Objective:To investigate the predictive value of the cancer antigen 125 (CA 125) elimination rate constant K (KELIM) score for no visible residual disease (R0) and prognosis in high-grade serous ovarian carcinoma (HGSOC) patients undergoing neoadjuvant chemotherapy (NACT)+interval debulking surgery (IDS). Methods:A retrospective analysis was conducted on 78 HGSOC patients treated with NACT+IDS at Beijing Hospital, from June 2014 to June 2024. The KELIM score was calculated, and its predictive value for R0 resection, chemotherapy response score (CRS), platinum-free interval (PFI), progression-free survival (PFS) time, and overall survival (OS) time was analyzed.Results:(1) The mean age at diagnosis was (61.9±9.9) years. The mean KELIM score was 1.1±0.4, with 44 patients having KELIM score≥1 and 34 having KELIM score <1. (2) Patients with KELIM score ≥1 had significantly higher rates of R0 resection (84% vs 56%; P=0.006), CRS3 grading (41% vs 0; P<0.001), and PFI ≥6 months (84% vs 53%; P=0.04) compared to those with KELIM score <1. Additionally, the median PFS time (18.7 vs 13.2 months; P<0.001) and OS time (34.8 vs 29.9 months; P=0.007) were significantly longer in the KELIM score ≥1 group. Chemosensitivity: patients with PFI <6 months had a significantly lower median KELIM score than those with PFI ≥6 months (0.8 vs 1.2; P=0.005). Surgical outcome: patients achieving R0 resection had a significantly higher median KELIM score than those without R0 (1.2 vs 0.7; P<0.001). (3) Univariate analysis identified non-R0 resection, CRS3 grading, lack of poly adenosine diphosphate ribose polymerase (PARP) inhibitor maintenance therapy, and KELIM score <1 as significant risk factors for OS time (all P<0.05). Multivariate analysis confirmed non-R0 resection ( HR=3.78,95% CI: 1.13-12.66; P=0.031), no PARP inhibitor maintenance ( HR=7.41,95% CI:1.82-30.15; P=0.005), and KELIM score <1 ( HR=5.14,95% CI:1.41-18.72; P=0.013) as independent risk factors for OS time. Conclusions:The KELIM score may serve as a predictive marker for chemosensitivity, R0 resection, PFS time, and OS time in HGSOC patients undergoing NACT+IDS. KELIM score<1 is an independent risk factor for OS.

