Therapy of human non-small-cell lung carcinoma using antibody targeting of a modified superantigen

Superantigens activate T-cells by linking the T-cell receptor to MHC class II on antigen-presenting cells, and novel reactivity can be introduced by fusing the superantigen to a targeting molecule. Thus, an antibody-targeted superantigen, which activates T cells to destroy tumour cells, might be used as cancer therapy. A suitable target is the 5T4 oncofetal antigen, which is expressed on many carcinomas. We constructed a fusion protein from a Fab of a monoclonal antibody recognizing the 5T4 antigen, and an engineered superantigen. The recombinant product 5T4FabV13-SEAD227A bound the 5T4 antigen expressed on the human non-small-cell lung cancer cell line Calu-1 with a Kd of 1.2 nM while the substitution of Asp227 to Ala in the superantigen moiety reduced binding activity to MHC class II. 5T4FabV13-SEAD227A tumour reactivity was demonstrated in 7/7 NSCLC samples by immunohistochemistry, while normal tissue reactivity was low to moderate. 5T4FabV13-SEAD227A induced significant T-cell-dependent in vitro killing of sensitive 5T4 bearing Calu-1 cells, with maximum lysis at 10−10M, while the capacity to lyse MHC class II expressing cells was approximately 1000 times less effective. Immunotherapy of 5T4FabV13-SEAD227A against human NSCLC was investigated in SCID mice reconstituted with human peripheral blood mononuclear cells. Mice carrying intreperitoneally growing Calu-1 cells showed significant reduction in tumour mass and number after intravenous therapy with 5T4FabV13-SEAD227A. Thus, 5T4FabV13-SEAD227A has highly attractive properties for therapy of human NSCLC. © 2001 Cancer Research Campaign http://www.bjcancer.co

Global Soil Moisture Patterns Observed by Space Borne Microwave Radiometers and Scatterometers

Within the scope of the upcoming launch of a new water related satellite mission (SMOS) a global evaluation study was performed on two available global soil moisture products. ERS scatterometer surface wetness data was compared to AMSR-E soil moisture data. This study pointed out a strong similarity between both products in sparse to moderate vegetated regions with an average correlation coefficient of 0.83. Low correlations were found in densely vegetated areas and deserts. The low values in the vegetated regions can be explained by the limited soil moisture retrieval capabilities over dense vegetation covers. Soil emission is attenuated by the canopy and tends to saturate the microwave signal with increasing vegetation density, resulting in a decreased sensor sensitivity to soil moisture variations. It is expected that the new low frequency satellite mission (SMOS) will obtain soil moisture products with a higher quality in these regions. The low correlations in the desert regions are likely due to volume scattering or to the dielectric dynamics within the soil. The volume scattering in dry soils causes a higher backscatter under very dry conditions than under conditions when the sub-surface soil layers are somewhat wet. In addition, at low moisture levels the dielectric constant has a reduced sensitivity in response to changes in the soil moisture content. At a global scale the spatial correspondence of both products is high and both products clearly distinguish similar regions with high seasonal and inter annual variations. Based on the global analyses we concluded that the quality of both products was comparable and in the sparse to moderate vegetated regions both products may be beneficial for large scale validation of SMOS soil moisture. Some limitations of the studied products are different, pointing to significant potential for combining both products into one superior soil moisture data set. © The Author(s) 2008

Spatial distribution of surface temperature and land cover: A study concerning Sardinia, Italy

Land surface temperature (LST) is a key climate variable that has been studied mainly at the urban scale and in the context of urban heat islands. By analyzing the connection between LST and land covers, this study shows the potential of LST to analyze the relation between urbanization and heating phenomena at the regional level. Land cover data, drawn from Copernicus, and LST, retrieved from Landsat 8 satellite images, are analyzed through a methodology that couples GIS and regression analysis. By looking at the Italian island of Sardinia as a case study, this research shows that urbanization and the spatial dynamics of heating phenomena are closely connected, and that intensively farmed areas behave quite similarly to urban areas, whereas forests are the most effective land covers in mitigating LST, followed by areas covered with Mediterranean shrubs. This leads to key policy recommendations that decision makers could implement to mitigate LST at the regional scale and that can, in principle, be exported to regions with similar climate and land covers. The significance of this study can be summed up in a novel approach to analyze the relationship between LST and land covers that uses freely available spatial data and therefore can easily be replicated in other regional contexts to derive appropriate policy recommendations