Associations between seminal plasma metals/metalloids and semen quality: A cross-sectional study.

Exposure to metals/metalloids is reported to potentially influence semen quality. While most studies have focused on single metal impacts, the link between exposure to multiple metals and semen quality has remained less explored. The study aimed to investigate the effects of both individual and mixed metal/metalloid exposure on semen quality. A total of 330 men were recruited from three reproductive centers in eastern China. Seminal plasma levels of 25 metals/metalloids and sperm parameters were determined. We used the Generalized Linear Model (GLM) and Restricted Cubic Spline (RCS) to assess the relationships between single metals/metalloids and semen quality. The weighted quantile sum (WQS) models were then applied to evaluate the combined effect of all these metals/metalloids. We observed positive associations of exposure to lithium (Li), zinc (Zn), and magnesium (Mg) with an increased risk of below reference values for progressive motility and total motility using a logistic regression model (P < 0.05). Additionally, our results also revealed a significant inverse relationship between aluminum (Al) and both sperm concentration and count, while cobalt (Co) demonstrated a positive association with sperm concentration (P < 0.05). Notably, the WQS model indicated a significant positive association between exposure to metal/metalloid mixtures and the risk of abnormal progressive motility (OR: 1.57; 95%CI: 1.10, 2.24) and abnormal total motility (OR: 1.53; 95%CI: 1.06, 2.19), with this association primarily driven by Li, Mg, and Zn. In summary, our findings indicate that exposure to metal/metalloid mixtures might have an adverse effect on semen quality.

Association between exposure to multiple metals and stress urinary incontinence in women: a mixture approach.

There is limited evidence linking exposure to heavy metals, especially mixed metals, to stress urinary incontinence (SUI). This study aimed to explore the relationship between multiple metals exposure and SUI in women. The data were derived from the National Health and Nutrition Examination Survey (NHANES), 2007-2020. In the study, a total of 13 metals were analyzed in blood and urine. In addition, 5155 adult women were included, of whom 2123 (41.2%) suffered from SUI. The logistic regression model and restricted cubic spline (RCS) were conducted to assess the association of single metal exposure with SUI risk. The Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) were used to estimate the combined effect of multiple metals exposure on SUI. First, we observed that blood Pb, Hg and urinary Pb, Cd were positively related to SUI risk, whereas urinary W was inversely related by multivariate logistic regression (all p-FDR < 0.05). Additionally, a significant non-linear relationship between blood Hg and SUI risk was observed by RCS analysis. In the co-exposure models, WQS model showed that exposure to metal mixtures in blood [OR (95%CI) = 1.18 (1.06, 1.31)] and urine [OR (95%CI) = 1.18 (1.03, 1.34)] was positively associated with SUI risk, which was consistent with the results of BKMR model. A potential interaction was identified between Hg and Cd in urine. Hg and Cd were the main contributors to the combined effects. In summary, our study indicates that exposure to heavy metal mixtures may increase SUI risk in women.

Urinary antibiotic levels and risk of overweight/obesity in preschool children: A biomonitoring-based study from eastern China.

There is limited evidence linking antibiotic exposure, particularly from contaminated food or drinking water, to childhood obesity. The study aimed to investigate the association between urinary antibiotic levels and overweight/obesity in preschool children. In the case-control study, 121 overweight/obese preschoolers and 242 controls (aged 3-6 years) from eastern China were enrolled in 2022 based on age, sex, and study site matching. Overweight/obesity was determined using body mass index (BMI) and weight for height (WFH) criteria derived from national data. A total of 50 antibiotics from 8 categories were analyzed using ultra-performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS). We identified major dietary patterns using principal component analysis (PCA) and examined the associations of antibiotic exposure with childhood overweight/obesity using multivariate logistic regression. Twenty-four individual antibiotics were detected in more than 10 % of the samples, and overall detection rates were up to 100 %. Overweight/obese children had a higher exposure to veterinary antibiotics (VAs) than normal weight children. PCA analysis showed that children who were overweight/obese had higher scores of "Aquatic products preferred dietary pattern" and "Cereals preferred dietary pattern" compared to children with normal weight. Multivariate logistic regression analyses indicated that exposure to elevated levels of deoxytetracycline (OR: 1.72; 95 %CI: 1.00-2.93) and quinolones (OR: 1.63; 95 %CI: 1.04-2.57) was significantly related to an increased risk of BMI-based overweight/obesity. Quinolones exposure was also significantly associated with WFH-based overweight/obesity, primarily in boys. After adjustment for all covariates, higher exposure to ofloxacin (of the quinolones) was significantly related to overweight/obesity in girls. Exposure to certain antibiotics, especially quinolones, may increase the risk of overweight/obesity in preschoolers. More prospective, well-designed studies are needed to clarify these findings.

