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The HA is present in almost all vertebrates and plays a critical role in tissue development and cell proliferation, it has been demonstrated to promote wound healing and involved in angiogenesis and inflammation. Also polynucleotydes (PN) have proved to promote the “in vitro” growth and activity of human fibroblasts and osteoblasts, to increase reparation on UVB damaged dermal fibroblasts and seems to promote proliferation of human pre-adipocytes. Several in vivo studies have demonstrated the PN effect also in vivo, inducing an increase of angiogenesis and healing process. In this paper we have evaluated the effect of a mixture of Polynucleotides (PN) and entire Hyaluronic Acid (HA) on cultured human fibroblasts by analyzing cell growth. Different mixture have been tested and it has been demonstrated that the presence of HA even at low concentration (1 mg/ml) determine an increase of PN activity up to 20%. Furthermore, the addition of HA 1 mg/ml to PN 100 μg/ml induces a cell growth rate comparable to that exerted by PN concentration of 12 μg/ml.
A data assimilation system combines all available information on the atmospheric state in a given time-window to produce an estimate of atmospheric conditions valid at a prescribed analysis time. Nowadays, increased computing power coupled with greater access to real-time asynoptic data is paving the way toward a new generation of high-resolution (i.e. on the order of 10 km) operational mesoscale analyses and forecasting systems. Moreover, better initial conditions are increasingly considered of the utmost importance for Numerical Weather Prediction (NWP) at the short range (0 - 12 h). This paper presents a general-purpose data assimilation system, which is coupled with the Regional Atmospheric Modelling System (RAMS) to give the analyses for: zonal and meridional wind components, temperature, relative humidity, and geopotential height. In order to show its potential, the data assimilation systems applied to produce analyses over Central Europe. For this application the background field is given by a short-range forecast (12 h) of the RAMS and analyses are produced by 2D-Var with 0.25? horizontal resolution. Results show the validity of the analyses because they are closer to the observations, consistently with the settings of the data assimilation system. To quantify the impact of improved initial conditions on the forecast, the analyses are then used as initial conditions of a short-range (6 h) forecast of the RAMS model. The results show that the RMSE is effectively reduced for the one- and two hours forecast, with some improvement for the three-hours forecast.
Several links between
continued fractions and classical and less classical constructions in dynamical
systems theory are presented and discussed.