Background and Aims:Extrahepatic cholangiocarcinoma(ECCA)is a malignancy with insidious onset,strong invasiveness,and poor prognosis,characterized by a high postoperative recurrence rate and a 5-year overall survival of less than 20％.Most existing prognostic models are based on the Cox proportional hazards model,which is limited by the proportional hazards assumption and linearity constraints.The random survival forest(RSF)model,a novel machine learning algorithm,can capture complex interactions and nonlinear effects among variables;however,its application in ECCA remains scarce.Therefore,this study developed a prognostic model for ECCA patients after radical resection using the RSF algorithm,aiming to provide precise and individualized prognostic assessments and support clinical decision-making.Methods:A total of 515 postoperative ECCA patients from the SEER database(2016-2021)were retrospectively enrolled and randomly divided into a training set(n=361)and a test set(n=154).Demographic and clinical variables were collected.Cox models were developed using univariate and multivariate regression,while RSF models were constructed using variable importance(VIMP)and minimal depth methods.Model performance was evaluated using the concordance index(C-index),time-dependent area under the curve(AUC),Brier scores,calibration plots,and decision curve analysis.Survival differences were assessed using Kaplan-Meier analysis,and interpretability was enhanced through the use of SurvSHAP and SurvLIME.Results:Multivariate Cox regression identified seven independent prognostic factors:age,race,income,T stage,N stage,tumor size,and chemotherapy.The RSF model selected four key predictors:age,tumor size,lymph node positive rate,and chemotherapy.In the test cohort,the RSF model achieved a C-index of 0.751,outperforming the Cox model(0.711).The RSF model yielded AUCs of 0.843,0.749,and 0.814 at 1,2,and 3 years,respectively,with superior calibration,overall performance,and net clinical benefit.Nonlinear associations were observed for lymph node positive rate,age,and tumor size,while chemotherapy was associated with reduced mortality risk.Stratified survival curves indicated poorer prognosis in patients without chemotherapy,lymph node positive rate＞0.1,age＞70 years,or tumor size＞20 mm.Conclusion:The RSF model,based on only four readily available clinical variables,demonstrated superior predictive performance compared with the Cox model.It provides a reliable tool for individualized prognosis and postoperative management in ECCA patients.The integration of interpretability frameworks further enhances its clinical applicability,offering potential to improve survival outcomes and quality of life.

Objective To analyze the distribution characteristics of infectious respiratory particles(IRPs)in hospi-tal waiting rooms,and explore the impact of indoor air environmental on the distribution characteristics of bacterial IRPs.Methods In the summer and winter of 2024,nine waiting rooms in non-infectious departments of three ter-tiary hospitals in a district of Beijing were selected for on-site investigation on basic conditions.Concentration and distribution of particle diameter of cultivable bacteria from 36 air specimens collected by the impacting method were analyzed.Cyclone method was employed to collect 36 IRPs specimens.Major respiratory pathogens were analyzed by fluorescence polymerase chain reaction(PCR).Results The median of the total bacterial count in IRPs in the waiting rooms in summer was 1 035 CFU/m3,which was higher than that in winter(295 CFU/m3),with statisti-cally significant difference(P＜0.05).The orders of medians of the total bacterial count from IRPs of different types in the waiting rooms in both summer and winter were as follows:emergency department waiting room＜re-spiratory department waiting room＜pediatric waiting room＜general outpatient waiting room.There was no sta-tistically significant difference in the total bacterial count among different waiting rooms(P＞0.05).Particle diame-ter of bacterial IRPs in the waiting rooms in summer and winter mainly distributed in the range of＜4.7 μm,ac-counting for 73.77％and 69.44％,respectively.The total number of bacteria in IRPs in the waiting rooms was positively correlated with indoor air temperature,relative humidity,PM10,and PM2.5(all P＜0.01),while nega-tively correlated with indoor wind speed(all P＜0.01).The types of respiratory infectious and non-infectious pathogens detected from IRPs in different types of waiting rooms were different between summer and winter.The pathogens detected in summer were mainly concentrated in respiratory non-infectious pathogens(Escherichia coli,Klebsiella pneumoniae,Staphylococcus aureus).In winter,respiratory infectious pathogens(virus and Mycoplas-ma pneumoniae)were detected.The types of detected pathogens in different types of waiting rooms were different.Non-infectious respiratory pathogens detected from IRPs in winter were mainly Escherichia coli,Klebsiella pneumoniae,and Staphylococcus aureus.Conclusion Particle diameter of bacterial IRPs in the waiting room is mainly＜4.7 μm.These particles can enter the lower respiratory tract of human body,and pose potential risk to health.The detection of main infectious and non-infectious respiratory pathogens from IRPs in waiting rooms suggests risk of exposure to infection for patients and healthcare workers.

