ObjectiveTo investigate microbial contamination status and distribution characteristics in laboratory animal barrier facilities, so as to provide a scientific basis for environmental quality control in barrier facilities. MethodsIn accordance with the national standard "Laboratory Animals—Environment and Housing Facilities" and the "Standard Operating Procedures" of the barrier facility, bacterial monitoring was performed on samples of air-settling bacteria, materials, and personnel gloves in the single-corridor barrier facility of the Animal Core Facility, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences (CEMCS). The monitoring data from January 2020 to December 2024 were collected, organized and statistically analyzed, and partial samples were subjected to species identification using PCR and sequencing methods. ResultsA total of 7 898 samples were collected from 2020 to 2024, including 3 175 air-settling bacteria samples, 3 353 material samples, and 1 370 glove samples. The overall compliance rate was 95.7% (7 559/7 898), among which the compliance rate of air-settling bacteria was 97.1% (3 084/3 175), that of materials was 93.2% (3 125/3 353), and that of personnel gloves was 98.5% (1 350/1 370). Over the five years, the compliance rates of all three types of monitored samples were above 90%. There were statistically significant differences in the compliance rates of air-settling bacteria and material samples among different quarters (P<0.05). Further investigation was conducted on samples collected from January to March 2024, and 190 bacterial strains were obtained through isolation and culture, including 126 strains from air-settling bacteria, 52 strains from materials, and 12 strains from personnel gloves. The strains were identified by PCR amplification and sequencing, and the 190 bacterial strains belonged to 9 genera and 20 species. Gram-positive bacteria accounted for the majority, with Staphylococcus as the dominant genus, accounting for 77.9% (148/190). ConclusionMicroorganisms carried by air, materials, and personnel gloves in barrier facilities are mainly Gram-positive bacteria. Regular monitoring of air-settling bacteria, materials, and personnel gloves in barrier facilities enables timely detection and control of potential risks during husbandry management and facility operation, which is of great significance for maintaining the sound operation of the barrier facility system and ensuring the quality of animal experiments.

Metabolic associated fatty liver disease （MAFLD） is the main type of chronic liver disease in the world， with an increasingly higher incidence rate and a younger age of onset. At present， the treatment of MAFLD mainly depends on lifestyle intervention and comorbidity management， and there is still a lack of effective drugs for MAFLD itself. As a classic nonsteroidal anti-inflammatory drug of the salicylic acid family， aspirin can intervene in the pathological process of MAFLD by regulating lipid metabolism， relieving insulin resistance， reducing liver inflammation and oxidative stress response， exerting an anti-liver fibrosis effect， and inhibiting hepatocellular carcinoma， and therefore， it has the value of preventing disease onset， delaying disease progression， and reversing disease condition. This article systematically reviews the mechanism of action and safety of aspirin in the treatment of MAFLD， in order to provide more drug treatment options for MAFLD patients.

