[Changes of lung function and inflammatory factors in rat models of coal workers' pneumoconiosis].

Objective: To observe the changes of lung function and inflammatory factors in rat models of coal workers' pneumoconiosis at different time points. Methods: In June 2021, 96 healthy male SD rats with SPF grade were divided into 1, 3, and 6-month control group and dust staining group (coal dust group, coal silica dust group, quartz group) according to random number table method, with 8 rats in each group. After one week of adaptive feeding, a one-time non-exposed tracheal perfusion method (1 ml/ piece) was used. The dust dyeing group was given 50 g/L coal dust, coal silica mixed dust and quartz dust suspension, respectively, and the control group was given 0.9% normal saline solution. At 1, 3 and 6 months after perfusion, lung function was detected by animal lung function apparatus, then all lung tissues and alveolar lavage fluid were killed, and lung histopathological morphological changes were observed by HE staining, and the contents of interleukin (IL-1ß), IL-18, IL-4 and IL-10 in alveolar lavage fluid were detected by ELISA. One-way analysis of variance was used to compare groups. Two factors (inter-group treatment factor (4 levels) and observation time factor (3 levels) ) were used in the analysis of the effects of inter-group treatment and treatment time on related indicators. Results: HE staining results showed that coal spot appeared in the lung tissue of coal dust group, coal spot and coal silicon nodule appeared in the lung tissue of coal dust group, and silicon nodule appeared in the lung tissue of quartz group. Compared with the control group, the forced vital capacity (FVC) and forced expiratory volume at 0.2 second (FEV(0.2)) of rats in the dust staining group had interaction between the treatment and treatment time (P<0.05). With the increase of dust dyeing time, FVC and FEV(0.2) decreased significantly at 3-6 months of dust dyeing, and the maximum gas volume per minute (MVV) decreased significantly at 1-3 months of dust dyeing (P<0.05). The lowest lung function index was in quartz group, followed by coal-silica group and coal-dust group. There were statistically significant differences in the main effect and interaction effect of the pro-inflammatory factor IL-18 among all groups in treatment and treatment time (IL-18: F=70.79, 45.97, 5.90, P<0.001), and interaction existed. The highest content of inflammatory factors in alveolar lavage fluid of all dust groups was quartz group, followed by coal silica group and coal dust group. There were significant differences in the main effect and interaction effect of anti-inflammatory factors between groups and treatment time (IL-4: F=41.55, 33.01, 5.23, P<0.001, <0.001, <0.001; IL-10: F=7.46, 20.80, 2.91, P=0.002, <0.001, 0.024), and there was interaction. The highest content of anti-inflammatory factor was in quartz group, followed by coal silica group and coal dust group. Conclusion: Lung function decreased and levels of inflammatory fators increased in rat models of coal workers' pneumoconiosis, with the quartz group being the most severely damaged. Lung function is mainly impaired in thrid-six months, and the content of inflammatory factors begins to change in first-thrid months. MVV are the earliest and most obvious in lung function. IL-18 is suitable for monitoring changes in the pro-inflammatory response of coal workers' pneumoconiosis, and IL-10 is suitable for monitoring changes in anti-inflammatory response.

Airway bacterial microbiome signatures correlate with occupational pneumoconiosis progression.

Recent evidence has pinpointed a key role of the microbiome in human respiratory health and disease. However, significant knowledge gaps still exist regarding the connection between bacterial communities and adverse effects caused by particulate matters (PMs). Here, we characterized the bacterial microbiome along different airway sites in occupational pneumoconiosis (OP) patients. The sequencing data revealed that OP patients exhibited distinct dysbiosis in the composition and function of the respiratory microbiota. To different extents, there was an overall increase in the colonization of microbiota, such as Streptococcus, implying a possible intrusion pathway provided by exogenous PMs. Compared to those of healthy subjects, unhealthy living habits (i.e., smoking) had a greater impact on microbiome changes in OP patients. Importantly, the associations between the bacterial community and disease indicators indicated that specific bacterial species, including Prevotella, Actinobacillus, and Leptotrichia, might be surrogate markers of OP disease progression. Collectively, our results highlighted the potential participation of the bacterial microbiota in the pathogenesis of respiratory diseases and helped in the discovery of microbiome-based diagnostics for PM-induced disorders.

Computed Tomography of Contemporary Occupational Lung Disease: A Pictorial Review.

