Valutazione dell'impatto della farmacogenetica in ambito di Sanità Pubblica. Analisi del polimorfismo genetico dell'enzima CYP2D6 metabolizzante xenobiotici.

Pharmacogenetic testing provides an outstanding opportunity to improve prescribing safety and efficacy. In Public health policy pharmacogenetics is relevant for personalized therapy and to maximize therapeutic benefit minimizing adverse events. CYP2D6 is known to be a key enzyme responsible for the biotransformation of about 25-30% of extensively used drugs and genetic variations in genes coding for drug-metabolizing enzymes might lead to adverse drug reactions, toxicity or therapeutic failure of pharmacotherapy. Significant interethnic differences in CYP2D6 allele distribution are well established, but immigration is reshaping the genetic background due to interethnic admixture which introduces variations in individual ancestry resulting in distinct level of population structure. The present thesis deals with the genetic determination of the CYP2D6 alleles actually present in the Emilia-Romagna resident population providing insights into the admixture process. A random sample of 122 natives and 175 immigrants from Africa, Asia and South America where characterized considering the present scenario of migration and back migration events. The results are consistent with the known interethnic genetic variation, but introduction of ethnic specific variants by immigrants predicts a heterogeneous admixed population scenario requiring, for drugs prescription and pharmacogenetics studies, an interdisciplinary approach applied in a properly biogeographical and anthropological frame. To translate pharmacogenetics knowledge into clinical practice requires appropriated public health policies, possibly guiding clinicians to evaluate prospectively which patients have the greatest probability of expressing a variant genotype.

Ethical Perspectives on Big Data in Agri-food: Ownership and Governance for Safety

Big data are reshaping the way we interact with technology, thus fostering new applications to increase the safety-assessment of foods. An extraordinary amount of information is analysed using machine learning approaches aimed at detecting the existence or predicting the likelihood of future risks. Food business operators have to share the results of these analyses when applying to place on the market regulated products, whereas agri-food safety agencies (including the European Food Safety Authority) are exploring new avenues to increase the accuracy of their evaluations by processing Big data. Such an informational endowment brings with it opportunities and risks correlated to the extraction of meaningful inferences from data. However, conflicting interests and tensions among the involved entities - the industry, food safety agencies, and consumers - hinder the finding of shared methods to steer the processing of Big data in a sound, transparent and trustworthy way. A recent reform in the EU sectoral legislation, the lack of trust and the presence of a considerable number of stakeholders highlight the need of ethical contributions aimed at steering the development and the deployment of Big data applications. Moreover, Artificial Intelligence guidelines and charters published by European Union institutions and Member States have to be discussed in light of applied contexts, including the one at stake. This thesis aims to contribute to these goals by discussing what principles should be put forward when processing Big data in the context of agri-food safety-risk assessment. The research focuses on two interviewed topics - data ownership and data governance - by evaluating how the regulatory framework addresses the challenges raised by Big data analysis in these domains. The outcome of the project is a tentative Roadmap aimed to identify the principles to be observed when processing Big data in this domain and their possible implementations.

Robotic Sensing and Manipulation of Deformable Linear Objects with Learning-based methods

Nowadays robotic applications are widespread and most of the manipulation tasks are efficiently solved. However, Deformable-Objects (DOs) still represent a huge limitation for robots. The main difficulty in DOs manipulation is dealing with the shape and dynamics uncertainties, which prevents the use of model-based approaches (since they are excessively computationally complex) and makes sensory data difficult to interpret. This thesis reports the research activities aimed to address some applications in robotic manipulation and sensing of Deformable-Linear-Objects (DLOs), with particular focus to electric wires. In all the works, a significant effort was made in the study of an effective strategy for analyzing sensory signals with various machine learning algorithms. In the former part of the document, the main focus concerns the wire terminals, i.e. detection, grasping, and insertion. First, a pipeline that integrates vision and tactile sensing is developed, then further improvements are proposed for each module. A novel procedure is proposed to gather and label massive amounts of training images for object detection with minimal human intervention. Together with this strategy, we extend a generic object detector based on Convolutional-Neural-Networks for orientation prediction. The insertion task is also extended by developing a closed-loop control capable to guide the insertion of a longer and curved segment of wire through a hole, where the contact forces are estimated by means of a Recurrent-Neural-Network. In the latter part of the thesis, the interest shifts to the DLO shape. Robotic reshaping of a DLO is addressed by means of a sequence of pick-and-place primitives, while a decision making process driven by visual data learns the optimal grasping locations exploiting Deep Q-learning and finds the best releasing point. The success of the solution leverages on a reliable interpretation of the DLO shape. For this reason, further developments are made on the visual segmentation.

