Assessment of radio-activation using spectroscopy in medical linear accelerators.

In radiotherapy, when photon energy exceeding 8 MV is utilized, photoneutrons can activate the components within the gantry of the linear accelerator (linac). At the end of the linac's lifecycle, radiation workers are tasked with its dismantling and disposal, potentially exposing them to unintentional radiation. This study aims to identify and measure the radioisotopes generated by this activation through spectroscopy, and to evaluate the effective dose rate. We selected nine medical linacs, considering various factors such as manufacturer (Siemens, Varian, and Elekta), model, energy, period of operation, and workload. We identified the radionuclides in the linac head by employing an in situ high-purity germanium (HPGe) detector. Spectroscopy and dose-rate measurements were conducted post-shutdown. We also measured the dose rates at the beam-exit window following irradiation with 10 MV and 15 MV photon beams. As a result of the spectroscopy, we identified approximately 20 nuclides including those with half-lives of 100 days or longer, such as 54Mn, 60Co, 65Zn, 122Sb, and 198Au. The dose rate measurements after 10 MV irradiation decreased to the background level in 10 min. By contrast, on 15 MV irradiation, the dose rate was 628 nSv/h after 10 min and decreased to 268 nSv/h after 1.5 hours. It was confirmed that the difference in the level of radiation and the type of nuclide depends on the period of use, energy, and workload. However, the type of nuclide does not differ significantly between the linacs. It is necessary to propose appropriate guidelines for the safety of workers, and disposal/move-install should be planned while taking into consideration the equipment's energy usage rate.

Assessment of two non-invasive techniques for measuring turbulent benthic fluxes in a shallow lake.

Benthic fluxes refer to the exchange rates of nutrients and other compounds between the water column and the sediment bed in aquatic ecosystems. Their quantification contributes to our understanding of aquatic ecosystem functioning. Near-bed hydrodynamics plays an important role at the sediment-water interface, especially in shallow lakes, but it is poorly considered by traditional measuring techniques of flux quantification, such as sediment incubations. Thus, alternative sampling techniques are needed to characterize key benthic fluxes under in-situ hydrodynamic conditions. This study aimed to evaluate the performance of two promising methods: relaxed eddy accumulation (REA) and mass transfer coefficient (MTC). We applied them in a hyper-eutrophic shallow lake to measure the fluxes of ammonium, phosphate, iron, and manganese ions. For the first time, REA revealed hourly nutrient flux variations, indicating a strong lake biogeochemical dynamics at short time-scales. Daily average fluxes are of similar orders of magnitude for REA and MTC for ammonium (24 and 42 mmol m2 d-1), manganese (1.0 and 0.8), and iron (0.8 and 0.7) ions. They are one order of magnitude higher than fluxes estimated from sediment incubations, due to the difficulty in reproducing in-situ oxygen and hydrodynamic conditions in the laboratory. Although the accuracy of both techniques needs to be improved, the results revealed their potential: REA follows the short-term biogeochemical dynamics of sediments, while MTC could be widely used for lake monitoring because of its simpler implementation.

Risk assessment and strontium isotopic tracing of potentially toxic metals in creek sediments around a uranium mine, China.

The contamination of creek sediments near industrially nuclear dominated site presents significant environmental challenges, particularly in identifying and quantifying potentially toxic metal (loid)s (PTMs). This study aims to measure the extent of contamination and apportion related sources for nine PTMs in alpine creek sediments near a typical uranium tailing dam from China, including strontium (Sr), rubidium (Rb), manganese (Mn), lithium (Li), nickel (Ni), copper (Cu), vanadium (V), cadmium (Cd), zinc (Zn), using multivariate statistical approach and Sr isotopic compositions. The results show varying degrees of contamination in the sediments for some PTMs, i.e., Sr (16.1-39.6 mg/kg), Rb (171-675 mg/kg), Mn (224-2520 mg/kg), Li (11.6-78.8 mg/kg), Cd (0.31-1.38 mg/kg), and Zn (37.1-176 mg/kg). Multivariate statistical analyses indicate that Sr, Rb, Li, and Mn originated from the uranium tailing dam, while Cd and Zn were associated with abandoned agricultural activities, and Ni, Cu, and V were primarily linked to natural bedrock weathering. The Sr isotope fingerprint technique further suggests that 48.22-73.84% of Sr and associated PTMs in the sediments potentially derived from the uranium tailing dam. The combined use of multivariate statistical analysis and Sr isotopic fingerprint technique in alpine creek sediments enables more reliable insights into PTMs-induced pollution scenarios. The findings also offer unique perspectives for understanding and managing aqueous environments impacted by nuclear activities.

