We aimed to explore the effects of mixtures of lead and various metals on blood pressure (BP) and the odds of pre-hypertension (systolic blood pressure (SBP) 120–139 mmHg, and/or diastolic blood pressure (DBP) 80–89 mmHg) and hypertension (SBP/DBP ≥140/90 mmHg) among Chinese adults in a cross-sectional study. This study included 11,037 adults aged 18 years or older from the 2017–2018 China National Human Biomonitoring. Average BP and 13 metals (lead, antimony, arsenic, cadmium, mercury, thallium, chromium, cobalt, molybdenum, manganese, nickel, selenium, and tin) in blood and urine were measured and lifestyle and demographic data were collected. Weighted multiple linear regressions were used to estimate associations of metals with BP in both single and multiple metal models. Weighted quantile sum (WQS) regression was performed to assess the relationship between metal mixture levels and BP. In the single metal model, after adjusting for potential confounding factors, the blood lead levels in the highest quartile were associated with the greater odds of both pre-hypertension (odds ratio (OR): 1.56, 95% CI: 1.22–1.99) and hypertension (OR:1.75, 95% CI: 1.28–2.40) when compared with the lowest quartile. We also found that blood arsenic levels were associated with increased odds of pre-hypertension (OR:1.31, 95% CI:1.00–1.74), while urinary molybdenum levels were associated with lower odds of hypertension (OR:0.68, 95% CI:0.50–0.93). No significant associations were found for the other 10 metals. WQS regression analysis showed that metal mixture levels in blood were significantly associated with higher SBP (β = 1.56, P < 0.05) and DBP (β = 1.56, P < 0.05), with the largest contributor being lead (49.9% and 66.8%, respectively). The finding suggests that exposure to mixtures of metals as measured in blood were positively associated with BP, and that lead exposure may play a critical role in hypertension development.

Most amyotrophic lateral sclerosis (ALS) cases are sporadic (∼90%) and environmental exposures are implicated in their etiology. Large industrial facilities are permitted the airborne release of certain chemicals with hazardous properties and report the amounts to the US Environmental Protection Agency (EPA) as part of its Toxics Release Inventory (TRI) monitoring program. The objective of this project was to identify industrial chemicals released into the air that may be associated with ALS etiology. We geospatially estimated residential exposure to contaminants using a de-identified medical claims database, the SYMPHONY Integrated Dataverse®, with ∼26,000 nationally distributed ALS patients, and non-ALS controls matched for age and gender. We mapped TRI data on industrial releases of 523 airborne contaminants to estimate local residential exposure and used a dynamic categorization algorithm to solve the problem of zero-inflation in the dataset. In an independent validation study, we used residential histories to estimate exposure in each year prior to diagnosis. Air releases with positive associations in both the SYMPHONY analysis and the spatio-temporal validation study included styrene (false discovery rate (FDR) 5.4e-5), chromium (FDR 2.4e-4), nickel (FDR 1.6e-3), and dichloromethane (FDR 4.8e-4). Using a large de-identified healthcare claims dataset, we identified geospatial environmental contaminants associated with ALS. The analytic pipeline used may be applied to other diseases and identify novel targets for exposure mitigation. Our results support the future evaluation of these environmental chemicals as potential etiologic contributors to sporadic ALS risk.

Soil contamination by potentially toxic elements (PTEs) is one of the greatest threats to environmental degradation. Knowing where PTEs accumulated in soil can mitigate their adverse effects on plants, animals, and human health. We evaluated the potential of using long-term remote sensing images that reveal the bare soils, to detect and map PTEs in agricultural fields. In this study, 360 soil samples were collected at the superficial layer (0–20 cm) in a 2574 km² agricultural area located in São Paulo State, Brazil. We tested the Soil Synthetic Image (SYSI) using Landsat TM/ETM/ETM+, Landsat OLI, and Sentinel 2 images. The three products have different spectral, temporal, and spatial resolutions. The time series multispectral images were used to reveal areas with bare soil and their spectra were used as predictors of soil chromium, iron, nickel, and zinc contents. We observed a strong linear relationship (−0.26 > r > −0.62) between the selected PTEs and the near infrared (NIR) and shortwave infrared (SWIR) bands of Sentinel (ensemble of 4 years of data), Landsat TM (35 years data), and Landsat OLI (4 years data). The clearest discrimination of soil PTEs was obtained from SYSI using a long term Landsat 5 collection over 35 years. Satellite data could efficiently detect the contents of PTEs in soils due to their relation with soil attributes and parent materials. Therefore, distinct satellite sensors could map the PTEs on tropics and assist in understanding their spatial dynamics and environmental effects.

