Serum levels of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans in a sample of Lebanese pregnant women: The role of dietary, anthropometric, and environmental factors.

Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) are unintentionally produced, toxic environmental chemicals that persist for long years and bioaccumulate along the food chain, contaminating humans through diet. A particularly critical population subgroup is pregnant women given the adverse health effects on fetuses and newborns. Several anthropogenic sources of exposure to PCDD/Fs exist in Lebanon. Therefore, the aim of the present cross-sectional study is to measure the levels of PCDD/Fs in a sample of pregnant women in Lebanon and to explore potential associated factors. In this study, we measured serum concentrations of seven dioxins and ten furans, among 423 pregnant women recruited at delivery, using gas chromatography MS/MS. Among 269 participants, maternal sociodemographic information was collected including vicinity to landfills, incineration, pesticide use, industrial activity, and smoking. Anthropometric data were registered regarding pre-pregnancy body mass index (BMI), pre-pregnancy weight loss from restrictive diet, and gestational weight gain. Intake of major food groups generally related to PCDD/Fs was reported (fish, red meat, poultry, and dairy). Bivariate and multivariate analyses were performed to identify associations. PCDD/Fs were detected in 0 to 56.1% of the sample. Geometric mean concentrations were 75.5 (2.35) pg/g lipid and 2.25 (1.39) TEQ2005 pg/g lipid for total dioxins, and 2.66 (1.76) pg/g lipid and 0.34 (1.78) TEQ2005 pg/g lipid for total furans. Levels were relatively lower than levels previously observed in France, Germany, Mexico, Ghana, and Japan. Red meat consumption was the most consistently associated factor with a 2.38-2.57 fold increase in PCDD/F levels. Pre-pregnancy weight loss showed inverse associations with PCDD/F congeners. Vicinity to illegal incineration was also associated with a 2.32-2.43 fold increase in PCDD/F levels. In conclusion, results showed the importance of dietary, anthropometric, and environmental factors in the present sample's exposure to PCDD/Fs, in a region that contains anthropogenic sources of contamination.

Dioxins and furans maternal transfer: A study of breast milk and cord serum levels among Lebanese mothers and associations with newborn anthropometric measurements.

Dioxins and furans (PCDD/Fs) are anthropogenic pollutants that persist in the environment for long years, bioaccumulating in food & contaminating humans. In pregnancy, they can transfer through the placenta and reach the fetus, which negatively affects fetal growth. They can also reach newborns through breastfeeding. In this study, we focused on this critical subpopulation and identified the presence of PCDD/Fs among pregnant women in breast milk (n = 41) and cord serum (n = 49); we assessed the correlation between different matrices, evaluated the predictors and associations with newborn anthropometric measurements. Over 70.7 % of PCDD/Fs were detected in breast milk and 46.9-55.1 % in cord serum. Cord/maternal serum and breast milk to maternal serum ratios were > 1 with a significant positive Spearman correlation (0.669-0.729). Breast milk & maternal serum PCDD/Fs were associated inversely with age and positively with red meat intake. Cord serum PCDD/Fs were inversely associated with pre-pregnancy weight loss and passive smoking. Parity and gestational weight gain showed positive associations with Z-scores at birth. Z-score differences showed negative and positive associations with passive smoking and pre-pregnancy BMI respectively.

Maternal Serum, Cord and Human Milk Levels of Per- and Polyfluoroalkyl Substances (PFAS), Association with Predictors and Effect on Newborn Anthropometry.

