Objectives. Pneumoconiosis is a concerning occupational health hazard in dentistry. This cross-sectional study aimed to estimate the prevalence of pneumoconiosis and its association with age, gender, type of dental profession and duration of exposure among dental healthcare professionals (DHCPs). Methods. The study enrolled 138 DHCPs from an Indian tertiary care dental teaching institution who underwent structured face-to-face interviews, clinical examination, spirometry and chest radiography interpreted using International Labour Organization (ILO) classification. Potential pneumoconiosis was defined based on occupational exposure, clinico-spirometric examination and radiological findings consistent with pneumoconiosis (ILO category ≥ 1/0). The χ[2] test was applied to examine association of demographic-occupational characteristics with clinical symptoms, spirometric findings, radiologic findings and pneumoconiosis occurrence. Results. The prevalence of pneumoconiosis was 3.6%, with 4.3% of subjects showing radiographic opacities. Spirometry results showed a restrictive pattern in 13.8% of participants. The frequency of potential pneumoconiosis based on clinical symptoms and radiological findings was significantly associated with age > 35 years (particularly among dental technicians) and duration of exposure > 20 years, respectively. Conclusions. Increased susceptibility of DHCPs, especially dental technicians, towards pneumoconiosis highlights the importance of adoption of stringent occupational health and safety precautions, and regular clinico-radiographic screening for timely detection of pneumoconiosis.

Excessively high dust concentrations can induce pneumoconiosis, a condition presenting considerable therapeutic challenges. Dust suppressants constitute one effective means of dust control; however, research on dust suppressants has predominantly focused on characterizing their performance properties, with no systematic evaluations to date of their toxic effects on lung tissue. Therefore, through modification and response surface analysis, this study determined the optimal formulation for a composite dust suppressant to be as follows: 0.47 g modified guar gum, 0.24 mL rhamnolipid, and 5.36 g polyethylene glycol. Three toxic-exposure models were established to investigate the effects of dust and dust suppressants-both individually and in combination-on the lung tissue of C57BL/6 mice. The results indicated that low concentrations of dust suppressant (4 mg/m[3]) reduced total protein and immunoglobulin levels, thereby lowering mucosal infection risk; moderate concentrations (4-20 mg/m[3]) inhibited M1-type alveolar macrophage polarization and inflammatory factor expression (IL-6, TNF-α, etc.); and high doses (100 mg/m[3]) reduced the pulmonary fibrosis positivity rate from 11.31% to 1.30%, showing a tendency to reduce the probability of fibrosis. This study preliminarily complements the toxicological research system of dust suppressants and offers preliminary reference for the safe application of composite dust suppressants.

Pulmonary fibrosis encompasses a spectrum of chronic lung diseases characterized by progressive scarring of lung tissue, ultimately leading to respiratory failure. Emerging clinical evidence indicates that pulmonary fibrosis patients frequently experience comorbid neuropsychiatric disorders, including cognitive impairment, anxiety, and depression. These complications significantly impact patients' quality of life and treatment outcomes. However, the mechanisms underlying this comorbidity remain incompletely understood, and there is a lack of effective interventions. This review summarizes the latest clinical evidence linking pulmonary fibrosis to neuropsychiatric complications and contributes to the understanding of the underlying mechanisms through the lung-brain axis theory. Studies indicate that various pulmonary fibrosis subtypes, including idiopathic pulmonary fibrosis and pneumoconiosis, exhibit high prevalence of neuropsychiatric disorders and abnormal brain networks, indicating a close pathophysiological connection between pulmonary fibrosis and neuropsychiatric complications. At the mechanistic level, accumulating experimental evidence suggests that pulmonary fibrosis may induce central nervous system damage through three interrelated pathways: (1) Systemic dissemination of pulmonary inflammation leads to blood-brain barrier disruption and microglial activation; (2) Chronic hypoxia exacerbates neuroinflammation and synaptic dysfunction; (3) The inhaled particulate matter enters the brain from the olfactory mucosa through the olfactory bulb or crosses the damaged alveolar capillary barrier, enters the circulation, and then passes through the already damaged blood-brain barrier, inducing local neurotoxicity. Furthermore, we advocate for actively exploring a comprehensive treatment model that shifts from "lung-focused therapy" to "lung-brain co-therapy". This approach employs multiple interventions-including medication, pulmonary rehabilitation training, and cognitive training-to prevent or delay systemic complications, including neuropsychiatric damage, in pulmonary fibrosis patients. Elucidating the lung-brain axis in pulmonary fibrosis may open new avenues for a more comprehensive understanding, early intervention, and holistic management of this devastating disease.

