Employing theoretical methods for chemical prediction: a ticket into copolymerization, metal-organic catalysis and antioxidants.

The thesis shows how ab initio and DFT quantum chemical methods can be useful toward the interpretation and the prediction of chemical properties and reactivities. Well know post-Hartree-Fock quantum chemical methods and stochastic simulation approaches are intermixed, the synergy between them providing all the tools needed to evaluate the impact and validity of reaction mechanisms, for instance helping to rationalize radical and homogeneously catalyzed copolymerizations. The potentially positive impact that theoretical chemistry can have in those contexts was exploited to put the basis of new theoretical protocols able to predict the chemical features, that is still an attractive goal in academic and industrial field. The first study regards an example of how theoretical chemistry can provide information otherwise not achievable from experimental measurement. Specifically, by means of ab initio perturbation theory, we study novel anion receptors acting via hydrogen-bonding and halogen-bonding: UV-Vis and 1H-NMR titrations show that Iodine on the target receptor enhance the anion binding tendencies and X-ray structures evidenc the formation of halogen-bonding. The geometries in solution computed via MP2, however, reveal few possible conformers of the proposed molecules: theoretical energies allow the calculation of the ion pair dissociation energy (IPDE) as a way to evaluate the affinity between the molecules and an anion. IPDE values gave the same trend of experimental affinity constants, confirming the experimental constant affinities; moreover, computed chemical shifts of conformers help the interpretation of 1H-NMR titrations, giving the right importance at the HB and XB conformers in solution. The second topic is the prediction of the antioxidant activity through a theoretical approach, that led to the benchmark of DFT methods. The in depth study of two prototype molecules, edaravone and quercetin, carries out the bond dissociation enthalpy (BDE), the ionization potential (IP) and the proton dissociation enthalpy (PDE); the examination of the cumulative mean absolute error on the three parameters, compared to CBS-Q3 reference values, indicates the most suitable methods (LC-!PDE, M05-2X and M06-2X). Once the method was defined, we have studied 15 antioxidant belonging to the flavonols family, computating BDE, IP, PDE, proton affinity (PA) and electron transfer enthalpy (ETE) in vacuum and in water; these theoretical parameters are then correlated individually to several experimental data set. Among all attempts, the best correlation was found with ETE in vacuum (showing a R2=0.93 on 6 data set), that allows us to suppose that ETE is the theoretical parameter determining for prediction of antioxidant activity. After the analysis about the properties of a single molecule, DFT is employed to rationalize the products of a chemical reaction. In particular, we study the alkoxyhalogenation of alkynyl ureas and carbamates catalyzed by CuCl2, with the final aim of defining the reactive step that influence the selectivity. First, we propos a mechanism coherent with experimental product, characterizing all the minima and the transition states via DFT vibrational analysis. Studying in depth the equilibria involved at the beginning of the reaction, we characterize the two tautomers and two coordination site of CuCl2, the C-C triple bond and the heteroatom; moreover, we describe the formation of dimers between two urea and the catalyst. Dimers\u2019 stabilization plus the comparison of the energy paths lead to expect the production of the 5-exo-O product, in total accord with experiments. Successively, we attempt to apply the same mechanism on two carbamates, following the same approach than before. The results however rationalize only partially the experiments, in fact, for the phenyl-N-carbamate we observe a strong kinetic competition between two paths, at the same time the experiments carry out a mixture of products; instead, the reaction on tosyl-N-carbamate experimentally leads to a single product, while the theoretical investigation is not able to discriminate between two different products. In the last Chapter we aim higher, trying to predict the copolymer features boosting the DFT method with stochastic simulations; the ability to predict the microstructure of a copolymer would be a great help during the design process and the set up of a catalyzed copolymerization. In this regards, we decided to study the copolymerization of methyl methacrylate (MMA) and 2-(dimethylamino)ethyl methacrylate (DMAEMA) obtained via atomic-transfer radical-polymerization (ATRP), since the macroscopic properties used in biological fields are strictly related to the microscopic structure. Here we propose a synergistic DFT/kinetic Monte Carlo approach: by means of DFT, we compute the energies of monomers, dimers and transition states, thanks to which e calculate the reactivity ratios r1 and r2; employing the DFT data, we wrote a kMC code that, treating the copolymerization as a Markov chain, carries out the chains\u2019 microstructure, the distributions of monomers, diads and triads along the chains. The results give indication about the presence of a preferential partitioning of one of the two monomers close to each one of the two radicals, known as bootstrap effect. Moreover, the triad distributions along the chain reveal the gradient nature of the copolymer, suggesting different features of the chains at the proximity of the core of PEG and at the end, influencing directly the behavior of the materials in solution. Then, our attention moves on the homogeneous-catalyzed copolymerization. The aim of the investigation pointed the attention on the characterization of copolymerization mechanism and on the effect of penultimate monomers and the counter ion on the reactivity. The synergistic DFT-kMC approach is applied on the ethene/propene copolymerization catalyzed by two C2-symmetric catalyst, carrying out several interesting results; among all simulated systems, we reproduce the experimental data only taking into account specific features. In order to obtain results close to the experiments, the model has to include: the presence of two coordination sites, both giving active paths for the insertion, the coordination preequilibrium as well-defined step, the influence of the counter ion on the coordination barriers. These claim underline the importance of several aspect generally overlooked during the copolymerization; moreover, the ability to reproduce the experimental results can open the way to a theoretical model able to predict the product of a homogeneous catalyzed copolymerization

