Generation and characterization of mouse models of Small cell lung cancer and Basal cell carcinoma for the preclinical evaluation of new therapies

Background. Human small cell lung cancer (SCLC) accounting for approximately 15-20% of all lung cancers, is an aggressive tumor with high propensity for early regional and distant metastases. Although the initial tumor rate response to chemotherapy is very high, SCLC relapses after approximately 4 months in ED and 12 months in LD. Basal cell carcinoma (BCC) is the most prevalent cancer in the western world, and its incidence is increasing worldwide. This type of cancer rarely metastasizes and the death rate is extraordinary low. Surgery is curative for most of the patients, but for those that develop locally advanced or metastatic BCC there is currently no effective treatment. Both types of cancer have been deeply investigated and genetic alterations, MYCN amplification (MA) among the most interesting, have been found. These could become targets of new pharmacological therapies. Procedures. We created and characterized novel BLI xenograft orthotopic mouse models of SCLC to evaluate the tumor onset and progression and the efficacy of new pharmacological strategies. We compared an in vitro model with a transgenic mouse model of BCC, to investigate and delineate the canonical HH signalling pathway and its connections with other molecular pathways. Results and conclusions. The orthotopic models showed latency and progression patterns similar to human disease. Chemotherapy treatments improved survival rates and validated the in vivo model. The presence of MA and overexpression were confirmed in each model and we tested the efficacy of a new MYCN inhibitor in vitro. Preliminar data of BCC models highlighted Hedgehog pathway role and underlined the importance of both in vitro and in vivo strategies to achieve a better understanding of the pathology and to evaluate the applicability of new therapeutic compounds

Climate impact studies of sediment transport on the Adriatic coastal zone

The study of the impact of climate change on the environment has been based, until very recently, on an global approach, whose interest from a local point of view is very limited. This thesis, on the contrary, has treated the study of the impact of climate change in the Adriatic Sea basin following a twofold strategy of regionalization and integration of numerical models in order to reproduce the present and future scenarios of the system through a more and more realistic and solid approach. In particular the focus of the study was on the impact on the physical environment and on the sediment transport in the basin. This latter is a very new and original issue, to our knowledge still uninvestigated. The study case of the coastal area of Montenegro was particularly studied, since it is characterized by an important supply of sediment through the Buna/Bojana river, second most important in the Adriatic basin in terms of flow. To do this, a methodology to introduce the tidal processes in a baroclinic primitive equations Ocean General Circulation Model was applied and tidal processes were successfully reproduced in the Adriatic Sea, analyzing also the impacts they have on the mean general circulation, on salt and heat transport and on mixing and stratification of the water column in the different seasons of the year. The new hydrodynamical model has been further coupled with a wave model and with a river and sea sediment transport model, showing good results in the reproduction of sediment transport processes. Finally this complex coupled platform was integrated in the period 2001-2030 under the A1B scenario of IPCC, and the impact of climate change on the physical system and on sediment transport was preliminarily evaluated.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.