Cellular Proliferation in the Prognosis of Intermediate Grade Mast Cell Tumour in Dogs

This was a retrospective study including ninety samples of dogs with a histological diagnosis of intermediate grade cutaneous mast cell tumour (MCT). The objectives of the study were to validate Minichromosome Maintenance Protein 7 (MCM7) as a prognostic marker in MCTs and to compare the ability of mitotic index (MI), Ki67 and MCM7 to predict outcome. The median survival for the entire population was not reached at 2099 days. The mean survival time was 1708 days. Seventy-two cases were censored after a median follow up of 1136 days and eighteen dogs died for causes related to the MCT after a median of 116 days. For each sample MI, Ki67 and MCM7 were determined. The Receiver Operating Characteristic (ROC) curve was obtained for each prognostic marker to evaluate the performance of the test, expressed as area under the curve, and whether the published threshold value was adequate. Kaplan-Meier and corresponding logrank test for MI, Ki67 and MCM7 as binary variables was highly significant (P<0.0001). Multivariable regression analysis of MI, Ki67 and MCM7 corrected for age and surgical margins indicated that the higher risk of dying of MCT was associated with MCM7 > 0.18 (Hazard Ration [HR] 14.7; P<0.001) followed by MI > 5 (HR 13.9; P<0.001) and Ki67 > 0.018 (HR 8.9; P<0.001). Concluding, the present study confirmed that MCM7 is an excellent prognostic marker in cutaneous MCTs being able to divide Patnaik intermediate grade tumours in two categories with different prognosis. Ki67 was equally good confirming its value as a prognostic marker in intermediate grade MCTs. The mitotic index was extremely specific, but lacked of sensitivity. Interestingly, mitotic index, Ki67 and MCM7 were independent from each other suggesting that their combination would improve their individual prognostic value.

Prediction Nomogram for 68Ga-PSMA-11 PET/CT in different clinical settings of PSA failure after radical treatment for Prostate Cancer

Objective The objective of this study was to develop a clinical nomogram to predict gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (68Ga-PSMA-11-PET/CT) positivity in different clinical settings of PSA failure. Materials and methods Seven hundred three (n = 703) prostate cancer (PCa) patients with confirmed PSA failure after radical therapy were enrolled. Patients were stratified according to different clinical settings (first-time biochemical recurrence [BCR]: group 1; BCR after salvage therapy: group 2; biochemical persistence after radical prostatectomy [BCP]: group 3; advanced stage PCa before second-line systemic therapies: group 4). First, we assessed 68Ga-PSMA-11-PET/CT positivity rate. Second, multivariable logistic regression analyses were used to determine predictors of positive scan. Third, regression-based coefficients were used to develop a nomogram predicting positive 68Ga-PSMA-11-PET/CT result and 200 bootstrap resamples were used for internal validation. Fourth, receiver operating characteristic (ROC) analysis was used to identify the most informative nomogram’s derived cut-off. Decision curve analysis (DCA) was implemented to quantify nomogram’s clinical benefit. Results 68Ga-PSMA-11-PET/CT overall positivity rate was 51.2%, while it was 40.3% in group 1, 54% in group 2, 60.5% in group 3, and 86.9% in group 4 (p < 0.001). At multivariable analyses, ISUP grade, PSA, PSA doubling time, and clinical setting were independent predictors of a positive scan (all p ≤ 0.04). A nomogram based on covariates included in the multivariate model demonstrated a bootstrap-corrected accuracy of 82%. The nomogram-derived best cut-off value was 40%. In DCA, the nomogram revealed clinical net benefit of > 10%. Conclusions This novel nomogram proved its good accuracy in predicting a positive scan, with values ≥ 40% providing the most informative cut-off in counselling patients to 68Ga-PSMA-11-PET/CT. This tool might be important as a guide to clinicians in the best use of PSMA-based PET imaging.