At present,reforming and innovating the public health talent training model are the challenges that the construc-tion of new medical in our country.Medical Immunology is the initial driving force in preventive medicine.Based on the course con-struction of Medical Immunology and centering on the core link of post competency of preventive medicine undergraduates,this study comprehensively reshapes the course system of Medical Immunology from the aspects of theoretical courses,practical courses,experi-mental courses,ideological and political courses and assessment methods,so as to provide reference for improving the teaching quality of preventive healthcare undergraduates.

Background and Aims:Extrahepatic cholangiocarcinoma(ECCA)is a malignancy with insidious onset,strong invasiveness,and poor prognosis,characterized by a high postoperative recurrence rate and a 5-year overall survival of less than 20％.Most existing prognostic models are based on the Cox proportional hazards model,which is limited by the proportional hazards assumption and linearity constraints.The random survival forest(RSF)model,a novel machine learning algorithm,can capture complex interactions and nonlinear effects among variables;however,its application in ECCA remains scarce.Therefore,this study developed a prognostic model for ECCA patients after radical resection using the RSF algorithm,aiming to provide precise and individualized prognostic assessments and support clinical decision-making.Methods:A total of 515 postoperative ECCA patients from the SEER database(2016-2021)were retrospectively enrolled and randomly divided into a training set(n=361)and a test set(n=154).Demographic and clinical variables were collected.Cox models were developed using univariate and multivariate regression,while RSF models were constructed using variable importance(VIMP)and minimal depth methods.Model performance was evaluated using the concordance index(C-index),time-dependent area under the curve(AUC),Brier scores,calibration plots,and decision curve analysis.Survival differences were assessed using Kaplan-Meier analysis,and interpretability was enhanced through the use of SurvSHAP and SurvLIME.Results:Multivariate Cox regression identified seven independent prognostic factors:age,race,income,T stage,N stage,tumor size,and chemotherapy.The RSF model selected four key predictors:age,tumor size,lymph node positive rate,and chemotherapy.In the test cohort,the RSF model achieved a C-index of 0.751,outperforming the Cox model(0.711).The RSF model yielded AUCs of 0.843,0.749,and 0.814 at 1,2,and 3 years,respectively,with superior calibration,overall performance,and net clinical benefit.Nonlinear associations were observed for lymph node positive rate,age,and tumor size,while chemotherapy was associated with reduced mortality risk.Stratified survival curves indicated poorer prognosis in patients without chemotherapy,lymph node positive rate＞0.1,age＞70 years,or tumor size＞20 mm.Conclusion:The RSF model,based on only four readily available clinical variables,demonstrated superior predictive performance compared with the Cox model.It provides a reliable tool for individualized prognosis and postoperative management in ECCA patients.The integration of interpretability frameworks further enhances its clinical applicability,offering potential to improve survival outcomes and quality of life.

Objective To analyze the distribution characteristics of infectious respiratory particles(IRPs)in hospi-tal waiting rooms,and explore the impact of indoor air environmental on the distribution characteristics of bacterial IRPs.Methods In the summer and winter of 2024,nine waiting rooms in non-infectious departments of three ter-tiary hospitals in a district of Beijing were selected for on-site investigation on basic conditions.Concentration and distribution of particle diameter of cultivable bacteria from 36 air specimens collected by the impacting method were analyzed.Cyclone method was employed to collect 36 IRPs specimens.Major respiratory pathogens were analyzed by fluorescence polymerase chain reaction(PCR).Results The median of the total bacterial count in IRPs in the waiting rooms in summer was 1 035 CFU/m3,which was higher than that in winter(295 CFU/m3),with statisti-cally significant difference(P＜0.05).The orders of medians of the total bacterial count from IRPs of different types in the waiting rooms in both summer and winter were as follows:emergency department waiting room＜re-spiratory department waiting room＜pediatric waiting room＜general outpatient waiting room.There was no sta-tistically significant difference in the total bacterial count among different waiting rooms(P＞0.05).Particle diame-ter of bacterial IRPs in the waiting rooms in summer and winter mainly distributed in the range of＜4.7 μm,ac-counting for 73.77％and 69.44％,respectively.The total number of bacteria in IRPs in the waiting rooms was positively correlated with indoor air temperature,relative humidity,PM10,and PM2.5(all P＜0.01),while nega-tively correlated with indoor wind speed(all P＜0.01).The types of respiratory infectious and non-infectious pathogens detected from IRPs in different types of waiting rooms were different between summer and winter.The pathogens detected in summer were mainly concentrated in respiratory non-infectious pathogens(Escherichia coli,Klebsiella pneumoniae,Staphylococcus aureus).In winter,respiratory infectious pathogens(virus and Mycoplas-ma pneumoniae)were detected.The types of detected pathogens in different types of waiting rooms were different.Non-infectious respiratory pathogens detected from IRPs in winter were mainly Escherichia coli,Klebsiella pneumoniae,and Staphylococcus aureus.Conclusion Particle diameter of bacterial IRPs in the waiting room is mainly＜4.7 μm.These particles can enter the lower respiratory tract of human body,and pose potential risk to health.The detection of main infectious and non-infectious respiratory pathogens from IRPs in waiting rooms suggests risk of exposure to infection for patients and healthcare workers.