Occupational lung disease remains one of the most common work-related illnesses and accounts for most deaths from occupational illness. Occupational lung diseases often have delayed manifestation over decades and nonspecific clinical presentations, making it challenging for clinicians to promptly identify the disease and implement preventive measures. Radiologists play a crucial role in identifying and diagnosing occupational lung diseases, allowing for removal of the exposure and early medical intervention. In this review, we share our clinical and radiologic approach to diagnosing occupational lung disease and its subtypes. A collection of sample cases of occupational lung diseases commonly encountered in the modern era at a large Canadian university hospital is included to facilitate understanding. This review will provide radiologists with valuable insights into recognizing and diagnosing occupational lung diseases.

Caplan Syndrome Mimicking Progressive Massive Fibrosis on CT: A Case Report.

This report presents a unique case of Caplan syndrome that mimicked accelerated progressive massive fibrosis. The patient, a former coal miner, had been diagnosed with coal worker's pneumoconiosis 15 years prior and had been treated for rheumatoid arthritis for over 20 years. Accelerated progressive massive fibrosis and the development of multiple nodules with cavitation in the basal lungs were subsequently observed on serial CT scans. Here, the CT manifestations of Caplan syndrome are highlighted in a case in which Caplan syndrome mimicked accelerated progressive massive fibrosis.

Application of improved Unet network in the recognition and segmentation of lung CT images in patients with pneumoconiosis.

BACKGROUND: Pneumoconiosis has a significant impact on the quality of patient survival. This study aims to evaluate the performance and application value of improved Unet network technology in the recognition and segmentation of lesion areas of lung CT images in patients with pneumoconiosis. METHODS: A total of 1212 lung CT images of patients with pneumoconiosis were retrospectively included. The improved Unet network was used to identify and segment the CT image regions of the patients' lungs, and the image data of the granular regions of the lungs were processed by the watershed and region growing algorithms. After random sorting, 848 data were selected into the training set and 364 data into the validation set. The experimental dataset underwent data augmentation and were used for model training and validation to evaluate segmentation performance. The segmentation results were compared with FCN-8s, Unet network (Base), Unet (Squeeze-and-Excitation, SE + Rectified Linear Unit, ReLU), and Unet + + networks. RESULTS: In the segmentation of lung CT granular region with the improved Unet network, the four evaluation indexes of Dice similarity coefficient, positive prediction value (PPV), sensitivity coefficient (SC) and mean intersection over union (MIoU) reached 0.848, 0.884, 0.895 and 0.885, respectively, increasing by 7.6%, 13.3%, 3.9% and 6.4%, respectively, compared with those of Unet network (Base), and increasing by 187.5%, 249.4%, 131.9% and 51.0%, respectively, compared with those of FCN-8s, and increasing by 14.0%, 31.2%, 4.7% and 9.7%, respectively, compared with those of Unet network (SE + ReLU), while the segmentation performance was also not inferior to that of the Unet + + network. CONCLUSIONS: The improved Unet network proposed shows good performance in the recognition and segmentation of abnormal regions in lung CT images in patients with pneumoconiosis, showing potential application value for assisting clinical decision-making.

Research progress on the pathogenesis and prediction of pneumoconiosis among coal miners.

Pneumoconiosis is the most common occupational disease among coal miners, which is a lung disease caused by long-term inhalation of coal dust and retention in the lungs. The early stage of this disease is highly insidious, and pulmonary fibrosis may occur in the middle and late stages, leading to an increase in patient pain index and mortality rate. Currently, there is a lack of effective treatment methods. The pathogenesis of pneumoconiosis is complex and has many influencing factors. Although the characteristics of coal dust have been considered the main cause of different mechanisms of pneumoconiosis, the effects of coal dust composition, particle size and shape, and coal dust concentration on the pathogenesis of pneumoconiosis have not been systematically elucidated. Meanwhile, considering the irreversibility of pneumoconiosis progression, early prediction for pneumoconiosis patients is particularly important. However, there is no early prediction standard for pneumoconiosis among coal miners. This review summarizes the relevant research on the pathogenesis and prediction of pneumoconiosis in coal miners in recent years. Firstly, the pathogenesis of coal worker pneumoconiosis and silicosis was discussed, and the impact of coal dust characteristics on pneumoconiosis was analyzed. Then, the early diagnostic methods for pneumoconiosis have been systematically introduced, with a focus on image collaborative computer-aided diagnosis analysis and biomarker detection. Finally, the challenge of early screening technology for miners with pneumoconiosis was proposed.

