OBJECTIVES: To compare the anti-inflammatory, antibacterial and analgesic effects of Yinqiao Powder (YQS) formulated granules and decoction. METHODS: We first evaluated the anti-inflammatory effects of the two dosage forms of YQS in a LPS-induced RAW 264.7 cell model using RT-qPCR and Western blotting. We further constructed zebrafish models of inflammation by copper sulfate exposure, caudal fin transection, or LPS and Poly (I:C) microinjection, and evaluated anti-inflammatory effects of YQS granules and decoction by examining neutrophil aggregation and HE staining findings. In a mouse model of acute lung injury (ALI) induced by intratracheal LPS instillation, the effects of YQS gavage at 10, 15, and 20 g/kg on lung pathologies were evaluated by calculating lung wet-dry weight ratio and using HE staining, ELISA and Western blotting. The microbroth dilution method was used to evaluate the antibacterial effect of YQS. Mouse pain models established by hot plate and intraperitoneal injection of glacial acetic acid were used to evaluate the analgesic effects of YQS at 10, 15, and 20 g/kg. RESULTS: Both YQS granules and decoction significantly reduced TNF-α, IL-6, and IL-1β expressions and p-STAT3 (Tyr 705) phosphorylation level in LPS-induced RAW 264.7 cells, and obviously inhibited neutrophil aggregation in the zebrafish models. In ALI mice, YQS granules and decoction effectively ameliorated lung injury, lowered lung wet-dry weight ratio, and reduced p-STAT3 (Tyr 705) expression and TNF-α and IL-6 levels. YQS produced obvious antibacterial effect at the doses of 15.63 and 31.25 mg/mL, and significantly reduced body torsion and increased pain threshold in the mouse pain models. CONCLUSIONS The two dosage forms of TQS have similar anti-inflammatory, antibacterial and analgesic effects with only differences in their inhibitory effect on TNF-α, IL-6 and IL-1β mRNA expressions in LPS-induced RAW 264.7 cells.
Animals ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Anti-Inflammatory Agents/pharmacology* ; Analgesics/pharmacology* ; RAW 264.7 Cells ; Zebrafish ; Anti-Bacterial Agents/pharmacology* ; Powders ; Tumor Necrosis Factor-alpha/metabolism* ; Acute Lung Injury/drug therapy* ; Interleukin-6/metabolism* ; Lipopolysaccharides

OBJECTIVES: To investigate the expression of parathyroid hormone-like hormone (PTHLH) in hepatocellular carcinoma (HCC) and analyze its correlation with clinical prognosis, its regulatory effects on HCC cell behaviors, and the signaling pathways mediating its effects. METHODS: We analyzed the differential expression of PTHLH in HCC and adjacent tissues and its association with patient prognosis based on data from TCGA and GEO databases and from 70 HCC patients treated in our hospital. The effects of PTHLH knockdown and overexpression on proliferation, migration, and invasion of cultured HCC cells were investigated using CCK-8 assay, colony formation assay, Transwell migration and invasion assays, and the signaling pathways activated by PTHLH were detected using Western blotting. RESULTS: TCGA and GEO database analysis showed significant overexpression of PTHLH mRNA in HCC tissues, which was associated with poor prognosis of the patients (P<0.05). High PTHLH mRNA expression was a probable independent prognostic risk factor for HCC (P<0.05). In the clinical samples, PTHLH mRNA and protein expressions were significantly higher in HCC tissues than in the adjacent tissues (P<0.001 or 0.01). Univariate and multivariate Cox regression analyses suggested that high PTHLH mRNA expression was an independent risk factor to affect postoperative disease-free survival of HCC patients (P<0.05). The prognostic prediction model based on PTHLH mRNA expression showed an improved accuracy for predicting the risk of postoperative recurrence in HCC patients. In cultured HCC cells, PTHLH overexpression significantly promoted cell proliferation, colony formation, migration and invasion, and caused activation of the ERK/JNK signaling pathway in Huh7 and Hep3B cells. CONCLUSIONS High PTHLH expression promotes HCC progression and is associated with poor patient prognosis. Its pro-tumor effects may be mediated by activation of the ERK/JNK signaling pathway.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Prognosis ; Cell Proliferation ; Parathyroid Hormone-Related Protein/genetics* ; Cell Line, Tumor ; Cell Movement ; Disease Progression ; Signal Transduction ; Male ; RNA, Messenger/genetics* ; Female

