Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

ObjectiveTo analyze the research hotspots and development trends in the field of spinal cord stimulation (SCS) for spinal cord injury (SCI). MethodsLiterature about SCS for SCI was retrieve from the Web of Science (WOS) Core Collection database, with a time range from January, 1999 to July, 2025. VOSviewer 1.6.20 and CiteSpace 6.4.R2 were used to analyze the annual publication volume, countries, authors, institutions, journals and keywords. ResultsA total of 636 literatures were included. From 1999 to 2025, the overall publication trend in this field showed an upward trajectory, with recent years fluctuating but tending to stabilize. The country with the most publications was the United States (429 papers), followed by Russia (98 papers) and China (70 papers). The institution with the highest number of publications was the University of California, Los Angeles (76 papers), the author with the most publications was V. Reggie Edgerton (70 papers), and the journal with the most publications was Journal of Clinical Medicine (31 papers). The most frequently cited study focused on exploring the combination of epidural spinal cord stimulation with task-specific training to restore motor function in patients with complete SCI. Keyword analysis showed that the research hotspots in this field were mainly focused on neuroregulation mechanisms, recovery of motor and autonomic nervous dysfunction, artificial intelligence, closed-loop stimulation and brain-computer interface technology innovations. In recent years, the research focus gradually shifted from basic mechanisms to personalized and precise multifunctional rehabilitation strategies. ConclusionThe field of SCS for SCI has undergone phases of basic mechanism exploration and clinical application expansion. Current research hotspots and future trends focus primarily on the development of new stimulation paradigms and combined innovative technologies.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

Objective:To analysis the influenced factors of readmission in hospital among patients with mood disorder,construct predictive models and compare the predictive performance of the models.Methods:The electron-ic medical record data of patients with mood disorder admitted to Beijing Anding Hospital from January 2010 to De-cember 2018 were retrospectively collected.Utilizing stepwise logistic regression to analyze the related factors of re-admission in patients with mood disorder.Logistic regression,support vector machine,random forest,extreme gradi-ent boosting(XGBoost)algorithms and convolutional neural networks(CNN)were used to construct a readmission prediction model and compare the predictive performances of the different models by using the accuracy,precision,recall,et.al.Results:A total of 6 234 patients with mood disorder were enrolled,24.9％(n=1 549)patients were readmitted after discharge.The stepwise logistic regression results revealed that readmissions were more likely to occur in patients with mood disorder who were female,had comorbidities,had a treatment outcome of cure,were treated with MECT and were on second-generation antipsychotics(OR=1.26,1.68,1.26,1.35,1.18).The CNN model demonstrated the highest accuracy,precision,and F1 scores,all at 0.87,with a recall of 0.86.The random forest achieved a recall of 0.86 and an AUC of 0.95.Conclusion:Readmission of patients with mood disorder is influenced by a multitude of factors.The convolutional neural networks and random forest models outperform other models in prediction.

OBJECTIVE To evaluate the immunoprotection effect of a novel inactivated whole cell vaccine against Acinetobacter baumannii based on ultrasonic microbubble physical damage technique(IWC)and explore its poten-tial of clinical transformation.METHODS Totally 48 C57BL/6 mice were randomly assigned to divide into three groups and receive the nasal inoculation of corresponding preparations,the IWC group and the paraformalde-hyde inactivated vaccine group were inoculated with 20 μl of 1× 107 CFU vaccine,the control group was treated with 20 μl phosphate buffered salt solution.The infection models were established 7 days after intraperitoneal in-jection of a lethal dose of A.baumannii.The 7-day mortality rates of the mice were statistically analyzed after tox-in attack.The counts of colonized bacterial colonies on lung and spleen tissues were determined by plate count method after toxin attack for 24 hours.The levels of inflammatory factors interleukin(IL)-6,tumor necro-sis factor α(TNF-α)and IL-1β in the lung tissues were detected by enzyme-linked immunosorbent assay(ELISA),and the pathological damage was observed.RESULTS The survival rate of the IWC group was higher than that of the control group,and the counts of colonized bacterial colonies on lung and spleen tissues were less in the IWC group than those in the control group(P＜0.05).As compared the paraformaldehyde inactivated vaccine group,the survival rate of the IWC group increased by 10.00％,and the counts of colonized bacterial colonies on the lung tissues were slightly less in the IWC group than those in the paraformaldehyde inactivated vaccine group(P＜0.05),and the counts of colonized bacterial colonies on spleens were basically the same.The levels of lung tis-sue inflammatory factors of the IWC group were lower than those of the other two groups(P＜0.05).The patho-logical damage was alleviated,and the IWC group was superior to the control group in the integrity of alveolar structure.CONCLUSIONS IWC can maintain the immunogenicity of pathogens through physical damage technique,effectively activate the immune response of the hose,and reduce the bacterial load and inflammatory injury,show-ing better immunoprotection effect than the traditional chemical inactivation method.The study has provided ex-perimental bases for development of novel,specific,safe and highly efficient vaccine as well as new ideas and strategies for clinical prevention and treatment of A.baumannii infection.