Toxicity and biokinetics following pulmonary exposure to aluminium (aluminum): A review.

During the manufacture and use of aluminium (aluminum), inhalation exposure may occur. We reviewed the pulmonary toxicity of this metal including its toxicokinetics. The normal serum/plasma level based on 17 studies was 5.7 ± 7.7 µg Al/L (mean ± SD). The normal urine level based on 15 studies was 7.7 ± 5.3 µg/L. Bodily fluid and tissue levels during occupational exposure are also provided, and the urine level was increased in aluminium welders (43 ± 33 µg/L) based on 7 studies. Some studies demonstrated that aluminium from occupational exposure can remain in the body for years. Excretion pathways include urine and faeces. Toxicity studies were mostly on aluminium flakes, aluminium oxide and aluminium chlorohydrate as well as on mixed exposure, e.g. in aluminium smelters. Endpoints affected by pulmonary aluminium exposure include body weight, lung function, lung fibrosis, pulmonary inflammation and neurotoxicity. In men exposed to aluminium oxide particles (3.2 µm) for two hours, lowest observed adverse effect concentration (LOAEC) was 4 mg Al2O3/m3 (= 2.1 mg Al/m3), based on increased neutrophils in sputum. With the note that a similar but not statistically significant increase was seen during control exposure. In animal studies LOAECs start at 0.3 mg Al/m3. In intratracheal instillation studies, all done with aluminium oxide and mainly nanomaterials, lowest observed adverse effect levels (LOAELs) started at 1.3 mg Al/kg body weight (bw) (except one study with a LOAEL of ∼0.1 mg Al/kg bw). The collected data provide information regarding hazard identification and characterisation of pulmonary exposure to aluminium.

Black Lung Disease Among Coal Miners in Asia: A Systematic Review.

Background: Coal miners are highly prone to occupational health risks, such as black lung disease. This study aims to assess the prevalence of black lung disease and the factors associated with black lung disease among coal miners in Asia. Method: This systematic review, conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, searched through the scientific literature of the following databases: EBSCO, ScienceDirect, PubMed, and Scopus. We selected articles that studied black lung disease among coal miners from 48 countries in Asia and were published between 2014 and 2023. Article quality was evaluated using the Critical Appraisal Skills Program. Result: The seven articles that we review studied a total of 653,635 coal miners from various types of coal mines from three countries in Asia. Of these miners, 59,998 experienced black lung disease. Black lung disease is prevalent among 9.18% of coal miners in Asia, which is approximately four times higher than the worldwide prevalence. Common factors that influence black lung disease in Asia include age, years of dust exposure, smoking, drinking, working types, and sizes of mines, type of mines, respiratory functions, spirometry parameters, tenure, lack of attention to occupational health, inefficient surveillance, and weak occupational health service. Conclusion: Although the prevalence of black lung disease among coal miners in Asia is considerably high, it can be addressed through effective prevention measures, monitoring, control, and case reporting.

Prevalence of nano-sized coal mine dust in North and Central Appalachian coal mines - Insights from SEM-EDS imaging.

The increasing prevalence of coal mine dust-related lung diseases in coal miners calls for urgent and meticulous scrutiny of airborne respirable coal mine dust (RCMD), specifically focusing on particles at the nano-level. This necessity is driven by expanding research, including the insights revealed in this paper, that establish the presence and significantly increased toxicity of nano-sized coal dust particles in contrast to their larger counterparts. This study presents an incontrovertible visual proof of these tiny particulates in samples collected from underground mines, utilizing advanced techniques such as scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). The intricate elemental composition of nano-sized coal dust identified through EDS analysis reveals the presence of elements such as silica and iron, which are known to contribute to lung pathologies when inhaled over prolonged periods. The outcomes of the statistical analyses reveal significant relationships between particle size and elemental composition, highlighting that smaller particles tend to have higher carbon content, while larger particles exhibit increased concentrations of elements like silica and aluminum. These analyses underscore the complex interactions within nano-sized coal dust, providing critical insights into their behavior, transport, and health impacts. The nano-sized coal dust could invade the alveoli, carrying these toxic elements from where they are impossible to exhale. The revelation of nano-sized coal dust's existence and the associated health hazards necessitate their incorporation into the regulatory framework governing the coal mining industry. This study lays the groundwork for heightened protective measures for miners, urging the invention of state-of-the-art sampling instruments, comprehensive physicochemical profiling of RCMD nanoparticles, and the pursuit of groundbreaking remedies to neutralize their toxic impact. These findings advocate for a paradigm shift in how the coal mining industry views and handles particulate matter, proposing a re-evaluation of occupational health standards and a call to action for protecting coal miners worldwide.

