ObjectiveTo analyze the risk factors for long-term cardiovascular events in patients undergoing long-term peritoneal dialysis （PD）， and to construct and validate a visual nomogram prediction model based on multiple parameters. MethodsA prospective cohort study was conducted， consecutively enrolling 248 maintenance PD patients （dialysis duration ≥ 3 months）. Demographic characteristics， clinical indicators， laboratory parameters， and echocardiographic indices （including left ventricular ejection fraction ［LVEF］， ratio of early diastolic mitral inflow velocity to early diastolic mitral annular velocity （E/e’）， etc.） were collected. The composite endpoint was defined as the occurrence of cardiovascular events or cardiovascular death， with non-cardiovascular death as the competing risk and loss to follow-up or the end of follow-up as censoring events. Fine-Gray competing risks model was used to screen independent predictors， based on which a nomogram model was constructed. Internal validation was performed using the Bootstrap method （1 000 resamplings）， and the concordance index （C-index） and time-dependent receiver operating characteristic （time-dependent ROC） curve were calculated to evaluate the model performance. ResultsWith a median follow-up of 29 months （interquartile range： 24–35 months）， 88 patients （35.48%） reached the composite endpoint， including 80 cases of cardiovascular events and 8 cases of cardiovascular death， and 4 patients died of non-cardiovascular causes. Multivariate Fine-Gray analysis revealed that age， diabetes mellitus， hemoglobin （HGB） level and E/e' ratio were independent influencing factors of the composite endpoint. Specifically， each 1-year increase in age was associated with a 3.0% increase in the risk of the composite endpoint （HR=1.030， P=0.006）； patients with diabetes mellitus had a 167.9% higher risk compared with non-diabetic patients （HR=2.679， P=0.007）； each 1g/L increase in HGB level contributed to a 1.5% reduction in the risk （HR=0.985， P=0.003）； and each 0.1 increase in E/e' ratio led to a 7.2% increase in the risk （HR=1.072， P=0.045）. The nomogram model had a C-index of 0.76 （95% CI： 0.698–0.820）， and the AUC of the time-dependent ROC curve reached 0.849 at 23 months of follow-up. ConclusionIncreased age， complicated with diabetes mellitus， decreased HGB， and elevated E/e' ratio are independent risk factors of long-term occurrence of cardiovascular events and cardiovascular death in patients undergoing long-term PD. The nomogram model constructed based on the above variables has good predictive value and clinical applicability， which can provide a reference for cardiovascular risk stratification and individualized intervention in long-term PD patients.

Objective:To investigate the expression characteristics and clinical significance of FOXC1 in colon cancer,and decipher its mo-lecular mechanism in regulating tumor cell proliferation and apoptosis.Methods:The GEPIA database was employed to analyze the expres-sion of FOXC1 and its correlation with prognosis in colon cancer.Differential expression of FOXC1 was detected by qRT-PCR and Western blot in colon cancer cells(HCT116 and SW620)and normal colon epithelial cells(NCM460),and stable FOXC1-knockdown(sh-FOXC1)cell lines were established.Western blot,flow cytometry,CCK-8,and plate colony formation assays were performed to analyze the effects of FOXC1 knockdown on cell proliferation,cell cycle,and apoptosis.Furthermore,the downstream signaling pathway was verified using Rap1 overexpression rescue experiments.Results:FOXC1 mRNA expression was significantly higher in colon cancer tissues than in normal tissues(P<0.001).FOXC1 overexpression was nearing significance in relation to tumor staging(P=0.053),and patients with high FOXC1 expression had a shorter overall survival(Log-rank P=0.013).After FOXC1 knockdown,the expression of CyclinD1 and Bcl-2 decreased,whereas the ex-pression of Bax increased(P<0.01).The proportion of cells in the G0/G1 phase increased,while the proportion of cells in the S phase de-creased(P<0.001),and the cell proliferation activity and number of colonies formed decreased(P<0.001).Mechanistic studies demonstrated that after FOXC1 knockdown,Rap1 expression was reduced,while the expression of Rap1GAP increased(P<0.05).After restoration of Rap1 expression in FOXC1-knockdown cells,the downregulation of CyclinD1 and Bcl-2 expression and the increase in Bax expression were re-versed(P<0.05),the S phase ratio was increased(P<0.05),and cell proliferation activity and colony formation abilities were also re-scued.Conclusion:FOXC1 promotes colon cancer progression by facilitating Rap1 expression and downregulating Rap1GAP.Targeted inter-vention of the FOXC1-Rap1 signaling axis may emerge as a potential therapeutic strategy.

