Objective To explore the feasibility,efficacy and safety of endoscopic submucosal dissection (ESD) for tumors originating from gastric muscularis propria.Methods A total of 20 patients with tumors originating from gastric muscularis propria confirmed by EUS and CT scan underwent ESD.Laparoscopic intervention was applied in 3 cases when difficulties in en bloc removal or perforation occurred.Results The mean ESD procedure time was 74.8 min (40-120 min),and the mean resected tumor size was 2.6 cm (1.5-3.5 cm).No severe complication occurred.Pathological findings were 17 cases of gastrointestinal stromal tumors and 3 cases of leiomyoma.Conclusion ESD is an effective method for treating the tumors originating from gastric muscularis propria,and laparoscopic intervention is necessary for en bloc resection in some cases.

Objective To evaluate the effect of different preparation processes on preparation of the glial cell line-derived neurotrophic factor(GDNF)loaded microspheres and observe the biological activity of GDNF.Methods With polylactide-co-glycolide(PLGA)as the coating material,the GDNF-loaded microspheres were prepared by using double emulsion(W1/O/W2).Two-factor factorial design variance analysis was done to analyze the effects of the composition proportion of lactic acid(LA)and glycolic acid(GA)in PLGA and the stirring speed of multiple emulsion on particle size,entrapment efficiency,burst release and in vitro release characteristics of the GDNF-loaded microspheres.PC-12 bioassay was employed to detect the biological activity of the released GDNF so as to determine the optimal preparation process.Results The composition proportion of PLGA could affect the microspheres'burst release(P ＜ 0.05),with no effect on particle size and entrapment efficiency.with the higher.With higher proportion of GA,the release speed of GDNF in the microspheres was increased.When the stirring speed of multiple emulsion was increased from 1 000 r/min to 3 000 r/min,the particle size of the microspheres was decrease significantly(P ＜ 0.01),the burst release was increased markedly(P ＜ 0.01)and the in vitro release rate was accelerated.The activity of GDNF in the microspheres could last for about 20 days at 37℃,which was 10 days longer than that of single GDNF.Conclusions Double emulsioncan prepare the GDNF-loaded microspheres with high entrapment efficiency and suitable in vitro release time.In the meantime,the microspheres can extend the validity of GDNF.

Objective To investigate the methylation status of E-cadherin(E-cad), p16, RASSF1A, DAPK and MGMT in histologically normal salivary gland tissues and provide reference for determination of the methylation status of salivary gland tumors.Methods Methylation of E-cad, p16, RASSF1A,DAPK and MGMT was analyzed using methylation-specific polymerase chain reaction ( MSP) .The results were compared with the methylation status of these genes in salivary adenoid cystic carcinoma ( ACC) tumor tissues in our previous studies and the association between promoter methylation of E-cad, p16, RASSF1A, DAPK, and MGMT on one hand and the patients′gender, age, smoking and types of gland on the other hand was also analyzed .Results Promoter methylation was detected in 8 of the 60 (13%) salivary glands, E-cad in 4(7%), p16 in 2(4%), RASSF1A in 2(4%), DAPK in 2 (4%), and MGMT in 1(2%).Compared with our previous results, there was a significantly lower methylation ratio in promoter methylation of E-cad(P<0.01), p16 (P<0.01), RASSF1A (P<0.01),and DAPK (P<0.01) in salivary gland tissues than in ACC tumor tissues.Conclusion Promoter methylation of E-cad, p16 and RASSF1A is a rare event in histologically normal salivary gland tissues .

Objective: To explore character strengths of college students who sought counseling, and its relationship with mental health. Methods: A total of 180 college students who sought counseling were investigated by using the short version of Character Strengths Questionnaire and the Symptom Checklist 90 (SCL-90) during March 2020 to October 2021. Results: The top five character strengths of college students who sought counseling were appreciation, authenticity, gratitude, humor, love of learning ( 8.39± 1.64, 7.82±1.74, 7.73±1.57, 7.29±1.81, 7.17±1.88); The bottom five character strengths were kindness, bravery, persistence, zest, leadership (5.59±1.75, 5.81±1.30, 5.86±1.72, 5.98±1.59, 6.06±1.60). Linear regression analysis found love, social intelligence and insight showed associations with different dimensions of mental health, with correlation coefficient of each regression equation between -0.12 and 0.16, and the coefficient of determination between 0.05 and 0.19 ( P <0.01). Love had a negativeassociation with all factors of SCL- 90 ( β=-0.314--0.159, P <0.05), which could explain 3.3%-12.5% of the variation of each factor. Social intelligence had a negative association with obsessive compulsive, interpersonal sensitivity and anxiety ( β=-0.200--0.150, P <0.05), which can explain 1.6%-3.2% of the variation. Insight had a positive association with somatization, hostility and paranoia ( β=0.168-0.279, P <0.05), which can explain 2.3%-3.8% of the variation. Conclusion The lack and excess of character strengths is associated with mental health problems. Therefore, it would be more effective to help counseling cases build an appropriate and balanced character in the context of a strengths based approach.

Shortcomings have been inherited in the traditional influenza early warning system, often expressed through the scope, accuracy on prediction and real-time performance of the monitor related programs. With the new round of scientific and technological revolution and the increasingly maturity of modern information system, related technology on influenza early warning has become the focus of research in this field, based on big data analysis technology. Using the traditional influenza surveillance and early warning system as reference, this paper summarizes the progress of influenza early warning research, based on the Internet, influencing factors, time and space trends, and risk assessment etc., to summarize the trends on the advantages, shortcomings and future development of big data, used in the early warning system on influenza.