Associations of heavy metal exposure with diabetic retinopathy in the U.S. diabetic population: a cross-sectional study.

Background: Mounting evidence suggests a correlation between heavy metals exposure and diabetes. Diabetic retinopathy (DR) is a prevalent and irreversible complication of diabetes that can result in blindness. However, studies focusing on the effects of exposure to heavy metals on DR remain scarce. Thus, this study aimed to investigate the potential correlation between heavy metals exposure and DR. Methods: A total of 1,146 diabetics from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were included in this study. Heavy metal levels were measured via urine testing. Weighted logistic regression, Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and restricted cubic spline (RCS) were utilized to investigate the potential relationships between exposure to 10 heavy metals and DR. Finally, subgroup analysis was conducted based on the glycemic control status. Results: Among the 1,146 participants, 239 (20.86%) were diagnosed with DR. Those with DR had worse glycemic control and a higher prevalence of chronic kidney disease compared to those without DR. Moreover, both the WQS regression and BKMR models demonstrated a positive relationship between exposure to mixed heavy metals and the risk of DR. The results of weighted logistic regression revealed a positive correlation between cobalt (Co) and antimony (Sb) exposure and the risk of DR (OR = 1.489, 95%CI: 1.064-2.082, p = 0.021; OR = 1.475, 95% CI: 1.084-2.008, p = 0.014), while mercury (Hg) exposure was found to promote DR exclusively in the group with good glycemic control (OR = 1.509, 95% CI: 1.157-1.967, p = 0.003). These findings were corroborated by the results of the RCS analysis. Conclusion: Heavy metal exposure is associated with an increased risk of DR, especially Sb, Co, and Hg exposure. Nevertheless, well-designed prospective studies are warranted to validate these findings.

Analyzing the impact of heavy metal exposure on osteoarthritis and rheumatoid arthritis: an approach based on interpretable machine learning.

Introduction: This investigation leverages advanced machine learning (ML) techniques to dissect the complex relationship between heavy metal exposure and its impacts on osteoarthritis (OA) and rheumatoid arthritis (RA). Utilizing a comprehensive dataset from the National Health and Nutrition Examination Survey (NHANES) spanning from 2003 to 2020, this study aims to elucidate the roles specific heavy metals play in the incidence and differentiation of OA and RA. Methods: Employing a phased ML strategy that encompasses a range of methodologies, including LASSO regression and SHapley Additive exPlanations (SHAP), our analytical framework integrates demographic, laboratory, and questionnaire data. Thirteen distinct ML models were applied across seven methodologies to enhance the predictability and interpretability of clinical outcomes. Each phase of model development was meticulously designed to progressively refine the algorithm's performance. Results: The results reveal significant associations between certain heavy metals and an increased risk of arthritis. The phased ML approach enabled the precise identification of key predictors and their contributions to disease outcomes. Discussion: These findings offer new insights into potential pathways for early detection, prevention, and management strategies for arthritis associated with environmental exposures. By improving the interpretability of ML models, this research provides a potent tool for clinicians and researchers, facilitating a deeper understanding of the environmental determinants of arthritis.

Construction of metal interpretable scoring system and identification of tungsten as a novel risk factor in COPD.

Numerous studies have highlighted the correlation between metal intake and deteriorated pulmonary function, emphasizing its pivotal role in the progression of Chronic Obstructive Pulmonary Disease (COPD). However, the efficacy of traditional models is often compromised due to overfitting and high bias in datasets with low-level exposure, rendering them ineffective in delineating the contemporary risk trends associated with pulmonary diseases. To address these limitations, we embarked on developing advanced, interpretable models, crucial for elucidating the intricate mechanisms of metal toxicity and enriching the domain knowledge embedded in toxicity models. In this endeavor, we scrutinized extensive, long-term metal exposure datasets from NHANES to explore the interplay between metal and pulmonary functionality. Employing a variety of machine-learning approaches, we opted for the "Mixer of Experts" model for its proficiency in identifying a myriad of toxicological trends and sensitivities. We conceptualized and illustrated the TSAP (Toxicity Score at Population-level), a metal interpretable scoring system offering performance nearly equivalent to the amalgamation of standard interpretable methods addressing the "black box" conundrum. This streamlined, bifurcated procedural analysis proved instrumental in discerning established risk factors, thereby uncovering Tungsten as a novel contributor to COPD risk. SYNOPSIS: TSAP achieved satisfied performance with transparent interpretability, suggesting tungsten intake need further action for COPD prevention.