Objective To investigate the effect of the rs3765467 polymorphism of glucagon-like peptide-1 receptor(GLP-1R)gene on the efficacy of Liraglutide(Lir)in patients with type 2 diabetes mellitus(T2DM)and metabolic associated fatty liver disease(MAFLD).Methods A total of 281 patients with T2DM from May 2022 to May 2023 were selected,including 125 patients with simple T2DM(T2DM group)and 156 patients with T2DM combined with MAFLD(T2DM+MAFLD group).120 healthy individuals during the same period were selected as the control(NC)group.The related indexes of glucose and lipid metabolism were detected.The polymorphism of GLP-1R gene rs3765467 was detected.Results BMI,FPG,HbA1c,HOMA-IR and TG in each group increased in turn(P<0.05),while the distribution frequency of genotype GG and allele G decreased in turn(P<0.05).TC and LDL-C in T2DM and T2DM+MAFLD groups were higher than those in NC group(P<0.05).TC and TG levels in genotype GA/AA patients were significantly higher than those in genotype GG patients(P<0.05).Compared with before treatment,the levels of BMI,FPG,HbA1c,HOMA-IR,TC,TG and LDL-C in T2DM patients with MAFLD were significantly decreased after Lir treatment(P<0.05).There was no significant difference in BMI and related indexes of glucose and lipid metabolism in GG and GA/AA patients before and after Lir treatment(P>0.05).Conclusions The distribution frequency of GG and G allele at rs3765467 of GLP-1R gene is reduced in T2DM patients with MAFLD.The carrying of allele A was associated with increased TC and TG levels,but did not affect the efficacy of Lir in reducing weight and improving glycolipid metabolism.

Objective To investigate the influence of auricular acupressure combined with repetitive transcranial magnetic stimulation(rTMS)on swallowing function and neurological function in stroke pa-tients.Methods A total of 120 patients with dysphagia after stroke admitted to the hospital from January 2022 to June 2023 were selected as the research objects and divided into the control group,the auricular acu-pressure group,the rTMS group and the combined group according to the random number table method,with 30 cases in each group.The control group received routine care,the auricular acupressure group received auric-ular acupressure treatment on the basis of the control group,while the rTMS group received rTMS treatment,and the combined group received both auricular acupressure and rTMS treatment.All interventions lasted 4 weeks.Swallowing function was assessed before and after treatment using Functional Oral Intake Scale(FOIS),modified Mann Assessment of Swallowing Ability(MASA),and Water Swallow Test.Swallowing-related quality of life was evaluated before and after treatment by the Swallowing Quality of Life(SWAL-QOL)questionnaire.Neurological impairment was assessed before and after treatment using National Institu-tes of Health Stroke Scale(NIHSS).Results After treatment,FOIS and MASA scores in the four groups were higher than those before treatment,with the auricular acupressure group and the rTMS group showing higher scores than the control group,and the combination group significantly higher than the other three groups(P<0.05).The overall effectiveness rate for swallowing function in the combination group was 93.33%,significantly higher than 60.00%in the control group,63.33%in the auricular acupressure group,and 73.33%in the rTMS group(P<0.05),while there was no significant difference among the other three groups(P>0.05).After treatment,SWAL-QOL scores in the four groups were higher than that before treat-ment,with the auricular acupressure group and the rTMS group showing higher scores than the control group,and the combination group significantly higher than the other three groups(P<0.05).After treat-ment,NIHSS scores in the four groups were lower than that before treatment,and the combination group had significantly lower scores compared to the other three groups(P<0.05).Conclusion Auricular acupressure combined with rTMS could improve swallowing function and quality of life,and promote neurological function recovery in stroke patients.