To establish an indirect enzyme linked immunosorbent assay(ELISA)method for the detection of Zaire Ebola virus(ZEBOV)specific antibodies,the full-length of ZEBOV GP1 gene was amplified by PCR and cloned into pET-30a(+)vector to generate the pET-30a(+)-GP1 plasmid.After expressed in the E.coli expression system,the purified GP1 protein was used as coating antigen to establish the indirect ELISA method for detection of ZEBOV antibody.The con-ditions including concentration of coating antigen and serum dilution were determined by chess-board titration.Specificity,sensitivity,and reproducibility of the established ELISA detection meth-od were evaluated.GP1 protein was successfully prepared by prokaryotic expression,and was used as the coatingantigen for indirect ELISA.By optimizing the reaction conditions,the optimal concen-tration of the coating antigen was determined to be 0.5 g/L;the optimal dilution of serum was cal-culated to be 1∶3 200;the optimal dilution of enzyme-labeled secondary antibody was measured to be 1∶20 000.The established method exhibited excellent specificity,sensitivity,and reproducibili-ty.In the present study,the GP1 protein was successfully expressed in the E.coli expression sys-tem and the high purity GP1 protein was used as the coating protein to establish an indirect ELISA assay for ZEBOV antibody.This method is highly specific,sensitive,and reproducible,which provides technical support for the fur-ther study of the biological function of GP1 and the detection of ZEBOV antibody in serum.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective:To explore the value of the vesical imaging-reporting and data system (VI-RADS) score based on multiparametric MRI (mpMRI) combined with quantitative tumor MRI parameters in assessing the muscle invasion of bladder cancer.Methods:The study was a case-control study. The data of 87 bladder cancer patients confirmed by pathology who underwent mpMRI of the bladder were retrospectively collected from the First Medical Center of Chinese PLA General Hospital between January 2019 and April 2023 The pathological findings were used as the gold standard to categorize them into the muscle invasive bladder cancer (MIBC) group (29 cases) and non-muscle invasive bladder cancer (NMIBC) group (58 cases). Quantitative parameters were measured based on preoperative mpMRI images, including the length of tumor bladder wall contact, the perpendicular distance between the bladder tumor and the tangent of the bladder wall, the maximal diameter of the bladder tumor, and the volume of the bladder tumor. Bladder cancer was classified according to the VI-RADS scoring criteria. The Mann-Whitney U test was used for intergroup comparisons. Multivariate logistic regression analysis was performed to obtain the independent risk factors related to muscle invasion of bladder cancer and to establish the model. The receiver operating characteristic curves were analyzed for MRI quantitative parameters and logistic regression models, and area under the curve (AUC) comparisons were performed using the DeLong test. Results:The differences in tumor bladder wall contact length, perpendicular distance from the tumor to the tangent line of the bladder wall, maximum diameter, bladder tumor volume, and the VI-RADS scores were statistically significant between the MIBC group and the NMIBC group ( P<0.05). Multifactorial logistic regression analysis showed that tumor bladder wall contact length ( OR=21.07, 95% CI 3.56-124.89, P=0.001) and VI-RADS score ( OR=11.90, 95% CI 3.53-40.12, P<0.001) were the independent risk factors for evaluating the muscle invasion of bladder cancer. The difference between the VI-RADS score and the tumor bladder wall contact length for assessing muscular infiltration of bladder cancer had AUCs of 0.802 (95% CI 0.704-0.899) and 0.759 (95% CI 0.652-0.865). The combined model of VI-RADS score combined with tumor bladder wall contact length had an AUC of 0.891 (95% CI 0.812-0.970), which was higher than the diagnostic efficacy of applying tumor bladder wall contact length or VI-RADS score alone ( Z=3.05, 2.37, P=0.002, 0.018). Conclusion:Tumor contact length with the bladder wall is an independent risk factor for assessing muscle invasion of bladder cancer and the combination of VI-RADS score may enhances diagnostic accuracy.

Objective:To explore the method for selecting characteristic prices of Chinese patent medicines based on informa-tion entropy theory.It involves analyzing the connotative differences among various price indicators and utilizing information entropy metrics to validate the scientific rigor of characteristic price selection so as to optimize the pricing model for Chinese patent medi-cines and improve the accuracy of price evaluation.Methods:A correlation analysis and information entropy calculation are con-ducted on the median price of the smallest preparation unit,average daily cost,and average course cost of TCM.It compares the information diversity and uncertainty of different pricing indicators.Results:The average daily cost exhibits the highest information diversity and uncertainty among all the pricing indicators examined.Conclusion:It is recommended that the average daily cost be used as the dependent variable for characteristic prices in TCM pricing research.This choice plays an important role in optimizing TCM pricing models and enhancing the accuracy of price evaluation.

Objective:To establish a scientific,systematic,and objective indicator system for the characteristic price variables of Traditional Chinese Patent Medicines(TCPM),providing a reference framework for the pricing mechanism of TCPM.Methods:The brainstorming method was initially used to screen related variable indicators.The Nominal Group Technique(NGT)and Delphi methods were applied to gather expert opinions,and SPSS 28.0 was employed for data statistical analysis.It led to the development of a TCPM characteristic price variable indicator system consisting of 6 dimensions,14 characteristic variables and 26 measurement indicators.Results:The authority coefficient of the experts exceeded 0.7,indicating the representativeness of the results.Expert opinions were generally concentrated.Based on the collected opinions and statistical analysis,the scope of selected TCPM characteristic price variables was preliminarily established.Conclusion:The TCPM characteristic price variable indicator system was initially developed.However,due to the complexity of the pricing mechanism and divergent expert opinions,further qualitative and quantitative research methods,along with a dynamic adjustment mechanism,are needed to verify and refine the system.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age-standardized prevalence, mortality, disability-adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio-demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age-period-cohort (BAPC) model. Results The global agestandardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/10⁵ [95% UI: (6.27/10⁵, 9.51/10⁵)], 0.02/10⁵ [95% UI: (0.01/10⁵, 0.02/10⁵)], and 1.32/10⁵ [95% UI: (0.99/10⁵, 1.69/10⁵)] in 2021. The global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age-standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = −0.66%, 95% confidence interval (CI): (−0.70%, −0.61%)] and from 2005 to 2015 [APC = −0.88%, 95% CI: (−0.93%, −0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC=0.30%, 95%CI: (0.19%, 0.40%)].Theagestandardized prevalence (r = −0.17, P < 0.05), mortality (r = −0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = −0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age-standardized mortality (r = −0.61, P < 0.05) and DALYs rates (r = −0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age-standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high-SDI countries or territories. In addition, the global age-standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age-standardized mortality [men: EAPC = −4.71%, 95% CI: (−4.71%, −4.37%); women: EAPC = −4.74%, 95% CI: (−4.74%, −4.74%)] and DALYs rates [men: EAPC = −3.35%, 95% CI: (−3.36%, −3.34%); women: EAPC = −3.17%, 95% CI: (−3.18%, −3.16%)] were projected to appear a tendency towards a decline among both men and women. Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended.

