Background The prevalence of chronic diseases among the Chinese occupational population is rising steadily, with hypertension and diabetes becoming important health concerns. Occupational health examinations (OHE) provide stable population coverage, standardized protocols, and fixed follow-up intervals, offering a robust data foundation for risk assessment. However, most existing hypertension prediction studies rely on cross-sectional data and mainly focus on clinic onset, failing to capture the dynamic progression and cumulation of individual risk. Objective To construct a machine learning-based risk prediction model for blood pressure abnormality in occupational populations, providing a reference for health risk stratification and targeted health interventions. Methods Longitudinal data from 2020 to 2023 were extracted from the occupational health examination database of an institution in Shanghai. After excluding individuals with hypertension in any of the first three years, 3710 workers who participated 4 consecutive years of OHE were included. Six categories of blood pressure-related indicators from 2020 to 2022 were selected, including basic information, lifestyles, occupational exposures, cardiovascular indicators, routine blood tests, and biochemical markers, comprising 30 variables in total. For feature engineering, continuous variables were processed to reflect three-year dynamic characteristics: level (mean), variability (variance), and temporal trend (slope). Categorical variables were incorporated using 2022 values. Least absolute shrinkage and selection operator regression was applied to identify variables for inclusion in the machine learning models. Five models (decision tree, logistic regression, random forest, support vector machine, and XGBoost) were employed to predict blood pressure abnormality risk in 2023. And then sensitive analysis was conducted. The optimal model was selected based on the area under the curve (AUC) of receiver operating characteristic. Feature importance and SHAP analyses were applied to interpret the final model. Results Feature engineering transformed 17 continuous variables into 51 secondary variables, combined with 13 baseline variables, resulted in 24 variables screened out by LASSO regression. The logistic regression model achieved the best performance. Feature importance analysis indicated that the dynamic trajectory of blood pressure played a central role in the model, complemented by other biochemical and lifestyle indicators. SHAP analysis further showed that the model’s ability to not only identify risks of high-normal blood pressure and hypertension but also quantify the specific contribution of individual examination indicators to predicted risk, supporting risk-stratified population management in occupational health management. Conclusion Based on an existing occupational health examination database and routinely collected data, this study has developed a risk prediction model for blood pressure abnormalities in occupational populations. By incorporating dynamic change characteristics from longitudinal examinations, the study demonstrates the feasibility of using routine health data for early risk identification and stratified management. However, its applicability is limited by the availability of repeated examination data and the focus on specific occupational groups, requiring further validation across broader populations and diverse clinic scenarios.

As a primary approach to safeguarding workers' occupational health in China, the work-related injury insurance still has insufficient preventive measures for occupational groups. By reviewing the preventive measures embedded in Germany’s statutory accident insurance (Gesetzliche Unfallversicherung) and Japan’s workers’ accident compensation insurance, this study summarized their best practices and then proposed the following policy directions based on China’s specific context: strengthening the prevention-oriented institutional framework, increasing financial investment in occupational injury prevention, improving the incentive mechanisms of floating premium rate, and promoting data integration and intelligent applications in occupational health management. These measures are expected to shift China’s work-related injury insurance system from a compensation-oriented model to one that emphasizes comprehensive prevention and health promotion, thereby providing useful insights for better safeguarding the health of Chinese workers.