Assessment of growth, reproduction, and vermi-remediation potentials of Eisenia fetida on heavy metal exposure.

Heavy metal pollution is a significant environmental concern with detrimental effects on ecosystems and human health, and traditional remediation methods may be costly, energy-intensive, or have limited effectiveness. The current study aims were to investigate the impact of heavy metal toxicity in Eisenia fetida, the growth, reproductive outcomes, and their role in soil remediation. Various concentrations (ranging from 0 to 640 mg per kg of soil) of each heavy metal were incorporated into artificially prepared soil, and vermi-remediation was conducted over a period of 60 days. The study examined the effects of heavy metals on the growth and reproductive capabilities of E. fetida, as well as their impact on the organism through techniques such as FTIR, histology, and comet assay. Atomic absorption spectrometry demonstrated a significant (P < 0.000) reduction in heavy metal concentrations in the soil as a result of E. fetida activity. The order of heavy metal accumulation by E. fetida was found to be Cr > Cd > Pb. Histological analysis revealed a consistent decline in the organism's body condition with increasing concentrations of heavy metals. However, comet assay results indicated that the tested levels of heavy metals did not induce DNA damage in E. fetida. FTIR analysis revealed various functional group peaks, including N-H and O-H groups, CH2 asymmetric stretching, amide I and amide II, C-H bend, carboxylate group, C-H stretch, C-O stretching of sulfoxides, carbohydrates/polysaccharides, disulfide groups, and nitro compounds, with minor shifts indicating the binding or accumulation of heavy metals within E. fetida. Despite heavy metal exposure, no significant detrimental effects were observed, highlighting the potential of E. fetida for sustainable soil remediation. Vermi-remediation with E. fetida represents a novel, sustainable, and cutting-edge technology in environmental cleanup. This study found that E. fetida can serve as a natural and sustainable method for remediating heavy metal-contaminated soils, promising a healthier future for soil.

The interaction effect of metals exposure and dietary habit on cognitive function in Chinese older adult cohort.

BACKGROUND: As the important factors in cognitive function, dietary habits and metal exposures are interactive with each other. However, fewer studies have investigated the interaction effect of them on cognitive dysfunction in older adults. METHODS: 2,445 registered citizens aged 60-85 years from 51 community health centers in Luohu District, Shenzhen, were recruited in this study based on the Chinese older adult cohort. All subjects underwent physical examination and Mini-cognitive assessment scale. A semi quantitative food frequency questionnaire was used to obtain their food intake frequency, and 21 metal concentrations in their urine were measured. RESULTS: Elastic-net regression model, a machine learning technique, identified six variables that were significantly associated with cognitive dysfunction in older adults. These variables included education level, gender, urinary concentration of arsenic (As) and cadmium (Cd), and the frequency of monthly intake of egg and bean products. After adjusting for multiple factors, As and Cd concentrations were positively associated with increased risk of mild cognitive impairment (MCI) in the older people, with OR values of 1.19 (95% CI: 1.05-1.42) and 1.32 (95% CI: 1.01-1.74), respectively. In addition, older adults with high frequency of egg intake (≥30 times/month) and bean products intake (≥8 times/month) had a reduced risk of MCI than those with low protein egg intake (<30 times/month) and low bean products intake (<8 times/month), respectively. Furthermore, additive interaction were observed between the As exposure and egg products intake, as well as bean products. Cd exposure also showed additive interactions with egg and bean products intake. CONCLUSIONS: The consumption of eggs and bean products, as well as the levels of exposure to the heavy metals Cd and As, have been shown to have a substantial influence on cognitive impairment in the elderly population.

Association between blood cadmium and depression varies by age and smoking status in US adult women: a cross-sectional study from NHANES 2005-2016.