Deep learning pneumoconiosis staging and diagnosis system based on multi-stage joint approach.

BACKGROUND: Pneumoconiosis has a significant impact on the quality of patient survival due to its difficult staging diagnosis and poor prognosis. This study aimed to develop a computer-aided diagnostic system for the screening and staging of pneumoconiosis based on a multi-stage joint deep learning approach using X-ray chest radiographs of pneumoconiosis patients. METHODS: In this study, a total of 498 medical chest radiographs were obtained from the Department of Radiology of West China Fourth Hospital. The dataset was randomly divided into a training set and a test set at a ratio of 4:1. Following histogram equalization for image enhancement, the images were segmented using the U-Net model, and staging was predicted using a convolutional neural network classification model. We first used Efficient-Net for multi-classification staging diagnosis, but the results showed that stage I/II of pneumoconiosis was difficult to diagnose. Therefore, based on clinical practice we continued to improve the model by using the Res-Net 34 Multi-stage joint method. RESULTS: Of the 498 cases collected, the classification model using the Efficient-Net achieved an accuracy of 83% with a Quadratic Weighted Kappa (QWK) score of 0.889. The classification model using the multi-stage joint approach of Res-Net 34 achieved an accuracy of 89% with an area under the curve (AUC) of 0.98 and a high QWK score of 0.94. CONCLUSIONS: In this study, the diagnostic accuracy of pneumoconiosis staging was significantly improved by an innovative combined multi-stage approach, which provided a reference for clinical application and pneumoconiosis screening.

[EQ-5D-3L based quality of life for patients of pneumoconiosis combined with tuberculosis and its influencing factors].

Objective: To understand the health-related quality of life for patients of pneumoconiosis combined with tuberculosis and its main influencing factors. Methods: This was a cross-sectional study, and 951 patients of pneumoconiosis combined with tuberculosis from the pneumoconiosis survey in 27 provinces and autonomous regions in China from December 2017 to December 2021 were selected for the study. The nonparametric Mann-Whitney test and the Kruskal-Wallis H test were used to compare the health utility values, and multiple linear regression was used for multifactor analysis. AMOS 24.0 was used to establish a structural equation modeling. Results: The mean age of 951 patients of pneumoconiosis combined with tuberculosis was (59.3±12.4) years. The main types were silicosis combined with tuberculosis (62.2%, 591/951) and coal-worker's pneumoconiosis combined with tuberculosis (34.9%, 332/951), and other type pneumoconiosis-combined tuberculosis was 2.9% (28/951). The proportion of patients with stage Ⅰ, Ⅱ, Ⅲ, and unstaged clinical diagnosis was 27.4% (261/951), 26.6% (253/951), 32.5% (309/951) and 13.5% (128/951), respectively. 63.3% (602/951) of study participants suffered from other chronic diseases, and the percentage of patients combined the number of chronic diseases with 1, 2, and more than 3 respectively were 24.1% (229/951), 16.3% (155/951) and 22.9% (218/951). The median and quartiles of health utility values and the mean±standard deviation of self-rating scores of patients of pneumoconiosis combined with tuberculosis were 0.562 (0.482, 0.766) and (53.7±18.4), respectively, which were lower than patients of pneumoconiosis without tuberculosis (Z=-11.29, P<0.001; t=8.97, P<0.01). The health utility values and self-rating scores for patients of pneumoconiosis combined with tuberculosis were significantly different between urban and rural areas (Z= -2.22, P=0.027; t=4.85, P<0.01). Pain/discomfort was the most frequently reported problem in the five-dimensional distribution of problems, followed by daily activities and anxiety/depression, and the difference in the percentage reported by anxiety/depression between urban and rural areas was significant (χ(2)=30.28, P<0.01). The results of multiple linear regression showed that the survey area, body mass index, education level, age, employment status, annual personal income, stage of pneumoconiosis, number of multi-morbidities, hemoptysis, acute exacerbation of symptoms in two-week, social support and minimum living standard were the main influences on the health utility values of the patients of pneumoconiosis combined with tuberculosis (P<0.05). The results of structural equation model showed that economic security and health status directly affected the health-related quality of life among patients of pneumoconiosis combined with tuberculosis and played a chain-mediating effect in the influence of socioeconomic status on the health-related quality of life among patients of pneumoconiosis combined with tuberculosis. Conclusion: Health-related quality of life was poorer in patients of pneumoconiosis with tuberculosis, with pain and discomfort and anxiety/depression problems being more pronounced, and economic status and health status played multiple mediating roles in the influence of general socio-demographic characteristics on quality of life in pneumoconiosis.

