Coal Dust Exposure Research Articles

Use of electron microscopy to determine presence of coal dust in a neighborhood bordering an open-air coal terminal in Curtis Bay, Baltimore, Maryland, USA

BackgroundDespite decreasing US consumption, over 90 million metric tons of coal were exported by the US in 2023, requiring significant infrastructure for transport, handling, and storage of coal at export terminals. Residents in Curtis Bay, Baltimore, Maryland, USA live at the fenceline of an open-air coal terminal and have, for decades, reported rapid accumulation of black dust at their homes. Community-level exposure to coal dust originating from coal handling and storage terminals has remained largely unexplored. ObjectivesTo investigate community-identified concerns and use a community-driven approach to determine the presence/absence of coal dust in Curtis Bay surfaces. MethodsPassive settled dust samples were collected from two residential areas, 345 m and 1235 m from the coal terminal, using conductive carbon tape. Scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDX) of standard reference coal material and a positive control material from the coal terminal in Curtis Bay were used to optimize the morphological and elemental classification criteria for coal dust. A manual SEM-EDX protocol was developed to identify coal particles in settled dust collected on conductive carbon tape in community settings. ResultsSEM-EDX analysis confirmed presence of coal dust sampled at both residential locations. Estimated coal dust particle loading at the proximal and distal site were 13.2 and 3.4 coal particles/mm2, respectively. The coal dust particles identified met specific criteria, including size (>5 μm), morphology, and elemental composition (≥75 % carbon, ≤20 % oxygen). DiscussionThese findings are consistent with longstanding community concerns and lived experiences regarding the presence of coal dust in Curtis Bay, which neighbors a major open-air coal terminal. This approach has potential for other communities neighboring coal terminals to assess similar concerns with residential coal dust exposure.

In vitro toxicity assessment of bioavailable iron in coal varieties of Central India

Introduction Information on bioavailable Iron (BAI) content in respirable coal dust (RCD) is crucial to address occupational health and safety, especially in preventing coal workers’ pneumoconiosis (CWP). Materials and methods In the present study, we determined BAI concentrations in seventy-seven coal samples collected from ten coal mining regions of Central India. The cytotoxic potential of BAI-RCD was established invitro by using alveolar epithelial (A549) and macrophage (U937) cell lines. The oxidative/antioxidant status, inflammations, and genotoxicity attributed to BAI-RCD exposure were evaluated and correlated with CWP pathophysiology. Results The mean BAI concentrations in the coal samples (n = 77) range from (275 to 9065 mg kg-1) and showed wide variability. Both cell lines were exposed to low (275 mg kg-1), moderate (4650 mg kg-1), and high (9065 mg kg-1) BAI-RCD samples showed significant (p < 0.001) cytotoxicity in a dose-dependent manner (low < moderate < high) compared to the control. After BAI-RCD treatment, both cell lines showed a decrease in antioxidant stress measures (SOD, CAT, and GSH) and a significant (p < 0.001) increase in oxidative stress parameters (NADPH, MPO, LPO, and PC). Furthermore, these cell line models demonstrated a statistically significant (p < 0.001) dose-dependent increase in cytokines (TGF-β1, IL-1β, TNF-α, MCP-1, and IL-6 cytokines) and oxidative DNA damage marker (8-OH-dG). Conclusion Results indicated that the central India coals (even at low BAI content) may be accountable for inflammatory responses and cytotoxicity. Hence, BAI can be important characteristic to establish safety standards for coal dust exposure before active mining.

Arginine-Proline Metabolism as a Mediator in the Association Between Coal Dust Exposure and Lung Function: A Retrospective Analysis.

To investigate the mediating role of the activation degree of arginine-proline metabolism in the association of coal dust and decreased lung function. CDE represented coal dust exposure, while the Hyp/Arg in BALF gauged arginine-proline metabolism activation. Pulmonary function indicators, including FVC%pred, FEV1/FVC%, and FEV1%pred, DLCO%pred, P(A-a) O2 and 6MWT, were assessed. Findings revealed a significant association between elevated CDE and increased Hyp/Arg, increased P(A-a) O2, decreased 6MWT, DLCO%pred, and decreased FVC%pred. However, no statistically significant association was found between CDE and FEV1%pred or FEV1/FVC%. The mediating effect of Hyp/Arg was significant for CDE's impact on P(A-a) O2 and DLCO%pred but not on 6MWT and FVC%pred. These results highlight the role of Hyp/Arg in mediating the association between CDE and lung function parameters, shedding light on potential therapeutic avenues for mitigating coal dust-induced lung function impairment.