Employing theoretical methods for chemical prediction: a ticket into copolymerization, metal-organic catalysis and antioxidants.

The thesis shows how ab initio and DFT quantum chemical methods can be useful toward the interpretation and the prediction of chemical properties and reactivities. Well know post-Hartree-Fock quantum chemical methods and stochastic simulation approaches are intermixed, the synergy between them providing all the tools needed to evaluate the impact and validity of reaction mechanisms, for instance helping to rationalize radical and homogeneously catalyzed copolymerizations. The potentially positive impact that theoretical chemistry can have in those contexts was exploited to put the basis of new theoretical protocols able to predict the chemical features, that is still an attractive goal in academic and industrial field. The first study regards an example of how theoretical chemistry can provide information otherwise not achievable from experimental measurement. Specifically, by means of ab initio perturbation theory, we study novel anion receptors acting via hydrogen-bonding and halogen-bonding: UV-Vis and 1H-NMR titrations show that Iodine on the target receptor enhance the anion binding tendencies and X-ray structures evidenc the formation of halogen-bonding. The geometries in solution computed via MP2, however, reveal few possible conformers of the proposed molecules: theoretical energies allow the calculation of the ion pair dissociation energy (IPDE) as a way to evaluate the affinity between the molecules and an anion. IPDE values gave the same trend of experimental affinity constants, confirming the experimental constant affinities; moreover, computed chemical shifts of conformers help the interpretation of 1H-NMR titrations, giving the right importance at the HB and XB conformers in solution. The second topic is the prediction of the antioxidant activity through a theoretical approach, that led to the benchmark of DFT methods. The in depth study of two prototype molecules, edaravone and quercetin, carries out the bond dissociation enthalpy (BDE), the ionization potential (IP) and the proton dissociation enthalpy (PDE); the examination of the cumulative mean absolute error on the three parameters, compared to CBS-Q3 reference values, indicates the most suitable methods (LC-!PDE, M05-2X and M06-2X). Once the method was defined, we have studied 15 antioxidant belonging to the flavonols family, computating BDE, IP, PDE, proton affinity (PA) and electron transfer enthalpy (ETE) in vacuum and in water; these theoretical parameters are then correlated individually to several experimental data set. Among all attempts, the best correlation was found with ETE in vacuum (showing a R2=0.93 on 6 data set), that allows us to suppose that ETE is the theoretical parameter determining for prediction of antioxidant activity. After the analysis about the properties of a single molecule, DFT is employed to rationalize the products of a chemical reaction. In particular, we study the alkoxyhalogenation of alkynyl ureas and carbamates catalyzed by CuCl2, with the final aim of defining the reactive step that influence the selectivity. First, we propos a mechanism coherent with experimental product, characterizing all the minima and the transition states via DFT vibrational analysis. Studying in depth the equilibria involved at the beginning of the reaction, we characterize the two tautomers and two coordination site of CuCl2, the C-C triple bond and the heteroatom; moreover, we describe the formation of dimers between two urea and the catalyst. Dimers’ stabilization plus the comparison of the energy paths lead to expect the production of the 5-exo-O product, in total accord with experiments. Successively, we attempt to apply the same mechanism on two carbamates, following the same approach than before. The results however rationalize only partially the experiments, in fact, for the phenyl-N-carbamate we observe a strong kinetic competition between two paths, at the same time the experiments carry out a mixture of products; instead, the reaction on tosyl-N-carbamate experimentally