Background Long-term occupational health surveillance facilitates the identification of chronic health risks arising from occupational hazard exposures. However, under low-level exposure conditions in chemical enterprises, traditional workplace-centered risk assessment models are insufficient to fully explain the observed health effects among workers, highlighting the need for individual-focused health management strategies that focus on the worker. Objective To characterize long-term health trends among workers in a chemical enterprise and examine the limitations of workplace hazard monitoring and health surveillance under low-level multiple exposure scenarios, thereby providing a scientific basis for more comprehensive worker health protection measures. Methods We analyzed 972 occupational health examination records collected over a 15-year period (2010–2024) from a chemical enterprise, integrating these with enterprise hazard monitoring reports and workshop air monitoring of volatile organic compounds (VOCs). The annual counts and prevalences of abnormalities in liver function tests, metabolic syndrome-related indicators, and liver imaging were summarized. Temporal trends were evaluated using the Cochran-Armitage trend test. Time-related changes in abnormal health indicators among active workers were evaluated by generalized linear mixed-effects models (GLMMs), adjusting for age and sex. Individual longitudinal profiles were described for nine workers with continuous 15-year records. In addition, paired comparisons of health outcomes were conducted for 81 workers with both pre-employment and periodic examinations. Results Workplace hazard monitoring indicated that airborne concentrations of major occupational contaminants including VOCs, acids and bases, dust, and physical factors were below national occupational exposure limits. However, 62 VOC species—including chlorobenzene, chloromethane, and cyclohexane—were detected in workshop air, suggesting complex mixed organic solvent exposure. From 2010 to 2015, occupational health examination records were primarily based on physicians’ qualitative assessment, yielding generally low abnormality detection rates. During 2016–2024, data collection was complete, and the prevalences of abnormalities in liver function, metabolic syndrome-related indicators, and liver imaging among active workers remained relatively high. Trend analysis indicated that only the abnormality rates of total bilirubin (TBIL) and hypertension showed statistically significant temporal trends; other indicators exhibited no significant linear changes despite high prevalences. After adjusting for age and sex, the GLMMs showed that the abnormality rates of aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), TBIL, and hypertension decreased over time, whereas those of total cholesterol, triglycerides, and fatty liver increased. In a subgroup of 9 workers with continuous 15-year follow-up data, the cumulative number of abnormal health indicators increased in several individuals after 2016. Among the 81 workers with both pre-employment and periodic records, abnormalities in total cholesterol, triglycerides, body mass index, and fatty liver were significantly more prevalent after employment over time, whereas changes in liver function enzymes were not statistically significant. Conclusion With increasing age, workers exhibit a gradual deterioration in liver function and metabolic-related health indicators, reaching abnormality rates comparable to those reported in the general population. These findings suggest that both workplace-related and non-occupational factors jointly contribute to the observed health changes. Consequently, occupational health management should shift towards an "individual-centered" approach. Enhancing workers' health literacy, strengthening workplace health promotion, and extending occupational health services beyond the workplace are essential to comprehensively protect workers' health.

Objective To analyze the coverage of chronic disease-related indicators and the distribution of positive detection rates in occupational medical examinations (OME). Methods A total of 872 862 currently employed workers who underwent OME from 2015 to 2023 were selected as the study participants using a convenience sampling method. According to the year of OME, the study period was divided into three periods: 2015-2017, 2018-2020, and 2021-2023. The examination rates and positive detection rates of five chronic disease-related indicators, including obesity, high blood pressure, hyperglycemia, dyslipidemia, and hyperuricemia, were analyzed. Results Regarding the routine medical examination indicators in OME, the examination rates for systolic and diastolic blood pressure were both 97.4%, while those for body height and weight were both 6.8%. Among the mandatory or optional examination items for specific occupational groups in OMEs, the examination rates of fasting blood glucose, triglycerides, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol were 35.2%, 18.5%, 18.5%, 7.8%, and 7.9%, respectively. Regarding items not included in OMEs, the examination rates of glycated hemoglobin and uric acid were 0.2% and 19.2%, respectively. The examination rates for systolic and diastolic blood pressure consistently exceeded 95.0%, the examination rates for fasting blood glucose, triglycerides, and uric acid ranged from 32.9% to 37.0%, 16.8% to 21.4%, and 16.9% to 24.1%, respectively, while the rates for body height and weight remained below 10.0% across these three periods. Among workers who completed corresponding OME items, dyslipidemia and hyperuricemia showed relatively higher positive detection rates, with rates of 23.2% and 23.0%, respectively. The positive detection rates of obesity, high blood pressure, and hyperglycemia were relatively lower, at 9.6%, 3.5%, and 1.4%, respectively. Across the three periods, the positive detection rates of dyslipidemia, hyperuricemia, obesity, high blood pressure, and hyperglycemia ranged from 18.0% to 33.7%, 7.0% to 28.5%, 7.8% to 10.9%, 3.3% to 3.9%, and 1.4% to 1.5%, respectively, all showing increasing trends with advancing OME periods (all P<0.01). Conclusion Current OME practices show a mismatch between the coverage of chronic disease-related indicators and the actual health risks among occupational worker populations. Although blood pressure monitoring is well implemented, basic physical indicators (body height and body weight) and key metabolic indicators (blood glucose, blood lipids, and uric acid) are insufficiently covered, limiting comprehensive assessment of occupational health risks. Optimization of monitoring strategies is urgently needed to improve data completeness.

