Despite the abundance of epidemiological evidence concerning the association between pesticide exposure and adverse health outcomes including acute childhood leukemia (AL), evidence remains inconclusive, and is inherently limited by heterogeneous exposure assessment and multiple statistical testing. We performed a literature search of peer-reviewed studies, published until January 2021, without language restrictions. Summary odds ratios (OR) and 95% confidence intervals (CI) were derived from stratified random-effects meta-analyses by type of exposure and outcome, exposed populations and window of exposure to address the large heterogeneity of existing literature. Heterogeneity and small-study effects were also assessed. We identified 55 eligible studies (n = 48 case-control and n = 7 cohorts) from over 30 countries assessing >200 different exposures of pesticides (n = 160,924 participants). The summary OR for maternal environmental exposure to pesticides (broad term) during pregnancy and AL was 1.88 (95%CI: 1.15–3.08), reaching 2.51 for acute lymphoblastic leukemia (ALL; 95%CI: 1.39–4.55). Analysis by pesticide subtype yielded an increased risk for maternal herbicide (OR: 1.41, 95%CI: 1.00–1.99) and insecticide (OR: 1.60, 95%CI: 1.11–2.29) exposure during pregnancy and AL without heterogeneity (p = 0.12–0.34). Meta-analyses of infant leukemia were only feasible for maternal exposure to pesticides during pregnancy. Higher magnitude risks were observed for maternal pesticide exposure and infant ALL (OR: 2.18, 95%CI: 1.44–3.29), and the highest for infant acute myeloid leukemia (OR: 3.42, 95%CI: 1.98–5.91). Overall, the associations were stronger for maternal exposure during pregnancy compared to childhood exposure. For occupational or mixed exposures, parental, and specifically paternal, pesticide exposure was significantly associated with increased risk of AL (ORₚₐᵣₑₙₜₐₗ: 1.75, 95%CI: 1.08–2.85; ORₚₐₜₑᵣₙₐₗ: 1.20, 95%CI: 1.07–1.35). The epidemiological evidence, supported by mechanistic studies, suggests that pesticide exposure, mainly during pregnancy, increases the risk of childhood leukemia, particularly among infants. Sufficiently powered studies using repeated biomarker analyses are needed to confirm whether there is public health merit in reducing prenatal pesticide exposure.

The solar ultraviolet radiation (UVR) at national, provincial and county levels in Iran during 2005–2019 were determined based on Ozone Monitoring Instrument (OMI) dataset. The temporal (annual and monthly) trends and spatial distributions of the UVR in terms of erythemally weighted daily dose (EDD), erythemally weighted irradiance at local solar noon time (EDR), and UV index and the major factors influencing the spatiotemporal trends were analyzed. The population-weighted average values of EDD, EDR, and UV index in Iran were respectively 3631 J/m², 176.3 mW/m², 7.1 in 2005 and rose by 0.22% per year to 3744 J/m², 181.7 mW/m², and 7.3, respectively in 2019, but the annual trend was not statistically significant. The EDD in Iran during the study period exhibited the highest monthly average value in June (6339 J/m²) and the lowest one in December (1263 J/m²). The solar UVA/UVB ratios at the national level during 2005–2019 were considerably lower in summer. The EDD provincial average values in the study period were in the range of 2717 (Gilan) to 4424 J/m² (Fars). The spatiotemporal variations of the solar UVR parameters were well described by the linear models as a function of cloud optical thickness (COT), ozone column amount, surface albedo, latitude, and altitude (R² > 0.961, p value < 0.001) and the temporal changes of the solar UVR parameters were mainly caused by the COT. The results indicated that non-burning exposure to solar UVR in summer can be more efficient for vitamin D synthesis due to higher contribution of UVB in the solar UVR. The spatial distributions and temporal trends should be considered to determine the optimal duration, time and condition of exposure to the solar UVR for the public and occupational training and public health measures.

The water and sediments of urban rivers are spatially heterogeneous because of the influence of environmental and anthropogenic factors. However, the spatial and functional diversity of bacterial communities in urban river sediments are unclear. We investigated the spatial distribution of microbial compositions in sediments in Qingdao section of the Dagu River, and the effects of sediment physiochemical properties on the variation were explored. Among the seven heavy metals analyzed, only the average concentration of Cd significantly exceeded the safety limit for sediments. The detailed composition and spatial distribution of bacterial communities fluctuated substantially between sites along the river. Bacterial datasets were separated into three clusters according to the environmental characteristics of sampling areas (the urbanized, scenic, and intertidal zones). For the urbanized zone, Acidobacteria, Firmicutes, Gemmatimonadetes, Bacteroidetes, and Gammaproteobacteria were significantly enriched, implying the effects of human activity. In the intertidal zone, Alphaproteobacteria and Deltaproteobacteria were significantly enriched, which are associated with S redox processes, as in the marine environment. Variation partitioning analysis showed that the amount of variation independently explained by variables of Na, Al, total S and Zn was largest, followed by sediment nutrients, while heavy metals and pH explained independently 13% and 9% of the variance, respectively. Overall, microbial structures in the Dagu River exhibited spatial variation and functional diversity as a result of natural and anthropogenic factors. The results will enable the prediction of the changes in urban river ecosystems that maintain their ecological balance and health.