BACKGROUND: Cadmium, a toxic metal, is widely encountered in diverse environmental contexts. Despite its pervasive exposure, there is limited research on the association between blood cadmium levels and depression, especially among females. This study aimed to investigate the relationship between blood cadmium levels and depression in adult women. METHODS: Data spanning 2005-2016 from the National Health and Nutrition Examination Survey (NHANES) were selected. Depression was diagnosed with the Patient Health Questionnaire (PHQ-9, score ≥10). Multiple logistic regression, multiple linear regression, and smoothed curve fitting were used to investigate the relationship between blood cadmium and depression. Subgroup analyses and interaction tests were performed to evaluate the stability of this association across populations. RESULTS: A total of 1,173 individuals were diagnosed with depression. The heightened prevalence of depression was linked to increased blood cadmium levels, a trend that persisted even after quartering blood cadmium. In the fully adjusted model, each incremental unit of blood cadmium was associated with a 33% rise in the prevalence of depression (OR = 1.33, 95% CI: 1.21-1.45). Participants in the highest quartile were 63% more likely to experience depression compared to those in the lowest quartile of blood cadmium (OR = 1.63, 95% CI: 1.15-2.30), and PHQ-9 score increased by 0.73 (ß = 0.73, 95% CI: 0.30-1.17). This positive association may be relevant to the general population. CONCLUSIONS: Blood cadmium levels are associated with depression in adult women, and this association varies by age and smoking status.

Metal stannum exposure increases the risk of congenital heart defects occurence in offspring: A case-control study in Lanzhou.

BACKGROUND: The purpose of this study was to analyse the association between stannum exposure during pregnancy and congenital heart diseases in offspring. METHODS: Based on a prospective birth cohort study conducted in Gansu Maternal and Child Health Hospital from 2010 to 2012, 14,359 pregnant women were followed up using a nested case-control study method. 97 pregnant women whose offspring were diagnosed with CHDs were used as the case group, and 194 pregnant women whose offspring did not suffer from congenital heart diseases were used as the control group in a ratio of 1:2 according to their age and place of birth. Inductively coupled plasma mass spectrometry was used to determine elemental stannum in blood samples from pregnant women hospitalized for delivery and in fetal cord blood samples. Multifactorial logistic regression analysis was used to assess the association between stannum and offspring CHDs. RESULTS: There was a moderate positive correlation between the concentration of stannum in pregnant women's blood and that in umbilical cord blood. A higher concentrations of maternal blood stannum level was associated with a greater risk of CHDs (aOR 3.409, 95%CI 1.785-6.826), isolated CHDs (aOR 4.044, 95%CI 1.803-9.070), multiple CHDs (aOR 2.625, 95%CI 1.137-6.061), patent ductus arteriosus (aOR 2.882, 95%CI 1.443-5.756), atrial septal defects (aOR 3.067, 95%CI 1.406-6.690), ventricular septal defects (aOR 7.414, 95%CI 1.414-38.874). There was a correlation between the maternal and cord blood sample suggesting stannum crosses the placenta.

Evaluating metal cookware as a source of lead exposure.

BACKGROUND: We previously demonstrated that aluminum cookware brought from Afghanistan by resettled families as well as some aluminum cookware available for purchase in the United States represent a previously unrecognized source of lead exposure. However, the extent to which this cookware represents a source of lead exposure to other United States residents is unclear. OBJECTIVES: To test additional cookware for lead content and its propensity to leach lead and other toxic metals. This will further our understanding of the extent to which this cookware represents a lead poisoning risk in the United States and elsewhere. METHODS: We screened an additional 28 pieces of aluminum cookware and 5 brass items for lead content using an X-ray fluorescence (XRF) analyzer and used our leachate method to estimate the amount of lead that migrates into food. We also tested 17 additional stainless steel items to determine whether they would be safer alternatives. RESULTS: Many aluminum cookware products contained in excess of 100 parts per million (ppm) of lead. Many also leached enough lead under simulated cooking and storage conditions to exceed recommended dietary limits. One hindalium appam pan (an Indian frying pan/wok) leached sufficient lead to exceed the childhood limit by 1400-fold. Brass cookpots from India also yielded high lead levels, with one exceeding the childhood limit by over 1200-fold. In contrast, stainless steel cookware leached much lower levels of lead. IMPACT: Aluminum and brass cookware available for purchase in the United States represents a previously unrecognized source of lead exposure.

Metal exposure and blood lipid biomarkers in early pregnancy: A cross-sectional study.

