Synthesis and Physical-Chemical characterization of Metallic Nanoparticles

The stabilization of nanoparticles against their irreversible particle aggregation and oxidation reactions. is a requirement for further advancement in nanoparticle science and technology. For this reason the research aim on this topic focuses on the synthesis of various metal nanoparticles protected with monolayers containing different reactive head groups and functional tail groups. In this work cuprous bromide nanocrystals haave been synthetized with a diameter of about 20 nanometers according to a new sybthetic method adding dropwise ascorbic acid to a water solution of lithium bromide and cupric chloride under continuous stirring and nitrogen flux. Butane thiolate Cu protected nanoparticles have been synthetized according to three different syntesys methods. Their morphologies appear related to the physicochemical conditions during the synthesis and to the dispersing medium used to prepare the sample. Synthesis method II allows to obtain stable nanoparticles of 1-2 nm in size both isolated and forming clusters. Nanoparticle cluster formation was enhanced as water was used as dispersing medium probably due to the idrophobic nature of the butanethiolate layers coating the nanoparticle surface. Synthesis methods I and III lead to large unstable spherical nanoparticles with size ranging between 20 to 50 nm. These nanoparticles appeared in the TEM micrograph with the same morphology independently on the dispersing medium used in the sample preparation. The stability and dimensions of the copper nanoparticles appear inversely related. Using the same methods above described for the butanethiolate protected copper nanoparticles 4-methylbenzenethiol protected copper nanoparticles have been prepared. Diffractometric and spectroscopic data reveal that decomposition processes didn’t occur in both the 4-methylbenzenethiol copper protected nanoparticles precipitates from formic acid and from water in a period of time six month long. Se anticarcinogenic effects by multiple mechanisms have been extensively investigated and documented and Se is defined a genuine nutritional cancer-protecting element and a significant protective effect of Se against major forms of cancer. Furthermore phloroglucinol was found to possess cytoprotective effects against oxidative stress, thanks to reactive oxygen species (ROS) which are associated with cells and tissue damages and are the contributing factors for inflammation, aging, cancer, arteriosclerosis, hypertension and diabetes. The goal of our work has been to set up a new method to synthesize in mild conditions amorphous Se nanopaticles surface capped with phloroglucinol, which is used during synthesis as reducing agent to obtain stable Se nanoparticles in ethanol, performing the synergies offered by the specific anticarcinogenic properties of Se and the antioxiding ones of phloroalucinol. We have synthesized selenium nanoparticles protected by phenolic molecules chemically bonded to their surface. The phenol molecules coating the nanoparticles surfaces form low ordered arrays as can be seen from the wider shape of the absorptions in the FT-IR spectrum with respect to those appearing in that of crystalline phenol. On the other hand, metallic nanoparticles with unique optical properties, facile surface chemistry and appropriate size scale are generating much enthusiasm in nanomedicine. In fact Au nanoparticles has immense potential for both cancer diagnosis and therapy. Especially Au nanoparticles efficiently convert the strongly adsorbed light into localized heat, which can be exploited for the selective laser photothermal therapy of cancer. According to the about, metal nanoparticles-HA nanocrystals composites should have tremendous potential in novel methods for therapy of cancer. 11 mercaptoundecanoic surface protected Au4Ag1 nanoparticles adsorbed on nanometric apathyte crystals we have successfully prepared like an anticancer nanoparticles deliver system utilizing biomimetic hydroxyapatyte nanocrystals as deliver agents. Furthermore natural chrysotile, formed by densely packed bundles of multiwalled hollow nanotubes, is a mineral very suitable for nanowires preparation when their inner nanometer-sized cavity is filled with a proper material. Bundles of chrysotile nanotubes can then behave as host systems, where their large interchannel separation is actually expected to prevent the interaction between individual guest metallic nanoparticles and act as a confining barrier. Chrysotile nanotubes have been filled with molten metals such as Hg, Pb, Sn, semimetals, Bi, Te, Se, and with semiconductor materials such as InSb, CdSe, GaAs, and InP using both high-pressure techniques and metal-organic chemical vapor deposition. Under hydrothermal conditions chrysotile nanocrystals have been synthesized as a single phase and can be utilized as a very suitable for nanowires preparation filling their inner nanometer-sized cavity with metallic nanoparticles. In this research work we have synthesized and characterized Stoichiometric synthetic chrysotile nanotubes have been partially filled with bi and monometallic highly monodispersed nanoparticles with diameters ranging from 1,7 to 5,5 nm depending on the core composition (Au, Au4Ag1, Au1Ag4, Ag). In the case of 4 methylbenzenethiol protected silver nanoparticles, the filling was carried out by convection and capillarity effect at room temperature and pressure using a suitable organic solvent. We have obtained new interesting nanowires constituted of metallic nanoparticles filled in inorganic nanotubes with a inner cavity of 7 nm and an isolating wall with a thick ranging from 7 to 21 nm.