Semi-quantitative health risk assessment of heavy metal dust exposure among nail technicians using the SQRA technique and Monte Carlo simulation.

Nail technology, including the application of artificial nails and nail care, is a developing sector of the global beauty industry. Nail technicians are exposed to a variety of chemical substances through inhalation, as they spend extended periods of time in close proximity to these materials. This study aimed to evaluate the semi-quantitative health risk of dust-containing heavy metals among nail technicians. This analytical descriptive study employed the risk assessment method provided by the Singapore Occupational Health Department to evaluate the health hazards of lead, cadmium, nickel, chromium, and manganese. Dust samples from nail filing were collected from the respiratory zone of 20 nail technicians following the NIOSH 7300 method. The samples were analyzed using ICP-OES instrumentation. Monte Carlo simulation was utilized to characterize the risk and its uncertainties. Manganese and cadmium had the highest and lowest mean concentrations, respectively. The risk scores of the metals ranked from highest to lowest were as follows: Ni>Cr>Cd>Mn>Pb. All five metals had risk rankings below 2.8, signifying a minimal risk level. Sensitivity analysis using Spearman's correlation coefficient demonstrated a positive relationship between concentration, daily hours of exposure, and the number of workdays per week with the risk score (RR) and exposure level (ER). Conversely, the variable of weekly working hours (W) showed a negative correlation with these parameters. Despite the low-risk level of the examined metals, continuous exposure and potential long-term effects on nail technicians warrant preventive measures. Recommendations include implementing local exhaust ventilation systems, using table fans, establishing work-rest cycles, wearing N95 dust masks, and using reputable and high-quality nail polishes.

Inhalation exposure to toxic heavy metals in nail salon technicians and health risk assessment using Monte Carlo simulation.

OBJECTIVE: Nail salons offer a developing and diverse occupation for many women, especially the new generation. Due to the increasing apprehension surrounding heavy metals in dust caused by filing nails containing dried nail polish, the present study was designed aimed to health risk assessment of heavy metals in breathing zone of nail salon technicians (NSTs). METHODS: This is a cross-sectional study that was conducted in NSTs. The concentration of Cadmium (Cd), Lead (Pb), Nickel (Ni), Chromium (Cr) and Manganese (Mn)in breathing zone of 20 NSTs was determined using ICP-OES. RESULTS: The metal concentrations were in the following order: Mn > Pb > Ni > Cr > Cd with corresponding arithmetic mean values of0.008, 0.0023, 0.0021, 0.001 and 0.0006 mg m-3, respectively, which are exceeded the recommended levels stated in the indoor air guidelines. The average lifetime carcinogenic risk (LCR) for Cr, Cd, Ni and Pb was calculated 0.0084, 0.00054, 0.00026 and 1.44 E - 05, respectively. The LCR values of all metals (except Pb) exceeded the acceptable level set by the USEPA. The mean of Hazard quotients (HQ) for Mn, Cd, Cr, Ni and Pb were calculated to be23.7, 4.74, 2.19, 0.51 and 0.0.24, respectively. The sensitivity analysis showed that, the exposure frequency (EF) for Cr and Ni had the strong effects on generation of both LCR and HQ. Furthermore, the concentrations of Mn, Cd and Pb had strong impacts on the HQ generation and the concentration of Cd and Pb had main effects on LCR generation. CONCLUSION: To effectively reduce pollutant concentration, it is recommended to install a ventilation system near nail salon work tables and conduct continuous monitoring and quality control of nail products.

