Maternal fasting serum C-peptide concentrations in the first and second trimesters and subsequent risk of gestational diabetes mellitus: A nested case-control study among Chinese women.

OBJECTIVE: To examine the association of serum connecting peptide (C-peptide) concentrations with gestational diabetes mellitus (GDM) risk among Chinese women. METHODS: A nested case-control study was conducted on 436 reproductive-aged women, involving 218 GDM cases and 218 controls matched at 1:1 by maternal age, in Beijing, China between January 2016 and December 2017. Fasting serum C-peptide were successively determined at 10-14 and 15-20 weeks of gestation. Restricted cubic spline and logistic regression analyses were utilized, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive capacity of C-peptide for GDM. RESULTS: Fasting serum C-peptide concentrations exhibited a significant decrease from the initial to the subsequent trimester in females with normal glucose tolerance (NGT). For each 1 log ng/mL increase of fasting serum C-peptide during the first and second trimesters, GDM risk increased by 2.38-fold [odds ratio (OR): 2.38, 95% confidence intervals (95%CI): 1.33-4.40] and 3.07-fold (OR: 3.07, 95%CI: 1.49-6.62), respectively. The areas under the ROC curves for the first- and second-trimester C-peptide were 80.4% and 82.4%. CONCLUSION: Our findings revealed a positive correlation between fasting serum C-peptide during the first and second trimesters and the risk of GDM or its subtypes, underscoring the potential of C-peptide as a predictor for GDM development.

Hematological Parameters in the First Trimester and the Risk of Gestational Diabetes Mellitus - Beijing, China, 2017-2020.

What is already known about this topic?: Hematological parameters may indicate the presence of chronic low-grade inflammation and increasing viscosity, which are involved in the pathological processes of gestational diabetes mellitus (GDM). However, the association between several hematological parameters in early pregnancy and GDM has yet to be elucidated. What is added by this report?: Hematological parameters in the first trimester, particularly red blood cell (RBC) count and systematic immune index, have a significant impact on GDM incidence. The neutrophils (NEU) count in the first trimester was particularly pronounced for GDM. The upward trend of RBC, white blood cell (WBC), and NEU counts was consistent across all GDM subtypes. What are the implications for public health practice?: Early pregnancy hematological parameters are associated with the risk of GDM.

Machine Learning-Based Prediction Model of Preterm Birth Using Electronic Health Record.

Objective: Preterm birth (PTB) was one of the leading causes of neonatal death. Predicting PTB in the first trimester and second trimester will help improve pregnancy outcomes. The aim of this study is to propose a prediction model based on machine learning algorithms for PTB. Method: Data for this study were reviewed from 2008 to 2018, and all the participants included were selected from a hospital in China. Six algorisms, including Naive Bayesian (NBM), support vector machine (SVM), random forest tree (RF), artificial neural networks (ANN), K-means, and logistic regression, were used to predict PTB. The receiver operating characteristic curve (ROC), accuracy, sensitivity, and specificity were used to assess the performance of the model. Results: A total of 9550 pregnant women were included in the study, of which 4775 women had PTB. A total of 4775 people were randomly selected as controls. Based on 27 weeks of gestation, the area under the curve (AUC) and the accuracy of the RF model were the highest compared with other algorithms (accuracy: 0.816; AUC = 0.885, 95% confidence interval (CI): 0.873-0.897). Meanwhile, there was positive association between the accuracy and AUC of the RF model and gestational age. Age, magnesium, fundal height, serum inorganic phosphorus, mean platelet volume, waist size, total cholesterol, triglycerides, globulins, and total bilirubin were the main influence factors of PTB. Conclusion: The results indicated that the prediction model based on the RF algorithm had a potential value to predict preterm birth in the early stage of pregnancy. The important analysis of the RF model suggested that intervention for main factors of PTB in the early stages of pregnancy would reduce the risk of PTB.

Maternal exposure to traffic-related ambient particles and risk of gestational diabetes mellitus with isolated fasting hyperglycaemia: A retrospective cohort study in Beijing, China.