[Utilization of outpatient service of pneumoconiosis patients in Chongqing and its influencing factors].

Objective: To understand the utilization and characteristics of outpatient services for pneumoconiosis patients within two weeks in Chongqing, and analyze the influencing factors, so as to provide reference for relevant policy making. Methods: From October 2020 to October 2022, 1771 pneumoconiosis patients who met the inclusion criteria were selected by multi-stage stratified random cluster sampling. A questionnaire survey was conducted on their basic situation, utilization of outpatient services within two weeks, treatment for pneumoconiosis-related symptoms, and selection of medical service institutions using χ(2)-test and logistic regression analysis. Results: All the 1771 pneumoconiosis patients were male, with the average age of (56.1±10.19) years old. In the pneumoconiosis patients were treated in outpatient department within 2 weeks.40.0% (204/510) of aged 41~50 years Rural patients accounted for 87.8% (448/510) ; 65.1% (332/510) of silicosis patients, 37.5% (191/510) of stage II patients, 75.1% (383/510) of patients did not continue to engage in dust work after diagnosis of pneumoconiosis, and 57.1% (291/510) of patients never had work-related injury insurance at work. The outpatient rate within two weeks of pneumoconiosis related assistance and subsistence allowance was 17.6% (90/510) and 12.5% (64/510), respectively. The average self-health score of the patients was (52.9±16.2). 28.2% of the patients had purchased work-related injury insurance; Among the 1204 patients who received the treatment within two weeks, 42.2% were in the outpatient department, 20.7% were in the inpatient department, and 36.9% were self-buyers. There was a significant difference between the different treatment methods of the patients (χ(2)=27.53, P<0.05). There was a significant difference in patients from different residence choosing to visit different medical institutions (χ(2)=13.97, P<0.05). The stage of pneumoconiosis, presence of complications, presence of work injury insurance, self-health score, and whether he/she has been hospitalized in the past year are the important factors affecting the outpatient treatment of pneumoconiosis patients. Conclusion: The utilization of outpatient service of pneumoconiosis patients is influenced by demographic sociology, social support and disease characteristics. The quality of occupational disease medical service in primary health institutions should be strengthened so that pneumoconiosis patients can get convenient and effective treatment. Establish a more perfect social security support system to reduce the disease burden of pneumoconiosis patients.

[Analysis of the epidemiological traits of occupational pneumoconiosis in Qinhuangdao between 1961 and 2020].

Objective: To study the prevalence of occupational pneumoconiosis in Qinhuangdao from 1961 to 2020 and offer a foundation for developing occupational pneumoconiosis prevention and control methods. Methods: In December 2020, the data of occupational pneumoconiosis cases diagnosed by medical institutions with occupational disease diagnosis qualifications in Qinhuangdao City from 1961 to 2020 were collected Anova or kruskal-Walls tests and chi-square tests were used for inter-group comparisons of continuous and categorical variables, and LSD tests or Tamhane T2 tests were used for multiple comparisons. Results: Between 1961 and 2020, 384 cases of pneumoconiosis were documented in Qinhuangdao, of which 382 (99.5%) patients were men and 2 (0.5%) were women. The average dust service duration is 15 (9, 25) years, with a minimum duration of 0.5 years and a maximum duration of 49 years; Cases were primarily distributed in Qinglong Manchu Autonomous County (187 cases, 48.7%) and the Haigang district (160 cases, 41.7%) ; Type of pneumoconiosis was silicosis (340 cases, 88.5%), mainly 273 cases (71.1%) of stage I, 88 cases (22.9%) of stage II, and 23 cases (6.0% of stage III) ; Cases of Phase II and III and with short lengths of service are mainly concentrated in medium-sized, small, private limited liability companies and collective enterprises. Rrock work (166 cases, 43.2%), and loading kiln workers (42 cases, 10.9%) were the main types. Conclusion: Because the distribution of pneumoconiosis cases in Qinhuangdao city is concentrated and the length of service is decreasing, it is important to enhance the oversight of important area, businesses, industries, and job categories in line with the growth of the region's mineral resources.