Assessment of the oxidative stress intensity and the integrity of cell membranes under the manganese nanoparticles toxicity in wheat seedlings.

A response to manganese nanoparticles was studied in seedlings of two wheat cultivars and a model system of plant cell membranes. Nanoparticles at concentrations of 125 and 250 mg/ml were applied foliar. The application of NPs enhanced the content of Mn in plant cells, indicating its penetration through the leaf surface. The stressful effect in the plant cells was estimated based on changes in the activity of antioxidant enzymes, content of chlorophylls and starch. MnNPs evoked no significant changes in the leaf morphology, however, an increase in enzyme activity, starch accumulation, and a decrease in chlorophyll synthesis indicated the stress occurrence. Moreover, a rise in the electrokinetic potential of the chloroplast membrane surface and the reconstruction of their hydrophobic parts toward an increase in fatty acid saturation was found.

Assessment of heavy metals in rainfall as an indicator of air pollution from Erbil Steel Factory in Iraq.

The goal of the current study is to evaluate the heavy metal rainfall contamination in the vicinity brought on by the Erbil Steel Factory in Iraq during the study period. The study's findings revealed the concentration of all studied heavy metals in the precipitation near and around the factory is significantly higher than that of the rural area of Barzan village which is used as a control site. The average concentration of the metals is in descending order manganese (Mn) > lead (Pb) > iron (Fe) > arsenic (As) > cobalt (Co) > selenium (Se) > mercury (Hg) > and cadmium (Cd) for the polluted site. The geo-accumulation index (I-geo) of the heavy metal Mn in the rainfall around the steel factory site is 6.28 > 5 which indicates extreme contamination. While the Igeo values of Cd, As, and Fe are 4.87, 4.54, and 4.04 > 4 that indicate heavy to extreme contamination, for Pb, 3.80 > 3 indicates moderate to heavy contamination, Cd 1.68 > 1 indicates moderate contamination, Hg 0.46 > 0 indicates uncontaminated to moderate contamination, and Se - 0.36 < 0 indicates uncontaminated. The pollution load index (PLI) of the rainwater around the steel factory site is 13.46 > 1, demonstrating that the area is highly metal-contaminated.

Assessment of human health risk from potentially toxic elements and predicting groundwater contamination using machine learning approaches.

The Rooppur Nuclear Power Plant (RNPP) at Ishwardi, Bangladesh is planning to go into operation within 2024 and therefore, adjacent areas of RNPP is gaining adequate attention from the scientific community for environmental monitoring purposes especially for water resources management. However, there is a substantial lack of literature as well as environmental datasets for earlier years since very little was done at the beginning of the RNPP's construction phase. Therefore, this study was conducted to assess the potential toxic elements (PTEs) contamination in the groundwater and its associated health risk for residents at the adjacent part of the RNPP during the year of 2014-2015. For the purposes of achieving the aim of the study, groundwater samples were collected seasonally (dry and wet season) from nine sampling sites and afterwards analyzed for water quality indicators such as temperature (Temp.), pH, electrical conductivity (EC), total dissolved solid (TDS), total hardness (TH) and for PTEs including Iron (Fe), Manganese (Mn), Copper (Cu), Lead (Pb), Chromium (Cr), Cadmium (Cd) and Arsenic (As). This study adopted the newly developed Root Mean Square water quality index (RMS-WQI) model to assess the scenario of contamination from PTEs in groundwater whereas the human health risk assessment model was utilized to quantify the risk of toxicity from PTEs. In most of the sampling sites, PTEs concentration was found higher during the wet season than the dry season and Fe, Mn, Cd and As exceeded the guideline limit for drinking water. The RMS score mostly classified the groundwater in terms of PTEs contamination into "Fair" condition. The non-carcinogenic risks (expressed as Hazard Index-HI) revealed that around 44% and 89% of samples for adults and 67% and 100% of samples for children exceeded the threshold limit set by USEPA (HI > 1) and possessed risks through the oral pathway during dry and wet season, respectively. Furthermore, the calculated cumulative HI score was found higher for children than the adults throughout the study period. In terms of carcinogenic risk (CR) from PTEs, the magnitude of risk decreased following the pattern of Cr > As > Cd. Although the current study is based on old dataset, the findings might serve as a baseline for monitoring purposes to reduce future hazardous impact from the power plant.

