Sleep motor activity in parkinsonian syndromes at onset: a prospective study to determine potential diagnostic and prognostic markers

Aim of this study is to describe the possible diagnostic value of sleep disturbances in the differential diagnosis of neurodegenerative diseases characterized by parkinsonism at onset. 42 consecutive patients with parkinsonian features and disease duration up to 3 years were included in the BO-ProPark study. Each patient was evaluated twice, at baseline (T0) and 16 months later (T1). Patients were diagnosed as Parkinson disease (PD, 27 patients), PD plus (PD with cognitive impairment/dementia or dysautonomia, 4 patients) and parkinsonian syndrome (PS, 11 patients). All patients underwent a full night video-polysomnography scored by a neurologist blinded to the clinical diagnosis. Sleep efficiency and total sleep time were reduced in all patients; wake after sleep onset was higher in patients with atypical parkinsonisms than in PD patients. No significant differences between groups of patients were detected in other sleep parameters. The mean percentage of epochs with enhanced tonic muscle EMG activity during REM sleep was higher in PD plus and PS than in PD. No difference in phasic muscle EMG activity during REM sleep was seen between the two groups. REM behaviour disorder was more frequent in PD plus and PS than in PD patients. Our data suggest that REM sleep motor control is more frequently impaired at disease onset in patients with PS and PD plus compared to PD patients. The presence of RBD or an enhanced tonic muscle EMG activity in a patient with recent onset parkinsonian features should suggest a diagnosis of atypical parkinsonism, rather than PD. More data are needed to establish the diagnostic value of these features in the differential diagnosis of parkinsonisms. The evaluation of sleep disorders may be a useful tool in the differential diagnosis of parkinsonism at onset.

Human papillomavirus (HPV) and associated diseases: between applied diagnostic and basic research

Human Papillomavirus (HPV) is the cause of cervical cancers (among these, adenocarcinoma, AdCa) and is associated to a subgroup of oropharyngeal carcinomas (OPSCCs). Even if the risk for cancer development is linked to the infection by some viral genotypes, mainly HPV16 and 18, viral DNA alone seems not to be sufficient for diagnosis. Moreover, the role of the virus in OPSCCs has not been totally clarified yet. In the first part of the thesis, the performances concerning viral genotyping in clinical cervical samples of a new pyrosequencing-based test and a well-known hybridization-based assay have been compared. Similar results between the methods have been obtained. However, the former showed advantages in detecting intratype variants, higher specificity and a broader spectrum of detectable HPV types. The second part deals with the evaluation of virological markers (genotyping, viral oncoproteins expression, viral load, physical state and CpG methylation of HPV16 genome) in the diagnosis/prognosis of cervical AdCa and HPV-associated OPSCCs. HPV16 has been confirmed the most prevalent genotype in both the populations. Interestingly, the mean methylation frequency of viral DNA at the early promoter showed the tendency to be associated to invasion for cervical AdCa and to a worse prognosis for OPSCCs, suggesting a promising role as diagnostic/prognostic biomarker. The experiments of the third part were performed at the DKFZ in Heidelberg (Germany) and dealt with the analysis of the response to IFN-k transfection in HPV16-positive cervical cancer and head&neck carcinoma cell lines to evaluate its potential role as new treatment. After 24h, we observed increased IFN-b expression which lead to the up-regulation of genes involved in the antigens presentation pathway (MHC class I and immunoproteasome) and antiviral response as well, in particular in cervical cancer cell lines. This fact suggested also the presence of different HPV-mediated carcinogenic pathways between the two anatomical districts.

Bioimaging of animal embryogenesis: mathematical methods and computational algorithms

