Occupational pneumoconiosis (referred to as “pneumoconiosis”) caused by exposure to occupational dust is the most serious occupational disease in China. Biological monitoring on occupational populations exposed to dust is important for the prevention, diagnosis, and treatment of pneumoconiosis. Biological monitoring is a systematic engineering process that includes a series of processes such as biological samples selection, selection of biological monitoring indicators, and selection of detection methods. The biological samples for biological monitoring mainly include urine, blood, exhaled breath gas, bronchoalveolar lavage fluid, saliva, sputum, and more. The indicators of biological monitoring involve multiple pathways such as oxidative stress, inflammatory response, collagen synthesis/degradation, phagocytic cell apoptosis, and pathways related to the formation of pneumoconiosis. Suitable detection methods need to be determined upon different biological monitoring indicators, including enzyme-linked immunosorbent assay, high-performance liquid chromatography, high-performance liquid chromatography-tandem mass spectrometry, inductively coupled plasma mass spectrometry, etc. Currently, there is a lack of true clinically valuable biological monitoring indicators that can indicate the correlation between dust exposure and the hazards of occupational populations, and there are no systematic and complete biological monitoring methods reported. It is necessary to further standardize the biological monitoring process and search for specific biological monitoring indicators.

Objective: To develop a rapid detection method for 21 elements in urine with inductively coupled plasma mass spectrometry (ICP-MS) . Methods: The urine samples were directly diluted 20 times by 1% HNO₃, and detected by ICP-MS, Indium, Yttrium, and Lutecium were used as on-line internal standard. Fe was analyzed by Dynamic Reaction Cell (DRC) mode, As, Cr, V and Zn were analyzed by collision cell technology (CCT) mode, and Be, Mn, Ni, Cd, Sn, Bi, Pb, Re, Sb, W, Li, Cu, Se, Sr, Mo were analyzed by standard mode. Dynamic band-pass tuning (DBT) was used to eliminate interference for Fe. Results: All the elements have good linearity in their determination range, with the correlation coefficient r>0.999 5. The limits of detection of the 21 elements were in the range of 0.017-11.14 μg/L. The inter-precision (relative standard deviation, RSD) was less than 9.96%, and the intra-precision was less than 13.90% (except As RSD<18.91%) . The spike recovery of all elements fell within 81.1%-116.4%. Conclusion The method was proved to be simple, fast, and accurate, and met the needs of testing requirements of large amounts of specimens.

Silicosis is a common occupational disease, and its main characteristic pathological features are the formation of silicon nodules and diffuse pulmonary fibrosis. In the process of silicosis fibrosis, macrophages can be polarized into M1 macrophages and M2 macrophages. M1 macrophages play a pro-inflammatory role in the early stage of silicosis and release a variety of inflammatory factors, which is the core of inflammatory response. M2 macrophages promote inflammation resolution and tissue repair in silicosis fibrosis stage by secreting anti-inflammatory cytokines and pro-fibrotic mediators. M1/M2 polarization balance plays an important role in the occurrence and development of silicosis, and the regulation of macrophage polarization direction may play a positive role in the prevention and treatment of silicosis fibrosis. In this review, the role of macrophage polarization in silicosis fibrosis, the related signaling pathways regulating macrophage polarization in silicosis fibrosis, and the potential therapeutic targets based on macrophage polarization in silicosis fibrosis are reviewed, with a view to further strengthening the understanding of the mechanism of macrophage polarization in the pathogenesis and treatment of silicosis fibrosis.

Silicosis is a common occupational disease, and its main characteristic pathological features are the formation of silicon nodules and diffuse pulmonary fibrosis. In the process of silicosis fibrosis, macrophages can be polarized into M1 macrophages and M2 macrophages. M1 macrophages play a pro-inflammatory role in the early stage of silicosis and release a variety of inflammatory factors, which is the core of inflammatory response. M2 macrophages promote inflammation resolution and tissue repair in silicosis fibrosis stage by secreting anti-inflammatory cytokines and pro-fibrotic mediators. M1/M2 polarization balance plays an important role in the occurrence and development of silicosis, and the regulation of macrophage polarization direction may play a positive role in the prevention and treatment of silicosis fibrosis. In this review, the role of macrophage polarization in silicosis fibrosis, the related signaling pathways regulating macrophage polarization in silicosis fibrosis, and the potential therapeutic targets based on macrophage polarization in silicosis fibrosis are reviewed, with a view to further strengthening the understanding of the mechanism of macrophage polarization in the pathogenesis and treatment of silicosis fibrosis.