OBJECTIVES: To evaluate the effectiveness of single-balloon and double-balloon enteroscopy in diagnosing pediatric small bowel diseases and assess the diagnostic efficacy of computed tomography enterography (CTE) for small bowel diseases using enteroscopy as the reference standard. METHODS: Clinical data from 576 children who underwent enteroscopy at Hunan Children's Hospital between January 2017 and December 2023 were retrospectively collected. The children were categorized based on enteroscopy type into the single-balloon enteroscopy (SBE) group (n=457) and double-balloon enteroscopy (DBE) group (n=119), and the clinical data were compared between the two groups. The sensitivity and specificity of CTE for diagnosing small bowel diseases were evaluated using enteroscopy results as the standard. RESULTS: Among the 576 children, small bowel lesions were detected by enteroscopy in 274 children (47.6%).There was no significant difference in lesion detection rates or complication rates between the SBE and DBE groups (P>0.05), but the DBE group had deeper insertion, longer procedure time, and higher complete small bowel examination rate (P<0.05). The complication rate during enteroscopy was 4.3% (25/576), with 18 cases (3.1%) of mild complications and 7 cases (1.2%) of severe complications, which improved with symptomatic treatment, surgical, or endoscopic intervention. Among the 412 children who underwent CTE, the sensitivity and specificity for diagnosing small bowel diseases were 44.4% and 71.3%, respectively. CONCLUSIONS SBE and DBE have similar diagnostic efficacy for pediatric small bowel diseases, but DBE is preferred for suspected deep small bowel lesions and comprehensive small bowel examination. Enteroscopy in children demonstrates relatively good overall safety. CTE demonstrates relatively low sensitivity but comparatively high specificity for diagnosing small bowel diseases.
Retrospective Studies ; Treatment Outcome ; Double-Balloon Enteroscopy/statistics & numerical data* ; Single-Balloon Enteroscopy/statistics & numerical data* ; Humans ; Male ; Female ; Child ; Operative Time ; Tomography, X-Ray Computed/statistics & numerical data* ; Sensitivity and Specificity ; Intestine, Small/surgery* ; Intestinal Diseases/surgery*

OBJECTIVE: To investigate the effects of bortezomib (BTZ) combined with polyphyllin Ⅶ (PP7) on proliferation, apoptosis and oxidative stress of myeloma cell line ARH-77. METHODS: MTT assay was used to detect the inhibitory effects of different concentrations of BTZ, PP7 monotherapy, and their combination on the proliferation of ARH-77 cells. In subsequent experiments, the cells were divided into 4 groups: control group (no drug added), BTZ (15 nmol/L) group, PP7 (1.5 μmol/L) group and BTZ(15 nmol/L)+PP7 (1.5 μmol/L) group. The effects of the two drugs on the morphology of ARH-77 cells were observed. Flow cytometry was used to detect the apoptosis rate of the cells in each group. Calcein-AM/PI double staining kit was used to observe the status of the cells and the cell viability were evaluated. The expression of apoptosis-related proteins were detected by Western blot. DCFH-DA fluorescent probe was used to detect the levels of reactive oxygen species (ROS). RESULTS: Both BTZ and PP7 monotherapy, as well as their combination, could inhibit the growth of ARH-77 cells in a dose-dependent manner (r_BTZ=-0.9717, r_PP7=-0.9941, r_BTZ+PP7=-0.9951), and the combination of BTZ and PP7 exhibited a synergistic effect within a certain concentration range. Compared with the BTZ group and PP7 group, the apoptosis rate of the BTZ+PP7 group was significantly increased (P < 0.01), the expressions of pro-apoptotic proteins Bax, Smac and P53 were significantly upregulated (P < 0.05), the expression of anti-apoptotic protein Bcl-2 was significantly downregulated (P < 0.01), and the ratio of Bax/Bcl-2 was significantly increased (P < 0.01). Compared with the control group, the level of ROS in the BTZ, PP7 monotherapy group and BTZ+PP7 group were significantly increased (P < 0.05). CONCLUSION BTZ combined with PP7 can inhibit the proliferation and induce apoptosis of ARH-77 cells, and increase the level of intracellular ROS.
Apoptosis/drug effects* ; Bortezomib ; Humans ; Cell Proliferation/drug effects* ; Oxidative Stress/drug effects* ; Multiple Myeloma/metabolism* ; Cell Line, Tumor ; Saponins/pharmacology*

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Epstein-Barr virus(EBV)has a high prevalence of infection worldwide,with early onset of a-symptomatic latent infection,and has been shown to be closely associated with the development of many lym-phomas and lymphoproliferative disorders.These diseases are characterized by both viral infection and involve-ment of the blood and lymphatic system,with complex clinical manifestations and poor prognosis,which pose problems in the diagnosis and selection of treatment options.Early detection and intervention are essential for the prevention and treatment of EBV-related diseases.However,traditional detection methods face the diffi-culties of viral leakage and the complex genetic features of EBV-associated lymphomas,and there is an urgent need for new detection techniques to assist in the diagnosis of the disease.This article mainly focuses on the clinical features of common EBV-associated lymphomas and the research progress of the corresponding detec-tion technologies.

