Cheering the soul: Ibn Qāḍī Baʿlabakk’s Mufarriḥ an-Nafs. Arabic edition, english translation, study and glossaries

The Mufarriḥ an-nafs (Soul-Cheerer), attributed to Badr ad-Dīn Muẓaffar Ibn Qāḍī Baʿlabakk, who served under the Ayyubids as the Chief Medical Officer of Damascus in the mid-13th century, was written as a comprehensive guide for physicians outlining different approaches to cheering the soul. The tractate is divided into ten chapters, which explore the nature of the soul, its distinction to the body as well as their connection through sensorial perception. Ibn Qāḍī Baʿlabakk distinguishes the bodily senses – hearing, vision, smell, taste, touch – and the inner senses, which he sees as stimulated through activities such as hunting and engagement in poetry and the sciences. The seventh chapter of the Mufarriḥ an-nafs includes an extended encyclopedia on materia medica as well as dispensatory of simple and compound drugs, which is devoted to treating the soul and remains unparalleled in the history of Islamicate medicine. My doctoral dissertation offers a complete recension and translation of the Mufarriḥ an-nafs based on a stemma codicum drawn from the seventeen extant text witnesses. The dissertation contextualizes the work, its author as well as sources, and features a text commentary that seeks to enable the reader to easily place and understand the Mufarriḥ an-nafs within the tradition of Galenic medicine. The glossaries on materia medica found at the end of the dissertation are aimed at facilitating access to the pharmacological dispensatory included in the seventh chapter

Assessment of bone mineral density at the bone-implant interface and joint temperature in patients undergoing total knee arthroplasty

The field of knee prosthetic surgery has undergone significant advancements to enhance patient outcomes and implant longevity. While innovations in design, alignment, soft tissue balancing, and fixation techniques have progressed, material-related challenges remain crucial. Traditional cobalt-chrome (CoCr) prostheses exhibit distinct disparities compared to human bone in stiffness and thermal conductivity. Excessive stiffness leads to “stress shielding,” contributing to periprosthetic bone resorption, implant loosening, and fractures. High thermal conductivity, in contrast, often causes patient discomfort, such as altered heat sensitivity in the operated knee. These challenges underscore the need for novel materials, particularly as osteoarthritis arises earlier and joint replacement increasingly targets younger, active patients. This PhD thesis investigates the influence of joint prostheses on periprosthetic bone remodeling and joint temperature trends, with a focus on Total Knee Arthroplasty (TKA). The research objectives included: (I) a literature review on femoral component migration and clinical outcomes; (II) a systematic review on periprosthetic Bone Mineral Density (BMD) variations, influenced by fixation techniques and implant design; (III) a clinical study utilizing Dual X-ray Absorptiometry (DXA) to assess BMD changes post-TKA; and (IV) an evaluation of postoperative knee surface temperature. The findings demonstrated that femoral component migration exceeding 0.10 mm annually correlates with implant failure, often linked to poor primary fixation and low BMD. Systematic analysis revealed progressive BMD reduction post-TKA, influenced by fixation and implant design. Clinical DXA evaluations, a first at Rizzoli Orthopedic Institute, showed promising preliminary results regarding CoCr prostheses’ impact on BMD. Finally, increased postoperative knee temperatures aligned with patients' subjective discomfort and correlated with clinical outcomes. This thesis provides a foundation for developing biocompatible materials to enhance prosthetic durability, reduce bone resorption, and improve patient satisfaction

AF4 as a passepartout technique for the characterization of nanosystems of medical interest

Nanomedicines (NMs) are therapeutic or diagnostic medicines with dimensions typically between 1 and 1000 nm. NMs have drawn attention due to their ability to improve therapeutic efficacy and reduce toxicity compared to traditional drugs. Despite progress, many NMs struggle to transition from development to clinical use due to challenges like carrier toxicity, instability, and complex quality control (QC). The diverse nature of NMs makes difficult to establish universal analytical methods. Asymmetrical Flow Field-Flow Fractionation (AF4) is a promising technique for separating and characterizing nanoparticles (NPs), polymers, and macromolecules in a wide array of analytical conditions. This research aims to explore the potential of AF4 as a passepartout technique in characterizing NMs during the various stages of their development. Chapter 1 provides an overview of the topic. Chapter 2 focuses on Polydopamine (PDA) nanosystems, widely used in fields like drug delivery due to their biocompatibility and degradability although its structural diversity remains poorly understood. A miniaturized form of AF4, combined with multiple detectors, identified two distinct species formed during PDA synthesis. This breakthrough highlighted the ability of the technique to select optimal PDA nanoforms for clinical use. Chapter 3 discusses antimicrobial NPs. Nanosilver-based antimicrobials, combined with PDA, show potential in combating bacterial resistance. AF4, in conjunction with light scattering and spectrophotometric detection, streamlined the synthesis, purification, and characterization of these NPs, therefore acting as an eco-friendly multi-purpose tool. Chapter 4 examines the behavior of magnetic NPs in biological environments, focusing on stability and protein binding. AF4 allowed to study real-time interactions between MNPs and human serum albumin, addressing key safety concerns. Chapter 5 finally focuses on peptide-based drugs and their aggregation states. AF4 was crucial in assessing stability of liraglutide to aggregation, providing accurate insights into potential aggregation phenomena, which is a vital factor for regulatory approval of its various formulations

