Objective To construct a visual imaging decision model for evaluating the prognosis of hepatocellular carcinoma(HCC)patients treated with interventional therapy based on MRI features.Methods A total of 130 HCC patients were selected.All of them underwent MRI examination upon admission,and then the interventional therapy was implemented after clinical evaluation.The patients were followed up for 2 years after the last interventional therapy,and then were divided into poor prognosis group(50 cases)and good prognosis group(80 cases)according to the follow-up results.The risk factors affecting the poor prognosis of HCC patients treated with interventional therapy were screened.A nomogram model was constructed based on the risk factors,and its prediction efficiency was then evaluated.Results The incomplete capsule,unsmooth tumor margin,portal vein tumor thrombus,cirrhosis,apparent diffusion coefficient(ADC)value,red blood cell distribution width within 24 h after admission,and aspartate aminotransferase were significantly different between the poor prognosis group and the good prognosis group(P＜0.05),and these indicators were the risk factors affecting the poor prognosis of HCC patients treated with interventional therapy(P＜0.05).Based on the above risk factors,a nomogram model of poor prognosis risk for the HCC patients treated with interventional therapy was constructed,and the sensitivity,specificity,and area under the curve(AUC)for predicting poor prognosis of HCC patients treated with interventional therapy were 90.00％,81.80％and 0.899[95％confidence interval(CI)0.827-0.972],respectively.Conclusion The risk nomogram model of poor prognosis of HCC patients treated with interventional therapy based on incomplete capsule,unsmooth tumor margin,portal vein tumor thrombus,cirrhosis,ADC value,red blood cell distribution width,and aspartate aminotransferase has good predictive efficacy.

Objective:To investigate the potential diagnostic value of peripheral blood soluble programmed cell death protein 1 (sPD-1) and soluble programmed cell death protein ligand 1 (sPD-L1) in acute rejection (AR) following liver transplantation using a rat model.Methods:A rat liver transplantation AR model was established, with the AR group (Lewis→BN) set as the experimental group (n=6) and the non-AR group (BN→BN) as the control group (n=6). Peripheral blood sPD-1 and sPD-L1 concentrations were measured using enzyme-linked immunosorbent assay (ELISA) at 1 day before transplantation and at 1, 3, and 7 days postoperatively. On postoperative day 7, the expression levels of PD-1 and PD-L1 in liver tissues were detected by immunohistochemistry (IHC). Independent samples t-test and repeated measures ANOVA were used to compare the results between the two groups. Pearson correlation analysis was conducted to evaluate the relationship between sPD-1, sPD-L1, the sPD-1/sPD-L1 ratio, and the rejection activity index.Results:On postoperative day 7, the experimental group exhibited significantly higher peripheral sPD-1 levels (218.59±36.88 vs. 164.95±15.82 ng/L) and a higher sPD-1/sPD-L1 ratio (0.44±0.12 vs. 0.36±0.07), but lower sPD-L1 levels (379.56±73.41 vs. 423.64±96.55 ng/L) compared to the control group (all P<0.05). Correlation analysis revealed a significant positive correlation between sPD-1 levels and the rejection activity index ( r=0.680, P<0.05), as well as between the sPD-1/sPD-L1 ratio and the rejection activity index ( r=0.795, P<0.01), while no correlation was observed between sPD-L1 levels and the rejection activity index. IHC demonstrated positive PD-1 and PD-L1 expression in the liver tissues of the experimental group, whereas the control group showed negative expression. Conclusion:Peripheral blood sPD-1 levels and the sPD-1/sPD-L1 ratio are significantly associated with AR after liver transplantation in rats, suggesting their potential as biomarkers for diagnosing AR in liver transplant recipients.