At present,reforming and innovating the public health talent training model are the challenges that the construc-tion of new medical in our country.Medical Immunology is the initial driving force in preventive medicine.Based on the course con-struction of Medical Immunology and centering on the core link of post competency of preventive medicine undergraduates,this study comprehensively reshapes the course system of Medical Immunology from the aspects of theoretical courses,practical courses,experi-mental courses,ideological and political courses and assessment methods,so as to provide reference for improving the teaching quality of preventive healthcare undergraduates.

Objective:Chimeric antigen receptor T-cell(CAR-T)immunotherapy has made major breakthroughs in the treatment of blood tu-mors.However,current CAR-T therapies face several limitations:they require autologous cells,involve a lengthy and costly production pro-cess,and use lentiviral transduction that carry risk of insertional carcinogenesis due to random integration.Therefore,there is an urgent need to develop a universal cost-effective cancer immunotherapy method generating CAR-T cells for in vivo cancer immunotherapy.Meth-ods:This study successfully established an exosome-mediated,T-cell targeted delivery system,demonstrating both precise design and func-tional efficacy for biomedical applications.To optimize CAR-T cell generation the transfection dose was adjusted,and the kinetics of CAR-T cell percentage were recorded.The cytotoxicity of the resulting CAR-T cells was evaluated in vitro by calcein-AM release.To test the tumor-killing in vivo of engineered exosomes,human PBMCs were injected into NPG mice via the tail vein to establish humanized mice,followed by intravenous injection of tumor cells to induce cancer.Results:To overcome the limitations of conditional autologous CAR-T cells,we de-veloped a T cell-targeted exosome system capable of specifically targeting human CD3+,CD4+,and CD8+T cells.CAR-T production was dose-dependent,with transfection efficiency reaching upto 97.8%at 106 particles/cell.Both in vitro cytotoxicity assays and in vivo animal experi-ments demonstrated that exosome-incubated CAR-T cells effectively eliminated CD19-positive Raji cells,highlighting their specificity and therapeutic potential in antigen-directed applications.Conclusions:We successfully established a CD8-targeting exosome delivery system for CAR-T cell production capable of transforming CD8+T cells into functional CAR-T cells,which showed significant tumor-killing ability in vitro and in mice.Compared with the traditional lentiviral vector for the preparation of CAR-T cells in vitro,in vivo-reprogrammed CAR-T cells us-ing our CD8-targeted exosome delivery system,with higher transfection efficiency,shorter production period,lower cost,and eliminated the risk of insertion carcinogenesis.This strategy promises to bring a new era of universal CAR-T medicine,which can improve cancer immuno-therapy and may hold promise as a therapeutic platform to treat various diseases.

