Application of Machine Learning Methods to Predict the Air Half-Lives of Persistent Organic Pollutants
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PROVIDER: S-EPMC10673120 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
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Project description:Genome-wide DNA methylation profiling was performed in human mesenchymal stem cells (hMSCs) differentiated into adipocytes (day 10) while being continuously exposed to either one of three different persistent organic pollutants (POPs), namely TCDD, PFOS, and TBT. The Illumina Infinium 450K Human DNA methylation Beadchip v1.2 was used to measure DNA methylation of unexposed differentiated adipocytes and compared to POP-exposed differentiated adipocytes. Our aims were to 1) measure genome-wide DNA methylation changes upon POP exposure during adipocyte differentiation in primary hMSCs and 2) investigate the relationship between DNA methylation and gene expression regulation after POP-exposure in a panel of 84 adipocyte-related genes.
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Project description:We sought to investigate the relationship between maternal preconception exposures to persistent organic pollutants (POPs) and pregnancy complications, gestational diabetes (GDM) and gestational hypertension. Data from 258 (51%) women with human chorionic gonadotropin (hCG) confirmed pregnancies reaching ≥24weeks gestation, from a prospective cohort of 501 couples who discontinued contraception to attempt pregnancy, were analyzed. Preconception concentrations of 9 organochlorine pesticides (OCPs) and 10 polybrominated diphenyl ethers (PBDEs) were quantified in serum. In separate multiple logistic regression models of self-reported physician diagnosed outcomes: GDM (11%) and gestational hypertension (10%), chemicals were natural log-transformed and rescaled by their standard deviation (SD). Models were adjusted for serum lipids, and then adjusted for age, body mass index, race, and smoking. Models were additionally adjusted for the sum of the remaining POPs in each chemical class. Women's serum concentration of PBDE congener 153 (PBDE-153) was positively associated with an increased odds of GDM per SD increase in log-transformed concentration, for unadjusted (OR=1.36, 95%CI: 1.02-1.81), a priori adjusted (OR=1.38, 95% CI: 1.03-1.86) and with the sum of remaining PBDEs (OR=1.79, 95% CI: 1.18, 2.74) models. Our findings suggest that at environmentally relevant concentrations, maternal exposure to POPs prior to conception may contribute to increased chance of developing GDM.
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Project description:Scavenging of gas- and aerosol-phase organic pollutants by rain is an efficient wet deposition mechanism of organic pollutants. However, whereas snow has been identified as a key amplification mechanism of fugacities in cold environments, rain has received less attention in terms of amplification of organic pollutants. In this work, we provide new measurements of concentrations of perfluoroalkyl substances (PFAS), organophosphate esters (OPEs), and polycyclic aromatic hydrocarbons (PAHs) in rain from Antarctica, showing high scavenging ratios. Furthermore, a meta-analysis of previously published concentrations in air and rain was performed, with 46 works covering different climatic regions and a wide range of chemical classes, including PFAS, OPEs, PAHs, polychlorinated biphenyls and organochlorine compounds, polybromodiphenyl ethers, and dioxins. The rain-aerosol (KRP) and rain-gas (KRG) partition constants averaged 105.5 and 104.1, respectively, but showed large variability. The high field-derived values of KRG are consistent with adsorption onto the raindrops as a scavenging mechanism, in addition to gas-water absorption. The amplification of fugacities by rain deposition was up to 3 orders of magnitude for all chemical classes and was comparable to that due to snow. The amplification of concentrations and fugacities by rain underscores its relevance, explaining the occurrence of organic pollutants in environments across different climatic regions.