Objective:To summarize the clinical characteristics, diagnostic and therapeutic approaches, and prognosis of posttransplant lymphoproliferative disease (PTLD) following kidney transplantation.Methods:A retrospective case series analysis was conducted on 7 PTLD patients after kidney transplantation treated in the Department of Transplant Oncology, Tianjin First Central Hospital between January 2018 and December 2023. Clinical features, laboratory findings, imaging and pathological characteristics, treatment modalities, and outcomes were analyzed.Results:Among 7 PTLD patients, there were 5 male and 2 females with a median age of 41 (17-65) years. The median time of onset after operation was 4 (0.5-11) years. Among them, 2 patients had early onset (<1 year post-transplantation) and 5 patients had late onset (>1 year). The clinical manifestations included abdominal mass in 4 cases, anemia in 4 cases, fever in 3 cases, lymphadenopathy in 4 cases, gastrointestinal bleeding in 1 case, abdominal pain in 2 cases, and intestinal obstruction in 2 cases. Pathological types included diffuse large B-cell lymphoma in 4 cases, Burkitt lymphoma in 1 case, marginal zone lymphoma in 1 case, and polymorphic PTLD in 1 case. Reducing the immunosuppressant level was the basal treatment plan, and rituximab, chemotherapy, surgery, radiotherapy and CD19-targeted chimeric antigen receptor therapy were given according to the pathological classification. Until the date of submission, 2 patients had died, 4 had a complete response, and 1 had a partial response. None of the patients had acute rejection, and 1 patient had chronic renal insufficiency.Conclusions:PTLD after kidney transplantation presents with nonspecific manifestations, necessitating prompt imaging and histopathological evaluation for definitive diagnosis. At the same time, a series of measures should be given to improve the prognosis, including discontinuous use of anti-metabolic drugs, dosage decline of calcitric phosphatase inhibitor by 50% or convert it to sirolimus treatment, and corresponding treatment according to the specific conditions of the recipient.

Objective To identify and analyze the obstacles to public participation in the supervision of medical insurance funds,distill their commonalities,and propose strategies to break them down.Methods The preliminary obstacles were obtained through literature research and interviews with 22 public,modified and perfected through consultation with 12 experts and the fuzzy Delphi method,and the dimensions of each obstacle were determined through 200 questionnaires and factor analysis.Results Public participation in medical insurance funds supervision is hindered by 18 factors,including"medical insurance knowledge is too specialized,unable to participate","lack of understanding of policies related to medical insurance funds supervision",and"inability to identify fraudulent insurance behaviors".They can be categorized into four dimensions:costs and consequences of participation,subjective factors of participation,knowledge of medical insurance funds supervision,and external environment factors,with a cumulative contribution rate of 68.034%.Conclusion The four dimensions constitute the main obstacles to public participation in the supervision of medical insurance funds.Efforts should be made from the aspects of reducing the cost of participation,safeguarding the consequences,enhancing the awareness,improving the knowledge,and creating a social atmosphere,to form a coordinated system of supervision of medical insurance funds.

