BACKGROUND: It is inaccurate to reflect the level of dust exposure through working years. Furthermore, identifying a predictive indicator for lung function decline is significant for coal miners. The study aimed to explored whether club cell secretory protein (CC16) levels can reflect early lung function changes. METHODS: The cumulative respiratory dust exposure (CDE) levels of 1,461 coal miners were retrospectively assessed by constructed a job-exposure matrix to replace working years. Important factors affecting lung function and CC16 were selected by establishing random forest models. Subsequently, the potential of CC16 to reflect lung injury was explored from multiple perspectives. First, restricted cubic spline (RCS) models were used to compare the trends of changes in lung function indicators and plasma CC16 levels after dust exposure. Then mediating analysis was performed to investigate the role of CC16 in the association between dust exposure and lung function decline. Finally, the association between baseline CC16 levels and follow-up lung function was explored. RESULTS: The median CDE were 35.13 mg/m³-years. RCS models revealed a rapid decline in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and their percentages of predicted values when CDE exceeded 25 mg/m³-years. The dust exposure level (<5 mg/m³-years) causing significant changes in CC16 was much lower than the level (25 mg/m³-years) that caused changes in lung function indicators. CC16 mediated 11.1% to 26.0% of dust-related lung function decline. Additionally, workers with low baseline CC16 levels experienced greater reductions in lung function in the future. CONCLUSIONS CC16 levels are more sensitive than lung indicators in reflecting early lung function injury and plays mediating role in lung function decline induced by dust exposure. Low baseline CC16 levels predict poor future lung function.
Uteroglobin/blood* ; Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Lung Injury/chemically induced* ; Coal Mining ; Biomarkers/blood* ; China/epidemiology* ; Air Pollutants, Occupational ; Female

To explore the differences in biological gas production in the waterlogged zone of a coal seam fire-affected area, in this study the in-situ gas production experiment was conducted with the mine water from aquitard layers in coal seam fire zones in Xinjiang. The results showed that the biogas production first increased and then decreased with the increase in distance, and the highest gas production reached 216.55 mL. The changes in key metabolic pathways during the anaerobic fermentation of coal were analyzed, which showed that as the distance from the aquitard layer in the coal seam fire zone increased, the methanogenesis pathways gradually shifted from acetic acid decarboxylation and carbon dioxide reduction to acetic acid decarboxylation and methylamine methanogenesis. The significant variability in the in-situ mine water reservoir conditions contributed to the differences. In addition, the reservoir pressure and temperature increased as the distance from the fire zone became longer, and the salinity of the farthest mine water in the reverse fault was the highest due to the lack of groundwater supply. Pearson correlation analysis revealed significant correlations of microbial communities with key functional genes and the types and concentrations of ions. The ions significantly influencing microbial enzymatic metabolic activities included Al³⁺, Fe²⁺, Co²⁺, Ni²⁺, Cu²⁺, Zn²⁺, Mg²⁺, PO₄^3-, and Mo⁶⁺. The differences in metabolic pathways were attributed to the integrated effects of a co-occurring environment with multiple ions. The gas production simulation experiments and metagenomic analyses provide data support for the practical application of in-situ biogas experiments, laying a foundation for engineering applications.
Biofuels ; Coal ; Methane/biosynthesis* ; Fires ; Groundwater ; Coal Mining ; Fermentation ; China ; Anaerobiosis

Humans ; Vascular Stiffness ; Coal Mining ; Occupational Diseases/epidemiology* ; Risk Factors ; Coal ; Miners