Microenvironment and prognostic factors in bone tumors: IDH mutations in chondrosarcoma

Microenvironment in bone tumors is a dynamic entity composed of cells from different origins (immune cells, stromal cells, mesenchymal stem cells, endothelial cells, pericytes) and vascular structures surrounded by a matrix of different nature (bone, cartilage, myxoid). Interactions between cancer cells and tumor microenvironment (TME) are complex and can change as tumor progress, but are also crucial in determining response to cancer therapies. Chondrosarcoma is the second most frequent bone cancer in adult age, but its treatment still represents a challenge, for the intrinsic resistance to conventional chemotherapy and radiation therapy. This resistance is mainly due to pathological features, as dense matrix, scarce mitoses and poor vascularization, sustained by biological mechanisms only partially delucidated. Somatic mutation in the Krebs cycle enzyme isocytrate dehydrogenase (IDH) have been described in gliomas, acute myeloid leukemia, cholangiocarcinoma, melanoma, colorectal, prostate cancer, thyroid carcinoma and other cancers. In mesenchymal tumors IDH mutations are present in about 50% of central chondrosarcoma. IDH mutations are an early event in chondrosarcoma-genesis, and contribute to the acquisition of malignancy through the block of cellular differentiation, hypoxia induction through HIF stabilization, DNA methylation and alteration of cellular red-ox balance. While in gliomas IDH mutations confers a good prognosis, in chondrosarcoma IDH prognostic role is controversial in different reported series. First aim of this project is to define the prevalence and the prognostic role of IDH mutation in high grade central conventional chondrosarcoma patients treated at Istituto Ortopedico Rizzoli. Second aim is the critical revision of scientific literature to understand better how a genomic event in cancer cell can trigger alteration in the TME, through immune infiltrate reshaping, angiogenesis induction, metabolic and methylation rewiring. Third aim is to screen other sarcoma histotypes for the presence of IDH mutation.

The Legacy of Frankenstein’s Creature: Monstrosity and Female Grotesque in Mary Shelley, Angela Carter and Jeanette Winterson

This English Literature thesis (European PhD EDGES – Women’s and Gender Studies – 34th cycle) is an investigation into the representation of the monstrous body according to the British writers Mary Shelley, Angela Carter and Jeanette Winterson. The main objective is to observe how the representation of the categories of monstrous, abject and grotesque in Western cultural imagination have been influenced across time and literary genres. In the novels of Shelley, Carter and Winterson, the monstrous subject is configured as an alternative to the anthropocentric ideal embodied by the normative subject, of which Victor Frankenstein is the paradigmatic exponent. Plus, there are places considered anti-topoi within which the monster acquires a situatedness and claims a voice, generating an opposed counter-narrative to the imaginary conveyed by the normative subject. Monstrosity outlined by Shelley in the novels Frankenstein and The Last Man constitutes the starting point of my research, aiming to observe how the discourse of the normative body vs. the anti-normative body intersects with the discourse of the spaces of the centre vs. the spaces of the margin. In Carter's novels The Passion of New Eve and Nights at the Circus, the monstrous female constitutes the embodiment of wills, desires and claims challenging the heteronormative system. The space of otherness in which Carter's monster-woman is confined becomes a possibility of reshaping identity for the Subject, deconstructing the logic of power that moulded her within society. Finally, Winterson creates two monstrous women in Sexing the Cherry and The Passion who move through urban spaces, going from the centre to the margins and testifying to the arbitrariness of the system and its weaknesses. Similarly, in Frankissstein, Winterson recovers Shelley's original novel and transforms it into a parodic and intertextual speculation on the fluidity of identity and the limits of transhumanism.

