Objective To study the influence of precision medicine-based health education on cognitive level of disease knowledge,anxiety and depression in patients with gestational diabetes.Methods Toally 84 cases of gestational diabetes patients in our hospital from September 2014 to December 2015 were divided into a study group and a control group according to the random number table,42 cases in each group.While the routine nursing intervention was done in the control group,the precision medicinebased health education program was carried out in the study group.The two groups were assessed using the cognitive questionnaire designed by our hospital.The self rating anxiety scale (SAS) and self rating depression scale (SDS) prepared by Zung were used to assess the levels of anxiety and depression in the two groups before the intervention and two weeks after the intervention.Results The cognitive level of disease knowledge in the study group after the intervention was statistically significantly higher than that of the control group (P＜0.05).Before the intervention,there were statistically insignificant differences in anxiety and depression between the two groups (P＞0.05),but after the intervention,the levels of anxiety and depression in the study group were significantly lower than those of the control group (P＜0.05).Conclusion The precision medicine-based health education is helpful for the patients with gestational diabetes to improve their diabetes-related knowledge and meanwhile it can relieve their anxiety and depression.

Objective To evaluate the application of multiple locus variable number tandem repeat analysis (MLVA, 15-locus set)for genotyping of Mycobacterium tuberculosis (MTB) strains of Beijing genotype. Methods Total 72 Beijing genotype MTB strains obtained from Beijing Thoracic Hospital were genotyped by MLVA (15-locus set). The results were compared with that generated from "gold standard"IS6110-RFLP. Results After genotyped by MLVA ( 15-locus set), 72 strains were grouped into 59 types,of which 53 were unique types. The Hunter-Gaston index (HGI) of MLVA ( 15-locus set) was 0.990. The loci QUB-11b, Mtub 21 and QUB-26 were polymorphic in selected Beijing genotype strains. Genotyping by IS6110-RFLP generated 69 types, of which 66 were unique types. The HGI of IS6110-RFLP was up to 0.999, and the MLVA (15-locus set) clustered strains could be further subdivided. Conclusion MLVA(15-locus set) showed better discriminatory ability in Beijing genotype MTB strains, though secondary typing of clustered strains by IS6110-RFLP is needed.

Objective:To study the effect of excessive torsion of the umbilical cord on fetal or neonatal outcomes.Methods:The observation group was selected from the puerperae who delivered in Beijing Obstetrics and Gynecology Hospital from July 2016 to June 2020 with excessive torsion of the umbilical cord. In the same period, the puerperae without excessive torsion of the umbilical cord were selected as the control group with a ratio of 1∶1. The general condition, mode of delivery, perinatal outcomes, and the effect of different umbilical coiling index (UCI) [twisted umbilical cord weeks/umbilical cord length (cm)] on fetal and neonatal outcomes were retrospectively analyzed between two groups.Results:Compared with the control group, the observation group (1 780 cases) had smaller neonatal gestational age [(37.9±3.2) weeks vs. (38.4±2.9) weeks], birth weight [(3 007±726) g vs. (3 354±616) g] and length [(48.5±4.3) cm vs. (49.6±4.1) cm], but higher incidence of fetal distress [34.9% (622/1 780) vs. 12.9% (230/1 780)], neonatal asphyxia [1.5% (26/1 780) vs. 0.7% (13/1 780)], and cord blood pH<7.20 [4.2% (75/1 780) vs. 2.8% (49/1 780)], the difference was statistically significant ( P<0.05). The UCI≥0.73 group had lower neonatal gestational age, birth weight and length, but higher incidence of cord blood pH<7.20 and neonatal asphyxia than the UCI<0.73 group, with statistically significant differences ( P<0.05). Conclusions:Excessive torsion of the umbilical cord increases the incidence of fetal hypoxia and neonatal asphyxia and has a significant effect on neonatal gestational age, birth weight and length. The higher the UCI, the greater the impact on fetus and neonate.