[Study on the risk factors of coal workers' pneumoconiosis and the mechanism of pyroptosis in peripheral blood].

Objective: To explore the risk factors of coal workers' pneumoconiosis, reveal the molecular mechanism of pyroptosis in peripheral blood of coal workers' pneumoconiosis patients, and provide new strategies and potential diagnostic biomarkers for the treatment of the disease. Methods: From January 1, 2020 to December 31, 2022, workers with suspected occupational diseases who were diagnosed with coal workers' pneumoconiosis in the Third People's Hospital of Xinjiang Uygur Autonomous Region were included in the study, including 77 patients with coal workers' pneumoconiosis stage Ⅰ, 10 patients with stage Ⅱ, 6 patients with stage Ⅲ, and 49 workers with dust-free lung disease as the control group. General information of the subjects was collected, blood samples were collected for routine blood and blood biochemical results, and plasma levels of interleukin (IL) -1ß and IL-18 were measured. Combined with the results of clinical examination, multi-factor ordered logistic regression analysis was carried out to evaluate the influencing factors of coal workers' pneumoconiosis. At the same time, the expression of pyroptosis related proteins in blood cells was detected to reveal the molecular mechanism of coal workers' pneumoconiosis. Results: All 142 subjects were male, with an average age of (51.65±6.31) years old and an average working age of (15.94±9.38) years. There were significant differences in smoking age (F=4.95, P=0.003) and lunch break distribution (H=8.84, P=0.031) among all groups. The hemoglobin content of stage Ⅰ patients was higher than that of stage Ⅱ patients, and the neutrophil percentage of stage Ⅲ patients was higher than that of the other 3 groups (P<0.05). The levels of total bilirubin and indirect bilirubin in stage Ⅰ patients were higher than those in control group, while the erythrocyte sedimentation rate in stage Ⅱ patients was higher than that in the other 3 groups (P<0.05). The levels of IL-18 and IL-1ß in stage Ⅲ of coal workers' pneumoconiosis were higher than those in the other 3 groups (P<0.05). Multiple logistic regression analysis showed that smoking age (OR=1.03, 95%CI: 1.00-1.06) and IL-1ß level (OR=4.61, 95%CI: 1.59-13.32) were independent risk factors for coal workers' pneumoconiosis (P<0.05). Compared with the control group, the expression levels of nucleotide-binding of oligomeric domain-like receptor protein 3 (NLRP3), Caspase-1, GSDMD, Caspase-4 and other proteins in stage Ⅲ of coal workers' pneumoconiosis were significantly increased (P<0.05) . Conclusion: Smoking age is a risk factor for coal workers' pneumoconiosis, IL-1ß may be a potential biomarker for the diagnosis of coal workers' pneumoconiosis, and pyroptosis may play a role in the development of peripheral inflammation of coal workers' pneumoconiosis.

[Analysis of clinical characteristics and causes of death in 38 patients with pneumoconiosis].

