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

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 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

Objective: To understand the social security situation of current cases of pneumoconiosis in non-coal mine industries in Jiangsu Province, and to provide reference for the treatment and security work of pneumoconiosis patients. Methods: From January to October 2020, a follow-up survey was conducted on 4038 cases of pneumoconiosis in non-coal mine industries of the province from October 1949 to December 2019. The age, type of pneumoconiosis, industry type, and social security status of the patients were collected. Namely, work-related injury insurance, employer compensation, basic medical insurance for urban and rural residents, major illness insurance, etc. SPSS 19.0 was used for statistical description and analysis. Results: The cases of pneumoconiosis in non-coal mine industries in Jiangsu Province ranged in age from 36 to 105 (70.78±8.43) years old, and had been exposed to dust for 1 to 55 (19.27±9.29) years. Silicosis was the main form (3875 cases, 95.96%), and non-metallic mining and dressing industry was the main form (2618 cases, 64.83%). A total of 3991 cases (98.84%) of pneumoconiosis patients enjoyed social security, most of them were urban and rural residents with basic medical insurance (3624 cases, 89.75%), but there were still 47 patients without any social security. 15 cases (0.37%) enjoyed the subsistence allowance, with the monthly allowance amount ranging from 104 to 3960 yuan, with the average amount of 954.87 yuan/month. Conclusion: In Jiangsu Province, the proportion of pneumoconiosis patients in non-coal mine industries enjoying social security is relatively high, but there are still patients who do not enjoy any social security, and the difference in the amount of subsistence allowance is slightly larger. It is necessary to further improve the medical security of pneumoconiosis patients and improve their quality of life.
Humans ; Adult ; Middle Aged ; Aged ; Aged, 80 and over ; Social Security ; Prevalence ; Quality of Life ; Pneumoconiosis/epidemiology* ; Silicosis/epidemiology* ; Etoposide ; Ifosfamide ; Mesna ; Coal Mining ; China/epidemiology*

Objective: To analyze the clinical diagnostic characteristics of pneumoconiosis patients of migrant workers in Hunan Province, and to provide scientific basis for the prevention and treatment of pneumoconiosis. Methods: In February 2022, through the Hunan Provincial Medical Treatment and Assistance Information Platform for Pneumoconiosis Migrant Workers, the cases of irresponsible subjects with pneumoconiosis that were first diagnosed clinically in Hunan Province from January 2017 to December 2021 were collected, and analyzed their gender, age, length of service, types of pneumoconiosis, stages of pneumoconiosis, and comorbidities. Results: From January 2017 to December 2021, there were a total of 26131 cases of irresponsible pneumoconiosis patients diagnosed clinically in Hunan Province, with males accounting for 99.8% (26072 cases) and an average age of (60.66±8.04) years old. Among the 26131 patients, coal workers' pneumoconiosis and silicosis were the main causes, with 16816 and 9078 cases respectively, accounting for 99.1% of the diagnosed cases. There were 8640 cases (33.1%) of stageⅠpneumoconiosis, 6601 cases (25.2%) of stage Ⅱ pneumoconiosis, and 10890 cases (41.7%) of stage Ⅲ pneumoconiosis. 2051 patients experienced complications. The average age of exposure to dust of 26131 patients was (17.81±9.69) years, and the age of exposure to dust in silicosis patients was (14.60±9.62) years. The working age of coal worker's pneumoconiosis was (19.60±9.26) years. Compared with coal workers' pneumoconiosis patients, silicosis patients had a shorter working time exposed to dust, and the difference was statistically significant (P<0.05) . Conclusion: Coal workers' pneumoconiosis and silicosis are mainly diagnosed for the first time in migrant workers' pneumoconiosis patients in Hunan Province. Pneumoconiosis patients should be diagnosed in time, which is conducive to treatment and rehabilitation.
Male ; Humans ; Middle Aged ; Aged ; Child ; Adolescent ; Young Adult ; Adult ; Child, Preschool ; Coal Mining ; Pneumoconiosis/epidemiology* ; Silicosis ; Anthracosis/epidemiology* ; Dust ; Coal ; China/epidemiology*

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