Risk Factors for Hypoglycemia Among Neonates: A Prospective Cohort Study Among Pregnant People With Gestational Diabetes Mellitus.

OBJECTIVE: Neonatal hypoglycemia (NH) is the most frequent complication in neonates born to pregnant people with gestational diabetes mellitus (GDM) and an important cause of brain damage and death of neonates. We explored the risk factors for NH in neonates of pregnant people with GDM. METHODS: A prospective cohort study was conducted involving 322 pregnant people with GDM at the Guangzhou Women and Children's Medical Centre. Maternal sociodemographic, clinical, and biochemical data, as well as general characteristics of neonates, were collected to analyze their associations with NH in neonates of pregnant people with GDM. RESULTS: The incidence of NH among neonates of pregnant people with GDM was 19.57% (63/322). After adjustment for confounders, the factors significantly associated with an increased risk of NH were cesarean delivery (relative risk [RR] = 3.44; 95% confidence interval [CI], 1.83-6.45), red blood cell (RBC) count (RR = 2.19; 95% CI, 1.22-3.96), and 1-hour postprandial glucose (RR = 2.35; 95% CI, 1.23-4.46) during pregnancy, whereas later gestational age (RR = 0.58; 95% CI, 0.42-0.80) and multiparity (RR = 0.32; 95% CI, 0.16-0.66) were associated with a reduced risk of NH. CONCLUSION: Cesarean delivery, maternal 1-hour glucose of the oral glucose tolerance test, and increased RBC count of pregnant people with GDM are independent risk factors for NH, while later gestational age and multiparity are protective factors.

SERPINA5 may promote the development of preeclampsia by disruption of the uPA/uPAR pathway.

Preeclampsia (PE) is the leading cause of maternal and fetal morbidity or mortality but lacks reliable methods for early diagnosis. In a previous study, serum SERPINA5 levels were higher in women with PE before the clinical manifestation of the disease. This study aimed to evaluate the efficacy of SERPINA5 in predicting PE and investigate its role in trophoblast cell biology. A multicenter, 2-stage observational case-control study was performed to develop and validate an early predictive PE model based on SERPINA5, maternal characteristics, and inflammatory factors. To further understand the relationship between SERPINA5 and PE, SERPINA5 was overexpressed or knocked down in extravillous trophoblast cells (EVT) and a pregnant rat model. After development and initial validation, a model that combined SERPINA5 and inflammatory factors had a high predictive ability for PE before 20 weeks gestation with an AUC of 0.90 (95% CI 0.83-0.96). It also demonstrated that SERPINA5 inhibited primary EVT cell invasion by disrupting the urokinase-type plasminogen activator/urokinase-type plasminogen activator receptor (uPA/uPAR) pathway, in turn, is involved in the development of PE. In vivo experiments also proved that overexpression of SERPINA5 induced a PE-like syndrome (hypertension and proteinuria) in pregnant rats. Therefore, serum SERPINA5 is a promising early biomarker of PE, suggesting that it may be involved in placental development through its action on the uPA/uPAR system prior to the clinical manifestation of PE.

Tacrolimus pharmacokinetics in pediatric nephrotic syndrome: A combination of population pharmacokinetic modelling and machine learning approaches to improve individual prediction.

Background and Aim: Tacrolimus (TAC) is a first-line immunosuppressant for the treatment of refractory nephrotic syndrome (RNS), but the pharmacokinetics of TAC varies widely among individuals, and there is still no accurate model to predict the pharmacokinetics of TAC in RNS. Therefore, this study aimed to combine population pharmacokinetic (PPK) model and machine learning algorithms to develop a simple and accurate prediction model for TAC. Methods: 139 children with RNS from August 2013 to December 2018 were included, and blood samples of TAC trough and partial peak concentrations were collected. The blood concentration of TAC was determined by enzyme immunoassay; CYP3A5 was genotyped by polymerase chain reaction-restriction fragment length polymorphism method; MYH9, LAMB2, ACTN4 and other genotypes were determined by MALDI-TOF MS method; PPK model was established by nonlinear mixed-effects method. Based on this, six machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Extra-Trees, Gradient Boosting Decision Tree (GBDT), Adaptive boosting (AdaBoost) and Lasso, were used to establish the machine learning model of TAC clearance. Results: A one-compartment model of first-order absorption and elimination adequately described the pharmacokinetics of TAC. Age, co-administration of Wuzhi capsules, CYP3A5 *3/*3 genotype and CTLA4 rs4553808 genotype were significantly affecting the clearance of TAC. Among the six machine learning models, the Lasso algorithm model performed the best (R2 = 0.42). Conclusion: For the first time, a clearance prediction model of TAC in pediatric patients with RNS was established using PPK combined with machine learning, by which the individual clearance of TAC can be predicted more accurately, and the initial dose of administration can be optimized to achieve the goal of individualized treatment.