Objective:To explore the non-target metabonomics of serum in worker's pneumoconiosis (CWP) patients with latent tuberculosis and the biomarkers of latent tuberculosis infection of pneumoconiosis.Methods:In December 2018, 39 CWP inpatients from a hospital in Beijing were taken as subjects. The subjects were screened for latent tuberculosis using the in vitro release test of mycobacterium tuberculosis-interferon (IGRAs) test. According to the screening results, 21 positive patients with latent tuberculosis infection were selected as the latent tuberculosis group of pneumoconiosis. While 18 negative patients with CWP alone were selected as the pneumoconiosis group. Polarity components of metabolites were analyzed by UPLC-QTOF/MS. The data was processed with Progenesis QI software for multidimensional statistical analysis. Identification of structure of differential metabolites were matched through accurate mass and secondary mass spectrum. Searching the Human Metabolome Database (HMDB) , differential metabolites were imported into MetaboAnalyst 4.0 to analyze the metabolic pathways.Results:All 42 differential metabolites were screened out. Excepted for exogenous metabolites, 14 endogenous differential metabolites were identified. Compared with the pneumoconiosis group, 6 metabolites including PC [18∶4 (6Z, 9Z, 12Z, 15Z) /P-18∶1 (11Z) ], 3-Oxododecanoyl-CoA in the latent tuberculosis group were up-regulated, while 8 metabolites including the Stearoyl-CoA, (2S) -Pristanoyl-CoA were down-regulated. These results might be related to lipid, fatty acid and arachidonic acid metabolism pathways.Conclusion:There are significant differences in serum metabonomics between the patients with latent tuberculosis of pneumoconiosis and the patients with ordinary pneumoconiosis, which provide a reference for the study of biomarkers for the diagnosis of latent tuberculosis infection of pneumoconiosis.

Objective:To explore the non-target metabonomics of serum in worker's pneumoconiosis (CWP) patients with latent tuberculosis and the biomarkers of latent tuberculosis infection of pneumoconiosis.Methods:In December 2018, 39 CWP inpatients from a hospital in Beijing were taken as subjects. The subjects were screened for latent tuberculosis using the in vitro release test of mycobacterium tuberculosis-interferon (IGRAs) test. According to the screening results, 21 positive patients with latent tuberculosis infection were selected as the latent tuberculosis group of pneumoconiosis. While 18 negative patients with CWP alone were selected as the pneumoconiosis group. Polarity components of metabolites were analyzed by UPLC-QTOF/MS. The data was processed with Progenesis QI software for multidimensional statistical analysis. Identification of structure of differential metabolites were matched through accurate mass and secondary mass spectrum. Searching the Human Metabolome Database (HMDB) , differential metabolites were imported into MetaboAnalyst 4.0 to analyze the metabolic pathways.Results:All 42 differential metabolites were screened out. Excepted for exogenous metabolites, 14 endogenous differential metabolites were identified. Compared with the pneumoconiosis group, 6 metabolites including PC [18∶4 (6Z, 9Z, 12Z, 15Z) /P-18∶1 (11Z) ], 3-Oxododecanoyl-CoA in the latent tuberculosis group were up-regulated, while 8 metabolites including the Stearoyl-CoA, (2S) -Pristanoyl-CoA were down-regulated. These results might be related to lipid, fatty acid and arachidonic acid metabolism pathways.Conclusion:There are significant differences in serum metabonomics between the patients with latent tuberculosis of pneumoconiosis and the patients with ordinary pneumoconiosis, which provide a reference for the study of biomarkers for the diagnosis of latent tuberculosis infection of pneumoconiosis.