Objective:To explore the risk factors of pneumoconiosis complicated with pulmonary tuberculosis, to construct a clinical prediction model for patients with pneumoconiosis complicated with pulmonary tuberculosis, and to provide a scientific basis for the prevention of pneumoconiosis complicated with pulmonary tuberculosis.Methods:In January 2024, a total of 232 patients with pneumoconiosis (including coal workers' pneumoconiosis and silicosis) who were treated in the Department of Respiratory and Critical Care Medicine of the Third People's Hospital of Xinjiang Uygur Autonomous Region (Xinjiang Uygur Autonomous Region Occupational Disease Hospital) from January 2022 to January 2023 were randomly selected as the study subjects. Collectted basic patient information and diagnostic data. Multivariate logistic regression analysis was used to screen the risk factors related to pneumoconiosis complicated with pulmonary tuberculosis. According to the results of multivariate logistic regression analysis, a nomogram was established, and the area under the receiver operating characteristic (ROC) curve (AUC), calibration curve and decision curve analysis (DCA) were used to evaluate the predictive ability.Results:Among the 232 patients with pneumoconiosis, 73 were complicated with pulmonary tuberculosis, accounting for 31.47% (73/232). Multivariate logistic regression analysis determined that dust exposure time, type of work, smoking history, and lung function level were all risk factors for pneumoconiosis complicated with tuberculosis ( OR=10.33, 95% CI=1.92~55.66, OR=5.43, 95% CI=1.91~15.44, OR=3.10, 95% CI=1.15~8.37, OR=4.00, 95% CI=1.62~9.87; P<0.05). The constructed nomogram model has good clinical applicability when the area under the receiver operating characteristic (ROC) curve is 0.77 [95% CI (0.69, 0.73) ], the calibration curve is close to the ideal diagonal, the absolute error between the simulation curve and the actual curve is 0.03, and the DCA decision curve shows that the probability threshold of the nomogram model is 1%-90%. Conclusion:The risk of pneumoconiosis complicated with tuberculosis is high, and the risk factors of dust exposure time, smoking history, type of work and lung function level are high. This nomogram model can be used to predict the risk of pulmonary tuberculosis in patients with pneumoconiosis, which is helpful for early intervention.

Objective:To explore the application effect of BOPPPS (Bridge-in, Objectives, Pre-assessment, Participatory learning, Post-assessment, and Summary) combined with scenario simulation in cultivating the humanistic care ability of undergraduate nursing interns.Methods:Undergraduate nursing students who were interning at the First Affiliated Hospital of Zhengzhou University were selected by convenience sampling. The 46 interns from June to December 2023 were set as the control group, and the 46 interns from June to December 2024 were set as the experimental group. The control group adopted the traditional lecture-based teaching method, while the experimental group adopted BOPPPS combined with scenario simulation. Theoretical and practical scores, humanistic care ability, empathy ability, and critical thinking ability of the two groups were compared.Results:After the intervention, the theoretical and practical scores, as well as humanistic care ability, empathy ability, and critical thinking ability scores of the experimental group were all higher than those of the control group, and the differences were statistically significant ( P<0.05) . Conclusions:BOPPPS combined with scenario simulation plays a positive role in improving theoretical and practical scores, humanistic care ability, empathy ability, and critical thinking ability of undergraduate nursing interns, and it is worthy of further promotion and application.