AIM: Through the Monte Carlo simulation to monitor the change of MIC in late-onset sepsis of gram-positive cocci in neonates, through the cumulative fraction of response to evaluate the changing trend of bacterial resistance in our center and analyze the possibility of inducing drug resistance of bacterial, to reduce the occurrence of bacterial drug resistance in clinical work. METHODS: This study retrospectively investigated the basic information, pathogen species and drug sensitivity results of neonatal late-onset sepsis of gram-positive cocci in Neonatal Intensive Care Units of Beijing Maternity Hospital from 2016 to 2019, and divided them into four groups by year. Crystal ball software was used to calculate the annual CFR of sensitive antibiotics (Vancomycin) against the gram-positive cocci by Monte Carlo simulation. RESULTS: From 2016 to 2019, there were 58 cases of late-onset sepsis caused by gram-positive cocci in neonates, and the number of pathogens detected each year showed no significant change, and there was no statistical difference in the affected population each year. Among them, the top three were 31 strains of Staphylococcus epidermidis (53.5%), 9 strains of Enterococcus faecium (15.5%), and 6 strains of Enterococcus faecalis (10.3%). Drug sensitivity tests showed that the resistance rates of Staphylococcus epidermidis, Enterococcus faecium and Enterococcus faecalis to Vancomycin and Linezolid were 0%. The CFR of Vancomycin against gram-positive cocci from 2016 to 2019 calculated by Monte Carlo simulation were 82%, 88.72%, 81.73% and 78.53%, respectively, which showed a downward trend. CONCLUSION: By using Monte Carlo simulation method, CFR can reflect the change of bacterial drug resistance with drug sensitivity test as the standard, and evaluate the current treatment plan, which should be paid attention to in clinical work.

BACKGROUND: Autophagy related genes (ARGs) regulate lysosomal degradation to induce autophagy, and are involved in the occurrence and development of a variety of cancers. The expression of ARGs in tumor tissues has a great prospect in predicting the survival of patients. The aim of this study was to construct a prognostic risk score model for lung adenocarcinoma (LUAD) based on ARGs. METHODS: 5,786 ARGs were obtained from GeneCards database. Gene expression profiles and clinical data of 395 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. All ARGs expression data were extracted, and The ARGs differentially expressed were identified by R software. Survival analysis of differentially expressed ARGs was performed to screen for ARGs with prognostic value, and functional enrichment analysis was performed. The least absolute selection operator (LASSO) regression and Cox regression model were used to construct a prognostic risk scoring model for ARGs. The receiver operating characteristic (ROC) curve was drawn to obtain the optimal cut-off value of risk score. According to the cut-off value, the patients were divided into high-risk group and low-risk group. The area under curve (AUC) and the Kaplan-Meier survival curve was plotted to evaluate the model performance, which was verified in external data sets. Finally, univariate and multivariate Cox regression analysis was applied to evaluate the independent prognostic value of the model, and its clinical relevance was analyzed. RESULTS: Survival analysis, Lasso regression and Cox regression analysis were used to construct a LUAD prognostic risk score model with five ARGs (ADAM12, CAMP, DKK1, STRIP2 and TFAP2A). The survival time of patients with low-risk score in this model was significantly better than that of patients with high-risk score (P<0.001). The model showed good prediction performance for LUAD in both the training set (AUCmax=0.78) and two external validation sets (AUCmax=0.88). Risk score was significantly associated with the prognosis of LUAD patients in univariate and multivariate Cox regression analyses, suggested that risk score could be a potential independent prognostic factor for LUAD. Correlation analysis of clinical characteristic showed that high risk score was closely associated with high T stage, high tumor stage and poor prognosis. CONCLUSIONS We constructed a LUAD risk score model consisting of five ARGs, which can provide a reference for predicting the prognosis of LUAD patients, and may be used in combination with tumor node metastasis (TNM) staging for prognosis prediction of LUAD patients in the future.