Mediating effects of gut microbiota in the associations of air pollutants exposure with adverse pregnancy outcomes.

BACKGROUND: The aim of this study was to investigate alterations in gut microbiota after exposure to air pollutants during pregnancy and its mediation effect in inducing adverse pregnancy outcomes (APOs). METHODS: Participants (n = 916) were enrolled between 2017 and 2018 from a prospective cohort study of pregnant women in Guangzhou, China. The relative abundance of fecal microbiota was profiled using 16SrRNA V4 region sequencing. Exposure to air pollutants in each trimester of pregnancy was assessed using measurements from the nearest monitoring station. APOs including pre-term birth (PTB), post-term birth (POTB), low birth weight (LBW), macrosomia fetus (MF), birth defects (BDs), pathological cesarean section (PCS) and postpartum hemorrhage (PPH)) were determined by referring to reliable clinical records and diagnostic criteria. Univariate analysis, multivariate analysis and mediation analysis were performed to estimate the association among air pollutants, gut microbiota and APOs. RESULTS: Air pollutants exposure during pregnancy was significantly correlated with the alterations in the gut microbiota, and increased risks of various APOs by 1.07-1.36-fold (P < 0.05). The mediation analyses indicated that alterations in Eggerthella, Phascolarctobacterium and Clostridium partially mediated the effects of air pollutants exposure (PM2.5, PM10, O3, NO2 and SO2) on APOs. The relative abundance of f_Micrococcaceae explained 11.39%, 64.90% and 54.80% of the correlation between SO2, PM2.5, PM10 and POTB, respectively; whereas g_Rothia explained 11.97%, 67.80% and 54.50%, respectively. g_Parabacteroides explained 53.0% of the correlation between PM2.5 and PTB. CONCLUSIONS: Increased air pollutants exposure during pregnancy may induce adverse pregnancy outcomes via alteration of the gut microbiota.

The potential risk factors of placenta increta and the role of octamethylcyclotetrasiloxane.

BACKGROUND: The study aimed to investigate the potential risk factors for the placenta accreta spectrum (PAS), determine the predictive value of a diagnostic model, and evaluate the effects of octamethylcyclotetrasiloxane (OMCTS) on trophoblast proliferation and migration. METHODS: This case-control study included 244 pregnant women with PAS and 327 normal pregnant women who visited Guangzhou Women and Children's Medical Centre, China, from January 2014 to December 2017. Blood was collected from 42 women with PAS and 77 controls, and plasma specimens were analyzed by gas chromatography-time-of-flight mass spectrometry. In addition, the proliferation and migration of trophoblast cells were examined after treatment with OMCTS. RESULTS: We found an association between the risk of PAS and clinical factors related to fasting blood glucose levels (BS0, OR = 5.78), as well as factors related to endometrial injury [history of cesarean section (OR = 179.59), uterine scarring (OR = 68.37), and history of abortion (OR = 5.66)]. Equally important, pregnant women with PAS had significantly higher plasma OMCTS concentrations than controls. In vitro, we found that OMCTS could promote the proliferation and migration of HTR8/SVneo cells. The model of combining clinical factors and OMCTS had a good performance in PAS prediction (AUC = 0.97, 95% CI 0.78-0.93). CONCLUSIONS: The early diagnosis of PAS in pregnant women requires assessing risk factors, metabolic status, and BS0 levels before 20 weeks of gestation. OMCTS may be related to the development of PAS by promoting trophoblast cell proliferation and migration.

Non-Invasive Detection of Fetal Vascular Endothelial Function in Gestational Diabetes Mellitus.