Objective:This study investigated the independent risk factors for lymph node metastasis（LNM）in high-risk prostate cancer（HRPCa）patients undergoing robot-assisted radical prostatectomy（RARP），and constructed a nomogram model based on clinical data to improve the accuracy and clinical practicality of preoperative prediction of LNM.Methods:A retrospective analysis was conducted on the clinical data of 218 HRPCa patients who received RARP treatment at the First Medical Center of the PLA General Hospital from January 2020 to March 2025 as the modeling group. The age of the modeling group was（66.91±6.94）years old. 75 cases（34.40%）had a history of smoking，and 48 cases（22.02%）had a history of drinking. There were a body mass index（BMI）of 25.55（23.58，27.00）kg/m 2，a total prostate-specific antigen（tPSA）of 20.59（10.42，30.61）ng/ml，a free prostate-specific antigen（fPSA）of 1.87（1.04，3.26）ng/ml，a prostate volume（PV）of（41.19±21.00）ml，a prostate-specific antigen density（PSAD）of 0.52（0.30，0.84）ng/ml 2. Among the patients，60 cases（27.52%）had a preoperative biopsy Gleason score >8，and the percentage of positive biopsy cores（PPBC）was 50%（31%，80%）. Thirty-one patients（14.22%）were staged clinically as >T 2c. The diagnostic criteria for high-risk prostate cancer（HRPCa）were defined as meeting any one of the following：PSA >20 ng/ml，Gleason score on prostate biopsy ≥8，or clinical stage ≥T 3. Among the 218 patients in the modeling cohort，67 cases（30.73%）met two of the criteria，and 7 cases（3.21%）met all three criteria. All 218 patients underwent RARP，and based on postoperative pathology，they were divided into the LNM group and the non-LNM group. The relationship between the number of diagnostic criteria met and the occurrence of LNM was analyzed. An external validation cohort included 42 HRPCa patients who underwent RARP at the Third，Fifth Medical Centers of the PLA General Hospital between January 2023 and May 2025. Their mean age was（66.79±5.92）years. Eighteen patients（42.86%）had a smoking history，and nine（21.43%）had a history of alcohol consumption. The median BMI was 26.00（23.80，27.13）kg/m 2. The median tPSA level was 17.34（8.97，27.30）ng/ml. The median fPSA was 1.51（0.83，2.52）ng/ml，and the median PV was（35.57 ± 15.25）ml. The median PSAD was 0.57（0.23，0.87）ng/ml 2，and the median PPBC was 58%（36%，71%）. Three patients（7.14%）had a clinical stage >T 2c，and 12 patients（28.57%）had a Gleason score >8 on preoperative biopsy. Univariate and multivariate binary logistic regression analyses were used to identify independent risk factors for LNM，and a nomogram model was constructed based on these factors. The predictive performance of the model was evaluated using receiver operating characteristic（ROC）curves and calibration plots，and the model was validated in the external cohort. Result:According to postoperative pathology，45 patients were classified into the LNM group，and 173 into the non-LNM group. The probability of LNM increased proportionally with the number of diagnostic criteria met for HRPCa（meeting two criteria： OR = 4.762，95% CI 2.323-9.761， P < 0.01；meeting three criteria： OR = 10.667，95% CI 2.187-52.025， P=0.003）. Binary logistic regression analysis revealed that age（ OR=0.913，95% CI 0.859-0.971， P = 0.004），tPSA（ OR=1.039，95% CI 1.018-1.061， P<0.01），PPBC（ OR = 5.656，95% CI 1.101-29.056， P = 0.038），and clinical T stage（T 2c stage： OR=2.945，95% CI 0.888-9.769， P=0.077；>T 2c stage OR = 18.351，95% CI 4.790-70.306， P < 0.01）were independent risk factors for postoperative LNM in HRPCa patients after RARP. The ROC curve of the nomogram model based on these factors showed an area under the curve（AUC）of 0.853（95% CI 0.790-0.917）. In the external validation cohort，the nomogram achieved an AUC of 0.743（95% CI 0.556-0.929）. The calibration plots demonstrated good agreement between the predicted probabilities and actual observations. Conclusions:Age，tPSA，PPBC，and clinical T stage were independent predictors of postoperative LNM in HRPCa patients undergoing RARP. The greater the number of HRPCa diagnostic criteria met，the higher the likelihood of postoperative LNM. The nomogram developed in this study could effectively predict the risk of LNM in HRPCa patients after RARP.

