Search Results (126)

The long-term inhalation of free silica dust causes silicosis—a prevalent occupational hazard—yet its systemic effect on male reproductive toxicity remains underexplored. Tetrandrine (Tet) is the only plant-derived anti-silicosis drug approved in China. This study investigates silica (SiO₂) -induced male reproductive damage and evaluates Tet’s protective effects. Sixty male C57BL/6 mice (6–8 weeks) were divided into control, SiO₂ exposure, and SiO₂ + Tet groups. SiO₂ was administered via intranasal infusion and Tet via gavage. Mice were sacrificed at day 7 (male reproductive injury model corresponding to the pulmonary inflammation stage) and day 42 (male reproductive injury model corresponding to the pulmonary fibrosis stage). Analyses included sperm morphology, testicular transcriptome sequencing, RT-qPCR, and immunofluorescence. At day 7, SiO₂ exposure upregulated testicular inflammatory markers, which were partially mitigated by Tet. At day 42, SiO₂ increased sperm deformity and testicular fibrosis markers (fibronectin and vimentin); Tet intervention reduced these abnormalities. Transcriptome analysis revealed distinct gene expression patterns at day 7 versus day 42, indicating time-dependent injury mechanisms. Tetrandrine alleviates silica-induced reproductive damage in male mice, suggesting potential therapeutic applications for occupational silica exposure and expanding the understanding of silica toxicity beyond the respiratory system. Full article

Workers’ exposure to silica dust is a global occupational and public health concern and is particularly prevalent in Southern Africa, mainly because of inadequate dust control measures. It is worsened by the high prevalence of HIV/AIDS, which exacerbates tuberculosis and other occupational lung diseases. The prevalence of silicosis in the region ranges from 9 to 51%; however, silica dust exposure levels and controls, especially in the informal mining sector, particularly in artisanal small-scale mines (ASMs), leave much to be desired. This is important because silicosis is incurable and can only be eliminated by preventing worker exposure. Additionally, several studies have indicated inadequate occupational health and safety policies, weak inspection systems, inadequate monitoring and control technologies, and inadequate occupational health and hygiene skills. Furthermore, there is a near-absence of silica dust analysis laboratories in southern Africa, except in South Africa. This protocol aims to systematically evaluate the effectiveness of respirable dust and respirable crystalline silica dust exposure evaluation and control methodology for the mining industry. The study will entail testing the effectiveness of current dust control measures for controlling microscale particles using various exposure dose metrics, such as mass, number, and lung surface area concentrations. This will be achieved using a portable Fourier transform infrared spectroscope (FTIR) (Nanozen Industries Inc., Burnaby, BC, Canada), the Nanozen DustCount, which measures both the mass and particle size distribution. The surface area concentration will be analysed by inputting the particle size distribution (PSD) results into the Multiple-Path Particle Dosimetry Model (MPPD) to estimate the retained and cleared doses. The MPPD will help us understand the sub-micron dust deposition and the reduction rate using the controls. To the best of our knowledge, the proposed approach has never been used elsewhere or in our settings. The proposed approach will reduce dependence on highly skilled individuals, reduce the turnaround sampling and analysis time, and provide a reference for regional harmonised occupational exposure limit (OEL) guidelines as a guiding document on how to meet occupational health, safety and environment (OHSE) requirements in ASM settings. Therefore, the outcome of this study will influence policy reforms and protect hundreds of thousands of employees currently working without any form of exposure prevention or protection. Full article

Background/Objectives: Silicosis remains a major occupational health concern worldwide and is characterized by notable clinical heterogeneity in terms of disease progression and complications. However, the underlying metabolic mechanisms contributing to this heterogeneity remain poorly understood. Methods: We conducted a case–control study involving 156 silicosis patients and 132 silica-exposed controls. The plasma samples were analyzed via untargeted metabolomics based on liquid chromatography–mass spectrometry (LC-MS/MS). To explore disease subtypes and potential biomarkers, we applied non-negative matrix factorization (NMF) clustering, weighted gene co-expression network analysis (WGCNA), and machine learning approaches. Results: A total of 860 differentially abundant metabolites, including elevated pathogen-associated compounds, were identified in silicosis patients. Unsupervised NMF clustering revealed two distinct metabolic subtypes with different clinical features. Patients in the NMF2 subgroup had a 5.3-fold greater risk of pulmonary infections (p = 0.026) than those in the NMF1 subgroup. Metabolomic analysis revealed that NMF2 was enriched in arachidonic acid and unsaturated fatty acid metabolism pathways, with prominent LysoPC accumulation, suggesting inflammation-related lipid peroxidation. In contrast, NMF1 was characterized by increased spermidine biosynthesis and urea cycle activity, along with suppressed saturated fatty acid metabolism and reduced LysoPC processing, potentially affecting membrane integrity and promoting fibrosis. A machine learning-derived dual-metabolite panel, tyrosocholic acid and PI (20:4/0:0), achieved AUC values above 0.85 for both silicosis detection and subtype classification. Conclusions: These findings highlight metabolic heterogeneity in silicosis and suggest clinically relevant subtypes, providing a foundation for improved stratification, early detection, and targeted interventions. Full article

