In the battle of COVID-19 epidemic prevention and control in China, the "countermarching people" faced up to all difficulties and went forward one after another to the forefront of anti-epidemic. Many vivid figures and examples have aroused our feelings and thoughts on life. Under the background of this special period, medical colleges should take the COVID-19 prevention and control as an opportunity to enrich the contents of bioethics education, blend in patriotism education, social responsibility education, medical moral education, and life and death culture education. By strengthening the construction of teaching staff, attaching importance to the integration of teaching contents, optimizing teaching carriers, expanding practical activities and recommending online teaching resources, the teaching reform of bioethics education is explored in order to enhance the effectiveness and sustainability of bioethics education and moral education.

Incontinence-associated dermatitis is one of the common complications in critically ill patients.This paper reviews the research progress of risk prediction models for incontinence-associated dermatitis in critically ill patients,introduces and compares the characteristics and application effects of different risk prediction models.The purpose is to provide ideas for constructing a localized risk prediction model and provide evidence for medical staff to identify risk factors of incontinence-associated dermatitis at an early stage and take preventive measures.

Objective This study explored the association between air pollution exposure and birth weight by using the multilevel linear model,after controlling related meteorological factors and individual differences of both mothers and babies.Methods Women of childbearing age who were pregnant in Xi'an from 2010 to 2013,were selected as objects of this study.Multistage random sampling method was used to select 4 631 subjects followed by a self-designed questionnaire survey.Data related to quality of air and meteorology were gathered from routine monitoring system.Gestational age and date of birth,together with the average levels of air pollution were calculated for each trimester on each mother,and then the impact of air pollution on birth weight was assessed.A multilevel linear model was employed to investigate the association between the levels of exposure to air pollution by birth weight.Confounding factors were under control.We established three models in this study:Model 1 which involving the variable of air pollution exposure.Model 2 was adjusted for variables in Model 1 plus some other individual differences of both mother and baby.Model 3 was adjusted for variables in Model 2 plus meteorological factors.Results There were significant differences seen in birth weight within the subgroups of gender,gestational age,mother's reproductive age,maternal education,residential areas and family incomes (P＜0.01) of the infants.However,there was no difference found in Model 1 (P＞0.05).Data from Model 3 indicated that a decrease of 13.3 g (10.9 g in Model 2) and 6.6 g (5.9 g in Model 2) in birth weight that were associated with an increase of 10 μg/m3 in the average level of NO2 and PM10 during the second trimester;A decrease of 13.7 g (9.8 g in Model 2) in birth weight was associated with an increase of 10 μg/m3 in the average level of NO2 during the third trimester.Conclusion After controlling for meteorological factors,the levels of exposure to NO2 and PM10 during the second trimester and NO2 during the third trimester were negatively associated with birth weight.

Objective:To investigate the risk factors of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients in plain-sand areas and loess hilly areas of Gansu province.Methods:A total of 1 599 T2DM patients who participated in chronic disease and risk factors monitoring and basic public health service management were selected by multi-stage stratified random sampling method in the sandy plain areas and loess hilly areas of Gansu province. Questionnaire survey, physical measurement and laboratory tests were performed. Multivariate binary logistic model was used to analyze the influencing factors.Results:The prevalence of DKD was 22.1% (174/787) among T2DM patients in the sandy plain areas and 19.1%(155/812) in the loess hilly area, respectively. Hypertension ( OR=3.022), hyperuricemia ( OR=2.114) and HbA1c≥7%( OR=2.231) were the risk factors for DKD in the plain-sand areas, and the risk of DKD increased with age. In the loess hilly areas, female sex ( OR=0.379) was the protective factor for DKD; while duration of disease≥10 years ( OR=2.476), hyperuricemia ( OR=1.907), HbA1c≥7% ( OR=1.927) were the risk factors for DKD; and the risk of DKD increased with the increase of age, and decreased with the increase of per capita monthly income. Conclusions:The prevalence of DKD and its influencing factors are different between sandy plain areas and loess hilly areas in Gansu province. The prevention and treatment of hypertension should be given more attention in sandy plain areas. In addition, the screening of DKD should be conducted among T2DM patients, particularly for those with old age, hyperuricemia and HbA1c≥7% in both areas of the province.

AIM: The main chemical components of Yufang Fangji II (Hubei Fang) of COVID-19 were studied systematically and combined with network pharmacology to provide a reference for the study of its effective substances. METHODS: Ultra high-performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-TOF/MS) was applied to identify the absorbed components of the prescription in rat plasma. TCMSP database and Swiss Target Prediction data platform were used to predict the target of the identified blood components, and network visualization software Cytoscape 3.7.2 was used draw the association network diagram, and GO enrichment analysis and KEGG pathway enrichment analysis were conducted for the key targets. With the help of CB-Dock online molecular docking platform, the molecular docking of key targets and blood entering compounds was carried out, and the docking combination with good affinity value was displayed by ligplot software to verify the preventive effect of Yufang Fangji II on COVID-19. RESULTS: A total of 52 chemical components identified in the prescription, in which 13 components were absorbed in the rat plasma as the prototype, and they were from Astragalus membranaceus, Atractylodes macrocephala, Saposhnikoviae Radix, Lonicerae Japonicae Flos, and Citri Reticulatae Pericarpium, respectively. These compounds were recognized to act on 17 core targets, including mapk3, TNF and other targets related to inflammation, MPO and other targets related to oxidative stress, VEGFR, KDR and other targets related to vascular endothelium. The results of molecular docking showed that the absorbed components had good binding activity with the key targets. CONCLUSION: Compounds in Yufang Fangji II are involved in regulating inflammation, oxidative stress, vascular and cellular physiological activities, which have preventive effects on COVID-19 through regulating IL-17, PI3K Akt, MAPK and other pathways.