Noninvasive Assessment of Kidney Injury by Combining Structure and Function Using Artificial Intelligence-Based Manganese-Enhanced Magnetic Resonance Imaging.

Contrast-enhanced magnetic resonance imaging (MRI) is seriously limited in kidney injury detection due to the nephrotoxicity of clinically used gadolinium-based contrast agents. Herein, we propose a noninvasive method for the assessment of kidney injury by combining structure and function information based on manganese (Mn)-enhanced MRI for the first time. As a proof of concept, the Mn-melanin nanoprobe with good biocompatibility and excellent T1 relaxivity is applied in MRI of a unilateral ureteral obstruction mice model. The abundant renal structure and function information is obtained through qualitative and quantitative analysis of MR images, and a brand new comprehensive assessment framework is proposed to precisely identify the degree of kidney injury successfully. Our study demonstrates that Mn-enhanced MRI is a promising approach for the highly sensitive and biosafe assessment of kidney injury in vivo.

Probabilistic risk assessment for determining nonessential metals in commercial infant formula products in Taiwan.

During the early months of life, infant formula plays a crucial role as a primary source of both food and essential nutrients for infants, serving as a replacement for or supplement to breast milk. However, nonessential metals in infant formulas are a concern because infants are highly vulnerable to chemical exposure. The aim of this study was to investigate infant exposure to nonessential metals in infant formula products in Taiwan and assess the associated health risks. In this study, concentrations of arsenic (As), barium (Ba), cadmium (Cd), manganese (Mn), lead (Pb), and vanadium (V) in 45 formula products for 0-1-year-old infants were determined by inductively coupled plasma mass spectrometry. The mean As, Ba, Cd, Mn, Pb, and V concentrations were 6.42, 280, 3.72, 1425, 20.4, and 21.9 µg/kg, respectively. According to our probabilistic simulation of the estimated daily intake of metals, the proportion of hazard quotients exceeding one was 7.69% for As and 3.29% for Mn, and that of hazard index (HI) values exceeding 1 was >17% for metals. Arsenic had the largest HI contribution (46.9%), followed by Mn (22.3%) and Pb (12.7%). The nonessential metals content in infant formula raises potential noncarcinogenic health concerns for infants in Taiwan. Therefore, regulations for nonessential metals must be imposed on related food products in Taiwan, with a particular focus on As and Mn.

Association between Mineral Intake and Cognition Evaluated by Montreal Cognitive Assessment (MoCA): A Cross-Sectional Study.

BACKGROUND: Mineral intake may protect against cognitive impairment (CI) and all-cause dementia, which affects a large number of adults worldwide. The aim of this study was to investigate the association between mineral intake and Montreal Cognitive Assessment (MoCA), which is a sensitive and specific test. METHODS: In total, 201 adults were included in a cross-sectional study. They completed a three-day dietary record to estimate their average daily intake of minerals. Contributions to dietary reference intakes (DRIs) were also calculated. The participants were divided into tertiles according to their mineral intake. CI classifications were determined via the MoCA (score < 26). Apolipoprotein E (APOE) genotyping was carried out, and the patients' anthropometric measurements and physical activity, health and personal data were collected. RESULTS: The prevalence of CI in this selective sample was 54.2% (34.3% females and 19.9% males). In women, being in the third tertiles of iron and manganese intake was associated with lower odds of having CI (OR [95% CI]: 0.32 [0.11 ± 0.93]; 0.33 [0.12 ± 0.93], p < 0.05). No significant differences were observed for any of the nutrients studied in men. CONCLUSIONS: These findings suggest that a low mineral intake, especially low iron and manganese intake in women, is associated with a worse cognition as assessed by MoCA.