Objective: To analyze the clinical characteristics and causes of death of patients with pneumoconiosis, and to provide evidence for the prevention and management of pneumoconiosis. Methods: From June 2022 to July 2023, 38 dead patients with pneumoconiosis confirmed by Shandong Academy of Occupational Health and Occupational Medicine were selected as the research objects. The clinical data of patients were collected through hospital information system (HIS) and laboratory information management system (LIS) to analyze the basic situation of patients with pneumoconiosis who died, the distribution of industry types, the course of disease, the nature of work, the type of reimbursement, complications/comorbidities, and the direct causes of death. Univariate analysis of variance was used to compare the course of pneumoconiosis death in patients with different age of exposure to dust. Results: Among the 38 patients with pneumoconiosis, there were 37 males and 1 female. The age of exposure to dust was 5-37 (19.29±8.17) years, the duration of disease was 5-41 (20.26±8.53) years, and the age of death was 27-86 (70.42±12.26) years old. There were 10 cases of stage Ⅰ pneumoconiosis, 18 cases of stage Ⅱ, 10 cases of stage Ⅲ pneumoconiosis and 32 cases (84.21%) of silicosis. There were 30 (78.95%) people aged ≥65 years and 8 (21.05%) people aged <65 years. The industry was mainly metal products (18 workers, 47.37%), and the distribution of work was mainly excavation workers (11 workers, 28.95%). The death course of pneumoconiosis patients with 10-<30 years of exposure to dust accounted for 76.32% (29/38). The average course of pneumoconiosis patients with 20-<30 years of exposure to dust was the longest[ (24.00±9.39) years], and there was no statistically significant difference in the average course of disease among different age of exposure to dust groups (F=1.81, P=0.165). The working units of the deceased patients were private enterprises or factories, and the hospitalization expenses were borne by individuals for 21 people (55.26%). The working unit was a state-owned enterprise, and 17 people (44.74%) were reimbursed for hospitalization expenses and work-related injuries. The main comorbidities/complications of pneumoconiosis patients were respiratory infection in 18 cases (47.37%) and chronic pulmonary heart disease (47.37%). The top 3 direct causes of death were pneumoconiosis in 13 cases (34.21%), pulmonary infection in 10 cases (26.32%) and lung cancer in 7 cases (18.42%) . Conclusion: Most of 38 cases of pneumoconiosis patients death diseases such as multiple combination of respiratory system, cardiovascular system, respiratory system disease is a major cause of death in pneumoconiosis patients.

[Comparative study on CT image characteristics of pneumoconiosis large shadow and primary lung cancer mass].

Objective: To compare the CT image characteristics of pneumoconiosis large shadow and primary lung cancer mass, and analyze the value of CT image characteristics in the differential diagnosis of pneumoconiosis large shadow and primary lung cancer. Methods: In September 2022, 43 patients with stage Ⅲ pneumoconiosis who were hospitalized in Zibo Occupational Disease Prevention Hospital from January 2020 to June 2021 and 52 patients with primary lung cancer who were confirmed by pathology in the Affiliated Hospital of Jining Medical University during the same period were selected as the investigation objects, and the image characteristics of pneumoconiosis large shadow or lung cancer mass and surrounding tissues in the chest CT images of the two groups were compared. Univariate analysis, cluster analysis and cross analysis were used to screen out statistically significant indicators as independent variables, and pneumoconiosis and lung cancer as dependent variables for logistic regression analysis. Results: There were statistically significant differences between large shadow of pneumoconiosis and primary lung cancer mass in single factor CT imaging, such as irregular shape of lesions, CT attenuation value, calcification, cavitation, spiculation, liquefactive necrosis, satellite lesions, adjacent emphysema, short spicules, and pleural thickening (P<0.05). CT value ≥92 HU (abnormal CT attenuation value), calcification, peripheral satellite lesions, pleural thickening, parapunctal emphysema, spines on the lesion margin, irregular lesion morphology were typical features of stage Ⅲ pneumoconiosis, with multiple features of aggregation. The typical features of lung cancer were liquefaction necrosis, round or quasi-round appearance, cavitation and interlobar pleura. A logistic regression model was constructed using satellite lesions, spiculation, pleural thickening, and lesion abnormal CT attenuation value had an R(2) of 0.880 and an accuracy of 95.3% for differentiation. Conclusion: Abnormal CT attenuation value, calcification, peripheral satellite lesions, pleural thickening, spiculation at the edges, liquefaction necrosis, interlobar pleura involvement, and cavitation can distinguish the large shadow of stage Ⅲ pneumoconiosis from lung cancer mass.

Detection and Genomic Characterization of Torque Teno Virus in Pneumoconiosis Patients in China.