Rising China and Internet governance: Multistakeholderism, fragmentation and the Liberal Order in the age of digital sovereignty

In its open and private-based dimension, the Internet is the epitome of the Liberal International Order in its global spatial dimension. Therefore, normative questions arise from the emergence of powerful non-liberal actors such as China in Internet governance. In particular, China has supported a UN-based multilateral Internet governance model based on state sovereignty aimed at replacing the existing ICANN-based multistakeholder model. While persistent, this debate has become less dualistic through time. However, fear of Internet fragmentation has increased as the US-China technological competition grew harsher. This thesis inquires “(To what extent) are Chinese stakeholders reshaping the rules of Global Internet Governance?”. This is further unpacked in three smaller questions: (i) (To what extent) are Chinese stakeholders contributing to increased state influence in multistakeholder fora?; (ii) (how) is China contributing to Internet fragmentation?; and (iii) what are the main drivers of Chinese stakeholders’ stances? To answer these questions, Chinese stakeholders’ actions are observed in the making and management of critical Internet resources at the IETF and ICANN respectively, and in mobile connectivity standard-making at 3GPP. Through the lens of norm entrepreneurship in regime complexes, this thesis interprets changes and persistence in the Internet governance normative order and Chinese attitudes towards it. Three research methods are employed: network analysis, semi-structured expert interviews, and thematic document analysis. While China has enhanced state intervention in several technological fields, fostering debates on digital sovereignty, this research finds that the Chinese government does not exert full control on its domestic private actors and concludes that Chinese stakeholders have increasingly adapted to multistakeholder Internet governance as they grew influential within it. To enhance control over Internet-based activities, the Chinese government resorted to regulatory and technical control domestically rather than establishing a splinternet. This is due to Chinese stakeholders’ interest in retaining the network benefits of global interconnectivity.

QoS-aware architectures, technologies, and middleware for the cloud continuum

The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions.

Movement analysis on the field in young football players: biomechanical patterns of performance and injury prevention

The integration of quantitative data from movement analysis technologies is reshaping the analysis of athletes’ performances and injury mitigation, e.g., anterior cruciate ligament (ACL) rupture. Most of the movement assessments are performed in laboratory environments. Recent progress provides the chance to shift the paradigm to a more ecological approach with sport-specific elements and a closer examination of “real” movement patterns associated with performance and (ACL) injury risk. The present PhD thesis aimed at investigating the on-field motion patterns related to performance and injury prevention in young football players. The objectives of the thesis were: (I) in-lab measures of high-dynamics movements were used to validate wearable inertial sensors technology; (II) in-laboratory and on-field agility movement tasks were compared to inspect the effect of football-specific environment; (III) on-field analysis was conducted to challenge wearable sensors technology in the assessment of dangerous movement patterns towards the ACL rupture; (IV) an overview of technologies that could shape present and future assessment of ACL injury risk in daily practice was presented. The validity of wearables in the assessment of high-dynamics movements was confirmed. Relevant differences emerged between the movements performed in a laboratory setting and on the football pitch, supporting the inclusion of an ecological dynamics approach in preventive protocols. The on-field analysis of football-specific movement tasks demonstrated good reliability of wearable sensors and the presence of residual dangerous patterns in the injured players. A tool to inspect at-risk movement patterns on the field through objective measurements was presented. It discussed how potential alternatives to wearable inertial sensors embrace artificial intelligence and closer collaboration between clinical and technical expertise. The present thesis was meant to contribute to setting the basis for data-driven prevention protocols. A deeper comprehension of injury-related principles and counteractions will contribute to preserving athletes’ careers and health over time.

Investigation on the role of polymeric ligands in heterogeneous nanocatalysis towards the development of hybrid metal-polymer catalysts

The relationship between catalytic properties and the nature of the active phase is well-established, with increased presence typically leading to enhanced catalysis. However, the costs associated with acquiring and processing these metals can become economically and environmentally unsustainable for global industries. Thus, there is potential for a paradigm shift towards utilizing polymeric ligands or other polymeric systems to modulate and enhance catalytic performance. This alternative approach has the potential to reduce the requisite amount of active phase while preserving effective catalytic activity. Such a strategy could yield substantial benefits from both economic and environmental perspectives. The primary objective of this research is to examine the influence of polymeric hydro-soluble ligands on the final properties, such as size and dispersion of the active phase, as well as the catalytic activity, encompassing conversion, selectivity towards desired products, and stability, of colloidal gold nanoparticles supported on active carbon. The goal is to elucidate the impact of polymers systematically, offering a toolbox for fine-tuning catalytic performances from the initial stages of catalyst design. Moreover, investigating the potential to augment conversion and selectivity in specific reactions through tailored polymeric ligands holds promise for reshaping catalyst preparation methodologies, thereby fostering the development of more economically sustainable materials.