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BackgroundIn most industrialized societies, regulations, inspections, insurance, and legal options are established to support workers who suffer injury, disease, or death in relation to their work; in practice, these resources are imperfect or even unavailable due to workplace or employer obstruction. Thus, limitations exist to identify unmet needs in occupational safety and health information. ObjectiveThe aim of this study was to explore hidden issues related to occupational accidents by examining social network services (SNS) data using topic modeling. MethodsBased on the results of a Google search for the phrases occupational accident, industrial accident and occupational diseases, a total of 145 websites were selected. From among these websites, we collected 15,244 documents on queries related to occupational accidents between 2002 and 2018. To transform unstructured text into structure data, natural language processing of the Korean language was conducted. We performed the latent Dirichlet allocation (LDA) as a topic model using a Python library. A time-series linear regression analysis was also conducted to identify yearly trends for the given documents. ResultsThe results of the LDA model showed 14 topics with 3 themes: workers’ compensation benefits (Theme 1), illicit agreements with the employer (Theme 2), and fatal and non-fatal injuries and vulnerable workers (Theme 3). Theme 1 represented the largest cluster (52.2%) of the collected documents and included keywords related to workers’ compensation (ie, company, occupational injury, insurance, accident, approval, and compensation) and keywords describing specific compensation benefits such as medical expense benefits, temporary incapacity benefits, and disability benefits. In the yearly trend, Theme 1 gradually decreased; however, other themes showed an overall increasing pattern. Certain queries (ie, musculoskeletal system, critical care, and foreign workers) showed no significant variation in the number of queries. ConclusionsWe conducted LDA analysis of SNS data of occupational accident–related queries and discovered that the primary concerns of workers posting about occupational injuries and diseases were workers’ compensation benefits, fatal and non-fatal injuries, vulnerable workers, and illicit agreements with employers. While traditional systems focus mainly on quantitative monitoring of occupational accidents, qualitative aspects formulated by topic modeling from unstructured SNS queries may be valuable to address inequalities and improve occupational health and safety.

Objectives: To investigate the internal structure of the nasomaxillary complex, including the maxillary sinus, nasal cavity and nasal septum according to the facial asymmetry pattern and to evaluate its correlation with external maxillomandibular asymmetry in Class III patients based on cone‐beam computerized tomography (CBCT) images. Materials and Methods: Facial asymmetry was analysed in a total of 100 Class III patients aged 16 years or older using CBCT scans. Patients were categorized into subgroups based on asymmetry pattern. Measurements of the nasomaxillary complex were obtained from the CBCT scans, including the volume and width of the maxillary sinuses and nasal cavities on deviated and non‐deviated sides, as well as the displacement of the nasal septum. Statistical analysis was performed to compare the internal nasomaxillary variables within and between groups, and regression analysis was conducted to evaluate the correlation between facial asymmetry and the internal nasomaxillary variables. Results: Group comparisons showed that there were no significant differences in the volume of the maxillary sinus and nasal cavity. However, the direction and extent of nasal septum deviation, as well as the width of the nasal cavity, varied depending on the maxillary asymmetry pattern. Regression analysis indicated a correlation between nasal septum deviation and the difference in maxillary height, while the difference in nasal cavity width was correlated with the difference in maxillary width. Conclusion: A comprehensive evaluation of the internal nasal anatomy is vital for understanding the intricate relationship between nasal structure and maxillary growth. [ABSTRACT FROM AUTHOR]

BackgroundPlasminogen activator inhibitor-1 (PAI-1) is induced in airways by virus and may mediate asthmatic airway remodeling. We sought to evaluate if genetic variants and early life lower respiratory infections jointly affect asthma risk.MethodsWe included Latino children, adolescents, and young adults aged 8-21 years (1736 subjects with physician-diagnosed asthma and 1747 healthy controls) from five U.S. centers and Puerto Rico after excluding subjects with incomplete clinical or genetic data. We evaluated the independent and joint effects of a PAI-1 gain of function polymorphism and bronchiolitis / Respiratory Syncytial Virus (RSV) or other lower respiratory infections (LRI) within the first 2 years of life on asthma risk, asthma exacerbations and lung function.ResultsRSV infection (OR 9.9, 95%CI 4.9-20.2) and other LRI (OR 9.1, 95%CI 7.2-11.5) were independently associated with asthma, but PAI-1 genotype was not. There were joint effects on asthma risk for both genotype-RSV (OR 17.7, 95% CI 6.3-50.2) and genotype-LRI (OR 11.7, 95% CI 8.8-16.4). A joint effect of genotype-RSV resulted in a 3.1-fold increased risk for recurrent asthma hospitalizations. In genotype-respiratory infection joint effect analysis, FEV1% predicted and FEV1/FVC % predicted were further reduced in the genotype-LRI group (β -2.1, 95% CI -4.0 to -0.2; β -2.0, 95% CI -3.1 to -0.8 respectively). Similarly, lower FEV1% predicted was noted in genotype-RSV group (β -3.1, 95% CI -6.1 to -0.2) with a trend for lower FEV1/FVC % predicted.ConclusionsA genetic variant of PAI-1 together with early life LRI such as RSV bronchiolitis is associated with an increased risk of asthma, morbidity, and reduced lung function in this Latino population.