Thiyl radicals are co-products of dinitrosyl iron complex (DNIC) formation.

Thiyl radicals are detected by EPR as co-products of dinitrosyl iron complex (DNIC) formation. In demonstrating that DNIC formation generates RS˙ in a NO rich environment, these results provide a novel route for S-nitroso thiol formation

Managing emergent stigmatised social identities at work: a study of the antecedents, consequences, and evolution of individual coping and identity management strategies

This thesis asks what happens when individuals targeted with prejudiced behaviours push back on discrimination at work? It investigates when and how individuals resist, and what outcomes ensue for them personally and the organisation. Deploying a triangulation strategy, the multi-method approach of this thesis allowed for the investigation of the phenomenon from different and complementary perspectives. Study 1 is a qualitative, exploratory study that introduces the concept of emergent stigma, which I define as a stigmatised social identity that comes into being by acquisition and/or disclosure, and stress and coping as analytical lens for this thesis. Exploring the experience of individuals with an emergent stigma, this study gathers evidence of resistance to discrimination at work, and identifies key items in the process of stigma management in the workplace and clues to cause-and-effect relationships. Study 2 is a longitudinal, repeated cross-sectional survey that tests these relationships directly, particularly the explanatory role that coping and identity management strategies have in the process of stigma emergence. Additionally, it explores how these strategies change over time. Finally, study 3 is a laboratory experiment that examines in detail the causal links between different identity management strategies and individual and interpersonal outcomes, and the processes underlying these cause-and-effect relationships. In conclusion this thesis argues that being open about one’s stigma, intended as challenging stereotypes, assumptions, and discriminatory treatment, ultimately yields positive outcomes for individuals and organisations alike. However, openness is not just disclosure; it is an evolving, iterative learning process influenced by individual attributes and context characteristics, and constantly adapted on the basis of the feedback from the social environment

Event classification in MAGIC through Convolutional Neural Networks

The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescopes are able to detect gamma rays from the ground with energies beyond several tens of GeV emitted by the most energetic known objects, including Pulsar Wind Nebulae, Active Galactic Nuclei, and Gamma-Ray Bursts. Gamma rays and cosmic rays are detected by imaging the Cherenkov light produced by the charged superluminal leptons in the extended air shower originated when the primary particle interacts with the atmosphere. These Cherenkov flashes brighten the night sky for short times in the nanosecond scale. From the image topology and other observables, gamma rays can be separated from the unwanted cosmic rays, and thereafter incoming direction and energy of the primary gamma rays can be reconstructed. The standard algorithm in MAGIC data analysis for the gamma/hadron separation is the so-called Random Forest, that works on a parametrization of the stereo events based on the shower image parameters. Until a few years ago, these algorithms were limited by the computational resources but modern devices, such as GPUs, make it possible to work efficiently on the pixel maps information. Most neural network applications in the field perform the training on Monte Carlo simulated data for the gamma-ray sample. This choice is prone to systematics arising from discrepancies between observational data and simulations. Instead, in this thesis I trained a known neural network scheme with observation data from a giant flare of the bright TeV blazar Mrk421 observed by MAGIC in 2013. With this method for gamma/hadron separation, the preliminary results compete with the standard MAGIC analysis based on Random Forest classification, which also shows the potential of this approach for further improvement. In this thesis first an introduction to the High-Energy Astrophysics and the Astroparticle physics is given. The cosmic messengers are briefly reviewed, with a focus on the photons, then astronomical sources of γ rays are described, followed by a description of the detection techniques. In the second chapter the MAGIC analysis pipeline starting from the low level data acquisition to the high level data is described. The MAGIC Instrument Response Functions are detailed. Finally, the most important astronomical sources used in the standard MAGIC analysis are listed. The third chapter is devoted to Deep Neural Network techniques, starting from an historical Artificial Intelligence excursus followed by a Machine Learning description. The basic principles behind an Artificial Neural Network and the Convolutional Neural Network used for this work are explained. Last chapter describes my original work, showing in detail the data selection/manipulation for training the Inception Resnet V2 Convolutional Neural Network and the preliminary results obtained from four test sources

Dynamics of Dinitrosyl Iron Complex (DNIC) Formation with Low Molecular Weight Thiols.