Recognizing the risk factors for dyslipidemia during pregnancy is crucial for safeguarding the health of both the mothers and the offspring. Growing evidence emerged and suggested links between environmental factors, including metals, and alteration in lipid levels or dyslipidemia in general populations. However, knowledge of the associations during pregnancy remains extremely lacking. Herein, we aimed to explore whether elevated metal exposure constitutes a risk factor for dyslipidemia in pregnant women. Based on the Tongji-Shuangliu Birth Cohort (TSBC), a total of 663 pregnant women were recruited and their urinary levels of 17 metals and blood lipid biomarkers in early pregnancy were measured, namely triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). The multivariable linear regression models revealed that exposure to selected metals during early pregnancy was significantly associated with some important biomarkers. In particular, after natural log-transformed for the levels of lipid biomarkers and metals, copper (Cu) exposure was positively associated with HDL-C (ß = 0.024, 95% CI: 0.001, 0.046), while zinc (Zn) was associated with TG (ß = 0.062, 95% CI: 0.013, 0.110) and selenium with TC (ß = 0.028, 95% CI: 0.004, 0.054). Exposure to rubidium (Rb) was positively associated with multiple lipid biomarkers, including HDL-C (ß = 0.020, 95% CI: 0.002, 0.037) and LDL-C (ß = 0.022, 95% CI: 0.001, 0.042). Mixture exposure analysis further identified significant associations between Cu and HDL-C, Zn and TG, Rb and HDL-C, when multiple metal exposures were considered in the Bayesian kernel machine regression model simultaneously. Our findings showed that exposure to several metals during early pregnancy was associated with an increased prevalence of blood lipid abnormalities in pregnant women. These findings underscore the potential impact of metal combinations on lipid metabolism and increase our understanding of the risk factors associated with abnormal lipid metabolism during pregnancy.

Association of serum metal levels with type 2 diabetes: A prospective cohort and mediating effects of metabolites analysis in Chinese population.

Several studies have suggested an association between exposure to various metals and the onset of type 2 diabetes (T2D). However, the results vary across different studies. We aimed to investigate the associations between serum metal concentrations and the risk of developing T2D among 8734 participants using a prospective cohort study design. We utilized inductively coupled plasmamass spectrometry (ICP-MS) to assess the serum concentrations of 27 metals. Cox regression was applied to calculate the hazard ratios (HRs) for the associations between serum metal concentrations on the risk of developing T2D. Additionally, 196 incident T2D cases and 208 healthy control participants were randomly selected for serum metabolite measurement using an untargeted metabolomics approach to evaluate the mediating role of serum metabolite in the relationship between serum metal concentrations and the risk of developing T2D with a nested casecontrol study design. In the cohort study, after Bonferroni correction, the serum concentrations of zinc (Zn), mercury (Hg), and thallium (Tl) were positively associated with the risk of developing T2D, whereas the serum concentrations of manganese (Mn), molybdenum (Mo), barium (Ba), lutetium (Lu), and lead (Pb) were negatively associated with the risk of developing T2D. After adding these eight metals, the predictive ability increased significantly compared with that of the traditional clinical model (AUC: 0.791 vs. 0.772, P=8.85×10-5). In the nested casecontrol study, a machine learning analysis revealed that the serum concentrations of 14 out of 1579 detected metabolites were associated with the risk of developing T2D. According to generalized linear regression models, 7 of these metabolites were significantly associated with the serum concentrations of the identified metals. The mediation analysis showed that two metabolites (2-methyl-1,2-dihydrophthalazin-1-one and mestranol) mediated 46.81% and 58.70%, respectively, of the association between the serum Pb concentration and the risk of developing T2D. Our study suggested that serum Mn, Zn, Mo, Ba, Lu, Hg, Tl, and Pb were associated with T2D risk. Two metabolites mediated the associations between the serum Pb concentration and the risk of developing T2D.

Possible Risk Factors and Their Potential Associations with Combined Heavy Metal Exposures in Pregnant Women in the Republic of Suriname.

Background: The exposure of pregnant women to multiple environmental pollutants may be more disadvantageous to birth outcomes when compared to single-compound contaminations. Objective: This study investigated the mixed exposures to mercury, manganese, or lead in 380 pregnant Surinamese women. The factors that might be associated with the heavy metal exposures and the relative risk of the potential factors to cause the mixed exposures were explored. The influencing factors of exposures to mixed contaminants assessed were living in Suriname's rural regions, several parts of which are contaminated with heavy metals emitted from artisanal and small-scale gold mining and agricultural activities; the consumption of potentially contaminated foods; advanced maternal age; as well as a relatively low formal educational level and monthly household income. Methods: Descriptive statistics were used to calculate frequency distributions and χ2-contingency analyses to calculate associations and relative risks (RR) with 95% confidence intervals (CI). Findings: Blood levels of two or three of the heavy metals above public health limits were observed in 36% of the women. These women were more often residing in the rural regions, primarily consumed potentially contaminated food items, were 35 years or older, were lower educated, and more often had a lower household income. However, only living in the rural regions (RR = 1.48; 95% CI 1.23-1.77) and a low household income (RR = 1.38; 95% CI 1.15-1.66) significantly increased the risk of exposure exceeding levels of concern to two or three of the heavy metals (by 48% and 38%, respectively). Conclusion: More comprehensive pharmacological, ecological, and epidemiological studies about exposures to mixed heavy metal contaminations in pregnant women are warranted.