Pneumoconiosis is a common occupational disease that can worsen with accompanying infection. Torque teno virus (TTV) is a prevalent human virus with multiple genotypes that can chronically and persistently infect individuals. However, the prevalence of TTV in pneumoconiosis patients is still unclear. This research aims to detect the presence and prevalence of TTV in the alveolar lavage fluid of pneumoconiosis patients in the Hunan Province of China using PCR. As a result, a 65.5% positive rate (19 out of 29) of TTV was detected. The TTV detection rate varies among different stages of silicosis and different pneumoconiosis patient ages. Nine novel TTV genomes ranging in size from 3719 to 3908 nt, named TTV HNPP1, HNPP2, HNPP3, HNPP4, HNPP5, HNPP6-1, HNPP6-2, HNPP7-1 and HNPP7-2, were identified. A genomic comparison and phylogenetic analysis indicated that these nine TTVs represent five different species with high genetic diversity which belong to the genus Alphatorquevirus. HNPP6-1 and HNPP6-2 belong to TTV3, HNPP5 belongs to TTV13, HNPP1 belongs to TTV24, HNPP4 belongs to TTV20, and the others belong to TTV19. The genomes of TTV HNPP1, HNPP6-1, and HNPP6-2 contain three putative open reading frames (ORFs) coding for proteins, ORF1, ORF2, and ORF3, while the other six TTV genomes contain two ORFs coding for proteins, ORF1 and ORF2. These results provide the first description of TTV epidemiology in pneumoconiosis patients in China. The newly identified TTV genome sequences reveal the high genetic diversity of TTV in pneumoconiosis patients and could contribute to a deeper understanding of TTV retention and infection in humans.

AMFP-net: Adaptive multi-scale feature pyramid network for diagnosis of pneumoconiosis from chest X-ray images.

Early detection of pneumoconiosis by routine health screening of workers in the mining industry is critical for preventing the progression of this incurable disease. Automated pneumoconiosis classification in chest X-ray images is challenging due to the low contrast of opacities, inter-class similarity, intra-class variation and the existence of artifacts. Compared to traditional methods, convolutional neural networks have shown significant improvement in pneumoconiosis classification tasks, however, accurate classification remains challenging due to mainly the inability to focus on semantically meaningful lesion opacities. Most existing networks focus on high level abstract information and ignore low level detailed object information. Different from natural images where an object occupies large space, the classification of pneumoconiosis depends on the density of small opacities inside the lung. To address this issue, we propose a novel two-stage adaptive multi-scale feature pyramid network called AMFP-Net for the diagnosis of pneumoconiosis from chest X-rays. The proposed model consists of 1) an adaptive multi-scale context block to extract rich contextual and discriminative information and 2) a weighted feature fusion module to effectively combine low level detailed and high level global semantic information. This two-stage network first segments the lungs to focus more on relevant regions by excluding irrelevant parts of the image, and then utilises the segmented lungs to classify pneumoconiosis into different categories. Extensive experiments on public and private datasets demonstrate that the proposed approach can outperform state-of-the-art methods for both segmentation and classification.

Resting diffusing capacity and severity of radiographic disease predict gas exchange abnormalities with exercise in former US coal miners.

BACKGROUND: The US Department of Labor (DOL) does not fund diffusing capacity (DLCO) or metabolic measurements from cardiopulmonary exercise testing (CPET) for coal miners' disability evaluations. Although exercise arterial blood gas testing is covered, many miners are unable to perform maximal tests, and sampling at peak exercise can be challenging. We explored the relationship between resting DLCO, radiographic disease severity, and CPET abnormalities in former US coal miners. METHODS: We analyzed data from miners evaluated between 2005 and 2015. Multivariable linear and logistic regression analyses were used to examine relationships between percent predicted (pp) forced expiratory volume in 1 s (FEV1pp), DLCOpp, VO2maxpp, A-a oxygen gradient (A-a)pp, dead space fraction (Vd/Vt), disabling oxygen tension (PO2), and radiographic findings of pneumoconiosis. RESULTS: Data from 2015 male coal miners was analyzed. Mean tenure was 28 years (SD 8.6). Thirty-twopercent had an abnormal A-a gradient (>150 pp), 20% had elevated Vd/Vt (>0.33), and 34% a VO2max < 60 pp. DLCOpp strongly predicted a disabling PO2, with an odds ratio (OR) of 2.33 [2.09-2.60], compared to 1.18 [1.08-1.29] for FEV1. Each increase in subcategory of small opacity (simple) pneumoconiosis increased the odds of a disabling PO2 by 42% [1.29-1.57], controlling for age, body mass index, pack-years of tobacco smoke exposure, and years of coal mine employment. CONCLUSIONS: DLCO is the best resting pulmonary function test predictor of CPET abnormalities. Radiographic severity of pneumoconiosis was also associated with CPET abnormalities. These findings support funding DLCO testing for impairment and suggest the term "small opacity" should replace "simple" pneumoconiosis to reflect significant associations with impairment.