BACKGROUND: The understanding of per- and polyfluoroalkyl substances (PFAS) health effects is rapidly advancing among critical populations. Therefore, the objective of this study was to assess PFAS serum levels among Lebanese pregnant women, cord serum and human milk levels, their determinants, and effects on newborn anthropometry. METHODS: We measured concentrations of six PFAS (PFHpA, PFOA, PFHxS, PFOS, PFNA and PFDA) using liquid chromatography MS/MS for 419 participants, of which 269 had sociodemographic, anthropometric, environmental and dietary information. RESULTS: The percentage of detection for PFHpA, PFOA, PFHxS and PFOS was 36.3-37.7%. PFOA and PFOS levels (95th percentile) were higher than HBM-I and HBM-II values. While PFAS were not detected in cord serum, five compounds were detected in human milk. Multivariate regression showed that fish/shellfish consumption, vicinity to illegal incineration and higher educational level were associated with an almost twice higher risk of elevated PFHpA, PFOA, PFHxS and PFOS serum levels. Higher PFAS levels in human milk were observed with higher eggs and dairy products consumption, in addition to tap water (preliminary findings). Higher PFHpA was significantly associated with lower newborn weight-for-length Z-score at birth. CONCLUSIONS: Findings establish the need for further studies, and urgent action to reduce exposure among subgroups with higher PFAS levels.

Variance-based global sensitivity analysis for rear-end crash investigation using deep learning.

Traffic accidents are rare events with inconsistent spatial and temporal dimensions; thus, accident injury severity (INJ-S) analysis faces a significant challenge in its classification and data stability. While classical statistical models have limitations in accurately modeling INJ-S, advanced machine learning methods have no apparent equations to prioritize/analyze different contributing factors to predict INJ-S levels. Also, the intercorrelations among the input factors could make the results of a typical sensitivity analysis misleading. Rear-end accidents constitute the most frequent type of traffic accidents; and therefore, their associated INJ-S need more insight investigations. To resolve all these issues, this study presents a sophisticated approach based on a deep learning paradigm combined with a Variance-Based Globa1 Sensitivity Analysis (VB/GSA). The methodology proposes a deep residual neural networks structure that utilizes residual shortcuts (i.e., connections), unlike other neural network architectures. The connections allow the DRNNs to bypass a few layers in the deep network architecture, circumventing the regular training with high accuracy problems. The Monte Carlo simulation with the aid of the trained DRNNs model was conducted to investigate the impact of each explanatory factor on the INJ-S levels based on the VB/GSA. The developed methodology was used to analyze all rear-end accidents in North Carolina from 2010 to 2017. The performance of the developed methodology was evaluated utilizing some selected representative indicators and then compared with the well-known ordered logistic regression (OLR) model. The developed methodology was found to achieve an overall accuracy of 83% and attained a superior performance, as compared with the OLR model. Furthermore, the VB/GSA analysis could identify the most significant attributes to rear-end crashes INJ-S level.

Effect of Nanoclay Particles on the Performance of High-Density Polyethylene-Modified Asphalt Concrete Mixture.

Utilizing polymers for asphalt concrete (AC) mixture modification has many drawbacks that hinder its wide implementations for roadway construction. Recently, research on employing complementary materials, such as nanomaterials, to balance negative impacts of polymers while enhancing the AC mixture's performance has received great attention. This study aimed to investigate the effect of incorporating nanoclay (NC) particles on the performance of a high-density polyethylene (HDPE)-modified AC mixture. A 60/70 asphalt binder was first modified with HDPE, and then NC particles were gradually added at a concentration of 1-4% by weight of the asphalt binder. The binders' physical characteristics, storage stability, and chemical change were scrutinized. AC mixture performance, including pseudo-stiffness, moisture damage resistance, stripping susceptibility, and rutting tendency, was investigated. A statistical analysis on the experimental results was conducted using Kruskal-Wallis and Dunn tests. Test results showed that employing NC/HDPE significantly increased penetration index and thereby enhanced binder temperature sensitivity. Moreover, it prevented oxidation action and separation and, therefore, enhanced binder storage stability. Furthermore, incorporating NC amplified pseudo-stiffness and significantly improved resistance against moisture damage and stripping of HDPE-modified mixtures. Moreover, it improved both elastic (recoverable) and plastic (unrecoverable) deformations of mixtures. The most satisfactory results were attained when incorporating 3% of NC.