Assessing urinary phenol and paraben mixtures in pregnant women with and without gestational diabetes mellitus: a case-control study

Prior studies have identified the associations between environmental phenol and paraben exposures and increased risk of gestational diabetes mellitus (GDM), but no study addressed these exposures as mixtures. As methods have emerged to better assess exposures to multiple chemicals, our study aimed to apply Bayesian kernel machine regression (BKMR) to evaluate the association between phenol and paraben mixtures and GDM. This study included 64 GDM cases and 237 obstetric patient controls from the University of Oklahoma Medical Center. Mid-pregnancy spot urine samples were collected to quantify concentrations of bisphenol A (BPA), benzophenone-3, triclosan, 2,4-dichlorophenol, 2,5-dichlorophenol, butylparaben, methylparaben, and propylparaben. Multivariable logistic regression was used to evaluate the associations between individual chemical biomarkers and GDM while controlling for confounding. We used probit implementation of BKMR with hierarchical variable selection to estimate the mean difference in GDM probability for each component of the phenol and paraben mixtures while controlling for the correlation among the chemical biomarkers. When analyzing individual chemicals using logistic regression, benzophenone-3 was positively associated with GDM [adjusted odds ratio (aOR) per interquartile range (IQR) = 1.54, 95% confidence interval (CI) 1.15, 2.08], while BPA was negatively associated with GDM (aOR 0.61, 95% CI 0.37, 0.99). In probit-BKMR analysis, an increase in z-score transformed log urinary concentrations of benzophenone-3 from the 10th to 90th percentile was associated with an increase in the estimated difference in the probability of GDM (0.67, 95% Credible Interval 0.04, 1.30), holding other chemicals fixed at their medians. No associations were identified between other chemical biomarkers and GDM in the BKMR analyses. We observed that the association of BPA and GDM was attenuated when accounting for correlated phenols and parabens, suggesting the importance of addressing chemical mixtures in perinatal environmental exposure studies. Additional prospective investigations will increase the understanding of the relationship between benzophenone-3 exposure and GDM development

Urinary total arsenic and arsenic methylation capacity in pregnancy and gestational diabetes mellitus: A case-control study

Previous studies suggest arsenic exposure may increase the risk of gestational diabetes mellitus (GDM). However, prior assessments of total arsenic concentrations have not distinguished between toxic and nontoxic species. Our study aimed to investigate the relationships between inorganic arsenic exposure, arsenic methylation capacity, and GDM. Sixty-four cases of GDM and 237 controls were analyzed for urinary concentrations of inorganic arsenic species and their metabolites (arsenite (As3), arsenate (As5), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA)), and organic forms of arsenic. Inorganic arsenic exposure was defined as the sum of inorganic and methylated arsenic species (iSumAs). Methylation capacity indices were calculated as the percentage of inorganic arsenic species [iAs% = (As3 + As5)/iSumAs, MMA% = MMA/iSumAs, and DMA% = DMA/iSumAs]. Multivariable logistic regression was performed to evaluate the association between inorganic arsenic exposure, methylation capacity indices, and GDM. We did not observe evidence of a positive association between iSumAs and GDM. However, women with GDM had an increased odds of inefficient methylation capacity when comparing the highest and lowest tertiles of iAs% (adjusted odds ratio (aOR) = 1.48, 95% CI 0.58–3.77) and MMA% (aOR = 1.95 (95% CI 0.81–4.70) and a reduced odds of efficient methylation capacity as indicated by DMA% (aOR = 0.62 (95% CI 0.25–1.52), though the confidence intervals included the null value. While the observed associations with arsenic methylation indices were imprecise and warrant cautious interpretation, the direction and magnitude of the relative measures reflected a pattern of lower detoxification of inorganic arsenic exposures among women with GDM

Plasmonics in the visible domain for a one-dimensional truncated photonic crystal terminated by graphene: sensing beyond Dirac point's approximation

Visible surface plasmon resonances (SPRs) could be excited by TE wave polarization in one-dimensional photonic crystals (PCs) coated by a graphene layer under the Kretschmann configuration. In this work, the plasmonic Bloch wave properties beyond Dirac points in a one-dimensional graphene-based photonic sensing structure have been numerically studied. We demonstrate that emergent plasmonic dips in the reflectance spectra of the suggested photonic device in the visible region exhibit tunable characteristics upon modulation of the chemical potential and the hopping parameter. The sensitivity of the sensor in the visible domain has been numerically evaluated and also was compared with those considering the surface plasmon resonances in the terahertz regime

A STABLE SIMPLE SEQUENCE REPEAT MARKER FOR RESISTANCE TO WHITE MOULD IN TOBACCO

White mould, caused by Golovinomyces cichoracearum, is a major fungal disease of tobacco. Breeding for resistance to white mould is slow due to the intensive labour needed in artificial screening and the huge effect of the environment. In order to improve selection efficiency, molecular markers need to be identified to help in the rapid selection of germplasm resistant to white mould. The purpose of this study was, therefore, to identify the neutral, simple sequence repeat markers that can assist breeders in selecting for resistant plants. Two resistant parental lines XZ and STNCB, and three susceptible parental lines XSR, K51 and T71, were used in this study. Backcrosses of the hybrid from XZ and XSR were grown in a greenhouse, and DNA was extracted for molecular analysis. Eight simple sequence repeat markers and ten inter-simple sequence repeat markers were used. These markers were screened on the parental lines and the backcross generations for the differences between resistant (score 1) and susceptible (score 5) material. Single marker analysis was done using a t-test and significant (P<0.001) differences were found between the means of resistant and susceptible plants based on the marker PT30021. Marker PT30021 showed linkage to the white mould resistance gene, and thus managed to distinguish between resistant and susceptible materials in parental and advanced generations. Locus PT30021 has the potential of being used to identify white mould resistant germplasm in marker assisted backcrossing