Objective:To develop and validate a machine learning (ML) noninvasive model based on routine laboratory parameters to preoperatively predict the microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).Methods:A total of 629 HCC patients who underwent hepatectomy at the First Affiliated Hospital of Fujian Medical University between January 2019 and December 2023 were retrospectively enrolled in this study and were divided chronologically into a training set ( n=464) and internal validation set ( n=165). A cohort with 190 HCC patients from Fujian Provincial Hospital were used as an external validation set. Preoperatively demographic features, tumor size and routine laboratory data were collected. All patients were divided into MVI-positive or MVI-negative group. The Boruta algorithm and LASSO regression algorithm were used to screen out related features in the training set. Eight different ML algorithms including multivariate logistic regression, decision tree (DT), random forest (RF), extreme gradient boosting (XGboost), k-nearest neighbor (KNN), support vector machine (SVM), light gradient boosting machine (LGBM) and Naive Bayes were used to construct the prediction models. The predictive performances of these models on training and internal validation sets were evaluated by the receiver operating characteristic (ROC) curve with the area under the curve (AUC). The ML model with the highest AUC values was defined as the optimal model and its performance was further validated in the external validation set. The calibration curve showed that the probability value curve was close to the actual occurrence probability curve, and the DCA showed that it could be applied within the threshold probability range of 0.3-0.8 to obtain net benefits. Results:After screening, eight parameters including α-fetoprotein (AFP), protein induced by vitamin K absence Ⅱ (PIVKA-Ⅱ), tumor size, eosinophil count, neutrophil count, creatinine, ApoA1 and total bilirubin were finally selected for the construction of the preoperative prediction model for MVI in HCC. Among all the tested eight ML algorithms, XGboost obtained the optimal performance with an AUC of 0.820 in training set, an AUC of 0.803 in internal testing set and an AUC of 0.758 in external testing set. Further stratified analysis showed that the AUC for preoperatively predicting MVI by XGboost was 0.817 for HCC patients with positive hepatitis B surface antigen, 0.779 for male patients and 0.790 for elder patients. The calibration curves showed good agreement between observed and predicted values and the decision curve analysis curve showed relatively higher net benefits.Conclusions:We successfully established and verified a novel XGboost model based on eight routine laboratory parameters with relatively high and reliable predictive accuracy to preoperatively predict MVI in HCC.

Objective:To evaluate the service capability and operational efficiency of surgical departments in a hospital using data analysis models such as entropy weight TOPSIS and Boston matrix analysis, for references for optimizing medical resource allocation, promoting refined management and sustainable development of the hospital.Methods:The operational data of 24 surgical departments (A~X) in a tertiary public hospital in 2023 from its information system were extracted. The number of doctors, actual number of open beds, and average length of stay etc., were served as evaluation indicators. The TOPSIS and rank sum ratio methods were used to evaluate the medical service capabilities, the data envelopment analysis (DEA) was used to analyze operational efficiency, and Boston matrix analysis was used for departmental classification.Results:In terms of medical service capabilities, the top 5 departments were F, S, K, D, and C ( Ci>0.41), all of which were in the excellent category; The bottom three departments were L, N, and G ( Ci<0.04), all of which were in the poor range. From the perspective of operational efficiency, 8 departments had achieved strong DEA effectiveness, while the remaining 16 departments were non DEA effective, resulting in resource redundancy or insufficient output. According to the Boston Matrix analysis, 8 departments (stars) had strong medical service capabilities and high operational efficiency; 6 departments (cash cows) had poor medical service capabilities but high operational efficiency, and 8 departments (dogs) had poor medical service capabilities and operational efficiency; 2 departments (question marks) had strong medical service capabilities but low operational efficiency. Conclusions:This study comprehensively applied multiple data models to objectively and comprehensively evaluate the service capabilities and operational efficiency of surgical departments. Hospitals could develop corresponding resource allocation optimization strategies based on the Boston matrix classification results, combined with the disease characteristics and business scale configuration of each department.