Manganese-enhanced magnetic resonance assessment of changes in hippocampal neural function after the treatment of radiation-induced brain injury with bone marrow mesenchymal stem cells.

The role of bone marrow mesenchymal stem cells (BMSCs) in treating radiation-induced brain injury (RIBI) is not completely understood, and assessment methods to directly characterize neurological function are lacking. In this study, we aimed to evaluate the effects of BMSCs treatment on changes in hippocampal neural function in Sprague-Dawley(SD) rats with RIBI, and to evaluate the therapeutic effect of BMSCs by manganese-enhanced magnetic resonance imaging (MEMRI). First, we assessed cognitive function after RIBI treatment with BMSCs using the Morris water maze. Next, we used MEMRI at two time points to observe the treatment effect and explore the correlation between MEMRI and cognitive function. Finally, we evaluated the expression of specific hippocampal neurofunctional proteins, the ultrastructure of hippocampal nerves, and the histological changes in the hippocampus. After BMSCs treatment of RIBI, cognitive dysfunction improved significantly, the expression of hippocampal neurofunctional proteins was increased, the integrity of the hippocampal neural structure was protected, and nerve cell survival was enhanced. The improvement in neurological function was successfully detected by MEMRI, and MEMRI was highly correlated with cognitive function and histological changes. These results suggest that BMSCs treatment of RIBI is an optional modality, and MEMRI can be used for treatment evaluation.

Assessment of heavy metals bioaccumulation in Silver Birch (Betula pendula Roth) from an AMD active, abandoned gold mine waste.

Acid mine drainage (AMD) is generally outlined as one of the largest environmental concerns, characterized by very low pH value of mine waste, heavy metals and high sulphate content. This extremely hostile environment reduces plant ability to develop and grow. Present study focuses on a silver birch (Betula pendula Roth), a pioneer species that grows on an extremely hostile gold mine waste, to investigate the bioaccumulation of rare metals (thallium (Tl) and indium (In)), as well as nine other more common heavy metals (bismuth (Bi), cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), manganese (Mn), nickel (Ni), silver (Ag) and zinc (Zn)), and to asses phytoextraction and phytostabilization potential of silver birch. Additionally, parameters determining AMD process and overall contamination (pH, electrical conductivity (EC), sulphates (SO42-), arsenic (As), iron (Fe), oxidation-reduction potential (ORP), turbidity, dissolved oxygen (DO), total dissolved solids (TDS), acidity, hardness, X-ray diffraction (XRD) and radioactivity) were determined in mine waste and drainage water samples. To assess the heavy metals bioaccumulation and mine waste status, statistical geochemical indices were determined: bioaccumulation factor (BCF), pollution load index (PLI), geochemical abundance index (GAI) and exposure index (EI). The results show that silver birch bioaccumulates the essential elements Cu, Ni, Mn and Zn, and the nonessential elements Tl (average BCF = 24.99), In (average BC = 23.01) and Pb (average BCF = 0.84). Investigated mine waste was enriched by Bi, Ag and Cd according to positive values of GAI index. Present research provides a novel insight into bioaccumulation of nonessential heavy metals in silver birches who grow on the extremely hostile mine waste, and they exhibit significant phytoremediation potential.

Magnetic signature and X-ray fluorescence for mapping trace elements in soils originating from basalt and sandstone.