Source apportionment can be an effective tool in mitigating soil pollution but its efficacy is often limited by a lack of information on the factors that influence the accumulation of pollutants at a site. In response to this limitation and focusing on a suite of heavy metals identified as priorities for pollution control, the study established a comprehensive pollution control framework using factor identification coupled with spatial agglomeration for agricultural soils in an industrialized part of Zhejiang Province, China. In addition to elucidating the key role of industrial and traffic activities on heavy metal accumulation through implementing a receptor model, specific influencing factors were identified using a random forest model. The distance from the soil sample location to the nearest likely industrial source was the most important factor in determining cadmium and copper concentrations, while distance to the nearest road was more important for lead and zinc pollution. Soil parent materials, pH, organic matter, and clay particle size were the key factors influencing accumulation of arsenic, chromium, and nickel. Spatial auto-correlation between levels of soil metal pollution and industrial agglomeration can enable a more targeted approach to pollution control measures. Overall, the approach and results provide a basis for improved accuracy in source apportionment, and thus improved soil pollution control, at the regional scale.

Aging is a leading cause of mortality for the elderly and DNA methylation age is reported to be predictive of biological aging. However, few studies have investigated the associations between multiple metals exposure and accelerated aging in the elderly. We performed a pilot study of 288 elderly participants aged 50–115 years and measured genome-wide DNA methylation and 22 blood metals concentrations. Measures of DNA methylation age were estimated using CpGs from Illumina HumanMethylation EPIC BeadChip. Linear mixed regression and Bayesian kernel machine regression (BKMR) models were used to estimate the individual and overall associations between multiple metals and accelerated methylation aging. Single metal models revealed that each 1-standard deviance (SD) increase in log-transformed vanadium, cobalt, nickel, zinc, arsenic, and barium was associated with a −2.256, −1.318, 1.004, −1.926, 1.910 and −1.356 changes in ΔAge, respectively; meanwhile, for aging rate, the change was −0.019, −0.013, 0.010, −0.018, 0.023, and −0.012, respectively (all P < 0.05). The BKMR models showed reverse U-shaped associations of the overall metals mixture with ΔAge and aging rate. Downward trends of ΔAge and aging rate were observed for increasing quantiles of essential metals mixture, but upward trends were observed for non-essential metals mixture. Further individual analysis of the BKMR revealed that the 95% confidence interval of ΔAge and aging rate associated with vanadium, zinc, and arsenic did not cross 0, when other metals concentrations set at 25th, 50th, and 75th percentile. Our findings suggest reverse U-shaped associations of the overall metals mixture with accelerated methylation aging for the first time, and vanadium, zinc, and arsenic may be major contributors driving the associations.