Electrochemistry of carbon based engineered structures

The main aims of my PhD research work have been the investigation of the redox, photophysical and electronic properties of carbon nanotubes (CNT) and their possible uses as functional substrates for the (electro)catalytic production of oxygen and as molecular connectors for Quantum-dot Molecular Automata. While for CNT many and diverse applications in electronics, in sensors and biosensors field, as a structural reinforcing in composite materials have long been proposed, the study of their properties as individual species has been for long a challenging task. CNT are in fact virtually insoluble in any solvent and, for years, most of the studies has been carried out on bulk samples (bundles). In Chapter 2 an appropriate description of carbon nanotubes is reported, about their production methods and the functionalization strategies for their solubilization. In Chapter 3 an extensive voltammetric and vis-NIR spectroelectrochemical investigation of true solutions of unfunctionalized individual single wall CNT (SWNT) is reported that permitted to determine for the first time the standard electrochemical potentials of reduction and oxidation as a function of the tube diameter of a large number of semiconducting SWNTs. We also established the Fermi energy and the exciton binding energy for individual tubes in solution and, from the linear correlation found between the potentials and the optical transition energies, one to calculate the redox potentials of SWNTs that are insufficiently abundant or absent in the samples. In Chapter 4 we report on very efficient and stable nano-structured, oxygen-evolving anodes (OEA) that were obtained by the assembly of an oxygen evolving polyoxometalate cluster, (a totally inorganic ruthenium catalyst) with a conducting bed of multiwalled carbon nanotubes (MWCNT). Here, MWCNT were effectively used as carrier of the polyoxometallate for the electrocatalytic production of oxygen and turned out to greatly increase both the efficiency and stability of the device avoiding the release of the catalysts. Our bioinspired electrode addresses the major challenge of artificial photosynthesis, i.e. efficient water oxidation, taking us closer to when we might power the planet with carbon-free fuels. In Chapter 5 a study on surface-active chiral bis-ferrocenes conveniently designed in order to act as prototypical units for molecular computing devices is reported. Preliminary electrochemical studies in liquid environment demonstrated the capability of such molecules to enter three indistinguishable oxidation states. Side chains introduction allowed to organize them in the form of self-assembled monolayers (SAM) onto a surface and to study the molecular and redox properties on solid substrates. Electrochemical studies on SAMs of these molecules confirmed their attitude to undergo fast (Nernstian) electron transfer processes generating, in the positive potential region, either the full oxidized Fc+-Fc+ or the partly oxidized Fc+-Fc species. Finally, in Chapter 6 we report on a preliminary electrochemical study of graphene solutions prepared according to an original procedure recently described in the literature. Graphene is the newly-born of carbon nanomaterials and is certainly bound to be among the most promising materials for the next nanoelectronic generation.