Exposure of the general French population to metals and metalloids in 2014-2016: Results from the Esteban study.

BACKGROUND: The purpose of the Esteban study was to describe levels of various biomarkers of exposure to several environmental pollutants, including metals and metalloids, among the French population. This paper describes the distribution of concentrations of 28 metals and metalloids in two different populations, and estimates the main determinants of exposure to total arsenic, the sum of inorganic arsenic (iAs) and its two metabolites monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA), cadmium, chromium, copper, mercury and nickel. METHODS: Esteban is a cross-sectional study conducted between 2014 and 2016 on a random sample of 2503 adults (18-74 years old) and 1104 children (6-17 years old) from the general population. The data collected included biological samples (blood, hair, and urines), socio-demographic characteristics, environmental and occupational exposure, and information on dietary factors and lifestyle. The geometric mean and percentiles of the distribution were estimated for each metal. Multivariate analyses were performed to identify the determinants of exposure using a generalized linear model. RESULTS: Only four metals had a quantification rate below 90% in adults (beryllium, iridium, palladium, and platinum), and three metals in children (beryllium, iridium, and platinum). The concentrations of total arsenic, cadmium, chromium and mercury were higher than those found in most international studies. The determinants significantly associated with exposure were mainly diet and smoking. CONCLUSIONS: Esteban provided a nationwide description of 28 metal and metalloid exposure levels for adults (some never measured before) and for the first time in children. The study results highlighted widespread exposure to several metals and metalloids. These results could be used to advocate public health decisions for continued efforts to reduce harmful exposure to toxic metals. The Reference values (RV95) built from Esteban could also be used to support future government strategies.

Systematic literature review of heavy metal contamination of the Nigerian environment from e-waste management: Associated health and carcinogenic risk assessment.

E-waste -the aftermath of large amount of electrical and electronic equipment ferried into Africa from which Nigeria receives a significant chunk, is composed of components known to be hazardous to health. Composition of series of heavy metals (HMs) in e-waste is traceable to many health conditions including cancer which is hitherto incompletely understood. This study harmonizes primary data on HMs from e-waste in different Nigerian environmental media including the air, soil, surface dust, water and plant. We estimated the possible health implications, single and aggregative soil and water pollution indices both in adult and children categories, carcinogenic and non-carcinogenic risks secondary to HM exposure and mapped out the possible mechanism of carcinogenesis. Analysis showed that soil, water, surface dust and plant matrices in Nigerian environment are variedly but considerably contaminated with combination of HMs. The significantly high values of the hazard quotient and hazard index of both water and surface dust matrices are indicative of adverse health effect of the non-carcinogenic risk. The highest HQ is generated by Pb and Cr through dermal exposure to soil and surface dust with mean values of 1718.48, 1146.14, 1362.10 and 1794.61 respectively among Nigerian children followed by the oral exposure. This pattern of observation is similar to that obtained for adult category. HI due to Pb and Cr in soil constitutes the highest HI (2.05E+03 and 1.18E+03 respectively) followed by surface dust. However, this study precipitates the observation that children are more at health risk than adults in contaminated environment. Carcinogenic risk also follows the same pattern of expression in the Nigerian environment. We conclude that exposure to e-waste poses significant carcinogenic and non-carcinogenic health risks and the induction of toxicity may be mediated via DNA damage, oxidative stress and inflammatory/immune cells dysfunction in Nigerian environment.

Pro-vegetarian dietary patterns and essential and heavy metal exposure in children of 4-5-years from the INfancia y medio Ambiente cohort (INMA).

