OBJECTIVES:We aimed to examine the association between PM1 exposure during different stages of pregnancy and emotional and behavioral problems in offspring, and to evaluate whether maternal diet quality interacts with these relationships. STUDY DESIGN:Birth cohort study. METHODS:This cohort study included 391 mother-child pairs from Guangzhou, China. Prenatal PM1 exposure was estimated using a spatiotemporal model. Maternal diet was assessed via a validated food frequency questionnaire and scored using the Chinese Healthy Eating Index (CHEI). At age 5, offspring's emotional and behavioral problems were evaluated with the Strengths and Difficulties Questionnaire, including emotional, conduct, hyperactivity, peer relationship problems, prosocial behavior, and total difficulties. Generalized linear models were used to examine the association. RESULTS:Overall, 15.9% of children exhibited at least one type of emotional and behavioral problem. The mean maternal PM1 was 17.51 ± 2.38 μg/m3. Each interquartile range (IQR) increase in PM1 concentration during the first trimester was associated with elevated risk of offspring behavioral problems (OR = 2.25; 95% CI: 1.06∼4.89). Increased PM1 exposure during both the first (OR = 2.90; 1.07∼8.21) and second trimesters (OR = 4.50; 1.23∼16.76) was linked to higher odds of total difficulties. Higher maternal CHEI scores, particularly the total score and dark vegetable intake component, were associated with weaker PM1-related associations. CONCLUSION:Maternal exposure to PM1 during pregnancy, especially during the first and second trimesters, was associated with an increased risk of emotional and behavioral problems in offspring. A high-quality maternal diet, particularly one rich in vegetables, may mitigate these adverse effects.

Neonicotinoid insecticides (NEOs) are widely used globally, leading to human exposure including pregnant women, and may pose risks of neurocognitive toxicity. In this study, we analyzed 114 mother-child pairs from the Guangxi Zhuang birth cohort. Umbilical cord plasma concentrations of 10 NEOs were measured using ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS), and child neurocognitive development was assessed using the Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition (WPPSI-IV) and the Ages and Stages Questionnaire, Third Edition (ASQ-3). NEOs were frequently detected, with detection rates ranging from 15.8% to 96.5%, and dinotefuran (DIN) showed the highest prevalence. Prenatal exposure to several NEOs was associated with lower neurocognitive scores. Specifically, DIN and clothianidin (CLO) exposure were associated with lower Full-Scale Intelligence Quotient (FSIQ), while thiacloprid (THIA) exposure was linked to poorer communication performance. In addition, imidacloprid (IMI) and THIA exposure were associated with reduced gross motor function, and thiamethoxam (TMX) was further associated with reduced fine motor development. Mixed exposure analysis suggested a negative but non-significant association between overall NEO exposure and FSIQ or fine motor outcomes. These findings suggest a potential association between prenatal exposure to NEOs and neurocognitive development in preschool children, highlighting the need for further research to inform public health strategies.

The majority of studies have predominantly used body mass index or waist circumference as measures to establish a link between urinary metals and obesity, leading to inconsistent outcomes. Visceral fat index was a simple, practical and non-invasive physical examination indicator for measuring visceral obesity, and the association between urinary metal and VFI is unclear. This study utilized a cross-sectional design and based on the baseline data of the Prospective Cohort Study of Chronic Diseases in Ethnic Minority Natural Population in Guangxi from May 2019 to December 2019. Information on demographics, health status, lifestyle, and additional variables was obtained through structured face-to-face interviews. The study employed multiple statistical models, including lasso regression, logistic regression, restricted cubic spline, quantile g-computation, weighted quantile sum, and Bayesian kernel machine regression. This study encompassed a total of 5794 participants, comprising 2641 males and 3153 females. Among the participants, 1423 (24.6

