Objective To explore the application effect of postural animation video instruction mode in elderly patients undergoing epidural anesthesia. Methods A total of 300 patients with epidural anesthesia were registered from January 2015 to February 2016. The patients were divided into trial group and control group with 150 cases each. The trial group was preoperatively interviewed by the postural anatomy video instruction mode, and the control group was only preoperatively interviewed by oral interpretation. The epidural anesthesia effect and anxiety between the two groups were compared. Results The difference of anesthesia posture and anatomical position, the average time of epidural puncture, the success rate of one puncture and the degree of anxiety before and after mission were 90.67% (136/150), (14.50 ± 10.20) s, (425.60 ± 78.30) s, 97.33% (146/150) and (21.65 ± 6.62) points respectively. The control group was 22.00%(33/150), (112.60 ± 60.80) s, (589.40 ± 90.70)s, 82.67%(124/150) and (6.65 ± 5.40) points respectively. There were significant differences between the two groups (χ2=8.79, t=13.54-19.88, all P < 0.01). Conclusions The postural anatomical video teaching mode can relieve anxiety, improve the degree of fit of epidural anesthesia and the success rate of puncture, shorten the time of posture, thus shorten the average time of epidural puncture, improve the quality of nursing in the operating room, work efficiency.

Intensive cancer treatment with drug combination is widely exploited in the clinic but suffers from inconsistent pharmacokinetics among different therapeutic agents.To overcome it,the emerging nanomedicine offers an unparalleled opportunity for encapsulating multiple drugs in a nano-carrier.Herein,a two-step super-assembled strategy was performed to unify the pharmacokinetics of a pep-tide and a small molecular compound.In this proof-of-concept study,the bioinformatics analysis firstly revealed the potential synergies towards hepatoma therapy for the associative inhibition of exportin 1(XPO1)and ataxia telangiectasia mutated-Rad3-related(ATR),and then a super-assembled nano-pill(gold nano drug carrier loaded AZD6738 and 97-110 amino acids of apoptin(AP)(AA@G))was con-structed through camouflaging AZD6738(ATR small-molecule inhibitor)-binding human serum albumin onto the AP-Au supramolecular nanoparticle.As expected,both in vitro and in vivo experiment results verified that the AA@G possessed extraordinary biocompatibility and enhanced therapeutic effect through inducing cell cycle arrest,promoting DNA damage and inhibiting DNA repair of hepatoma cell.This work not only provides a co-delivery strategy for intensive liver cancer treatment with the clinical translational potential,but develops a common approach to unify the pharmacokinetics of peptide and small-molecular compounds,thereby extending the scope of drugs for developing the advanced com-bination therapy.

【Objective】 To explore the key genes and potential therapeutic drugs for ER-negative breast cancer by bioinformatics. 【Methods】 The gene expression profile of breast cancer (GSE22219) was downloaded from the Gene Expression Omnibus (GEO). Principal components analysis (PCA) of GSE22219, and analyses of differentially expressed genes (DEGs) between the ER-negative and ER-positive subjects and Gene Ontology (GO) analysis were performed by R software. We analyzed The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Protein-Protein Interaction (PPI) network using STRING. The hub genes were identified using Cytoscape and analyzed using online programs. Drugbank analysis was used to find small molecular compounds as potential therapeutic agents to target the DEGs. 【Results】 We detect 69 DEGs and 8 hub genes between the ER-negative and ER-positive subjects. We found the most significant KEGG pathway of DEGs was aldosterone-regulated sodium reabsorption. The Gene Ontology (GO) analysis indicated that the most significantly enriched in prostate gland morphogenesis. Totally 21 small molecular compounds were identified as potential therapeutic agents for ER-negative breast cancer. 【Conclusion】 The bioinformatical analysis combined with drug database can help us find potential therapeutic agents to treat diseases. This method is a new paradigm which can guide future research on drugs.