ObjectiveTo investigate the therapeutic mechanism of Xuefu Zhuyutang （XFZYT） for metabolic-associated fatty liver disease （MAFLD） through integrated network pharmacology and animal experiments. MethodsNetwork pharmacology was utilized to predict the core components， key therapeutic targets， and signaling pathways of XFZYT in the treatment of MAFLD. For animal experiments， a rat model of MAFLD was established by feeding a high-cholesterol diet for 4 weeks. Intervention was then administered with low-dose （2 g·kg^-1） and high-dose （4 g·kg^-1） XFZYT for 2 weeks. Biochemical assays were performed to measure the serum levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. In addition， the activities of superoxide dismutase （SOD） and catalase （CAT） and levels of malondialdehyde （MDA） and glutathione （GSH） in the serum were measured. The same way was adopted to measure the levels of TC and TG in the liver tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to quantify the serum levels of interleukin （IL）-6， IL-1β， and tumor necrosis factor-alpha （TNF-α）. Histopathological evaluations included hematoxylin and eosin （HE） staining for liver tissue morphology， Oil Red O staining for lipid deposition， and dihydroethidium （DHE） probe staining for reactive oxygen species （ROS） levels. Western blot analysis was conducted to assess the protein levels of AMP-activated protein kinase （AMPK）， phosphorylated （p）-AMPK， nuclear factor erythroid 2-related factor 2 （Nrf2）， heme oxygenase-1 （HO-1）， nuclear factor-kappa B （NF-κB）， and p-NF-κB in the liver tissue. Untargeted metabolomics analysis of the serum was performed by liquid chromatography-tandem mass spectrometry （LC-MS/MS）. ResultsNetwork pharmacology analysis predicted 155 potential targets of XFZYT for MAFLD treatment， with core targets including signal transducer and activator of transcription 3 （STAT3）， protein kinase B1 （Akt1）， TNF， and IL-6. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment primarily implicated the AMPK signaling pathway. Animal experiments demonstrated that compared with the normal group， the model group exhibited dyslipidemia， hepatic function impairment， pronounced hepatic lipid deposition， and inflammatory manifestations， with elevated serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， reduced HDL and GSH levels plus decreased SOD and CAT activities （P<0.05）， downregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and upregulated protein level of p-NF-κB （P<0.05） in the liver tissue. Compared with the model group， XFZYT intervention groups showed significant amelioration of dyslipidemia and hepatic function impairment， markedly reduced hepatic lipid deposition and inflammatory cell infiltration， decreased serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， increased HDL and GSH levels plus enhanced SOD and CAT activities （P<0.05）， upregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and downregulated protein level of p-NF-κB （P<0.05）. Serum metabolomics revealed 511 differentially expressed metabolites （231 upregulated and 280 downregulated） between normal and model groups， while XFZYT groups versus model group showed 94 differential metabolites （51 upregulated and 43 downregulated）. Among them， 11 metabolites displayed the most significant alterations， with enriched pathways including glycerolipid metabolism， cholesterol metabolism， and insulin resistance， multiple of which demonstrated AMPK association. ConclusionXFZYT alleviates MAFLD by regulating the AMPK signaling pathway and associated metabolic networks.

Over the past two decades, genome-wide association study(GWAS) has identified numerous genetic variants and loci associated with heritable diseases. With the gradual maturation and saturation of GWAS methodologies, transcriptome-wide association study(TWAS) offers a novel perspective by linkinggenetic phenotypes to gene expression levels. By integrating TWAS with other multi-omics analyses, researchers can gain a deeper understanding of heritable diseases. This article provides an overview of recent groundbreaking and representative TWAS methods and tools, analyzes their strengths and limitations, and discusses future trends in TWAS development.

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.