Silicosis is an irreversible and progressive pulmonary fibrotic disease caused by the long-term inhalation of silica dust. The precise molecular mechanisms underlying the disease remain incompletely understood, and effective early diagnostic biomarkers are still lacking. In this study, we used a silicosis mouse model and transcriptomic sequencing to identify 2950 mRNAs, 461 lncRNAs, 81 miRNAs, and 44 circRNAs that were differentially expressed in lung tissue. Enrichment analysis revealed that these differentially expressed genes were significantly enriched in the phosphatidylinositol 3-kinase (PI3K)–protein kinase B (Akt) signaling pathway, nuclear factor kappa-light-chain-enhancer of activated B cell (NF-κB) signaling pathway, and tumor necrosis factor (TNF) signaling pathway. The constructed competing endogenous RNA (ceRNA) network highlighted extensive regulatory interactions among lncRNAs/circRNAs, miRNAs, and mRNAs. Human validation showed that the expression levels of hsa-miR-215-5p and hsa-miR-146b-5p were significantly upregulated in the peripheral blood of early-stage pneumoconiosis patients, while hsa-miR-485-5p was downregulated. Logistic regression analysis revealed that hsa-miR-215-5p (OR = 1.966, 95% CI: 1.6938–2.2796, p < 0.001) and hsa-miR-146b-5p (OR = 1.9367, 95% CI: 1.697–2.201, p < 0.001) were independent risk factors for pneumoconiosis (p < 0.001). ROC curve analysis showed that both miRNAs demonstrated good diagnostic efficacy for pneumoconiosis, with AUC values of 0.9563 and 0.8876, respectively. These results provide novel insights into the complex ceRNA regulatory network involved in silicosis pathogenesis and suggest potential early, non-invasive diagnostic biomarkers. Full article

Granite wet edge finishing is widely adopted to improve surface durability and aesthetics while reducing dust dispersion compared to dry processes. However, even under flooded lubrication, fine particles (FP, 0.5–20 µm) and ultrafine particles (UFP, <100 nm) containing crystalline silica are emitted, posing health risks such as silicosis and pulmonary or cardiovascular diseases. This study investigates particle emissions during CNC edge finishing of black (containing 0% quartz) and white granites (containing 41% quartz) using two industrially relevant profile tools: Half-Beveled (HB) and Ogee (OG). A full factorial design evaluated the effects of granite type, tool geometry, abrasive grit size, spindle speed, and feed rate. Particle concentrations were measured with Aerodynamic and Scanning Mobility Particle Sizers. Results show that spindle speed (N) is the dominant factor, explaining up to 92% of variance in emissions, whereas feed rate (V_f) played a minor role. Tool geometry had a pronounced effect on UFP release: sharp-edged geometries (HB) promoted localized micro-fracturing and higher emissions, while curved geometries (OG) distributed stresses and reduced particle detachment. White granite generated higher mass emissions due to its high quartz content, while black granite exhibited more stable emission behavior. These findings highlight the dual necessity of optimizing cutting kinematics and selecting appropriate tool profiles to balance surface quality and occupational health in granite processing. Full article

Underground mining environments present elevated occupational health risks, primarily due to substantial exposure to diesel exhaust emissions within confined and poorly ventilated spaces. This study assesses the real-world performance of two advanced retrofit emission control systems—Proventia NOxBuster and Purifilter—installed on underground mining trucks operating in a Spanish mine. Emissions of carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO₂) were quantified using a Testo 350 multigas analyser, while ultrafine particle (UFP) concentrations were measured with an Engine Exhaust Particle Sizer (EEPS-3090) equipped with a thermodiluter. Controlled tests under both idling and acceleration conditions revealed substantial reductions in pollutant emissions: CO decreased by 60–98%, NO by 51–92%, and NO₂ by 20–87%, depending on the system and operational phase. UFP concentrations during idling dropped by approximately 90%, from 542,000 particles/cm³ in untreated trucks to below 50,000 particles/cm³ in retrofitted vehicles. Under acceleration, the Proventia NOxBuster achieved reductions exceeding 95%. Conversely, Purifilter-equipped trucks exhibited a counterintuitive increase in UFPs within the 5.6–40 nm range, potentially due to ammonia slip events during selective catalytic reduction (SCR). Despite these discrepancies, both systems demonstrated considerable mitigation potential, albeit highly dependent on exhaust temperature (optimal: 200–450 °C), urea dosing precision, and maintenance protocols. This work underscores the necessity of in situ performance verification, regulatory vigilance, and targeted intervention strategies to protect underground workers effectively. Further investigation is warranted into the long-term health benefits, system durability, and nanoparticle emission dynamics under variable load conditions. Full article