Exposure to coal dust exacerbates cognitive impairment by activating the IL6/ERK1/2/SP1 signaling pathway

Coal dust (CD) is a common pollutant, and epidemiological surveys indicate that long-term exposure to coal dust not only leads to the occurrence of pulmonary diseases but also has certain impacts on cognitive abilities. However, there is little open-published literature on the effects and specific mechanisms of coal dust exposure on the cognition of patients with Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). An animal model has been built in this study with clinical population samples to explore the changes in neuroinflammation and cognitive abilities with coal dust exposure. In the animal model, compared to C57BL/6 mice, APP/PS1 mice exposed to coal dust exhibited more severe cognitive impairment, accompanied by significantly elevated levels of neuroinflammatory factors Apolipoprotein E4 (AOPE4) and Interleukin-6 (IL6) in the hippocampus, and more severe neuronal damage. In clinical sample sequencing, it was found that there is significant upregulation of AOPE4, neutrophils, and IL6 expression in the peripheral blood of MCI patients compared to normal individuals. Mechanistically, cell experiments revealed that IL6 could promote the phosphorylation of ERK1/2 and enhance the expression of transcription factor SP1, thereby promoting AOPE4 expression. The results of this study suggest that coal dust can promote the upregulation of IL6 and AOPE4 in patients, exacerbating cognitive impairment.

Associations of coal mine dust exposure with arterial stiffness and atherosclerotic cardiovascular disease risk in chinese coal miners.

Whether coal mine dust exposure increases cardiovascular diseases (CVDs) risk was rarely explored. Our objective was to examine the association between coal mine dust exposure and cardiovascular risk. We estimated cumulative coal mine dust exposure (CDE) for 1327 coal miners by combining data on workplace dust concentrations and work history. We used brachial-ankle pulse wave velocity (baPWV, a representative indicator of arterial stiffness) and ten-year atherosclerotic cardiovascular disease (ASCVD) risk to assess potential CVD risk, exploring their associations with CDE. Positive dose-response relationships of CDE with baPWV and ten-year ASCVD risk were observed after adjusting for covariates. Specifically, each 1 standard deviation (SD) increase in CDE was related to a 0.27m/s (95% CI: 0.21, 0.34) increase in baPWV and a 1.29 (95% CI: 1.14, 1.46) elevation in OR(odds ratio) of risk of abnormal baPWV. Moreover, each 1 SD increase in CDE was associated with a 0.74% (95% CI: 0.63%, 0.85%) increase in scores of ten-year ASCVD and a 1.91 (95% CI: 1.62, 2.26) increase in OR of risk of ten-year ASCVD. When compared with groups unexposed to coal mine dust, significant increase in the risk of arterial stiffness and ten-year ASCVD in the highest CDE groups were detected. The study suggested that cumulative exposure to coal mine dust was associated with elevated arterial stiffness and ten-year ASCVD risk in a dose-response manner. These findings contribute valuable insights for cardiovascular risk associated with coal mine dust.

Comparison and analysis research on occupational exposure limits of coal dust between China and foreign countries

Objective: To study and compare the occupational exposure limits (OELs) of coal dust between China and foreign countries, understand the OEL of coal dust in China, and provide data and basis for revising the OEL of coal dust in China. Methods: In August 2023, by searching the official websites of limits setting institutions in relevant countries and regions at home and abroad, collecting and sorting out the OELs of coal dust issued by 10 limit setting institutions in 6 countries and the background information of the formulation, and conducting specific analysis on the classification, limit level and formulation principles of coal dust OEL in each country/institution. Results: In China and Japan, the total dust and respirable dust of coal dust OEL were established respectively, while in other countries, only the time-weighted average concentration (TWA) of respirable coal dust exposure was established. The TWA prescribed by China's Notional Health Commission, the United States Occupational Safety and Health Administration (OSHA) , the United States Mining Safety and Health Administration (MSHA) and the Australian Safety Work Bureau when the SiO(2) content was less than 5% were 5, 2.4, 2 and 3 mg/m(3) respectively. China GBZ 2.1-2019 sets the limit of 2.5 mg/m(3) for respirable coal dust with SiO(2) content less than 10%. The TWA set by the American Conference of Government Industrial Hygienists (ACGIH) and the South African Department of Mines and Energy (DME) for anthracite coal were 0.4 and 0.8 mg/m(3), respectively, and bituminous coal or lignite were 0.9 and 1.8 mg/m(3), respectively. The respirable coal dust TWA set by the National Institute for Occupational Safety and Health (NIOSH) in the United States was 1 mg/m(3), and the TWA set by the New Zealand Work Safety Authority was 3 mg/m(3). Conclusion: At present, the OEL of coal dust in China is at a relatively loose level, and it is suggested to further explore the possibility of revising coal dust OEL.