Previous studies linking prenatal air pollution to adverse birth outcomes may be confounded by unmeasured familial factors, potentially leading to biased effect estimates and misleading public health recommendations. This sibling-matched case-control study re-examined associations between six criteria air pollutants and preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA). Associations were assessed using both a sibling-matched generalized linear mixed model (estimating subject-specific conditional effects) and conventional unmatched logistic regression (estimating population-averaged marginal effects) for comparison. We analyzed 194 284 mother-infant pairs (97 142 sibling pairs) from Nanning, China (2016–2022). Pollutant data were sourced from the high-resolution CHAP dataset. In sibling-matched analyses, first-trimester NO2 exposure increased PTB risk (OR = 1.004), while exposures to SO₂ (ORfirst=1.009, ORsecond=1.009, ORthird=1.010) and CO (ORsecond=1.163, ORthird=1.157) in specific trimesters were associated with elevated SGA risk. Some significant associations observed in unmatched designs (e.g., CO exposure across trimesters and PTB) were attenuated to non-significance after sibling matching. Furthermore, unmatched designs generally overestimated pollutant-PTB associations while underestimating pollutant-SGA links, with the largest between-model differences in effect estimates for CO. Prenatal exposure to NO₂, SO₂, and CO is associated with increased risks of PTB and SGA. Conventional unmatched study may lead to divergent effect estimates due to both unmeasured familial confounding and inherent mathematical differences between statistical models, underscoring the critical need to control for familial confounders in environmental epidemiological studies. Our findings highlight the importance of methodological refinement in environmental risk assessment to inform evidence-based air quality policies.

Residential greenness, as an essential aspect of the environment, contributes significantly to alleviating the negative impacts of accelerated urbanization and promoting sustainable urban development. However, the associations between residential greenness exposure and the risks of preterm birth (PTB) and small for gestational age (SGA), as well as the potential biological mechanisms underlying these associations, remain underexplored. In this study, we assessed the associations of residential greenness exposure across different periods of pregnancy (first, second, and third trimesters, as well as the entire pregnancy) with the risks of PTB and SGA, examined the interaction effects between greenness and PM2.5, and quantified the mediating role of the systemic immune-inflammation index (SII) in the associations between greenness and PTB or SGA using mediation analyses. We found that each 0.1-unit increment within 500-meter buffer (NDVI-500m) throughout pregnancy was associated with a 5.0-6.0 % lower risk of PTB and a 4.0-10.0 % lower risk of SGA. The third trimester emerged as the period during which greenness exposure had the most pronounced impact on these adverse outcomes. Non-linear exposure-response relationships were observed between residential greenness and the risks of PTB and SGA. Significant interactions were observed between NDVI-500m and PM2.5, whereby greater greenness combined with lower PM2.5 concentrations was jointly associated with the lowest risks of PTB and SGA. The SII mediated 8.6-16.1 % and 4.2-12.1 % of the effects of NDVI-500m on PTB and SGA, respectively. These findings support that exposure to residential greenness lowers the risks of PTB and SGA, and mitigates the adverse impacts of PM2.5 on these outcomes, and may partially exert its effects through SII.

BACKGROUND:Previous studies have explored the effects of metal exposure on sleep indifferent age groups, but few have examined the effects in postmenopausal women. The study was aimed to investigate the single and mixed effects of exposure to 22 metals on sleep quality in postmenopausal women. METHODS:The baseline data of 1914 postmenopausal women were extracted from the Prospective Cohort of Chronic Diseases in Guangxi Ethnic Minority Natural Population in China. Concentrations of 22 metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality in postmenopausal women. The binary logistic regression model was used to analyze the effect of single metals exposure on the risk of poor sleep quality and quantile g-computation regression model was applied to assess the mixed effects of multiple metals exposure. RESULTS:Among the 1914 participants,736(38.5%) had poor sleep quality. In single-metal analyses, only manganese showed a positive association with poor sleep quality before multiple comparison correction (continuous variable, adjusted OR=1.21,95%CI:1.03-1.41), but this did not remain significant after false discovery rate (FDR) correction. Similarly, quartile-based analyses showed nominally positive associations for Mn (Q2:OR=1.51,95%CI:1.16-1.98,Q4:OR=1.41, 95%CI:1.07-1.85), Zn (Q2:OR=1.40, 95%CI:1.07-1.83), Ca (Q3:OR=1.36,95%CI:1.04-1.77), and Mo (Q3:OR=1.30, 95%CI:1.00-1.70), but none remained significant after FDR correction. However, the qgcomp mixture analysis revealed that exposure to the essential metal mixture was significantly associated with poor sleep quality (OR=1.23, 95%CI:1.05-1.44), with Mn, Zn, Ca, and Mo as the main positive contributors. CONCLUSION:No single metal remained significantly associated with poor sleep quality after FDR correction, whereas the essential metal mixture showed a significant positive association, with Mn identified as the primary contributor. Associations for Ca, Zn, and Mo were observed only in specific quartiles with non-monotonic patterns and should therefore be considered exploratory. These findings highlight the importance of mixture-based approaches in environmental health research. Further longitudinal studies, animal experiments, and cell-based investigations are warranted to validate these findings.