Background China is the world's largest producer and consumer of cobalt. Skin exposure to excess cobalt can cause symptoms such as contact dermatitis. At present, there are few studies on skin contact of cobalt and its compounds. Objective To investigate the skin contact characteristics of cobalt and its compounds. Methods A cross-sectional study was conducted in February 2024 involving 70 workers from a hard metal tool manufacturing company and the workers were divided into four groups according to their job positions: powder mixing, sintering, automatic pressing, and grinding processing. General demographic information was collected through questionnaires. Workplace air samples were collected using personal samplers, and cobalt concentrations in workplace air were measured by inductively coupled plasma optical emission spectrometry (ICP-OES). Skin samples were collected from the workers' foreheads using cotton swabs, and urine samples were collected within 30 min after the end of their shift. Urine specific gravity was measured immediately after collection, and disqualified samples were discarded. Cobalt concentrations in the swab extracts and urine were determined by inductively coupled plasma mass spectrometry (ICP-MS). Statistical analysis was performed using Kruskal-Wallis test for multiple group comparisons, Mann-WhitneyU test for pairwise comparisons, Chi-square test for categorical variables, and Spearman's rank correlation analysis to examine the correlations among air, dermal, and urinary cobalt levels. Results The 8 h time-weighted average (TWA) cobalt concentration was (2.30±2.15) μg·m⁻³ (\begin{document}$ \bar{x}\pm s $\end{document}). The median skin exposure level was 53.8 ng·cm⁻², with a range of 4.25 ng·cm⁻² to 1090.2 ng·cm⁻². The median urinary cobalt level was 3.74 µg·L⁻¹, with a range of 0.83 to 382.9 µg·L⁻¹. Statistically significant differences in TWA cobalt concentration, skin exposure levels, and urinary cobalt levels were found between different work positions (H=9.012, P=0.029; H=16.348, P＜0.001; H=11.078, P=0.011). A positive correlation was observed between skin exposure levels and urinary cobalt levels (r=0.537, P＜0.01). Conclusion Skin contact may be one of the main sources of cobalt levels in urine. Therefore, it is essential for workers to improve skin protection and hygiene practices.

Background Volatile organic compounds (VOCs) in exhaled breath are closely associated with respiratory diseases and are linked to various metabolic reactions in the human body. A quantitative analytical method can provide technical support for studying VOCs related to various diseases. Objective To establish a thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) method for the determination of 27 VOCs in exhaled breath. Methods VOCs in exhaled breath were collected using a Bio-VOC sampler and enriched with Tenax TA thermal desorption tubes before TD-GC-MS analysis. Standards were collected using thermal desorption tubes and optimized for thermal desorption conditions as well as chromatographic and mass spectrometric conditions: The separation of the 27 VOCs was achieved by an optimized temperature program, the improvement of sensitivity by optimizing quantitative ions, and the increase of VOCs desorption efficiency by optimizing thermal desorption time and temperature. Limit of detection, limit of quantification, accuracy, precision, and stability of the proposed method were investigated by spiking with a blank gas bag, and exhaled breath samples from 20 healthy individuals were collected for an application study of the proposed method. Results The thermal desorption temperature was 280 ℃, and desorption time was 6 min. A VF-624ms chromatographic column was selected for the separation of target substances. The initial temperature of heating program was 35 ℃, maintained for 1 min, and then increased to 100 ℃ at a heating rate of 3 ℃·min⁻¹ for 1 min, followed by increasing to 210 ℃ at a heating rate of 28 ℃·min⁻¹ for 5 min. A quantitative analysis was conducted with a single ion monitoring (SIM) mode. Under these conditions, the 27 VOCs showed good linear relationships in their respective concentration ranges and the correlation coefficients were higher than 0.9990. The limits of detection of the method were in the range of 0.01-0.13 nmol·mol⁻¹, the limits of quantification were in the range of 0.02-0.44 nmol·mol⁻¹, and the spiked recoveries were in the range of 80.1%-120.5%, with intra-batch and inter-batch precision ≤ 18.8% and 17.9% respectively. All substances can be stored at room temperature (23-28 °C) for 7 d and at 4 °C for 14 d. The proposed method was applied to exhaled breath samples from 20 subjects with detection rates≥ 80% (except for trans-2-pentene and decane) and a concentration range of 0.00-465.50 nmol·mol⁻¹. Conclusion The established TD-GC-MS method for quantification of VOCs in exhaled breath is characterized by high sensitivity and good accuracy, and is suitable for quantitative determination of VOCs in exhaled breath, which can provide technical support for the study of exhaled breath VOCs.

