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Gene therapy may provide a cure for hemophilia and overcome the limitations of protein replacement therapy. Increasing the potency of gene transfer vectors may allow to improve their therapeutic index, as lower doses can be administered to achieve therapeutic benefit, reducing toxicity of in vivo administration. Here we generated codon-usage optimized and hyper-functional factor IX (FIX) transgenes carrying a R338L amino acid substitution, previously associated with clotting hyperactivity and thrombophilia. We delivered these transgenes to hemophilia B mice by hepatocyte-targeted integration-competent and -defective lentiviral vectors. The hyper-functional FIX transgenes increased FIX activity reconstituted in the plasma without detectable adverse effects, allowing correction of the disease phenotype at lower vector doses and resulting in improved hemostasis in vivo. The combined effect of codon optimization with the hyper-activating FIX-R338L mutation resulted in a robust 15-fold gain in potency and therefore provides a promising strategy to improve the efficacy, feasibility and safety of hemophilia gene therapy.

International audience; La deuxième conférence internationale Iasi (Infrared Atmospheric Sounding Interferometer), qui s'est tenue à Sévrier (Haute-Savoie) du 24 au 29 janvier 2010, a rassemblé 150 scientifiques de tous horizons pour faire le point sur l'instrument Iasi, le traitement des données, les résultats de son exploitation, trois ans après sa mise en service, et pour envisager les suites du programme. Dans cet article, on présente l'instrument monté sur les trois satellites Metop d'Eumetsat qui se succéderont jusqu'en 2020.On illustre succinctement les extraordinaires performances de cet instrument devenu référence pour l'interétalonnage de capteurs infrarouges. Après un rappel sur l'organisation du traitement des données, les perspectives à court et moyen termes sont mises en lumière. La partie principale traite des résultats les plus récents exposés à la conférence dans les différents domaines d'application de Iasi : la prévision numérique, l'étude de la composition atmosphérique, les applications opérationnelles de la chimie atmosphérique et le suivi du changement climatique. Le dernier paragraphe est consacré au futur avec les évolutions attendues des produits et les perspectives de l'après Iasi avec le sondeur infrarouge sur Météosat troisième génération et le sondeur Iasi nouvelle génération.

Ground-based Fourier Transform Spectrometer observations in the infrared, acquired during the Italian phase of the EAQUATE campaign, have been considered in this study and compared to calculations. Synthetic spectral radiances have been obtained using the 2000 and 2004 releases and the 2006 upgrade of HITRAN spectral databases. It has been found that synthetic radiance computations fit the data quite well, even though the goodness of the fit depends on the spectral database. Differences in the spectral residual behaviour appear to be mostly localized in the long-wave side of the Earth emission spectrum, i.e. in the spectral region 520-610 cm(-1), which is dominated by the water vapour rotational absorption band. In this range, computation performed with the latest updates provides almost the same results as those of HITRAN2000, while HITRAN2004 shows a mixed behaviour - better than the first two in a large region of the spectral range, but worse at very few specific wave numbers. Overall, HITRAN2006 yields the highest consistency with the observations. No sensitive differences appear at higher wave numbers.

Direct solar irradiance and IR atmospheric radiance have been measured during different measurements campaigns, conducted in three mountain sites in Italy, far from anthropogenic sources. Direct solar irradiance has been measured by a high resolution (1.5 nm) AVANTES radiometer, working in the spectral range 400 nm-900 nm, while down welling IR sky radiance measurements has been measured by an MR100 BOMEM Fourier Transform Spectrometer covering the spectral ranges 500 cm-1-5000 cm-1 and 1 cm-1 of resolution. At least two Radiosonde launches per day furnished temperature and water vapour profiles. The instruments were located on a mobile laboratory, specifically projected to host them. The parameters obtained from direct solar irradiance are Aerosol Optical Depth, Angstrom parameters and Aerosol Size Distributions retrieval, while from IR data water vapour and temperature profiles have been retrieved. Different orographic characteristics and different air-masses circulation on the measurement sites influenced Aerosol Optical Depth values and variation. Infrared radiances inversion allows the water vapour content retrieval and a correlation between aerosol effective radii and water vapour content has been looked for.

The physical forward/inverse scheme phi-IASI has been applied to the retrieval of atmospheric vertical profiles of temperature, water vapour and ozone by inverting high spectral infrared observations recorded by the NAST-I Fourier Transform Spectrometer. For the retrieval exercise we have used clear-sky spectra recorded over the sea surface on the night of 9-10 September 2004, during the Italian phase of the EAQUATE field campaign. During the campaign NAST-I flew on board the NASA Proteus aircraft at an altitude of 15 km. Retrievals have been compared to radiosonde observations, profiles from the ECMWF analysis and AIRS level 2 products. While providing a basis for the validation of the phi-IASI inversion scheme, the retrieval exercise has also demonstrated (i) the NAST-I ability to accurately detect H2O fine-scale vertical features, and (ii) the good quality of the temperature and water vapour profiles from the ECMWF analysis.

In this work a soft computing approach, based on a neural network methodology, is presented, aimed to retrieve atmospheric parameters of meteorological interest such as temperature, water vapour and ozone profiles from high resolution infrared sensor spectra. Specific neural network has been developed on basis of the specifications of the Infrared Atmospheric Sounding Interferometer (IASI). The performance of the neural network based inversion methodology has been evaluated by considering an inversion case in which test cases are retrieved. Given the nature of available data, a preliminary elaboration of spectra by means of principal component analysis has made, and an online adaptive pruning of the network during training is performed. The adaptive pruning is based on a bi-local technique and allows to optimize the network size and architecture.

It is shown that IMG (interferometric monitoring of greenhouse gases) spectra recorded over African and Arabian deserts clearly contain the fingerprint of quartz-rich soils. We illustrate how this spectral signature can be exploited to devise a suitable cloud-detection scheme to identify which infrared observations are affected by clouds. As a by-product, the scheme also allows one to identify the most likely underlying emitting surface type and provides a suitable first guess for the surface emissivity to be used, e.g., for the retrieval of geophysical parameters from high-spectral-resolution infrared radiance from space. The analysis has focused on African deserts because of their intrinsic relevance to numerical weather prediction and Earth's climate. Desert areas, like oceans, are poorly covered by the world meteorological radiosonde network and therefore are geographical regions for which the global coverage capability of satellites soundings is expected to provide better initializations for numerical weather prediction than are now available. Application of the cloud-detection scheme to IMG spectra has been considered, which demonstrates the good performance of the method.

An original algorithm is illustrated for the inversion of geophysical parameters from spectral observations in the thermal band. The algorithm exploits the Hotelling transform and projects the linearized version of the radiative transfer equation in a space of reduced dimensionality. The inversion is performed in this latter space, which speeds up the computations and makes the method attractive for real-time retrieval from high spectral resolution infrared observations.

A crucial task in modern genetic medicine is the understanding of complex genetic diseases. The main complicating features are that a combination of genetic and environmental risk factors is involved, and the phenotype of interest may be complex. Traditional statistical techniques based on lod-scores fail when the disease is no longer monogenic and the underlying disease transmission model is not defined. Different kinds of association tests have been proved to be an appropriate and powerful statistical tool to detect a candidate gene for a complex disorder. However, statistical techniques able to investigate direct and indirect influences among phenotypes, genotypes and environmental risk factors, are required to analyse the association structure of complex diseases. In this paper we propose graphical models as a natural tool to analyse the multifactorial structure of complex genetic diseases. An application of this model to primary hypertension data set is illustrated.