Development of strategies for vascular damage repair in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) is a progressive and rare disease with so far unclear pathogenesis, limited treatment options and poor prognosis. Unbalance of proliferation and migration in pulmonary arterial smooth muscle cells (PASMCs) is an important hallmark of PAH. In this research Sodium butyrate (BU) has been evaluated in vitro and in vivo models of PAH. This histone deacetylase inhibitor (HDACi) counteracted platelet-derived growth factor (PDGF)-induced ki67 expression in PASMCs, and arrested cell cycle mainly at G0/G1 phases. Furthermore, BU reduced the transcription of PDGFRbeta, and that of Ednra and Ednrb, two major receptors in PAH progression. Wound healing and pulmonary artery ring assays indicated that BU inhibited PDGF-induced PASMC migration. BU strongly inhibited PDGF-induced Akt phosphorylation, an effect reversed by the phosphatase inhibitor calyculinA. In vivo, BU showed efficacy in monocrotaline-induced PAH in rats. Indeed, the HDACi reduced both thickness of distal pulmonary arteries and right ventricular hypertrophy. Besides these studies, Serial Analysis of Gene Expression (SAGE) has be used to obtain complete transcriptional profiles of peripheral blood mononuclear cells (PBMCs) isolated from PAH and Healthy subjects. SAGE allows quantitative analysis of thousands transcripts, relying on the principle that a short oligonucleotide (tag) can uniquely identify mRNA transcripts. Tag frequency reflects transcript abundance. We enrolled patients naïve for a specific PAH therapy (4 IPAH non-responder, 3 IPAH responder, 6 HeritablePAH), and 8 healthy subjects. Comparative analysis revealed that significant differential expression was only restricted to a hundred of down- or up-regulated genes. Interestingly, these genes can be clustered into functional networks, sharing a number of crucial features in cellular homeostasis and signaling. SAGE can provide affordable analysis of genes amenable for molecular dissection of PAH using PBMCs as a sentinel, surrogate tissue. Altogether, these findings may disclose novel perspectives in the use of HDACi in PAH and potential biomarkers.

Sistemi endorfinergici e modulazione di segnali molecolari e profili trascrizionali coinvolti in processi di protezione e autoriparazione del miocardio danneggiato

Con il termine IPC (precondizionamento ischemico) si indica un fenomeno per il quale, esponendo il cuore a brevi cicli di ischemie subletali prima di un danno ischemico prolungato, si conferisce una profonda resistenza all’infarto, una delle principali cause di invalidità e mortalità a livello mondiale. Studi recenti hanno suggerito che l’IPC sia in grado di migliorare la sopravvivenza, la mobilizzazione e l’integrazione di cellule staminali in aree ischemiche e che possa fornire una nuova strategia per potenziare l’efficacia della terapia cellulare cardiaca, un’area della ricerca in continuo sviluppo. L’IPC è difficilmente trasferibile nella pratica clinica ma, da anni, è ben documentato che gli oppioidi e i loro recettori hanno un ruolo cardioprotettivo e che attivano le vie di segnale coinvolte nell’IPC: sono quindi candidati ideali per una possibile terapia farmacologica alternativa all’IPC. Il trattamento di cardiomiociti con gli agonisti dei recettori oppioidi Dinorfina B, DADLE e Met-Encefalina potrebbe proteggere, quindi, le cellule dall’apoptosi causata da un ambiente ischemico ma potrebbe anche indurle a produrre fattori che richiamino elementi staminali. Per testare quest’ipotesi è stato messo a punto un modello di “microambiente ischemico” in vitro sui cardiomioblasti di ratto H9c2 ed è stato dimostrato che precondizionando le cellule in modo “continuativo” (ventiquattro ore di precondizionamento con oppioidi e successivamente ventiquattro ore di induzione del danno, continuando a somministrare i peptidi oppioidi) con Dinorfina B e DADLE si verifica una protezione diretta dall’apoptosi. Successivamente, saggi di migrazione e adesione hanno mostrato che DADLE agisce sulle H9c2 “ischemiche” spronandole a creare un microambiente capace di attirare cellule staminali mesenchimali umane (FMhMSC) e di potenziare le capacità adesive delle FMhMSC. I dati ottenuti suggeriscono, inoltre, che la capacità del microambiente ischemico trattato con DADLE di attirare le cellule staminali possa essere imputabile alla maggiore espressione di chemochine da parte delle H9c2.