BACKGROUND: Ambient particles have been associated with gestational diabetes mellitus (GDM), however, no study has evaluated the effects of traffic-related ambient particles on the risks of GDM subgroups classified by oral glucose tolerance test (OGTT) values. METHODS: A retrospective analysis was conducted among 24,001 pregnant women who underwent regular prenatal care and received OGTT at Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. A total of 3,168 (13.2%) pregnant women were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH). At a fixed-location monitoring station, routinely monitored ambient particles included fine particulate matter (PM2.5), black carbon (BC) and particles in size ranges of 5-560 nm (PNC5-560). Contributions of PNC5-560 sources were apportioned by positive matrix factorization model. Logistic regression model was applied to estimate odds ratio (OR) of ambient particles on GDM risk. RESULTS: Among the 24,001 pregnancy women recruited in this study, 3,168 (13.2%) were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH) and 1,295 with isolated post-load hyperglycaemia (GDM-IPH). We observed increased GDM-IFH risk with per interquartile range increase in first-trimester exposures to PM2.5 (OR = 1.94; 95% Confidence Intervals: 1.23-3.07), BC (OR = 2.14; 1.73-2.66) and PNC5-560 (OR = 2.46; 1.90-3.19). PNC5-560 originated from diesel and gasoline vehicle emissions were found in associations with increases in GDM-IFH risk, but not in GDM-IPH risk. CONCLUSION: Our findings suggest that exposure to traffic-related ambient particles may increase GDM risk by exerting adverse effects on fasting glucose levels during pregnancy, and support continuing efforts to reduce traffic emissions for protecting vulnerable population who are at greater risk of glucose metabolism disorder.

Maternal exposures to fine and ultrafine particles and the risk of preterm birth from a retrospective study in Beijing, China.

Maternal exposure to fine particulate matter (PM2.5) has been associated with increased risk of preterm birth (PTB), but evidence on particles in smaller sizes and PTB risk remains limited. In this retrospective analysis, we included birth records of 24,001 singleton live births from Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. Concurrently, number concentrations of size-fractioned particles in size ranges of 5-560 nm (PNC5-560) and mass concentrations of PM2.5, black carbon (BC) and gaseous pollutants were measured from a fixed-location monitoring station in central Haidian District. Logistic regression models were used to estimate the odds ratio (OR) of air pollutants on PTB risk after controlling for temperature, relative humidity, and individual covariates (e.g., maternal age, ethnicity, gravidity, parity, gestational weight gain, fetal gender, the year and season of conception). Positive matrix factorization models were then used to apportion the sources of PNC5-560. Among the 1062 (4.4%) PTBs, increased PTB risk was observed during the third trimester of pregnancy per 10 µg/m3 increase in PM2.5 [OR = 1.92; 95% Confidence Interval (95% CI): 1.76, 2.09], per 1000 particles/cm3 increase in PNC25-100 (OR = 1.09; 95% CI: 1.03, 1.15) and PNC100-560 (OR = 1.22; 95% CI: 1.05, 1.42). Among the identified sources of PNC5-560, emissions from gasoline and diesel vehicles were significantly associated with increased PTB risk, with ORs of 1.14 (95% CI: 1.01, 1.29) and 1.11 (95% CI: 1.04, 1.18), respectively. Exposures to other traffic-related air pollutants, such as BC and nitrogen dioxide (NO2) were also significantly associated with increased PTB risk. Our findings highlight the importance of traffic emission reduction in urban areas.

Ultrafast Synthesis of Ni-MOF in One Minute by Ball Milling.

A mechanical ball milling method for ultrafast synthesis of a nickel-based metal organic framework (Ni-MOF) has been proposed. The Ni-MOF was successfully synthesized in merely one minute without any solvent, additives, or preliminary preparation. The effect of milling time, mechano-frequency, type of assistant liquid, and amount of assistant water were systematically explored. It was found that the product can be obtained even only at a mechano-frequency of 10 Hz within one minute without any external solvent-assist, which indicated that the crystal water present in the nickel precursor was sufficient to promote MOF formation. Increasing the milling time, raising the mechano-frequency, and the addition of assistant solvent could promote the reaction and increase the yield. The method is rapid, highly efficient, eco-friendly, and has great scalability. The product generated within merely one minute even exhibited high capacitance.

Rheological Behavior of a Novel Organic-Inorganic Hybrid: Micro/Nano-Tin Fluorophosphate Glass-Polycarbonate.

