What adverse health effects will environmental heavy metal co-exposure bring us: based on a biological monitoring study of sanitation workers

Cyanoremediation of heavy metals (As(v), Cd(ii), Cr(vi), Pb(ii)) by live cyanobacteria (Anabaena variabilis, and Synechocystis sp.): an eco-sustainable technology

The cyanoremediation technique for heavy metal (HM) removal from wastewater using live cyanobacteria is promising to reduce the pollution risk both for the environment and human health. In this study, two widely recognized freshwater cyanobacteria, Anabaena variabilis and Synechocystis sp., were used to explore their efficacy in HM (As(v), Cd(ii), Cr(vi), Pb(ii)) removal. The different optimum adsorption conditions were pH 8 and 7.5 for A. variabilis and Synechocystis sp., respectively, but the temperature (25 °C) and contact time (48 hours) were the same for both strains. Under these specified conditions, A. variabilis exhibited the capability to remove 25% of As(v), 78% of Cd(ii), 54% of Cr(vi), and 17% of Pb(ii), whereas Synechocystis sp. removed 77% of As(v), 57% of Cd(ii), 91% of Cr(vi), and 77% of Pb(ii) at different initial concentrations. Metal diversity interfered negatively with cyanobacterial growth, especially Cd(ii) and As(v), as measured by OD730, dry biomass, chlorophyll a, and carotenoid production for both strains. Fourier transform infrared spectrum (FT-IR) analysis revealed the existence of diverse surface binding sites for HM adsorption, stemming from proteins and polysaccharides. Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) confirmed the presence of HMs on the surface of the cyanobacterial cells. Finally, the zeta potential results indicating alterations in the surface negative charges elucidated the adsorption mechanisms involved in the HM removal by both cyanobacteria. These results provided a comprehensive understanding of the HM adsorption mechanism by cyanobacteria, offering valuable theoretical insights that can be extrapolated to enhance our comprehension of the cyanoremediation mechanisms by various other cyanobacterial strains.

Occupational exposure and health surveys at metal additive manufacturing facilities

Introduction

Additive manufacturing is a novel state-of-the art technology with significant economic and practical advantages, including the ability to produce complex structures on demand while reducing the need of stocking materials and products. Additive manufacturing is a technology that is here to stay; however, new technologies bring new challenges, not only technical but also from an occupational health and safety perspective. Herein, leading Swedish companies using metal additive manufacturing were studied with the aim of investigating occupational exposure and the utility of chosen exposure- and clinical markers as predictors of potential exposure-related health risks.

Methods

Exposure levels were investigated by analysis of airborne dust and metals, alongside particle counting instruments measuring airborne particles in the range of 10 nm-10 μm to identify dusty work tasks. Health examinations were performed on a total of 48 additive manufacturing workers and 39 controls. All participants completed a questionnaire, underwent spirometry, and blood and urine sampling. A subset underwent further lung function tests.

Results

Exposure to inhalable dust and metals were low, but particle counting instruments identified specific work tasks with high particle emissions. Examined health parameters were well within reference values on a group level. However, statistical analysis implied an impact on workers kidney function and possible airway inflammation.

Conclusion

The methodology was successful for investigating exposure-related health risks in additive manufacturing. However, most participants have been working <5 years. Therefore, long-term studies are needed before we can conclusively accept or reject the observed effects on health.

Study on the correlation and interaction between metals and dyslipidemia: a case-control study in Chinese community-dwelling elderly