The knowledge of the lithological context is necessary to interpret trace elements concentrations in the soil. Soil magnetic signature (χ) and soil X-ray fluorescence (XRF) are promising approaches in the study of the spatial variability of trace elements and the environmental monitoring of soil quality. This research aimed to assess the efficiency of measurements of χ and XRF sensors for spatial characterization of zinc (Zn), manganese (Mn), and copper (Cu) contents in soils of a sandstone-basalt transitional environment, using machine learning modeling. The studied area consisted of the Western Plateau of São Paulo (WPSP), with soils originating from sandstone and basalt. A total of 253 soil samples were collected at a depth of 0.0-0.2 m. The soils were characterized by particle size and chemical analysis: organic matter (OM), cation exchange capacity (CEC), ammonium oxalate-extracted iron (Feo), sodium dithionite-citrate-bicarbonate-extracted iron (Fed), and sulfuric acid-extracted iron (Fet). Hematite (Hm), goethite (Gt), kaolinite (Kt), and gibbsite (Gb) contents were obtained by X-ray diffraction (XRD). Magnetite (Mt) and maghemite (Mh) contents were obtained by soil χ, while trace elements contents were obtained by XRF and predicted by χ. Descriptive analysis, the test of means, and correlation were performed between attributes. Zn, Mn, and Cu contents were predicted using the machine learning algorithm random forest, and the spatial variability was obtained using the ordinary kriging interpolation technique. Landscape dissections influenced iron oxides, which had the highest contents in slightly dissected environments. Trace elements contents were not influenced by landscape dissections, demonstrating that lithological knowledge is necessary to characterize trace elements in soils. The prediction models developed through the machine learning algorithm random forest showed that χ can be used to characterize trace elements. The similar spatial pattern of trace elements obtained by XRF and χ measurements confirm the applicability of these sensors for mapping it under lithological and landscape transition, aiming for sustainable strategic planning of land use and occupation.

Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software.

Rapid urbanization, population growth, agricultural practices, and industrial activities have led to widespread groundwater contamination. This study evaluated heavy metal contamination in residential drinking water in Shiraz, Iran (2021). The analysis involved 80 groundwater samples collected across wet and dry seasons. Water quality was comprehensively assessed using several indices, including the heavy metals evaluation index (HEI), heavy metal pollution index (HPI), contamination degree (CD), and metal index (MI). Carcinogenic and non-carcinogenic risk assessments were conducted using deterministic and probabilistic approaches for exposed populations. In the non-carcinogenic risk assessment, the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) are employed. The precision of risk assessment was bolstered through the utilization of Monte Carlo simulation, executed using the R software platform. Based on the results, in both wet and dry seasons, Zinc (Zn) consistently demonstrates the highest mean concentration, followed by Manganese (Mn) and Chromium (Cr). During the wet and dry seasons, 25% and 40% of the regions exhibited high CD, respectively. According to non-carcinogenic risk assessment, Cr presents the highest CDI and HQ in children and adults, followed by Mn, As and HI values, indicating elevated risk for children. The highest carcinogenic risk was for Cr in adults, while the lowest was for Cd in children. The sensitivity analysis found that heavy metal concentration and ingestion rate significantly impact both carcinogenic and non-carcinogenic risks. These findings provide critical insights for shaping policy and allocating resources towards effectively managing heavy metal contamination in residential drinking water.

[Pollution Characteristics, Source Analysis, and Risk Assessment of Heavy Metals in the Surrounding Farmlands of Manganese Mining Area].

In order to understand the status of heavy metal pollution and the resulting ecological risk of farmland soil surrounding the manganese mining area, 174 soil samples were collected, and the heavy metals(Cu, Zn, Pb, Cr, Ni, Mn, As, and Hg) were analyzed. Principal component analysis (PCA) and the positive matrix factorization (PMF) model were used to determine the source of heavy metals in the soils. The single-factor pollution index method, geo-accumulation index method, potential ecological risk assessment method, and US EPA health risk assessment model were used to evaluate the ecological environment risk of heavy metals. The results showed that the average values of Cu, Zn, Cr, Ni, Mn, and Hg exceeded the background value of Guizhou. 100% of Zn samples and 38.86% of Cu samples exceeded the risk screening value for agricultural land soil pollution. Source analysis revealed that the main sources of soil heavy metals were mining emission, mixed agricultural activity and transportation, nature, and agricultural activities. The risk evaluation showed that Ni, Cr, Pb, and As belonged to the clean level, Hg and Cu were in a light pollution stage, Zn fell into the category of moderate contamination, and Mn reached the heavy pollution level. Cu, Zn, Pb, Cr, Ni, Mn, As, and Cd posed low potential ecological risk, while Hg caused a considerable potential ecological risk. In total, the integrated potential ecological risk of heavy metals was ranked "strong", eight types of heavy metals had carcinogenic risks and non-carcinogenic risks for children aged 0-5 years, and the main contributing factors were Cr and Mn, respectively.

