[Diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers].

Objective: To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population. Methods: In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model. Results: Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant (P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant (P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers (OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion: Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.

[Research progress in transcriptional and immunological biomarkers associated with tuberculosis infection].

Tuberculosis (TB) is an infectious disease that poses a serious threat to human health. About a quarter of the world's population were infected with Mycobacterium tuberculosis in 2020, and the majority of them were latently infected. Approximately 5%-10% of the population with latent tuberculosis infection may progress to active TB disease. Identifying latent TB infection from active TB by biomarkers and screening people with latent TB infection at high risk of progression for preventive treatment by biomarkers that can reliably predict the progression is one of the most effective strategies to control TB. This article reviews the progress of research on transcriptional and immunological biomarkers for identifying TB infection and predicting the progression from latent infection to active TB, with the aim of providing new ideas for tuberculosis control.