Objectives: Endothelial dysfunction in the fetuses of women with gestational diabetes mellitus (GDM) is associated with their subsequent cardiovascular events. Prenatal assessment of endothelial function in fetuses exposed to intrauterine hyperglycemic environment remains challenging. The aim of this study was to assess the fetal vascular endothelial function in GDM patients using color M-mode derived aortic propagation velocity (APV) and evaluate the correlation of APV with endothelial function biomarkers. Methods: This observational cross-sectional study included 31 gestational diabetic mothers and 30 healthy pregnant mothers from August 2019 to January 2020. Clinical data were compared between the groups. Fetal APV was measured using color M-mode echocardiography at late gestation. Concentrations of endothelial biomarkers including von Willebrand Factor (vWF), vascular endothelial-cadherin and endothelin-1 in umbilical cord serum were assessed. Measurements between diabetic group and controls were compared. Results: vWF was the only endothelial functional marker that differed between the two groups. Fetuses in the GDM group had significantly lower APV levels and higher vWF levels compared with the healthy controls (P < 0.05). There was a moderate but significant correlation between APV and vWF (r =-0.58, P < 0.001). There were no associations between APV and ventricular wall thickness or umbilical artery pulsatility index. Conclusions: Color M-mode propagation velocity of aorta is a non-invasive, practical method that correlates well with GDM and fetal endothelial function. This novel metric could contribute to recognizing early vascular functional alterations and hence represents a potential strategy for early risk factor surveillance and risk modification.

Serum complement proteomics reveal biomarkers for hypertension disorder of pregnancy and the potential role of Clusterin.

INTRODUCTION: Hypertension disorder of pregnancy (HDP) is one of the leading causes of maternal and foetal illness. The aim of the current study was to identify and verify novel serum markers for HDP. METHODS: A label-free LC-MS/MS method was used to establish the serum proteomic profiles of 12 pre-HDP (before clinical diagnosis of HDP) pregnancies and verify prioritized candidates in the verification set of 48 pre-HDP pregnancies. These biomarkers were revalidated by ELISA in an independent cohort of 88 pre-HDP pregnancies. Subsequently, the candidate biomarkers were histologically analysed by immunohistochemistry, and function was evaluated in TEV-1 cells. RESULTS: We identified 33 proteins with significantly increased abundance and 14 with decreased abundance (peptide FDR ≤ 1%, P < 0.05). Complement was one of the top enriched components in the pre-HDP group compared with the control group. Three complement factors (CLU, CFHR5, and CRP) were significantly increased in the three sets, of which CLU was a critical factor for the development of HDP (OR = 1.22, P < 0.001). When these three factors and body weight were combined, the AUC was 0.74, with a sensitivity of 0.67 and specificity of 0.68 for HDP prediction compared with normal pregnancy. In addition, inflammation-induced CLU could inhibit the invasion of TEV-1 cells. CONCLUSIONS: Complement proteins may play an essential role in the occurrence of HDP by acting on trophoblast cells. CLU may be a high-risk factor for HDP, and the models combining candidates show reasonable screening efficiency of HDP in the first half of pregnancy.

Circulating expression of Hsa_circRNA_102893 contributes to early gestational diabetes mellitus detection.

Due to a poor availability of reliable biomarkers, detecting gestational diabetes mellitus (GDM) in early pregnancy remains a challenge. Novel biomarkers like Circular RNAs (circRNAs) may be a promising diagnostic tool. The aim of this study was (a) to identify circRNAs deregulated in GDM and (b) evaluate the potential of circRNAs in detecting GDM. The circRNAs expression profiling in 6 paired women (with and without GDM) was measured by microarray. The levels of five most relevant circRNAs were validated in 12 paired participants by qRT-PCR. To verify the reproducibility of qRT-PCR, significantly differential expressed circRNA levels were confirmed in 18 paired participants. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value. The areas under ROC curves of hsa_circRNA_102893 were 0.806 (95% CI 0.594-0.937) and 0.741 (0.568-0.872) in training set and test set, respectively. Circulating circRNAs reflect the presence of GDM. Hsa_circRNA_102893 may be a potential novel and stable noninvasive biomarker for detecting GDM in early pregnancy.

Systematic analysis of gut microbiota in pregnant women and its correlations with individual heterogeneity.

