Design, implementation and evaluation of a virtual laboratory for Computer Engineering Education

Broad consensus has been reached within the Education and Cognitive Psychology research communities on the need to center the learning process on experimentation and concrete application of knowledge, rather than on a bare transfer of notions. Several advantages arise from this educational approach, ranging from the reinforce of students learning, to the increased opportunity for a student to gain greater insight into the studied topics, up to the possibility for learners to acquire practical skills and long-lasting proficiency. This is especially true in Engineering education, where integrating conceptual knowledge and practical skills assumes a strategic importance. In this scenario, learners are called to play a primary role. They are actively involved in the construction of their own knowledge, instead of passively receiving it. As a result, traditional, teacher-centered learning environments should be replaced by novel learner-centered solutions. Information and Communication Technologies enable the development of innovative solutions that provide suitable answers to the need for the availability of experimentation supports in educational context. Virtual Laboratories, Adaptive Web-Based Educational Systems and Computer-Supported Collaborative Learning environments can significantly foster different learner-centered instructional strategies, offering the opportunity to enhance personalization, individualization and cooperation. More specifically, they allow students to explore different kinds of materials, to access and compare several information sources, to face real or realistic problems and to work on authentic and multi-facet case studies. In addition, they encourage cooperation among peers and provide support through coached and scaffolded activities aimed at fostering reflection and meta-cognitive reasoning. This dissertation will guide readers within this research field, presenting both the theoretical and applicative results of a research aimed at designing an open, flexible, learner-centered virtual lab for supporting students in learning Information Security.

Longitudinal evolution of cognitive functions in patients with multiple system atrophy: a prospective study

Introduction and Background: Multiple system atrophy (MSA) is a sporadic, adult-onset, progressive neurodegenerative disease characterized clinically by parkinsonism, cerebellar ataxia, and autonomic failure. We investigated cognitive functions longitudinally in a group of probable MSA patients, matching data with sleep parameters. Patients and Methods: 10 patients (7m/3f) underwent a detailed interview, a general and neurological examination, laboratory exams, MRI scans, a cardiovascular reflexes study, a battery of neuropsychological tests, and video-polysomnographic recording (VPSG). Patients were revaluated (T1) a mean of 16±5 (range: 12-28) months after the initial evaluation (T0). At T1, the neuropsychological assessment and VPSG were repeated. Results: The mean patient age was 57.8±6.4 years (range: 47-64) with a mean age at disease onset of 53.2±7.1 years (range: 43-61) and symptoms duration at T0 of 60±48 months (range: 12-144). At T0, 7 patients showed no cognitive deficits while 3 patients showed isolated cognitive deficits. At T1, 1 patient worsened developing multiple cognitive deficits from a normal condition. At T0 and T1, sleep efficiency was reduced, REM latency increased, NREM sleep stages 1-2 slightly increased. Comparisons between T1 and T0 showed a significant worsening in two tests of attention and no significant differences of VPSG parameters. No correlation was found between neuropsychological results and VPSG findings or RBD duration. Discussion and Conclusions: The majority of our patients do not show any cognitive deficits at T0 and T1, while isolated cognitive deficits are present in the remaining patients. Attention is the cognitive function which significantly worsened. Our data confirm the previous findings concerning the prevalence, type and the evolution of cognitive deficits in MSA. Regarding the developing of a condition of dementia, our data did not show a clear-cut diagnosis of dementia. We confirm a mild alteration of sleep structure. RBD duration does not correlate with neuropsychological findings.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Cognitive and behavioural assessment of parkinsonian syndromes at onset: a longitudinal study

Background: cognitive impairment is one of the non motor features widely descripted in parkinsonian syndrome, it has been related to the motor characteristics of the parkinsonian syndrome, associated with neuropsychiatric dysfunction and the characteristic sleep and autonomic features. It has been shown to be highly prevalent at all disease stages and to contribute significantly to disability. Objectives: aim of this study is to evaluate longitudinally the cognitive and behavioral characteristics of patients with a parkinsonian syndrome at onset; to describe the cognitive and behavioral characteristics of each parkinsonian syndrome; to define in PD patients at onset the presence of MCI or Parkinson disease dementia; to correlate the cognitive and behavioral characteristics with the features of the parkinsonian syndrome and with the associated sleep and autonomic features. Results: we recruited 55 patients, 22 did not present cognitive impairment both at T0 and at T1. 18 patients presented a progression of cognitive impairment. Progressive cognitively impaired patients were older and presented the worst motor phenotype. Progression of cognitive impairment was not associated to sleep and autonomic features. Conclusion: the evaluation of cognitive impairment could not be useful as a predictor of a correct diagnosis but each non motor domain will help to clarify and characterize the motor syndrome. The diagnosis of parkinsonian disorders lies in building a clinical profile in conjunction with other clinical characteristics such as mode of presentation, disease progression, response to medications, sleep and autonomic features.

