Axl is a tyrosine kinase receptor and although it is expressed in malignancy such as leukemia, colon cancer, melanoma, endometrial, prostate and thyroid cancers, its role has not been completely elucidated yet and appears to be complex. The ligand of Axl, Gas6, is a 75 KDa multimodular protein with an N-terminal gamma-carboxy-glutamic acid that is essential for binding. Gas6 has a mitogenic effect on several normal cell lines. The receptor Axl is expressed in primary prostate carcinoma and in prostate cancer cell lines as such as PC-3 and DU 145. We demonstrated a mitogenic activity determined by Gas6/Axl interaction in these undifferentiated metastatic human prostatic cancer cell lines. This effect is proportional to Axl expression, not due to inhibition of apoptosis, and induces AKT and MAPK phosphorylation. However, only MEK phosphorylation seems to be essential for growth signaling. Our results suggest that Axl overexpression and activation by Gas6 could be involved in progression of prostate neoplastic disease.

During the last few years the photovoltaic energy market has seen an outstanding growth. According to the new Directive on renewable energies of the European Commission (2009/28/EC), the European Union should reach a 20% share of the total energy consumption from renewable sources by 2020. The national overall targets impose for Italy a 17% renewable share: in case of failure the gap would be filled by importation of renewable energy from non-UE countries. The abitious national targets and thus the continuously increasing interest on renewable fuels, require simple but reliable methods for the energy potential assessment over large-scale territories. Considering roof-top integrated PV systems, the assessment of the PV energy potential passes through the evaluation of the roof surface area available for installations. In the present paper a methodology for estimating the PV solar energy potential is presented, together with its application to Piedmont Region (North-Western Italy). The roof area suitable for solar applications, is calculated through the analysis of available GIS data. The solar radiation maps are taken from the database of the Joint Research Centre of the European Commission. Different solar energy exploitation scenarios are proposed with the relative perspective results and confidence interval. Further developments and applications of the presented methodology are finally discussed.

The ongoing rush of the UE member states to the 2020 overall targets on the national renewable energy share (see Directive 2009/28/EC), is propelling the large exploitation of the solar resource for the electricity production. However, the incentives to the large employment of PV solar modules and the relative perspective profits, are often cause of massive ground-mounted installations. These kind of installations are obviously the preferred solution by the investors for their high economic yields, but their social impact should be also considered. Over the Piedmont Region for instance, the large proliferation of PV farms is jeopardizing wide agricultural terrains and turistic areas, therefore the policy of the actual administration is to encourage the use of integrated systems in place of massive installations. For these reasons, an effort to demonstrate that the distributed residential generation can play a primary role in the market is mandatory. In our previous work "Scalable methodology for the photovoltaic solar energy potential assessment based on available roof surface area: application to Piedmont Region (Italy)", we already proposed a basic methodology for the evaluation of the roof-top PV system potential. However, despite the total roof surface has been computed on a given cartographical dataset, the real roof surface available for PV installations has been evaluated through the assumption of representative roofing typologies and empirical coefficients found via visual inspection of satellite images. In order to overcome this arbitrariness and refine our methodology, in the present paper we present a brand new algorithm to compute the available roof surface, based on the systematical analysis and processing of aerial georeferenced images (ortho-images). The algorithm, fully developed in MATLAB ® , accounts for shadow, roof surface available (bright and not), roof features (i.e. chimneys or walls) and azimuthal angle of the eventual installation. Here we apply the algorithm to the whole city of Turin, and process more than 60,000 buildings. The results achieved are finally compared with our previous work and the updated PV potential assessment is consequently discussed.

This new method more accurately computes the initial conditions, resulting in a useful stratification of patients which improves the quantitative evaluation and treatment of hyperosmolar coma.

Gas6 protein is possibly involved in human diseases, but a validated plasma assay is lacking. So, we developed a sandwich enzyme-linked immunosorbent assay (ELISA) method using commercially available reagents. An appropriate plasma-based matrix was prepared to optimize the assay. The ELISA method showed inter- and intra-assay coefficients of variation lower than 15%. Recoveries all fell within 15% of expected values. Plasma Gas6 concentration in 61 healthy donors was 20.3+/-3.8 ng/mL. Our assay meets FDA requirements for precision and accuracy for the validation of bioanalytical methods and it is suitable for research or diagnostic purposes.