Gout typically develops from hyperuricemia (HUA), but the metabolic alterations driving this transition remain poorly understood, limiting our understanding of disease pathogenesis. To identify stage-specific putative biomarker candidates and to characterize dysregulated metabolic pathways distinguishing gout from HUA. We conducted a targeted metabolomics assay on the baseline plasma samples from a Zhuang minority cohort using LC-MS/MS. The analyzed sample set comprised 38 HUA patients, 47 gout patients, and 52 healthy controls. Sex-stratified differential metabolite analysis was performed across all participants, as well as in female and male subgroups. Pathway enrichment analysis was carried out using the KEGG database. Machine learning approaches, including the Boruta algorithm and support vector machine (SVM), were employed for putative biomarker discovery and model evaluation in male participants. Among all participants, 24 metabolites reached nominal significance (P < 0.05), but only uric acid remained significant after FDR correction. In sex-stratified analyses, no metabolite survived FDR correction in females, whereas in males, seven metabolites (flavone, glutamine, L-2-aminoadipic acid, L-pipecolic acid, N1-methyl-2-pyridone-5-carboxamide, phenyllactic acid, and uric acid) showed significant differences among healthy controls, HUA patients, and gout patients (FDR < 0.1). These metabolites were primarily involved in nitrogen metabolism, arginine biosynthesis, D-amino acid metabolism, nicotinate and nicotinamide metabolism, and purine metabolism. Machine learning identified four metabolites (N1-methyl-2-pyridone-5-carboxamide, flavone, glutamine, and phenyllactic acid) that distinguished gout from healthy controls, with AUCs of 0.902 and 0.800 in the training and validation sets, respectively. A second model (L-pipecolic acid, glutamine, phenyllactic acid, and flavone) discriminated gout from HUA, achieving AUCs of 0.850 and 1.000. Sensitivity analyses excluding obese or hypertriglyceridemic participants confirmed the robust performance of both models. This study suggests sex-specific metabolic alterations in gout and provides robust machine learning-based models for male participants. The identified metabolite signatures appear to extend purine metabolism to involve amino acid and energy metabolic pathways. These findings provide a basis for mechanism-targeted strategies in HUA management. External validation remains essential.

BACKGROUND:Isoflavones are plant-derived estrogenic compounds that can cross the placenta and influence fetal development, but evidence on fetal ultrasound parameters is limited. OBJECTIVES:This study aims to assess associations between individual and combined isoflavones and fetal ultrasound parameters in a prospective birth cohort in Guangxi, China. METHODS:We included 577 mother-infant pairs. Fetal parameters included biparietal diameter, head circumference, femur length, abdominal circumference, and estimated fetal weight. Maternal serum isoflavones in early pregnancy were measured by ultrahigh-performance liquid chromatography-mass spectrometry. Associations were analyzed using multiple linear regression and Bayesian kernel machine regression. RESULTS:Higher daidzein, genistein, and glycitein levels (highest compared with lowest tertile) were linked to significantly increased second-trimester biparietal diameter [β = 0.291, 95% confidence interval (CI): 0.091, 0.492; β = 0.256, 95% CI: 0.053, 0.459, and β = 0.296, 95% CI: 0.095, 0.498, respectively] and head circumference z-scores (β = 0.216, 95% CI: 0.004, 0.427, β = 0.240, 95% CI: 0.025, 0.456, and β = 0.264, 95% CI: 0.050, 0.478, respectively). Higher daidzein concentrations were also correlated with significantly increased third-trimester head circumference (β = 0.304, 95% CI: 0.086, 0.522). Glycitein exhibited sex-specific effects on abdominal circumference and estimated fetal weight in females, whereas daidzein affected third-trimester estimated fetal weight in females and head circumference in males (all P < 0.05). In Bayesian kernel machine regression, higher isoflavone combined levels (daidzein, genistein, glycitein, and equol) were significantly associated with increased second-trimester biparietal diameter) z-scores in the total population and female fetuses, as well as increased second-trimester estimated fetal weight in female fetuses, with glycitein identified as the major contributor. CONCLUSIONS:Early-pregnancy isoflavone exposure may positively influence fetal growth, with trimester- and sex-specific effects. Further mechanistic studies on placental nutrient transport, gene expression, and long-term offspring outcomes are warranted.