Advancing occupational health in mining: investigating low-cost sensors suitability for improved coal dust exposure monitoring

Exposure to coal dust in underground coal mines poses significant health risks to workers, including the development of diseases such as coal workers’ pneumoconiosis and silicosis. Current available methods for monitoring coal dust exposure are expensive and time-consuming, necessitating the exploration of alternative approaches. Low-cost light scattering particulate matter sensors offer a promising solution, and its development in recent years has demonstrated some success in air quality monitoring However, its application in sensing coal particles is limited partially due to that the operating condition in a mine is different than the atmosphere. Thus, the objective of this paper is to evaluate the impact of common factors encountered in a mining environment on these sensors. The findings revealed that the Air trek and Gaslab sensors were unsuitable, showing poor correlation with reference monitors. SPS30 was promising for low concentrations (0–1.0 mg m−3), while PMS5003 effectively monitored up to 3.0 mg m−3. Changing sensor orientation reduced accuracy. Higher wind speeds (3 m s−1) improved results. Low-cost sensors performed well with coal dust but poorly with Arizona road dust. This study underscores the imperative for enhancing these sensors, thereby facilitating their potential application to enhance the occupational health of miners.

The role of macrophage polarization and related key molecules in pulmonary inflammation and fibrosis induced by coal dust dynamic inhalation exposure in Sprague-Dawley rats

Coal dust is the main occupational hazard factor during coal mining operations. This study aimed to investigate the role of macrophage polarization and its molecular regulatory network in lung inflammation and fibrosis in Sprague-Dawley rats caused by coal dust exposure. Based on the key exposure parameters (exposure route, dose and duration) of the real working environment of coal miners, the dynamic inhalation exposure method was employed, and a control group and three coal dust groups (4, 10 and 25 mg/m3) were set up. Lung function was measured after 30, 60 and 90 days of coal dust exposure. Meanwhile, the serum, lung tissue and bronchoalveolar lavage fluid were collected after anesthesia for downstream experiments (histopathological analysis, RT-qPCR, ELISA, etc.). The results showed that coal dust exposure caused stunted growth, increased lung organ coefficient and decreased lung function in rats. The expression level of the M1 macrophage marker iNOS was significantly upregulated in the early stage of exposure and was accompanied by higher expression of the inflammatory cytokines TNF-α, IL-1β, IL-6 and the chemokines IL-8, CCL2 and CCL5, with the most significant trend of CCL5 mRNA in lung tissues. Expression of the M2 macrophage marker Arg1 was significantly upregulated in the mid to late stages of coal dust exposure and was accompanied by higher expression of the anti-inflammatory cytokines IL-10 and TGF-β. In conclusion, macrophage polarization and its molecular regulatory network (especially CCL5) play an important role in lung inflammation and fibrosis in SD rats exposed to coal dust by dynamic inhalation.

Hazardous Impact of Coal Dust on Hematological Parameters of Underground Coal Mine Workers