Objective: Differential flora and differential metabolites shared by the intestinal and respiratory tracts of rats were screened to analyze the possible role of changes in intestinal flora and metabolites in the progression of pneumoconiosis in rats. Methods: In April 2020, 18 SD rats were randomly divided into three groups (control group, coal mine dust group and silica group, 6 in each group) , rats in the coal mine dust group and silica group were perfused with 1 ml of 50 mg/ml coal mine well dust suspension and silica suspension by nontracheal exposure, respectively. While rats in the control group were perfused with an equal dose of sterilized normal saline. Twenty four weeks after dust staining, rat feces, throat swabs, and lung lavages were collected. 16SrDNA gene sequencing and UHPLC-QTOF-MS untargeted metabolomics were used to analyze the flora and metabolites in feces, throat swabs and lung lavage fluid of rats in each group, to screen for shared differential flora and shared differential metabolites in intestinal and respiratory tract, and the correlation analysis between the differential flora and metabolites was performed using Spearman's statistics. Results: Compared with the control group, a total of 9 species shared differential flora between intestinal and respiratory tract were screened at phylum level, and a total of 9 species shared differential genus between intestinal and respiratory tract were screened at genus level in the coal mine dust group, mainly Firmicutes, Actinobacteria, Streptococcus, Lactobacillus, etc. Compared with the control group, a total of 9 shared differential flora were screened at the phylum level, and a total of 5 shared differential genus were screened at the genus level in the silica group, mainly Proteobacteria, Actinobacteria, Allobactera, Mucilaginibacter, etc. Compared with the control group, a total of 7 shared differential metabolites were screened for up-regulation of Stigmatellin, Linalool oxide and Isoleucine-leucine in both intestinal and respiratory tract in the coal mine dust group. Compared with the control group , a total of 19 shared differential metabolites werescreened in the silica group, of which Diethanolamine, 1-Aminocyclopropanecarboxylic acid, Isoleucine-leucine, Sphingosine, Palmitic acid, D-sphinganine, 1, 2-dioleoyl-sn-glycero-3-phosphatidylcholine, and 1-Stearoyl-2-oleoyl-sn-glycerol 3-phosphocholine were up-regulated in both the intestinal and respiratory tract. Conclusion: There is a translocation of intestinal and respiratory flora in pneumoconiosis rats, and rats have an imbalance of lipid metabolism during the progression of pneumoconiosis.
Rats ; Animals ; Isoleucine ; Leucine ; Coal Mining ; Rats, Sprague-Dawley ; Pneumoconiosis ; Dust/analysis* ; Silicon Dioxide ; Coal

Objective: To construct and verify a light-weighted convolutional neural network (CNN), and explore its application value for screening the early stage (subcategory 0/1 and stage Ⅰ of pneumoconiosis) of coal workers' pneumoconiosis (CWP) from digital chest radiography (DR) . Methods: A total of 1225 DR images of coal workers who were examined at an Occupational Disease Prevention and Control Institute in Anhui Province from October 2018 to March 2021 were retrospectively collected. All DR images were collectively diagnosed by 3 radiologists with diagnostic qualifications and gave diagnostic results. There were 692 DR images with small opacity profusion 0/- or 0/0 and 533 DR images with small opacity profusion 0/1 to stage Ⅲ of pneumoconiosis. The original chest radiographs were preprocessed differently to generate four datasets, namely 16-bit grayscale original image set (Origin16), 8-bit grayscale original image set (Origin 8), 16-bit grayscale histogram equalized image set (HE16) and 8-bit grayscale histogram equalized image set (HE8). The light-weighted CNN, ShuffleNet, was applied to train the generated prediction model on the four datasets separately. The performance of the four models for pneumoconiosis prediction was evaluated on a test set containing 130 DR images using measures such as the receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, and Youden index. The Kappa consistency test was used to compare the agreement between the model predictions and the physician diagnosed pneumoconiosis results. Results: Origin16 model achieved the highest ROC area under the curve (AUC=0.958), accuracy (92.3%), specificity (92.9%), and Youden index (0.8452) for predicting pneumoconiosis, with a sensitivity of 91.7%. And the highest consistency between identification and physician diagnosis was observed for Origin16 model (Kappa value was 0.845, 95%CI: 0.753-0.937, P<0.001). HE16 model had the highest sensitivity (98.3%) . Conclusion: The light-weighted CNN ShuffleNet model can efficiently identify the early stages of CWP, and its application in the early screening of CWP can effectively improve physicians' work efficiency.
Humans ; Retrospective Studies ; Anthracosis/diagnostic imaging* ; Pneumoconiosis/diagnostic imaging* ; Coal Mining ; Neural Networks, Computer ; Coal