Some fundamental biological processes such as embryonic development have been preserved during evolution and are common to species belonging to different phylogenetic positions, but are nowadays largely unknown. The understanding of cell morphodynamics leading to the formation of organized spatial distribution of cells such as tissues and organs can be achieved through the reconstruction of cells shape and position during the development of a live animal embryo. We design in this work a chain of image processing methods to automatically segment and track cells nuclei and membranes during the development of a zebrafish embryo, which has been largely validates as model organism to understand vertebrate development, gene function and healingrepair mechanisms in vertebrates. The embryo is previously labeled through the ubiquitous expression of fluorescent proteins addressed to cells nuclei and membranes, and temporal sequences of volumetric images are acquired with laser scanning microscopy. Cells position is detected by processing nuclei images either through the generalized form of the Hough transform or identifying nuclei position with local maxima after a smoothing preprocessing step. Membranes and nuclei shapes are reconstructed by using PDEs based variational techniques such as the Subjective Surfaces and the Chan Vese method. Cells tracking is performed by combining informations previously detected on cells shape and position with biological regularization constraints. Our results are manually validated and reconstruct the formation of zebrafish brain at 7-8 somite stage with all the cells tracked starting from late sphere stage with less than 2% error for at least 6 hours. Our reconstruction opens the way to a systematic investigation of cellular behaviors, of clonal origin and clonal complexity of brain organs, as well as the contribution of cell proliferation modes and cell movements to the formation of local patterns and morphogenetic fields.

Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.

Synthesis of constrained peptidomimetics for therapeutic, diagnostic and theranostic applications

This thesis work deals, principally, with the development of different chemical protocols ranging from environmental sustainability peptide synthesis to asymmetric synthesis of modified tryptophans to a series of straightforward procedures for constraining peptide backbones without the need for a pre-formed scaffold. Much efforts have been dedicated to the structural analysis in a biomimetic environment, fundamental for predicting the in vivo conformation of compounds, as well as for giving a rationale to the experimentally determined bioactivity. The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, titration experiments, molecular dynamics, etc.), FT-IR and ECD spectroscopy. As a practical application, 3D rigid scaffolds have been employed for the synthesis of biological active compounds based on peptidomimetic and retro-mimetic structures. These mimics have been investigated for their potential as antiflammatory agents and actually the results obtained are very promising. Moreover, the synthesis of Amo ring permitted the development of an alternative high effective synthetic pathway for obtaining Linezolid antibiotic. The final section is, instead, dedicated to the construction of a new biosensor based on zeolite L SAMs functionalized with the integrin ligand c[RGDfK], that has showed high efficiency for the selective detection of tumor cells. Such kind of sensor could, in fact, enable the convenient, non-invasive detection and diagnosis of cancer in early stages, from a few drops of a patient's blood or other biological fluids. In conclusion, the researches described herein demonstrate that the peptidomimetic approach to 3D definite structures, allows unambiguous investigation of the structure-activity relationships, giving an access to a wide range bioactive compounds of pharmaceutical interest to use not only as potential drugs but also for diagnostic and theranostic applications.

New knowledge, diagnostic and control tools to limit the impact of viral nervous necrosis (VNN) in the Mediterranean aquaculture sector

The role of aquaculture in satisfying the global seafood demand is essential. The expansion of the aquaculture sector and the intensification of its activities have enhanced the circulation of infectious agents. Among these, the nervous necrosis virus (NNV) represents the most widespread in the Mediterranean basin. The NNV is responsible for a severe neuropathological condition named viral nervous necrosis (VNN), impacting hugely on fish farms due to the serious disease-associated losses. Therefore, it is fundamental to develop new strategies to limit the impact of VNN in this area, interconnecting several aspects of disease management, diagnosis and prevention. This PhD thesis project, focusing on aquatic animals’ health, deals with these topics. The first two chapters expand the knowledge on VNN epidemiology and distribution, showing the possibility of interspecies transmission, persistent infections and a potential carrier role for invertebrates. The third study expands the horizon of VNN diagnosis, by developing a quick and affordable multiplex RT-PCR able to detect and simultaneously discriminate between NNV variants, reducing considerably the time and costs of genotyping. The fourth study, with the development of a fluorescent in situ hybridization technique and its application to aquatic vertebrates and invertebrates’ tissues, contributes to expand the knowledge on NNV distribution at cellular level, localizing also the replication site of the virus. Finally, the last study dealing with an in vitro evaluation of the NNV susceptibility to a commercial biocide, stress the importance to implement proper disinfectant procedures in fish farms to prevent virus spread and disease outbreaks.