Dietary patterns provide a comprehensive assessment of food consumption, including essential nutrients and potential exposure to environmental contaminants. While pro-vegetarian (PVG) dietary patterns have shown health benefits in adults, their effects on children are less well studied. This study aims to explore the association between children's adherence to the most common PVG dietary patterns and their exposure to metals, assessed through urine concentration. In our study, we included a population of 723 children aged 4-5-years from the INfancia y Medio Ambiente (INMA) cohort in Spain. We calculated three predefined PVG dietary patterns, namely general (gPVG), healthful (hPVG), and unhealthful (uPVG), using dietary information collected through a validated Food Frequency Questionnaire. Urinary concentrations of various essential and heavy metals (Co, Cu, Zn, Se, Mo, Pb, and Cd) were measured using mass spectrometry. Additionally, urinary arsenic speciation, including arsenobetaine (AsB), dimethylarsinic acid (DMA), monomethylarsonic acid (MMA), and inorganic arsenic (iAs), was measured. The sum of urinary MMA and iAs was used to assess iAs exposure. We estimated primary (PMI) and secondary iAs methylation (SMI) indices. To explore the association between PVG dietary patterns in quintiles and metal exposure, we utilized multiple-adjusted linear regression models and the quantile g-computation approach. Compared with the lowest quintile, participants in the highest quintile of gPVG showed a 22.7% lower urinary Co (95% confidence interval (CI): -38.7; -1.98) and a 12.6% lower Se (95%CI: -22.9; -1.00) concentrations. Second quintile of adherence to hPVG was associated with a 51.7% lower urinary iAs + MMA concentrations (95%CI: -74.3; -8.61). Second quintile of adherence to an uPVG was associated with a 13.6% lower Se levels (95%CI: -22.9; -2.95) while the third quintile to this pattern was associated with 17.5% lower Mo concentrations (95%CI: -29.5; -2.95). The fourth quintile of adherence to gPVG was associated with a 68.5% higher PMI and a 53.7% lower SMI. Our study showed that adherence to a gPVG dietary pattern in childhood may modestly reduce the intakes of some essential metals such as Co and Se. Further investigations are warranted to explore any potential health implications.

Analysis of relationship between mixed heavy metal exposure and early renal damage based on a weighted quantile sum regression and Bayesian kernel machine regression model.

BACKGROUND: Occupation, environmental heavy metal exposure, and renal function impairment are closely related. The relationship between mixed metal exposure and chronic renal injury is inadequately described, and the interaction between each metal is poorly explored. OBJECTIVE: This cross-sectional study assessed mixed heavy metal exposure in the general population and their relationship with early renal impairment, as well as possible interactions between metals. METHODS: The study was conducted in two communities in Taiyuan City in northern China. Multiple linear regression, weighted quantile sum (WQS) and bayesian kernel machine regression (BKMR) regression were used to explore the relationship of mixed heavy metal exposure with indicators of early kidney injury (N-acetyl-ß-D- glucosidase (UNAG), urinary albumin (UALB)). Meanwhile, BKMR was used to explore the possible interactions between mixed heavy metal and indicators of early kidney injury. RESULTS: Based on the WQS regression results, we observed adjusted WQS coefficient ß (ß-WQS) of 0.711 (95% CI: 0.543, 0.879). Notably, this change was primarily driven by As (35.6%) and Cd (22.5%). In the UALB model, the adjusted ß-WQS was 0.657 (95% CI: 0.567, 0.747), with Ni (30.5%), Mn (22.1%), Cd (21.2%), and As (18.6%) exhibiting higher weights in the overall effect. The BKMR results showed a negative interaction between As and other metals in the UNAG and UALB models, a positive interaction between Mn and Ni and other metals. No significant pairwise interaction was observed in the association of metals with indicators of early kidney injury. CONCLUSION: Through multiple linear regression, WQS regression, and BKMR analyses, we found that exposure to mixed heavy metals such as Cd, Cr, Pb, Mn, As, Co and Ni was positively correlated with UNAG and UALB. Moreover, there are complex interactions between two or more heavy metals in more than one direction.

Associations between patterns of blood heavy metal exposure and health outcomes: insights from NHANES 2011-2016.