Use of VEGFR-2 targeted microbubbles (BR55, Bracco imaging) for the early ultrasound evaluation of response to antiangiogenic treatment in a xenograft model of hepatocarcinoma

Aim: To evaluate the early response to treatment to an antiangiogenetic drug (sorafenib) in a heterotopic murine model of hepatocellular carcinoma (HCC) using ultrasonographic molecular imaging. Material and Methods: the xenographt model was established injecting a suspension of HuH7 cells subcutaneously in 19 nude mice. When tumors reached a mean diameter of 5-10 mm, they were divided in two groups (treatment and vehicle). The treatment group received sorafenib (62 mg/kg) by daily oral gavage for 14 days. Molecular imaging was performed using contrast enhanced ultrasound (CEUS), by injecting into the mouse venous circulation a suspension of VEGFR-2 targeted microbubbles (BR55, kind gift of Bracco Swiss, Geneve, Switzerland). Video clips were acquired for 6 minutes, then microbubbles (MBs) were destroyed by a high mechanical index (MI) impulse, and another minute was recorded to evaluate residual circulating MBs. The US protocol was repeated at day 0,+2,+4,+7, and +14 from the beginning of treatment administration. Video clips were analyzed using a dedicated software (Sonotumor, Bracco Swiss) to quantify the signal of the contrast agent. Time/intensity curves were obtained and the difference of the mean MBs signal before and after high MI impulse (Differential Targeted Enhancement-dTE) was calculated. dTE represents a numeric value in arbitrary units proportional to the amount of bound MBs. At day +14 mice were euthanized and the tumors analyzed for VEGFR-2, pERK, and CD31 tissue levels using western blot analysis. Results: dTE values decreased from day 0 to day +14 both in treatment and vehicle groups, and they were statistically higher in vehicle group than in treatment group at day +2, at day +7, and at day +14. With respect to the degree of tumor volume increase, measured as growth percentage delta (GPD), treatment group was divided in two sub-groups, non-responders (GPD>350%), and responders (GPD<200%). In the same way vehicle group was divided in slow growth group (GPD<400%), and fast growth group (GPD>900%). dTE values at day 0 (immediately before treatment start) were higher in non-responders than in responders group, with statistical difference at day 2. While dTE values were higher in the fast growth group than in the slow growth group only at day 0. A significant positive correlation was found between VEGFR-2 tissue levels and dTE values, confirming that level of BR55 tissue enhancement reflects the amount of tissue VEGF receptor. Conclusions: the present findings show that, at least in murine experimental models, CEUS with BR55 is feasable and appears to be a useful tool in the prediction of tumor growth and response to sorafenib treatment in xenograft HCC.

Study of Italian isolates of Alternaria spp.: molecular and morphological characterization and pathogenesis on apple tree

It was decided to carry out a morphological and molecular characterization of the Italian Alternaria isolatescollected from apple , and evaluate their pathogenicity and subsequently combining the data collected. The strain collection (174 isolates) was constructed by collecting material (received from extension service personnel) between June and August of 2007, 2008, and 2009. A Preliminary bioassays were performed on detached plant materials (fruit and leaf wounded and unwounded), belonging to the Golden cultivar, with two different kind of inoculation (conidial suspension and conidial filtrate). Symptoms were monitored daily and a value of pathogenicity score (P.S.) was assigned on the basis of the diameter of the necrotic area that developed. On the basis of the bioassays, the number of isolates to undergo further molecular analysis was restricted to a representative set of single spore strains (44 strains). Morphological characteristics of the colony and sporulation pattern were determined according to previous systematic work on small-spored Alternaria spp. (Pryor and Michaelides, 2002 and Hong et al., 2006). Reference strains (Alternaria alternata, Alternaria tenuissima, Alternaria arborescens and four Japanese strains of Alternaria alternata mali pathotype), used in the study were kindly provided by Prof. Barry Pryor, who allows a open access to his own fungal collection. Molecular characterization was performed combining and comparing different data sets obtained from distinct molecular approach: 1) investigation of specific loci and 2) fingerprinting based on diverse randomly selected polymorphic sites of the genome. As concern the single locus analysis, it was chosen to sequence the EndoPG partial gene and three anonymous region (OPA1-3, OPA2- and OPa10-2). These markers has revealed a powerful tool in the latter systematic works on small-spored Alternaria spp. In fact, as reported in literature small-spored Alternaria taxonomy is complicated due to the inability to resolve evolutionary relationships among the taxa because of the lack of variability in the markers commonly used in fungi systematic. The three data set together provided the necessary variation to establish the phylogenetic relationships among the Italian isolates of Alternaria spp. On Italian strains these markers showed a variable number of informative sites (ranging from 7 for EndoPg to 85 for OPA1-3) and the parsimony analysis produced different tree topologies all concordant to define A. arborescens as a mophyletic clade. Fingerprinting analysis (nine ISSR primers and eight AFLP primers combination) led to the same result: a monophyleic A. arborescens clade and one clade containing both A. tenuissima and the A. alternata strains. This first attempt to characterize Italian Alternaria species recovered from apple produced concordant results with what was already described in a similar phylogenetic study on pistachio (Pryor and Michaelides, 2002), on walnut and hazelnut (Hong et al., 2006), apple (Kang et al., 2002) and citurus (Peever et al., 2004). Together with these studies, this research demonstrates that the three morphological groups are widely distributed and occupy similar ecological niches. Furthermore, this research suggest that these Alternaria species exhibit a similar infection pattern despite the taxonomic and pathogenic differences. The molecular characterization of the pathogens is a fundamental step to understanding the disease that is spreading in the apple orchards of the north Italy. At the beginning the causal agent was considered as Alteraria alternata (Marshall and Bertagnoll, 2006). Their preliminary studies purposed a pathogenic system related to the synthesis of toxins. Experimental data of our bioassays suggest an analogous hypothesis, considering that symptoms could be induced after inoculating plant material with solely the filtrate from pathogenic strains. Moreover, positive PCR reactions using AM-toxin gene specific primers, designed for identification of apple infecting Alternaria pathovar, led to a hypothesis that a host specific toxin (toxins) were involved. It remains an intriguing challenge to discover or not if the agent of the “Italian disease” is the same of the one previously typified as Alternaria mali, casual agent of the apple blotch disease.

