Construction of multifunctional stimuli-responsive nanotherapeutics enabling improved intratumoral penetration of therapeutics and reversal of multiple-drug resistance (MDR) is potent to achieve effective cancer treatment. Herein, we report a general method to synthesize pH-dissociable calcium carbonate (CaCO3) hollow nanoparticles with amorphous CaCO3 as the template, gallic acid (GA) as the organic ligand, and ferrous ions as the metallic center via a one-pot coordination reaction. The obtained GA–Fe@CaCO3 exhibits high loading efficiencies to both oxidized cisplatin prodrug and doxorubicin, yielding drug loaded GA–Fe@CaCO3 nanotherapeutics featured in pH-responsive size shrinkage, drug release, and Fenton catalytic activity. Compared to nonresponsive GA–Fe@silica nanoparticles prepared with silica nanoparticles as the template, such GA–Fe@CaCO3 confers significantly improved intratumoral penetration capacity. Moreover, both types of drug-loaded GA–Fe@CaCO3 nanotherapeutics exhibit synergistic therapeutic efficacies to corresponding MDR cancer cells because of the GA–Fe mediated intracellular oxidative stress amplification that could reduce the efflux of engulfed drugs by impairing the mitochondrial-mediated production of adenosine triphosphate (ATP). As a result, it is found that the doxorubicin loaded GA–Fe@CaCO3 exhibits superior therapeutic effect towards doxorubicin-resistant 4T1 breast tumors via combined chemodynamic and chemo-therapies. This work highlights the preparation of pH-dissociable CaCO3-based nanotherapeutics to enable effective tumor penetration for enhanced treatment of drug-resistant tumors.
This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes. 相似文献
ZnO/Cu2S nanotube arrays are fabricated firstly by a facile and capping-agent-free method, and the photo-electrochemical performance has been studied systematically. The results show that ZnO/Cu2S nanotube arrays achieve enhanced photo-electrochemical water splitting performance and the photocurrent densities of ZnO/Cu2S are 7.9 times than that of ZnO at 0 V versus Ag/AgCl. The performance of the ZnO/Cu2S nanotube arrays can be adjusted by changing the amount of Cu2S microcrystals. The results confirm that the enhanced photo-electrochemical performance of ZnO/Cu2S is due to the significantly improved visible light absorption, effective separation of photo-induced carriers due to the well band energy match and the formed p-n junction between ZnO and Cu2S. 相似文献