Functionalized rare earth-doped nanoparticles for breast cancer nanodiagnostic using fluorescence and CT imaging.

BACKGROUND: Breast cancer is the second leading cause of cancer death among women and represents 14% of death in women around the world. The standard diagnosis method for breast tumor is mammography, which is often related with false-negative results leading to therapeutic delays and contributing indirectly to the development of metastasis. Therefore, the development of new tools that can detect breast cancer is an urgent need to reduce mortality in women. Here, we have developed Gd2O3:Eu3+ nanoparticles functionalized with folic acid (FA), for breast cancer detection. RESULTS: Gd2O3:Eu3+ nanoparticles were synthesized by sucrose assisted combustion synthesis and functionalized with FA using EDC-NHS coupling. The FA-conjugated Gd2O3:Eu3+ nanoparticles exhibit strong red emission at 613 nm with a quantum yield of ~ 35%. In vitro cytotoxicity studies demonstrated that the nanoparticles had a negligible cytotoxic effect on normal 293T and T-47D breast cancer cells. Cellular uptake analysis showed significantly higher internalization of FA-conjugated RE nanoparticles into T-47D cells (Folr hi ) compared to MDA-MB-231 breast cancer cells (Folr lo ). In vivo confocal and CT imaging studies indicated that FA-conjugated Gd2O3:Eu3+ nanoparticles accumulated more efficiently in T-47D tumor xenograft compared to the MDA-MB-231 tumor. Moreover, we found that FA-conjugated Gd2O3:Eu3+ nanoparticles were well tolerated at high doses (300 mg/kg) in CD1 mice after an intravenous injection. Thus, FA-conjugated Gd2O3:Eu3+ nanoparticles have great potential to detect breast cancer. CONCLUSIONS: Our findings provide significant evidence that could permit the future clinical application of FA-conjugated Gd2O3:Eu3+ nanoparticles alone or in combination with the current detection methods to increase its sensitivity and precision.

The geospatial relationship of geologic strata, geological fractures, and land use attained by a time-series aridity index in a semiarid region.

In a vast semiarid region of the Baja California Peninsula, remote sensing and GIS techniques were applied to moderate resolution images of Landsat 5 TM to explore the geospatial correlation among the grid aridity index (AI), shapefiles of geologic strata, land use, and geological fractures. A dataset of randomized sample points in a time-series of one hydrologic year along with vector file GIS delineated geologic fractures-including the area between their left/right parallel buffer lines-was used as mask analysis. MANOVA results were significant (p < 0.05) for geologic strata, land use, and basin. Overall results reveal the effects of soil texture on water retention on deeper soil horizons and the rate of vertical motion of rainwater. Despite the fact that geologic fractures underlie a large number of biotic communities, in both latitude and longitude gradients of the peninsula, no statistical significance was observed among the fractures themselves or the areas between their parallel buffer lines. One pulse rainfall event was documented by the AI grid maps enabling a robust vegetative response in early summer to an abnormal amount of rain provided by tropical storm Julio. AI grids appear to be useful for characterizing an ecosystem's dynamism. New options are suggested for this research strategy by expanding the number of datasets and incorporating geographic exclusion areas.