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Due to overexpression of glycyrrhetinic acid (GA) receptor in liver cancer cells, glycyrrhetinic acid modified recombinant human serum albumin (rHSA) nanoparticles for targeting liver tumor cells may result in increased therapeutic efficacy and decreased adverse effects of cancer therapy. In this study, doxorubicin (DOX) loaded and glycyrrhetinic acid modified recombinant human serum albumin nanoparticles (DOX/GA-rHSA NPs) were prepared for targeting therapy for liver cancer. GA was covalently coupled to recombinant human serum albumin nanoparticles, which could efficiently deliver DOX into liver cancer cells. The resultant GA-rHSA NPs exhibited uniform spherical shape and high stability in plasma with fixed negative charge (∼-25 mV) and a size about 170 nm. DOX was loaded into GA-rHSA NPs with a maximal encapsulation efficiency of 75.8%. Moreover, the targeted NPs (DOX/GA-rHSA NPs) showed increased cytotoxic activity in liver tumor cells compared to the nontargeted NPs (DOX/rHSA NPs, DOX loaded recombinant human serum albumin nanoparticles without GA conjugating). The targeted NPs exhibited higher cellular uptake in a GA receptor-positive liver cancer cell line than nontargeted NPs as measured by both flow cytometry and confocal laser scanning microscopy. Biodistribution experiments showed that DOX/GA-rHSA NPs exhibited a much higher level of tumor accumulation than nontargeted NPs at 1 h after injection in hepatoma-bearing Balb/c mice. Therefore, the DOX/GA-rHSA NPs could be considered as an efficient nanoplatform for targeting drug delivery system for liver cancer.

Timeliness of steel distribution centers can effectively ensure the smooth progress of ship construction, but the carbon emissions of vehicles in the distribution process are also a major source of pollution. Therefore, when considering the common cost of vehicle distribution, taking the carbon emissions of vehicles into account, this paper establishes a Mixed Integer Linear Programming (MILP) model called green vehicle routing and scheduling problem with simultaneous pickups and deliveries and time windows (GVRSP-SPDTW). An intelligent water drop algorithm is designed and improved, and compared with the genetic algorithm and traditional intelligent water drop algorithm. The applicability of the improved intelligent water drop algorithm is proven. Finally, it is applied to a specific example to prove that the improved intelligent water drop algorithm can effectively reduce the cost of such problems, thereby reducing the carbon emissions of vehicles in the distribution process, achieving the goals of reducing environmental pollution and green shipbuilding.

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