BACKGROUND: Extensive research has explored the association between heavy metal exposure and various health outcomes, including malignant neoplasms, hypertension, diabetes, and heart diseases. This study aimed to investigate the relationship between patterns of exposure to a mixture of seven heavy metals and these health outcomes. METHODS: Blood samples from 7,236 adults in the NHANES 2011-2016 studies were analyzed for levels of cadmium, manganese, lead, mercury, selenium, copper, and zinc. Cluster analysis and logistic regression identified three distinct patterns of mixed heavy metal exposure, and their associations with health outcomes were evaluated. RESULTS: Pattern 1 exhibited higher odds ratios (ORs) for malignancy during NHANES 2011-2012 (OR = 1.33) and 2015-2016 (OR = 1.29) compared to pattern 2. Pattern 3 showed a lower OR for malignancy during NHANES 2013-2014 (OR = 0.62). For hypertension, pattern 1 displayed higher ORs than pattern 2 for NHANES 2011-2012 (OR = 1.26), 2013-2014 (OR = 1.31), and 2015-2016 (OR = 1.41). Pattern 3 had lower ORs for hypertension during NHANES 2013-2014 (OR = 0.72) and 2015-2016 (OR = 0.67). In terms of heart diseases, pattern 1 exhibited higher ORs than pattern 2 for NHANES 2011-2012 (OR = 1.34), 2013-2014 (OR = 1.76), and 2015-2016 (OR = 1.68). Pattern 3 had lower ORs for heart diseases during NHANES 2013-2014 (OR = 0.59) and 2015-2016 (OR = 0.52). However, no significant trend was observed for diabetes. All three patterns showed the strongest association with hypertension among the health outcomes studied. CONCLUSIONS: The identified patterns of seven-metal mixtures in NHANES 2011-2016 were robust. Pattern 1 exhibited higher correlations with hypertension, heart disease, and malignancy compared to pattern 2, suggesting an interaction between these metals. Particularly, the identified patterns could offer valuable insights into the management of hypertension in healthy populations.

Aging of nanosized titanium dioxide modulates the effects of dietary copper exposure on Daphnia magna - an assessment over two generations.

Nanosized titanium dioxide (nTiO2) is widely used in products, warranting its discharge from various sources into surface water bodies. However, nTiO2 co-occurs in surface waters with other contaminants, such as metals. Studies with nTiO2 and metals have indicated that the presence of natural organic matter (NOM) can mitigate their toxicity to aquatic organisms. In addition, "aging" of nTiO2 can affect toxicity. However, it is a research challenge, particularly when addressing sublethal responses from dietary exposure over multiple generations. We, therefore exposed the alga Desmodesmus subspicatus to nTiO2 (at concentrations of 0.0, 0.6 and 3.0 mg nTiO2/L) in nutrient medium aged for 0 or 3 days with copper (Cu) at concentrations of 0 and 116 µg Cu/L and with NOM at concentrations equivalent to 0 and 8 mg total organic carbon (TOC) per litre. Subsequently, the exposed alga was fed to Daphnia magna for 23 days over two generations and survival, reproduction and body length were assessed as endpoints of toxicity. In parallel, Cu accumulation and depuration from D. magna were measured. The results indicate that the reproduction of D. magna was the most sensitive parameter in this study, being reduced by 30% (at both parental (F0) and filial (F1) generations) and 50% (at F0 but not F1) due to the dietary Cu exposure in combination with nTiO2 for 0 and 3 days aging, respectively. There was no relationship between the effects observed on reproduction and Cu body burden in D. magna. Moreover, D. magna from the F1 generation showed an adaptive response to Cu in the treatment with 3.0 mg nTiO2/L aged for 3 days, potentially due to epigenetic inheritance. Unexpectedly, the presence of NOM hardly changed the observed effects, pointing towards the function of algal exopolymeric substances or intracellular organic matter, rendering the NOM irrelevant. Ultimately, the results indicate that the transferability of the impacts observed during the F0 to the responses in the F1 generation is challenging due to opposite effect directions. Additional mechanistic studies are needed to unravel this inconsistency in the responses between generations and to support the development of reliable effect models.

Effect of acute cadmium exposure on oxidative stress and antioxidant system of the scallop Aequipecten tehuelchus.

This study aimed to assess the impact of acute exposure (96 h) to Cd in gills, digestive gland and muscle of the Tehuelche scallop Aequipecten tehuelchus from San José gulf in Patagonia, Argentina. Scallops were exposed to Cd concentrations of 0, 25, 50, 100, 150, 204, 275, 371, and 500 µg/L, and mortality rates were recorded after 96 h of exposure. Surviving organisms were analyzed for the biochemical response through reactive oxygen and nitrogen species (RONS), activities of catalase (CAT) and glutathione-S-transferase (GST), metallothioneins (MT), lipid peroxidation (LPO) and liposoluble antioxidants α-tocopherol (α-T) and ß-carotene (ß-C). The mean lethal concentration (LC50) was 155.8 µg Cd/L, a lower value than other scallops' species, showing that A. tehuelchus has a particular sensitivity to Cd. In the three tissues, at all exposure concentrations, there was no significant response in RONS levels, GST activity or LPO. Nevertheless, CAT activity and α-T levels decreased in the gills but increased in the digestive gland, with no significant response in the muscle. Two-way ANOVA revealed a significant interaction between Cd concentration and tissue on MT, which increased significantly in gills, decreased in digestive gland with 100 compared to 50 µg Cd/L; whereas in muscle a significant increase was observed with 25 µg Cd/L compared to control. The results show a significant effect of Cd in scallop's gills on CAT activity and α-T levels, highlighting this tissue as the primary target against relevant concentrations of metal in seawater. The effect on digestive gland and muscle was minimal. The overall results suggest that Cd toxicity is tissue-specific. This study will help reduce the existence knowledge gap regarding potential impacts of acute exposure to Cd in a bivalve species with high ecological and commercial importance, as well as identifying the most responsive biomarkers associated with Cd stress for monitoring assessment.