Evaluation of alpha-synuclein RT-QuIC for an early and differential diagnosis of Lewy body disease

Synucleinopathies are a group of neurodegenerative diseases characterized by tissue deposition of insoluble aggregates of the protein α-synuclein. Currently, the clinical diagnosis of these diseases, including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), is very challenging, especially at an early disease stage, due to the heterogeneous and often non-specific clinical manifestations. Therefore, identifying specific biomarkers to aid the diagnosis and improve the clinical management of patients with these disorders represents a primary goal in the field. Pursuing this aim, we applied the α-Syn Real-Time Quaking-Induced Conversion (RT-QuIC), an ultrasensitive technique able to detect minute amounts of amyloidogenic proteins, to a large cohort of 953 CSF samples from clinically well-characterized (“clinical” group), or neuropathologically verified (“NP” group) patients with parkinsonism or dementia. Of significance, we also studied patients with prodromal synucleinopathies (“prodromal” group), such as pure autonomic failure (PAF) (n = 28), isolated REM sleep behavior disorder (iRBD) (n = 18), and mild cognitive impairment due to probable Lewy body (LB) disease (MCI-LB) (n = 81). Our findings show that α-syn RT-QuIC can accurately detect α-Syn seeding activity across the whole spectrum of LB-related disorders (LBD), exhibiting a mean sensitivity of 95.2% in the “clinical” and “NP” group, while ranging between 89.3% (PAF) and 100% (RBD) in the “prodromal group”. Moreover, we observed 95.1% sensitivity and 96.6% specificity in the distinction between MCI-LB patients and cognitively unimpaired controls, demonstrating the solid diagnostic potential of α-Syn RT-QuIC in the early phase of the disease. Finally, 13.3% of MCI-AD patients also had a positive test, suggesting an underlying LB co-pathology. This work demonstrated that α-Syn RT-QuIC is an efficient assay for accurate and early diagnosis of LBD, which should be implemented for clinical management and recruitment for clinical trials in memory clinics.

Evaluation of the transcriptomic response of an Alzheimer's disease murine model induced at different ages: searching for predictors

Alzheimer’s disease (AD) is a chronic, progressive neurodegenerative disease, characterized by the impairment of mnesic and cognitive functions, that represents the most frequent type of dementia in older people worldwide. Aging is the most important risk factor for the sporadic form of the pathology and it is associated to the progressive impairment of the proteostasis network. The endoplasmic reticulum (ER), the main cellular actor involved in proteostasis, appears significantly compromised in AD due to the accumulation of β-amyloid (Aβ) protein and phosphorylated-tau protein. Increasing proteins misfolding activates a specific cellular response known as Unfolded Protein response (UPR) which orchestrates the recovery of ER function. The aim of the present study was to investigate the role of UPR and aging process in a murine model of AD induced by intracerebroventricular (i.c.v.) injection of Aβ1-42 oligomers at 3 or 18 months. The oligomers injection in aged animals caused the increased of memory impairment, oxidative stress, and the depletion of glutathione reserve. Furthermore, the RNA-sequencing analysis was performed and the bioinformatic analysis showed the enrichment of several pathways involved in neurodegeneration and protein regulations. The following analysis highlighted the significant dysregulation of the three branches of the UPR, the protein kinase RNA-like ER kinase (PERK), inositol-requiring protein 1α (IRE1α) and activating transcription factor 6 (ATF-6). In turn, ER stress affected the PI3K/Akt/Gsk3β and MAPK/ERK pathways, highlighting Mapkapk5 as a potential marker of the neurodegenerative process, which regulation could lead to the definition of new pharmacological and neuroprotective strategies to counteract AD.

Design, synthesis and biological evaluation of dual inhibitors of GSK-3B and Fyn kinases for the study of inflammatory pathways in neurodegenerative diseases

Neuroinflammation represents a key hallmark of neurodegenerative diseases and is the result of a complex network of signaling cascades within microglial cells. A positive feedback loop exists between inflammation, microglia activation and protein misfolding processes, that, together with oxidative stress and excitotoxicity, lead to neuronal degeneration. Therefore, targeting this vicious cycle can be beneficial for mitigating neurodegeneration and cognitive decline in central nervous system disorders. At molecular level, GSK-3B and Fyn kinases play a crucial role in microglia activation and their deregulation has been associated to many neurodegenerative diseases. Thus, we envisioned their combined targeting as an effective approach to disrupt this toxic loop. Specifically in this project, a hit compound, based on a 7-azaindole-3-aminothiazole structure, was first identified in a virtual screening campaign, and displayed a weak dual inhibitory activity on GSK-3B and Fyn, unbalanced towards the former. Then, in a commitment to uncover the structural features required for modulating the activity on the two targets, we systematically manipulated this compound by inserting various substitution patterns in different positions. The most potent compounds obtained were advanced to deeper investigations to test their ability of tackling the inflammatory burden also in cellular systems and to unveil their binding modes within the catalytic pocket. The new class of molecules synthesized emerged as a valuable tool to deepen our understanding of the complex network governing the inflammatory events in neurodegenerative disorders.