Objective:To investigate the risk factors for positive surgical margins（PSM）after robot-assisted radical prostatectomy（RARP），and to develop and validate a predictive nomogram.Methods:We retrospectively analyzed the clinicopathological data of 874 prostate cancer patients who underwent RARP performed by a single surgeon at the First Medical Center of Chinese PLA General Hospital between January 2012 and December 2018. Patients were divided into positive surgical margin（n=327）and negative surgical margin（n=547）groups based on postoperative margin status.The PSM group had significantly higher preoperative median tPSA［31.200（19.050，54.400）ng/ml vs. 15.050（9.840，27.590）ng/ml， P<0.01］，higher proportion of patients with PSAD>1 ng/ml 2［49.5%（162/327）vs. 21.2%（116/547）， P<0.01］，biopsy Gleason score ≥8［33.3%（109/327）vs. 21.2%（116/547）， P<0.01］，ISUP grade 4-5［33.3%（109/327）vs. 21.2%（116/547）， P<0.01］，clinical T stage ≥cT 3［11.3%（37/327）vs. 4.2%（23/547）， P<0.01］，and high-risk classification［82.3%（269/327）vs. 55.9%（306/547）， P<0.01］compared to the negative surgical margin group. Conversely，the PSM group had a lower prevalence of hypertension［29.7%（97/327）vs. 40.2%（220/547）， P=0.002］.Patients were randomly split into a training cohort（n=656，75%）and an internal validation cohort（n=218，25%）. An external validation cohort included 71 patients who underwent RARP by different surgeons between January 2014 and December 2016. No significant differences in baseline characteristics were observed between cohorts（ P>0.05）.Univariate and multivariate logistic regression analyses identified independent predictors of PSM，which were incorporated into a nomogram. Predictive performance was assessed using receiver operating characteristic（ROC）curves，decision curve analysis（DCA），and calibration curve. Internal and external validations were performed. Results:The PSM group had longer postoperative hospitalization［6（5，8）vs. 6（5，7）days， P=0.028］，higher rates of pathologic Gleason score ≥8［41.5%（115/277）vs. 24.9%（111/446）， P<0.01］，ISUP grade 4-5［41.5%（115/277）vs. 24.9%（111/446）， P<0.01］，pT 3 stage［52.3%（171/327）vs. 17.4%（95/547）， P<0.01］，pN 1 stage［12.8%（42/327）vs. 3.8%（21/547）， P<0.01］，extracapsular extension［52.3%（171/327）vs. 17.4%（95/547）， P<0.01］，and seminal vesicle invasion［34.6%（113/327）vs. 9.1%（50/547）， P<0.01］.Multivariate analysis identified elevated tPSA（ OR=1.014，95% CI 1.004—1.024，P=0.006）and PSAD ≥0.15 ng/（ml/g）（ OR=11.638，95% CI 1.450—93.396，P=0.021）as independent risk factors for PSM. The area under the ROC curve（AUC）of the nomogram constructed based on the above variables was 0.770（95% CI 0.735—0.805）. The AUC values for the internal and external validation sets were 0.698（95% CI 0.630—0.767）and 0.643（95% CI 0.513—0.774），respectively. The calibration curve demonstrated good agreement between the predicted and observed outcomes，and the DCA indicated that the predictive model has potential clinical utility in decision-making. Conclusion:tPSA and PSAD were identified as independent risk factors for PSM. The nomogram constructed based on these two independent predictive variables effectively predicted PSM after RARP.

Objective:To define the concept of public value on digital supervision of medical insurance funds and to interpret its basic characteristics.Methods:Based on defining the concept of"public value"using the atomic atlas method,the formal logic definition method is used to define the"public value on digital supervision of medical insurance funds".Results:Among 47 concepts related to"public value",public,citizen,collective,and preference are the core elements;negotiation,utility,and expectation are the quasi-core elements;government,outcome,and common are the important elements;and integration,construction,and appeal are the non-important elements.The"public value on digital supervision of medical insurance fund"can be defined as"in the practice of digital supervision of the health insurance fund,citizens' value demands and expectations,and the degree of satisfaction of these demands and expectations,based on their knowledge and basic value judgments of the health insurance system and digital technology,and formed through a wide range of value-constructing mechanisms,such as social communication and political consultation."Conclusion:The public value on digital supervision of medical insurance funds has the characteristics of people-centeredness,the construction of multi-subject negotiation,and the integration of multiple value dimensions.These features together constitute the rich connotation of the public value of digital supervision of medical insurance funds,which provides a certain reference for promoting the modernization and governance of healthcare insurance and the construction of digital government.