Heavy metals pollution of soil in central plains urban agglomeration (CPUA), China: human health risk assessment based on Monte Carlo simulation.

The present study conducted the concentration evaluation, pollution assessment, source analysis, and risk assessment of heavy metals in the soil of the CPUA, China, to contribute to the smooth construction of urban agglomeration. Elevated levels of mean concentrations of cadmium (Cd), chromium (Cr), and copper (Cu) in the soils were shown compared to background values. Cu and zinc (Zn) and also lead (Pb) and Cd exhibited spatial similarity. Manganese (Mn) and Cr exhibited point source characteristics such as the concentrations at a point much higher than the surrounding area. The potential ecological risk in the northern region belonged to the moderate risk level category. Cd contributed over 90% to the potential ecological risk. The health risk among children was higher than that among adults. The major exposure pathways were different for adults and children. Exposure, as shown using Hazard Index (HI), to adults was mainly through the skin contact route, while to children was through both the skin contact and ingestion route. The primary CR (carcinogenic risk) to adults was through the inhalation route, while that to children was through the ingestion route. In both children and adults, Cr was the main contributor to HI and CR. According to the Monte Carlo simulation results, the cumulative probability of exceeding the critical value of HI for children was approximately 2.8-3.0 times that for adults. According to the sensitivity analysis results, non-carcinogenic risk prevention should begin mainly by reducing exposure duration and skin contact. The cancer risk may be reduced primarily by decreasing the exposure duration and controlling ingestion. The PMF (Positive Matrix Factorization) source analysis revealed that Pb mainly came from transportation sources. In addition, Cu, Pb, and Mn were derived mainly from agricultural sources. Cr was derived mostly from a natural source, and Cd originated mainly from an industrial source.

Dietary sources apportionment and health risk assessment for trace elements among residents of the Tethys-Himalayan tectonic domain in Tibet, China.

Dietary intake of toxic elements (TEs) and essential trace elements (ETEs) can significantly impact human health. This study collected 302 samples, including 78 food, 104 drinking water, 73 cultivated topsoil, and 47 sedimentary rock from a typical area of Tethys-Himalaya tectonic domain. These samples were used to calculate the average daily dose of oral intake (ADDoral) and assess the health risks of five TEs and five ETEs. The results indicate that grain and meat are the primary dietary sources of TEs and ETEs for local residents. The intake of manganese (Mn) and copper (Cu) is mainly from local highland barley (66.90% and 60.32%, respectively), iron (Fe) is primarily from local grains (75.51%), and zinc (Zn) is mainly from local yak meat (60.03%). The ADDoral of arsenic (As), Mn, Fe and Zn were found to be higher than the maximum oral reference dose in all townships of study area, indicating non-carcinogenic health risks for local residents. Additionally, lead (Pb) and nickel (Ni) in 36.36% townships, and Cu in 81.82% townships were above the maximum oral reference dose, while As posed a carcinogenic risk throughout the study area. The concentrations of As, mercury (Hg), Pb, Mn, Cu Fe and selenium (Se) in grains were significantly correlated with those in soils. Moreover, the average concentrations of As in Proterozoic, Triassic, Jurassic and Cretaceous was 43.09, 12.41, 15.86 and 6.22 times higher than those in the South Tibet shell, respectively. The high concentrations of TEs and ETEs in the stratum can lead to their enrichment in soils, which, in turn, can result in excessive intake by local residents through the food chain and biogeochemical cycles . To avoid the occurrence of some diseases caused by dietary intake, it is necessary to consume a variety of exotic foods, such as high-selenium foods, foreign rice and flour in order to improve the dietary structure.

Arsenic, polycyclic aromatic hydrocarbons, and metal exposure and risk assessment of stroke.

