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Eucommia ulmoides (E. ulmoides) is a deciduous perennial tree belonging to the order Garryales, and is known as "living fossil" plant, along with ginkgo (Ginkgo biloba), metaspaca (Metasequoia glyptostroboides) and dove tree (Davidia involucrata Baill). However, the genetic diversity and population structure of E. ulmoides are still ambiguous nowdays. In this study, we re-sequenced the genomes of 12 E. ulmoides accessions from different major climatic geography regions in China to elucidate the genetic diversity, population structure and evolutionary pattern. By integration of phylogenetic analysis, principal component analysis and population structure analysis based on a number of high-quality SNPs, a total of 12 E. ulmoides accessions were clustered into four different groups. This result is consistent with their geographical location except for group samples from Shanghai and Hunan province. E. ulmoides accessions from Hunan province exhibited a closer genetic relationship with E. ulmoides accessions from Shanghai in China compared with other regions, which is also supported by the result of population structure analyses. Genetic diversity analysis further revealed that E. ulmoides samples in Shanghai and Hunan province were with higher genetic diversity than those in other regions in this study. In addition, we treated the E. ulmoides materials from Shanghai and Hunan province as group A, and the other materials from other places as group B, and then analyzed the evolutionary pattern of E. ulmoides. The result showed the significant differentiation (Fst = 0.1545) between group A and group B. Some candidate highly divergent genome regions were identified in group A by selective sweep analyses, and the function analysis of candidate genes in these regions showed that biological regulation processes could be correlated with the Eu-rubber biosynthesis. Notably, nine genes were identified from selective sweep regions. They were involved in the Eu-rubber biosynthesis and expressed in rubber containing tissues. The genetic diversity research and evolution model of E. ulmoides were preliminarily explored in this study, which laid the foundation for the protection of germplasm resources and the development and utilization of multipurpose germplasm resources in the future. [ABSTRACT FROM AUTHOR]

Background: Fertility awareness and menses prediction are important for improving fecundability and health management. Previous studies have used physiological parameters, such as basal body temperature (BBT) and heart rate (HR), to predict the fertile window and menses. However, their accuracy is far from satisfactory. Additionally, few researchers have examined irregular menstruators. Thus, we aimed to develop fertile window and menstruation prediction algorithms for both regular and irregular menstruators. Methods: This was a prospective observational cohort study conducted at the International Peace Maternity and Child Health Hospital in Shanghai, China. Participants were recruited from August 2020 to November 2020 and followed up for at least four menstrual cycles. Participants used an ear thermometer to assess BBT and wore the Huawei Band 5 to record HR. Ovarian ultrasound and serum hormone levels were used to determine the ovulation day. Menstruation was self-reported by women. We used linear mixed models to assess changes in physiological parameters and developed probability function estimation models to predict the fertile window and menses with machine learning. Results: We included data from 305 and 77 qualified cycles with confirmed ovulations from 89 regular menstruators and 25 irregular menstruators, respectively. For regular menstruators, BBT and HR were significantly higher during fertile phase than follicular phase and peaked in the luteal phase (all P < 0.001). The physiological parameters of irregular menstruators followed a similar trend. Based on BBT and HR, we developed algorithms that predicted the fertile window with an accuracy of 87.46%, sensitivity of 69.30%, specificity of 92.00%, and AUC of 0.8993 and menses with an accuracy of 89.60%, sensitivity of 70.70%, and specificity of 94.30%, and AUC of 0.7849 among regular menstruators. For irregular menstruators, the accuracy, sensitivity, specificity and AUC were 72.51%, 21.00%, 82.90%, and 0.5808 respectively, for fertile window prediction and 75.90%, 36.30%, 84.40%, and 0.6759 for menses prediction. Conclusions: By combining BBT and HR recorded by the Huawei Band 5, our algorithms achieved relatively ideal performance for predicting the fertile window and menses among regular menstruators. For irregular menstruators, the algorithms showed potential feasibility but still need further investigation. Trial registration: ChiCTR2000036556. Registered 24 August 2020. [ABSTRACT FROM AUTHOR]