Small extracellular vesicles (sEV) are small lipid bilayer particles released by cells. sEV have been shown to play critical roles in intercellular communication. Di (2-ethylhexyl) phthalate (DEHP), widely used as plasticizers, has been detected in the environment and human beings. DEHP was found to exist in the air particles and showed pulmonary toxicity. However, there’s little knowledge about the role of sEV in mediating the toxicity of DEHP-induced lung toxicity. We hypothesized that sEV mediated the toxicity of DEHP through their cargo. To validate this, lung epithelial cells (A549) were exposed to various concentrations (0, 0.2, 2 and 20 μM) of DEHP for 48 h. sEV extracted from DEHP-exposed A549 cells were cultured with unexposed A549 cells. Results showed that DEHP induced the epithelial-mesenchymal transition (EMT) and promoted the migration and invasion ability of A549 cells. The number of released sEV significantly increased in the culture media in DEHP-exposed groups compared to unexposed groups. The sEV can enter the unexposed A549 cells and enhance its EMT and the ability of migration and invasion. Treatment with GW4869 in DEHP-exposed A549 cells almost blocked the effects of DEHP-elicited sEV in normal A549 cells. Sequencing and functional analysis showed that the enrichment of significantly differentially expressed sEV miRNAs were related to tumor etiology. MiR-26a-5p was significantly enriched in DEHP-elicited sEV. Inhibition of miR-26a-5p in DEHP-exposed cells led to the downregulation of miR-26a-5p in sEV, and thus abolished the effects of DEHP-elicited sEV in normal A549 cells, whereas overexpression of miR-26a-5p restored the effects. The transcription factors twist is one of the downstream targets in the effects of sEV-miR-26a-5p on EMT process. In all, our results showed that DEHP exposure promoted the secretion of miR-26a-5p in sEV, which subsequently enhanced the EMT, migration and invasion ability in neighboring normal cells via the twist.

The importance of microplastic (MPs) contamination in marine environments is reflected by increasing number of studies in fish species. Some even dedicated to the toxicological effects from the ingestion. Microplastics (MPs) and their trace metal composition were examined in the muscle and intestine of five commercially important fish species (i.e., Sufflamen fraenatus, Heniochus acuminatus, Atropus atropos, Pseudotriacanthus and Leiognathus brevirostris) from Thoothukudi at the Gulf of Mannar coast in south India. The abundance and morphology of MPs (size, shape, and texture) in muscle and intestinal were investigated by micro-Fourier Transform Infrared Spectroscopy (μ-FT-IR) and atomic force microscope (AFM). ICP-OES was used to investigate the adsorption/leaching of trace metals in microplastics in order to assess health risk for adults and children. Particles of 100–250 μm and white color dominated, and the mean abundances (items/100 g) of total MPs were more in Pseudotriacanthus (muscle: 51.2; intestine: 50.1) compared to Heniochus acuminatus (muscle: 9.6; intestine: 15), Leiognathus brevirostris (muscle: 12; intestine: 13.2) and Atropus atropus (muscle: 15.2; intestine: 44.1). Polyethylene (35.3%), polypropylene (27.2%), polyamide (nylon) (22.2%) and fiber (15.3%) represented the MPs present in muscles, and polyamide (nylon) (30.2%), polyethylene (28.1%), polypropylene (25.9%), and fiber (15.8%) composed the intestine MPs. We estimated possible consumption of 121–456 items of MPs/week by adults and about 19–68 items of MPs/week by children by considering the sizes of safe meals. Zn, Cu, Mn and Cr in these fish species reflected influence of the sewage waste. However, the non-carcinogenic risk evaluated through EDI, THQ, HI, and CR did not suggest any immediate health problem for the consumers.