OBJECTIVES: Wild-caught Microtus fortis (M. fortis) at the age of 9-15 months can develop epithelial ovarian cancers similar to human epithelial ovarian cancers under natural conditions during experimental animal breeding, but its pathological types and biological characteristics remain unclear. This study aims to analyze the biological characteristics of spontaneous ovarian cancer in M. fortis, intending to develop M. fortis as an animal model for human epithelial ovarian cancer. METHODS: The female M. fortis (9-15 months old) with spontaneous ovarian cancer were selected as the experimental group, and healthy M. fortis from the same litter were selected as the control group. The ovarian pathological changes of the two groups were observed by dissection. Blood routine and biochemical indicators were measured by biochemical analysis. Hematoxylin and eosin (HE) staining was performed to observe the pathological changes in the ovarian cancer tissue of M. fortis. Immunohistochemical staining was used to detect the protein expression of common ovarian cancer markers, and real-time RT-PCR was used to analyze the transcription levels of ovarian cancer-related genes. RESULTS: Spontaneous ovarian cancer in M. fortis mainly affects both ovaries, with tumors appearing solid or cystic. HE staining and histopathological analysis confirmed that the ovarian tumors originated from ovarian surface epithelium. Compared to the control group, the experimental group showed significantly decreased hemoglobin (P<0.01), hematocrit (P<0.05), albumin (P<0.05), and blood glucose levels (P<0.01), while lymphocyte percentage (P<0.05), monocyte percentage (P<0.05), cholesterol (P<0.01), and progesterone (P<0.01) levels were significantly increased. Expression of ovarian cancer-related genes, including ID3, CDC42, RHOA, RB1CC1, NF1, PIN1, MIB1, PDS5A, MCM7, and MLH1, was significantly downregulated (all P<0.05), while PAX8 gene expression was significantly upregulated (P<0.05). Immunohistochemical results showed that Wilms' tumor gene 1 (WT1) protein was mainly distributed throughout the cell, with significantly higher expression in ovarian cancer M. fortis. Tumor protein 53 (TP53) was expressed in both healthy and ovarian cancer M. fortis and was distributed throughout the cell. Hepatocyte nuclear factor 1 beta (HNF1B) and progesterone receptor (PR) protein were highly expressed in the ovarian tissue of healthy M. fortis but were significantly reduced in the ovarian cancer M. fortis, though both were located in the cytoplasm. CONCLUSIONS Spontaneous ovarian cancer in M. fortis is serous ovarian cancer. Compared to healthy M. fortis, significant differences were observed in ovarian tissue morphology, biochemical indicators, ovarian cancer-related gene expression, and protein expression, which show similarity to the biological characteristics of human serous ovarian cancer. This suggests that M. fortis could be an ideal animal model for studying human serous ovarian cancer.
