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Bacterial infection and excess reactive oxygen species are key factors that lead to slow or substantially delayed wound healing. It is crucial to design and develop new nanomaterials with antibacterial and antioxidative capabilities for wound healing. Here, positively charged carbon dots (CDs) are rationally designed and synthesized from p-phenylenediamine and polyethyleneimine by a facile one-pot solvothermal method, which show good biocompatibility in in vitro cytotoxicity, hemolysis assays, and in vivo toxicity evaluation. The positively charged CDs show superior antimicrobial effect against Staphylococcus aureus(S. aureus) at very low concentrations, reducing the risk of wound infection. At the same time, CDs with surface defects and unpaired electrons can effectively scavenge excess free radicals to reduce oxidative stress damage, accelerate wound inflammation–proliferation transition, and promote wound healing. The mouse model of skin infection demonstrates that CDs can effectively promote the wound healing of skin infection without obvious side effects by simply dropping or spraying onto the wound. We believe that the prepared CDs have satisfactory biocompatibility, antioxidant capacity, and excellent antibacterial activity and have great application potential in wound healing.

This paper presents a 3D surface tracking algorithm which converts volumetric edge data to a surface model. Existing 3D model generation methods either threshold intensity data, which is sensitive to nonuniform illumination, or trace a surface from multiple layers of edge voxels, where a time-consuming heuristic search is used to extract boundaries. The huge search space prevents using it in 3D. Our algorithm directly constructs a surface model from edge voxels. A voxel is identified as being on the surface if its second derivative is negative and changes sign for neighbors in the gradient direction. By this definition, there can only exist one layer of surface voxels, and the tracking algorithm is simply a breadth-first search. Moreover, the definition of surface voxels is not sensitive to gradient directions, thus this approach is robust against noise. The test results on real data are also reported.