ObjectiveTo explore the application effect of using the comprehensive index method for occupational health risk assessment in the lead-acid battery enterprises. Methods Convenient sampling method was used to select two lead-acid battery enterprises A and B in Jiangsu Province, with eight key positions including ball grinding, plate casting, pasting, plate coating, plate grinding, plate slicing and brushing, welding and acid charging as the research subjects. Worksite survey of occupational health was conducted in these two lead enterprises, and the levels of lead smoke, lead dust and sulfuric acid in the key positions were detected. The health risk of occupational hazards in the eight key positions was evaluated by a comprehensive index method. Results The time-weighted average concentration (C_TWA) of lead smoke in plate casting and welding positions of enterprise A, the C_TWA of lead dust in plate grinding and plate slicing and brushing positions of enterprise A, the C_TWA of lead dust in plate grinding position of enterprise B, the C_TWA of lead smoke in welding position of enterprise B were exceeded national occupational exposure limits. The risk assessment results of the plate casting, welding, plate grinding and plate slicing and brushing positions were moderate risk, while other positions were low risk in enterprise A. The risk assessment results of the plate grinding and welding positions were moderate risk, while other positions were low risk in enterprise B. Conclusion The results of risk assessment by the comprehensive index method were consistent with the results of occupational hazard factors detection. The comprehensive index method could well evaluate the occupational health risks of lead-acid battery enterprises.

Objective:To screen and identify plasma differentially expressed genes and related signal pathway by human gene expression profile array and fluorescent quantitative PCR.Methods:From September 2018 to October 2019, 291 workers from a Mercury-in-glass thermometer factory in Jiangsu Province were selected for an occupational health examination, a total of 60 persons were divided into two groups: high and low mercury exposure groups (30 persons in each group) . Plasma total RNA samples from the high exposure group and the low exposure group (10 cases each) were detected by gene expression microarray, and differentially expressed genes (DEGs) with fold change >2 were selected. DEGs were submitted to David and Metascape for gene function clustering, pathway and protein interaction network analysis. Finally, fluorescence quantitative PCR was performed to verify the changes in the expression levels of key DEGs in the high exposure group and the low exposure group (another 20 cases in each group) .Results:A total of 269 DEGs, of which 203 up regulated and 66 down regulated were identified in the differential expression analysis of gene expression microarray. Bioinformatics analysis suggested that, DEGs were involved in forebrain development, glial cell fate determinants of GO biological process and PID NF-KB, PTEN signal pathway. NFE2L1, SOX8, SOX6 and RNF2 ( P<0.05) were confirmed down regulated in high level group by fluorescent quantitative PCR compared with the low level group (fold changes were 2.10, 11.52, 2.19, and 4.38 respectively) . Conclusion:The plasma NFE2L1, SOX8, SOX6 and RNF2 gene expressions are significantly altered in occupa tional high mercury exposure population. PTEN signaling pathway and fate of glia cells determines the biological process may be closely related to the body injury caused by mercury exposure.

Objective:To screen and identify plasma differentially expressed genes and related signal pathway by human gene expression profile array and fluorescent quantitative PCR.Methods:From September 2018 to October 2019, 291 workers from a Mercury-in-glass thermometer factory in Jiangsu Province were selected for an occupational health examination, a total of 60 persons were divided into two groups: high and low mercury exposure groups (30 persons in each group) . Plasma total RNA samples from the high exposure group and the low exposure group (10 cases each) were detected by gene expression microarray, and differentially expressed genes (DEGs) with fold change >2 were selected. DEGs were submitted to David and Metascape for gene function clustering, pathway and protein interaction network analysis. Finally, fluorescence quantitative PCR was performed to verify the changes in the expression levels of key DEGs in the high exposure group and the low exposure group (another 20 cases in each group) .Results:A total of 269 DEGs, of which 203 up regulated and 66 down regulated were identified in the differential expression analysis of gene expression microarray. Bioinformatics analysis suggested that, DEGs were involved in forebrain development, glial cell fate determinants of GO biological process and PID NF-KB, PTEN signal pathway. NFE2L1, SOX8, SOX6 and RNF2 ( P<0.05) were confirmed down regulated in high level group by fluorescent quantitative PCR compared with the low level group (fold changes were 2.10, 11.52, 2.19, and 4.38 respectively) . Conclusion:The plasma NFE2L1, SOX8, SOX6 and RNF2 gene expressions are significantly altered in occupa tional high mercury exposure population. PTEN signaling pathway and fate of glia cells determines the biological process may be closely related to the body injury caused by mercury exposure.