Objective To analyze the association between mixed metal exposure and sleep quality within the Guangxi natural population cohort, providing scientific evidence for developing prevention and control strategies for sleep disorders. Methods A cross-sectional study design was implemented using baseline data from the "Prospective Cohort of Chronic Diseases in Guangxi Ethnic Minority Natural Population", enrolling 5, 486 participants. Sleep quality was evaluated with the Pittsburgh Sleep Quality Index (PSQI), while basic information was collected via standardized questionnaires and physical examinations. Concentrations of 22 metal elements in firstmorning urine samples were quantified via inductively coupled plasma mass spectrometry. The least absolute shrinkage and selection operator (LASSO) regression was employed for metal feature selection, followed by logistic regression to assess associations between the selected metals and sleep disorder risk. Furthermore, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) models were integrated to systematically evaluate the joint effects of mixed metal exposure and identify the primary contributing metals. Results The detection rate of sleep disturbance among the study participants was 29.4% (1, 613/5, 486). LASSO regression selected 10 metals associated with sleep disorder risk: titanium, manganese, zinc, strontium, molybdenum, cadmium, tin, antimony, barium, and thallium. Logistic regression results showed that concentrations of manganese (OR=1.1, 95% CI: 1.0-1.2), zinc (OR=1.2, 95% CI: 1.0-1.6), and barium (OR=1.1, 95% CI: 1.0-1.2) were significantly associated with an increased risk of sleep disorders, while antimony (OR=0.8, 95% CI: 0.7-0.9) concentration was associated with a decreased risk. Joint effect analysis revealed that the positive WQS index for mixed exposure to the 10 metals was significantly associated with an increased risk of sleep disorders (OR=1.15, 95% CI: 1.01-1.31). The primary contributing metals identified by the WQS regression, qgcomp, and BKMR models were consistent with the logistic regression findings. Stratified and sensitivity analyses further confirmed that the associations between manganese, zinc, barium, antimony, and sleep disorder risk were consistent with the logistic regression findings. Conclusion Urinary levels of manganese, zinc, barium, and antimony are significantly associated with the risk of sleep disturbance in the general population of Guangxi. Furthermore, combined exposure to these metals may be associated with an elevated risk of sleep disturbance.

Urban green space exposure and air pollutants impact birth outcomes. However, the association between prenatal greenness, air pollutants, and twin growth discordance (TGD) have been rarely investigated. This study aims to evaluate the association of prenatal greenness on TGD risk, and to explore whether this association is modified or mediated by air pollutants. We enrolled 4449 twin pairs from Guangdong Province, China, between 2013 and 2018. NDVI and daily levels of PM2.5, NO2, O3 were derived from satellite-based exposure models. The combined oxidative potential (OX) was calculated based on NO2 and O3 levels. Generalized linear models were employed to examine the associations between prenatal greenness, PM2.5, NO2, O3, and OX and TGD risk. Mediation analyses were further conducted to quantify the indirect effect of air pollutants on the association between greenness and TGD. Results showed that each interquartile increase in NDVI was consistently associated with reduced TGD risk, with adjusted ORs ranging from 0.77 (95%CI: 0.69, 0.86) in the third trimester of pregnancy to 0.85 (95%CI: 0.76, 0.95) in the first trimester of pregnancy. Higher exposure to NO2 and OX was associated with increased TGD risk. A significant interaction was observed between greenness and NO2 across the entire pregnancy (OR: 1.13, 95%CI:1.01, 1.25). Mediation analysis found that the relationship between prenatal greenness exposure and TGD risk was partly mediated by reduced NO2 (19.0%) and OX (8.6%). These findings provide a novel evidence that promoting urban greening and reducing air pollution exposure may serve as effective strategies for mitigating TGD risk.