Sarcoidosis is a chronic, idiopathic, multisystemic inflammatory disease characterized by non-caseating granulomas, most commonly affecting the lungs and mediastinal lymph nodes. Radiological imaging plays a fundamental role in the diagnosis, assessment of disease extent, and differentiation from other pulmonary conditions. This narrative review offers a comprehensive overview of the imaging features of pulmonary sarcoidosis, focusing on both typical patterns—such as bilateral hilar lymphadenopathy, perilymphatic nodules, and upper lobe-predominant infiltrates—and atypical manifestations—including alveolar opacities, miliary nodules, fibrocystic changes, and lower lobe involvement. Emphasis is placed on the utility of high-resolution computed tomography (HRCT) in detecting early parenchymal changes and complications such as fibrosis, bronchiectasis, and pulmonary hypertension. Differential diagnosis, including tuberculosis, silicosis, metastatic disease, organizing pneumonia, and hypersensitivity pneumonitis, are discussed to aid interpretation. Recognizing the spectrum of radiological presentations is essential for distinguishing sarcoidosis from other interstitial and granulomatous lung diseases. Radiologists play a pivotal role in the multidisciplinary diagnostic process, contributing to timely diagnosis, risk stratification, and optimized patient management. Full article

Diesel-powered machinery is the primary energy source in underground mining, exposing workers to hazardous diesel exhaust emissions. This study evaluates occupational exposure to diesel particulate matter (DPM) and gaseous pollutants (NO, NO₂) at an underground mine before and after implementing Diesel Particulate Filters (DPF) and Selective Catalytic Reduction (SCR) in mining equipment. A comprehensive monitoring campaign was conducted, employing elemental carbon (EC) as a tracer for diesel particulate emissions and electrochemical sensors for gas measurements. Results show a substantial reduction in EC concentrations following the implementation of DPFs, with median EC exposure decreasing from 0.145 mg/m³ in 2021 to 0.034 mg/m³ in 2023, and the proportion of samples exceeding the occupational exposure limit (OEL) falling from 90% to 28%. Similarly, SCR implementation led to a 72% reduction in NO₂ levels and a 77.5% decrease in NO concentrations in certain equipment; however, NO levels remained persistently high near loaders, suggesting that additional mitigation measures are required. These findings underscore the efficacy of DPF and SCR technologies in improving air quality and reducing occupational exposure in underground mining environments. Nevertheless, persistent NO concentrations and maintenance-related challenges highlight the need for a holistic emission control approach, integrating ventilation improvements, expanded DPF adoption, alternative propulsion systems, and enhanced maintenance protocols. This study provides critical insights into the effectiveness of advanced emission reduction strategies and informs future regulatory compliance efforts in the mining industry. Full article

Background/Objectives: Silicosis, a fibrotic lung disease, is re-emerging globally, driven by an aggressive form linked to engineered stone processing that rapidly progresses to progressive massive fibrosis (PMF). The standard diagnostic approach, chest X-ray (CXR), is subject to considerable inter-observer variability, making the distinction between simple silicosis (SS) and PMF particularly challenging. The purpose of this study was to develop and validate an automated multimodal framework for silicosis staging by integrating artificial intelligence (AI), CXR images, and routine blood biomarkers. Methods: We developed three fusion architectures, early, late, and hybrid, connecting blood biomarker analysis with CXR analysis. Deep learning and conventional (shallow) machine learning models were combined. The models were trained and validated on a cohort of 94 patients with engineered stone silicosis, providing 341 paired CXR and biomarker samples. A patient-aware 5-fold cross-validation was used to ensure the model’s generalizability and prevent patient data leakage between folds. Results: The hybrid and late fusion models achieved the best performance for disease staging, yielding an area under the receiver operating characteristic (ROC) curve (AUC) of 0.85. This multimodal approach outperformed both the unimodal CXR-based model (AUC = 0.83) and the biomarker-based model (AUC = 0.70). Conclusions: This study reveals that AI-based techniques that utilize a multimodal fusion approach have the potential to outperform single-modality methods have the potential to serve as an objective decision support tool for clinicians, leading to more consistent staging and improved patient management. Full article