Female ; Ovarian Neoplasms/metabolism* ; Animals ; Carcinoma, Ovarian Epithelial ; Disease Models, Animal ; Humans ; Neoplasms, Glandular and Epithelial/metabolism* ; Ovary/pathology*

OBJECTIVES: Recent evidence suggests that the gut may be a primary site of metformin action. However, studies on the effects of metformin on gut microbiota remain limited, and its impact on gut microbial metabolites such as short-/medium-chain fatty acids is unclear. This study aims to investigate the effects of metformin on gut microbiota, short-/medium-chain fatty acids, and associated metabolic benefits in high-fat diet rats. METHODS: Twenty-four Sprague-Dawley rats were randomly divided into 3 groups: 1) Normal diet group (ND group), fed standard chow; 2) high-fat diet group (HFD group), fed a high-fat diet; 3) high-fat diet + metformin treatment group (HFD+Met group), fed a high-fat diet for 8 weeks, followed by daily intragastric administration of metformin solution (150 mg/kg body weight) starting in week 9. At the end of the experiment, all rats were sacrificed, and serum, liver, and colonic contents were collected for assessment of glucose and lipid metabolism, liver pathology, gut microbiota composition, and the concentrations of short-/medium-chain fatty acids. RESULTS: Metformin significantly improved HFD-induced glucose and lipid metabolic disorders and liver injury. Compared with the HFD group, the HFD+Met group showed reduced abundance of Blautia, Romboutsia, Bilophila, and Bacteroides, while Lactobacillus abundance significantly increased (all P<0.05). Colonic contents of butyric acid, 2-methyl butyric acid, valeric acid, octanoic acid, and lauric acid were significantly elevated (all P<0.05), whereas acetic acid, isoheptanoic acid, and nonanoic acid levels were significantly decreased (all P<0.05). Spearman correlation analysis revealed that Lactobacillus abundance was negatively correlated with body weight gain and insulin resistance, while butyrate and valerate levels were negatively correlated with insulin resistance and liver injury (all P<0.05). CONCLUSIONS Metformin significantly increases the abundance of beneficial bacteria such as Lactobacillus and promotes the production of short-/medium-chain fatty acids including butyric, valeric, and lauric acid in the colonic contents of HFD rats, suggesting that metformin may regulate host metabolism through modulation of the gut microbiota.
Animals ; Metformin/pharmacology* ; Rats, Sprague-Dawley ; Diet, High-Fat/adverse effects* ; Rats ; Gastrointestinal Microbiome/drug effects* ; Male ; Fatty Acids, Volatile/metabolism* ; Fatty Acids/metabolism*

Objective:To explore the molecular mechanism by which interferon regulatory factor 1 (IRF1) affects hepatic ischemia-reperfusion injury (HIRI) by regulating the polarization of Kupffer cells.Methods:Twelve male healthy C57BL/6 wild-type mice weighing 20-25 g and aged 6-8 weeks were divided into a sham operation group ( n=6) and a HIRI group ( n=6); Twelve male healthy C57BL/6 IRF1 gene knockout (IRF1 -/-) mice weighing 20-25 g and aged 6-8 weeks were divided into a sham operation IRF1 -/- group ( n=6) and a HIRI IRF1 -/- group ( n=6). The levels of serum alanine transaminase (ALT) and aspartate transaminase (AST) in mice were measured, and hematoxylin-eosin (HE) staining of liver tissues was performed for Suzuki scoring to evaluate liver injury. Fluorescence quantitative polymerase chain reaction (qRT-PCR) was used to evaluate the mRNA levels of IRF1 and tumor necrosis factor α (TNFα) in liver tissues. Flow cytometry and qRT-PCR were used to detect the proportion and functional changes of M1/M2-type Kupffer cells in liver tissues. IRF1 was overexpressed or knocked down in the mononuclear macrophage cell line ANA1, and a co-culture and hypoxia-reoxygenation system with the hepatocyte cell line AML12 was established. Flow cytometry was used to detect the apoptosis of AML12 cells. Results:At 12 hours after hepatic ischemia-reperfusion in wild-type mice, the liver tissue injury was the most severe. Compared with the sham operation group, the levels of serum ALT [(8 073±83) U/L vs. (81±19) U/L, q=13.59] and AST [(11 170±2 890) U/L vs. (412±210) U/L, q=13.77] in the HIRI group were significantly higher, and the differences were statistically significant (both P<0.001). The Suzuki score reached 5-6 