Due to the nature of their work, coal miners have historically faced significant exposure to large amounts of dust, placing them at a heightened risk. The present study was conducted to explore the hazardous effects of inhalation of coal dust on the haematological parameters of underground coal miners. 120 underground coal miners (60 workers having 5-10 years of experience and the other 60 having 10-20 years of experience) and 62 matched non-exposed to coal dust subjects as control from the locality were recruited for the study. After obtaining consent, different physiological parameters were measured, and blood was collected for assessment of haematological parameters. Observations revealed that there were lower mean values of total RBC count, haemoglobin level, MCV, PCV, MCHC and MCH in coal mine workers whereas mean values of Red Cell Distribution Width (RDW) and ESR were increased in the workers group. Further, coal dust exposure causes increased total leucocyte to count as well as a differential count of lymphocyte, neutrophil, monocyte, and eosinophil in the workers group but, a decreased differential count of basophils was detected among coal dust-exposed workers. All the changes in haematological parameters were found to occur experience-dependent and maximum changes were observed in workers having 10-20 years of working experience. There is a significant likelihood of coal mine workers experiencing changes in their blood composition, which suggests the harmful impact of coal dust on this group. Further, haematological parameters will help health professionals to screen any pathologic conditions and may help to prevent coal dust exposure-associated haematological disorders and complications thereof.

The dangerous link between coal dust exposure and DNA damage: unraveling the role of some of the chemical agents and oxidative stress

Exposure to coal mining dust poses a substantial health hazard to individuals due to the complex mixture of components released during the extraction process. This study aimed to assess the oxidative potential of residual coal mining dust on human lymphocyte DNA and telomeres and to perform a chemical characterization of coal dust and urine samples. The study included 150 individuals exposed to coal dust for over ten years, along with 120 control individuals. The results revealed significantly higher levels of DNA damage in the exposed group, as indicated by the standard comet assay, and oxidative damage, as determined by the FPG-modified comet assay. Moreover, the exposed individuals exhibited significantly shorter telomeres compared to the control group, and a significant correlation was found between telomere length and oxidative DNA damage. Using the PIXE method on urine samples, significantly higher concentrations of sodium (Na), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K), iron (Fe), zinc (Zn), and bromine (Br) were observed in the exposed group compared to the control group. Furthermore, men showed shorter telomeres, greater DNA damage, and higher concentrations of nickel (Ni), calcium (Ca), and chromium (Cr) compared to exposed women. Additionally, the study characterized the particles released into the environment through GC–MS analysis, identifying several compounds, including polycyclic aromatic hydrocarbons (PAHs) such as fluoranthene, naphthalene, anthracene, 7H-benzo[c]fluorene, phenanthrene, pyrene, benz[a]anthracene, chrysene, and some alkyl derivatives. These findings underscore the significant health risks associated with exposure to coal mining dust, emphasizing the importance of further research and the implementation of regulatory measures to safeguard the health of individuals in affected populations.Graphic abstract

A Toxicological Study of the Respirable Coal Mine Dust: Assessment of Different Dust Sources within the Same Mine

Respirable coal mine dust (RCMD) exposure is one of the utmost health hazards to the mining community causing various health issues, including coal worker pneumoconiosis (CWP). Considering multiple potential sources of RCMD having different physicochemical properties within the same mine suggests a wide range of health impacts that have not yet been studied extensively. In this work, we investigate the toxicity of lab-created RCMD based on different sources: coal seam, rock dust, host floor, and host roof collected from the same mine. Comparative samples obtained from several mines situated in various geographic locations were also assessed. This work quantifies metal leaching in simulated lung fluids and correlates dissolution with in vitro immune responses. Here, dissolution experiments were conducted using two simulated lung fluids; Gamble solution (GS) and artificial lysosomal fluid (ALF). In vitro studies were performed using a lung epithelial cell line (A549) to investigate their immune responses and cell viability. Si and Al are the most dissolved metals, among several other trace metals, such as Fe, Sr, Ba, Pb, etc. RCMD from the coal seam and the rock dust showed the least metal leaching, while the floor and roof samples dissolved the most. Results from in vitro studies showed a prominent effect on cell viability for floor and roof dust samples suggesting high toxicity.

Bayesian Hierarchical Framework from Expert Elicitation in the South African Coal Mining Industry for Compliance Testing.

