Mortality in Underground Miners in a Former Uranium Ore Mine–Results of a Cohort Study Among Former Employees of Wismut AG in Saxony and Thuringia

Efficient clinical data analysis for prediction of coal workers' pneumoconiosis using machine learning algorithms

PURPOSE

The purpose of this study is to propose an efficient coal workers' pneumoconiosis (CWP) clinical prediction system and put it into clinical use for clinical diagnosis of pneumoconiosis.

METHODS

Patients with CWP and dust-exposed workers who were enrolled from August 2021 to December 2021 were included in this study. Firstly, we chose the embedded method through using three feature selection approaches to perform the prediction analysis. Then, we performed the machine learning algorithms as the model backbone and combined them with three feature selection methods, respectively, to determine the optimal predictive model for CWP.

RESULTS

Through applying three feature selection approaches based on machine learning algorithms, it was found that AaDO₂ and some pulmonary function indicators played an important role in prediction for identifying CWP of early stage. The support vector machine (SVM) algorithm was proved as the optimal machine learning model for predicting CWP, with the ROC curves obtained from three feature selection methods using SVM algorithm whose AUC values of 97.78%, 93.7%, and 95.56%, respectively.

CONCLUSION

We developed the optimal model (SVM algorithm) through comparisons and analyses among the performances of different models for the prediction of CWP as a clinical application.

Where do you live and what do you do? Two questions that might impact your kidney health

In many cases the social determinants of health need to be assessed through their interaction with environmental factors. This review looks at the impact of physical location and occupation of individuals on their kidney health. It examines the effect of living at high altitude on kidney function and the relationship between extreme cold or hot temperatures and the incidence of kidney injury. It reviews as well the many occupations that have been linked to kidney disease in high-income and low-and-middle-income countries. As a conclusion, this overview proposes preventive recommendations that could be individualized based on weather, altitude, socio-economic level of the country and occupation of the individual.

Risk of Developing Non-Cancerous Central Nervous System Diseases Due to Ionizing Radiation Exposure during Adulthood: Systematic Review and Meta-Analyses

Background: High-dose ionizing radiation (IR) (>0.5 Gy) is an established risk factor for cognitive impairments, but this cannot be concluded for low-to-moderate IR exposure (<0.5 Gy) in adulthood as study results are inconsistent. The objectives are to summarize relevant epidemiological studies of low-to-moderate IR exposure in adulthood and to assess the risk of non-cancerous CNS diseases. Methods: A systematic literature search of four electronic databases was performed to retrieve relevant epidemiological studies published from 2000 to 2022. Pooled standardized mortality ratios, relative risks, and excess relative risks (ERR) were estimated with a random effect model. Results: Forty-five publications were included in the systematic review, including thirty-three in the quantitative meta-analysis. The following sources of IR-exposure were considered: atomic bomb, occupational, environmental, and medical exposure. Increased dose-risk relationships were found for cerebrovascular diseases incidence and mortality (ERRpooled per 100 mGy = 0.04; 95% CI: 0.03−0.05; ERRpooled at 100 mGy = 0.01; 95% CI: −0.00−0.02, respectively) and for Parkinson’s disease (ERRpooled at 100 mGy = 0.11; 95% CI: 0.06−0.16); Conclusions: Our findings suggest that adult low-to-moderate IR exposure may have effects on non-cancerous CNS diseases. Further research addressing inherent variation issues is encouraged.

The German Uranium Miners’ Biobank—A Biobank for OMICs Radiation Research

Systematic bio- and databanks are key prerequisites for modern radiation research to investigate radiation response mechanisms in the context of genetic, environmental and lifestyle-associated factors. This report presents the current status of the German Uranium Miners’ Biobank. In 2008, the bio- and databank was established at the Federal Office for Radiation Protection, and the sampling of biological materials from former uranium miners with and without lung cancer was initiated. For this purpose, various biological specimens, such as DNA and RNA, were isolated from blood samples as well as from formalin-fixed paraffin-embedded lung tissue. High-quality biomaterials suitable for OMICs research and the associated data on occupational radiation and dust exposure, and medical and lifestyle data from over 1000 individuals have been stored so far. Various experimental data, e.g., genome-wide SNPs, whole genome transcriptomic and miRNA data, as well as individual chromosomal aberration data from subgroups of biobank samples, are already available upon request for in-depth research on radiation-induced long-term effects, individual radiation susceptibility to lung cancer and radon-induced fingerprints in lung cancer. This biobank is the first systematic uranium miners´ biobank worldwide that is suitable for OMICs research on radiation-exposed workers. It offers the opportunity to link radiation-induced perturbations of biological pathways or processes and putative adverse outcome(s) by OMICs profiling at different biological organization levels.

[Silica-induced scleroderma in miners in former uranium ore mining (Wismut AG)]

As part of the reappraisal of the legacy of Wismut AG, 12 patients with silica-induced scleroderma among underground uranium ore mine workers (Wismut AG) under long-term exposure to silica fine dust, as well as radon and its daughter products, during the 1960s and 1970s are reported on. Silica-induced scleroderma is clinically, serologically and immunologically indistinguishable from idiopathic systemic sclerosis. In experimental studies, endothelial cells, monocytes and fibroblasts, as well as their synthesis rates and the release of cytokines and chemokines, were activated by silica fine dust in a way that is consistent with the pathophysiological processes in idiopathic systemic sclerosis. It was not possible to achieve recognition of silica-induced systemic sclerosis as an occupational disease in Germany.