Technologies for Ambient intelligence: from Smart Objects to Sensor Networks

n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.

Media activism on and off line by Italian adolescents and young adults

From several researchers it appears that Italian adolescents and young people are grown up with commercial television which is accused to contain too much violence, sex, reality shows, advertising, cartoons which are watched from 1 to 4 hours daily. Adolescents are also great users of mobile phones and spend a lot of time to use it. Their academic results are below the average of Ocse States. However the widespread use of communication technology and social networks display also another side of adolescents who engage in media activism and political movement such as Ammazzateci tutti!, Indymedia, Movimento 5 Stelle, Movimento No Tav. In which way does the world economic crisis -with the specific problems of Italy as the cutting founds for school, academic research and welfare, the corruption of political class, mafia and camorra organisation induce a reaction in our adolescents and young people? Several researches inform us about their use of internet in terms of spending time but, more important, how internet, and the web 2.0, could be an instrument for their reaction? What do they do online? How they do it? Which is the meaning of their presence online? And, has their online activity a continuity offline? The research aims are: 1. Trough a participant observation of Social Network profiles opened by 10 young active citizens, I would seek to understand which kind of social or political activities they engage in online as individuals and which is the meaning of their presence online. 2. To observe and understand if adolescents and young people have a continuity of their socio-political engagement online in offline activities and which kind of experiences it is. 3. Try to comprehend which was (or which were) the significant, learning experiences that convinced them about the potential of the web as tool for their activism.

The Making of a Shiite Bourgeoisie in Lebanon Political Mobilisation, Economic Resources and Formation of a Social Group

The thesis analyses the making of the Shiite middle- and upper/entrepreneurial-class in Lebanon from the 1960s till the present day. The trajectory explores the historical, political and social (internal and external) factors that brought a sub-proletariat to mobilise and become an entrepreneurial bourgeoisie in the span of less than three generations. This work proposes the main theoretical hypothesis to unpack and reveal the trajectory of a very recent social class that through education, diaspora, political and social mobilisation evolved in a few years into a very peculiar bourgeoisie: whereas Christian-Maronite middle class practically produced political formations and benefited from them and from Maronite’s state supremacy (National Pact, 1943) reinforcing the community’s status quo, Shiites built their own bourgeoisie from within, and mobilised their “cadres” (Boltanski) not just to benefit from their renovated presence at the state level, but to oppose to it. The general Social Movement Theory (SMT), as well as a vast amount of the literature on (middle) class formation are therefore largely contradicted, opening up new territories for discussion on how to build a bourgeoisie without the state’s support (Social Mobilisation Theory, Resource Mobilisation Theory) and if, eventually, the middle class always produces democratic movements (the emergence of a social group out of backwardness and isolation into near dominance of a political order). The middle/upper class described here is at once an economic class related to the control of multiple forms of capital, and produced by local, national, and transnational networks related to flows of services, money, and education, and a culturally constructed social location and identity structured by economic as well as other forms of capital in relation to other groups in Lebanon.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