Occupational exposure assessment is important in preventing occupational coal worker's diseases. Methods have been proposed to assess compliance with exposure limits which aim to protect workers from developing diseases. A Bayesian framework with informative prior distribution obtained from historical or expert judgements has been highly recommended for compliance testing. The compliance testing is assessed against the occupational exposure limits (OEL) and categorization of the exposure, ranging from very highly controlled to very poorly controlled exposure groups. This study used a Bayesian framework from historical and expert elicitation data to compare the posterior probabilities of the 95th percentile (P95) of the coal dust exposures to improve compliance assessment and decision-making. A total of 10 job titles were included in this study. Bayesian framework with Markov chain Monte Carlo (MCMC) simulation was used to draw a full posterior probability of finding a job title to an exposure category. A modified IDEA ("Investigate", "Discuss", "Estimate", and "Aggregate") technique was used to conduct expert elicitation. The experts were asked to give their subjective probabilities of finding coal dust exposure of a job title in each of the exposure categories. Sensitivity analysis was done for parameter space to check for misclassification of exposures. There were more than 98% probabilities of the P95 exposure being found in the poorly controlled exposure group when using expert judgments. Historical data and non-informative prior tend to show a lower probability of finding the P95 in higher exposure categories in some titles unlike expert judgments. Expert judgements tend to show some similarity in findings with historical data. We recommend the use of expert judgements in occupational risk assessment as prior information before a decision is made on current exposure when historical data are unavailable or scarce.

Predicting the risk of nodular thyroid disease in coal miners based on different machine learning models.

Nodular thyroid disease is by far the most common thyroid disease and is closely associated with the development of thyroid cancer. Coal miners with chronic coal dust exposure are at higher risk of developing nodular thyroid disease. There are few studies that use machine learning models to predict the occurrence of nodular thyroid disease in coal miners. The aim of this study was to predict the high risk of nodular thyroid disease in coal miners based on five different Machine learning (ML) models. This is a retrospective clinical study in which 1,708 coal miners who were examined at the Huaihe Energy Occupational Disease Control Hospital in Anhui Province in April 2021 were selected and their clinical physical examination data, including general information, laboratory tests and imaging findings, were collected. A synthetic minority oversampling technique (SMOTE) was used for sample balancing, and the data set was randomly split into a training and Test dataset in a ratio of 8:2. Lasso regression and correlation heat map were used to screen the predictors of the models, and five ML models, including Extreme Gradient Augmentation (XGBoost), Logistic Classification (LR), Gaussian Parsimonious Bayesian Classification (GNB), Neural Network Classification (MLP), and Complementary Parsimonious Bayesian Classification (CNB) for their predictive efficacy, and the model with the highest AUC was selected as the optimal model for predicting the occurrence of nodular thyroid disease in coal miners. Lasso regression analysis showed Age, H-DLC, HCT, MCH, PLT, and GGT as predictor variables for the ML models; in addition, heat maps showed no significant correlation between the six variables. In the prediction of nodular thyroid disease, the AUC results of the five ML models, XGBoost (0.892), LR (0.577), GNB (0.603), MLP (0.601), and CNB (0.543), with the XGBoost model having the largest AUC, the model can be applied in clinical practice. In this research, all five ML models were found to predict the risk of nodular thyroid disease in coal miners, with the XGBoost model having the best overall predictive performance. The model can assist clinicians in quickly and accurately predicting the occurrence of nodular thyroid disease in coal miners, and in adopting individualized clinical prevention and treatment strategies.

Questionnaire-Based Polyexposure Assessment Outperforms Polygenic Scores for Classification of Type 2 Diabetes in a Multiancestry Cohort.

Environmental exposures may have greater predictive power for type 2 diabetes than polygenic scores (PGS). Studies examining environmental risk factors, however, have included only individuals with European ancestry, limiting the applicability of results. We conducted an exposome-wide association study in the multiancestry Personalized Environment and Genes Study to assess the effects of environmental factors on type 2 diabetes. Using logistic regression for single-exposure analysis, we identified exposures associated with type 2 diabetes, adjusting for age, BMI, household income, and self-reported sex and race. To compare cumulative genetic and environmental effects, we computed an overall clinical score (OCS) as a weighted sum of BMI and prediabetes, hypertension, and high cholesterol status and a polyexposure score (PXS) as a weighted sum of 13 environmental variables. Using UK Biobank data, we developed a multiancestry PGS and calculated it for participants. We found 76 significant associations with type 2 diabetes, including novel associations of asbestos and coal dust exposure. OCS, PXS, and PGS were significantly associated with type 2 diabetes. PXS had moderate power to determine associations, with larger effect size and greater power and reclassification improvement than PGS. For all scores, the results differed by race. Our findings in a multiancestry cohort elucidate how type 2 diabetes odds can be attributed to clinical, genetic, and environmental factors and emphasize the need for exposome data in disease-risk association studies. Race-based differences in predictive scores highlight the need for genetic and exposome-wide studies in diverse populations.