The underground environment is dark and humid, and it is easy to breed pathogenic microorganisms. A lump in the right lung of a coal mine underground transport worker was found druing occupational health examination. CT examination showed that the lump was located in the posterior segment of the upper lobe of the right lung, with point strip calcification, liquefaction necrosis, and proximal bronchial stenosis and occlusion. MRI examination FS-T(2)WI and DWI showed "target sign", annular low signal around the central high signal, and low mixed signal around the periphery, and annular high signal in the isosignal lesions on T(1)WI. Then the pulmonary aspergillus infection was confirmed by pathology.
Humans ; Coal ; Miners ; Pneumonia ; Lung ; Aspergillosis ; Coal Mining

Humans ; Coal ; Dust/analysis* ; Anthracosis ; China/epidemiology* ; Coal Mining ; Occupational Exposure

BACKGROUND: Xuanwei and Fuyuan are rural counties, located in the late Permian coal poly area of eastern Yunnan and western Guizhou, where lung cancer mortality rates are among the highest in the China, with similarity for both men and women, younger age at diagnosis and death, and higher in rural areas than in urban areas. In this paper, long-term follow-up of lung cancer cases in local peasants was conducted to observe their survival prognosis and its influencing factors. METHODS: Data of patients diagnosed with lung cancer from January 2005 to June 2011, who had lived in Xuanwei and Fuyuan counties for many years, were collected from 20 hospitals at the local provincial, municipal and county levels. To estimate survival outcomes, individuals were followed up until the end of 2021. The 5-year, 10-year and 15-year survival rates were estimated using the Kaplan-Meier method. Survival differences were examined with Kaplan-Meier curves and Cox proportional hazards models. RESULTS: A total of 3,017 cases were effectively followed up (2,537 peasants and 480 non-peasants). The median age at diagnosis was 57 years, and the median follow-up time was 122 months. During the follow-up period, 2,493 cases (82.6%) died. The distribution of cases by clinical stage was as follows: stage I (3.7%), stage II (6.7%), stage III (15.8%), stage IV (21.1%) and unknown stage (52.7%). Treatment at the provincial, municipal and county-level hospitals accounted for 32.5%, 22.2% and 45.3%, respectively, and surgical treatment was performed in 23.3% of cases. The median survival time was 15.4 months (95%CI: 13.9-16.1), and the 5-year, 10-year and 15-year overall survival rates were 19.5% (95%CI: 18.0%-21.1%), 7.7% (95%CI: 6.5%-8.8%) and 2.0% (95%CI: 0.8%-3.9%), respectively. Peasants with lung cancer had a lower median age at diagnosis, higher proportion residing in remote rural areas, and higher use of bituminous coal as a household fuel. They also have a lower proportion of early-stage cases, treatment at provincial or municipal hospitals, and surgical treatment, leading to poorer survival outcomes (HR=1.57). Even when considering factors such as gender, age, residential location, clinical stage at diagnosis, histological type, hospital level of service, and surgical intervention, peasants still exhibit a survival disadvantage. Multivariable Cox model analysis comparing peasants and non-peasants reveals that surgical intervention, tumor-node-metastasis (TNM) stage, and hospital level of service are common factors influencing survival prognosis, while the use of bituminous coal as a household fuel, hospital level of service and adenocarcinoma (compared to squamous cell carcinoma) are independent prognostic factors for lung cancer survival among peasants. CONCLUSIONS The lower lung cancer survival rate among peasants is associated with their lower socioeconomic status, lower proportion of early-stage diagnoses, lower proportion of surgical interventions, and treatment at provincial-level hospitals. Furthermore, the impact of other factors such as high-risk exposure to bituminous coal pollution on survival prognosis requires further investigation.
Male ; Humans ; Female ; Lung Neoplasms/epidemiology* ; China/epidemiology* ; Adenocarcinoma ; Carcinoma, Squamous Cell ; Coal