Liver cancer ranks sixth in cancer incidence and third in cancer-related deaths worldwide. Hepatocellular carcinoma (HCC) is the primary histological subtype, and hepatitis B virus (HBV) carriers have a higher risk of HCC. Although several susceptibility loci for HCC have been identified in East Asian populations through genome-wide association studies (GWAS), the underlying biological mechanisms of this malignancy remain incompletely understood. Here, we conduct a two-stage GWAS including 2413 cases and 2794 HBV-positive controls from a high-incidence region in Southern China. The function of the susceptibility locus is investigated by bioinformatic and experimental approaches, supported by a xenograft model. We identify a 4p14 locus significantly associated with the risk of HCC (rs55718051, OR [95% CI] = 0.73 [0.67-0.80], Pmeta = 9.14 × 10-11), and 18q23 locus with borderline significance (rs12964643: OR [95% CI] = 0.75 [0.67-0.83], Pmeta = 1.11 × 10-7). Functional experiments indicate the role of rs55718051 in FAM114A1 expression regulation, possibly through the interaction with FOXA1. Knockdown of FAM114A1 significantly promote the oncogenic phenotypes in liver cancer cells, suggesting its potential tumor suppressor role. Our findings expand the understanding of HCC susceptibility and suggest FAM114A1 as a potential suppressor in HBV-related HCC carcinogenesis.

BACKGROUND:Prenatal exposure to Polyfluoroalkyl Substances (PFASs) had been associated with adverse effects on multiple systems in offspring. However, the effects on visual system had not been previously explored. OBJECTIVE:The study aimed to assess the association between prenatal exposure to PFASs and visual acuity and visual impairment in preschool children. METHODS:A total of 1008 mother-infant pairs were extracted from the Guangxi Zhuang Birth Cohort in China. Maternal serum concentrations of nine PFASs were measured using Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS). The preschool visual acuity (VA) in the offspring was obtained through the local maternal and child health information system. Multiple linear regression models and logistic regression models were performed to study the single effects of individual PFAS on VA and visual impairment (VI), respectively. Additionally, Bayesian kernel machine regression (BKMR) and quantile g-computation (Qgcomp) models were utilized to assess the joint effects of the nine PFASs. RESULTS:Prenatal exposure to PFOS (β = 0.074, 95 % CI: 0.033, 0.116), PFHxS (β = 0.062, 95 % CI: 0.012, 0.111), and PFBS (β = 0.023, 95 % CI: 0.001, 0.044) exhibited significant positive associations with enhanced VA. Conversely, PFOS (OR = 0.481, 95 % CI: 0.245, 0.946) and PFHxS (OR = 0.450, 95 % CI: 0.244, 0.830) were significantly associated with reduced odds of VI. BKMR and quantile g-computation (Qgcomp) modeling consistently displayed positive joint-effects for nine PFASs mixtures on VA. Stratified analysis by sex indicated that certain significant associations were observed exclusively in boys or girls, and these associations were positively correlated with VA. CONCLUSIONS:The evidence does not substantiate the hypothesis that prenatal exposure to PFASs adversely impacts visual development. Nonetheless, inverse associations reported here should not be interpreted as protective, as these associations might be driven by some unresolved confounding factors and biases. Their relationship still needs to be elucidated in future studies, using larger samples and accounting for both prenatal and childhood periods.

BackgroundOur previously research has validated the effect of circELMOD3 on HCC tumor inhibition. However, further investigations are warranted to investigate the prognostic significance of circELMOD3 in HCC and its regulation via the competitive endogenous RNA (ceRNA) network.MethodsThe gene expression profiles and clinical information were obtained from The Cancer Genome Atlas (TCGA-LIHC) and International Cancer Genome Consortium (ICGC). Base on the circMine, miRWalk and TargetScan database, we constructed circELMOD3-miRNA-mRNA network. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis was used to constructed the prognostic model. Additionally, Gene set enrichment analysis (GSEA) was conducted for the prognostic-related genes. Finally, the expression levels of genes and proteins were respectively assessed by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting.ResultsWe constructed a ceRNA network comprising circELMOD3, 5 miRNAs, and 274 mRNAs. From this ceRNA network, we identified four prognostication-relation genes to develop a survival prediction model. In the TCGA-LIHC training set, the area under the curve (AUC) values for one-, three- and five-years of survival were 0.734, 0.718 and 0.707, respectively, then we validated the prognostic model in International Cancer Genome Consortium database. Gene set enrichment analysis displayed that these four prognostic genes were primary enriched pathways related to cell cycle regulation. Our finding demonstrated that circELMOD3 could affect the relative expression levels of N-cadherin, E-cadherin, CDK4, CDK6 and CyclinD1 proteins.Conclusionwe constructed a novel ceRNA network based on circELMOD3, to comprehensively characterizing the prognosis of HCC, providing valuable insights for the therapy and prognosis of HCC.