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Project description:To better understand the influence of land use and meteorological parameters on air pollutants, we deployed passive air samplers in 15 regions with different land use in eastern Austria. The samplers consisted of polyurethane PUF and polyester PEF filter matrices, which were analyzed for 566 substances by gas-chromatography/mass-spectrometry. In a previous article, we highlighted a widespread contamination of ambient air with pesticides that depends on the surrounding land use and meteorological parameters. Here we report that, in addition to agricultural pesticides, eight other substances were frequently detected in ambient air: Nitrapyrin, a nitrification inhibitor used to increase nitrogen use efficiency of fertilizers and banned in Austria since 1993; biocides against insects (DEET and transfluthrin) used mainly outside agriculture; piperonyl butoxide (PBO), a synergist mixed into pesticide formulations; and four industrially used polychlorinated biphenyls (PCBs), long banned worldwide. Concentrations of the detected substances were positively related to air temperature, but only slightly related to agricultural land use in the sampler's vicinity. The city center showed the highest concentrations of biocides, PCBs and PBO, but also medium concentrations of nitrapyrin. Four sites had no air contamination with these substances; including two national parks dominated by grassland or forest, but also two sites with mixed land use. The potential human toxicity of the detected substances based on globally harmonized hazard classifications was high: seven substances had specific organ toxicity, six were cancerogenic, and two were acutely toxic; however, several substances had incomplete information of hazard profiles. Moreover, all substances were acutely and chronically toxic to aquatic life. We recommend that substances of different origins be included in the air pollution monitoring portfolio to comprehensively assess the potential hazards to humans and the environment.
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Project description:In this study, machine learning (ML) algorithms were employed to predict the pseudo-1st-order reaction rate constants for the sonochemical degradation of aqueous organic pollutants under various conditions. A total of 618 sets of data, including ultrasonic, solution, and pollutant characteristics, were collected from 89 previous studies. Considering the difference between the electrical power (Pele) and calorimetric power (Pcal), the collected data were divided into two groups: data with Pele and data with Pcal. Eight input variables, including frequency, power density, pH, temperature, initial concentration, solubility, vapor pressure, and octanol-water partition coefficient (Kow), and one target variable of the degradation rate constant, were selected for ML. Statistical analysis was conducted, and outliers were determined separately for the two groups. ML models, including random forest (RF), extreme gradient boosting (XGB), and light gradient boosting machine (LGB), were used to predict the pseudo-1st-order reaction rate constants for the removal of aqueous pollutants. The prediction performance of the ML models was evaluated using different metrics, including the root mean squared error (RMSE), mean absolute error (MAE), and R squared (R2). A significantly higher prediction performance was obtained using data without outliers and augmented data. Consequently, all the applied ML models could be used to predict the sonochemical degradation of aqueous pollutants, and the XGB model showed the highest accuracy in predicting the rate constants. In addition, the power density and frequency were the most influential factors among the eight input variables in prediction with the Shapley additive explanation (SHAP) values method. The degradation rate constants of the two pollutants over a wide frequency range (20-1,000 kHz) were predicted using the trained ML model (XGB) and the prediction results were analyzed.
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Project description:Exposure to persistent organic pollutants (POPs), such as dichlorodiphenyltrichloroethane (DDT) and polychlorinated biphenyls (PCBs), has historically been linked to population collapses in wildlife. Despite international regulations, these legacy chemicals are still currently detected in women of reproductive age, and their levels correlate with reduced ovarian reserve, longer time-to-pregnancy, and higher risk of infertility. However, the specific modes of action underlying these associations remain unclear. Here, we examined the effects of five commonly occurring POPs − hexachlorobenzene (HCB), p,p'-dichlorodiphenyldichloroethylene (DDE), 2,3,3′,4,4′,5-hexachlorobiphenyl (PCB156), 2,2′,3,4,4′,5,5′-heptachlorobiphenyl (PCB180), perfluorooctane sulfonate (PFOS) − and their mixture on human ovaries in vitro. We exposed human ovarian cancer cell lines COV434, KGN, and PA1 as well as primary ovarian cells for 24 h, and ovarian tissue containing unilaminar follicles for 6 days. RNA-sequencing of samples exposed to concentrations covering epidemiologically relevant levels revealed significant gene expression changes related to central energy metabolism in the exposed cells, indicating glycolysis, oxidative phosphorylation, fatty acid metabolism, and reactive oxygen species as potential shared targets of POP exposures in ovarian cells. Alpha-enolase (ENO1), lactate dehydrogenase A (LDHA), cytochrome C oxidase subunit 4I1 (COX4I1), ATP synthase F1 subunit alpha (ATP5A), and glutathione peroxidase 4 (GPX4) were validated as targets through qPCR in additional cell culture experiments in KGN. In ovarian tissue cultures, we observed significant effects of exposure on follicle growth and atresia as well as protein expression. All POP exposures, except PCB180, decreased unilaminar follicle proportion and increased follicle atresia. Immunostaining confirmed altered expression of LDHA, ATP5A, and GPX4 in the exposed tissues. Moreover, POP exposures modified ATP production in KGN and tissue culture. In conclusion, our results demonstrate the disruption of cellular energy metabolism as a novel mode of action underlying POP-mediated interference of follicle growth in human ovaries.