points. At 12 hours after hepatic ischemia-reperfusion in IRF1 gene knockout mice, the liver tissue injury was not obvious. There were no significant differences in the levels of serum ALT [668 (514, 2 344) U/L vs. 254 (147, 285) U/L, q=2.52, P=0.348] and AST [1 936 (1 262, 2 003) U/L vs. 628 (423, 759) U/L, q=1.22, P=0.824] between the HIRI IRF1 -/- group and the sham operation IRF1 -/- group. Compared with the HIRI group, the ratio of M1/M2-type Kupffer cells in the liver of the HIRI IRF1 -/- group decreased [(0.958±0.090) vs. (2.788±0.258), q=2.06, P<0.0001], and the mRNA expression of TNFα decreased [(4.363±0.393) vs. (12.900±5.504), q=5.59, P=0.018], and the differences between the two groups were statistically significant. In the co-culture and hypoxia-reoxygenation experiment using ANA1 cells overexpressing IRF1 and AML12 cells, the proportion of AML12 hepatocytes in late apoptosis was higher than that in the control group [(14.05±4.25) vs. (3.15±1.16), t=2.85, P=0.047], and the difference was statistically significant. In contrast, when the expression of IRF1 was knocked down, the proportion of apoptotic AML12 cells decreased [(9.26±3.04) vs. (13.36±4.64), t=2.15, P=0.098], but the difference was not statistically significant. Conclusion:The IRF1 protein can regulate the polarization of Kupffer cells into M1-type macrophages, promote the inflammatory injury of the liver tissue after ischemia-reperfusion, and increase the apoptosis of hepatocytes.

Background With the progression of industrialization, an increasing number of emerging contaminants are entering aquatic environments, posing significant threats to the safety of drinking water. Therefore, establishing a system for identifying unknown hazardous factors and implementing safety warning mechanisms for drinking water is of paramount importance. Among these efforts, non-target screening plays a critical role, but its effectiveness is largely constrained by the scope of coverage of sample pre-treatment methods. Objective To integrate modern chromatography/mass spectrometry techniques with advanced data mining methods to develop a non-discriminatory sample pre-treatment method for comprehensive enrichment of unknown contaminants in drinking water, laying a technical foundation for the discovery and identification of unknown organic hazardous factors in drinking water. Methods A non-discriminatory pre-treatment method based on supramolecular and solid-phase extraction was developed. The final target compounds including 333 pesticides, 194 pharmaceuticals and personal care products (PPCPs), and 59 per- and polyfluoroalkyl substances (PFASs) were used for optimizing the pre-treatment method, confirming its coverage. The impacts of different eluents on the absolute recovery rates of target compounds were compared to select the conditions with the highest recovery for sample pre-treatment. The effects of different supramolecular solvents and salt concentrations on target compound recovery were also evaluated to determine the most suitable solvent and salt concentration. Results The solid-phase extraction elution solvents, supramolecular extraction solvents, and salt concentrations were optimized based on the target compound recovery rates. The optimal recovery conditions were achieved using 2 mL methanol, 2 mL methanol (containing 1% formic acid), 2 mL ethyl acetate, 2 mL dichloromethane, hexanediol supramolecular solvent, and 426 mg salt. The detection method developed based on these conditions showed a good linear relationship for all target compounds in the range of 0.1-100.0 ng·mL⁻¹, with R² > 0.99. The method’s limit of detection ranged from 0.01 ng⁻¹ to 0.95 ng⁻¹, and 95% of target compounds were recovered in the range of 20%-120%, with relative standard deviation (RSD) less than 30%, indicating good precision. Conclusion The combined pre-treatment method of solid-phase extraction and supramolecular solvent extraction can effectively enrich contaminants in drinking water across low, medium, and high polarities, enabling broad-spectrum enrichment of diverse trace contaminants in drinking water. It provides technical support for broad-spectrum, high-throughput screening and identification of organic pollutants in drinking water, and also serves as a reference for establishing urban drinking water public safety warning systems.

