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The treatment of drug-resistant cancer is a clinical challenge, hence screening for novel anticancer drugs is critically important. In the present study we investigated the anti-tumor potential of three plant-derived flavone compounds 3-hydroxy flavone (3-HF), 6-hydroxy flavone (6-HF) and 7-hydroxy flavone (7-HF) either alone or combined with silica nanoparticles (3-HF+NP, 6-HF+NP and 7-HF+NP) on the human breast carcinoma cell lines MDA-MB-231 and MCF-7, as well as on non-tumorigenic normal breast epithelial cells (MCF-10). The IC50 values of these flavone compounds loaded with NP (flavones+NP) in these cell lines were determined to be 1.5µg/ml without affecting the viability of normal MCF-10 cells. Additionally, we found that combination of flavones with NP significantly induced apoptosis in MCF-7 and MDA-MB-231 cancer cells using annexin-V/PI double staining followed by flow cytometry analysis. Furthermore, flavones+NP increased the expression of cytochrome C and caspase 9 mediating growth arrest of these cancer cells. Most importantly, combination of flavones with NP significantly abolished the expression of ATF-3, which in turn is responsible for the proliferation and invasion of bone metastatic breast cancer cells. Our data revealed the potential therapeutic effects of these flavones in fighting breast cancer cells and provided the first insight concerning the underlying molecular mechanisms.

Securing medical images are a very essential process in medical image authentication. Medical image watermarking is a very popular tool to achieve this goal. In this paper, an extremely fast, highly accurate, and robust algorithm is proposed for watermarking both gray-level and color medical images. In the proposed method, a scrambled binary watermark is embedded in the host medical image. Simplified exact kernels are used to compute the moments of the polar complex exponential transform (PCET) for the host gray-level images and the moments of the quaternion PCET for the host color images without approximation errors. The stability of the computed moments enables us to use higher order moments in a perfect reconstruction of the watermarked medical images. The accurate moment invariant to rotation, scaling, and translation ensures the robustness of the proposed watermarking algorithm against geometric attacks. Performed experiments clearly show very high visual imperceptibility and robustness to different levels of geometric distortions and common signal processing attacks. The implementation of parallel multi-core CPU and GPU result in a tremendous reduction of the overall watermarking times. For a color image of size 256 × 256, the watermarking time is accelerated by 20× and 11× using a GPU and a CPU with 16 cores, respectively.