Innovation Diffusion and Biostimulant knowledge in Moroccan agriculture

Our study focused on Morocco investigating the dissemination of PBs amongst farmers belonging to the first pillar of the GMP, located in the Fès-Meknès region. As well as to assess how innovation adoption is influenced by the network of relationships that various farmers are involved in. We adopted an “ego network” approach to identify the primary stakeholders responsible for the diffusion of PBs. We collected data through “face-to-face” interviews with 80 farmers in April and May 2021. The data were processed with the aim of: 1) analysing the total number of main and specific topics discussed between egos and egos’ alters regarding the variation of some egos attributes; 2) analysing egos’ network characteristics using E-Net software, and 3) identifying the significant variables that influence farmers to access knowledge, use and reuse of PBs a Binary Logistic Regression (LR) was applied. The first result disclosed that the main PBs topics discussed were technical positioning, the need to use PBs, knowledge of PBs, and organic PBs. We noted that farmers have specific features: they have a high school diploma and a bachelor's degree; they are specialised in fruits and cereals farming, and they are managers and members of a professional organisation. The second result showed results of SNA: 1) PBs seem to become generally a common argument for farmers who have already exchanged fertiliser information with their alters; 2) we disclosed a moderate heterogeneity in the networks, farmers have access to information mainly from acquaintances and professionals, and 3) we revealed that networks have a relatively low density and alters are not tightly connected to each other. Farmers have a brokerage position in the networks controlling the flow of information about the PBs. LR revealed that both the farmers’ attributes and the networks’ characteristics influence growers to know, use and reuse PBs.

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.

NB-IoT via non terrestrial networks

Massive Internet of Things is expected to play a crucial role in Beyond 5G (B5G) wireless communication systems, offering seamless connectivity among heterogeneous devices without human intervention. However, the exponential proliferation of smart devices and IoT networks, relying solely on terrestrial networks, may not fully meet the demanding IoT requirements in terms of bandwidth and connectivity, especially in areas where terrestrial infrastructures are not economically viable. To unleash the full potential of 5G and B5G networks and enable seamless connectivity everywhere, the 3GPP envisions the integration of Non-Terrestrial Networks (NTNs) into the terrestrial ones starting from Release 17. However, this integration process requires modifications to the 5G standard to ensure reliable communications despite typical satellite channel impairments. In this framework, this thesis aims at proposing techniques at the Physical and Medium Access Control layers that require minimal adaptations in the current NB-IoT standard via NTN. Thus, firstly the satellite impairments are evaluated and, then, a detailed link budget analysis is provided. Following, analyses at the link and the system levels are conducted. In the former case, a novel algorithm leveraging time-frequency analysis is proposed to detect orthogonal preambles and estimate the signals’ arrival time. Besides, the effects of collisions on the detection probability and Bit Error Rate are investigated and Non-Orthogonal Multiple Access approaches are proposed in the random access and data phases. The system analysis evaluates the performance of random access in case of congestion. Various access parameters are tested in different satellite scenarios, and the performance is measured in terms of access probability and time required to complete the procedure. Finally, a heuristic algorithm is proposed to jointly design the access and data phases, determining the number of satellite passages, the Random Access Periodicity, and the number of uplink repetitions that maximize the system's spectral efficiency.

Internet of healthcare (law): privacy and data protection aspects in an internet of everything

The purpose of this research study is to discuss privacy and data protection-related regulatory and compliance challenges posed by digital transformation in healthcare in the wake of the COVID-19 pandemic. The public health crisis accelerated the development of patient-centred remote/hybrid healthcare delivery models that make increased use of telehealth services and related digital solutions. The large-scale uptake of IoT-enabled medical devices and wellness applications, and the offering of healthcare services via healthcare platforms (online doctor marketplaces) have catalysed these developments. However, the use of new enabling technologies (IoT, AI) and the platformisation of healthcare pose complex challenges to the protection of patient’s privacy and personal data. This happens at a time when the EU is drawing up a new regulatory landscape for the use of data and digital technologies. Against this background, the study presents an interdisciplinary (normative and technology-oriented) critical assessment on how the new regulatory framework may affect privacy and data protection requirements regarding the deployment and use of Internet of Health Things (hardware) devices and interconnected software (AI systems). The study also assesses key privacy and data protection challenges that affect healthcare platforms (online doctor marketplaces) in their offering of video API-enabled teleconsultation services and their (anticipated) integration into the European Health Data Space. The overall conclusion of the study is that regulatory deficiencies may create integrity risks for the protection of privacy and personal data in telehealth due to uncertainties about the proper interplay, legal effects and effectiveness of (existing and proposed) EU legislation. The proliferation of normative measures may increase compliance costs, hinder innovation and ultimately, deprive European patients from state-of-the-art digital health technologies, which is paradoxically, the opposite of what the EU plans to achieve.