Preterm birth (PTB) is a primary cause of mortality among newborns globally. Prenatal exposure to environmental pollutants has been suggested to increase the PTB risk. Studies have shown NEOs may be linked to adverse birth outcomes. However, the impact of maternal NEOs exposure on PTB remains unclear. Therefore, to examine the association between NEOs exposure and PTB risk, we performed a case-control analysis utilizing data from a birth cohort study in Guangxi, China. A total of 157 preterm infants and 471 full-term infants were included. Concentrations of 10 NEOs and their metabolites in maternal serum were quantified using liquid chromatography-tandem mass spectrometry. We employed logistic regression, quantile g-computation, and restricted cubic spline models to evaluate the effects of individual and mixed NEOs exposures. Subsequently, XGBoost machine learning, combined with SHAP, was employed to predict the implications of serum NEOs on PTB. Finally, for 1-standard deviation increment in ln-transformed concentrations of imidacloprid and dinotefuran, significant correlations with higher odds of PTB were observed, showing odds ratios of 1.17 (95 % CI: 1.02, 1.36) and 1.41 (95 % CI: 1.16, 1.72). Similar patterns and higher risks were observed in late preterm birth. In both mixed exposure and machine learning models, dinotefuran and imidacloprid were identified as major predictors of increased PTB risk. Exposure to n-desmethylacetamiprid, sulfoxaflor, thiacloprid, nitenpyram, and thiamethoxam was negatively associated with PTB. Our findings suggested dinotefuran and imidacloprid exposure during pregnancy were risk factors of PTB, particularly among late preterm births. Subsequent research is necessary to illuminate the underlying mechanisms involved.

Background: Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and seriously threatens the health of mothers and offspring. Neonicotinoids (NEOs) is a new class of pesticide and widely used worldwide. Prenatal NEOs exposure had negative effects on fetal growth, but the potential effect of NEOs exposure on pregnancy complications remain unclear. Objectives: To examine the individual and jointed effects of serum neonicotinoids (NEOs) pesticide exposure on gestational diabetes mellitus (GDM), and explore the application of NEOs exposure levels as predictor of GDM. Methods: We conducted a prospective cohort study based on Guangxi Zhuang Birth Cohort, China. A total of 1450 mather-infant pairs were included from 2015 to 2019. Ten NEOs were measured by UPLC-MS. Maternal serum samples were collected during gestational age 0-12 weeks. Individual and jointed effects of NEOs on GDM were assessed through binomial regressions, Bayesian Kernel Machine Regression and quantile g-computation. Prediction of GDM using XGboost machine learning and SHapley Additive exPlanations (SHAP). Results: A total of 122 (8.4%) mothers were diagnosed with GDM. In the individual exposure models, sulfoxaflor and thiamethoxam exposure in the first trimester significantly increased the risk of GDM (OR = 1.48, 95%CI: 1.21, 1.82; OR = 1.42, 95%CI: 1.14, 1.78). Moreover, GDM risk increased significantly with NEOs mixture concentration was above 75th percentile, compared with the 50th percentile. Sulfoxaflor and thiamethoxam as the main positive contributing factors in NEOs mixture to increase the GDM with a weight of 29.3% and 27.6%, respectively. Furthermore, sulfoxaflor and thiamethoxam were the most important contributing factors for predicting GDM after combining traditional risk factors in machine learning model, with predicted contribution values of 0.79 and 0.46, respectively. Conclusion: Our findings suggested that elevated maternal serum sulfoxaflor, thiamethoxam and NEOs mixture were positively associated with GDM, and sulfoxaflor, thiamethoxam were the important contributing factors for predicting GDM.