Exposure to metal mixtures and young children's growth and development: A biomonitoring-based study in Eastern China.

Exposure to metal mixtures may affect children's health but the conclusions are controversial. We aimed to investigate the associations of metal mixture exposure with children's physical and behavioral development. 15 metals were detected in the urine samples of 278 preschoolers aged 3-6 years from eastern China. Multiple linear models and restricted cubic splines were used to evaluate dose-response relationships between single metal and children's physical and behavioral development. The Bayesian Kernel Machine Regression (BKMR) models, the weighted quantile sum (WQS) models and Quantile G-Computation were applied to evaluate the joint effects of metal mixtures. The results showed that arsenic (As) was negatively associated with z score of height for age (HAZ) in individual-metal models [ß (95%CI): - 0.22 (-0.38, -0.06), P = 0.006]. Concerning children's behavioral development, multiple-metal models demonstrated a negative association with strontium (Sr) [ß (95%CI): - 0.82 (-1.38, -0.26), P = 0.004], and a positive association with tin (Sn) [ß (95%CI): 0.69 (0.16, 1.21), P = 0.010]. Notably, these associations remained significant or suggestive even after adjustments for multiple tests, sensitivity analyses, and application of different statistical models, including BKMR, WQS, and Quantile G-Computation. Furthermore, the study identified a negative joint effect of the metal mixture on HAZ, as demonstrated by BKMR and Quantile G-Computation models, with As playing an irreplaceable role in this observed impact. In summary, exposure to As appears to have adverse effects on HAZ, while exposure to Sn may hinder children's behavioral development. Conversely, exposure to Sr may have a protective effect on children's behavioral development. Additionally, the combined impact of metal mixtures is implicated in potentially impairing children's physical development, particularly in terms of HAZ.

Impacts of the COVID-19 pandemic on early pregnancy outcomes among women undergoing frozen-thawed embryo transfer: a retrospective cohort study.

The effect of COVID-19 pandemic on early pregnancy outcomes among women undergoing frozen-thawed embryo transfer (FET) remains unclear. We aimed to evaluate whether early pregnancy outcomes were altered in patients undergoing FET during the pandemic. In this retrospective cohort study, women conceived through FET in 2016-2021 from two hospitals in China were included. The early pregnancy outcomes were compared using Logistic regression model, including biochemical pregnancy rate (BPR), clinical pregnancy rate (CPR), and early pregnancy loss rate (EPLR). A total of 16,669 (67.2%) and 6,113 (26.8%) FET cycles enrolled before and during the pandemic, respectively. Univariate analyses showed that women undergoing FET during the pandemic had significantly increased BPR (72.9% vs. 69.7%) and CPR (59.5% vs. 55.0%), and significantly decreased EPLR (13.7% vs. 16.7%) compared to pre-pandemic (all P < 0.001). Moreover, after adjustment, the results were in accordance with univariate analysis for CPR [adjusted OR (95%CI) = 1.08 (1.01-1.14)] and EPLR [adjusted OR (95%CI) = 0.82 (0.73-0.91)], while the statistical significance between BPR and the pandemic disappeared. In summary, women conceived by FET did not have a reduced possibility of clinical pregnancy and a higher risk of early pregnancy loss during the pandemic compared with the pre-pandemic.

Serum levels of polychlorinated biphenyls and polybrominated diphenyl ethers in early pregnancy and their associations with gestational diabetes mellitus.