Background: Silicosis is a lung disease caused by inhalation of crystalline silica dust, leading to lung fibrosis, respiratory symptoms, and impaired lung function. This study aimed to determine the prevalence of silicosis, asthma, and chronic obstructive pulmonary disease (COPD), and to identify factors associated with abnormal pulmonary function among residents living in dust-exposed areas in Thailand. Methods: A cross-sectional study was conducted from March 2024 to July 2024 among adults aged 18 years or older in Saraburi, Thailand. Data collected included demographics, comorbidities, respiratory symptoms, risk of silicosis, chest radiographs, and spirometry (forced vital capacity (FVC), forced expiratory volume in one second (FEV₁), and bronchodilator responsiveness (BDR)). Silicosis was confirmed based on a history of significant silica exposure and characteristic chest radiographic findings. Results: Among 290 participants (55.9% female, mean age 47.6 ± 16.4 years), the prevalence of silicosis, asthma, and COPD was 0.3%, 4.5%, and 10.3%, respectively. Abnormal chest radiographs were observed in 8.3%, and abnormal lung function in 34.1%, including restrictive lung patterns (16.6%), airway obstruction (9.0%), mixed defects (2.8%), and small-airway disease (5.9%). BDR was observed in 4.8%. Logistic regression identified increasing age as a significant predictor of abnormal lung function. Conclusions: Silicosis prevalence was lower than that of asthma and COPD, but abnormal pulmonary function—especially restrictive defects—was common. Notably, the prevalence of asthma and COPD was higher than previously reported community-based diagnosis rates, suggesting potential underdiagnosis. Older age was associated with a higher likelihood abnormal lung function. These findings highlight the need for targeted surveillance, preventive measures, and public health interventions to mitigate the respiratory impacts of dust exposure in community settings Full article

The link between occupational exposure to Respirable Crystalline Silica (RCS) and silicosis, a potentially fatal respiratory disease, has been well-established, leading to global reductions in RCS Exposure Standards (ES). In Western Australia (WA), RCS data have been collected by the Department of Energy, Mining, Industry Regulation and Safety (DEMIRS) from 1986 to 2024 (n = 144,141). These results were analysed to assess the impacts of recent changes to the ES on compliance. Findings suggest that the WA mining sector, regardless of commodity type, is compliant with RCS exposures as assessed against the 0.05 mg/m³ ES (2019). Laboratory technicians, exploratory drilling, miscellaneous trades/utilities, trades assistant, sample preparation, and sampler/sample operator are SEGS that had the highest RCS exposures. Exposure assessment did not account for the protection provided by respiratory protective equipment (RPE). In the WA mining sector, a robust respiratory protection regime is enforced that includes respirator fit testing, and this is most likely the case throughout Australia. On the balance of epidemiological evidence, industry compliance over decades, reducing exposure profiles, and robust RPE programmes, it could be argued that further reductions to the RCS exposure standard are not justified. Regulators need to consider the protection provided by respirators in exposure assessment. Full article

Background/Objectives: Silicosis caused by dust from engineered stone (ES) exposure is an emerging occupational lung disease that severely impacts respiratory health. This study aimed to analyze the association between cytokine profiles and disease severity and progression in patients with engineered stone silicosis (ESS) to assess their potential as biomarkers of progression and their usefulness to stratify risk. Methods: A longitudinal study was conducted with a seven-year follow-up (2017-2024) on 72 workers with simple silicosis (SS) or progressive massive fibrosis (PMF), all with a history of cutting, polishing, and finishing ES countertops. Data on lung function and levels of 27 cytokines were collected at four control points. Machine learning (ML) models were built to classify the disease stage and predict its progression. Results: 39% of patients with SS progressed to PMF. Significant differences in the expression of some cytokines were observed between ESS stages, suggesting a role in the evolution of the inflammatory process. Specifically, higher levels of IL-1RA, IL-8, IL-9, and IFN-$\gamma$ were found at checkpoint 1 in patients with PMF compared to SS. The longitudinal analysis revealed a significant relationship between IL-1RA and MCP-1$\alpha$ and disease duration with MCP-1$\alpha$ also being associated with time and disease grade. Machine learning (ML) models were built using the cytokines selected through a sequential backward feature selection. The Support Vector Machine model achieved an accuracy of 83% in classifying disease stage (SS, PMF), and of 77% in predicting the disease progression. Conclusions: The findings suggest that cytokines can be used as dynamic biomarkers to reflect underlying inflammatory processes and monitor disease evolution. The performance of ML algorithms to predict diagnostic status based on cytokine profiles highlights their clinical value in supporting early diagnosis, monitoring disease progression, and guiding clinical decisions. Full article