2024-05-03 | GSE252776 | GEO
Project description:BackgroundNumerous methods exist to analyze complex environmental mixtures in health studies. As an illustration of the different uses of mixture methods, we employed methods geared toward distinct research questions concerning persistent organic chemicals (POPs) as a mixture and leukocyte telomere length (LTL) as an outcome.MethodsWith information on 18 POPs and LTL among 1,003 U.S. adults (NHANES, 2001-2002), we used unsupervised methods including clustering to identify profiles of similarly exposed participants, and Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) to identify common exposure patterns. We also employed supervised learning techniques, including penalized, weighted quantile sum (WQS), and Bayesian kernel machine (BKMR) regressions, to identify potentially toxic agents, and characterize nonlinear associations, interactions, and the overall mixture effect.ResultsClustering separated participants into high, medium, and low POP exposure groups; longer log-LTL was found among those with high exposure. The first PCA component represented overall POP exposure and was positively associated with log-LTL. Two EFA factors, one representing furans and the other PCBs 126 and 118, were positively associated with log-LTL. Penalized regression methods selected three congeners in common (PCB 126, PCB 118, and furan 2,3,4,7,8-pncdf) as potentially toxic agents. WQS found a positive overall effect of the POP mixture and identified six POPs as potentially toxic agents (furans 1,2,3,4,6,7,8-hxcdf, 2,3,4,7,8-pncdf, and 1,2,3,6,7,8-hxcdf, and PCBs 99, 126, 169). BKMR found a positive linear association with furan 2,3,4,7,8-pncdf, suggestive evidence of linear associations with PCBs 126 and 169, and a positive overall effect of the mixture, but no interactions among congeners.ConclusionsUsing different methods, we identified patterns of POP exposure, potentially toxic agents, the absence of interaction, and estimated the overall mixture effect. These applications and results may serve as a guide for mixture method selection based on specific research questions.
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Project description:Kidney function decreases with age. A potential mechanistic explanation for kidney and allograft half-life has evolved through the realization that linear reduction in glomerular podocyte density could drive progressive glomerulosclerosis to impact both native kidney and allograft half-lives. Predictions from podometrics (quantitation of podocyte parameters) were tested using independent pathologic, functional, and outcome data for native kidneys and allografts derived from published reports and large registries. With age, native kidneys exponentially develop glomerulosclerosis, reduced renal function, and end-stage kidney disease, projecting a finite average kidney life span. The slope of allograft failure rate versus age parallels that of reduction in podocyte density versus age. Quantitative modeling projects allograft half-life at any donor age, and rate of podocyte detachment parallels the observed allograft loss rate. Native kidneys are designed to have a limited average life span of about 100-140 years. Allografts undergo an accelerated aging-like process that accounts for their unexpectedly short half-life (about 15 years), the observation that older donor age is associated with shorter allograft half-life, and the fact that long-term allograft survival has not substantially improved. Podometrics provides potential readouts for these processes, thereby offering new approaches for monitoring and intervention. National Institutes of Health.
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Project description:A realistic mixture of Persistant Organic Pollutants (POPs), as found in the blood of a Scandinivian population, was used at realistic concentrations to evaluate developmental, behavioral, and gene expression modifications in zebrafish larvae.
2023-03-31 | GSE208019 | GEO
Project description:This data article presents mean serum concentrations (wet weight and lipid standardized) of 32 persistent organic pollutants (POPs) detected in >75% of participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study across levels of POPs scores, and their corresponding coefficients of determination. POPs scores were calculated as: A) the sum of each participant's log-transformed POPs concentrations (∑ of log Pops], or B) as the sum of the participants' log-transformed concentrations of each POP divided by the groups' standard deviation of the corresponding log-transformed POP (POPs summary score. Scores were calculated for both wet weight and lipid standardized concentrations and for all 32 POPs and for PCBs and organochlorine pesticides separately. POPs summary scores analyses were used in the article "Organochlorine pesticides and polychlorinated biphenyls (PCBs) in early adulthood and blood lipids over a 23-year follow-up" [Suarez-Lopez et al., 2018].
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