BACKGROUND:Rheumatoid arthritis is influenced by complex genetic and environmental factors.Although observational studies have found some correlation between plasma proteins and rheumatoid arthritis,the susceptibility to confounding and reverse causation makes it difficult to clarify whether these proteins are pathogenic factors of rheumatoid arthritis.OBJECTIVE:To explore the potential of plasma proteins as biomarkers and therapeutic targets in rheumatoid arthritis through Mendelian randomization analysis of plasma proteins in the onset and progression of rheumatoid arthritis.METHODS:A large-scale two-sample Mendelian randomization analysis was conducted to comprehensively assess the causal relationships between 1 553 circulating proteins and rheumatoid arthritis based on the Decode database(developed by Decode Genetics in Iceland,which contains genomic data from the Icelandic population),the MR-Base platform(developed by a team of researchers at the University of Oxford in the United Kingdom,specifically designed to provide genetic and phenotypic data for Mendelian randomization analyses),and the GWAS Catalog platform(developed by the European Institute of Bioinformatics,which provides data for genome wide association studies worldwide).The causal effects were estimated using the Wald ratio and inverse variance weighting methods,with Bonferroni correction applied to control for false positives caused by multiple testing.To ensure the robustness of the results,sensitivity analyses were performed to validate the positive causal relationship between circulating proteins and rheumatoid arthritis,and Bayesian colocalization and phenome scanning were used to exclude confounding effects and horizontal pleiotropy.Additionally,external validation was carried out using new plasma protein datasets to reduce the likelihood of false discoveries.Finally,small-molecule compounds associated with candidate proteins were identified using the Drug Signatures Database(DsigDB),and molecular docking was performed to predict the binding patterns and energies between proteins and compounds,identifying the most stable and likely binding molecules and mechanisms.RESULTS AND CONCLUSION:(1)Sensitivity analyses,including Bayesian colocalization and phenome scanning,identified four plasma proteins with reliable causal relationships with rheumatoid arthritis:FCRL3,IL6R,ICOSLG,and TNFAIP3.Their genetic effects were estimated as follows:FCRL3[odds ratio(OR)=1.12,95％confidence interval(CI):1.07-1.17],IL6R(OR=0.94,95％CI:0.91-0.96),ICOSLG(OR=2.42,95％CI:1.67-3.52),and TNFAIP3(OR=2.19,95％CI:1.88-2.56).Furthermore,molecular docking analysis revealed that the small-molecule compound benzo[a]pyrene exhibited favorable binding with these candidate proteins,suggesting its potential as a therapeutic agent for rheumatoid arthritis.(2)This study provides a comprehensive analysis of the genetic causal relationships of FCRL3,IL6R,ICOSLG,and TNFAIP3 in rheumatoid arthritis.These proteins not only serve as potential molecular biomarkers for rheumatoid arthritis risk screening and disease prevention,but also offer key candidate targets for further understanding the pathogenic mechanisms of rheumatoid arthritis and developing targeted therapies.Although the study is based on European populations,its findings offer important insights for biomedical research in China.By incorporating Mendelian randomization methods to analyze genetic causality,future research on rheumatoid arthritis in the Chinese population could provide more accurate causal inferences,offering theoretical support for localized risk assessment and treatment strategies.

BACKGROUND:Rheumatoid arthritis is influenced by complex genetic and environmental factors.Although observational studies have found some correlation between plasma proteins and rheumatoid arthritis,the susceptibility to confounding and reverse causation makes it difficult to clarify whether these proteins are pathogenic factors of rheumatoid arthritis.OBJECTIVE:To explore the potential of plasma proteins as biomarkers and therapeutic targets in rheumatoid arthritis through Mendelian randomization analysis of plasma proteins in the onset and progression of rheumatoid arthritis.METHODS:A large-scale two-sample Mendelian randomization analysis was conducted to comprehensively assess the causal relationships between 1 553 circulating proteins and rheumatoid arthritis based on the Decode database(developed by Decode Genetics in Iceland,which contains genomic data from the Icelandic population),the MR-Base platform(developed by a team of researchers at the University of Oxford in the United Kingdom,specifically designed to provide genetic and phenotypic data for Mendelian randomization analyses),and the GWAS Catalog platform(developed by the European Institute of Bioinformatics,which provides data for genome wide association studies worldwide).The causal effects were estimated using the Wald ratio and inverse variance weighting methods,with Bonferroni correction applied to control for false positives caused by multiple testing.To ensure the robustness of the results,sensitivity analyses were performed to validate the positive causal relationship between circulating proteins and rheumatoid arthritis,and Bayesian colocalization and phenome scanning were used to exclude confounding effects and horizontal pleiotropy.Additionally,external validation was carried out using new plasma protein datasets to reduce the likelihood of false discoveries.Finally,small-molecule compounds associated with candidate proteins were identified using the Drug Signatures Database(DsigDB),and molecular docking was performed to predict the binding patterns and energies between proteins and compounds,identifying the most stable and likely binding molecules and mechanisms.RESULTS AND CONCLUSION:(1)Sensitivity analyses,including Bayesian colocalization and phenome scanning,identified four plasma proteins with reliable causal relationships with rheumatoid arthritis:FCRL3,IL6R,ICOSLG,and TNFAIP3.Their genetic effects were estimated as follows:FCRL3[odds ratio(OR)=1.12,95％confidence interval(CI):1.07-1.17],IL6R(OR=0.94,95％CI:0.91-0.96),ICOSLG(OR=2.42,95％CI:1.67-3.52),and TNFAIP3(OR=2.19,95％CI:1.88-2.56).Furthermore,molecular docking analysis revealed that the small-molecule compound benzo[a]pyrene exhibited favorable binding with these candidate proteins,suggesting its potential as a therapeutic agent for rheumatoid arthritis.(2)This study provides a comprehensive analysis of the genetic causal relationships of FCRL3,IL6R,ICOSLG,and TNFAIP3 in rheumatoid arthritis.These proteins not only serve as potential molecular biomarkers for rheumatoid arthritis risk screening and disease prevention,but also offer key candidate targets for further understanding the pathogenic mechanisms of rheumatoid arthritis and developing targeted therapies.Although the study is based on European populations,its findings offer important insights for biomedical research in China.By incorporating Mendelian randomization methods to analyze genetic causality,future research on rheumatoid arthritis in the Chinese population could provide more accurate causal inferences,offering theoretical support for localized risk assessment and treatment strategies.

Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Hepatocellular carcinoma (HCC) imposes a major health and economic burden worldwide, with disproportionate effects in low- and middle-income countries (LMICs). Surveillance in high-risk populations, typically using semiannual ultrasound and alpha-fetoprotein testing, has been shown to be cost-effective by enabling earlier detection and improving survival. Yet, its overall value is reduced by poor adherence and the limited sensitivity of ultrasound, particularly in patients with metabolic-associated steatotic liver disease. Emerging approaches—including abbreviated magnetic resonance imaging, multi-biomarker models (e.g., gender, age, AFP, AFP-L3, and DCP), and liquid biopsy assays such as methylated DNA markers—demonstrate greater diagnostic accuracy and potential economic advantages compared with conventional methods. Integration of artificial intelligence into imaging may further enhance efficiency and reduce downstream costs. Moving toward precision surveillance, guided by individualized risk stratification that incorporates etiology, fibrosis stage, and molecular profiles, can optimize allocation of resources and maximize cost-effectiveness at the population level. Interventions to improve adherence, including mailed outreach and behavioral economic incentives, have shown both clinical benefit and cost savings, underscoring the role of implementation science. Because socioeconomic disparities influence both access and outcomes, economic models must explicitly address equity to achieve sustainable impact. Future research should prioritize prospective trials that evaluate not only clinical performance but also the real-world cost-effectiveness of novel technologies and stratified surveillance strategies. For LMICs, adapting proven models into affordable, context-appropriate programs is essential. By combining prevention, precision risk assessment, innovative technologies, and equitable implementation, HCC surveillance can deliver both clinical and economic value, reducing the global burden of disease.

Cavernous transformation of the portal vein （CTPV） is a significant challenge in clinical practice. In recent years， transjugular intrahepatic portosystemic shunt has gradually been applied in the treatment of CTPV patients， but it had a technical success rate and a relatively high surgical risk. The scholars have adopted various modified techniques of portosystemic shunt to improve success rate and safety. However， for CTPV patients with extensive occlusion of the main portal vein， this surgery remains difficult， and individualized strategies for portosystemic shunt should be formulated. This article reports a case of CTPV treated by transjugular extrahepatic portosystemic shunt assisted by endoscopic ultrasound-guided portal vein localization， in order to explore a new pathway for the clinical management of patients with CTPV.

AIM:To investigate the current status of astigmatism and its associated factors among children and adolescents from kindergarten through senior high school in Yangpu District, Shanghai, and to provide scientific evidence for the prevention and control of refractive errors.METHODS:A cluster sampling method was employed. From September to November 2024, students from 14 randomly selected schools in Yangpu District, Shanghai, were enrolled as study subjects. Autorefraction and ocular biometry were performed under non-cycloplegic conditions, and questionnaire surveys were administered. Comparisons of astigmatism degree, detection rate, and axis were made across age groups, educational stages, and sexes. Multiple linear and logistic regression analyses were conducted to identify factors associated with astigmatism.RESULTS:A total of 7 233 students aged 4-18 y were enrolled including 3 731 males, 3 502 females, with the mean age 10.13±4.18 y, astigmatism -0.76±0.82 D, and the detection rate(≤-1.00 D)was 29.23%. Both the degree and detection rate of astigmatism were correlated with age and educational stage, peaking in senior high school, with the most pronounced changes observed during primary school. Besides age, astigmatic refractive power was influenced by spherical equivalent(β=0.105, P<0.001), mean keratometry(β=-0.118, P<0.001), sex(with boys as the reference, girls: β=0.054, P<0.001), frequent sustained near work for 30-40 min(with “almost never” as the reference, β=-0.030, P=0.038), preterm birth(β=-0.023, P=0.044), maternal myopia(β=-0.028, P=0.020), and homework completion time on rest days(β=-0.035, P=0.041). The detection rate of astigmatism was associated with maternal myopia(OR=1.130, P=0.039), male sex(OR=0.773, P<0.001), shorter sleep duration on school days(OR=0.909, P=0.028), shorter sleep duration on rest days(OR=0.937, P=0.046), preterm birth(OR=1.382, P=0.012), frequent excessive head lowering(OR=1.216, P=0.045), homework completion time on rest days(OR=1.043, P=0.046), higher spherical equivalent(OR=0.891, P<0.001), and higher mean keratometry(OR=1.188, P<0.001).CONCLUSION:The degree and detection rate of astigmatism among children and adolescents from kindergarten to senior high school in Yangpu District, Shanghai are correlated with educational stage, and primary school may represent a critical period for astigmatism prevention and control. Male sex, maternal myopia, preterm birth, high-intensity near work, and insufficient sleep and other factors may be associated with the onset and progression of astigmatism. It is recommended that education and health departments strengthen visual health screening during primary school, while promoting behavioral interventions such as scientific eye-use habits and adequate sleep across different educational stages to delay the onset and progression of astigmatism.