Management and routing algorithms for ad-hoc and sensor networks

Large scale wireless adhoc networks of computers, sensors, PDAs etc. (i.e. nodes) are revolutionizing connectivity and leading to a paradigm shift from centralized systems to highly distributed and dynamic environments. An example of adhoc networks are sensor networks, which are usually composed by small units able to sense and transmit to a sink elementary data which are successively processed by an external machine. Recent improvements in the memory and computational power of sensors, together with the reduction of energy consumptions, are rapidly changing the potential of such systems, moving the attention towards datacentric sensor networks. A plethora of routing and data management algorithms have been proposed for the network path discovery ranging from broadcasting/floodingbased approaches to those using global positioning systems (GPS). We studied WGrid, a novel decentralized infrastructure that organizes wireless devices in an adhoc manner, where each node has one or more virtual coordinates through which both message routing and data management occur without reliance on either flooding/broadcasting operations or GPS. The resulting adhoc network does not suffer from the deadend problem, which happens in geographicbased routing when a node is unable to locate a neighbor closer to the destination than itself. WGrid allow multidimensional data management capability since nodes' virtual coordinates can act as a distributed database without needing neither special implementation or reorganization. Any kind of data (both single and multidimensional) can be distributed, stored and managed. We will show how a location service can be easily implemented so that any search is reduced to a simple query, like for any other data type. WGrid has then been extended by adopting a replication methodology. We called the resulting algorithm WRGrid. Just like WGrid, WRGrid acts as a distributed database without needing neither special implementation nor reorganization and any kind of data can be distributed, stored and managed. We have evaluated the benefits of replication on data management, finding out, from experimental results, that it can halve the average number of hops in the network. The direct consequence of this fact are a significant improvement on energy consumption and a workload balancing among sensors (number of messages routed by each node). Finally, thanks to the replications, whose number can be arbitrarily chosen, the resulting sensor network can face sensors disconnections/connections, due to failures of sensors, without data loss. Another extension to {WGrid} is {W*Grid} which extends it by strongly improving network recovery performance from link and/or device failures that may happen due to crashes or battery exhaustion of devices or to temporary obstacles. W*Grid guarantees, by construction, at least two disjoint paths between each couple of nodes. This implies that the recovery in W*Grid occurs without broadcasting transmissions and guaranteeing robustness while drastically reducing the energy consumption. An extensive number of simulations shows the efficiency, robustness and traffic road of resulting networks under several scenarios of device density and of number of coordinates. Performance analysis have been compared to existent algorithms in order to validate the results.

Crashworthiness and composite materials: development of an experimental test method for the energy absorption determination and implementation of the relative numerical model

In this PhD thesis the crashworthiness topic is studied with the perspective of the development of a small-scale experimental test able to characterize a material in terms of energy absorption. The material properties obtained are then used to validate a nu- merical model of the experimental test itself. Consequently, the numerical model, calibrated on the specific ma- terial, can be extended to more complex structures and used to simulate their energy absorption behavior. The experimental activity started at University of Washington in Seattle, WA (USA) and continued at Second Faculty of Engi- neering, University of Bologna, Forl`ı (Italy), where the numerical model for the simulation of the experimental test was implemented and optimized.

The school environment as a teacher. The role of space and place in enhancing ecological literacy and social competence development in children and young people

Can space and place foster child development, and in particular social competence and ecological literacy? If yes, how can space and place do that? This study shows that the answer to the first question is positive and then tries to explain the way space and place can make a difference. The thesis begins with the review of literature from different disciplines – child development and child psychology, education, environmental psychology, architecture and landscape architecture. Some bridges among such disciplines are created and in some cases the ideas from the different areas of research merge: thus, this is an interdisciplinary study. The interdisciplinary knowledge from these disciplines is translated into a range of design suggestions that can foster the development of social competence and ecological literacy. Using scientific knowledge from different disciplines is a way of introducing forms of evidence into the development of design criteria. However, the definition of design criteria also has to pass through the study of a series of school buildings and un-built projects: case studies can give a positive contribution to the criteria because examples and good practices can help “translating” the theoretical knowledge into design ideas and illustrations. To do that, the different case studies have to be assessed in relation to the various themes that emerged in the literature review. Finally, research by design can be used to help define the illustrated design criteria: based on all the background knowledge that has been built, the role of the architect is to provide a series of different design solutions that can give answers to the different “questions” emerged in the literature review.