Objective:To develop and validate a clinical warning model for severe pediatric community-acquired pneumonia (CAP) using electronic health records.Methods:A retrospective cohort study was conducted, analyzing clinical data of 15 750 children hospitalized for CAP at Wuhan Children′s Hospital between January 1, 2019, and December 31, 2023. Patient data were randomly split into training and testing sets at a 7∶3 ratio. Six supervised machine learning models were constructed in the training set, optimized using five-fold cross-validation, and evaluated in the testing set. Model performance was assessed using ROC-AUC, sensitivity, specificity, positive predictive value, negative predictive value, calibration curves, and clinical decision curve analysis at optimal thresholds. The best-performing model was selected, and SHapley Additive exPlanations (SHAP) were used to interpret feature importance. A program interface was developed based on the model results, enabling integration into clinical decision support systems for automated early warning.Results:A total of 15 750 participants, ranging in age from 28 days to 18 years, were included in the study. The median age was 2 years [interquartile range (IQR): 0-4 years], with 9 555 males (60.67%) and 6 195 females (39.33%). Among them, 2 211 (14.04%) developed severe pneumonia. In the prediction models, XGB outperformed other models with an ROC-AUC of 0.884 (95% CI: 0.870-0.898), sensitivity (0.803, 95% CI: 0.772-0.832), specificity (0.828, 95% CI: 0.816-0.839). Calibration analysis showed strong agreement between predicted and observed risks (Brier score: 0.081, 95% CI: 0.075-0.086). The analysis based on the SHAP method revealed that respiratory rate, heart rate, T-lymphocyte subsets, and red blood cell volume distribution width-SD are predictive factors for severe progression of community-acquired pneumonia (CAP) in children. Conclusion:An interpretable machine learning model was developed for the early detection and personalized treatment planning of severe CAP in children, providing valuable support to clinicians.

Objective: To investigate the prevalence and influencing factors of menopausal syndrome among postmenopausal women in Pan'an County, Zhejiang Province, so as to provide the basis for guiding the health management of postmenopausal women. Methods: From May 2023 to April 2024, the postmenopausal women aged 40 to 69 years in Pan'an County were selected using the random cluster sampling method. Demographic information, lifestyle and prevalence of gynecological diseases were collected through questionnaire surveys. The prevalence of menopausal syndrome was assessed by modified Kupperman Score Scale. Factors affecting menopausal syndrome were analyzed by a multivariable logistic regression model. Results: A total of 816 postmenopausal women were surveyed, with an mean age of (57.63±2.92) years and a mean natural menopause age of (49.85±2.13) years. There were 574 cases with menopausal syndrome, with a prevalence of 70.34%. Flashes and sweating, insomnia and irritability were common symptoms, accounting for 62.87%, 47.43% and 41.18%, respectively. Multivariable logistic regression analysis showed that monthly personal income of ≤5 000 yuan (<3 000 yuan, OR=3.124, 95%CI: 1.829-5.335; 3 000-5 000 yuan, OR=2.399, 95%CI: 1.370-4.201) and having gynecological diseases (OR=1.970, 95%CI: 1.292-3.004) were associated with a higher risk of menopausal syndrome, while average (OR=0.141, 95%CI: 0.072-0.276) or sufficient sleep quality (OR=0.095, 95%CI: 0.049-0.185) were associated with a lower risk of menopausal syndrome. Conclusion The prevalence of menopausal syndrome among postmenopausal women in Pan'an County is relatively high, and is mainly influenced by personal economic status, sleep quality and the presence of gynecological diseases.

With the development of science and technology worldwide, the blooming of artificial intelligence (AI) and big data has brought new opportunities and challenges to the promotion of the research capacity of professional master's students in oncology. The construction of the new medical education in China aims to cultivate high-level medical talents with comprehensive multidisciplinary skills and innovative abilities to flexibly solve complex problems at the frontier of medicine. In this context, professional master's students in oncology, who are facing problems such as low scientific research output and uneven quality and needing improving scientific research literacy, have been required to develop into compound talents with both clinical and research prowess. To cultivate and promote the research capacity of professional master's students in oncology, the key steps include accelerating the construction of AI education and databases, highlighting the cultivation of their scientific research capacity, implementing and fostering the cultivation of innovative ability and scientific research thinking, piloting joint cultivation models by engineering universities and medical universities, emphasizing the construction of the curriculum and teacher team for oncology, piloting the multidisciplinary mode and COME mode, and establishing a multidisciplinary cooperation network.