Dinitrosyl iron complexes (DNICs) are ubiquitous in mammalian cells and tissues producing nitric oxide (NO) and have been argued to play key physiological and pathological roles. Nonetheless, the mechanism and dynamics of DNIC formation in aqueous media remain only partially understood. Here, we report a stopped-flow kinetics and density functional theory (DFT) investigation of the reaction of NO with ferrous ions and the low molecular weight thiols glutathione (GSH) and cysteine (CysSH) as well as the peptides WCGPC and WCGPY to produce DNICs in pH 7.4 aqueous media. With each thiol, a two-stage reaction pattern is observed. The first stage involves several rapidly established pre-equilibria leading to a ferrous intermediate concluded to have the composition FeII(NO)(RS)2(H2O)x (C). In the second stage, C undergoes rate-limiting, unimolecular autoreduction to give thiyl radical (RS•) plus the mononitrosyl Fe(I) complex FeI(NO)(RS)(H2O)x following the reactivity order of CysSH > WCGPC > WCGPY > GSH. Time course simulations using the experimentally determined kinetics parameters demonstrate that, at a NO flux characteristic of inflammation, DNICs will be rapidly formed from intracellular levels of ferrous iron and thiols. Furthermore, the proposed mechanism offers a novel pathway for S-nitroso thiol (RSNO) formation in a biological environment

Sustainable Business Models: Literature Review of Main Contributions and Themes

Literature on sustainable business models (SBM) has recently emerged and is rapidly expanding. This promising research field is aimed at intersecting traditional business model approaches with corporate sustainability. Most of the research to date has focused on existing case studies or examples of sustainability innovations in business models or on the use of frameworks and tools to categorise or design SBMs or suggest the stages of this innovative process towards sustainability. This article presents an integrative literature review aimed at describing the objective aspects of the SBM literature such as its temporal, industrial, geographical and methodological factors. As well as this descriptive analysis, the paper categorises the SBM literature in terms of its main purposes and themes. This categorisation is aimed at synthesising the main contributions of the SBM literature and to highlight gaps to suggest possible further developments. Despite presenting different perspectives on value (proposition, creation, delivery and capture), the current research on SBM has failed to take a holistic approach towards sustainable value measurement and representation in its models and frameworks

A Literature Review on Sustainable Business Model: first insights about the value measurement gap

Although business models have been extensively studied by researchers, latest trends have led organizations to rethink their way of doing business, focusing not only on profit, but also on social and environmental purposes. That’s why literature on sustainable business models (SBM) has been recently developed and is rapidly spreading. The purpose of this paper is to explore this body of literature, describing its temporal, industrial, geographical and methodological features, but also categorizing articles in terms of main purposes and specific themes addressed. To do so, we conducted an integrative literature review, which highlighted that SBM literature has so far focused on the descriptive analysis of case studies, on the process of innovation of the business model towards sustainability, or on the visual representation and design of the SBM, while a gap emerges in terms of quantitative analysis and performance measurement of SBM. As a result, a specific analysis on SBM articles dealing with the concept of value in its components of proposition, creation, delivery and capture was carried out: we found that authors mainly focused on extending the concept of value proposition and value creation and distribution, but only few of them addressed value capture and almost no one investigated how to measure it in an alternative way, compared to traditional business models. This paper ends by highlighting the research gap on sustainable business model value measurement and suggesting new ideas for future research

Language development and disorders: Possible genes and environment interactions

Language development requires both basic cognitive mechanisms for learning language and a rich social context from which learning takes off. Disruptions in learning mechanisms, processing abilities, and/or social interactions increase the risks associated with social exclusion or developmental delays. Given the complexity of language processes, a multilevel approach is proposed where both cognitive mechanisms, genetic and environmental factors need to be probed together with their possible interactions. Here we review and discuss such interplay between environment and genetic predispositions in understanding language disorders, with a particular focus on a possible endophenotype, the ability for statistical sequential learning

Melanoma and the Nervous System – Novel Pathways Mediated by Neurotrophins and Their Receptors

Le neurotrofine sono una famiglia di proteine sintetizzate e prodotte da molte cellule cutanee, mentre i loro recettori sono espressi nel melanoma. Le neurotrofine stimolano la proliferazione e la migrazione delle cellule di melanoma

CD271 downregulation promotes melanoma progression and invasion in 3-dimensional models and in zebrafish

CD271 is a neurotrophin receptor variably expressed in melanoma. While contradictory data are reported on its role as a marker of tumor initiating cells, little is known on its function in tumor progression. CD271 expression was higher in spheroids derived from freshly isolated cells of primary melanomas and in primary WM115 and WM793-B cell lines, while it decreased during progression to advanced stages in cells isolated from metastatic melanomas and in metastatic WM266-4 and 1205Lu cell lines. Moreover, CD271 was scarcely detected in the highly invasive spheroids (SKMEL28 and 1205Lu). CD271, originally expressed in the epidermis of skin reconstructs, disappeared when melanoma started to invade the dermis. SKMEL8 CD271(-) cells showed greater proliferation and invasiveness in vitro, and were associated with a higher number of metastases in zebrafish, as compared to CD271(+) cells. CD271 silencing in WM115 induced a more aggressive phenotype in vitro and in vivo. On the contrary, CD271 overexpression in SKMEL28 cells reduced invasion in vitro, and CD271 overexpressing 1205Lu cells was associated with a lower percentage of metastases in zebrafish. A reduced cell-cell adhesion was also observed in absence of CD271. Taken together, these results indicate that CD271 loss is critical for melanoma progression and metastasis