In this report, we investigated the accumulation of heavy metals in the lizard Microlophus atacamensis, in three coastal areas of the Atacama Desert, northern Chile. We captured reptiles in a non-intervened area (Parque Nacional Pan de Azúcar, PAZ), an area of mining impact (Caleta Palitos, PAL) and an active industrial zone (Puerto de Caldera, CAL). Our methods included a non-lethal sampling of reptiles’ tails obtained by autotomy and a few sacrificed animals to perform a stomach contents analysis. The concentrations of lead, copper, nickel, zinc and cadmium were measured by atomic absorption spectrophotometry in both soil and prey and compared to those recorded in the lizards’ tails. Data obtained from lizard tails captured in PAL showed significantly high concentrations of Pb, Cu, Ni, and Zn compared to the other two sites PAZ and CAL. We did not find statistically significant differences among PAZ, PAL and CAL soils, probably due to the similar geological composition of the sites. However, the regional background values for Pb indicate contamination or at least metal enrichment in soils of the three sites, for Cu the global background values indicate contamination for the three sites, and for Cd both the regional and global backgroud values show high values. The analysis of the stomach content showed differences in the food sources of the lizards among the sites studied. The concentration of heavy metal in lizard tissues versus prey delivered values of the Trophic Transfer Factor higher than one (1), suggesting that food may be a primary source of metals in the tissues of M. atacamensis. Calculations of the Bioaccumulation Factor (BAF) and the Ecological Risk (IR) resulted in values higher than one (1) indicating the relevance of this process in the sites studied. In this article, we report relationships between environmental contaminants, mainly putative preys, and concentrations found in lizard tails, which is more substantial in areas with historical heavy metal contamination such as PAL where the non-lethal technique developed in this research suggests a process of metal bioaccumulation in M. atacamensis.

Oral bioaccessibility (BAc) is a surrogate for the bioavailability (BAv) of a broad range of substances, reflecting the value that the approach offers for assessing oral exposure and risk. BAc is generally considered to have been validated as a proxy for oral BAv for the important soil contaminants Pb, Cd, and As. Here, using literature data for Ni BAc and BAv, we confirmed that Ni BAc (gastric only, with HCl mimicking stomach conditions) is a conservative measure of BAv for the oral exposure pathway. Measured oral BAv of Ni in soil was shown to be 50–100 times less than the simplest oral BAc estimates (%BAv = 0.012(%BAc) - 0.023 (r = 0.701, 95%CI [0.456, 0.847], n = 30)) in rats, demonstrating a significant conservatism for exposure assessment. The relationship between the oral BAv and BAc of nickel sulfate hexahydrate (NSHH) was comparable to that of soil, with measured oral BAv of NSHH (1.94%) being a small fraction of NSHH gastric BAc (91.1%). BAc and BAv reflect the underlying Ni speciation of the sample, with the bioaccessible leaching limits being represented by the highly soluble Ni salts and the poorly soluble Ni monoxide, and the environmental (e.g. soil properties) or gastric (e.g. food present) conditions. BAc has potential utility for chemical classification purposes because pure Ni substances can be grouped by %BAc values(using standardized methodologies for the relevant exposure routes), these groupings reflecting the underlying chemistry and speciation of the samples of substances tested here, with 0.008% %BAc for alloys (SS304, SS316, Inconel, Monel), <1% in green NiO and Ni metal massives, 0.9–23.6% for Ni powders, 9.8–22.7% for Ni sulfides, 26.3–29.6% for black oxidic Ni, and 82–91% for the soluble Ni salts. Oral BAc provides realistic yet conservative estimates of BAv for the hazard classification and risk assessment of Ni substances.

Six ecotypes of Typha domingensis Pers. Jahlar (E₁), Sheikhupura (E₂), Sahianwala (E₃), Gatwala (E₄), Treemu (E₅) and Knotti (E₆) from different ecological regions were collected to evaluate the leaf anatomical and biochemical attributes under different levels of salinity and nickel stress viz; L₀ (control), L₁ (100 mM + 50 mg kg⁻¹), L₂ (200 mM + 100 mg kg⁻¹) and L₃ (300 mM + 150 mg kg⁻¹). Presence of salt and Ni in rooting medium consistently affected growth, anatomical and physio-biochemical attributes in all Typha ecotypes. Discrete anatomical modifications among ecotypes such as reduced leaf thickness, increased parenchyma area, metaxylem cell area, aerenchyma formation and improved metaxylem vessels were recorded with increasing dose of salt and Ni. The minimum anatomical damages were recorded in E₁ and E₆ ecotypes. In all ecotypes, progressive perturbations in ionic homeostasis (Na⁺, K⁺, Cl⁻, N) due to salt and metal toxicity were evident along with reduction in photosynthetic pigments. Maximum enhancement in Catalase (CAT), Superoxide dismutase (SOD), Peroxidase (POD) and modulated Malondialdehyde (MDA) activity was recorded in E₁ and E₆ as compared to other ecotypes. Accumulation of large amounts of metabolites such as total soluble sugars, total free amino acids content in Jahlar, Knotti, Treemu and Sahianawala ecotypes under different levels of salt and Ni prevented cellular damages in T. domingensis Pers. The correlation analysis exhibited a close relationship among different levels of salinity and Ni with various plant attributes. PCA-Biplot verified our correlational analysis among various attributes of Typha ecotypes. An obvious separation of Typha characters in response to different salinity and Ni levels was exhibited by PC1. We recommend that genetic potential of T. domingensis Pers. To grow under salt and Ni stresses must be investigated and used for phytoremediation and reclamation of contaminated soil.