The rheological behavior of a novel, binary organic-inorganic hybrid consisting of an ultra-low Tg tin fluorophosphate glass (Pglass) and polycarbonate (PC) was investigated using oscillatory rheometry. It was found that the complex viscosity of the hybrid showed Pglass content dependence. Under low Pglass content (10-30%), the complex viscosity of the hybrid was lower than that of pure PC. While the complex viscosity was dramatically increased and higher than that of pure PC with the content of Pglass above 30%. This phenomenon was particularly remarkable at low frequencies. Besides, with the addition of Pglass the hybrid material exhibited shear-thinning behavior and the shear-thinning characteristics became more obvious with the enhancement of the Pglass content, indicating the presence of nonlinear chemical and physical interactions between the hybrid components. Differential scanning calorimetry (DSC) measurements revealed that increasing the content of Pglass caused a decrease of the glass transition temperature (Tg) of the hybrids, suggesting that Pglass was acting as a macromolecular plasticizer for the PC. The microstructure of the Pglass in the hybrid material was characterized by scanning electron microscopy (SEM). The results showed that the Pglass were dispersed as micro- and nano-bead in the continuous phase of PC and the Pglass appeared aggregation partly with the increase of the Pglass content. This contribution was anticipated to be a guideline for the processing of this promising new class of hybrid materials.

Dynamic Mechanical Properties, Crystallization Behavior and Morphology of Nanoscale Tin Fluorophosphate Glass/Polyamide 66 Hybrid Materials.

The dynamic mechanical properties, crystallization behavior and morphology of nanoscale Tg tin fluorophosphate glass (TFP glass)/polyamide 66 (PA66) hybrid materials were investigated by XRD, DSC and SEM. The experimental results showed that the Tg of TFP/PA66 hybrid decreased and the third relaxation in the highly filled hybrid appeared due to the interaction between the TFP glass and amide groups of PA66. The storage modulus of the hybrid materials increased with increase in the content of TFP at low temperatures but had little effect at high temperatures. This result was attributed to the stiffness depression of the TFP glass when the temperature rose above its Tg and the similar elasticity of the two phases because of the interaction between the components. The degree of crystallinity and a, y crystal content of PA66 both decreased due to the interaction between the two phases. In addition, the phase defect, the size distribution and the compatibility of TFP in the PA66 matrix were discussed by SEM, the results showed that the TFP appeared aggregation partly, but had the favorable compatibility in the PA66 matrix.

[A community-based study on relations between metabolic syndrome and carotid atherosclerosis in a middle-aged population].

OBJECTIVE: To explore the association between metabolic syndromes (MS) and carotid atherosclerosis and to estimate the predictive effects of MS under 3 different definitions. METHODS: A cross-sectional study was conducted in 2 community-based populations in Beijing, in 2008. 1266 subjects (598 men, 668 women), aged 45 - 69, were included in the analyses. MS was defined by the criteria of International Diabetes Federation (IDF), the revised NCEP ATP III (ATPIII-R) and "The Guidelines of Dyslipidemia Control for Chinese Adult" ("Guidelines") in 2007. RESULTS: The prevalence rates of MS by the 3 criteria were 39.0%, 43.3% and 30.9% respectively. The Kappa value for the measure of the agreement between each pair of the 3 definitions were 0.911, 0.719 and 0.730 respectively. The intima-media thickness in common carotid artery (CCA-IMT) was significantly higher (P < 0.001) in all MS groups than in non-MS groups, diagnosed with the 3 criteria independent of age, gender, LDL-C, and current smoking status. After adjustment of age, gender, LDL-C, and current smoking status, the classification of MS significantly increased the risk of prevalence of carotid atherosclerotic plaques, compared to the non-MS group. OR value were 1.499 (95%CI: 1.157 - 1.942) for IDF, 1.696 (95%CI: 1.314 - 2.189) for NCEP-R, 1.763 (95%CI: 1.344 - 2.312) for "Guideline" respectively. CONCLUSION: Our research findings indicated that, when MS were defined with the 3 definitions, prediction on the risk of sub-clinical atherosclerosis would work beyond some of the conventional cardiovascular risk factors such as smoking, LDL-C. There might exist some differences in gender issue on the strength of association between MS when diagnosed by different criteria and carotid plaque.