Background Enhancing the sense of honor and belonging among medical staff is a key component of establishing a modern hospital management system. Compared to medical staff at general hospitals, medical staff at oncology hospitals are more prone to job burnout, yet few studies in China have focused on job burnout among employees in oncology hospitals. Objective To propose a hypothetical model in which job well-being moderates the relationship between stressors and occupational burnout, to explore how stressors influence burnout and potential moderating role of job well-being, and to provide better understanding of job burnout and motivate employees based on the double-edge sword effect of stressors. Methods A cross-sectional survey was conducted in May 2022 at a tertiary oncology specialty hospital in Chongqing, China. A total of 1 898 medical staff were recruited. Data were collectedthrough four scales including a general information questionnaire, Maslach Burnout Inventory-Human Service Survey, Work Stressor Scale, and Occupational Well-being Scale for Medical Staff. Independent sample t-tests and one-way ANOVA were used for univariate comparisons of job burnout. Pearson correlation analysis was employed to examine the relationships between job burnout, stressors, and job well-being. Hierarchical linear regression was conducted to identify factors influencing job burnout and to examine potential moderating role of job well-being in the relationship between stressors and job burnout. Results A total of 2 123 questionnaires were distributed, with 1 898 valid responses, yielding an effective response rate of 89.4%. The prevalence of job burnout was 60.1%. The correlation coefficient was 0.717 (P<0.001) between stressors and burnout, −0.784 (P<0.05) between job well-being and burnout, and −0.744 (P<0.001) between stressors and job well-being. The quadratic stressors showed a statistically significant effect on burnout (β=0.404, P<0.01). Job well-being positively moderated the relationship between the linear stressors and burnout (β=1.289, P<0.001) and negatively moderated the relationship between the quadratic stressors and job burnout (β=−0.571, P<0.01), explaining 7.1% of the variance. Conclusion Job burnout prevalence is relatively high among employees in oncology hospitals. There is a curvilinear relationship between stressors and job burnout, with job well-being moderating this relationship. From a practical perspective, it is recommended to establish a tiered stress alert system to monitor employees’ stress levels and prevent prolonged exposure to high-pressure conditions. Additionally, improving employees’ job well-being through institutional incentives and developmental support can enhance its moderating role in mitigating the adverse effects of stressors on job burnout. Meanwhile, fostering coordinated responses between organizations and individuals is crucial for strengthening mental health management systems, thereby supporting a healthy, stable, and sustainable development of the healthcare workforce.

ObjectiveTo investigate the value of Fried Frailty Phenotype （FFP）， liver frailty index （LFI）， and Short Physical Performance Battery （SPPB） in predicting 2-year all-cause mortality and decompensation events in patients with liver cirrhosis. MethodsA total of 277 patients with liver cirrhosis who were hospitalized in Beijing Friendship Hospital， Capital Medical University， from December 2020 to December 2021 were enrolled， and FFP， LFI， and SPPB were used to assess the state of frailty. Based on the scores of each tool， these patients were divided into frail and non-frail groups. These three tools were compared in terms of consistency and independent predictive performance. The primary endpoints were 2-year all-cause mortality rate and composite endpoints （death+decompensation events）， and the Cox regression analysis， the receiver operating characteristic （ROC） curve， net reclassification index （NRI）， and integrated discrimination improvement （IDI） index were used to analyze the predictive value of the three tools. Normally distributed continuous data were compared between two groups using the independent samples t-test， while non-normally distributed continuous data were compared using the Mann-Whitney U test. Categorical data were compared between groups using the chi-square test or Fisher’s exact test. The agreement among different frailty tools was evaluated using Cohen’s Kappa statistic. The Kaplan-Meier survival curve was plotted， and a survival analysis was performed using the log-rank test. ResultsThe prevalence rate of frailty assessed by FFP， LFI， and SPPB was 37.2%， 22.4%， and 20.2%， respectively， with a moderate consistency between FFP and LFI/SPPB （κ=0.57， 95% confidence interval ［CI］： 0.47 — 0.67； κ=0.51， 95%CI： 0.41 — 0.62） and a relatively high consistency between LFI and SPPB （κ=0.87， 95%CI： 0.80 — 0.94）. Compared with the non-frailty group， the frailty group had significantly higher all-cause mortality rate and incidence rate of composite endpoints （P0.001）. After multivariate adjustment， FFP， LFI， and SPPB had a hazard ratio of 2.42（95%CI： 1.51 — 5.11）， 2.21（95%CI： 1.11 — 4.42）， and 2.21（95%CI： 1.14 — 4.30）， respectively， in predicting all-cause mortality， as well as a hazard ratio of 2.51（95%CI： 1.61 — 3.91）， 2.40（95%CI： 1.51 — 3.80）， and 2.20（95%CI： 1.39 — 3.47）， respectively， in predicting composite endpoints. Compared with Child-Pugh score， FFP had a significantly greater area under the ROC curve （AUC） in predicting all-cause mortality （0.79 vs 0.69， P=0.032） and composite endpoints （0.75 vs 0.68， P=0.044）. Frailty assessment tools combined with Child-Pugh score significantly improved the performance in predicting all-cause mortality and composite endpoints， with an AUC of 0.81 — 0.82 and 0.77 — 0.78， respectively （P0.05）. NRI and IDI analyses further confirmed the improvement of the combined model in classification （all P0.001）. ConclusionFFP， LFI， and SPPB can independently predict adverse outcomes in patients with liver cirrhosis， among which FFP has the best predictive performance， and the combination of frailty assessment tools with Child-Pugh score can significantly enhance the accuracy of prognostic evaluation.