As the prevalence of chronic diseases increases among occupational populations in China, the focus of occupational health management has shifted from ″occupational disease prevention and control″ to ″occupational disease and chronic disease prevention and control″. At present, occupational medical examinations (OME) are mainly focused on occupational disease prevention and control, and generally lack of chronic disease indicators such as blood lipids and blood glucose, limiting the role of OME in life-cycle health management of workers. To address this gap, it is necessary to incorporate chronic disease screening indicators into OME. Integrating OME and chronic disease screening faces bottlenecks, including concerns about increased operating costs in small- and medium-sized enterprises, and the risk of employment discrimination caused by the leakage of employee health privacy. A tiered strategy is recommended. Incorporating low-cost indicators such as blood lipids, waist circumference into routine examinations, and customizing advanced screening for elder or high-risk position workers. The prioritization of screening indicators can be determined by expert consultation and employer-employee discussions. Meanwhile, the results of chronic disease screening indicators should not be included in occupational health surveillance records to protect workers′ privacy. In summary, expanding OME to cover more chronic disease indicators provides valuable economic and social benefits. In the long run, common chronic disease screening indicators should be included in the regular medical examination indicators of OME, thereby reducing the burden of chronic diseases on occupational populations and promoting the health management of occupational populations.

Objective: To compare quality control (relative purity and specific activity) and process control [plasminogen (Pg) antigen recovery and potency recovery] indexes of samples before and after adding the Q chromatography step to the full chromatography process of human Pg, thereby determining whether the addition of this step could improve Pg recovery by affinity chromatography. Methods: A Q chromatography step was added before the Pg affinity chromatography in the original Pg chromatography process. The loading solution, flow through solution and eluate of Q chromatography and Pg affinity chromatography were collected. The potency of coagulation factor Ⅱ (FⅡ), Ⅶ (FⅦ), Ⅷ (FⅧ), Ⅸ (FⅨ), and Ⅹ(FⅩ) were detected by the coagulation method, the total protein content was detected by the BCA method, and the Pg potency was detected by the chromogenic substrate method. The content of specific plasma proteins was detected by immunoturbidimetry, the potency recovery of coagulation factors was calculated, and the flow direction of coagulation factors was analyzed. The recovery of different plasma protein antigens were calculated, and the distribution of impurity proteins was analyzed. The relative purity and specific activity of Pg, antigen content, and potency recovery in the target fractions were calculated and compared with the original process indicators, so as to determine the effect of adding Q chromatography on the original process. Furthermore, the reproducibility after process modification was assessed. Results: 100% of FⅡ, FⅩ, and FⅨ, 87.81% of FⅧ, and 40.44% of FⅦ in filtered plasma were removed by Q chromatography. The residual FⅦ (53.26%) and FⅧ (13.30%) in Q flow-through fraction were completely removed by Pg affinity chromatography. In both the original process (without Q-chromatography) and the modified process (with Q-chromatography), non-target plasma proteins mainly existed in the flow-through fraction of Pg affinity chromatography. The antigen recovery of IgM, ceruloplasmin (CER), and fibronectin (FNC) in Q-chromatography flow-through fraction were reduced. In contrast, antigen recovery of other plasma proteins [IgG, IgA, Pg, albumin (AlB), alpha-1-antitrypsin (AAT), and fibrinogen (Fg)] were all >90%, which were consistent with the protein composition and proportion in the original affinity chromatography loading solution. Compared with the recovery rate of Pg antigen in the original process (74.4%), the total recovery of Pg antigen in the modified process was significantly increased (89.97%). Compared with the recovery of IgG (97.48%) and Fg (95.32%) in the Pg affinity flows-through fraction of the original process, the modified process resulted in a slight reduction in the recovery of IgG (94.60%), while the recovery of Fg was not affected (95.05%). The potency recovery rate, specific activity, and relative purity of Pg after Q chromatography were 99.3%, 0.016 U/mg, and 0.15%. These values were the same as those of Pg affinity chromatography loading solution by the original process, indicating that introduction of Q chromatography did not affect subsequent Pg affinity chromatography. Compared with the recovery of Pg antigen in three batches of the original process (66.49±1.02)%, the recovery of Pg antigen in the affinity chromatography eluent of the modified process [five batches; (77.43±4.43)%] was significantly improved. Furthermore, the potency recovery was (86.80±4.28)%, the relative purity was (81.99±1.25)%, the specific activity was (8.679±1.073)U/mg, and the process was reproducible. Conclusion: The addition of Q chromatography could improve the recovery of Pg affinity chromatography in the full chromatography process.