The woman's gut microbiota during pregnancy may support nutrient acquisition, is associated with diseases, and has been linked to infant health. However, there is limited information on gut microbial characteristics and dependence in pregnant women. In this study, we provide a comprehensive overview of the gut microbial characteristics of 1479 pregnant women using 16S rRNA gene sequencing of fecal samples. We identify a core microbiota of pregnant women, which displays a similar overall structure to that of age-matched nonpregnant women. Our data show that the gestational age-associated variation in the gut microbiota, from the ninth week of gestation to antepartum, is relatively limited. Building upon rich metadata, we reveal a set of exogenous and intrinsic host factors that are highly correlated with the variation in gut microbial community composition and function. These microbiota covariates are concentrated in basic host properties (e.g., age and residency status) and blood clinical parameters, suggesting that individual heterogeneity is the major force shaping the gut microbiome during pregnancy. Moreover, we identify microbial and functional markers that are associated with age, pre-pregnancy body mass index, residency status, and pre-pregnancy and gestational diseases. The gut microbiota during pregnancy is also different between women with high or low gestational weight gain. Our study demonstrates the structure, gestational age-associated variation, and associations with host factors of the gut microbiota during pregnancy and strengthens the understanding of microbe-host interactions. The results from this study offer new materials and prospects for gut microbiome research in clinical and diagnostic fields.

Early and Accurate Prediction of Clinical Response to Methotrexate Treatment in Juvenile Idiopathic Arthritis Using Machine Learning.

Background and Aims: Accurately predicting the response to methotrexate (MTX) in juvenile idiopathic arthritis (JIA) patients before administration is the key point to improve the treatment outcome. However, no simple and reliable prediction model has been identified. Here, we aimed to develop and validate predictive models for the MTX response to JIA using machine learning based on electronic medical record (EMR) before and after administering MTX. Materials and Methods: Data of 362 JIA patients with MTX mono-therapy were retrospectively collected from EMR between January 2008 and October 2018. DAS44/ESR-3 simplified standard was used to evaluate the MTX response. Extreme gradient boosting (XGBoost), support vector machine (SVM), random forest (RF), and logistic regression (LR) algorithms were applied to develop and validate models with 5-fold cross-validation on the randomly split training and test set. Data of 13 patients additionally collected were used for external validation. Results: The XGBoost screened out the optimal 10 pre-administration features and 6 mix-variables. The XGBoost established the best model based on the 10 pre-administration variables. The performances were accuracy 91.78%, sensitivity 90.70%, specificity 93.33%, AUC 97.00%, respectively. Similarly, the XGBoost developed a better model based on the 6 mix-variables, whose performances were accuracy 94.52%, sensitivity 95.35%, specificity 93.33%, AUC 99.00%, respectively. Conclusion: Based on common EMR data, we developed two MTX response predictive models with excellent performance in JIA using machine learning. These models can predict the MTX efficacy early and accurately, which provides powerful decision support for doctors to make or adjust therapeutic scheme before or after treatment.

Expression of galectin-3 and apoptosis in placental villi from patients with missed abortion during early pregnancy.

The success of a pregnancy relies on moderate trophoblast apoptosis. If the 'inhibition-induction' balance of apoptosis is broken, a pathological pregnancy may occur. Galectin-3 has an important role in numerous biological processes, including tumor cell apoptosis. However, the association between galectin-3 and missed abortion (MA) has remained elusive. In the present study, the mRNA and protein expression levels of galectin-3 in placental villi, and the apoptotic index of placental cells from patients with MA were assessed and compared with those in a normal spontaneous abortion group. The present study investigated the function of galectin-3 in the process of MA and the possible association between placental apoptosis and galectin-3 expression in MA patients. Furthermore, the role of galetin-3 in patients with MA at different times (<4 and >4 weeks) was explored. The present study provided a potential mechanism of MA from a perspective of apoptosis and also provided potential therapeutic approaches to prevent MA.

Risk for Gestational Diabetes Mellitus and Adverse Birth Outcomes in Chinese Women with Polycystic Ovary Syndrome.

