ObjectiveTo explore the possible mechanisms by which ligustilide （LIG） exerts neuroprotective effects on ischemic stroke （IS） by inhibiting the release of neutrophil extracellular traps （NETs）， promoting blood-brain barrier repair， and alleviating post-ischemic neuroinflammation， thereby providing a new direction for IS treatment. MethodsA middle cerebral artery occlusion （MCAO） model was established in rats. The rats were divided into the sham operation （Sham） group， model （Model） group， low- and high-dose LIG groups （20， 40 mg·kg^-1）， and the NET inhibitor CI-amidine group （CI-amidine， 10 mg·kg^-1）. Drug treatments were administered for 3 days. Neurological injury after ischemia was evaluated by 2，3，5-triphenyltetrazolium chloride （TTC） staining， neurological deficit scoring， and brain index measurement. Flow cytometry and Western blot were used to analyze changes in neutrophil expression. Immunofluorescence was used to observe the fluorescence intensity of the NET marker citrullinated histone H3 （H3Cit）. Western blot was performed to detect the expression of blood-brain barrier tight junction-related proteins and inflammatory factors， including interleukin-18 （IL-18） and interleukin-1β （IL-1β）. ResultsCompared with the Sham group， the Model group exhibited significant brain tissue injury （P<0.05）， significantly increased neutrophil numbers and NET expression （P<0.05）， significantly impaired blood-brain barrier permeability （P<0.05）， and significantly increased expression of inflammatory factors （P<0.05）. Compared with the Model group， both low- and high-dose LIG significantly alleviated brain tissue injury in rats （P<0.01）， inhibited neutrophil numbers and NET expression （P<0.01）， reduced blood-brain barrier damage （P<0.01）， and suppressed the expression of inflammatory factors IL-18 and IL-1β （P<0.01）， thereby ultimately exerting a neuroprotective effect. ConclusionThe neuroprotective effect of LIG in rats with cerebral ischemia-reperfusion injury may be related to inhibition of neutrophils and the NETs induced by them.

Background With China's socio-economic development, the dietary structure of Chinese residents has gradually shifted from a traditional Eastern pattern characterized by high carbohydrate intake to a relatively high-fat Western dietary model, alongside a growing burden of chronic diseases. However, dietary changes may vary across different occupational groups. Objective To analyze the long-term trends in dietary energy and three major macronutrient intake among various occupational groups aged 18-59 years in nine provinces of China from 1989 to 2018, providing a scientific basis for developing occupation-specific dietary intervention strategies. Methods Based on 11 waves of data (1989–2018) from the China Health and Nutrition Survey (CHNS), 57458 employed individuals aged 18-59 years were selected as observation subjects after applying inclusion and exclusion criteria. Joinpoint regression was used to analyze temporal trends by calculating the annual percentage change (APC) and average annual percentage change (AAPC) with 95% confidence intervals. The analysis covered the energy supply ratio from the three major macronutrients and the proportion of the participants within the acceptable macronutrient distribution ranges (AMDR) for the total occupational population and specific occupational group. Results From 1989 to 2018, the dietary structure of the occupational population in the nine provinces gradually Westernized. The carbohydrate energy supply ratio showed a decreasing trend (AAPC=−0.77%, 95%CI: −1.00%, −0.55%, P<0.05), while the fat energy supply ratio increased (AAPC=1.42%, 95%CI: 1.07%, 1.77%, P<0.05). The protein energy supply ratio remained largely unchanged (AAPC=−0.19%, 95%CI: −0.08%, 0.46%, P>0.05), and the total energy intake declined (AAPC=−0.62%, 95%CI: −0.94%, −0.30%, P<0.05). Among the occupational groups studied, white-collar workers were the first to show characteristics of dietary Westernization. Using the AMDR as the criterion, their average fat energy supply ratio first exceeded the AMDR upper limit (30%) in 1993, and their average carbohydrate energy supply ratio first fell below the AMDR lower limit (50%) in 2006, both time points being earlier than other occupational groups. Agricultural workers lagged in this transition (their average fat energy supply ratio first reached ≥30% in 2011), but their rate of increase in the fat energy supply ratio was the fastest among all occupational groups (AAPC=1.59%, 95%CI: 0.90%, 2.30%, P<0.05; P for trend comparison between groups<0.05). The other three occupational groups (blue-collar workers, service workers, and others) generally fell between these two extremes. Taking the fat energy supply ratio as an example, their AAPCs of increase were 1.02% (95%CI: 0.73%, 1.32%, P<0.05) for blue-collar workers, 0.85% (95%CI: 0.61%, 1.09%, P<0.05) for service workers, and 0.88% (95%CI: 0.58%, 1.17%, P<0.05) for others. Conclusion From 1989 to 2018, the macronutrient structure of the occupational population aged 18-59 years in nine China provinces is gradually Westernized. The energy supply ratios of carbohydrates and proteins primarily face issues of potential inadequacy, while the fat energy supply ratio is excessively high. Furthermore, the patterns of change vary among different occupational groups. It is recommended to propose personalized dietary advice tailored to specific occupations.

