Language of Lullabies: The Russification and De-Russification of the Baltic States

This article argues that the laws for promotion of the national languages are a legitimate means for the Baltic states to establish their cultural independence from Russia and the former Soviet Union

Automated Machine Learning (AutoML)-Derived Preconception Predictive Risk Model to Guide Early Intervention for Gestational Diabetes Mellitus

The increasing prevalence of gestational diabetes mellitus (GDM) is contributing to the rising global burden of type 2 diabetes (T2D) and intergenerational cycle of chronic metabolic disorders. Primary lifestyle interventions to manage GDM, including second trimester dietary and exercise guidance, have met with limited success due to late implementation, poor adherence and generic guidelines. In this study, we aimed to build a preconception-based GDM predictor to enable early intervention. We also assessed the associations of top predictors with GDM and adverse birth outcomes. Our evolutionary algorithm-based automated machine learning (AutoML) model was implemented with data from 222 Asian multi-ethnic women in a preconception cohort study, Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO). A stacked ensemble model with a gradient boosting classifier and linear support vector machine classifier (stochastic gradient descent training) was derived using genetic programming, achieving an excellent AUC of 0.93 based on four features (glycated hemoglobin A(1c) (HbA(1c)), mean arterial blood pressure, fasting insulin, triglycerides/HDL ratio). The results of multivariate logistic regression model showed that each 1 mmol/mol increase in preconception HbA(1c) was positively associated with increased risks of GDM (p = 0.001, odds ratio (95% CI) 1.34 (1.13-1.60)) and preterm birth (p = 0.011, odds ratio 1.63 (1.12-2.38)). Optimal control of preconception HbA(1c) may aid in preventing GDM and reducing the incidence of preterm birth. Our trained predictor has been deployed as a web application that can be easily employed in GDM intervention programs, prior to conception.Peer reviewe

Prepregnancy adherence to plant-based diet indices and exploratory dietary patterns in relation to fecundability

Background Modest associations have been reported between specific food groups or nutrients and fecundability [measured by time to pregnancy (TTP)]. Examining overall diets provides a more holistic approach towards understanding their associations with fecundability. It is not known whether plant-based diets indices or exploratory dietary patterns are associated with fecundability. Objectives We examine the associations between adherence to 1) plant-based diet indices; and 2) exploratory dietary patterns and fecundability among women planning pregnancy. Methods Data were analyzed from the Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO) study. Prepregnancy diet was assessed using a semi-quantitative FFQ from which the overall, healthful, and unhealthful plant-based diet indices (oPDI, hPDI, and uPDI, respectively) were calculated. Exploratory dietary patterns were derived using factor analysis based on 44 predefined food groups. Participants were categorized into quintiles based on their dietary pattern scores. TTP (expressed in menstrual cycles) was ascertained within a year from the prepregnancy dietary assessment. Discrete-time proportional hazard models, adjusted for confounders, were used to estimate fecundability ratios (FRs) and 95% CIs, with FR > 1 indicating a shorter TTP. Results Among 805 women, 383 pregnancies were confirmed by ultrasound scans. Compared with women in the lowest quintile, those in the highest quintile of the uPDI had reduced fecundability (FR of Q5 compared with Q1, 0.65; 95% CI, 0.46-0.91; P trend, 0.009). Conversely, greater adherence to the hPDI was associated with increased fecundability (1.46; 95% CI, 1.02-2.07; P trend, 0.036). The oPDI was not associated with fecundability. Among the 3 exploratory dietary patterns, only greater adherence to the Fast Food and Sweetened Beverages (FFSB) pattern was associated with reduced fecundability (0.61; 95% CI, 0.40-0.91; P trend, 0.018). Conclusions Greater adherence to the uPDI or the FFSB dietary pattern was associated with reduced fecundability among Asian women. Greater adherence to the hPDI may be beneficial for fecundability, though this requires confirmation by future studies.Peer reviewe