Nano-sized particles and elongated mineral particles (EMPs) pose significant inhalation hazards in mineral extraction and processing, and are key contributors to pneumoconiosis, yet their inhalation risks remain inadequately characterized. In this study, a high-fidelity CFD-based modelling framework was developed to systematically investigate inhalation and deposition characteristics of ultrafine and EMPs in an all-in-one human airway model coupled with a breathing region. The size distribution and morphology of mineral dusts were first experimentally examined. A wide range of micro- and nano-sized spherical particles, together with elongated particles with varying aspect ratios, were then numerically simulated with various breathing rates using User-Defined Function. Their transport and deposition patterns were qualitatively visualized and deposition efficiency in total and regional airway areas was systematically evaluated. The outcomes revealed that in the upper airway, micro-sized particles 10μm exhibited high deposition (up to ∼80% in the nasal cavity), while nanoparticles remained below 3% and insensitive to breathing rate. In contrast, nanoparticles showed enhanced deep lung penetration, with deposition up to ∼4% in the trachea and individual lobes and ∼52% reaching pulmonary regions. For EMPs, deposition was strongly morphology-dependent and non-monotonic. High-aspect-ratio particles (β=50) showed up to ∼20% higher deposition in the nasal cavity compared to other β values, while moderate aspect ratio (β=5) yielded the highest deposition efficiency (∼7%) in the lower airway. This study is expected to highlight the necessity of explicitly accounting for nanoscale effects and particle morphology in assessing inhalation risks associated with mineral dust exposure.

Objective: To employ gas chromatography-ion mobility spectrometry (GC-IMS) technology for the detection of volatile organic compounds (VOCs) and their associated metabolic pathways in patients with coal worker pneumoconiosis and healthy individuals, thereby identifying potential biomarkers for the disease. Methods: In August 2024, 35 coal worker pneumoconiosis patients aged 18-80 years who underwent alveolar lavage at the Beidaihe Rehabilitation Hospital of the Ministry of Emergency Management between June and July 2024 were selected as the case group, while 20 healthy males without major diseases or dust exposure history served as the control group. Exhaled breath, blood, and urine samples were collected from both groups and analyzed using GC-IMS for qualitative and quantitative VOC identification. Differential VOCs were identified through independent-sample t-tests, fold change analysis, orthogonal partial least squares discriminant analysis (OPLS-DA), and rank-sum tests, with differential metabolic pathways analyzed using the Metabo Analyst platform. Results: Among the 35 patients, 23 were in Stage I (65.7%), 7 in Stage II (20.0%), and 5 in Stage III (14.3%), with both groups consisting exclusively of males. Exhaled breath samples contained 25 distinct VOCs, urine samples 110, and blood samples 64. Four differential VOCs were identified in exhaled breath samples, while 16 were detected in urine samples. No differential compounds were identified in blood samples. Through metabolomic analysis, five significantly different metabolic pathways were identified, from which six key differential metabolites were selected as potential biomarkers. Conclusion: GC-IMS technology enables differentiation between the VOC profiles of healthy individuals and patients with coal worker pneumoconiosis, with urine samples demonstrating particularly outstanding diagnostic value. The differential VOCs and metabolic pathways identified in this study can serve as a reference for early detection of coal worker pneumoconiosis.

Objective: To investigate the mechanism by which inhibition of Rho GTPase-activating protein 29 (ArhGAP29) affects epithelial-mesenchymal transition (EMT) and the progression of pulmonary fibrosis induced by silicon dioxide (SiO(2)) . Methods: From September 2024 to June 2025, forty SPF-grade male C57BL/6N mice were used to establish a silicosis model via intratracheal instillation of SiO(2). At 14 days after SiO(2) exposure, adeno-associated virus (AAV) carrying ArhGAP29 inhibitor was administered to infect the lungs of silicotic mice. Mice were divided into four groups (n=10 per group) : saline group (intratracheal instillation of sterile saline), SiO(2) group (intratracheal instillation of 50 μl 50 mg/ml SiO(2) suspension), SiO(2)+empty vector AAV group (AAV-BLANK group, SiO(2) modeling followed by negative control AAV intervention), and AAV-si-ArhGAP29 group (SiO(2) modeling followed by targeted ArhGAP29 interference AAV intervention) .Hematoxylin-eosin (HE) staining was performed to observe pathological changes in lung tissues. Hydroxyproline (HYP) content detection was used to evaluate the degree of pulmonary fibrosis. Western blotting was applied to detect the protein expression levels of ArhGAP29, α-smooth muscle actin (α-SMA) and E-cadherin (E-cad) in lung tissues. Immunofluorescence (IF) staining was conducted to detect the expression and localization of α-SMA and ArhGAP29. Intergroup comparisons between two groups with normal distribution and homogeneity of variance were analyzed by Student's t-test, while non-parametric tests were adopted for data not conforming to normal distribution. Results: Compared with the saline group, the expression levels of ArhGAP29 and α-SMA were significantly upregulated, while E-cad expression was markedly downregulated in lung tissues of silicotic mice (P<0.05). Compared with the AAV-BLANK group, the number and area of silicotic nodules were significantly reduced, pulmonary fibrosis was markedly alleviated, α-SMA expression was downregulated and E-cad expression was upregulated in the AAV-si-ArhGAP29 group, with statistically significant differences (P<0.05) . Conclusion: Inhibition of ArhGAP29 expression effectively alleviates SiO(2)-induced pulmonary fibrosis, and its mechanism may be associated with the suppression of epithelial-mesenchymal transition (EMT) .