Background With China's socioeconomic development, significant lifestyle changes have occurred among occupational groups, leading to alterations in cardiovascular metabolic risk factors. However, few studies have examined the secular trends of these risk factors in China's working population. Objective To analyze the trends in cardiovascular metabolic risk factors among the occupational population in nine provinces of China from 2009 to 2018, and to explore the associations between different occupational types and these risk factors, along with their clustering patterns, thereby providing evidence for targeted interventions. Methods This study utilized data from the China Health and Nutrition Survey (CHNS) in 2009, 2015, and 2018. The dataset covered 13274 employed individuals aged 18-59 years. Only participants with complete blood test results and physical measurement data were included in the final analysis. The average annual percentage change (AAPC) in the positive rates of risk factors was calculated using Joinpoint regression to analyze temporal trends. Multinomial logistic regression and binary logistic regression models were employed to examine the cross-sectional associations between occupational types (categorized as white-collar workers, agricultural workers, blue-collar workers, service workers, and others) and nine cardiovascular metabolic risk factors and their clustering (defined as having ≥2 risk factors) in 2018. Results A total of 8451 participants were included. From 2009 to 2018, significant increasing trends (AAPC>0, P<0.05) were observed for overweight, obesity, central obesity, borderline elevated triglycerides (TG), borderline elevated to elevated total cholesterol (TC), borderline elevated low-density lipoprotein cholesterol (LDL-C), elevated blood pressure and hypertension, diabetes. The most rapid increases were found for obesity (AAPC=6.07%, 95%CI: 3.42%, 8.88%), hypertension (AAPC=4.10%, 95%CI: 0.62%, 7.77%), and central obesity (AAPC=3.27%, 95%CI: 1.24%, 5.36%). The clustering rate of risk factors increased from 62.3% in 2009 to 73.2% in 2018 (AAPC=1.87%, 95%CI: 1.02%, 2.73%). The cross-sectional analysis in 2018, after adjusting for confounders, showed that compared with white-collar workers, blue-collar workers had a significantly lower risk of overweight (OR=0.67, 95%CI: 0.48, 0.95), central obesity (OR=0.65, 95%CI: 0.45, 0.92), and borderline high TG (OR=0.54, 95%CI: 0.35, 0.82). In contrast, agricultural workers had a higher risk of hypertension (OR=1.76, 95%CI: 1.14, 2.72). Conclusion Between 2009 and 2015, the burden of most cardiometabolic risk factors increases significantly among the Chinese occupational population, with the rate of increase slowing by 2018. Risks vary across occupational types, among which blue- collar workers report lower target outcomes. Targeted interventions focusing on the rapidly increasing risk factors and high-risk occupational groups are recommended.

