The characteristic of stress and load transmission in the semilunar cartilage model was studied with three-dimensional photoelastic method based on the principle of biomechanics. In addition to the liner function, the menisci may also provide with significant load-bearing capacity, The bearing capacity of external semilunar cartilage is larger than that of the internal one. Besides, the capsule and other soft tissue of the knee joint also participate in the load transmission. This study suggests that application of three-dimensional photoelastic method for the semilunar cartilage research may be a useful mean and with widespread prospect.

Objective:To establish a speech recognition system based on adaptive technology and to evaluate its value in pathological grossing processes.Methods:A total of 600 tissue specimens were collected at the Zhejiang Provincial People's Hospital affiliated to Hangzhou Medical College between October 1, 2020 and December 31, 2020. A speech recognition system based on adaptive technology was used in the pathological grossing processes, and the pathological examination reports were generated and extracted.Results:The speech recognition system based on adaptive technology showed a good recognition rate (overall recognition rate = 77.87%) and helped achieve rapid input and output of pathological examination data.Conclusions:The speech recognition system can reduce the labor costs, improve the work efficiency of pathologists and increase the quality of medical services, which may be valuable for building next-generation smart hospitals.

Objective To explore the effective constituents from Sonchus arvensis L. and the potential mechanism in treating sepsis by network pharmacology. Methods The chemical ingredients reported in the literature were taken as research objects and Swiss Target Prediction database was used to collect the identify the potential targets of those ingredients. The GeneCards, OMIM and TTD databases were applied to screen the sepsis related molecular targets. The cross targets were obtained and used to construct the active ingredient-disease target network. In addition, the targets were also imported into STRING database to construct a PPI network. Finally, GO and KEGG enrichment analysis were performed on the target genes to predict the mechanism via DAVID database. Results 71 components from S. arvensis L. were obtained, which corresponded to 579 potential drug targets. There were 3437 related targets of sepsis. S. arvensis L. and sepsis shared 272 common targets. The results showed that 1366 terms were found by GO function enrichment, including 245 molecular functions (MF), 1002 biological processes (BP), and 119 cell composition (CC), The KEGG enrichment analysis suggested that 166 signaling pathways were involved. Conclusion The study revealed that TNF, AKT1, IL-6, IL-1β, TP53 and some other targets might be affected by potentially active ingredients of S arvensis L. such as linoleic acid, linolenic acid and oleic acid to regulate the expression of steroids, sphingolipids hormones as well as epidermal factors and chemokines in treating sepsis.