Objective: To develop an interpretable machine learning model to predict the risk of respiratory failure in patients with pneumoconiosis. Methods: In February 2025, based on the retrospective West China Occupational Pneumoconiosis Cohort, 1367 hospitalized pneumoconiosis patients in West China Fourth Hospital of Sichuan University from January 1, 2012 to November 30, 2021 were selected as the research objects. Predictive variables were selected using least absolute shrinkage and selection operator (LASSO) -Cox regression. Four machine learning models, including random survival forest model (RSF), gradient boosting survival model (GBM), extreme gradient boosting survival model (XGBoost), and survival support vector machine (SSVM), as well as a traditional Cox proportional hazards regression model (CPH) were constructed. The performance of the model was evaluated using the concordance index (C-index), Brier score, area under the curve (AUC) of the receiver operating characteristic curve, and decision curve analysis (DCA). Shapley additive explanations (SHAP) were used to analyze the interpretability of the model. The stability of the model was tested using an external validation set. Results: The median follow-up time for pneumoconiosis patients was 2.69 years. During the follow-up period, 197 patients were complicated with respiratory failure, and the cumulative incidence rate was 14.41%. Fifteen variables were selected by LASSO-Cox regression and included in the prediction models, mainly including age, pneumoconiosis stage, albumin, and concurrent pulmonary hypertension. The model evaluation results showed that the C-index of the GBM model in the test set was 0.794, the Brier score was 0.044, and the 3-year AUC was 0.788, with better performance than other models. DCA showed that in the probability range of 0% to 50%, the GBM model had a high clinical net benefit in predicting the risk of respiratory failure. In the external validation, the C-index of the GBM model was 0.644. The top three influential factors in the SHAP feature importance ranking were pneumoconiosis stage, age, and body mass index. Conclusion: The prediction model for the concurrent respiratory failure in pneumoconiosis patients constructed based on GBM has high reliability and accuracy.

Patients with acute respiratory distress syndrome (ARDS) frequently develop a series of neurological complications that occur not only during the acute phase of the disease but may also persist for months or even years after discharg, leading to increased long-term mortality and disability. This article systematically reviews the clinical manifestations of neurological complications associated with ARDS, and examines in depth their complex pathophysiological mechanisms, aiming to provide a theoretical basis and clinical guidance for the early identification of high-risk patients and for the development of individualized, neuroprotection-oriented treatment strategies, with the goal of reducing mortality, and improving long-term cognitive function and quality of life.

Aluminum-magnesium (Al-Mg) alloy dusts, characterized by high chemical reactivity, present significant risks of occupational pneumoconiosis and dust explosions in wheel manufacturing. This study integrates experimental characterization with multiphase numerical simulations to investigate the process-dependent physicochemical properties and dynamic behaviors of Al-Mg dusts generated from machining (MA), smelting (SM), heat treatment (HT), and shot blasting (SB). Analyses of true density, BET surface area, SEM-EDS, and laser diffraction reveal distinct process-specific characteristics: HT dust exhibits the highest specific surface area (5.31 m2/g) and pronounced adsorption capacity, SB dust contains 9.19 wt.% carcinogenic Cr and the maximum true density (6.88 g/cm3), MA dust is predominantly composed of Al (77.92 wt.%), while SM and HT dusts are primarily Al-Mg-Na oxides. Particle size analysis indicates that 82-91% of particles exceed 10 μm, with those below 200 μm being explosible. Multiphase simulations elucidate strong couplings among particle size distribution, morphology, and dynamic behavior: MA dust (D[4,3] = 126.54 μm) deposits inertially; fine SM dust (D50 = 10.28 μm) is retained in inlet vortices; flaky SB dust exhibits a 25% reduction in settling velocity; and elliptical HT dust contributes to a cooler upper zone (413-415 K). These findings provide critical insights for optimizing worker protection strategies, dust explosion prevention, and dust collector design.