Globally, stroke is one of the primary causes of morbidity and mortality. In the USA, stroke is a major cause of death and disability. Limited studies assessed the impact of polycyclic aromatic hydrocarbons, arsenic, and other metal exposure and their association with the risk of stroke. This study aimed to assess different arsenic species, including total arsenic; two types of organic arsenic, i.e., arsenobetaine and arsenocholine; four types of inorganic arsenic, i.e., arsenic acid, arsenous acid, dimethylarsinic acid (DMA), and monomethylarsonic acid (MMA); six types of urinary polycyclic aromatic hydrocarbon (PAH) compounds, i.e., 1-hydroxynaphthalene, 1-hydroxyphenanthrene, 1-hydroxypyrene, 2-hydroxynaphthalene, 2-hydroxyfluorene, and 3-hydroxyfluorene; and fourteen types of metals from urine specimen, i.e., manganese, cadmium, lead, mercury, barium, cobalt, strontium, molybdenum, cesium, thallium, antimony, tin, tungsten, and uranium and their association with those who reported having been told they had had a stroke by a medical professional. The National Health and Nutrition Examination Survey (NHANES) data used in this study include three data cycles from 2011-2016. In this study, data from a total of 5537 males and females who are aged 20 years and older were analyzed using logistic modeling of the complex weighted survey design. R version 3.6.3 software was used to conduct the analyses. Four species of urinary PAHs, including the third quantiles of 1-hydroxynaphthalene [odds ratio (OR): 2.327, 95% confidence interval (CI): 0.961-5.632], 2-hydroxynaphthalene [OR: 2.449, 95% CI: 1.067-5.622], and 3-hydroxyfluorene [OR: 2.289, 95% CI: 1.077-4.861] and the second quantiles of 3-hydroxyfluorene [OR: 2.201, 95% CI: 1.115, 4.346] and 1-hydroxypyrene [OR: 2.066, 95% CI: 1.037, 4.114], showed a positive correlation with increased odds of stroke. Among metals, the third (3rd) [OR: 3.566, 95% CI: 1.370, 9.280] and fourth (4th) [OR: 2.844, 95% CI: 0.947, 8.543] quantiles of urinary manganese showed a positive correlation with increased odds of stroke.

First assessment of atmospheric pollution by trace elements and particulate matter after a severe collapse of a tailings dam, Minas Gerais, Brazil: An insight into biomonitoring with Tillandsia usneoides and a public health dataset.

In this study, samples of bromeliad Tillandsia usneoides (n = 70) were transplanted and exposed for 15 and 45 days in 35 outdoor residential areas in Brumadinho (Minas Gerais state, Brazil) after one of the most severe mining dam collapses in the world. Trace elements aluminum (Al), arsenic (As), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), nickel (Ni) and zinc (Zn) were quantified by atomic absorption spectrometry. Scanning electron microscope generated surface images of T. usneoides fragments and particulate matter (PM2.5, PM10 and PM > 10). Aluminum, Fe and Mn stood out from the other elements reflecting the regional geological background. Median concentrations in mg kg-1 increased (p < 0.05) between 15 and 45 days for Cr (0.75), Cu (1.23), Fe (474) and Mn (38.1), while Hg (0.18) was higher at 15 days. The exposed-to-control ratio revealed that As and Hg increased 18.1 and 9.4-fold, respectively, not showing a pattern associated only with the most impacted sites. The PM analysis points to a possible influence of the prevailing west wind on the increase of total particles, PM2.5 and PM10 in transplant sites located to the east. Brazilian public health dataset revealed increase in cases of some cardiovascular and respiratory diseases/symptoms in Brumadinho in the year of the dam collapse (1.38 cases per 1000 inhabitants), while Belo Horizonte capital and its metropolitan region recorded 0.97 and 0.37 cases, respectively. Although many studies have been carried out to assess the consequences of the tailings dam failure, until now atmospheric pollution had not yet been evaluated. Furthermore, based on our exploratory analysis of human health dataset, epidemiological studies are required to verify possible risk factors associated with the increase in hospital admissions in the study area.