leads to a single product, while the theoretical investigation is not able to discriminate between two different products. In the last Chapter we aim higher, trying to predict the copolymer features boosting the DFT method with stochastic simulations; the ability to predict the microstructure of a copolymer would be a great help during the design process and the set up of a catalyzed copolymerization. In this regards, we decided to study the copolymerization of methyl methacrylate (MMA) and 2-(dimethylamino)ethyl methacrylate (DMAEMA) obtained via atomic-transfer radical-polymerization (ATRP), since the macroscopic properties used in biological fields are strictly related to the microscopic structure. Here we propose a synergistic DFT/kinetic Monte Carlo approach: by means of DFT, we compute the energies of monomers, dimers and transition states, thanks to which e calculate the reactivity ratios r1 and r2; employing the DFT data, we wrote a kMC code that, treating the copolymerization as a Markov chain, carries out the chains’ microstructure, the distributions of monomers, diads and triads along the chains. The results give indication about the presence of a preferential partitioning of one of the two monomers close to each one of the two radicals, known as bootstrap effect. Moreover, the triad distributions along the chain reveal the gradient nature of the copolymer, suggesting different features of the chains at the proximity of the core of PEG and at the end, influencing directly the behavior of the materials in solution. Then, our attention moves on the homogeneous-catalyzed copolymerization. The aim of the investigation pointed the attention on the characterization of copolymerization mechanism and on the effect of penultimate monomers and the counter ion on the reactivity. The synergistic DFT-kMC approach is applied on the ethene/propene copolymerization catalyzed by two C2-symmetric catalyst, carrying out several interesting results; among all simulated systems, we reproduce the experimental data only taking into account specific features. In order to obtain results close to the experiments, the model has to include: the presence of two coordination sites, both giving active paths for the insertion, the coordination preequilibrium as well-defined step, the influence of the counter ion on the coordination barriers. These claim underline the importance of several aspect generally overlooked during the copolymerization; moreover, the ability to reproduce the experimental results can open the way to a theoretical model able to predict the product of a homogeneous catalyzed copolymerization

Statistical moments of power spectrum: a fast tool for the classification of seismic events recorded on volcanoes

Abstract. Spectral analysis has been applied to almost thousand seismic events recorded at Vesuvius volcano (Naples, southern Italy) in 2018 with the aim to test a new tool for a fast event classification. We computed two spectral parameters, central frequency and shape factor, from the spectral moments of order 0, 1, and 2, for each event at seven seismic stations taking the mean among the three components of ground motion. The analyzed events consist of volcano-tectonic earthquakes, low frequency events and unclassified events (landslides, rockfall, thunders, quarry blasts, etc.). Most of them are of low magnitude, and/or low maximum signal amplitude, therefore the signal to noise ratio is very different between the low noise summit stations and the higher noise stations installed at low elevation around the volcano. The results of our analysis show that volcano-tectonic earthquakes and low frequency events are easily distinguishable through the spectral moments values, particularly at seismic stations closer to the epicenter. On the contrary, unclassified events show the spectral parameters values distributed in a broad range which overlap both the volcano-tectonic earthquakes and the low frequency events. Since the computation of spectral parameters is extremely easy and fast for a detected event, it may become an effective tool for event classification in observatory practice