Objective:To develop and validate a clinical warning model for severe pediatric community-acquired pneumonia (CAP) using electronic health records.Methods:A retrospective cohort study was conducted, analyzing clinical data of 15 750 children hospitalized for CAP at Wuhan Children′s Hospital between January 1, 2019, and December 31, 2023. Patient data were randomly split into training and testing sets at a 7∶3 ratio. Six supervised machine learning models were constructed in the training set, optimized using five-fold cross-validation, and evaluated in the testing set. Model performance was assessed using ROC-AUC, sensitivity, specificity, positive predictive value, negative predictive value, calibration curves, and clinical decision curve analysis at optimal thresholds. The best-performing model was selected, and SHapley Additive exPlanations (SHAP) were used to interpret feature importance. A program interface was developed based on the model results, enabling integration into clinical decision support systems for automated early warning.Results:A total of 15 750 participants, ranging in age from 28 days to 18 years, were included in the study. The median age was 2 years [interquartile range (IQR): 0-4 years], with 9 555 males (60.67%) and 6 195 females (39.33%). Among them, 2 211 (14.04%) developed severe pneumonia. In the prediction models, XGB outperformed other models with an ROC-AUC of 0.884 (95% CI: 0.870-0.898), sensitivity (0.803, 95% CI: 0.772-0.832), specificity (0.828, 95% CI: 0.816-0.839). Calibration analysis showed strong agreement between predicted and observed risks (Brier score: 0.081, 95% CI: 0.075-0.086). The analysis based on the SHAP method revealed that respiratory rate, heart rate, T-lymphocyte subsets, and red blood cell volume distribution width-SD are predictive factors for severe progression of community-acquired pneumonia (CAP) in children. Conclusion:An interpretable machine learning model was developed for the early detection and personalized treatment planning of severe CAP in children, providing valuable support to clinicians.

Objective To investigate the effect of the rs3765467 polymorphism of glucagon-like peptide-1 receptor(GLP-1R)gene on the efficacy of Liraglutide(Lir)in patients with type 2 diabetes mellitus(T2DM)and metabolic associated fatty liver disease(MAFLD).Methods A total of 281 patients with T2DM from May 2022 to May 2023 were selected,including 125 patients with simple T2DM(T2DM group)and 156 patients with T2DM combined with MAFLD(T2DM+MAFLD group).120 healthy individuals during the same period were selected as the control(NC)group.The related indexes of glucose and lipid metabolism were detected.The polymorphism of GLP-1R gene rs3765467 was detected.Results BMI,FPG,HbA1c,HOMA-IR and TG in each group increased in turn(P<0.05),while the distribution frequency of genotype GG and allele G decreased in turn(P<0.05).TC and LDL-C in T2DM and T2DM+MAFLD groups were higher than those in NC group(P<0.05).TC and TG levels in genotype GA/AA patients were significantly higher than those in genotype GG patients(P<0.05).Compared with before treatment,the levels of BMI,FPG,HbA1c,HOMA-IR,TC,TG and LDL-C in T2DM patients with MAFLD were significantly decreased after Lir treatment(P<0.05).There was no significant difference in BMI and related indexes of glucose and lipid metabolism in GG and GA/AA patients before and after Lir treatment(P>0.05).Conclusions The distribution frequency of GG and G allele at rs3765467 of GLP-1R gene is reduced in T2DM patients with MAFLD.The carrying of allele A was associated with increased TC and TG levels,but did not affect the efficacy of Lir in reducing weight and improving glycolipid metabolism.

With the development of science and technology worldwide, the blooming of artificial intelligence (AI) and big data has brought new opportunities and challenges to the promotion of the research capacity of professional master's students in oncology. The construction of the new medical education in China aims to cultivate high-level medical talents with comprehensive multidisciplinary skills and innovative abilities to flexibly solve complex problems at the frontier of medicine. In this context, professional master's students in oncology, who are facing problems such as low scientific research output and uneven quality and needing improving scientific research literacy, have been required to develop into compound talents with both clinical and research prowess. To cultivate and promote the research capacity of professional master's students in oncology, the key steps include accelerating the construction of AI education and databases, highlighting the cultivation of their scientific research capacity, implementing and fostering the cultivation of innovative ability and scientific research thinking, piloting joint cultivation models by engineering universities and medical universities, emphasizing the construction of the curriculum and teacher team for oncology, piloting the multidisciplinary mode and COME mode, and establishing a multidisciplinary cooperation network.