary symptoms underwent cystoscopy and cytology evaluation. In the second study, UCF DNA was isolated from 51 bladder cancer patients, 46 symptomatic patients, and 32 healthy volunteers. c-Myc, BCAS1 and HER2 gene sequences longer than 250 bp were quantified by real time PCR to verify UCF DNA integrity. In the first study, sensitivity and specificity were 0.39 and 0.83, respectively, for cytology; 0.66 and 0.72 for TRAP; 0.78 and 0.60 for the cytology and TRAP combination; 0.78 and 0.78 for the cytology, TRAP and FISH combination; and 0.65 and 0.93 for the TRAP and FISH combination. In the second study, at the best cutoff of 0.1 ng/µl, UCF DNA integrity analysis showed a sensitivity of 0.73 and a specificity of 0.84 in healthy individuals and 0.83 in symptomatic patients. The preliminary results suggest that these biomarkers could potentially be used for the early diagnosis of bladder cancer, especially in high-risk populations (e.g, symptomatic individuals exposed to occupational risk) who may benefit from the use of noninvasive diagnostic tests in terms of cost-benefit.