Path planning is a fundamental issue in the aspect of robot navigation. As robots work in 3D environments, it is meaningful to study 3D path planning. To solve general problems of easily falling into local optimum and long search times in 3D path planning based on the ant colony algorithm, we proposed an improved the pheromone update and a heuristic function by introducing a safety value. We also designed two methods to calculate safety values. Concerning the path search, we designed a search mode combining the plane and visual fields and limited the search range of the robot. With regard to the deadlock problem, we adopted a 3D deadlock-free mechanism to enable ants to get out of the predicaments. With respect to simulations, we used a number of 3D terrains to carry out simulations and set different starting and end points in each terrain under the same external settings. According to the results of the improved ant colony algorithm and the basic ant colony algorithm, paths planned by the improved ant colony algorithm can effectively avoid obstacles, and their trajectories are smoother than that of the basic ant colony algorithm. The shortest path length is reduced by 8.164%, on average, compared with the results of the basic ant colony algorithm. We also compared the results of two methods for calculating safety values under the same terrain and external settings. Results show that by calculating the safety value in the environmental modeling stage in advance, and invoking the safety value directly in the path planning stage, the average running time is reduced by 91.56%, compared with calculating the safety value while path planning.

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Sepsis is an intense immune response to infection that contributes to the pathophysiological process of acute lung injury (ALI). Inflammation and oxidative stress serve an important role in the development of ALI. Leonurine (LEO) is a natural phenolic alkaloid extracted from Leonurus cardiaca , which possesses anti-inflammatory and antioxidative properties. Therefore, the aim of the present study was to explore the effect of LEO on sepsis-induced ALI and to investigate its underlying mechanism. MTT and Cell Counting Kit-8 assays were performed to measure cell viability. The levels of reactive oxygen species, lactate dehydrogenase and malondialdehyde, as well as the activity of superoxidase dismutase, were quantified using commercial assay kits. The expression levels of specific inflammatory cytokines were measured by using ELISA. In addition, western blotting was employed to assess the expression levels of cytokines, including TNF-α, IL-6, nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1. The findings demonstrated that LEO increased the viability of lipopolysaccharide (LPS)-stimulated BEAS-2B human lung epithelial cells in a dose-dependent manner. Additionally, LEO suppressed LPS-induced oxidative stress and inflammatory cytokine release in BEAS-2B cells. Treatment with Nrf2 inhibitor reversed the effects of LEO treatment on LPS-induced oxidative stress and inflammatory response in BEAS-2B cells. Taken together, the data of the present study indicated that LEO attenuated LPS-induced ALI through the inhibition of oxidative stress and inflammation regulated by the Nrf2 signaling pathway. Therefore, LEO may be a novel and effective agent for the prevention of sepsis-induced ALI.

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