Identification of outcome-oriented cut-offs for copy number alterations in multiple myeloma: predictive biomarkers with improved prognostic accuracy

Aim of the present study was to develop a statistical approach to define the best cut-off Copy number alterations (CNAs) calling from genomic data provided by high throughput experiments, able to predict a specific clinical end-point (early relapse, 18 months) in the context of Multiple Myeloma (MM). 743 newly diagnosed MM patients with SNPs array-derived genomic and clinical data were included in the study. CNAs were called both by a conventional (classic, CL) and an outcome-oriented (OO) method, and Progression Free Survival (PFS) hazard ratios of CNAs called by the two approaches were compared. The OO approach successfully identified patients at higher risk of relapse and the univariate survival analysis showed stronger prognostic effects for OO-defined high-risk alterations, as compared to that defined by CL approach, statistically significant for 12 CNAs. Overall, 155/743 patients relapsed within 18 months from the therapy start. A small number of OO-defined CNAs were significantly recurrent in early-relapsed patients (ER-CNAs) - amp1q, amp2p, del2p, del12p, del17p, del19p -. Two groups of patients were identified either carrying or not ≥1 ER-CNAs (249 vs. 494, respectively), the first one with significantly shorter PFS and overall survivals (OS) (PFS HR 2.15, p<0001; OS HR 2.37, p<0.0001). The risk of relapse defined by the presence of ≥1 ER-CNAs was independent from those conferred both by R-IIS 3 (HR=1.51; p=0.01) and by low quality (< stable disease) clinical response (HR=2.59 p=0.004). Notably, the type of induction therapy was not descriptive, suggesting that ER is strongly related to patients’ baseline genomic architecture. In conclusion, the OO- approach employed allowed to define CNAs-specific dynamic clonality cut-offs, improving the CNAs calls’ accuracy to identify MM patients with the highest probability to ER. As being outcome-dependent, the OO-approach is dynamic and might be adjusted according to the selected outcome variable of interest

Analytical methods for modeling elastic metasurfaces

This dissertation aims at developing advanced analytical tools able to model surface waves propagating in elastic metasurfaces. In particular, four different objectives are defined and pursued throughout this work to enrich the description of the metasurface dynamics. First, a theoretical framework is developed to describe the dispersion properties of a seismic metasurface composed of discrete resonators placed on a porous medium considering part of it fully saturated. Such a model combines classical elasticity theory, Biot’s poroelasticity and an effective medium approach to describe the metasurface dynamics and its coupling with the poroelastic substrate. Second, an exact formulation based on the multiple scattering theory is developed to extend the two-dimensional classical Lamb’s problem to the case of an elastic half-space coupled to an arbitrary number of discrete surface resonators. To this purpose, the incident wavefield generated by a harmonic source and the scattered field generated by each resonator are calculated. The substrate wavefield is then obtained as solutions of the coupled problem due to the interference of the incident field and the multiple scattered fields of the oscillators. Third, the above discussed formulation is extended to three-dimensional contexts. The purpose here is to investigate the dynamic behavior and the topological properties of quasiperiodic elastic metasurfaces. Finally, the multiple scattering formulation is extended to model flexural metasurfaces, i.e., an array of thin plates. To this end, the resonant plates are modeled by means of their equivalent impedance, derived by exploiting the Kirchhoff plate theory. The proposed formulation permits the treatment of a general flexural metasurface, with no limitation on the number of plates and the configuration taken into account. Overall, the proposed analytical tools could pave the way for a better understanding of metasurface dynamics and their implementation in engineered devices

Understanding the causes of junctional failure in lumbar spine surgery through retrospective clinical analyses and ex-vivo tests