Objective. To examine the association of polycystic ovary syndrome (PCOS) in early pregnancy with gestational diabetes mellitus (GDM) and adverse birth outcomes. Methods. In this retrospective cohort study including 2389 pregnant women, the medical records of 352 women diagnosed with PCOS were evaluated. Outcomes included GDM, preterm birth, low birth weight, macrosomia, and being small and large for gestational age. Multivariable logistic regression models were used to examine the association of the risk for GDM and adverse birth outcomes with PCOS after adjusting for confounders. Results. Women previously diagnosed with PCOS had a higher risk of GDM (adjusted odds ratio [OR] 1.55, 95% confidence interval [CI]: 1.14-2.09). A strong association was seen between PCOS and preterm birth (adjusted OR 1.69, 95% CI: 1.08-2.67). On stratified analysis, the adjusted OR for GDM among women with PCOS undergoing assisted reproductive technology was 1.44 (95% CI: 1.03-1.92) and among women with PCOS who conceived spontaneously was 1.60 (1.18-2.15). No increased risk for other adverse birth outcomes was observed. Conclusions. Women with PCOS were more likely to experience GDM and preterm birth.

Establishment of reference range of plasma amino acids for younger Chinese children by reverse phase HPLC.

BACKGROUND: Due to lack of country-specific norms in China, we established the reference range of plasma amino acids for younger Chinese children by reverse phase high-performance liquid chromatography (HPLC). METHODS: Plasma proteins were precipitated with ethanol. L-Norvaline served as an internal standard. This HPLC method was based on automated precolumn derivatization using o-phthalaldehyde 3-mercaptopropionic acid for primary amino acids and 9-fluorenylmethyl chloroformate for secondary amino acids. Twenty-three amino acid derivatives were separated by a Zorbax Eclipse AAA column and detected fluorometrically. Plasma amino acids were measured in 108 healthy Chinese children (ages 0-5 years, 59 boys and 49 girls). RESULTS: The assay was linear from 7.2 to 925.0 micromol/L for all amino acids. Recovery of amino acids added to plasma samples was 93%-107%. Within- and between-run reproducibility was 0.18%-6.27% and 2.94%-16.15%, respectively. Sex- and age-specific plasma amino acid reference range for younger Chinese children was established. In our study, the boys had significantly higher levels of glutamine, citrulline, and tryptophan than girls (p < 0.05), and the girls had a significantly higher level of alanine than boys (p < 0.05). Compared with the 0- to 1-year group, the 1- to 5-year group had significantly higher levels of citrulline, valine, phenylalanine, isoleucine, and sarcosine and lower levels of aspartate, glutamate, serine, threonine, alanine, methionine, and tryptophan (p < 0.05). CONCLUSIONS: This study validates the HPLC method described here as a simple, rapid, and reliable assay. The reference range of plasma amino acids for younger Chinese children is different from that for Caucasian children and will facilitate our clinical diagnosis in the future.

[Study on the status of unintentional injuries in children under age 7 in Guangzhou].

OBJECTIVE: To understand the prevalence and distribution of unintentional injuries in children under age 7 in Guangzhou. METHODS: Data was descriptively analyzed from the Guangzhou Unintentional Injuries Surveillance System among 470 770 children under age 7 living scatter or collectively. RESULTS: The incidence rates of unintentional injuries among children in Guangzhou was 1.48%, among which the incidence rates were: living scatter as 1.11% living collectively as 1.66%, living in urban areas as 1.36% in rural as 2.52%. In order, the proportion of main causes of children's unintentional injuries were as follows: falls (70.54%), animal injuries (8.48%), burn and scald (5.75%), blunt force injuries (3.92%), and road traffic injuries (RTIs) (3.48%). The main body parts being injured were head and face (60.00%), wrist and hand (15.48%), knee and leg (11.70%), elbow and forearm (4.54%), shoulder and arm (2.99%). The degrees of children's unintentional injuries were as follows: mild impairment (85.35%), moderate impairment (9.12%), and severe impairment (0.57%). Places that the patients went were as follows: hospital outpatient department or emergency room (49.66%), inpatient department or ICU (2.06%), home and kindergarten (43.34%). CONCLUSION: The overall incidence rate of children's unintentional injuries under age 7 in Guangzhou was 1.48%, with main causes as fall, animal injuries, burn and scald, blunt force injuries, and RTIs. There were considerable differences of characteristics and distributions on age and areas among the patients.