Identification of a molecular signature as potential biomarker in blood of symptomatic and asymptomatic patients with carotid atherosclerosis

Background and Objectives: Carotid revascularization to prevent future vascular events is reasonable in patients with high-grade carotid stenosis. Currently, several biomarkers to predict carotid plaque development and progression have been investigated, among which microRNAs (miRs) are promising tools for the diagnosis of atherosclerosis. Methods and Results: A total of 49 participants were included in the study, divided into two main populations: Population 1 comprising symptomatic and asymptomatic inpatients, and Population 2 comprising asymptomatic outpatients. The study consisted of two main phases: a preliminary discovery phase and a validation phase, applying different techniques. MiR-profiles were performed on plasma and plaque tissue samples obtained from 4 symptomatic and 4 asymptomatic inpatients. MiRs emerging from profiling comparisons, i.e. miR-126-5p, miR-134-5p, miR-145-5p, miR-151a-5p, miR-34b, miR-451a, miR-720 and miR-1271-5p, were subjected to validation through RT-qPCR analysis in the total cohort of donors. Comparing asymptomatic and symptomatic inpatients, significant differences were reported in the expression levels of c-miRs for miR-126-5p and miR-1271-5p in blood, being more expressed in symptomatic subjects. In contrast, simultaneous evaluation of the selected miRs in plaque tissue samples did not confirm data obtained by the miR profiling, and no significant differences were observed. Using Receiver-Operating Characteristic (ROC) analysis, a circulating molecular signature (mir-126-5p, miR-1271-5p, albumin, C-reactive protein, and monocytes) was identified, allowing the distinction of the two groups in Population 1 (AUC = 0.795). Conclusions: Data emerging from this thesis suggest that c-miRs (i.e. miR-126-5p, miR-1271-5p) combined with selected haemato-biochemical parameters (albumin, C-reactive protein, and monocytes) produced a good molecular 'signature' to distinguish asymptomatic and symptomatic inpatients. C-miRs in blood do not necessarily reflect the expression levels of the same miRs in carotid plaque tissues since different mechanism can influence their expression.

Seizure prediction and control in epilepsy

The first part of my thesis presents an overview of the different approaches used in the past two decades in the attempt to forecast epileptic seizure on the basis of intracranial and scalp EEG. Past research could reveal some value of linear and nonlinear algorithms to detect EEG features changing over different phases of the epileptic cycle. However, their exact value for seizure prediction, in terms of sensitivity and specificity, is still discussed and has to be evaluated. In particular, the monitored EEG features may fluctuate with the vigilance state and lead to false alarms. Recently, such a dependency on vigilance states has been reported for some seizure prediction methods, suggesting a reduced reliability. An additional factor limiting application and validation of most seizure-prediction techniques is their computational load. For the first time, the reliability of permutation entropy [PE] was verified in seizure prediction on scalp EEG data, contemporarily controlling for its dependency on different vigilance states. PE was recently introduced as an extremely fast and robust complexity measure for chaotic time series and thus suitable for online application even in portable systems. The capability of PE to distinguish between preictal and interictal state has been demonstrated using Receiver Operating Characteristics (ROC) analysis. Correlation analysis was used to assess dependency of PE on vigilance states. Scalp EEG-Data from two right temporal epileptic lobe (RTLE) patients and from one patient with right frontal lobe epilepsy were analysed. The last patient was included only in the correlation analysis, since no datasets including seizures have been available for him. The ROC analysis showed a good separability of interictal and preictal phases for both RTLE patients, suggesting that PE could be sensitive to EEG modifications, not visible on visual inspection, that might occur well in advance respect to the EEG and clinical onset of seizures. However, the simultaneous assessment of the changes in vigilance showed that: a) all seizures occurred in association with the transition of vigilance states; b) PE was sensitive in detecting different vigilance states, independently of seizure occurrences. Due to the limitations of the datasets, these results cannot rule out the capability of PE to detect preictal states. However, the good separability between pre- and interictal phases might depend exclusively on the coincidence of epileptic seizure onset with a transition from a state of low vigilance to a state of increased vigilance. The finding of a dependency of PE on vigilance state is an original finding, not reported in literature, and suggesting the possibility to classify vigilance states by means of PE in an authomatic and objectic way. The second part of my thesis provides the description of a novel behavioral task based on motor imagery skills, firstly introduced (Bruzzo et al. 2007), in order to study mental simulation of biological and non-biological movement in paranoid schizophrenics (PS). Immediately after the presentation of a real movement, participants had to imagine or re-enact the very same movement. By key release and key press respectively, participants had to indicate when they started and ended the mental simulation or the re-enactment, making it feasible to measure the duration of the simulated or re-enacted movements. The proportional error between duration of the re-enacted/simulated movement and the template movement were compared between different conditions, as well as between PS and healthy subjects. Results revealed a double dissociation between the mechanisms of mental simulation involved in biological and non-biologial movement simulation. While for PS were found large errors for simulation of biological movements, while being more acurate than healthy subjects during simulation of non-biological movements. Healthy subjects showed the opposite relationship, making errors during simulation of non-biological movements, but being most accurate during simulation of non-biological movements. However, the good timing precision during re-enactment of the movements in all conditions and in both groups of participants suggests that perception, memory and attention, as well as motor control processes were not affected. Based upon a long history of literature reporting the existence of psychotic episodes in epileptic patients, a longitudinal study, using a slightly modified behavioral paradigm, was carried out with two RTLE patients, one patient with idiopathic generalized epilepsy and one patient with extratemporal lobe epilepsy. Results provide strong evidence for a possibility to predict upcoming seizures in RTLE patients behaviorally. In the last part of the thesis it has been validated a behavioural strategy based on neurobiofeedback training, to voluntarily control seizures and to reduce there frequency. Three epileptic patients were included in this study. The biofeedback was based on monitoring of slow cortical potentials (SCPs) extracted online from scalp EEG. Patients were trained to produce positive shifts of SCPs. After a training phase patients were monitored for 6 months in order to validate the ability of the learned strategy to reduce seizure frequency. Two of the three refractory epileptic patients recruited for this study showed improvements in self-management and reduction of ictal episodes, even six months after the last training session.

