Objective:To explore the risk factors of pneumoconiosis complicated with pulmonary tuberculosis, to construct a clinical prediction model for patients with pneumoconiosis complicated with pulmonary tuberculosis, and to provide a scientific basis for the prevention of pneumoconiosis complicated with pulmonary tuberculosis.Methods:In January 2024, a total of 232 patients with pneumoconiosis (including coal workers' pneumoconiosis and silicosis) who were treated in the Department of Respiratory and Critical Care Medicine of the Third People's Hospital of Xinjiang Uygur Autonomous Region (Xinjiang Uygur Autonomous Region Occupational Disease Hospital) from January 2022 to January 2023 were randomly selected as the study subjects. Collectted basic patient information and diagnostic data. Multivariate logistic regression analysis was used to screen the risk factors related to pneumoconiosis complicated with pulmonary tuberculosis. According to the results of multivariate logistic regression analysis, a nomogram was established, and the area under the receiver operating characteristic (ROC) curve (AUC), calibration curve and decision curve analysis (DCA) were used to evaluate the predictive ability.Results:Among the 232 patients with pneumoconiosis, 73 were complicated with pulmonary tuberculosis, accounting for 31.47% (73/232). Multivariate logistic regression analysis determined that dust exposure time, type of work, smoking history, and lung function level were all risk factors for pneumoconiosis complicated with tuberculosis ( OR=10.33, 95% CI=1.92~55.66, OR=5.43, 95% CI=1.91~15.44, OR=3.10, 95% CI=1.15~8.37, OR=4.00, 95% CI=1.62~9.87; P<0.05). The constructed nomogram model has good clinical applicability when the area under the receiver operating characteristic (ROC) curve is 0.77 [95% CI (0.69, 0.73) ], the calibration curve is close to the ideal diagonal, the absolute error between the simulation curve and the actual curve is 0.03, and the DCA decision curve shows that the probability threshold of the nomogram model is 1%-90%. Conclusion:The risk of pneumoconiosis complicated with tuberculosis is high, and the risk factors of dust exposure time, smoking history, type of work and lung function level are high. This nomogram model can be used to predict the risk of pulmonary tuberculosis in patients with pneumoconiosis, which is helpful for early intervention.

Objective:To explore the risk factors of pneumoconiosis complicated with pulmonary tuberculosis, to construct a clinical prediction model for patients with pneumoconiosis complicated with pulmonary tuberculosis, and to provide a scientific basis for the prevention of pneumoconiosis complicated with pulmonary tuberculosis.Methods:In January 2024, a total of 232 patients with pneumoconiosis (including coal workers' pneumoconiosis and silicosis) who were treated in the Department of Respiratory and Critical Care Medicine of the Third People's Hospital of Xinjiang Uygur Autonomous Region (Xinjiang Uygur Autonomous Region Occupational Disease Hospital) from January 2022 to January 2023 were randomly selected as the study subjects. Collectted basic patient information and diagnostic data. Multivariate logistic regression analysis was used to screen the risk factors related to pneumoconiosis complicated with pulmonary tuberculosis. According to the results of multivariate logistic regression analysis, a nomogram was established, and the area under the receiver operating characteristic (ROC) curve (AUC), calibration curve and decision curve analysis (DCA) were used to evaluate the predictive ability.Results:Among the 232 patients with pneumoconiosis, 73 were complicated with pulmonary tuberculosis, accounting for 31.47% (73/232). Multivariate logistic regression analysis determined that dust exposure time, type of work, smoking history, and lung function level were all risk factors for pneumoconiosis complicated with tuberculosis ( OR=10.33, 95% CI=1.92~55.66, OR=5.43, 95% CI=1.91~15.44, OR=3.10, 95% CI=1.15~8.37, OR=4.00, 95% CI=1.62~9.87; P<0.05). The constructed nomogram model has good clinical applicability when the area under the receiver operating characteristic (ROC) curve is 0.77 [95% CI (0.69, 0.73) ], the calibration curve is close to the ideal diagonal, the absolute error between the simulation curve and the actual curve is 0.03, and the DCA decision curve shows that the probability threshold of the nomogram model is 1%-90%. Conclusion:The risk of pneumoconiosis complicated with tuberculosis is high, and the risk factors of dust exposure time, smoking history, type of work and lung function level are high. This nomogram model can be used to predict the risk of pulmonary tuberculosis in patients with pneumoconiosis, which is helpful for early intervention.

Objective Utilizing transcriptomic sequencing,this study aimed to monitor the expression alterations of GIMAP8 and SEC14L5 throughout the progression of pulmonary fibrosis,thereby providing insights into the underlying mechanisms of its pathogenesis and evolution.Methods C57BL/6 male mice were assigned in a randomized manner to either the Silica or PBS group.The Silica group underwent non-exposed endotracheal intubation on days 0 and 14 with 50 μL 100 mg/mL silica suspension,while the control group received 50 μL phosphate-buffered saline solution.On day 28,lung function was detected and the mice were sacrificed,and lung morphology,fibrosis,and mRNA levels were observed.Results When contrasted with individuals in good health,a differential expression analysis of mRNA in patients with pneumoconiosis identified a total of 584 mRNAs with significant expression differences.Among these,the expression of 242 mRNA was observed to be markedly elevated,while that of 342 mRNA was found to be considerably diminished.The enrichment analysis indicated that the primarily affected mRNAs with altered expression were associated with pathways such as p53,nuclear factor-κB,tumor necrosis factor,AMP-activated protein kinase,and other signaling pathways.In the Silica mice,the alveolar structures were compromised,characterized by the presence of collagen fiber accumulation and the formation of fibrous masses.In contrast,the PBS mice maintained a normal pulmonary architecture.GIMAP8 expression was up-regulated whereas SEC14L5 expression was down-regulated in lung tissues in the Silica mice,and mice in the Silica group had poorer lung function.Conclusions The onset and progression of pulmonary fibrosis may be significantly influenced by GIMAP8 and SEC14L5 expression in patients with pneumoconiosis and in silicosis animal models.This association could serve as a foundational molecular insight,paving the way for the development of preventative and therapeutic strategies against these conditions.