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Skeleton labeled (13)C-carbon nanoparticles for the imaging and quantification in tumor drainage lymph nodes.

Carbon nanoparticles (CNPs) have been widely used in tumor drainage lymph node (TDLN) imaging, drug delivery, photothermal therapy, and so on. However, during the theranostic applications, the accumulation efficiency of CNPs in target organs is unknown yet, which largely hinders the extension of CNPs into clinical uses. Herein, we prepared skeleton-labeled (13)C-CNPs that had identical properties to commercial CNPs suspension injection (CNSI) for the imaging and quantification in TDLN. (13)C-CNPs were prepared by arc discharge method, followed by homogenization with polyvinylpyrrolidone. The size distribution and morphology of (13)C-CNPs were nearly the same as those of CNSI under transmission electron microscope. The hydrodynamic radii of both (13)C-CNPs and CNSI were similar, too. According to X-ray photoelectron spectroscopy and infrared spectroscopy analyses, the chemical compositions and chemical states of elements were also nearly identical for both labeled and commercial forms. The skeleton labeling of (13)C was reflected by the shift of G-band toward lower frequency in Raman spectra. (13)C-CNPs showed competitive performance in TDLN imaging, where the three lymph nodes (popliteal lymph node, common iliac artery lymph node, and paraaortic lymph node) were stained black upon the injection into the hind extremity of mice. The direct quantification of (13)C-CNPs indicated that 877 μg/g of (13)C-CNPs accumulated in the first station of TDLN (popliteal lymph node). The second station of TDLN (common iliac artery lymph node) had even higher accumulation level (1,062 μg/g), suggesting that (13)C-CNPs migrated efficiently along lymphatic vessel. The value decreased to 405 μg/g in the third station of TDLN (paraaortic lymph node). Therefore, the (13)C-CNPs provided quantitative approach to image and quantify CNSI in biological systems. The implication in biomedical applications and biosafety evaluations of CNSI is discussed.

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