Background:To compare the efficacy and safety of monthly administrations of gonadotropin releasing hormone (GnRH) agonists LY01005 and Zoladex ? in Chinese patients with premenopausal breast cancer. Methods:From October 2020 to November 2021, 188 premenopausal breast cancer patients were enrolled in 34 hospitals and randomized 1:1 to receive either LY01005 or Zoladex ? every 28 days for a total of three injections. All patients concomitantly received oral tamoxifen (TAM). The primary efficacy endpoint was cumulative probability of maintaining menopausal level [oestradiol (E2) ≤30 pg/ml] from day 29 to day 85. The second efficacy endpoint included changes in E2, luteinizing hormone (LH), and follicle-stimulating hormone (FSH) compared with the baseline. Pharmacokinetics (PK), pharmacodynamics (PD), and safety were analyzed. The study also evaluated the pharmacokinetic and pharmacodynamic characteristics of LY01005. Results:A total of 188 patients were randomised and 187 patients received either LY01005 or Zoladex ?. Cumulative probabilities of maintaining menopausal level (E2≤30 pg/ml) from day 29 to day 85 were 93.1% for LY01005 and 86.3% for Zoladex ?. The between-group difference was 6.8% (95% CI: -2.3%, 15.9%) and primary efficacy in the LY01005 group was not inferior to that in the Zoladex ? group. Changes in E2, LH, and FSH levels compared with the baseline were equivalent between the two groups (E2: 89.34% to 90.23% vs. 82.11% to 85.02%; LH: 88.89% to 95.52% vs. 89.70% to 97.02%; FSH: 75.36% to 80.85% vs.73.07% to 80.24%, respectively). After three consecutive doses of LY01005, the LH and FSH levels of the subjects showed a transient increase after the first dose, reached a peak on the second day and then started to decrease. The LH and FSH reached a lower level and remained at or below that level until the 85th day. Both treatments were well-tolerated. Conclusion:LY01005 is as effective as Zoladex ? in suppressing E2 to menopausal levels in Chinese patients with premenopausal breast cancer, with a similar safety profile.

Objective:This study aimed to examine the association between malnutrition diagnosed by the Global Leadership Initiative on Malnutrition(GLIM)criteria and clinical outcomes in surgical patients,as well as to assess its prognostic impact on postoperative adverse clinical outcomes.Methods:Electronic databases,including PubMed,Embase,Web of Science,CINAHL,Scopus,The Cochrane Library,Clinical Trials,CNKI,Wanfang Data Knowledge Service Platform,and the Chinese Biomedical Literature Database,were systematically searched.Relevant cohort studies utilizing GLIM criteria to preoperatively diagnose malnutrition in surgical inpatients were included.The exposed group comprised surgical patients diagnosed with preoperative malnutrition using GLIM criteria,while the control group consisted of surgically treated patients without malnutrition as per GLIM criteria.Literature quality was evaluated using the Newcastle-Ottawa Scale(NOS),and meta-analysis was performed using Review Manager 5.4 software.Results:Fourteen literatures were included,with a total sample size of 10,045 patients.Meta-analysis revealed that the malnourished group had a higher incidence of postoperative complications compared to the non-malnourished group[risk ratio(RR)=1.81,95%CI:1.66～1.98),P<0.00001].Additionally,the incidence of severe complications was significantly higher in GLIM-diagnosed malnourished patients.The malnourished group exhibited poorer overall survival[hazard ratio(HR)=1.90,95%CI:1.55～2.34,P<0.00001]and disease-free survival[HR=2.25,95%CI:1.02～4.93,P=0.04]compared to the non-malnourished group.Conclusion:GLIM-diagnosed malnutrition is significantly associated with adverse clinical outcomes in surgical patients,increasing postoperative complication rates and reducing overall and disease-free survival.The GLIM criteria demonstrate value in predicting adverse clinical outcomes in this population.Further high-quality studies are warranted to validate these findings.

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.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

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