Background Both productive dust and noise are occupational hazards, and each can induce changes in blood glucose levels among workers. Objective To explore the potential interactive effects of exposure to productive dust and noise on the risk of hyperglycemia among automobile manufacturing workers. Methods Using a cluster sampling method, workers undergoing occupational health examination from three automobile manufacturing plants in Wuhan in 2022 were selected. Basic information was collected using a questionnaire designed by the Chinese Center for Disease Control and Prevention. Exposure history was obtained through occupational history interviews. Clinic indicators such as blood pressure, blood lipids, fasting blood glucose (FBG), and fatty liver status, were retrieved from examination records. Hyperglycemia was defined as FBG > 6.1 mmol·L^-1. Logistic regression models analyzed the independent effects of occupational noise and dust exposure, while additive and multiplicative interaction models assessed their interactive effects on hyperglycemia. Results The prevalence of hyperglycemia among the 1223 participants was 7.7%. Logistic regression showed that using workers without exposure as reference, the odds ratios (OR) and 95% confidence intervals (CI) for hyperglycemia among workers exposed only to dust, only to noise, and to both were 2.15 (1.90, 4.23), 2.23 (1.40, 5.08), and 3.75 (1.95, 7.24), respectively. A linear association was observed between the duration of noise exposure and blood glucose levels (P<0.05). Interaction analysis showed no multiplicative interaction or additive interaction. Conclusion Exposure to productive dust and noise are independent risk factors for hyperglycemia among workers. While both contribute to increased risk, no significant synergistic interaction is observed.

Objective To systematically evaluate the risk prediction models for postoperative pulmonary infection in patients with esophageal cancer, providing an objective basis for clinical selection and optimization of models. Methods A systematic search was conducted in Chinese and English databases such as VIP, Wanfang, CNKI, CBM, PubMed, Cochrane Library, Embase, and Web of Science for studies related to the risk prediction models of postoperative pulmonary infection in patients with esophageal cancer from the inception to September 30, 2024. The PROBAST tool was used to assess the quality of prognostic model research, and the RevMan 5.4 software was used for meta-analysis of predictive factors. Results A total of 17 articles were included, containing 26 pulmonary infection risk prediction models. The area under the receiver operating characteristic curve (AUC) ranged from 0.627 to 0.942, among which 21 models had good predictive performance (AUC>0.7). Quality assessment through the PROBAST tool revealed that all 17 articles had a high risk of bias. Meta-analysis results showed that common predictive factors for postoperative pulmonary infection in esophageal cancer included smoking history (OR=1.97), smoking index ≥200 (cigarettes-years) (OR=4.38), smoking index ≥400 (cigarettes-years) (OR=2.00), age (OR=1.27), comorbid diabetes (OR=2.13), comorbid emphysema or chronic obstructive pulmonary disease (OR=1.55), low plasma albumin levels (OR=1.17), prognostic nutritional index (OR=4.45), history of related lung diseases (OR=2.10), tumor location (OR=2.32), surgical approach (OR=2.21), operation time (OR=1.73), preoperative serum procalcitonin levels (OR=3.06), anastomotic leakage (OR=3.39), reduced forced expiratory volume in the first second/forced vital capacity ratio (OR=0.86), and hoarseness (OR=2.23). Conclusion At present, the risk prediction models for postoperative pulmonary infection in esophageal cancer are still in the stage of continuous development and optimization, and their research quality needs to be further improved. Future research can refer to the predictive factors summarized in this study based on meta-analysis, combined with clinical practice, to select appropriate methods to construct and validate the risk prediction models for postoperative pulmonary infection in esophageal cancer, thus providing early targeted preventive strategies for high-risk patients.