ObjectiveTo observe the efficacy of Huoxue Jiedu Formulas （活血解毒方药， HJF） as an adjunctive treatement for patients with binding of stasis and toxin syndrome during the vulnerable period after acute myocardial infarction （AMI） percutaneous coronary intervention （PCI） surgery， and to explore its potential mechanism from the perspective of serum neutrophil extracellular traps （NETs）. MethodsA total of 129 patients with binding of stasis and toxin syndrome within 6 months after PCI for AMI were enrolled and divided into a treatment group （65 cases） and a control group （64 cases） based on patients' willingness to take Chinese herbal medicine. The control group received standard western medical therapy alone， while the treatment group additionally received HJF， one dose daily. Both groups were treated for four weeks. Before and after treatment， TCM syndrome scores were assessed. Seattle angina questionnaire （SAQ） was used to record angina stability and frequency scores， while the short form-36 health survey （SF-36） was employed to assess quality of life across eight dimensions， including physical functioning， role-physical， bodily pain， general health， vitality， social functioning， role-emotional， and mental health. The Pittsburgh sleep quality index （PSQI） was used to evaluate sleep quality， and the patient health questionnaire-15 （PHQ-15） was used to assess psychosomatic symptoms； Duke activity status index （DASI） was used to measure daily physical activity. Serum levels of neutrophil extracellular traps （NET） markers including myeloperoxidase-DNA （MPO-DNA）， neutrophil elastase-DNA （NE-DNA）， and citrullinated histone H3 （CitH3） were measured in 20 patients from the treatment group. ResultsAfter treatment， TCM syndrome score， PSQI score and PHQ-15 score in both groups significantly decreased， while DASI score， angina stability and frequency scores， and all eight dimensions of the SF-36 scale significantly increased （P＜0.05）. Compared to the control group， the treatment group had significantly lower TCM syndrome scores and significantly higher DASI， angina stability and frequency scores （P＜0.05）， as well as higher scores in the SF-36 dimensions of physical functioning， role-physical， social functioning， bodily pain， and vitality （P＜0.05）. After treatment， serum levels of MPO-DNA， CitH3， and NE-DNA in the treatment group were significantly reduced （P＜0.05）. ConclusionHJF combined with conventional therapy can significantly improve angina symptoms， TCM syndrome scores， and psychosomatic conditions in patients with binding of stasis and toxin syndrome during the vulnerable period after AMI. It also enhances quality of life， sleep quality， and daily physical activity. The underlying mechanism may be associated with the inhibition of serum NETs level.

Objective:To explore the independent risk factors for chemoresistance during gemcitabine plus cisplatin (GC) adjuvant chemotherapy in patients with locally advanced bladder cancer after radical cystectomy and to construct a related predictive model.Methods:The clinical data of 228 patients with locally advanced bladder cancer who received GC chemotherapy after radical cystectomy at Beijing Friendship Hospital, Capital Medical University, from January 2013 to June 2024 were retrospectively analyzed. Among them, 184 were males, and 44 were females, with an average age of (68.8±10.6)years and an average body mass index (BMI) of (24.2±3.6)kg/m 2. According to tumor progression during chemotherapy, patients were divided into a chemotherapy-resistant(CR) group ( n=59) and a non-chemotherapy-resistant(NCR) group ( n=169). Independent sample t-test, chi-square test, and non-parametric test were used to compare general clinical characteristics and relevant examination results during chemotherapy between the two groups. Multivariate linear regression analysis was used to identify independent risk factors for GC chemoresistance. Propensity score matching (PSM) was used to match the TNM stage data between the two groups, and Kaplan-Meier and log-rank tests were used to compare overall survival(OS)after matching. Results:The median number of chemotherapy cycles was 3 in the CR group and 4 in the NCR group. Compared with the NCR group, CR patients were younger [(66.3±9.4) years vs.(69.7±10.9)years], had a higher proportion of kidney transplantation history[6.8%(4/59) vs. 0.6%(1/169)], hypertension [50.8%(30/59) vs. 36.1%(61/169)], coronary heart disease[23.7%(14/59) vs.9.5% (16/169)], and hydronephrosis [13.6%(8/59) vs. 4.1%(7/169)](all P<0.05). CR patients had a higher proportion of T 4 stage [20.3% (12/59) vs. 5.9% (10/169)], N 2 stage [42.4% (25/59) vs. 8.3% (14/169)], multifocal tumors at initial diagnosis [59.3% (35/59) vs. 26.6% (45/169)], and larger maximum tumor diameter [2.5 (1.5, 3.4) cm vs. 1.6 (1.2, 2.5) cm] (all P < 0.05). The CR group showed higher proportions of long-term urinary tract infection (UTI) [90.1% (53/59) vs. 7.7% (15/169)], higher systemic immune-inflammation index (SII) [991.6 (451.0, 1577.9) vs. 462.8 (309.0, 766.7)], absolute neutrophil count [6.5(4.1, 7.8)× 10 9/L vs. 3.9 (2.9, 5.1)× 10 9/L], and platelet count [(220.0 ± 96.2)× 10 9/L vs. (191.0 ± 64.8)× 10 9/L], but lower albumin levels [(34.3 ± 4.2) g/L vs. (39.9 ± 3.8) g/L] and albumin-to-globulin ratio (A/G) [(1.2 ± 0.3) vs. (1.3 ± 0.2)] (all P < 0.05). Multivariate linear regression analysis identified only T stage and long-term UTI as independent risk factors for GC chemoresistance( P<0.05).The probability of GC chemoresistance in bladder cancer patients was calculated as: P(Chemoresistance)=[0.155×T stage+ 0.624×(long-term UTI)]×100%(long-term UTI = 1 if present during chemotherapy, otherwise=0). After PSM, survival analysis showed that the median OS was significantly higher in the NCR group (55 months) than that in the CR group (30 months) ( P=0.020). Conclusions:This study demonstrates that advanced T stage and persistent UTI are independent risk factors for GC chemotherapy resistance in locally advanced bladder cancer patients. Based on these findings, a predictive model for chemotherapy resistance probability was constructed using multivariate linear regression analysis.