Objective: To investigate the spatial distribution characteristics and correlation between the prevalence of dental fluorosis and the chemical elemental composition of drinking water sources in coal-fired fluorosis areas. Methods: Based on the survey data on the prevalence of dental fluorosis at CDC in Guizhou Province in 2022, 274 original surface drinking water sources were collected in typical coal-fired fluorosis areas, and fluoride (F), calcium (Ca), magnesium (Mg), aluminum (Al), titanium (Ti), chromium (Cr), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), molybdenum (Mo), cadmium (Cd), barium (Ba), lead (Pb) 17 elements; apply Moran's I index, Getis-Ord Gi* hotspot analysis of the global spatial autocorrelation of chemical elements in drinking water and the degree of aggregation of each element on the local area, and correlation analysis with the prevalence of dental fluorosis in the region. Results: Except for Cu, Zn, and Cd, global spatial autocorrelation Moran's I was negative, and all other elements were positive. F, Ca, Al, Ti, As, Mo, Cd, and Cu elements showed high values of aggregation in the southeastern low-altitude area; Mg, Ba, Pb, Cr, Mn, and Fe elements were mainly aggregated in the central altitude terrain transition area, Zn and Se elements in water sources are significantly positively correlated with the prevalence of dental fluorosis (P<0.05). In contrast, F, Mg, Al, Ti, As, Mo, Cd, Ba, and Pb elements negatively correlate (P<0.05). Elements in the central region were high-high aggregation, as a hot spot aggregation area with high disease incidence, while F, Al, Mn, Mo, Cd, and Ba elements in the western region were low-low aggregation, as a cold spot aggregation area with a low incidence of fluorosis. Conclusions: The risk of population fluoride exposure in surface drinking water sources is shallow. However, the chemical element content of drinking water sources in coal-fired polluted endemic fluorosis areas has prominent spatial geographical distribution characteristics. There is a significant spatial aggregation effect with the prevalence of dental fluorosis, which may play a synergistic or antagonistic effect on the occurrence and prevalence of dental fluorosis.
Humans ; Drinking Water ; Prevalence ; Coal ; Fluorides/adverse effects* ; Cadmium ; Fluorosis, Dental/epidemiology* ; Lead ; Selenium ; Arsenic

Objective: To understand the exposure level of dust and noise in the mining industry and provide data support for revising policy for the prevention and control of occupational diseases. Methods: In May 2022, Data was collected through the National Surveillance Program for Occupational Hazards in the Workplace. Descriptive analysis was conducted for dust and noise levels by industry type and enterprise size from 7, 679 enterprises in the mining industry among 29 provincial regions nationwide. Results: The enterprises in the mining industry included in the National Surveillance Program for Occupational Hazards in the Workplace are mainly small and micro, accounting for 47.97% (3684/7679) and 30.00% (230/7679) respectively. The industry is mainly compred of employers in the non-metallic ming and beneficiation industry, accounting for 50.25% (3859/7679). Among the enterprises with silica dust, coal dust, and noise hazards, the proportion of enterprises where total dust concentration and noise intensity exceed the standard is higher than 50%. 30% of the posts are with an exposure level of silica dust, coal dust, and noise that exceeds the standard. The exceedance rate and the median of the time-weighted average concentration of total coal dust among large and medium-sized enterprises are higher than those among small and micro-sized enterprises (P<0.05) . Conclusion: The dust and noise hazards in the mining industry are lower than in the past in China, but more than 25% of workers are still at a high risk of occupational pneumoconiosis and noise deafness. Therefore, intervention and surveillance strategies should be strengthened in the future.
Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Occupational Health ; Coal ; Silicon Dioxide/analysis* ; Coal Mining