Polychlorinated Biphenyls (PCBs) and Polybrominated Diphenyl Ethers (PBDEs) are extensively present in humans and may disturb glucose metabolism during pregnancy. However, previous reports on the associations between PCBs/PBDEs levels and gestational diabetes mellitus (GDM) have been inconsistent. We performed a nested case-control study to measure the serum levels of 6 PCB and 7 PBDE congeners in early pregnancy, and to assess their associations with GDM risk and blood glucose levels. Totally, 208 serum samples (104 GDM cases and 104 controls) were included based on a prospective cohort which was carried out in Jiangsu province, China, from 2020 to 2022. The results showed that PCB-153 was the major PCB congener, whereas PBDE-47 was the predominant PBDE congener. The continuous concentrations of PCB-153, PBDE-28, and total PCB were significantly related to an increased risk of GDM, with adjusted ORs (95%CI) of 1.25 (1.04-1.50), 1.19 (1.02-1.39), and 1.37 (1.05-1.79), respectively. Potential dose-response relationships were also observed between serum levels of PCB-153 (P = 0.011), PBDE-28 (P = 0.028), total PCB (P = 0.048), and total PCB/PBDE (P = 0.010) and GDM risk. Moreover, PCB-153, PBDE-28 and total PCB levels were positively related to 1-h OGTT blood glucose (adjusted ßPCB-153: 0.14, 95%CI: 0.00-0.28; adjusted ßPBDE-28: 0.20, 95%CI: 0.08-0.32; adjusted ßtotal PCB: 0.30, 95%CI: 0.09-0.50), whereas none of the PCBs/PBDEs were statistically related to fasting blood glucose and 2-h OGTT blood glucose (all P > 0.05). Further meta-analysis also supported the association of PCBs exposure with GDM risk. Our study provides further evidence that PCBs/PBDEs exposure may increase GDM risk during pregnancy.

Urinary antibiotic concentrations in preschool children from eastern China and health risk assessment.

Despite limited biomonitoring studies suggesting extensive antibiotic exposure in general population, the body burden of antibiotics in young children and their potential health risks remain unclear. To assess the antibiotic exposure levels in young children, 508 preschoolers aged 3-6 years were recruited from eastern China in 2022, and a total of 50 representative antibiotics from 8 categories, including 17 human antibiotics (HAs), 4 antibiotics preferred as HAs (PHAs), 16 veterinary antibiotics (VAs), and 13 antibiotics preferred as VAs (PVAs), were analyzed by UPLC-MS/MS. Hazard quotient (HQ) and hazard index (HI) were calculated to evaluate the health risks, and multivariate logistic regression was applied to examine diet with antibiotic exposure. Our results showed that there were 41 antibiotics detected in children's urine, and the overall detection frequency was as high as 100%. Sulfonamides, macrolides, ß-lactams, quinolones, and azoles were the predominant categories of antibiotic detected. Among the studied children, 6.5% had a sum of estimated daily intake (EDI) of all VAs and PVAs larger than 1 µg/kg/day. Notably, 10.0% of the children had a microbiological HI value exceeding 1, primarily contributed by ciprofloxacin. Children with higher consumption of seafood had a relatively increased exposure to multiple categories of antibiotics, including HAs, VAs, quinolones, azoles, and others. Principal component analysis suggested that "Aquatic products and viscera preferred dietary pattern" scores were positively correlated with the exposure levels of ciprofloxacin (OR: 1.23; 95% CI: 1.02-1.47) and carbadox (OR: 1.32; 95% CI: 1.10-1.59), and a relatively increased exposure of PHAs was realized in children with higher "Meat-egg preferred dietary pattern" scores (OR: 1.24; 95% CI: 1.03-1.50). In conclusion, there was a widespread exposure to antibiotics among preschool children from eastern China, and children who consumed more animal-derived foods may had an increased exposure to antibiotics.

Environmental pollutants exposure and gestational diabetes mellitus: Evidence from epidemiological and experimental studies.

Except for known sociodemographic factors, long-term exposure to environmental pollutants has been shown to contribute to the development of gestational diabetes mellitus (GDM), but the conclusions remain controversial. To provide a comprehensive overview of the association between environmental pollutants and GDM, we performed a systematic review and meta-analysis. Several electronic databases (PubMed, Embase, Web of Science, Medline and Cochrane) were searched for related epidemiological and experimental studies up to September 2022. For epidemiological studies, a meta-analysis was carried out to appraise the effect of environmental pollutants, including polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), per- and polyfluoroalkyl substances (PFASs), phenols, phthalates (PAEs), polybrominated diphenyl ethers (PBDEs) and parabens exposure on GDM. Moreover, we also summarized possible biological mechanisms linking pollution exposure and GDM based on the included experimental studies. A total of 80 articles were enrolled, including 38 epidemiological studies and 42 experimental studies. Meta-analysis results showed that exposure to PAEs [OR (95%CI) = 1.07 (1.00, 1.14)], PFASs [OR (95%CI) = 1.10 (1.01, 1.19)], as well as PCBs [OR (95%CI) = 1.18 (1.02, 1.36)] and PBDEs [OR (95%CI) = 1.33 (1.17, 1.50)] significantly increased the risk of GDM, but no significant effects were found for phenols, OCPs, and parabens. In addition, experimental studies suggested that the potential biological mechanisms of environmental pollutants contributing to GDM may involve insulin resistance, ß-cell dysfunction, neurohormonal dysfunction, inflammation, oxidative stress, epigenetic modification, and alterations in gut microbiome. In conclusion, long-term environmental pollutants exposure may induce the development of GDM, and there may be a synergistic effect between the homologs. However, studies conducted on the direct biological link between environmental pollutants and GDM were few. More prospective studies and high-quality in vivo and in vitro experiments were needed to investigate the specific effects and mechanisms.