Worker’s Perceptions and Attitudes of Coal-dust Exposure and Health Hazards: Case of a Coal-fired Power Station in Southern Africa

Introduction: Exposure to coal dust is one of the major health hazards that result in respiratory problems in the coal industry. Literature on workers’ perceptions of coal dust exposure and its health effects is limited. This study aimed to establish workers’ perceptions and attitudes about coal dust exposure and health hazards. Methods: The study used a descriptive cross-sectional design and stratified sampling approach to select 152 workers from a coal-fired power station. Quantitative data was collected using a structured interviewer-administered questionnaire to solicit information on age, gender, work experience, knowledge and perception, with Chi-square tests used for inferential analysis. The study was conducted at Bulawayo Power Station, Zimbabwe. Results: Respondents between 18 to 39 years were the majority. 72.4% had worked at the coal-fired power station for more than a year. Most respondents were aware of the sources of coal dust, its exposure routes, the frequency of exposure that may result in respiratory problems, health effects and methods of prevention. Most respondents perceived they were exposed to coal dust, which they identified as a significant health hazard; they were at risk of having respiratory difficulties and could be protected from its exposure. There was no correlation between workers’ perception of coal dust exposure and their work experience. Conclusion: Workers were knowledgeable of the health hazards associated with coal dust. Coal dust was perceived as the main health hazard resulting in respiratory complications. The perception was the same among workers with different work experiences.

In Vitro Metabolite Profiling and Anti-Inflammatory Activities of Rhodomyrtus Tomentosa with Red Blood Cell Membrane Stabilization Methods.

Rhodomyrtus Tomentosa (Karamunting) is one of South Kalimantan's biodiversity. In previous research on asthma and coal dust exposure models, nebulization with an ethanol extract of R. tomentosa leaves has been shown to reduce inflammatory cells. This study aimed to investigate the anti-inflammatory activity on the stabilization of red blood cell membranes and to identify the chemical compounds present in extracts of R. tomentosa leaves. Anti-inflammatory effect of R. tomentosa leaves was evaluated by in vitro red blood cell membrane stabilization methods. Nonsteroidal anti-inflammatory sodium diclofenac was used as the reference drug. The content of chemical compounds in the ethanol extract of R. tomentosa leaves was identified using Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS). The results of inhibition of red blood cells membrane lysis showed the n-hexane fraction (concentration 25 ppm), ethyl acetate fraction (concentration 50 ppm), and a fraction of water (concentration 50 ppm) with an inhibition level of 54.5%, 81.8%, 63.6%, respectively. The ethyl acetate fraction showed the highest inhibition of hemolysis. This result is not significantly different from the standard anti-inflammatory sodium diclofenac (90.09%). Oleanonic acid and ursonic acid were two similar metabolites in subfractions ethyl acetate 1, 2, and 3, which may have anti-inflammatory properties. R. Tomentosa leaves can have potency as an anti-inflammatory by increasing the red blood cell membrane stability equal to lysosome cells, depending on the concentration.

NLRP3 rs1539019 is significantly associated with chronic obstructive pulmonary disease in a Chinese Han population: a case-control study.

COPD is a complex respiratory disease characterized by chronic airway inflammation and the airflow limitations are not fully reversible due to the combination of genetic and environmental factors. Genetic factors such as polymorphisms, may affect the susceptibility of COPD. In the present study, we examined the association between the polymorphisms of three genes and COPD risk in a Chinese Han population. A total of 375 COPD patients and 284 control subjects were recruited from November 2018 to June 2021. Data on demographic basic information, smoking status, history of coal dust exposure, and peripheral blood were collected from subjects of two groups. Three polymorphisms (NLRP3 rs1539019, LAMB1 rs4320486, IL-6 rs1800796) were analyzed. Logistic analysis was used to evaluate the genetic contribution of selected SNPs to COPD susceptibility. The AC genotype of NLRP3 rs1539019 significantly decreased COPD risk compared with CC genotype (adjusted OR = 0.508, 95% CI 0.336-0.767). In the stratification analyses, the AC genotype significantly decreased the risk of COPD in subjects aged 60 and over (p=0.005; adjusted OR = 0.553; 95% CI 0.366-0.835) with current smoking status (p=0.002; adjusted OR = 0.419; 95% CI 0.240-0.732) when compared with AA+CC genotype. Moreover, a significantly decreased risk for GOLD III COPD was found in genotype AC of NLRP3 rs1539019 (p=0.006; adjusted OR = 0.502; 95% CI 0.306-0.822). Our present study revealed that the genotype AC of NLRP3 rs1539019 is related to a decreased risk of COPD in a Chinese Han population, a large-sample, multi-center, multi-ethnic study is needed to further confirm our study.

