ObjectiveTo assess the associations of gestational weight gain (GWG) in early and late pregnancy with subsequent risks of adverse pregnancy outcomes in Chinese women.DesignProspective cohort study.SettingShanghai, China.ParticipantsWe studied 2630 nulliparous singleton pregnant women with complete data on weight gain in early (≤17 weeks of gestation) and late (>17 weeks) pregnancy in the Shanghai Birth Cohort.MethodsGWG was standardised into z-scores by gestational age and categorised as low (z-score <−1), normal (−1 to +1) and high (>1). The adjusted relative risks (aRRs) and 95%CIs were estimated through log-binomial regression models. Interaction effects between GWG and some other adjustment factors were tested, further stratified analyses were performed separately where interaction terms were significant.Outcome measuresAdverse maternal and neonatal outcomes.ResultsIndependent from GWG in late pregnancy, higher GWG in early pregnancy was associated with higher risks of gestational diabetes mellitus (aRR: 1.66; 95% CI: 1.11 to 2.48), caesarean section (aRR: 1.21; 95% CI: 1.05 to 1.39) and prolonged hospitalisation (aRR: 1.56; 95% CI: 1.03 to 2.38). Higher GWG in late pregnancy was independently associated with higher risks of caesarean section (aRR: 1.24; 95% CI: 1.09 to 1.41), large for gestational age (aRR: 2.01; 95% CI: 1.50 to 2.7) and macrosomia (aRR: 1.90; 95% CI: 1.30 to 2.78). In addition, the risk of gestational hypertension increased significantly with increased total GWG (aRR: 1.78; 95% CI: 1.14 to 2.76). The effects of GWG in late pregnancy on maternal and neonatal outcomes were significantly different between the women bearing a female and the women bearing male fetus.ConclusionThe GWG associations with adverse pregnancy outcomes differ at early and late pregnancy, and there may be effect modification by fetal sex in the association of GWG in late pregnancy with some pregnancy outcomes.

Preeclampsia (PE) affects 3 to 5% of pregnant women worldwide and is associated with fetal and maternal morbidity and mortality. Although a complete understanding of PE remains elusive, it has been widely accepted that a dysfunction of the placenta plays a key role in the pathogenesis of PE. In this study, we investigated the role of excessive placental autophagy during PE pathogenesis and explored whether esomeprazole ameliorates PE by inhibiting the autophagy in the placenta. The PE cellular model was established by treating the cells’ L-NAME and hypoxia. The PE mice model was established by L-NAME administration and was confirmed by the increased systolic blood pressure (SBP) and urinary protein detected. The autophagy and key proteins were detected in human placental tissue, in cells, and in the mice model by Western blot and immunofluorescence staining. Results showed that excessive autophagy could be detected in human PE placental tissue, in the PE cellular model, and in the PE mice model. Hypoxia induces autophagy by activating AMPKα and inhibiting mTOR in vivo and in vitro. Esomeprazole inhibits L‐NAME-induced autophagy in mice by inhibiting AMPKα and activating mTOR. In conclusion, this study demonstrates that the excessive autophagy induced by the SIRT1/AMPKα-mTOR pathway plays a significant role in the pathogenesis of PE. However, esomeprazole treatment inhibits AMPKα but activates mTOR, resulting in the inhibition of autophagy in the placenta and, therefore, mitigates PE symptoms.

Pre-eclampsia (PE) is closely associated with perinatal morbidity and mortality and we want to investigate tetramethylpyrazine (TMP)'s effects on PE. Pregnant Sprague-Dawley rats were randomly divided into five groups: normal pregnant (PC), PE, PE+TMP 20 mg/kg, PE+TMP 40 mg/kg, and PE+TMP 60 mg/kg group. The PE rat model was established via L-NAME treatment. Systolic blood pressures (SBP) and urinary protein concentration were detected via the tail-cuff method and CBB kit, respectively. mRNA levels of key genes were analyzed via quantitative PCR and protein levels of key genes were measured by ELISA or western blot. TMP decreased SBP and urinary protein concentration of PE rats. TMP inhibited L-NAME-induced decrease in pups alive ratio, pups weight, and the ratio of pups/placenta weight and reversed L-NAME induced changes in placental histology, whereas it had little effect on placental weight. Urinary nephrin and podocin expressions were enhanced and serum placental growth factor level was decreased in PE rats, whereas TMP inhibited the above phenomena. TMP suppressed L-NAME-induced sFlt-1 upregulation in serums and kidneys of PE rats, whereas it downregulated IL-6 and MCP-1 expression in PE rats' serums, placentas and kidneys. TMP also suppressed the increase in placental sFlt-1 and vascular endothelial growth factor level caused by L-NAME. In addition, TMP inhibited CHOP and GRP78 expressions and decreased the ratio of p-elF2α/elF2α in PE rats. TMP attenuated the consequences of NO inhibition in pregnant rats. K E Y W O R D SER stress, hypertension, pre-eclampsia, proteinuria, tetramethylpyrazine

Objective We aimed to evaluate the prognostic value of C-C motif chemokine receptor type 5 (CCR5) expression level for patients with ovarian cancer and to establish a radiomics model that can predict CCR5 expression level using The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) database. Methods A total of 343 cases of ovarian cancer from the TCGA were used for the gene-based prognostic analysis. Fifty seven cases had preoperative computed tomography (CT) images stored in TCIA with genomic data in TCGA were used for radiomics feature extraction and model construction. 89 cases with both TCGA and TCIA clinical data were used for radiomics model evaluation. After feature extraction, a radiomics signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. A prognostic scoring system incorporating radiomics signature based on CCR5 expression level and clinicopathologic risk factors was proposed for survival prediction. Results CCR5 was identified as a differentially expressed prognosis-related gene in tumor and normal sample, which were involved in the regulation of immune response and tumor invasion and metastasis. Four optimal radiomics features were selected to predict overall survival. The performance of the radiomics model for predicting the CCR5 expression level with 10-fold cross- validation achieved Area Under Curve (AUCs) of 0.770 and of 0.726, respectively, in the training and validation sets. A predictive nomogram was generated based on the total risk score of each patient, the AUCs of the time-dependent receiver operating characteristic (ROC) curve of the model was 0.8, 0.673 and 0.792 for 1-year, 3-year and 5-year, respectively. Along with clinical features, important imaging biomarkers could improve the overall survival accuracy of the prediction model. Conclusion The expression levels of CCR5 can affect the prognosis of patients with ovarian cancer. CT-based radiomics could serve as a new tool for prognosis prediction.