Objective To design an intelligent monitoring platform for adverse drug reactions(ADRs)to solve the problems of the traditional ADR monitoring mode.Methods The ADR intelligent monitoring platform was designed based on artificial intelligence and big data technologies,which was developed with Browser/Server(B/S)architecture,C#programming language and.NET development tool.There were five functional modules involved in the platform for ADR knowledge base,monitoring rule setting,intelligent monitoring,report management and statistical analysis.Results The platform realized the full-process management of ADR intelligent monitoring,reporting,review and statistical analysis,which enhanced the ADR report in quantity,quality and timeliness.Conclusion The platform contributes to improving the monitoring of ADR and patient medication safety.[Chinese Medical Equipment Journal,2025,46(9):33-38]

Objective:To investigate the predictive value of endothelial activation and stress index(EASIX)for the prognosis of patients with mantle cell lymphoma(MCL).Methods:A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023,had therapeutic indications and received standard treatment.Results:A total of 66 patients were included and divided into high EASIX group and low EASIX group,according to a cutoff value of 0.97 determined by the receiver operating characteristic(ROC)curve.Multivariate Cox regression analysis showed that prealbumin＜0.2 g/L,high EASIX,and ECOG PS score ≥2 were independent risk factors influencing overall survival(OS)in MCL patients.The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months,and the median progression-free survival was 8.8 and 26.0 months,respectively.The proportions of patients with ECOG PS score ≥2 and prealbumin＜0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group.Conclusion:At the time of initial diagnosis,EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL.Furthermore,patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.

BACKGROUND:The highest incidence of spinal fracture is in the thoracolumbar segment,and its symptoms are back pain,posterior convexity deformity,activity limitation,or with spinal cord nerve injury causing lower limb pain,numbness,and even paraplegia and other complications.The finite element method is a digital computer modeling technique,which can simulate the physical model and carry out force analysis realistically.OBJECTIVE:To review the application of finite element method in thoracolumbar spine fractures.METHODS:We searched the Chinese and English literature databases PubMed,Web of Science,and CNKI for relevant literature on the application of the finite element analysis method in spinal thoracolumbar fracture published before March 2024.The search terms in Chinese and English were:finite element analysis methods,biomechanical phenomena,stress analysis,thoracolumbar fractures,spinal fractures.Finally,55 papers were included.RESULTS AND CONCLUSION:(1)The exploration of thoracolumbar fractures caused by different etiologies(osteoporotic,traumatic,and pathological)through the finite element method is conducive to a deeper understanding of the biomechanics of various types of thoracolumbar fractures,and to improve the individualized and fine-tuned treatment of thoracolumbar fractures.(2)The finite element analysis of a single sample or a small number of samples has the chance,and a larger number of samples are required for the future finite element analysis to reduce the chance caused by the sample.(3)The rigid structure of bones alone cannot meet the biomechanical working conditions of the integrity of the physical object,and future finite element models need to incorporate all the structures of the physical object(e.g.,soft tissues,such as muscles and ligaments)as far as possible.(4)The finite element method has been used in more studies on osteoporotic and traumatic thoracolumbar spine fractures,which will need to be more in-depth in the future,and less in the field of pathologic thoracolumbar fractures,which has a wider scope for future research.