Spine diseases and failure have a significant effect on the patient’s quality of life. The aim of this PhD project was to improve the understanding the mechanisms leading to the spine instability and junctional pathology in the lumbar spine after posterior fixation. A combination of ex-vivo experiments and retrospective clinical analyses were performed. In the first part, cadaver spine segments were sequentially tested in the intact condition, after two-level hemilaminectomy, after a full laminectomy and after posterior fixation. Hemilaminectomy did not significantly affect the biomechanics of the lumbar spine. Conversely, after laminectomy, the range of motion significantly increased in flexion. Lateral bending was the most critical configuration for the strain in the intervertebral discs. Posterior fixation significantly reduced the range of motion and increased the strain in the disc adjacent the fixation both in flexion and in lateral bending. Two retrospective studies focused on patients with posterior fixation on the lumbar spine who required a revision surgery due to a failure in the caudal region. The junctional pathology onset was assessed on the pre-operative and post-operative spinopelvic parameters both in the sagittal and coronal planes, on the correction performed, on the patients’ clinical data, and addressing the different mechanisms of failure. In the sagittal plane (1690 patients included), the likelihood of mechanical failure was higher in patients older than 40 years with a thoraco-lumbar fixation, where some spinopelvic parameters were not properly restored. In the coronal plane (105 scoliotic patients included), the main parameters and their post-operative variations leading to failure were identified. In conclusion, the findings of these ex-vivo and clinical analyses could support the surgeons in being aware of possible outcomes when a treatment is needed, and when possible, to personalize spine surgeries, aiming to the long term to decrease the mechanical failure and revision surgeries

Self-diagnostic and smart polymers based on fluorescent probes

This thesis explores luminescent molecules, including molecular rotors and aggregachromic dyes, integrated into polymer matrices to create self-diagnostic and smart polymers. Research spans mechanoluminochromism, temperature-dependent behavior, and sensitivity to free volume and chain mobility changes, providing insights into their dynamic interaction under diverse environmental conditions. Using molecular rotors, the link between dye emission properties and matrix characteristics was deeply studied, challenging conventional assumptions. It is concluded that fluorescence lifetime is a more robust tool for discerning dye property changes than fluorescence intensity. An innovative approach measures chain mobility using a temperature-independent AIE probe, visualizing it with high resolution. Then, a phosphorescent probe explores free volume changes during stress-strain tests and aging, facilitating real-time monitoring. Incorporating aggregachromic dyes aims to produce mechanoluminochromic materials sensitive to intermolecular distance and chromophore orientation changes. Bonding dyes to polymer chains versus blending is investigated. Overall, this work provides insights into luminescent dye utilization within polymer matrices, offering versatility and sensitivity for applications like damage detection, load-bearing devices, and mechanochromic textiles, paving the way for future developments in polymer-based luminescent material

Reinforcement learning for dynamic resource allocation in distributed systems

Resource Allocation (RA) problems are ubiquitous across diverse domains, spanning from health services provisioning, supply chain management, personnel scheduling as well as task scheduling, cloud resources orchestration, and network capacity allocation. When the resource request changes over time, we refer to the field of Dynamic Resource Allocation (DRA) problems. DRA problems find applicability in domains such as cloud computing, network management, energy or water supply, and public transportation systems as they allow adjustment of the number of resources assigned for each component or user. However, conventional allocation strategies employed in DRA yield suboptimal policies, primarily due to their reactive nature. They tend to overlook the long-term implications of allocations over future time windows. This thesis proposes an innovative approach to tackle DRA problems by leveraging reinforcement learning (RL). Through trial and error, RL allows the learning of policies that proactively consider the effects of allocations over time and respond effectively to unexpected changes in demand. The effectiveness and efficiency of this proposed approach are supported by empirical evaluations on challenging DRA problems. Initially, it addresses task scheduling in heterogeneous worker-based distributed queues, integrating an adaptive RL method with the popular Celery task queuing system. Subsequently, the Thesis presents a deep reinforcement learning (DRL) based resource orchestrator tailored for managing virtual resources in Open Radio Access Network (O-RAN) infrastructures. Finally, it implements a DRL solution for efficient bike redistribution in Bike Sharing Systems (BSS), simultaneously optimizing operational costs for system operators. The results, derived from both synthetic and real-world data, underscore the superiority of RL approaches over greedy allocation strategies, demonstrating enhanced optimization of the specified objectives. Moreover, the thesis provides technical insights on how to efficiently design and implement these solutions in real-world and well-engineered prototypes

Literary tourism in rural areas and small towns: development and governance of destinations associated with children's literature

