ABSTRACT
OBJECTIVE: This study aimed to study the correlation between preeclampsia (PE) and lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1), and to examine the molecular mechanisms behind the development of PE. METHODS: 30 PE and 30 normal pregnant women placental samples were assessed the levels of NEAT1 and miR-217 by quantitative real-time PCR (qRT-PCR). The trophoblast cell line HTR8/SVneo was used for silencing NEAT1 or miR-217 inhibitor in the absence or presence of an inhibitor and H2O2. Cell counting Kit 8 (CCK-8), flow cytometry, and Transwell were used to detect cell proliferation, apoptosis, migration, and invasion. Luciferase reporter gene assay was utilized to verify the binding between miR-217 and Wnt family member 3 (Wnt3), and between the miR-217 and NEAT1. Proteins related to the Wnt/ß-catenin signaling pathway were detected using western blotting. RESULTS: The PE group exhibited a significantly downregulated expression of miR-217 and a significantly upregulated expression of NEAT1. NEAT1 targeted miR-217, and Wnt is a miR-217 target gene. siRNA-NEAT1 inhibited the apoptosis of trophoblast cells, but promoted their invasion, migration, and proliferation. MiR-217 inhibitor could partially reverse the effects of siRNA-NEAT1. The expression of the Wnt/ß-catenin signaling pathway-related proteins, WNT signaling pathway inhibitor 1 (DKK1), cyclin-D1 and ß-catenin, was significantly increased after siRNA-NEAT1. CONCLUSIONS: NEAT1 could reduce trophoblast cell invasion and migration by suppressing miR-217/Wnt signaling pathway, leading to PE.
ABSTRACT
BACKGROUND: We aimed to develop and validate a nomogram for effective prediction of vaginal birth after cesarean (VBAC) and guide future clinical application. METHODS: We retrospectively analyzed data from hospitalized pregnant women who underwent trial of labor after cesarean (TOLAC), at the Fujian Provincial Maternity and Children's Hospital, between October 2015 and October 2017. Briefly, we included singleton pregnant women, at a gestational age above 37 weeks who underwent a primary cesarean section, in the study. We then extracted their sociodemographic data and clinical characteristics, and randomly divided the samples into training and validation sets. We employed the least absolute shrinkage and selection operator (LASSO) regression to select variables and construct VBAC success rate in the training set. Thereafter, we validated the nomogram using the concordance index (C-index), decision curve analysis (DCA), and calibration curves. Finally, we adopted the Grobman's model to perform comparisons with published VBAC prediction models. RESULTS: Among the 708 pregnant women included according to inclusion criteria, 586 (82.77%) patients were successfully for VBAC. Multivariate logistic regression models revealed that maternal height (OR, 1.11; 95% CI, 1.04 to 1.19), maternal BMI at delivery (OR, 0.89; 95% CI, 0.79 to 1.00), fundal height (OR, 0.71; 95% CI, 0.58 to 0.88), cervix Bishop score (OR, 3.27; 95% CI, 2.49 to 4.45), maternal age at delivery (OR, 0.90; 95% CI, 0.82 to 0.98), gestational age (OR, 0.33; 95% CI, 0.17 to 0.62) and history of vaginal delivery (OR, 2.92; 95% CI, 1.42 to 6.48) were independently associated with successful VBAC. The constructed predictive model showed better discrimination than that from the Grobman's model in the validation series (c-index 0.906 VS 0.694, respectively). On the other hand, decision curve analysis revealed that the new model had better clinical net benefits than the Grobman's model. CONCLUSIONS: VBAC will aid in reducing the rate of cesarean sections in China. In clinical practice, the TOLAC prediction model will help improve VBAC's success rate, owing to its contribution to reducing secondary cesarean section.