Objective To explore the risk factors for postoperative bleeding after endoscopic resection of gastric gastrointestinal stromal tumor(gGIST)and to construct prediction models using 4 different machine learning algorithms for accurately predicting postoperative bleeding.Methods The clinical data of gGIST patients were collected,and the patients were randomly divided into a training cohort(n=502)and a validation cohort(n=130)at an 8:2 ratio.Synthetic minority over-sampling technique-nominal continuous was used for oversampling in the training cohort.Four prediction models were constructed using gradient boost machine(GBM),deep learning,generalized linear model and distributed random forest,separately;and in addition,the least absolute shrinkage and selection operator was used to screen variables and construct a traditional Logistic regression model.Model performance was evaluated by calculating the area under the receiver operating characteristic curve(AUC),sensitivity,specificity,accuracy,positive predictive value and negative predictive value.Interpretability analyses,including feature importance,SHapley additive exPlanation and force plot,were performed on the optimal model,and a practically applicable web application was developed.Results Among 632 patients,78(12.3%)experienced postoperative bleeding.In the validation cohort,GBM model performed best among 5 prediction models,with an AUC value of 0.889 and a 95%CI of 0.829-0.948,superior to the other 4 models.Variable importance analysis identified surgeon experience,operation time,intraoperative hemorrhage,tumor size as the factors affecting postoperative bleeding prediction.The SHapley additive exPlanation plot and force plot showed the distribution characteristics of variables in the binary classification prediction results and the effect of each variable on the prediction results.Conclusion GBM model has high predictive value for postoperative bleeding following endoscopic resection of gGIST,and the construction of the web application facilitates its clinical use.

Objective To explore the influencing factors of urinary dysfunction in patients with rectal cancer after laparoscopic surgery,and to construct and validate a column chart prediction model.Methods A retrospective analysis was conducted on the clinical data of 415 rectal cancer patients in our hospital from January 2021 to April 2024.According to the computer-generated allocation order,they were stochastically grouped into a modeling group of 311 cases and a validation group of 104 cases in a 3∶1 ratio.The modeling group was further separated into a urinary dysfunction group of 55 cases and a non urinary dysfunction group of 256 cases.The patient's sex,diabetes history,tumor diameter and other relevant data were collected;MultivariateLogisticregression analysis was used to screen for risk factors;R software was used to construct a column chart prediction model for predicting urinary dysfunction in patients with colorectal cancer after laparoscopic surgery;The Hosmer-Lemeshow test,ROC curve,calibration curve,and DCA curve were used to validate the predictive performance of the column chart model.Results Male[OR(95％CI)=3.512(1.637～7.533),P=0.001],diabetes[OR(95％CI)=3.684(1.639～8.280),P=0.002],tumor diameter ≥ 5 cm[OR(95％CI)=4.459(1.993～9.979),P=0.000],large intraoperative bleeding[OR(95％CI)=1.018(1.011～1.026),P=0.000],anterior resection of rectum combined with abdominal perineum resection[OR(95％CI)=3.885(1.901～7.940),P=0.000]were Independent risk factors for postoperative urination dysfunction in rectal cancer patients after laparoscopic surgery.In internal and external validations,the Hosmer-Lemeshau test for the column chart model showed x2=0.159,P=0.254＞0.05,and x2=5.991,P=0.648＞0.05.The areas under the receiver operating characteristic curve were 0.846 and 0.828,respectively.The calibration curve indicated that the simulated curve had a similar trend to the actual curve,indicating good discrimination and calibration of the column chart prediction model.Clinical decision curve analysis results showed that when the high-risk threshold probability was between 0.05 and 0.98,the column chart prediction model could produce better clinical benefits.Conclusion The column chart model constructed by integrating independent risk factors for urinary dysfunction in rectal cancer patients after laparoscopic surgery has high predictive value.