Chronic pancreatitis is a chronic inflammatory disease characterized by progre-ssive fibrosis of pancreatic tissue. Its pathological features primarily include parenchymal fibrosis, intraductal stone formation or calcification deposits, as well as segmental stenosis and dilation of the pancreatic duct. Prolonged chronic inflammatory stimulation not only leads to progressive pancreatic dysfunction but may also trigger the formation of pancreatic pseudocysts and even malignant transformation. In the comprehensive treatment of chronic pancreatitis, the core clinical goals are the removal of pancreatic duct stones, restoration of unobstructed pancreatic duct drainage, and preservation of residual pancreatic function. Traditional treatment strategies have been based on the principle of progressive intervention and early surgical management. In recent years, with advancements in extracorporeal shock wave lithotripsy, the application of new techniques such as endoscopic retrograde cholangiopancreatography combined with laser lithotripsy under direct cholan-gioscopic visualization, and improvements in pancreas-preserving surgical approaches, the debate over the superiority of progressive intervention versus early surgical treatment has intensified. Against this backdrop, the treatment mode of Xi′an Jiaotong University Pancreatic Disease Center (hereinafter referred to as "Western Pancreas") has emerged, emphasizing a personalized, multimodal treatment strategy based on different types of pancreatic duct stones. The treatment mode of "Western Pancreas" integrates lithotripsy, endoscopic treatment, and surgical interventions to optimize patient outcomes. By conducting a comprehensive analysis of domestic and international pancreatic duct stone classi-fication systems and drawing from our team′s clinical experience in managing over a thousand cases of chronic pancreatitis, the authors have further refined and proposed a classification system for pancreatic duct stones under the treatment mode of "Western Pancreas". This refinement aims to enhance the overall diagnostic and therapeutic standards for chronic pancreatitis.

Objective To construct a visual imaging decision model for evaluating the prognosis of hepatocellular carcinoma(HCC)patients treated with interventional therapy based on MRI features.Methods A total of 130 HCC patients were selected.All of them underwent MRI examination upon admission,and then the interventional therapy was implemented after clinical evaluation.The patients were followed up for 2 years after the last interventional therapy,and then were divided into poor prognosis group(50 cases)and good prognosis group(80 cases)according to the follow-up results.The risk factors affecting the poor prognosis of HCC patients treated with interventional therapy were screened.A nomogram model was constructed based on the risk factors,and its prediction efficiency was then evaluated.Results The incomplete capsule,unsmooth tumor margin,portal vein tumor thrombus,cirrhosis,apparent diffusion coefficient(ADC)value,red blood cell distribution width within 24 h after admission,and aspartate aminotransferase were significantly different between the poor prognosis group and the good prognosis group(P＜0.05),and these indicators were the risk factors affecting the poor prognosis of HCC patients treated with interventional therapy(P＜0.05).Based on the above risk factors,a nomogram model of poor prognosis risk for the HCC patients treated with interventional therapy was constructed,and the sensitivity,specificity,and area under the curve(AUC)for predicting poor prognosis of HCC patients treated with interventional therapy were 90.00％,81.80％and 0.899[95％confidence interval(CI)0.827-0.972],respectively.Conclusion The risk nomogram model of poor prognosis of HCC patients treated with interventional therapy based on incomplete capsule,unsmooth tumor margin,portal vein tumor thrombus,cirrhosis,ADC value,red blood cell distribution width,and aspartate aminotransferase has good predictive efficacy.

Objective:To define the concept of public value on digital supervision of medical insurance funds and to interpret its basic characteristics.Methods:Based on defining the concept of"public value"using the atomic atlas method,the formal logic definition method is used to define the"public value on digital supervision of medical insurance funds".Results:Among 47 concepts related to"public value",public,citizen,collective,and preference are the core elements;negotiation,utility,and expectation are the quasi-core elements;government,outcome,and common are the important elements;and integration,construction,and appeal are the non-important elements.The"public value on digital supervision of medical insurance fund"can be defined as"in the practice of digital supervision of the health insurance fund,citizens' value demands and expectations,and the degree of satisfaction of these demands and expectations,based on their knowledge and basic value judgments of the health insurance system and digital technology,and formed through a wide range of value-constructing mechanisms,such as social communication and political consultation."Conclusion:The public value on digital supervision of medical insurance funds has the characteristics of people-centeredness,the construction of multi-subject negotiation,and the integration of multiple value dimensions.These features together constitute the rich connotation of the public value of digital supervision of medical insurance funds,which provides a certain reference for promoting the modernization and governance of healthcare insurance and the construction of digital government.