Shareholder protection and stock market development

The dissertation contains five parts: An introduction, three major chapters, and a short conclusion. The First Chapter starts from a survey and discussion of the studies on corporate law and financial development literature. The commonly used methods in these cross-sectional analyses are biased as legal origins are no longer valid instruments. Hence, the model uncertainty becomes a salient problem. The Bayesian Model Averaging algorithm is applied to test the robustness of empirical results in Djankov et al. (2008). The analysis finds that their constructed legal index is not robustly correlated with most of the various stock market outcome variables. The second Chapter looks into the effects of minority shareholders protection in corporate governance regime on entrepreneurs' ex ante incentives to undertake IPO. Most of the current literature focuses on the beneficial part of minority shareholder protection on valuation, while overlooks its private costs on entrepreneur's control. As a result, the entrepreneur trade-offs the costs of monitoring with the benefits of cheap sources of finance when minority shareholder protection improves. The theoretical predictions are empirically tested using panel data and GMM-sys estimator. The third Chapter investigates the corporate law and corporate governance reform in China. The corporate law in China regards shareholder control as the means to the ends of pursuing the interests of stakeholders, which is inefficient. The Chapter combines the recent development of theories of the firm, i.e., the team production theory and the property rights theory, to solve such problem. The enlightened shareholder value, which emphasizes on the long term valuation of the firm, should be adopted as objectives of listed firms. In addition, a move from the mandatory division of power between shareholder meeting and board meeting to the default regime, is proposed.

Real-Time Engine Diagnostic and Control Based on Acoustic Emissions Analysis

Engine developers are putting more and more emphasis on the research of maximum thermal and mechanical efficiency in the recent years. Research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting exhaust emissions limits. These new technologies require more complex engine control units. The sound emitted from a mechanical system encloses many information related to its operating condition and it can be used for control and diagnostic purposes. The thesis shows how the functions carried out from different and specific sensors usually present on-board, can be executed, at the same time, using only one multifunction sensor based on low-cost microphone technology. A theoretical background about sound and signal processing is provided in chapter 1. In modern turbocharged downsized GDI engines, the achievement of maximum thermal efficiency is precluded by the occurrence of knock. Knock emits an unmistakable sound perceived by the human ear like a clink. In chapter 2, the possibility of using this characteristic sound for knock control propose, starting from first experimental assessment tests, to the implementation in a real, production-type engine control unit will be shown. Chapter 3 focus is on misfire detection. Putting emphasis on the low frequency domain of the engine sound spectrum, features related to each combustion cycle of each cylinder can be identified and isolated. An innovative approach to misfire detection, which presents the advantage of not being affected by the road and driveline conditions is introduced. A preliminary study of air path leak detection techniques based on acoustic emissions analysis has been developed, and the first experimental results are shown in chapter 4. Finally, in chapter 5, an innovative detection methodology, based on engine vibration analysis, that can provide useful information about combustion phase is reported.

Essays in Economic Geography and Long-Term Development

This dissertation has two main themes: first, the economic impact of tourism on cities and, secondly, the determinants of European long-run development, with a focus on the pre-Industrial era. The common thread is the attempt to develop economic geography models that incorporate spatial frictions and are liable to be given empirical content. Chapter 1, written in conjunction with G. Alfredo Minerva, provides an empirical analysis of the relationship between tourism and economic activity across Italian municipalities, and lays down the basic elements of an urban theory of tourism in an a-spatial setting. Chapter 2 extends these ideas to a quantitative urban framework to study the economic impact and the welfare consequences of tourism into the city of Venice. The model is given empirical content thanks to a large collection of data at the Census tract level for the Municipality of Venice, and then used to perform counterfactual policty analysis. In chapter 3, with Matteo Santacesaria, we consider a setting where agents are continuously distributed over a two-dimensional heterogeneous geography, and are allowed to do business at a finite set of markets. We study the equilibrium partition of the economic space into a collection of mutually-exclusive market areas, and provide condition for this equilibrium partition to exist and to be unique. Finally, chapter 4 "The rise of (urban) Europe: a Quantitative-Spatial analysis", co-authored with Matteo Cervellati and Alex Lehner, sets up a quantitative economic geography model to understand the roots of the Industrial Revolution, in an attempt to match the evolution of the European urban network, and the corresponding city-size distribution, over the period A.D. 1000-1850. It highlights the importance of agricultural trade across cities for the emergence of large manufacturing hubs.

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.