Cognitive and affective processes in social actions and decisions

The question of how we make, and how we should make judgments and decisions has occupied thinkers for many centuries. This thesis has the aim to add new evidences to clarify the brain’s mechanisms for decisions. The cognitive and the emotional processes of social actions and decisions are investigated with the aim to understand which brain areas are mostly involved. Four experimental studies are presented. A specific kind of population is involved in the first study (as well as in study III) concerning patients with lesion of ventromedial prefrontal cortex (vmPFC). This region is collocated in the ventral surface of frontal lobe, and it seems have an important role in social and moral decision in forecasting the negative emotional consequences of choice. In study I, it is examined whether emotions, specifically social emotions subserved by the vmPFC, affect people’s willingness to trust others. In study II is observed how incidental emotions could encourage trusting behaviour, especially when individuals are not aware of emotive stimulation. Study III has the aim to gather a direct psychophysiological evidence, both in healthy and neurologically impaired individuals, that emotions are crucially involved in shaping moral judgment, by preventing moral violations. Study IV explores how the moral meaning of a decision and its subsequent action can modulate the basic component of action such as sense of agency.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Functional and Genetic characterization of new genomic islands from an E. coli strain associated with neonatal meningitis.

Enterobacteriaceae genomes evolve through mutations, rearrangements and horizontal gene transfer (HGT). The latter evolutionary pathway works through the acquisition DNA (GEI) modules of foreign origin that enhances fitness of the host to a given environment. The genome of E. coli IHE3034, a strain isolated from a case of neonatal meningitis, has recently been sequenced and its subsequent sequence analysis has predicted 18 possible GEIs, of which: 8 have not been previously described, 5 fully meet the pathogenic island definition and at least 10 that seem to be of prophagic origin. In order to study the GEI distribution of our reference strain, we screened for the presence 18 GEIs a panel of 132 strains, representative of E. coli diversity. Also, using an inverse nested PCR approach we identified 9 GEI that can form an extrachromosomal circular intermediate (CI) and their respective attachment sites (att). Further, we set up a qPCR approach that allowed us to determine the excision rates of 5 genomic islands in different growth conditions. Four islands, specific for strains appertaining to the sequence type complex 95 (STC95), have been deleted in order to assess their function in a Dictyostelium discoideum grazing assays. Overall, the distribution data presented here indicate that 16 IHE3034 GEIs are more associated to the STC95 strains. Also the functional and genetic characterization has uncovered that GEI 13, 17 and 19 are involved in the resistance to phagocitation by Dictyostelium d thus suggesting a possible role in the adaptation of the pathogen during certain stages of infection.