Maternal circulating metabolic biomarkers and their prediction performance for gestational diabetes mellitus related macrosomia.

INTRODUCTION: Gestational diabetes mellitus (GDM), a metabolism-related pregnancy complication, is significantly associated with an increased risk of macrosomia. We hypothesized that maternal circulating metabolic biomarkers differed between women with GDM and macrosomia (GDM-M) and women with GDM and normal neonatal weight (GDM-N), and had good prediction performance for GDM-M. METHODS: Plasma samples from 44 GDM-M and 44 GDM-N were analyzed using Olink Proseek multiplex metabolism assay targeting 92 biomarkers. Combined different clinical characteristics and Olink markers, LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomogram was developed based on the selected variables visually. Receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used to validate the model. RESULTS: We found 4 metabolism-related biomarkers differing between groups [CLUL1 (Clusterin-like protein 1), VCAN (Versican core protein), FCRL1 (Fc receptor-like protein 1), RNASE3 (Eosinophil cationic protein), FDR <  0.05]. Based on the different clinical characteristics and Olink markers, a total of nine predictors, namely pre-pregnancy body mass index (BMI), weight gain at 24 gestational weeks (gw), parity, oral glucose tolerance test (OGTT) 2 h glucose at 24 gw, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw, were identified by LASSO regression. The model constructed using these 9 predictors displayed good prediction performance for GDM-M, with an area under the ROC of 0.970 (sensitivity = 0.955, specificity = 0.886), and was well calibrated (P Hosmer-Lemeshow test = 0.897). CONCLUSION: The Model included pre-pregnancy BMI, weight gain at 24 gw, parity, OGTT 2 h glucose at 24 gw, HDL and LDL at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw had good prediction performance for predicting macrosomia in women with GDM.

Genome-wide identification and characterization of small auxin-up RNA (SAUR) gene family in plants: evolution and expression profiles during normal growth and stress response.

BACKGROUND: Auxin is critical to plant growth and development, as well as stress responses. Small auxin-up RNA (SAUR) is the largest family of early auxin responsive genes in higher plants. However, the function of few SAUR genes is known owing to functional redundancy among the many family members. RESULTS: In this study, we conducted a phylogenetic analysis using protein sequences of 795 SAURs from Anthoceros angustus, Marchantia polymorpha, Physcomitrella patens, Selaginella moellendorffii, Ginkgo biloba, Gnetum montanum, Amborella trichopoda, Arabidopsis thaliana, Oryza sativa, Zea mays, Glycine max, Medicago truncatula and Setaria italica. The phylogenetic trees showed that the SAUR proteins could be divided into 10 clades and three subfamilies, and that SAUR proteins of three bryophyte species were only located in subfamily III, which suggested that they may be ancestral. From bryophyta to anthophyta, SAUR family have appeared very large expansion. The number of SAUR gene in Fabaceae species was considerably higher than that in other plants, which may be associated with independent whole genome duplication event in the Fabaceae lineages. The phylogenetic trees also showed that SAUR genes had expanded independently monocotyledons and dicotyledons in angiosperms. Conserved motif and protein structure prediction revealed that SAUR proteins were highly conserved among higher plants, and two leucine residues in motif I were observed in almost all SAUR proteins, which suggests the residues plays a critical role in the stability and function of SAUR proteins. Expression analysis of SAUR genes using publicly available RNA-seq data from rice and soybean indicated functional similarity of members in the same clade, which was also further confirmed by qRT-PCR. Summarization of SAUR functions also showed that SAUR functions were usually consistent within a subclade. CONCLUSIONS: This study provides insights into the evolution and function of the SAUR gene family from bryophyta to anthophyta, particularly in Fabaceae plants. Future investigation to understand the functions of SAUR family members should employ a clade as the study unit.