The physiological functions of micronutrients in neurodevelopment are well documented, but their protective effects on neurodevelopmental disorders remain controversial. We assessed the associations between micronutrients and three main neurodevelopmental disorders, that is, autism spectrum disorder (18,381 cases), attention-deficit/hyperactivity disorder (38,691 cases), and Tourette's syndrome (4,819 cases), using two-sample Mendelian randomization analyses. In addition, we estimated the mediation role of brain imaging-derived phenotypes (n = 33,224) in these associations. Each 1 SD (0.08 mmol/L) increase in serum magnesium concentration was associated with a 16% reduced risk of autism spectrum disorder (odds ratio 0.84, 95% confidence interval 0.72-0.98). Each 1 SD (65 μmol/L) increase in blood erythrocyte zinc concentration was associated with an 8% reduced risk of attention-deficit/hyperactivity disorder (0.92, 0.86-0.98). Each 1 SD (173 pmol/L) increase in serum vitamin B12 concentration was associated with a 19% reduced risk of Tourette's syndrome (0.81, 0.68-0.97). These effects were partly mediated by alterations in multiple brain imaging-derived phenotypes, with mediated proportions ranging from 5.84% to 32.66%. Our results suggested that interventions targeting micronutrient deficiencies could be a practical and effective strategy for preventing neurodevelopmental disorders, especially in populations at high risk of malnutrition.Lay abstractIncreasing evidence highlights the critical role of micronutrients in neurodevelopment. However, the causal relationship between micronutrients and neurodevelopmental disorders remains unclear. Using genetic variants associated with micronutrient levels and neurodevelopmental disorders, our study revealed the protective effects of magnesium on autism spectrum disorders, zinc on attention-deficit/hyperactivity disorder, and vitamin B12 on Tourette's syndrome. These protective effects were partially mediated through alterations in brain structure, function, and connectivity. Our findings emphasize the importance of adequate micronutrient intake for healthy neurodevelopment and may support the development of intervention strategies aimed at preventing neurodevelopmental disorders by addressing micronutrient deficiencies.

Background and aims: The prevalence of hyperuricemia (HUA) and metabolic syndrome (MetS) in the Zhuang minority had not been examined. We aimed to determine the prevalence of HUA and MetS, and explore the interrelationship among the serum uric acid to creatinine (SUA/Cr) ratio, MetS, and its components. Methods and results: A cross-sectional study was conducted with structured questionnaire and physical examination based on the Zhuang minority cohort. A Structural Equation Model was performed to examine the hypothesis link between the SUA/Cr ratio, MetS, and its components. 10,902 aged 35-74 years Zhuang minority adults were included. The total prevalence of HUA and MetS was 17.5% and 23.7%, respectively. The SUA/Cr ratio had a positive effect on MetS (the standardized coefficient Or was 0.311 in males and 0.401 in females). The SUA/Cr ratio was positively associated with obesity (Or = 0.215), dyslipidemia (Or = 0.177), and high blood pressure (Or = 0.034) in males and was positively associated with obesity (Or = 0.303), dyslipidemia (Or = 0.162), and hyperglycemia (Or = 0.036) in females. Conclusions: The prevalence of HUA in the aged 35-74 years Zhuang minority adults was high while the prevalence of MetS was relatively low. As HUA is an earlier -onset metabolic disorder and the SUA/Cr ratio had a positive effect on MetS and its components, the prevention measures of MetS should be strengthened. And the SUA/Cr ratio can be used as an early warning sign to implement the intervention measures of MetS. (c) 2023 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

BackgroundAnimal studies have shown that exposure to REEs can cause severe liver damage, but evidence from population studies is still lacking. Therefore, we investigated the relationship between REEs concentrations in urine and liver function in the population.MethodsWe conducted a cross-sectional study on 1024 participants in Nanning, China. An inductively coupled plasma mass spectrometer (ICP-MS) was used to detect the concentrations of 12 REEs in urine. The relationship between individual exposure to individual REE and liver function was analyzed by multiple linear regression. Finally, the effects of co-exposure to 5 REEs on liver function were assessed by a weighted sum of quartiles (WQS) regression model and a Bayesian kernel machine regression (BKMR) model.ResultsThe detection rate of 5 REEs, lanthanum (La), cerium (Ce), praseodymium (Pr), neodymium (Nd), and dysprosium (Dy), is greater than 60%. After multiple factor correction, La, Ce, Pr, Nd, and Dy were positively correlated with serum ALP, Ce, Pr, and Nd were positively correlated with serum AST, while Ce was negatively correlated with serum TBIL and DBIL. Both WQS and BKMR results indicate that the co-exposure of the 5 REEs is positively correlated with serum ALP and AST, while negatively correlated with serum DBIL. There were potential interactions between La and Ce, La and Dy in the association of co-exposure of the 5 REEs with serum ALP.ConclusionsThe co-exposure of the 5 REEs was positively correlated with serum ALP and AST, and negatively correlated with serum DBIL.