Sex-specific associations between co-exposure to multiple metals and externalizing symptoms in adolescence and young adulthood.

Externalizing disorders, such as attention-deficit/hyperactivity disorder (ADHD), account for the majority of the child/adolescent referrals to mental health services and increase risk for later-life psychopathology. Although the expression of externalizing disorders is more common among males, few studies have addressed how sex modifies associations between metal exposure and adolescent externalizing symptoms. This study aimed to examine sex-specific associations between co-exposure to multiple metals and externalizing symptoms in adolescence and young adulthood. Among 150 adolescents and young adults (55% female, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study in Brescia, Italy, we measured five metals (manganese (Mn), lead (Pb), copper (Cu), chromium (Cr), nickel (Ni)) in four biological matrices (blood, urine, hair, and saliva). Externalizing symptoms were assessed using the Achenbach System of Empirically Based Assessment (ASEBA) Youth Self-Report (YSR) or Adult Self Report (ASR). Using generalized weighted quantile sum (WQS) regression, we investigated the moderating effect of sex (i.e., assigned at birth) on associations between the joint effect of exposure to the metal mixture and externalizing symptoms, adjusting for age and socioeconomic status. We observed that metal mixture exposure was differentially associated with aggressive behavior in males compared to females (ß = -0.058, 95% CI [-0.126, -0.009]). In males, exposure was significantly associated with more externalizing problems, and aggressive and intrusive behaviors, driven by Pb, Cu and Cr. In females, exposure was not significantly associated with any externalizing symptoms. These findings suggest that the effect of metal exposure on externalizing symptoms differs in magnitude between the sexes, with males being more vulnerable to increased externalizing symptoms following metal exposure. Furthermore, our findings support the hypothesis that sex-specific vulnerabilities to mixed metal exposure during adolescence/young adulthood may play a role in sex disparities observed in mental health disorders, particularly those characterized by externalizing symptoms.

Association between exposure to heavy metals in atmospheric particulate matter and sleep quality: A nationwide data linkage study.

BACKGROUND: Recent studies have demonstrated that long-term exposure to particulate matter (PM) is associated with poor sleep quality. However, no studies have linked PM constituents, particularly heavy metals, to sleep quality. OBJECTIVE: This study investigated the association between exposure to heavy metals in PM and sleep quality. METHODS: We obtained nationwide data from the Korean Community Health Survey conducted in 2018 among adults aged 19-80 years. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as PSQI ≥5. One-year and three-month average concentrations of heavy metals (lead, manganese, cadmium, and aluminum) in PM with diameter ≤10 µm were obtained from nationwide air quality monitoring data and linked to the survey data based on individual district-level residential addresses. Logistic regression analyses were performed after adjusting for age, gender, education level, marital status, smoking status, alcohol consumption, history of hypertension, and history of diabetes mellitus. RESULTS: Of 32,050 participants, 17,082 (53.3%) reported poor sleep quality. Increases in log-transformed one-year average lead (odds ratio, 1.14; 95% confidence interval, 1.08-1.20), manganese (1.31; 1.25-1.37), cadmium (1.03; 1.00-1.05), and aluminum concentrations (1.17; 1.10-1.25) were associated with poor sleep quality. Increases in log-transformed three-month average manganese (odds ratio, 1.13; 95% confidence interval, 1.09-1.17) and aluminum concentrations (1.28; 1.21-1.35) were associated with poor sleep quality. CONCLUSION: We showed for the first time that exposure to airborne lead, manganese, cadmium, and aluminum were associated with poor sleep quality. This study may be limited by self-reported sleep quality and district-level exposure data.