European rural areas face several significant challenges. Cultural heritage, particularly literary heritage, is often overlooked in rural development strategies. However, its protection and valorisation can play a pivotal role in rural regeneration. This research first undertakes a comprehensive exploration of how rurality is defined, analysing key European strategies and policies related to rural development. Secondly, it investigates how literary heritage is preserved and promoted by international organizations (Council of Europe, UNESCO). Furthermore, it reviews the current state of research on literary tourism, with special emphasis on literary tourism associated with children's literature. Thirdly, the research introduces an analytical framework to examine the development and governance of literary destinations in rural areas. Through four case studies, this thesis explores how literary heritage is managed and valorised at the local level, demonstrating that the effective utilisation of literary resources can contribute to the economic, social, and cultural development of certain rural areas and small towns. The thesis focuses specifically on children's literature, analysing the following case studies: (1) Sarmede (Italy), associated with the writer, painter, and illustrator Štěpán Zavřel, (2) Collodi (Pescia, Italy), linked to Carlo Lorenzini, better known by his pen name Carlo Collodi, author of Pinocchio, (3) Near Sawrey and the Lake District (United Kingdom), connected with Beatrix Potter, whose The Tale of Peter Rabbit is among her most famous works, and (4) Hartfield (United Kingdom), associated with Alan Alexander Milne, creator of Winnie-the-Pooh. Finally, through a comparative analysis of these case studies, this thesis identifies common challenges and opportunities, highlights best practices, and uncovers unique approaches across the different literary destinations. In conclusion, this thesis aims to provide practical recommendations for local stakeholders, offering a roadmap for leveraging literary heritage as a catalyst for rural regeneration.Le aree rurali europee si trovano ad affrontare numerose sfide. Il patrimonio culturale, in particolare il patrimonio letterario, è spesso trascurato nelle strategie di sviluppo rurale. Tuttavia, la sua tutela e valorizzazione possono svolgere un ruolo fondamentale nella rigenerazione rurale. Questa ricerca intraprende un’esplorazione comprensiva di come viene definita la ruralità, analizzando le principali strategie e politiche europee relative allo sviluppo rurale. Inoltre, indaga il modo in cui il patrimonio letterario viene preservato e promosso dalle organizzazioni internazionali. Inoltre, passa in rassegna lo stato attuale della ricerca sul turismo letterario, con particolare attenzione al turismo letterario associato alla letteratura per l’infanzia. La ricerca introduce un quadro analitico per esaminare lo sviluppo e la governance delle destinazioni letterarie nelle aree rurali. Attraverso quattro casi studio, questa tesi esplora come il patrimonio letterario viene gestito e valorizzato a livello locale, dimostrando che l'utilizzo efficace delle risorse letterarie può contribuire allo sviluppo economico, sociale e culturale di alcune aree rurali e piccole città. La tesi si concentra specificamente sulla letteratura per l'infanzia, analizzando i seguenti casi studio: (1) Sarmede (Italia), legata allo scrittore, pittore e illustratore Štěpán Zavřel, (2) Collodi (Pescia, Italia), legata a Carlo Lorenzini, meglio conosciuto con lo pseudonimo Carlo Collodi, autore di Pinocchio, (3) Near Sawrey e il Lake District (Regno Unito), legato a Beatrix Potter, la cui Storia di Peter Rabbit è tra le sue opere più famose, e (4) Hartfield (Regno Unito), associato ad Alan Alexander Milne, creatore di Winnie-the-Pooh. Infine, attraverso un'analisi comparativa di questi casi studio, questa tesi identifica sfide e opportunità comuni, evidenzia le migliori pratiche e scopre approcci unici nelle diverse destinazioni letterarie. In conclusione, questa tesi mira a fornire raccomandazioni pratiche agli stakeholder locali, offrendo una tabella di marcia per sfruttare il patrimonio letterario come catalizzatore per la rigenerazione rurale

Prognostic and diagnostic markers in neuroendocrine thymic tumours:a pilot study

Background: Thymic neuroendocrine neoplasm (TNENs) are rare and aggressive cancers. The aim of the present study was to examine the prognostic significance of a panel of twenty biomolecular markers and to select the most common ones in order to better understand the pathogenesis and the prognostic factors of TNENs. Material and methods: Clinical data and pathological tissue samples collected from surgically treated patients affected by TNENs were analysed. Twenty biomolecular markers, adopted in previously worldwide published papers, were utilized in a tissue microarray parallel in situ analyses. All patients were divided into three groups according to histological diagnosis: typical carcinoid(TC), atypical carcinoid(AC), and mixed (MxTNET). Overall and disease-free survival analysis was performed with the Kaplan-Meier method and the log-rank test. Results: A total of 20 patients (1994-2012) was outlined from the databases.The great majority were male (90%) with a mean age of 55 years (IQR 35-82). 5- and 10- year OS of the cohort were 65% and 47%. 5-and 10-year DFS were 27% and 18%. Analysing the 20 markers, different expression between different histological types of TNETs was noticed with a significant trend in the DFS, towards two molecules such as Osteopontin (p=0.032) and PTEN (p=0.023). Analysing the overall survival, significant differences were noticed for pMTor (p=0.004). This protein had also an impact on DFS (p=0.002). Conclusion: According to the reported data, our analysis confirms the importance of OPN and PTEN also in neuroendocrine thymic tumours. Those parameters may be studied in larger cohort and integrated with the already known prognosticators to better define their impact on long term outcomes. Large multicentre studies are mandatory to define a scoring system able to predict the recurrence after radical surgery and define who benefit the most from aggressive therapie