Occupational exposure to crystalline silica and peripheral biomarkers: An update

Respirable dust and crystalline silica exposure among rice mill workers of northeast India

Crystalline silica is a Group I lung carcinogen primarily known as a causative agent for silicosis. A study was performed to quantify respirable dust, and respirable crystalline silica (RCS) in the rice mills of northeast India. Seventy-two respirable dust samples were collected from the worker's breathing zone from four rice mills at three locations: feeding, sieving, and polishing sections for two paddy varieties: Ranjit and Sali. The National Institute of Occupational Safety and Health (NIOSH), method #7602, was used to determine RCS. The results show that geometric mean TWA dust and RCS emissions in the rice mills varied from 3.97 to 455.00 mg/m3 and 0.02 to 5.38 mg/m3, respectively. RCS exposures were higher during milling of the Sali variety paddy (GM: 0.76 mg/m3) than the Ranjit variety paddy (GM: 0.25 mg/m3). Respirable dust and RCS emissions were considerably higher in the feeding and sieving sections than in the polishing section. Respirable dust and RCS exposure varied significantly (p < 0.001) with paddy variety. Respirable dust and RCS were highly correlated for different rice mills; however, the proportion of RCS in the dust was higher in the Sali variety paddy than in the Ranjit variety paddy. RCS exposure to the workers at the feeding and sieving sections was observed to be higher than the occupational exposure limits (OELs) published by Safe Work Australia, American Conference of Governmental Industrial Hygienists (ACGIH), National Institute for Occupational Safety and Health (NIOSH), Health and Safety Executive (HSE), and Factories Amendment Act, 1987, Government of India.

A study of inflammatory biomarkers in crystalline silica exposed rock drillers

BACKGROUND

Crystalline silica (CS) exposure can cause serious lung disease in humans, but mechanisms of pulmonary toxicity have not been completely elucidated.

AIMS

To assess pro-inflammatory and anti-inflammatory biomarkers and biomarkers related to the development of chronic obstructive pulmonary disease and fibrosis in serum of rock drillers exposed to CS.

METHODS

Rock drillers (N = 123) exposed to CS and non-specified particulate matter (PM) were compared to 48 referents without current or past exposure to PM in a cross-sectional study.

RESULTS

The rock drillers had been exposed to CS for 10.7 years on average. Geometric mean (GM) current exposure was estimated to 36 µg/m3. Their GM concentration of matrix metalloproteinase 12 (MMP-12) was significantly higher (16 vs. 13 ng/L; p = 0.04), while interleukin (IL) 6 and IL-8 were significantly lower compared to the referents. Also pentraxin 3 was significantly lower (3558 vs. 4592 ng/L; p = 0.01) in the rock drillers. A dose-response relationship was observed between cumulative exposure to CS and MMP-12, the highest exposed subgroup having significantly higher MMP-12 concentrations than the referents.

CONCLUSION

Exposure to CS may increase circulating MMP-12 concentrations in a dose-response related fashion. The results may also suggest a down-regulation of pro-inflammatory pathways.

The value of single biomarkers in the diagnosis of silicosis: A meta-analysis

This study aims to establish a scientific foundation for early detection and diagnosis of silicosis by conducting meta-analysis on the role of single biomarkers in independent diagnosis. The combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score, and diagnostic odds ratio (DOR) were 0.84 (95% confidence interval (CI): 0.77-0.90), 0.83 (95% CI: 0.78-0.88), 5.08 (95% CI: 3.92-6.59), 0.19 (95% CI: 0.13-0.27), 3.31 (95% CI: 2.88-3.74) and 27.29 (95% CI: 17.77-41.91), respectively. The area under the curve (AUC) was 0.90 (95% CI: 0.88-0.93). The Fagan plot shows a positive posterior probability of 82% and a negative posterior probability of 15%. This study establishes an academic basis for the swift identification, mitigation, and control of silicosis through scientific approaches. The assessed biomarkers offer precision and dependability in silicosis diagnosis, opening novel paths for early detection and intervention, thereby mitigating the disease burden associated with silicosis.

Screening of Serum Biomarkers of Coal Workers' Pneumoconiosis by Metabolomics Combined with Machine Learning Strategy

Pneumoconiosis remains one of the most serious global occupational diseases. However, effective treatments are lacking, and early detection is crucial for disease prevention. This study aimed to explore serum biomarkers of occupational coal workers’ pneumoconiosis (CWP) by high-throughput metabolomics, combining with machine learning strategy for precision screening. A case–control study was conducted in Beijing, China, involving 150 pneumoconiosis patients with different stages and 120 healthy controls. Metabolomics found a total of 68 differential metabolites between the CWP group and the control group. Then, potential biomarkers of CWP were screened from these differential metabolites by three machine learning methods. The four most important differential metabolites were identified as benzamide, terazosin, propylparaben and N-methyl-2-pyrrolidone. However, after adjusting for the influence of confounding factors, including age, smoking, drinking and chronic diseases, only one metabolite, propylparaben, was significantly correlated with CWP. The more severe CWP was, the higher the content of propylparaben in serum. Moreover, the receiver operating characteristic curve (ROC) of propylparaben showed good sensitivity and specificity as a biomarker of CWP. Therefore, it was demonstrated that the serum metabolite profiles in CWP patients changed significantly and that the serum metabolites represented by propylparaben were good biomarkers of CWP.