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Exposure to fine particulate matter (PM2.5) from incomplete fossil fuel combustion (coal, oil, gas and diesel) has been linked to increased morbidity and mortality due to metabolic diseases. PM2.5 exaggerate adipose inflammation and insulin resistance in mice with diet‐induced obesity. Here, we elucidate the hypothesis that such systemic effects may be triggered by adhered particle components affecting adipose tissue directly. Studying adipocytes differentiated from primary human mesenchymal stem cells, we found that lipophilic organic chemicals (OC) from diesel exhaust particles induced inflammation‐associated genes and increased secretion of the chemokine CXLC8/interleukin‐8 as well as matrix metalloprotease 1. The oxidative stress response gene haem oxygenase‐1 and tumour necrosis factor alpha were seemingly not affected, while aryl hydrocarbon receptor‐regulated genes, cytochrome P450 1A1 (CYP1A1) and CYP1B1 and plasminogen activator inhibitor‐2, were clearly up‐regulated. Finally, expression of β‐adrenergic receptor, known to regulate adipocyte homoeostasis, was down‐regulated by exposure to these lipophilic OC. Our results indicate that low concentrations of OC from combustion particles have the potential to modify expression of genes in adipocytes that may be linked to metabolic disease. Further studies on mechanisms linking PM exposure and metabolic diseases are warranted. [ABSTRACT FROM AUTHOR]

Electricians frequently experience low-voltage electrical accidents. Some such accidents involve long-term negative health consequences. Early identification of victims at risk for long-term injury may improve acute medical treatment and long-term follow-up. This study aimed to determine acute exposure, health effects and treatment associated with general health ≥ 2 years after low-voltage electrical accidents. In a cross-sectional study, 89 male electricians who had experienced an electrical accident between 1994 and 2001 participated in a 2003 follow-up health examination. They were identified from a registry of low-voltage electrical accidents and included in the study. Based on exposure descriptions in the original accident reports, they were stratified into the following three groups: a current arc accident group (N = 34, mean age 38.8 years [standard deviation, SD = 12.2, range = 21–59]) and two groups with the passage of current through the body, either fixed to the current source ("no-let-go" group; N = 35, mean age 34.0 years [SD = 10.5, range = 21–57]) or not ("let-go" group; N = 20, mean age = 38.7 years [SD = 10.3, range = 21–63]). They retrospectively described acute reactions and assessed their current general health at the health examination. Multivariate linear regression, ordinal logistic regression and Fisher's exact test were used to compare acute reactions with health at follow-up in each exposure group. The multivariate analysis indicated that after accidents with the passage of current through the body, severe acute headache (β = − 0.56, p = 0.013), years since the accident (β = − 0.16, p = 0.017) and the accident being perceived as frightening (β = − 0.48, p = 0.040) were negatively associated with general health ≥ 2 years later (R2 = 0.25, p = 0.002). If the exposure included a no-let-go experience, then acute severe body numbness (β = − 0.53, p = 0.029) was also negatively associated with general health (R2 = 0.38, p = 0.002). Without such experience, only acute confusion (β = − 0.90, p = 0.029) was negatively associated with the health at follow-up (R2 = 0.24, p = 0.029). In univariate analyses, after the passage of current through the body, acute dizziness (p = 0.029), apathy (p = 0.028), confusion (p = 0.007) and irregular heartbeat (p ≤ 0.05) were associated with poor long-term general health. The no-let-go group, more often than the let-go group, reported panic (p = 0.001), fear of death (p = 0.029), confusion (p = 0.014), exhaustion (p = 0.009), bodily numbness (p = 0.013) and immediate unconsciousness (p = 0.019). Acute symptoms beyond the first day after a current arc accident were associated with poor long-term general health (p = 0.015). The acute reactions negatively associated with general health ≥ 2 years after low-voltage electrical accidents should alert the clinician in the acute phase after an electrical accident to the risk of developing negative long-term health effects. Future studies should specify long-term health beyond the concept of general health. • Nervous system reaction to passage of electrical current through the body is associated with impaired later general health. • Headache, bodily numbness, and confusion are the most important predictors of impaired general health after such accidents. • Short duration of acute reactions indicates the likelihood of good recovery after the passage of current through the body. • Acute burn injuries, rather than nervous system reactions, are typical of current arc accidents. [ABSTRACT FROM AUTHOR]