Glycogen metabolism reprogramming promotes inflammation in coal dust-exposed lung

Long-term coal dust exposure triggers complex inflammatory processes in the coal workers’ pneumoconiosis (CWP) lungs. The progress of the inflammation is reported to be affected by disordered cell metabolism. However, the changes in the metabolic reprogramming associated with the pulmonary inflammation induced by the coal dust particles are unknown. Herein, we show that coal dust exposure causes glycogen accumulation and the reprogramming of glucose metabolism in the CWP lung. The glycogen accumulation caused by coal dust is mainly due to macrophages, which reprogram glycogen metabolism and trigger an inflammatory response. In addition, 2-deoxy-D-glucose (2-DG) reduced glycogen content in macrophages, which was accompanied by mitigated inflammation and restrained NF-κB activation. Accordingly, we have pinpointed a novel and crucial metabolic pathway that is an essential regulator of the inflammatory phenotype of coal dust-exposed macrophages. These results shed light on new ways to regulate CWP inflammation.

Thermogravimetric Analysis of Respirable Coal Mine Dust for Simple Source Apportionment

ABSTRACT Resurgence of coal mine dust lung diseases in the central Appalachian region of the United States and elsewhere has spurred a range of efforts to better understand respirable coal mine dust (RCMD) exposures and sources. Thermogravimetric analysis (TGA) of RCMD samples can enable the dust mass to be fractionated into three main components: coal, non-carbonate minerals, and carbonates. These are expected to approximate, respectively, the three primary dust sources in many underground mines: the coal seam being mined, the surrounding rock strata (i.e., typically dominated by non-carbonate minerals) being drilled or mined along with the coal, and the rock dust products (i.e., typically made from carbonate-rich limestone or dolostone) being applied in the mine to mitigate explosibility hazards. As proof of concept, TGA was applied to respirable dust samples that were laboratory-generated from real source materials representing 15 mines. Except in the case of two mines, compositional results were generally consistent with expectations. TGA was also applied to RCMD samples collected in standard locations of 23 mines (including the 15 mines represented by the dust source materials). Results showed significantly different compositions with respect to sampling location and geographic region (i.e., within and outside of central Appalachia). To further interpret the RCMD results, a simple source apportionment model was built using the dust compositions yielded from the source materials analysis. Model results indicated that, on average, about twice as much dust was sourced from mining into rock strata than from mining the target coal seam. This finding is particularly important for mines extracting relatively large amounts of rock along with the coal or for mines that frequently encounter high-silica rock strata.

Serum metabolic profiling of coal worker's pneumoconiosis using untargeted lipidomics.

In this work, untargeted lipidomics was employed to analyze the effects of coal dust exposure on serum metabolite profiles. Furthermore, the potential of differential metabolites as novel biomarkers for diagnosis was investigated by binary logistic classification model. Nineteen differential metabolites were found among the three groups. The compounds were enriched in pathways associated with linoleic acid metabolism and pyrimidine metabolism. Fifty-three differential metabolites were found in coal dust-exposed people and CWP patients, and they were mainly enriched in glycerophospholipid metabolism. Three differential metabolites were correlated with lung function values. The diagnostic model, composed of lysoPI (16:0/0:0), bilirubin, and lysoPC (24:1/0:0), showed strong discrimination ability between dust-exposed people and CWP patients. The sensitivity, specificity, and AUC values of the model were 0.869, 0.600, and 0.750, respectively. The results suggest that coal worker's pneumoconiosis causes abnormal lipid metabolism in the body. A diagnostic model may aid current CWP diagnostic methods, and lysoPI (16:0/0:0), bilirubin, and lysoPC (24:1/0:0) can be used as potential CWP biomarkers. Further study is warranted to validate the findings in larger populations.