Background: The association between isolated maternal hypothyroxinemia (IMH) during pregnancy and preterm birth (PTB), especially for subtypes of PTB, is unclear. This study aimed at determining the association between IMH diagnosed in early pregnancy and PTB, with further investigation into various subtypes of PTB. Methods: This study included 41,911 pregnant women (963 with IMH and 40,948 euthyroid women) who underwent first-trimester prenatal screening at the International Peace Maternity and Child Health Hospital (IPMCH) in Shanghai, China between January 2013 and December 2016. PTB was defined as birth before 37 weeks of gestation. PTB was further classified into three clinically relevant groups to investigate the clinical heterogeneity of PTB: (a) preterm birth with premature rupture of membranes (PROM-PTB); (b) spontaneous preterm birth with intact membranes (S-PTB); and (c) medically-induced preterm birth (MI-PTB). The overall and sex-specific effect of IMH on PTB and various subtypes of PTB were estimated by using logistic regression in crude and adjusted models. Results: Pregnant women with IMH had an increased risk of PTB (odds ratio [OR]: 1.32 [95% confidence interval; CI: 1.02–1.70], p = 0.03) compared with women with euthyroid function. The increased risk of PTB is mainly driven by S-PTB (OR: 1.57 [CI: 1.11–2.24], p = 0.01), while women with early pregnancy IMH had no statistically significant increased risk of PROM-PTB and MI-PTB. The effect of IMH on PTB was modified by fetal sex (p-values for interaction = 0.04). More prominent effects were observed in women carrying a female fetus, while no statistically significant effects were found in women carrying a male fetus. Conclusions: This study revealed that pregnant women with IMH in early pregnancy have a higher risk of PTB compared with euthyroid women. The effect of IMH on PTB is mainly driven by S-PTB and is modified by fetal sex. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the preventive effects of low-dose aspirin on the incidence of preeclampsia and pregnancy outcomes of women at high-risk for preeclampsia.Study Design: This prospective randomized clinical trial was conducted at the Obstetrics Department of The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, China. It analyzed data from 1105 high-risk women who were divided into the control group (placebo group) and the aspirin group (including three subgroups: 25 mg, 50 mg and 75 mg). The aspirin group in this study was instructed to take aspirin daily before bedtime beginning in the 12th week of pregnancy.Main Outcome Measures: The primary outcome is the occurrence of preeclampsia. The secondary outcomes included maternal and neonatal outcomes (such as premature delivery, FGR etc.), maternal serum biomarkers (including d-dimers, platelet aggregation rates, etc.) and uterine arterial blood flow resistance. The onset of preeclampsia and pregnancy outcomes were recorded after all participants delivered.Results: Low-dose aspirin significantly reduced the incidence of preeclampsia and early-onset preeclampsia. Aspirin also showed significant dose dependence in preeclampsia prevention. The results of Mantel-Haenszel trend test showed that there was a linear relationship between the dosage and the incidence of preeclampsia and early preeclampsia (P < 0.05). Pearson's results showed that the incidence of preeclampsia and early preeclampsia was negatively correlated with aspirin dosage. There was also a linear relationship between the dosage and the rates of postpartum hemorrhage, fetal growth restriction, premature births and cesarean section (P < 0.05). There was no evidence to suggest differences in the incidence of fetal distress, miscarriage and placental abruption among the four groups. The blood resistance S/D value of uterine artery in early pregnancy was the only independent factor affecting the efficacy of aspirin (OR = 1.405; 95 %CI,1.058-1.867; P = 0.019).Conclusion: Low-dose aspirin can prevent preeclampsia and early-preeclampsia. Its efficacy is dose-dependent. It can reduce the rates of postpartum hemorrhage, fetal growth restriction, premature births and cesarean section. The prophylactic effect of aspirin on preeclampsia seemed to be greater in patients with higher blood resistance S/D value of uterine artery during early pregnancy. [ABSTRACT FROM AUTHOR]

Despite the longstanding evidence on the effect of air pollutants on preterm birth (PTB), few studies have focused on its subtypes, including spontaneous preterm birth (sPTB) and medically indicated preterm birth (miPTB). Most studies evaluated only the short-term or long-term effects of particulate matter (PM) on PTB. Thus, we designed this study, based on a cohort of 179,385 women, to evaluate both short- and long-term effects of PM with diameters ≤2.5 μm and ≤10 μm (PM 2.5 and PM 10) on PTB, sPTB and miPTB in Shanghai. Generalized additive models (GAMs) were applied to evaluate short-term effects. Lagged effects were identified using different lag structures. Exposure-response correlation curves were plotted using GAMs after adjustment for confounders. ORs and 95% CIs were calculated using logistic regression to estimate the long-term effect after adjustment for confounders. There was 5.67%, 3.70% and 1.98% daily incidence of PTB, sPTB, and miPTB on average. Every 10 μg/m3 increase in PM 2.5 and PM 10 was positively associated with PTB and sPTB at lag 2 day. The exposure-response curves (lag 2 day) indicated a rapid increase in sPTB for PM 2.5 and a linear increase for PM 10 , in PTB for PM 2.5 and PM 10 at concentrations over 100 μg/m3. Regarding long-term exposure, positive associations were found between 10 μg/m3 increases in PM 2.5 and PM 10 in 3rd trimester and greater odds of sPTB (aOR: 1.042, 95% CI: 1.018–1.065, and 1.018, 95% CI:1.002–1.034), and during the 3 months before conception and miPTB (aOR: 1.023, 95% CI: 1.003–1.042, and 1.017, 95% CI: 1.000–1.036). Acute exposure to PM 2.5 and PM 10 at lag 2 day and chronic exposure in 3rd trimester was significantly associated with sPTB, while miPTB was related to chronic exposure during the 3 months before pregnancy. These findings indicate that susceptibility windows of PM exposure can be influenced by different underlying etiologies of PTB. [Display omitted] • Short-term exposure to PM 2.5 and PM 10 at lag 2 day was significantly associated with an increased risk of sPTB. • At lag 2 day, the exposure-response curve was steeper in sPTB for PM 2.5 and linear for PM 10 at concentrations > 100 μg/m3. • Long-term exposure to PM 2.5 and PM 10 in the third trimester during pregnancy adversely affected sPTB. • An increased risk of miPTB was related to long-term exposure to PM 2.5 and PM 10 during the 3 months before pregnancy. [ABSTRACT FROM AUTHOR]