Exposure to diesel exhaust particles (DEPs) affects endothelial function and may contribute to the development of atherosclerosis and vasomotor dysfunction. As intracellular calcium concentration [Ca2+]i is considered important in myoendothelial signalling, we explored the effects of extractable organic matter from DEPs (DEP-EOM) on [Ca2+]i and membrane microstructure in endothelial cells. DEP-EOM of increasing polarity was obtained by pressurized sequential extraction of DEPs with n-hexane (n-Hex-EOM), dichloromethane (DCM-EOM), methanol, and water. Chemical analysis revealed that the majority of organic matter was extracted by the n-Hex- and DCM-EOM, with polycyclic aromatic hydrocarbons primarily occurring in n-Hex-EOM. The concentration of calcium was measured in human microvascular endothelial cells (HMEC-1) using micro-spectrofluorometry. The lipophilic n-Hex-EOM and DCM-EOM, but not the more polar methanol- and water-soluble extracts, induced rapid [Ca2+]i increases in HMEC-1. n-Hex-EOM triggered [Ca2+]i increase from intracellular stores, followed by extracellular calcium influx consistent with store operated calcium entry (SOCE). By contrast, the less lipophilic DCM-EOM triggered [Ca2+]i increase via extracellular influx alone, resembling receptor operated calcium entry (ROCE). Both extracts increased [Ca2+]i via aryl hydrocarbon receptor (AhR) non-genomic signalling, verified by pharmacological inhibition and RNA-interference. Moreover, DCM-EOM appeared to induce an AhR-dependent reduction in the global plasma membrane order, as visualized by confocal fluorescence microscopy. DCM-EOM-triggered [Ca2+]i increase and membrane alterations were attenuated by the membrane stabilizing lipid cholesterol. In conclusion, lipophilic constituents of DEPs extracted by n-hexane and DCM seem to induce rapid AhR-dependent [Ca2+]i increase in HMEC-1 endothelial cells, possibly involving both ROCE and SOCE-mediated mechanisms. The semi-lipophilic fraction extracted by DCM also caused an AhR-dependent reduction in global membrane order, which appeared to be connected to the [Ca2+]i increase. [ABSTRACT FROM AUTHOR]

An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Within the scope of the Exposome Project for Health and Occupational Research on applying the exposome concept to working life health, we aimed to provide a broad overview of the status of knowledge on occupational exposures and associated health effects across multiple noncommunicable diseases (NCDs) to help inform research priorities., Methods: We conducted a narrative review of occupational risk factors that can be considered to have "consistent evidence for an association," or where there is "limited/inadequate evidence for an association" for 6 NCD groups: nonmalignant respiratory diseases; neurodegenerative diseases; cardiovascular/metabolic diseases; mental disorders; musculoskeletal diseases; and cancer. The assessment was done in expert sessions, primarily based on systematic reviews, supplemented with narrative reviews, reports, and original studies. Subsequently, knowledge gaps were identified, e.g. based on missing information on exposure-response relationships, gender differences, critical time-windows, interactions, and inadequate study quality., Results: We identified over 200 occupational exposures with consistent or limited/inadequate evidence for associations with one or more of 60+ NCDs. Various exposures were identified as possible risk factors for multiple outcomes. Examples are diesel engine exhaust and cadmium, with consistent evidence for lung cancer, but limited/inadequate evidence for other cancer sites, respiratory, neurodegenerative, and cardiovascular diseases. Other examples are physically heavy work, shift work, and decision latitude/job control. For associations with limited/inadequate evidence, new studies are needed to confirm the association. For risk factors with consistent evidence, improvements in study design, exposure assessment, and case definition could lead to a better understanding of the association and help inform health-based threshold levels., Conclusions: By providing an overview of knowledge gaps in the associations between occupational exposures and their health effects, our narrative review will help setting priorities in occupational health research. Future epidemiological studies should prioritize to include large sample sizes, assess exposures prior to disease onset, and quantify exposures. Potential sources of biases and confounding need to be identified and accounted for in both original studies and systematic reviews., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)