Objective:To explore and analyze differential expressed genes in malignant pleural mesothelioma (MPM) by bioinformatics method, and to study their prognostic value in MPM and their potential role in immunotherapy.Methods:In January 2022, the dataset GSE51024 was downloaded from the GEO database, and MPM (55 cases) and normal tissue (41 cases) samples were obtained. Using R software and HMDD and miRNet database, MPM-related differential genes were screened and co-expressed genes were identified. Co-expressed genes were enriched and functionally annotated, and protein-protein interaction (PPI) networks were constructed and key genes were identified using the STRING database and Cytoscape software. TRRUST and GEPIA databases were used to predict transcription factors of key genes and to analyze prognosis and survival. The correlation between key genes and the degree of infiltration of immune cells was analyzed using TIMER.Results:A total of 435 co-expressed genes were obtained, which were mainly concentrated in the extracellular matrix tissue and the signaling pathways of cell adhesion molecules. Combined with PPI and TRRUST database, seven key MPM prognostic genes were identified. Among them, cyclin 20 (CDC20) , cell cycle checkpoint kinase 1 (CHEK1) , enhancer of Zeste homolog 2 (EZH2) , ribonucleotide reductase subunit M2 (RRM2) , topoisomerase 2A (TOP2A) , ubiquitin like plant homeodomain and ring finger domain 1 (UHRF1) were significantly up-regulated in MPM, while cyclin A1 (CCNA1) was significantly down-regulated. The expressions of CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 genes were significantly associated with MPM overall survival ( P<0.05) . The expressions of CDC20, CHEK1, EZH2, RRM2 and TOP2A genes were positively correlated with B cells and dendritic cells ( P<0.05) , and negatively correlated with neutrophils ( P<0.05) . Conclusion:CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 may be potential prognostic markers in MPM patients, and their expressions may be related to MPM tumor immunity.

Objective:To explore and analyze differential expressed genes in malignant pleural mesothelioma (MPM) by bioinformatics method, and to study their prognostic value in MPM and their potential role in immunotherapy.Methods:In January 2022, the dataset GSE51024 was downloaded from the GEO database, and MPM (55 cases) and normal tissue (41 cases) samples were obtained. Using R software and HMDD and miRNet database, MPM-related differential genes were screened and co-expressed genes were identified. Co-expressed genes were enriched and functionally annotated, and protein-protein interaction (PPI) networks were constructed and key genes were identified using the STRING database and Cytoscape software. TRRUST and GEPIA databases were used to predict transcription factors of key genes and to analyze prognosis and survival. The correlation between key genes and the degree of infiltration of immune cells was analyzed using TIMER.Results:A total of 435 co-expressed genes were obtained, which were mainly concentrated in the extracellular matrix tissue and the signaling pathways of cell adhesion molecules. Combined with PPI and TRRUST database, seven key MPM prognostic genes were identified. Among them, cyclin 20 (CDC20) , cell cycle checkpoint kinase 1 (CHEK1) , enhancer of Zeste homolog 2 (EZH2) , ribonucleotide reductase subunit M2 (RRM2) , topoisomerase 2A (TOP2A) , ubiquitin like plant homeodomain and ring finger domain 1 (UHRF1) were significantly up-regulated in MPM, while cyclin A1 (CCNA1) was significantly down-regulated. The expressions of CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 genes were significantly associated with MPM overall survival ( P<0.05) . The expressions of CDC20, CHEK1, EZH2, RRM2 and TOP2A genes were positively correlated with B cells and dendritic cells ( P<0.05) , and negatively correlated with neutrophils ( P<0.05) . Conclusion:CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 may be potential prognostic markers in MPM patients, and their expressions may be related to MPM tumor immunity.