Transforming the Chemical Structure and Bio-Nano Activity of Doxorubicin by Ultrasound for Selective Killing of Cancer Cells.

Reconfiguring the structure and selectivity of existing chemotherapeutics represents an opportunity for developing novel tumor-selective drugs. Here, as a proof-of-concept, the use of high-frequency sound waves is demonstrated to transform the nonselective anthracycline doxorubicin into a tumor selective drug molecule. The transformed drug self-aggregates in water to form ≈200 nm nanodrugs without requiring organic solvents, chemical agents, or surfactants. The nanodrugs preferentially interact with lipid rafts in the mitochondria of cancer cells. The mitochondrial localization of the nanodrugs plays a key role in inducing reactive oxygen species mediated selective death of breast cancer, colorectal carcinoma, ovarian carcinoma, and drug-resistant cell lines. Only marginal cytotoxicity (80-100% cell viability) toward fibroblasts and cardiomyocytes is observed, even after administration of high doses of the nanodrug (25-40 µg mL-1 ). Penetration, cytotoxicity, and selectivity of the nanodrugs in tumor-mimicking tissues are validated by using a 3D coculture of cancer and healthy cells and 3D cell-collagen constructs in a perfusion bioreactor. The nanodrugs exhibit tropism for lung and limited accumulation in the liver and spleen, as suggested by in vivo biodistribution studies. The results highlight the potential of this approach to transform the structure and bioactivity of anticancer drugs and antibiotics bearing sono-active moieties.

Optical to Planar X-ray Mouse Image Mapping in Preclinical Nuclear Medicine Using Conditional Adversarial Networks.

In the current work, a pix2pix conditional generative adversarial network has been evaluated as a potential solution for generating adequately accurate synthesized morphological X-ray images by translating standard photographic images of mice. Such an approach will benefit 2D functional molecular imaging techniques, such as planar radioisotope and/or fluorescence/bioluminescence imaging, by providing high-resolution information for anatomical mapping, but not for diagnosis, using conventional photographic sensors. Planar functional imaging offers an efficient alternative to biodistribution ex vivo studies and/or 3D high-end molecular imaging systems since it can be effectively used to track new tracers and study the accumulation from zero point in time post-injection. The superimposition of functional information with an artificially produced X-ray image may enhance overall image information in such systems without added complexity and cost. The network has been trained in 700 input (photography)/ground truth (X-ray) paired mouse images and evaluated using a test dataset composed of 80 photographic images and 80 ground truth X-ray images. Performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and Fréchet inception distance (FID) were used to quantitatively evaluate the proposed approach in the acquired dataset.