Risposta Immunitaria Epatite B specifica in pazienti affetti da Epatocarcinoma

Hepatitis B x protein (HBx) is a non structural, multifunctional protein of hepatitis B virus (HBV) that modulates a variety of host processes.Due to its transcriptional activity,able to alter the expression of growth-control genes,it has been implicated in hepatocarcinogenesis.Increased expression of HBx has been reported on the liver tissue samples of hepatocellular carcinoma (HCC),and a specific anti-HBx immune response can be detected in the peripheral blood of patients with chronic HBV.However,its role and entity has not been yet clarified.Thus,we performed a cross-sectional analysis of anti-HBx specific T cell response in HBV-infected patients in different stage of disease.A total of 70 HBV-infected subjects were evaluated:15 affected by chronic hepatitis (CH-median age 45 yrs),14 by cirrhosis (median age 55 yrs),11 with dysplastic nodules (median age 64 yrs),15 with HCC (median age 60 yrs),15 with IC(median age 53 yrs).All patients were infected by virus genotype D with different levels of HBV viremia and most of them (91%) were HBeAb positive.The HBx-specific T cell response was evaluated by anti-Interferon (IFN)-gamma Elispot assay after in vitro stimulation of peripheral blood mononuclear cells,using 20 overlapping synthetic peptides covering all HBx protein sequence.HBx-specific IFN-gamma-secreting T cells were found in 6 out of 15 patients with chronic hepatitis (40%), 3 out of 14 cirrhosis (21%), in 5 out of 11 cirrhosis with macronodules (54%), and in 10 out of 15 HCC patients (67%). The number of responding patients resulted significantly higher in HCC than IC (p=0.02) and cirrhosis (p=0.02). Central specific region of the protein x was preferentially recognize,between 86-88 peptides. HBx response does not correlate with clinical feature disease(AFP,MELD).The HBx specific T-cell response seems to increase accordingly to progression of the disease, being increased in subjects with dysplastic or neoplastic lesions and can represent an additional tool to monitor the patients at high risk to develop HCC

Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.