Previous studies on the association between metals and dyslipidemia are not completely consistent. There are few studies investigating the relationship between mixed metal exposure and dyslipidemia as well as the effects of metals on dyslipidemia in community-dwelling elderly. To evaluate the correlations and interaction effect between the urinary concentrations of metals and the risk of dyslipidemia in community-dwelling elderly. We designed a case-control study to assess the correlation between urine metals and dyslipidemia in elderly people in the Yinchuan. The urinary levels of 13 metals, including calcium, vanadium, iron, cobalt, zinc, copper, arsenic, selenium, molybdenum, cadmium, tellurium, and thallium, were measured by inductively coupled plasma-mass spectrometry (ICP-MS), and the blood biochemical analyzer was used to measure the blood lipid levels of 3384 senior individuals from four different areas of Yinchuan city. Logistic regression and restricted cubic splines (RCS) were used to explore the correlation and dose-response relationship between urinary metals and the risk of dyslipidemia. Least absolute shrinkage and selection operator (LASSO) regression was used to select metals, and then weighted quantile sum (WQS) regression was used to explore the weight of each metal in mixed metals. Bayesian kernel machine regression (BKMR) was used to explore the interactions between metals on dyslipidemia risk. (1) After selection by LASSO regression, in the multi-metal model, compared with the lowest quartile, the adjusted ORs (95%CI) of the highest quartiles were 0.47 (0.37-0.60) for Fe, 1.43 (1.13-1.83) for Zn, 1.46 (1.11-1.92) for As, 0.59 (0.44-0.80) for Se, 1.53 (1.18-2.00) for Mo, and 1.36 (1.07-1.73) for Te. (2) In the WQS regression model, Fe and Mo accounted for the largest weight in the negative and positive effects of dyslipidemia, respectively. (3) In the BKMR model, there may be a positive interaction between Te and Se on dyslipidemia. Among the mixed metals, Fe, As, Se, Mo, and Te were associated with the prevalence of dyslipidemia, with Fe and Mo contributing the most. There may be certain interactions between Te and Se.

Exposure to arsenic, polycyclic aromatic hydrocarbons, metals, and association with skin cancers in the US adults

Worldwide, skin cancer affects millions of people yearly and is broadly classified into melanoma and nonmelanoma types of skin cancer. The toxicity of metals to human health is a public and clinical health problem due to their widespread use in tools, machinery, and appliances as well as their widespread distribution in the air, water, and soil. Arsenic is a carcinogenic metalloid and available in the Earth's crust. Polycyclic aromatic hydrocarbons (PAHs) are toxic to humans, and incomplete combustion of fossil fuels is the main source of PAHs. Human populations exposed to metals from various sources can lead to various diseases including cancer. Limited studies are conducted to simultaneously assess the correlation of multiple arsenic, PAHs, metals with the occurrence of skin cancer. This study aimed to analyze the association between six PAHs compounds, seven types of arsenic, and fourteen metals from urine specimen with skin cancer in US adults. We performed a cross-sectional analysis using data from a total of 14,716 adults from the National Health Examination and Nutrition Survey (NHANES) database for three cycles ranging from 2011-2012 to 2015-2016. Specialized weighted complex survey logit regressions were conducted. Linear logit regression models using only main effects were performed first to identify the correlation between the selected demographic and lifestyle variables and melanoma, nonmelanoma, and unknown types of skin cancer. A second set of linear, main-effects logit regression models were constructed to examine the correlation between melanoma, nonmelanoma, and other types of skin cancers and seven types of arsenic (arsenous acid, arsenic acid, arsenobetaine, arsenocholine, dimethylarsinic acid, monomethylacrsonic acid, and total arsenic), six PAHs (1-hydroxynaphthalene, 2-hydroxynaphthalene, 3-hydroxyfluorene, 2-hydroxyfluorene, 1-hydroxyphenathrene, and 1-hydroxypyrene), and fourteen metals (barium, cadmium, cobalt, cesium, molybdenum, manganese, lead, antimony, tin, strontium, thallium, tungsten, uranium, and mercury) when adjusted for the selected covariates. The statistical analysis was conducted using R software, version 4.0.4. A marginal positive significant correlation between total arsenic and nonmelanoma was observed. This study identified a significant positive association between barium, cadmium, cesium, mercury, tin, and melanoma development. Cesium showed a significant positive statistical association for nonmelanoma, and thallium showed a borderline significant statistical association for nonmelanoma. A statistically significant positive association was found between cadmium and an unknown type of skin cancer. The findings of this study indicated a statistically significant positive association between skin cancer and barium, cadmium, cesium, tin, mercury, and thallium. Further studies are recommended in humans to refute or confirm these findings.