Antarctic melt streams are important ecosystems that increasingly face contaminant pressures from anthropogenic sources. Metal contaminants are often reported in the limno-terrestrial environment but their speciation is not well characterised, making environmental risk assessments difficult. This paper characterises labile metal concentrations in five melt streams and three shallow lakes around the Casey and Wilkes research stations in East Antarctica using chemical extracts and field deployments of diffusive gradients in thin-film (DGT) samplers. An acute toxicity test with field-collected Ceratadon purpeus and taxonomic identification of diatoms in melt streams were used to infer environmental risk. Copper and zinc were the most labile metals in the melt streams. DGT-labile copper concentrations were up to 3 μg Cu L⁻¹ in melt-stream waters but not labile below the sediment-water interface. DGT-labile zinc concentrations were consistent above and below the sediment-water interface at concentrations up to 14 μg Zn L⁻¹ in four streams, but one stream showed evidence of zinc mineralisation in the sediment with a flux to overlying and pore waters attributed to the reductive dissolution of iron and manganese oxides. Other metals, such as chromium, nickel, and lead were acid-extractable from the sediments, but not labile in pore waters or overlying waters. All streams had unique compositions of freshwater diatoms, but one had particularly reduced diversity and richness, which correlated to metal contamination and sediment physico-chemical properties such as a finer particle size. In laboratory bioassays with field-collected samples of the Antarctic moss C. purpeus, there was no change in photosynthetic efficiency following 28-d exposure to 700, 900, 1060, or 530 μg L⁻¹ of cadmium, copper, nickel, and zinc, respectively. This study shows that microorganisms such as diatoms may be at greater risk from contaminants than mosses, and highlights the importance of geochemical factors controlling metal lability.

The Pearl River Estuary (PRE) is the largest estuary in southern China and under high metal stress. In the present study, we employed an integrated method of transcriptomics and proteomics to investigate the ecotoxicological effects of trace metals on the Hong Kong oyster Crassostrea hongkongensis. Three oyster populations with distinct spatial distributions of metals were sampled, including the Control (Station QA, the lowest metal levels), the High Cd (Station JZ, the highest Cd), and the High Zn–Cu–Cr–Ni (Station LFS, with the highest levels of zinc, copper, chromium, and nickel). Dominant metals in oysters were differentiated by principal component analysis (PCA), and theirgene and protein profiles were studied using RNA-seq and iTRAQ techniques. Of the 2250 proteins identified at both protein and RNA levels, 70 proteins exhibited differential expressions in response to metal stress in oysters from the two contaminated stations. There were 8 proteins altered at both stations, with the potential effects on mitochondria and endoplasmic reticulum by Ag. The genotoxicity, including impaired DNA replication and transcription, was specifically observed in the High Cd oysters with the dominating influence of Cd. The structural components (cytoskeleton and chromosome-associated proteins) were impaired by the over-accumulated Cu, Zn, Cr, and Ni at Station LFS. However, enhanced tRNA biogenesis and exosome activity might help the oysters to alleviate the toxicities resulting from their exposure to these metals. Our study provided comprehensive information on the molecular changes in oysters at both protein and RNA levels in responding to multi-levels of trace metal stress.