Array and spectral ratio techniques applied to seismic noise to investigate the Campi Flegrei (Italy) subsoil structure at different scales

Abstract. The purpose of this work is to study the subsoil structure of the Campi Flegrei area using both spectral ratios and array techniques applied to seismic noise. We have estimated the dispersion curves of Rayleigh waves by applying the Frequency–Wavenumber (f–k hereinafter) and Modified Spatial Autocorrelation (MSPAC) techniques to the seismic noise recorded by the underground short period seismic Array "ARF", by the broadband stations of the UNREST experiment and by the broadband stations of the seismic monitoring network of INGV – Osservatorio Vesuviano. We have performed the inversion of a dispersion curve (obtained averaging the f–k and MSPAC dispersion curves of seismic noise and single phase velocity values of coherent transient signals) jointly with the H∕V spectral ratio of the broadband station CELG, to obtain a shear wave velocity model up to 2000 m depth. The best-fit model obtained is in a good agreement with the stratigraphic information available in the area coming from shallow boreholes and deep wells drilled for geothermal exploration. In active volcanic areas, such as Campi Flegrei, the definition of the velocity model is a crucial issue to characterize the physical parameters of the medium. Generally, a high quality characterization of the medium properties helps to separate the contributions of the volcanic source, path and site in the geophysical observables. Therefore, monitoring possible variations in time of such properties in general can help to recognize anomalies due to the volcano dynamics, i.e. fluid migration connected to the volcanic activity

Scattering and absorption imaging of a highly fractured fluid-filled seismogenetic volume in a region of slow deformation

Regions of slow strain often produce swarm-like sequences, characterized by the lack of a clear mainshock-aftershock pattern. The comprehension of their underlying physical mechanisms is challenging and still debated. We used seismic recordings from the last Pollino swarm (2010–2014) and nearby to separate and map seismic scattering (from P peak-delays) and absorption (from late-time coda-wave attenuation) at different frequencies in the Pollino range and surroundings. High-scattering and high-absorption anomalies are markers of a fluid-filled fracture volume extending from SE to NW (1.5–6 Hz) across the range. With increasing frequency, these anomalies approximately cover the area where the strongest earthquakes occurred from the sixteenth century until 1998. In our interpretation, the NW fracture propagation ends where carbonates of the Lucanian Apennines begin, as marked by a high-scattering and low-absorption area. At the highest frequency (12 Hz) the anomalies widen southward in the middle of the range, consistently marking the faults active during the recent Pollino swarm. Our results suggest that fracture healing has closed small-scale fractures across the SE faults that were active in the past centuries, and that the propagation of fluids may have played a crucial role in triggering the 2010–2014 Pollino swarm. Assuming that the fluid propagation ended at the carbonates barrier in the NW direction, fractures opened new paths to the South, favoring the nucleation of the last Pollino swarm. Indeed, the recently active faults in the middle of the seismogenic volume are marked by a high-scattering and high-absorption footprints. Our work provides evidence that attenuation parameters may track shape and dynamics of fluid-filled fracture networks in fault areas. Keywords: Pollino, Seismic attenuation, Scattering, Fluids, Fractures, Healin

Social Support Mediates the Relationship between Body Image Distress and Depressive Symptoms in Prostate Cancer Patients