Background The global prevalence of obesity is on the rise and is closely associated with various chronic non-communicable diseases such as cardiovascular diseases and diabetes. There is a relative lack of long-term dynamic studies on compound obesity among occupational populations. Objective To explore the changing trends of compound obesity among different occupational groups aged 18–59 years in nine provinces (autonomous regions, municipalities) of China from 1993 to 2018, and to provide a scientific basis for formulating targeted weight management strategies for occupational populations. Methods A total of 34519 employed adults aged 18–59 years from nine waves of the China Health and Nutrition Survey in1993, 1997, 2000, 2004, 2006, 2009, 2011, 2015, and 2018 were included. Obesity types were determined according to the Chinese Adult Weight Management Guidelines. The Joinpoint regression model was used to calculate the average annual percentage change (AAPC) and annual percentage change (APC) of compound obesity rates. Results From 1993 to 2018, the age-standardized compound obesity rate among the occupational population aged 18–59 years showed an upward trend (AAPC=6.24%, 95%CI: 5.09%, 7.41%, P<0.05). The AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, other occupational groups, service workers, and white-collar workers were 9.55% (7.51%, 11.64%), 6.18% (4.70%, 7.69%), 5.53% (2.27%, 8.90%), 4.07% (2.40%, 5.77%), and 3.89% (2.16%, 5.65%), respectively, with statistically significant differences (P<0.05). Among males, the AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, other occupational groups, service workers, and white-collar workers were 11.52% (7.71%, 15.47%), 7.28% (6.18%, 8.40%), 5.92% (2.28%, 9.69%), 5.56% (2.11%, 9.12%), and 4.22% (2.33%, 6.15%), respectively, with statistically significant differences (P<0.05). Among females, the AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, and white-collar workers were 7.45% (6.22%, 8.69%), 3.72% (0.84%, 6.67%), and 2.41% (0.17%, 4.70%), respectively, with statistically significant differences (P<0.05). A turning point was observed in the compound obesity rate among female white-collar workers in 2006, with an APC (95%CI) of 9.69% (5.24%, 14.33%) from 2006 to 2008, showing a statistically significant difference (P<0.05), while no significant trend was found from 1993 to 2006 (P>0.05). No significant trends were observed in the age-standardized compound obesity rates among females in other occupational groups and service workers (P>0.05). Conclusion The compound obesity rate among China's occupational population is increasing rapidly, with the growth rate among agricultural workers being particularly prominent. In 2018, male white-collar workers and female agricultural workers exhibit relatively high compound obesity rates, warranting focused attention. Although the overall growth rate among service workers is slower, the expanding workforce in this sector indicates that obesity remains a serious issue. Targeted occupational health and weight management interventions are needed in the future.

Background With rising obesity rates and earlier hypertension onset among occupational populations, there is an urgent need to elucidate the long-term cardiovascular impacts of dynamic body weight patterns. Current evidence lacks trajectory modeling studies examining occupation-specific prevention strategies. Objective To investigate the association between long-term body mass index (BMI) trajectories and incident hypertension risk in Chinese working adults, and to examine occupation-specific heterogeneity in this relationship. Methods A dynamic sub-cohort of 4 413 occupational participants was constructed from ten survey waves (1991–2018) of the China Health and Nutrition Survey (CHNS). Eligible individuals had valid key BMI records at three or more independent follow-ups before the outcome event; the individual baseline was set as the year of their first participation in the survey. Group-based trajectory modeling (GBTM) was used to identify BMI change patterns. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% confidence interval (CI) for hypertension incidence across trajectory groups, with stratified analysis by occupational categories. Results Among 4413 occupational participants, 1441 incident hypertension cases were reported during the follow-up window. Three long-term BMI trajectories were identified: low-stable, moderate-slowly rising, and high-rising. In Model 3 with all selected confounders adjusted, compared with the low-stable group, the moderate-slowly rising group showed a significantly higher risk of incident hypertension (HR=1.28, 95%CI: 1.12, 1.45; P < 0.001), as did the high-increasing group (HR=1.80, 95%CI: 1.45, 2.23; P < 0.001). The stratified analyses revealed occupational differences in the association. Among agricultural workers, the moderate-slowly rising group (HR=1.35, 95%CI: 1.15, 1.57) and the high-rising group (HR=2.00, 95%CI: 1.50, 2.66) both exhibited significantly increased risks of hypertension (P<0.001). Conversely, among white-collar workers, an increased risk of hypertension was observed only in the high-rising group (HR=1.97, 95%CI: 1.23, 3.17; P<0.05). Conclusion Rapid BMI escalation constitutes a significant risk factor for incident hypertension in occupational populations. Targeted long-term weight monitoring and tailored interventions are recommended for high-risk occupations.