Objective:To investigate the influence of genetic and environmental factors on the clinical characteristics of upper urinary tract calculi in pediatric patients.Methods:This study was a retrospective case series. The clinical data of 179 children under the age of 14 with upper urinary tract calculi treated at Beijing Friendship Hospital，Capital Medical University，from August 2014 to February 2023 were analyzed. There were 121 males（67.60%）and 58 females（32.40%），with a median age at onset of 2.10（1.14，5.17）years. Thirty-three cases（18.44%）had a family history of urinary stone disease. Stone characteristics was defined by CT，with a median stone burden（sum of the diameters of all stones）of 1.3（1.00，1.60）cm. Fifty-four（30.17%）children had staghorn calculi. Multiple stones were present in 92 cases（51.40%），and bilateral stones in 52 cases（29.05%），with hydronephrosis was present in 119 children（66.48%）. The median follow-up time was 67 months，and 36 children（20.11%）experienced stone recurrence. Dietary habits and related information were collected by electronic questionnaire，including a total of 115 children（64.25%）with an unbalanced diet，101（56.42%）with insufficient water intake，and 32 children（17.88%）with a preference for a high-protein diet. Tap water was used as the source of drinking water by 128 patients（71.51%），and 107（59.78%）took dietary supplements. Whole-exome sequencing revealed that 55 children（30.73%）carried pathogenic mutations in stone-related genes. Binary logistic regression was used for univariate analysis of above risk factors. Variables with P < 0.1 in univariate analysis and without multicollinearity were included in multivariate logistic regression to further screen for independent risk factors. Results:Multivariate analysis confirmed that carrying stone-related pathogenic gene mutations（ OR = 3.06，95% CI 1.25?7.45， P = 0.014）and insufficient water intake（ OR = 3.28，95% CI 1.14?9.47， P = 0.028）were independent risk factors for higher stone burden. A high-protein diet（ OR = 2.40，95% CI 1.03?5.63， P = 0.044），carrying stone-related pathogenic gene mutations（ OR = 4.57，95% CI 2.21?9.46， P<0.01），and a family history of stones（ OR = 3.18，95% CI 1.28 ~ 7.91， P = 0.013）were independent risk factors for staghorn calculi. Multiple stones were closely associated with a family history of stones（ OR = 2.66，95% CI 1.15-6.17， P = 0.022）and carrying stone-related pathogenic gene mutations（ OR = 3.22，95% CI 1.60-6.48， P = 0.001）. Moreover，carrying stone-related pathogenic gene mutations（ OR = 5.19，95% CI 2.52?13.82， P < 0.01）were an independent risk factor for stone recurrence，whereas dietary supplement intake was a protective factor（ OR = 0.26，95% CI 0.11?0.62， P = 0.002）. Conclusions:Genetic and environmental factors play significant roles in the occurrence and development of pediatric upper urinary tract stones. A high-protein diet as well as a positive family history of stones are independent risk factors for staghorn calculi，and insufficient water intake is a critical environmental factor for stone formation，while appropriate use of dietary supplements may help reduce the risk of stone recurrence. Genetic testing indicates that approximately 30% of children carry stone-related pathogenic gene mutations，and these patients prone to severe stone and an increased risk of recurrence.