Graph algorithms for bioinformatics

Biological data are inherently interconnected: protein sequences are connected to their annotations, the annotations are structured into ontologies, and so on. While protein-protein interactions are already represented by graphs, in this work I am presenting how a graph structure can be used to enrich the annotation of protein sequences thanks to algorithms that analyze the graph topology. We also describe a novel solution to restrict the data generation needed for building such a graph, thanks to constraints on the data and dynamic programming. The proposed algorithm ideally improves the generation time by a factor of 5. The graph representation is then exploited to build a comprehensive database, thanks to the rising technology of graph databases. While graph databases are widely used for other kind of data, from Twitter tweets to recommendation systems, their application to bioinformatics is new. A graph database is proposed, with a structure that can be easily expanded and queried.

A genome editing approach to the study of Parvovirus B19

Parvovirus B19 (B19V) is a ssDNA virus, with a 5596 nt long genome encapsidated within an icosahedral capsid with a diameter of 22 nm. Viral proteins are subdivided into structural and non-structural: the main non-structural one is the NS1, while the 2 structural proteins VP1 and VP2 assemble originating the capsid shell. B19V tropism is mainly limited to erythroid progenitor cells (EPCs), however, virus can be detected in several districts persisting in tissues possibly lifelong. The virus can induce anemia and erythroid aplasia. Therapeutic strategies are only symptomatic, so the search for antivirals is strongly active, with screenings showing the activity in vitro of different compounds like hydroxyurea, cidofovir and brincidofovir. In the first project, a functional minigenome of B19V was developed, able to express only the NS1 protein. This minigenome proved able to replicate and express the NS1 at levels comparable to unmodified clones. Furthermore, the ability of this minigenome to complement the function of NS1-deficient genomes was demonstrated, thus providing a proof-of-concept of B19V genome editing possibility and, at the same time, a useful tool to study the NS1 protein also as an antiviral target. In the second project I addressed the interplay between B19V and the cellular restriction factor APOBEC3B (A3B), a cytidine deaminase acting on ssDNA, whose footprint on B19V genome was proved by a bioinformatic sequence analysis performed by the hosting lab. To understand whether A3B still exerts activity and a potential antiviral effect on B19V, the UT7/EpoS1 cells were transduced with lentiviral vectors to silence A3B expression, then used as a model to study viral behavior. No significant role of A3B on B19V was demonstrated, in agreement with the hypothesis of viral adaptation to this cellular restriction factor; anyway, virus ability to alter A3B expression would deserve further investigations.

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.