AIM:To analyze the influencing factors of postoperative malignant glaucoma(MG)in patients with primary angle-closure glaucoma(PACG)using logistic regression and decision tree models.METHODS:A retrospective study was conducted on PACG patients who underwent surgery at Eye Hospital of Handan City from March 2020 to March 2025. Patients were divided into two groups: the MG group, who developed MG within 6 mo postoperatively, and the non-MG group. Data were collected from the electronic medical record system. Univariate analysis was performed, followed by multivariate logistic regression to identify independent risk factors. A classification and regression tree model was constructed to visualize the hierarchical relationships among predictors. The predictive performance of the two models was evaluated and compared using receiver operating characteristic(ROC)curve analysis.RESULTS:Totally 182 cases(182 eyes)with PACG were enrolled in this study, including 91 cases(91 eyes)in the MG group and 91 cases(91 eyes)in the non-MG group. In the MG group, there were 53 males and 38 females; 69 cases were aged ≥60 y and 22 cases were aged <60 y. In the non-MG group, there were 47 males and 44 females; 33 cases were aged ≥60 y and 58 cases were aged <60 y. The non-MG group comprised 91 patients, including 47 males and 44 females. Among them, 33 cases were aged ≥60 y, and 58 cases were aged<60 y. The MG group had significantly higher proportions of patients aged ≥60 y, diabetes, moderate-stage PACG, persistent high intraocular pressure(IOP), complete anterior chamber angle closure, lens thickness <4.5 mm, axial length <22 mm, and severe postoperative inflammation compared to the non-MG group(all P<0.01). Multivariate Logistic regression identified the following as independent influencing factors for postoperative MG: age [OR (95%CI)=2.136(1.401-3.255)], PACG stage [OR (95%CI)=2.996(2.044-4.391)], IOP [OR (95%CI)=3.527(1.604-7.755)],anterior chamber angle [OR (95%CI)=4.826(2.498-9.324)], axial length [OR (95%CI)=5.125(1.265-20.771)], and severe postoperative inflammation [OR (95%CI)=2.338(1.478-3.699)](all P<0.05). The decision tree model selected six explanatory variables: age, PACG stage, IOP, anterior chamber angle status, axial length, and severe postoperative inflammation. Axial length was the primary splitting factor at the root node. The areas under the ROC curve(AUC)for the logistic regression and decision tree models were 0.913(0.863-0.950)and 0.921(0.872-0.956), respectively, with no significant difference between them(Z=0.561, P=0.575).CONCLUSION:Both the logistic regression and decision tree models effectively identify key influencing factors for postoperative MG in PACG patients, including age, PACG stage, IOP, anterior chamber angle status, axial length, and severe postoperative inflammation. The decision tree model offers an intuitive, visual representation of risk stratification, facilitating clinical decision-making. Both models are applicable for clinical risk assessment.

Objective:To assess the effect of joint exposure to multiple air pollutants on sleep structure in patients with stable chronic obstructive pulmonary disease (COPD), identify key air pollutants, and analyze potential influencing factors.Methods:In this panel study, 92 stable COPD patients were recruited. From March 2021 to September 2023 in Beijing, all participants completed 254 nights of sleep monitoring. The total sleep duration, light sleep duration, deep sleep duration and rapid eye movement sleep duration and their respective proportions in total sleep duration were recorded. The exposure levels of fine particulate matter (PM 2.5), inhalable particulate matter (PM 10), nitrogen dioxide (NO 2), ozone (O 3), sulfur dioxide (SO 2), and carbon monoxide (CO) were estimated based on the infiltration factor method and time-activity logs of participants. To assess the lag effect of air pollutants, moving average concentrations of air pollutants from 0-1 day to 0-3 months were calculated. The linear mixed-effect model and Bayesian kernel machine regression (BKMR) model were used to assess the single and joint effects of air pollutants on sleep structure parameters in COPD patients, respectively. Results:All six types of air pollutants were associated with changes in sleep structure, manifesting as an increase in total sleep duration and light sleep proportion and a reduction in deep sleep proportion. The effects of O 3 were strongest at lag 0-6 days, while other air pollutants were at lag 0-3 months. Joint exposure to multiple air pollutants exerted significant joint effects on sleep structure, and NO 2 was identified as the dominant pollutant. NO 2 had a posterior inclusion probability (PIP) greater than 0.5 for light sleep proportion (PIP=0.691) and deep sleep proportion (PIP=0.957). With an interquartile range (IQR) increase of 8.6 μg/m 3 in NO 2 at lag 0-3 months, the light sleep proportion increased by 10.5% (95% CI: 2.2%-19.4%), and the deep sleep proportion decreased by 19.5% (95% CI:-30.6%- -6.8%). Conclusion:Joint exposure to air pollutants is associated with changes in sleep structure in stable COPD patients, and NO 2 may be a key pollutant.

Ehlers-Danlos syndromes(EDS)are a group of rare hereditary connective tissue disorders characterized by joint hypermobility,skin hyperextensibility,and tissue fragility.Short stature is defined as a height that is two standard deviations or more below the average height for individuals of the same age,sex,and race.The etiopathogenesis of short stature is complicated.Early detection and appropriate intervention are essential in disease treatment.However,short stature is not common among all EDS subtypes.It is frequently observed in patients with rare subtypes,such as spondylodysplastic EDS,dermatosparaxis EDS,and musculo-contractural EDS.Besides,height may be affected by other factors including spinal curvature and malnutrition.Deep phenotyping and multidisciplinary team approaches are recommended for the diagnosis and management.Short stature in patients with EDS has not been sufficiently acknowledged in China.There is currently a lack of high-level evidence for the treatment of EDS-related short stature.Therefore,this review aims to present recent progress of diagnosis and management of short stature in patients with EDS.Further studies focusing on short stature in rare subtypes are necessary to advance precision medicine and enhance patient care.