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Current learning platforms generally have problems such as fragmented knowledge, redundant information, and chaotic learning routes, which cannot meet learners' autonomous learning requirements. This paper designs a learning path recommendation system based on knowledge graphs by using the characteristics of knowledge graphs to structurally represent subject knowledge. The system uses the node centrality and node weight to expand the knowledge graph system, which can better express the structural relationship among knowledge. It applies the particle swarm fusion algorithm of multiple rounds of iterative simulated annealing to achieve the recommendation of learning paths. Furthermore, the system feeds back the students' learning situation to the teachers. Teachers check and fill in the gaps according to the performance of the learners in the teaching activities. Aiming at the weak links of students' knowledge points, the particle swarm intelligence algorithm is used to recommend learning paths and learning resources to fill in the gaps in a targeted manner.

Bacterial infections, especially those caused by multidrug‐resistant pathogens, pose a significant threat to public health. Vaccines are a crucial tool in fighting these infections; however, no clinically available vaccine exists for the most common bacterial infections, such as those caused by Pseudomonas aeruginosa. Herein, a multiantigenic antibacterial nanovaccine (AuNP@HMV@SPs) is reported to combat P. aeruginosa infections. This nanovaccine utilizes the hybrid membrane vesicles (HMVs) created by fusing macrophage membrane vesicles (MMVs) with bacterial outer membrane vesicles (OMVs). The HMVs mitigate the toxic effects of both OMVs and bacterial secreted toxins (SP) adsorbed on the surface of MMVs, while preserving their stimulating properties. Gold nanoparticles (AuNPs) are utilized as adjuvant to enhance immune response without comprising safety. The nanovaccine AuNP@HMV@SPs induces robust humoral and cellular immune responses, leading to destruction of bacterial cells and neutralization of their secreted toxins. In murine models of septicemia and pneumonia caused by P. aeruginosa, AuNP@HMV@SPs exhibits superior prophylactic efficacy compared to control groups including OMVs, or MMVs@SPs and HMV@SPs, achieving 100% survival in septicemia and > 99.9% reduction in lung bacterial load in pneumonia. This study highlights AuNP@HMV@SPs as a safe and effective antibacterial nanovaccine, targeting both bacteria and their secreted toxins, and offers a promising platform for developing multiantigenic antibacterial vaccines against multidrug‐resistant pathogens. [ABSTRACT FROM AUTHOR]

Objective To explore the role of apoliprotein D (APOD) in the proliferation and migration of human dental pulp cells (DPCs) and to provide a basis for the use of APOD to promote pulp regeneration. Methods APOD ex⁃ pression in human dental pulp cells was inhibited by siRNA. The inhibition effect of APOD was confirmed by qPCR and Western blot. After APOD inhibition, colony formation experiments and CCK8 assays were employed to confirm the proliferation ability of dental pulp cells. Transwell assays were used to verify the cell migration ability after the inhibi⁃ tion of APOD expression. Results After inhibiting APOD expression, the colony formation rate in the si⁃apod group was reduced compared with the NC group, and the difference was statistically significant (t＝7.624, P＝0.002). The CCK8 experiment showed that the OD value in the si⁃apod group decreased at 3, 5 and 7 d compared with that in the NC group (P < 0.05). Transwell results showed that the number of cell divisions was 57.25 ± 4.03 in the si⁃apod group and 154.50 ± 8.39 in the NC group, and the difference was statistically significant (t＝10.45, P < 0.001). Conclusion Inhibition of APOD expression in dental pulp cells inhibits their proliferation and migration ability.