Treatments for prostate cancer (PCa), the second most common cancer in men, may affect the body image (BI) of patients, increasing the risk of negative mental health outcomes. However, an enabling social support network may be a protective factor against the effects of BI distress on health. Therefore, the present study examined the mediating role of social support in the relationship between BI distress and depressive symptoms. Data were retrospectively collected from 197 PCa patients aged from 48 to 79 years (M = 67.19; SD = 6.83). The statistical package for the social sciences with PROCESS Macro was used to assess the direct and mediating effects with bias-corrected bootstrapping (10,000 samples). Results showed that BI distress was positively associated with depressive symptoms and that social support partially mediated this relationship. Moreover, among the different sources of social support, only friend support significantly mediated the association between BI distress and depressive symptoms. This study sheds light on the crucial role of social support as a dimension that can promote health in PCa patients

Giant endobronchial hamartoma resected by fiberoptic bronchoscopy electrosurgical snaring

Less than 1% of lung neoplasms are represented by benign tumors. Among these, hamartomas are the most common with an incidence between 0.025% and 0.32%. In relation to the localization, hamartomas are divided into intraparenchymal and endobronchial

COULD JC VIRUS PROVOKE METASTASIS IN COLON CANCER?

AIM: to evaluate the prevalence of John Cunningham Virus (JC virus) in a small cohort of patients with colon cancer and to assess its presence in hepatic metastasis.METHOD: Neneteen consecutive patients with histologically diagnosed colon cancer were included in our study, together with ten subjects affected by histologically and serologically diagnosed hepatitis C virus infection. in the patients included in the colon cancer group, JC virus was searched for the surgical specimen; in the control group, JC virus was searched in the hepatic biopsy. The difference in the prevalence of JC virus in the hepatic biopsy between the two groups was assessed through the X2 test. RESULTS: Four of 19 patients with colon cancer had a positive polymerase chain reaction (PCR) test for JC virus, and four had liver metastasis. Among the patients with liver metastasis, three out four had a positive PCR test for JC virus in the surgical specimen and in the liver biopsy; the only patient with liver metastasis with a negative test for JC virus also presenrted a negative test for JC virus in the surgical specimen. in the control group of patients with hepatitis C infection, none of the ten patients presented JC virus infection in the hepatic biopsy. The difference between the two groups regarding JC virus infection was statistically significant (X2=9.55, P=0,002)

The Borehole Experiment: Investigation of Cortical Structures Through 3D Array Techniques

Over the last few years it is growing the need to monitor the volcanic activity with modern technology in order to mitigate volcanic hazard through the detection of any possible precursor phenomena. The use of high performance seismic stations, such as borehole instruments, may increase the signal to noise ratio (SNR), improving the capability to detect very small signals. Over the past 40 years much attention has been given to the use of seismic arrays to measure the slowness vector of coherent signals. The main advantage of seismic arrays consists in their ability to detect weak or emergent signals, and to allow for an effective noise reduction through multichannel waveform stacking. A reliable prediction of the ray-path back-propagated from the recording site to the source is strongly limited by the poor knowledge of the local shallow velocity structure. Usually in volcanic environments the propagation of seismic signals through the shallow layers is strongly affected by lateral heterogeneity, attenuation, scattering, and interaction with the free surface. Driven by these motivations, on May 2014, in collaboration with the colleagues of Osservatorio Vesuviano (INGV), we deployed a 3D seismic array in the area where the borehole seismic station called Pozzo Pitarrone is installed at a depth of about 130 meters. This will improve our knowledge about: • the structure of the top layer and its relationship with geology; • analysis of the signal to noise ratio (SNR) of volcanic signals as a function of frequency; • study of seismic ray-path deformation caused by the interaction of the seismic waves with the free surface; • evaluation of the attenuation of the seismic signals correlated with the volcanic activity. The results of these analyses will improve the general knowledge of wave propagation in the shallow layers and will give a new contribution to the seismic monitoring of Etna volcano.PublishedNicolosi (Catania), Italy1T. Struttura della Terr