miR-20a-5p inhibits proliferation of lung cancer A549 cells by down-regulating HOXB13 / 南方医科大学学报

OBJECTIVE@#To investigate the molecular mechanism by which miR-20a-5p regulates HOXB13 gene expression and inhibits lung cancer cell proliferation.@*METHODS@#The expression levels of HOXB13 mRNA and protein in lung cancer A549 cells transfected with HOXB13 overexpression plasmid or HOXB13 siRNA were detected with real-time fluorescence quantitative PCR (qRT-PCR) and Western blotting. CCK-8 and EdU assays were used to examine the effect of modulation of HOXB13 expression on cell proliferation. We screened possible binding miRNAs of HOXB13 by bioinformatics analysis. In A549 cells transfected with miR-20a-5p mimic or miR-20a-5p inhibitor, the expression level of miR-20a-5p was detected by qRT-PCR and the protein expression of HOXB13 was determined with Western blotting. CCK-8 and EdU assays were used to assess the effect of miR-20a-5p overexpression on the proliferation of A549 cells. miR-20a-5p mimic and HOXB13 overexpression plasmids were co-transfected into A549 cells, and the changes in cell proliferation were evaluated with CCK-8 and EdU assays.@*RESULTS@#HOXB13 overexpression obviously promoted the proliferation of A549 cells (P < 0.05). miR-20a-5p was identified as the potential binding miRNA of HOXB13. Overexpression of miR-20a-5p in A549 cells significantly decreased the expression of HOXB13 protein (P < 0.05), while interference of miR-20a-5p obviously increased HOXB13 expression (P < 0.05). The results of cell proliferation experiment showed that miR-20a-5p and HOXB13 had opposite effects on cell proliferation, and the cells overexpressing both miR-20a-5p and HOXB13 showed a lower proliferation activity than the cells overexpressing HOXB13 but higher than the cells overexpressing miR-20a-5p alone (P < 0.05).@*CONCLUSION@#miR-20a-5p inhibits proliferation of lung cancer cells by down-regulating the expression of HOXB13.

Establishment and verification of preeclampsia risk assessment model / 中华疾病控制杂志

Objective To analyze the risk factors affecting pre-eclampsia, to establish a pre-eclampsia risk assessment model, and to assess the risk of pre-eclampsia early. Methods A face-to-face questionnaire survey was conducted for all women who gave birth in the Department of Obstetrics, the First Hospital of Shanxi Medical University from March 2012 to September 2016. A total of 10 319 qualified questionnaires were collected to exclude 9 623 cases of other hypertensive diseases related to pregnancy. A total of 70% of the subjects were randomly selected as training samples to analyze the influencing factors of pre-eclampsia, and a Logistic regression model was established. The remaining 30% of the objects are used as test samples to verify the effect of the model. Results Logistic regression model was established with training samples. Logit P=-2.517-0.696×Pre-pregnancy lean +0.200 ×Pre-pregnancy overweight +0.944×Pre-pregnancy obesity -1.995×Residential in city -0.409×Folic acid supplemented before pregnancy +1.323×Twin and multiple pregnancy +1.708× History of previous pregnancy hypertension. Homer-Lemeshow test P=0.377. Model AUC=0.767 (95%CI:0.747-0.786, P<0.001). Using the test sample to verify the model, the model sensitivity was 81.68%, the specificity was 75.05%, the positive likelihood ratio was 3.27, and the negative likelihood ratio was 0.24. The test sample model AUC = 0.771 (95%CI=0.763-0.790,P<0.001). Conclusion This study establishes a simple and effective pre-eclampsia risk assessment model with controllable factors. The model has good fit and sensitivity and specificity.