Respirable crystalline silica is a well-established occupational hazard in construction work. Despite increased awareness, consistent exposure control remains a challenge, particularly in dynamic and resource-constrained environments. Respirable crystalline silica exposure in construction environments challenges the achievement of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being) and SDG 8 (Decent Work and Economic Growth). Respirable crystalline silica particles cause severe health complications, including silicosis, lung cancer, cardiovascular diseases, and autoimmune disorders, representing a significant barrier to achieving SDG 3.9’s target of reducing deaths and illnesses from hazardous chemical exposures by 2030. This systematic review evaluates two decades of advancements (2004–2024) in respirable crystalline silica identification, characterisation, and mitigation within construction, synthesising evidence from 143 studies to assess progress toward sustainable occupational health management. This review documents a paradigmatic shift from traditional exposure assessment toward sophisticated monitoring approaches incorporating real-time detection systems, virtual reality–Computational Fluid Dynamics simulations, and wearable sensor technologies. Engineering controls, including local exhaust ventilation, wet suppression methods, and modified tool designs, have achieved exposure reductions exceeding 90%, directly supporting SDG 8.8’s commitment to safe working environments for all workers, including migrants and those in precarious employment. However, substantial barriers persist, including prohibitive costs, inadequate infrastructure, and regional regulatory disparities that particularly disadvantage lower-resourced countries, contradicting the Sustainable Development Goals’ principles of leaving no one behind. The findings advocate holistic approaches integrating technological innovation with context-specific regulations, enhanced international cooperation, and culturally adapted worker education to achieve equitable occupational health protection supporting multiple Sustainable Development Goals’ objectives by 2030 and also highlighting potential areas for future research. Full article

Background: Occupational bronchopulmonary diseases (OBPDs)—including pneumoconiosis, silicosis, and occupational COPD—remain a pressing public health issue, especially in regions with intensive mining, metallurgy, and construction industries. Caused by chronic inhalation of fibrogenic dusts, these conditions are often diagnosed at late stages, resulting in irreversible lung damage and diminished work capacity. Methods: A scoping review was performed using the Arksey and O’Malley framework, with methodological refinements from the Joanna Briggs Institute. Following PRISMA-ScR guidelines, we searched PubMed, Scopus, and gray literature for publications from 2014 to 2024. After screening 1761 records and full-text review, nine studies were included in the final synthesis, comprising two systematic reviews, two narrative literature reviews, and five observational studies. Results: Key risk factors identified included prolonged exposure to silica and coal dust, tobacco use, and genetic susceptibility. Diagnostic delays were attributed to the underuse of high-resolution CT and exhaled nitric oxide analysis. Several studies highlighted the diagnostic value of oxidative stress and inflammatory markers (e.g., IL-6, TNF-α). Nutritional rehabilitation and polyphenol-enriched herbal therapies were associated with improved respiratory function and quality of life. However, these strategies remain underutilized, particularly in low-resource settings. Conclusions: A coordinated, biomarker-driven approach integrating early diagnosis, dust exposure control, and tailored rehabilitation is urgently needed. Multidisciplinary models may reduce the clinical and socioeconomic burden of OBPDs. Full article

The identification of a type I interferon-induced transcriptomic signature in active tuberculosis suggests a potential role for these interferons in the pathogenesis of tuberculosis. Comorbidities such as human immunodeficiency virus, diabetes, systemic lupus erythematosus, end-stage renal disease, and coronavirus disease are epidemiologically linked to an increased risk for reactivation of latent tuberculosis infection. Notably, type I interferons are also implicated in the pathogenesis of these conditions, with a recognizable type I interferon transcriptomic signature. The mechanisms by which type I interferons in tuberculosis-risk-associated comorbidities may drive the progression of tuberculosis or maintenance of latent infection however remain largely unknown. This review summarizes the existing literature on the increased association between type I interferons, focusing on interferon-α and -β, and the heightened risk of tuberculosis reactivation. It also underscores the similarities in the immunopathogenesis of these comorbidities. A better understanding of these mechanisms is essential to guide the development of host-directed interferon therapies and improving diagnostic biomarkers in M. tuberculosis infection. Full article