Background: Growing evidence has demonstrated the role of ambient air pollutants in driving diabetes incidence. However, epidemiological evidence linking ozone (O3) exposure to diabetes risk has been scarcely studied in Zhuang adults in China. We aimed to investigate the associations of long-term exposure to O3 with diabetes prevalence and fasting plasma glucose (FPG) and estimate the mediating role of liver enzymes in Zhuang adults. Methods: We recruited 13 843 ethnic minority adults during 2018-2019 based on a cross-sectional study covering nine districts/counties in Guangxi. Generalized linear mixed models were implemented to estimate the relationships between O3 exposure and diabetes prevalence and FPG. Mediation effect models were constructed to investigate the roles of liver enzymes in the associations of O3 exposure with diabetes prevalence and FPG. Subgroup analyses were conducted to identify potential effect modifications. Results: Long-term exposure to O3 was positively associated with diabetes prevalence and FPG levels in Zhuang adults, with an excess risk of 7.32% (95% confidence interval [CI]: 2.56%, 12.30%) and an increase of 0.047 mmol L-1 (95% CI: 0.032, 0.063) for diabetes prevalence and FPG levels, respectively, for each interquartile range (IQR, 1.18 μg m-3) increment in O3 concentrations. Alanine aminotransferase (ALT) significantly mediated 8.10% and 29.89% of the associations of O3 with FPG and diabetes prevalence, respectively, and the corresponding mediation proportions of alkaline phosphatase (ALP) were 8.48% and 30.00%. Greater adverse effects were observed in females, obese subjects, people with a low education level, rural residents, non-clean fuel users, and people with a history of stroke and hypertension in the associations of O3 exposure with diabetes prevalence and/or FPG levels (all P values for interaction < 0.05). Conclusion: Long-term exposure to O3 is related to an increased risk of diabetes, which is partially mediated by liver enzymes in Chinese Zhuang adults. Promoting clean air policies and reducing exposure to environmental pollutants should be a priority for public health policies geared toward preventing diabetes.

Metal-organic frameworks (MOFs) are promising adsorbents for legacy per-/polyfluoroalkyl substances (PFASs), but they are being replaced by emerging PFASs. The effects of varying carbon chains and functional groups of emerging PFASs on their adsorption behavior on MOFs require attention. This study systematically revealed the structure-adsorption relationships and interaction mechanisms of legacy and emerging PFASs on a typical MOF MIL-101(Cr). It also presented an approach reflecting the average electronegativity of PFAS moieties for adsorption prediction. We demonstrated that short-chain or sulfonate PFASs showed higher adsorption capacities (μmol/g) on MIL-101(Cr) than their long-chain or carboxylate counterparts, respectively. Compared with linear PFASs, their branched isomers were found to exhibit a higher adsorption potential on MIL-101(Cr). In addition, the introduction of ether bond into PFAS molecule (e.g., hexafluoropropylene oxide dimeric acid, GenX) increased the adsorption capacity, while the replacement of CF2 moieties in PFAS molecule with CH2 moieties (e.g., 6:2 fluorotelomer sulfonate, 6:2 FTS) caused a decrease in adsorption. Divalent ions (such as Ca2+ and SO42−) and solution pH have a greater effect on the adsorption of PFASs containing ether bonds or more CF2 moieties. PFAS adsorption on MIL-101(Cr) was governed by electrostatic interaction, complexation, hydrogen bonding, π-CF interaction, and π-anion interaction as well as steric effects, which were associated with the molecular electronegativity and chain length of each PFAS. The average electronegativity of individual moieties (named Me) for each PFAS was estimated and found to show a significantly positive correlation with the corresponding adsorption capacity on MIL-101(Cr). The removal rates of major PFASs in contaminated groundwater by MIL-101(Cr) were also correlated with the corresponding Me values. These findings will assist with the adsorption prediction for a wide range of PFASs and contribute to tailoring efficient MOF materials.