Background Health literacy is closely related to mental health, and improving health literacy has been shown to promote mental well-being. However, whether occupational stress among workers in mining and manufacturing is associated with their occupational health literacy remains inconclusive. Objective To study the levels of occupational health literacy and occupational stress among workers in three industrial sectors (metal ores mining, metal smelting, and manufacture of non-metallic mineral products) in Gansu Province, and to analyze the correlation between them. Methods Between May and December 2024, a stratified cluster random sampling method was employed to survey workers from 73 large, medium, and small and micro sized enterprises across the aforementioned industries in Gansu Province. Participants’ occupational health literacy and occupational stress levels were assessed. The LASSO regression model was applied to identifykey factors influencing occupational stress, and subsequently a multilevel random intercept mixed-effects logistic model was used to study factors influencing occupational stress and to explore the relationship between occupational health literacy and occupational stress. Results A total of 3611 workers across the three industries were surveyed, among whom 1031 (28.55%) experienced occupational stress. Workers with adequate occupational health literacy—whether assessed in terms of overall literacy or specific dimensions—demonstrated a significantly lower prevalence of occupational stress compared to those without adequate literacy (P<0.05). Through the LASSO regression analysis, it was found that the factors closely related to occupational stress were dimension one (occupational health legal knowledge), dimension two (basic knowledge of occupational health protection), and dimension four (healthy working methods and behaviors) of occupational health literacy, gender, average monthly income, and night shifts. The results from the three-level random intercept mixed-effects logistic regression model indicated that dimensions one (OR=0.69, 95%CI: 0.58, 0.82), two (OR=0.71, 95%CI: 0.58, 0.87), and four (OR=0.81, 95%CI: 0.67, 0.98) of occupational health literacy were negatively correlated with the risk of occupational stress. Workers with an average monthly income of 3001–≤5000, 5001–≤7000, and ≥7001 yuan reported occupational stress risks that were 61% (OR=0.61, 95%CI: 0.45, 0.81), 56% (OR=0.56, 95%CI: 0.41, 0.78), and 36% (OR=0.36, 95%CI: 0.24, 0.53) of those with an average monthly income ≤3000 yuan, respectively. Male workers (OR=1.66, 95%CI: 1.32, 2.10) and those on night shifts (OR=2.29, 95%CI: 1.90, 2.76) had a higher risk of occupational stress. The random effects variance showed that the intraclass correlation coefficient was 0.12. Conclusion There is a negative correlation between occupational stress and occupational health literacy among workers in mining and manufacturing. Being male, having a low income, and working night shifts are risk factors affecting workers' occupational stress. It is recommended to focus on these groups of workers and incorporate occupational health literacy into workplace mental health promotion.

Background Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen for both human bloodstream infections and mastitis in cows. However, little attention has been paid to the cross-host transmission of MRSA from cows to high-risk groups in China. Objective To determine the MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang, identify the antibiotic resistance profiles and molecular characteristics of the isolates, and provide scientific evidence for the formulation of targeted infection control strategies. Method A cross-sectional survey combined with laboratory pathogen analysis was conducted. From June to August 2024, large-scale dairy farms in Xinjiang region were selected as study sites. Nasal swabs (n=96) and skin swabs (n=39) were collected from workers, and bovine nasal swab samples (n=109) were collected simultaneously. All samples were subjected to MRSA isolation, cultivation, and identification, followed by antibiotic susceptibility testing to characterize resistance phenotypes. Staphylococcus aureus protein A (Spa) typing was performed to determine strain genotypes and elucidate MRSA colonization rates and molecular epidemiological patterns. Results A total of 35 MRSA strains was successfully isolated from 244 samples. The MRSA colonization rates among dairy farm workers and dairy cows were 20.83% (20/96) and 12.84% (14/109), respectively, with an overall isolation rate of 14.34% (35/244). Among the workers, the nasal colonization rate was 16.67% (16/96), and the skin colonization rate was 12.82% (5/39). One worker exhibited MRSA colonization at multiple body sites. All MRSA strains were resistant to cefoxitin (100%, 35/35). The resistance rates to erythromycin and clindamycin were 42.86% (15/35) and 34.29% (12/35), respectively. Thirteen strains showed a multidrug-resistant phenotype, whereas all strains were susceptible to vancomycin. The MRSA isolates exhibited high genetic diversity, with 13 Spa types identified, among which t441 was the most prevalent (8 strains). Both t441 and t034 types were detected in samples from both the dairy cows and their handlers. These two Spa types also carried and stably inherited specific resistance combinations, including erythromycin–clindamycin–cefoxitin and ciprofloxacin–erythromycin–clindamycin–gentamicin–cefoxitin–tetracycline, and a statistically significant association was also observed between the two resistance profiles and the bacterial types (P < 0.001). In addition, one novel Spa type strain was identified. Conclusion MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang are relatively high, with evidence of multi-site colonization. The isolates exhibit high levels of multidrug resistance and genetic diversity, indicating a potential risk of cross-host transmission.