GNSS interference management techniques against malicious attacks

This thesis collects the outcomes of a Ph.D. course in Telecommunications Engineering and it is focused on the study and design of possible techniques able to counteract interference signal in Global Navigation Satellite System (GNSS) systems. The subject is the jamming threat in navigation systems, that has become a very increasingly important topic in recent years, due to the wide diffusion of GNSS-based civil applications. Detection and mitigation techniques are developed in order to fight out jamming signals, tested in different scenarios and including sophisticated signals. The thesis is organized in two main parts, which deal with management of GNSS intentional counterfeit signals. The first part deals with the interference management, focusing on the intentional interfering signal. In particular, a technique for the detection and localization of the interfering signal level in the GNSS bands in frequency domain has been proposed. In addition, an effective mitigation technique which exploits the periodic characteristics of the common jamming signals reducing interfering effects at the receiver side has been introduced. Moreover, this technique has been also tested in a different and more complicated scenario resulting still effective in mitigation and cancellation of the interfering signal, without high complexity. The second part still deals with the problem of interference management, but regarding with more sophisticated signal. The attention is focused on the detection of spoofing signal, which is the most complex among the jamming signal types. Due to this highly difficulty in detect and mitigate this kind of signal, spoofing threat is considered the most dangerous. In this work, a possible techniques able to detect this sophisticated signal has been proposed, observing and exploiting jointly the outputs of several operational block measurements of the GNSS receiver operating chain.

Landslide susceptibility in the Belt and Road Initiative

The Belt and Road Initiative (BRI) is a project launched by the Chinese Government whose main goal is to connect more than 65 countries in Asia, Europe, Africa and Oceania developing infrastructures and facilities. To support the prevention or mitigation of landslide hazards, which may affect the mainland infrastructures of BRI, a landslide susceptibility analysis in the countries involved has been carried out. Due to the large study area, the analysis has been carried out using a multi-scale approach which consists of mapping susceptibility firstly at continental scale, and then at national scale. The study area selected for the continental assessment is the south-Asia, where a pixel-based landslide susceptibility map has been carried out using the Weight of Evidence method and validated by Receiving Operating Characteristic (ROC) curves. Then, we selected the regions of west Tajikistan and north-east India to be investigated at national scale. Data scarcity is a common condition for many countries involved into the Initiative. Therefore in addition to the landslide susceptibility assessment of west Tajikistan, which has been conducted using a Generalized Additive Model and validated by ROC curves, we have examined, in the same study area, the effect of incomplete landslide dataset on the prediction capacity of statistical models. The entire PhD research activity has been conducted using only open data and open-source software. In this context, to support the analysis of the last years an open-source plugin for QGIS has been implemented. The SZ-tool allows the user to make susceptibility assessments from the data preprocessing, susceptibility mapping, to the final classification. All the output data of the analysis conducted are freely available and downloadable. This text describes the research activity of the last three years. Each chapter reports the text of the articles published in international scientific journal during the PhD.