Maintaining thyroid homeostasis during pregnancy is vital for fetal development. The few studies that have investigated associations between metal exposure and gestational thyroid function have yielded mixed findings. To evaluate the association of exposure to a mixture of toxic metals with thyroid parameters in 824 pregnant women from the Rhea birth cohort in Crete, Greece. Concentrations of three toxic metals [cadmium (Cd), antimony (Sb), lead (Pb)] and iodine were measured in urine using inductively coupled plasma mass spectrometry and thyroid hormones [Thyroid Stimulating Hormone (TSH), free thyroxine (fT4), and free triiodothyronine (fT3)] were measured in serum in early pregnancy. Associations of individual metals with thyroid parameters were assessed using adjusted regression models, while associations of the metal mixture with thyroid parameters were assessed using Bayesian Kernel Machine Regression (BKMR).Women with high (3rd tertile) concentrations of urinary Cd, Sb and Pb, respectively, had 13.3 % (95%CI: 2.0 %, 23.2 %), 12.5 % (95%CI: 1.8 %, 22.0 %) and 16.0 % (95%CI: 5.7 %, 25.2 %) lower TSH compared to women with low concentrations (2nd and 1st tertile). In addition, women with high urinary Cd had 2.2 % (95%CI: 0.0 %, 4.4 %) higher fT4 and 4.0 % (95%CI: −0.1 %, 8.1 %) higher fT3 levels, and women with high urinary Pb had 4 % (95%CI: 0.2 %, 8.0 %) higher fT3 levels compared to women with low exposure. The negative association of Cd with TSH persisted only when iodine sufficiency was unfavorable. BKMR attested that simultaneous exposure to toxic metals was associated with decreased TSH and increased fT3 and revealed a potential synergistic interaction of Cd and Pb in association with TSH. The present results suggest that exposure to toxic metals even at low levels can alter gestational thyroid homeostasis.

Exposure to ambient air pollution is associated with maternal and child health. Some air pollutants exhibit similar behavior in the atmosphere, and some interact with each other; thus, comprehensive assessments of individual air pollutants are required. In this study, we developed national-scale monthly models for six air pollutants (NO, NO₂, SO₂, O₃, PM₂.₅, and suspended particulate matter (SPM)) to obtain accurate estimates of pollutant concentrations at 1 km × 1 km resolution from 2010 through 2015 for application to the Japan Environment and Children's Study (JECS), which is a large-scale birth cohort study. We developed our models in the land use regression framework using random forests in conjunction with kriging. We evaluated the model performance via 5-fold location-based cross-validation. We successfully predicted monthly NO (r² = 0.65), NO₂ (r² = 0.84), O₃ (r² = 0.86), PM₂.₅ (r² = 0.79), and SPM (r² = 0.64) concentrations. For SO₂, a satisfactory model could not be developed (r² = 0.45) because of the low SO₂ concentrations in Japan. The performance of our models is comparable to those reported in previous studies at similar temporal and spatial scales. The model predictions in conjunction with the JECS will reveal the critical windows of prenatal and infancy exposure to ambient air pollutants, thus contributing to the development of environmental policies on air pollution.

The on-road remote sensing test was conducted in Zhengzhou to obtain a large dataset of ammonia emissions from in-use vehicles. The ammonia emission characteristics and high-emitter vehicles of different manufacture years, vehicles with different emission standards, and vehicles with different types of other fuel vehicles were analysed. The results show that the average ammonia emission concentration obtained through remote sensing tests fluctuated after the initial reduction. The ammonia emission factors generally range from 0.30 to 0.47 g/kg, 0.34–0.50 g/kg and 0.29–0.60 g/kg for gasoline vehicles, diesel vehicles and other fuel vehicles respectively. Improving the emission standards of new vehicles has a direct role in reducing exhaust pollution from in-use vehicles. However, after the China III emission standard, the ammonia emission level showed a stable trend and no obvious downward trend. The distributions of ammonia emission rates were highly skewed as the dirtiest 10% of vehicles emitted much higher emissions than other vehicles. In the group with the highest emissions, the emissions from other fuel vehicles were lower than those from gasoline and diesel vehicles. However, the percentage of high-emitters decreased with newer emission standards for vehicles. The results indicate that remote sensing test technology will be very effective in screening vehicles with high ammonia emissions. However, some clean vehicles can be exempted from annual inspection through remote sensing test technology. Finally, based on the comprehensive analysis of big data from remote sensing, the ammonia emissions of diesel vehicles and other fuel vehicles cannot be ignored.

Satellite-derived aerosol optical depth (AOD) has been widely used to predict ground-level fine particulate matter (PM₂.₅) concentrations, although its utility can be limited due to missing values. Despite recent attempts to address this issue by imputing missing satellite AOD values, the uncertainty associated with the AOD imputation and its impacts on PM₂.₅ predictions have been understudied. To fill this gap, we developed a missing data imputation model for the AOD derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and PM₂.₅ prediction models using several machine learning methods. We also examined how the uncertainty associated with the imputed AOD and a choice of machine learning algorithm were propagated to PM₂.₅ predictions. The application of the proposed imputation model to the data from New York State in the U.S. achieved a superior performance than those related studies, with a cross-validated R² of 0.94 and a Root Mean Square Error of 0.017. We also found that there was considerable uncertainty in PM₂.₅ predictions associated with the use of imputed AOD values, although it was not as high as the uncertainty from the machine learning algorithms used in PM₂.₅ prediction models. We concluded that the quantification of uncertainties for both AOD imputation and its propagation to AOD-based PM₂.₅ prediction is necessary for accurate and reliable PM₂.₅ predictions.