Background Occupational groups are facing a "dual health threat". Research indicates that enhancing the occupational health literacy (OHL) of workers is crucial for safeguarding their health and well-being. However, at present, the research on OHL in China is still in its infancy and there is an urgent need to carry out systematic studies. Objective To analyze the OHL level and influencing factors of key industry groups in Huangshan City, and to provide a basis for targeted intervention activities. Methods From 2022 to 2023, a stratified cluster random sampling method was used to select 621 frontline workers from 20 companies in four industries: non-metallic mineral mining and dressing, textile and apparel, rubber and plastic products, and non-metallic mineral products in Huangshan City. The participants were asked to anonymously complete the National Key Population Occupational Health Literacy Monitoring Survey Personal Questionnaire. The overall and 4 dimension levels of OHL were calculated according to the "2022 Calculation Standards for Occupational Health Literacy Levels of Key Populations". The OHL level was defined as the proportion of the target population possessing adequate OHL (indicated by an overall or dimension-specific score rate ≥80% on the questionnaire). Results A total of 621 workers were surveyed during the study period, with 597 valid questionnaires collected, resulting in an effective rate of 96.14%. The participants were mainly frontline workers in small enterprises, presenting the pattern of "three lows and one long". The male-to-female ratio was 1.16∶1. The overall OHL level of the participants was 45.06% during the study period. The dimension-specific levels of occupational health legal knowledge, basic knowledge, basic skills, and healthy working methods and behaviors were 50.25%, 73.53%, 30.49%, and 60.13%, respectively. There were statistically significant differences in the overall OHL level and the four dimension-specific levels among workers across different industries (P<0.05), with the lowest overall OHL level in the textile and apparel industry (32.06%). The results of logistic regression analysis showed that compared with those with a monthly income of less than 3000 yuan, those with a monthly income of 3000 to 4999 yuan, 7000 to 8999 yuan, and ≥9000 yuan had higher OHL levels (OR=4.152, 3.796, 5.382); compared with those working 40 h or less per week, those working 49 to 54 h had lower OHL level (OR=0.491); compared with those with less than 5 years of work experience, those with 5 to 9 years of work experience had higher OHL levels (OR=1.770); compared with workers in the non-metallic mineral products industry, workers in the non-metallic mineral mining and dressing industry and the rubber and plastic products industry had higher OHL levels (OR=3.790, 2.511) (P<0.05). Conclusion The OHL levels of workers in the four key industries of the secondary industry in Huangshan City are generally low and develop unevenly. We should focus on strengthening the occupational health intervention for frontline workers in the textile, clothing and apparel and frontline workers with low incomes, long working hours, and more than 15 years of service, and emphasize the training of practical application of theoretical knowledge to improve the OHL level of workers in all aspects.

Uveal melanoma(UM)is the most common primary intraocular malignancy in adults and arises predominantly from the choroid. Mitochondria, as essential organelles, not only fuel energy metabolism, but also orchestrate signal transduction and apoptosis. Recent studies have progressively uncovered the multifaceted roles of mitochondria in UM, including mitochondrial DNA copy-number alterations, reprogramming of mitochondria-related metabolic genes, and mitochondria-dependent autophagy. Moreover, mitochondria modulate UM progression partly through the PI3K/AKT axis. Natural compounds and small-molecule drugs that impair mitochondrial function have also shown promising activity in inducing UM cell dysfunction. These findings provide new insights into UM pathogenesis and highlight mitochondria as potential therapeutic targets.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.