Background Coal workers' pneumoconiosis is a serious occupational disease in China. Exhaled volatile organic compounds (VOCs) can serve as the "breath fingerprint" of internal pathological processes, which provides a theoretical basis for exhaled VOCs to be used as potential non-invasive biomarkers for early diagnosis of coal workers' pneumoconiosis. Objective To screen out the characteristic VOCs and important characteristic VOCs of exhaled air in patients with coal workers' pneumoconiosis, and to explore the potential of these VOCs as biomarkers for early non-invasive diagnosis of the disease. Methods In this study, 27 VOCs in the exhaled breath of 22 patients with stage I coal workers' pneumoconiosis, 77 workers exposed to dust, and 92 healthy controls were quantitatively detected by thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Substances with P<0.05 in univariate analysis and variable importance projection (VIP) >1 in supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model were selected as the characteristic VOCs for early diagnosis of coal workers' pneumoconiosis. Age was included in the LASSO regression model as a covariate to screen out important characteristic VOCs, and the diagnostic performance was evaluated by receiver operating characteristic (ROC) curve. Spearman correlation was further used to explore the correlation between important characteristic VOCs and clinical lung function indicators. Results Through univariate analysis and OPLS-DA modeling, 8 VOCs were selected, including 2-methylpentane, 3-methylpentane, n-hexane, methylcyclopentane, n-heptane, methylcyclohexane, 4-methyl-2-pentanone, and 2-hexanone, in exhaled breath of patients with coal workers' pneumoconiosis. The concentrations of 4 VOCs, including 3-methylpentane, n-hexane, 4-methyl-2-pentanone, and 2-hexanone, showed a decreasing trend with the increase of dust exposure years. By LASSO regression, the important characteristic VOCs of the coal workers' pneumoconiosis group and the dust exposure group were n-hexane, methylcyclohexane and 4-methyl-2-pentanone, and the important characteristic VOCs of the coal workers' pneumoconiosis group and the healthy group were 2-methyl-pentane and 4-methyl-2-pentanone. The ROC analysis showed that the area under the curve (AUC) of n-hexane, methylcyclohexane, and 4-methyl-2-pentanone were 0.969, 0.909, and 0.956, respectively, and the AUC of combined diagnosis was 0.988 and its Youden index was 0.961, suggesting that these results can serve as a valuable reference for further research on early diagnosis. The Correlation analysis found that there was a positive correlation between n-hexane and lung function indicators in the important characteristic VOCs, indicating that it could indirectly reflect the obstruction of lung function ventilation, further proving that important characteristic VOCs have the potential to monitor lung function decline. Conclusion Three important characteristic VOCs selected in this study have the potential to be used as non-invasive biomarkers for early diagnosis and disease monitoring of coal workers' pneumoconiosis, and are worthy of further study and verification.

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal hematopoietic stem cell disease caused by abnormal expression of glycosylphosphatidylinositol (GPI) on the cell membrane due to mutations in the phosphatidylinositol glycan class A(PIGA) gene. It is commonly characterized by intravascular hemolysis, repeated thrombosis, and bone marrow failure, as well as multiple systemic involvement symptoms such as renal dysfunction, pulmonary hypertension, swallowing difficulties, chest pain, abdominal pain, and erectile dysfunction. Due to the rarity of PNH and its strong heterogeneity in clinical manifestations, multidisciplinary collaboration is often required for diagnosis and treatment. Peking Union Medical College Hospital, relying on the rare disease diagnosis and treatment platform, has invited multidisciplinary clinical experts to form a unified opinion on the diagnosis and treatment of PNH, and formulated the Expert Consensus of Multidisciplinary Diagnosis and Treatment for Paroxysmal Nocturnal Hemoglobinuria (2024), with the hope of promoting the standardization of PNH diagnosis and treatment.