Objective:To evaluate the safety and complications of external cephalic version(ECV)for term breech presentation and to explore factors influencing the occurrence of ECV-related complications.Methods:Pregnant women with term breech presentation who underwent ECV(ECV group,n=751)and those who under-went direct cesarean section(CS)without ECV(CS group,n=706)at Guangzhou Women and Children's Medi-cal Center of Guangzhou Medical University,from January 1,2018,to July 31,2024,were enrolled.Differences in maternal clinical characteristics and neonatal outcomes were compared between the two groups.The ECV group was further divided into a successful ECV subgroup(n=537)and a failed ECV subgroup(n=214)to compare complication rates.Based on the presence or absence of complications,the ECV group was divided into a compli-cation subgroup(n=86)and a no-complication subgroup(n=665).Univariate analysis was performed on the clinical data of these subgroups.Statistically significant factors identified in the univariate analysis were subse-quently included in a multivariate Logistic regression analysis to identify high-risk factors for ECV complications.Results:①Among the 751 women undergoing ECV,the success rate was 71.50％(537/751).The vaginal deliv-ery rate following successful ECV was 57.26％(430/751).The overall complication rate was 11.45％(86/751),with a perinatal mortality rate of 0.13％(1/751).②There were no significant differences with regard to severe neonatal asphyxia and neonatal intensive care admission rate between ECV group and CS group(P＞0.05).③The total complication rate,incidence of cesarean delivery(CS)within 24 h,and incidence of uterine contrac-tions were significantly higher in the failed ECV group compared to the successful ECV group(P＜0.05).Howev-er,there was no statistically significant difference in the incidence of severe complications(fetal demise,placental abruption,emergency CS)between the two groups(P＞0.05).④Univariate and multivariate Logistic regression analyses revealed that three factors were associated with a reduced risk of ECV complications(P＜0.05):a high-er amniotic fluid index(AFI),non-engagement of the presenting part,and a palpable fetal head.Conversely,the use of anesthesia and the use of nifedipine as the tocolytic were associated with an increased risk of ECV compli-cations(P＜0.05).Conclusions:ECV does not increase the adverse outcomes of full-term neonates with breech presentation.But failed ECV can increase complications.Higher amniotic fluid index,not engaged of fetal presen-tation,touchable of fetal head and appropriate tocolytic agent application can reduce the complications while anes-thesia during ECV procedure can increase the complications of ECV.

The integrated medical and elderly care model provides comprehensive medical and elderly care services by establishing medical facilities in elderly care institutions or forming close cooperative relationships with surrounding medical institutions. Currently， there are 87，000 paired partnerships established nationwide between medical and health institutions and elderly care service institutions， and more than 7，800 integrated medical and elderly care institutions have obtained the qualifications of medical and health institutions and completed elderly care service registration. This model not only meets the elderly’s healthcare needs but also provides life care， psychological support， and social activities， thereby improving their quality of life. However， the integrated medical and elderly care model also faces numerous ethical dilemmas in practice. This paper aimed to explore in depth the ethical dilemmas and countermeasures optimization in the work of elderly care institutions under this model， to promote the improvement of service quality， comprehensively guarantee the rights and interests of the elderly， and promote the healthy development of this model in practice. Under this model， the elderly care institutions not only bear the responsibility of providing long-term care and life services but also need to cooperate with medical institutions to provide healthcare and health management services for the elderly. By exploring the practical paths for elderly care institutions to address the ethical dilemmas faced with this model， feasible solutions were proposed to enhance the welfare of the elderly and promote the harmonious development of society.

Objective To explore the research status and emerging focus of virtual reality(VR)technology in the field of stroke.Methods The global literature of VR technology in the field of stroke from Jan.2014 to Aug.2024 was retrieved from the Web of Science Core Collection.Bibliometric software was used to draw a visual knowledge map of authors,institutions,key words,etc.Results After excluding proofreading notices,editorial materials,conference papers,etc.,a total of 785 articles were included.Over the past decade,the number of new publications has shown an upward trend.China was the country with the largest total number of publications(130 articles).Lamontagne Anouk(10 articles)and Calabro Rocco Salvatore(10 articles)were tied for the authors with the highest number of publications.The institution and journal with the most literature in this field were McGill University(Canada,27 articles)and Journal of Neuroengineering and Rehabilitation(60 articles),respectively.The key word analysis and the results of the strongest burst key words indicated that the research focused on upper limb,gait training,motor function,cognitive rehabilitation,post-stroke unilateral spatial neglect,stimulation,motor imagery,cortical reorganization,etc.Conclusion Over the past decade,the application of VR technology has gradually increased in both breadth and depth in the field of stroke,bringing new opportunities and thoughts to stroke rehabilitation.The new forms of VR technology combined with neuromodulation,neuroimaging,brain-computer interfaces,artificial intelligence,and telemedicine may be the future research topics and directions.

Objective:To examine the validity and reliability of the DSM-5 Social Anxiety Disorder Severity Scale(SAD-D)in a Chinese adult population.Methods:The Chinese version of the DSM-5 Social Anxiety Disor-der Severity Scale was administered via online data collection platform Credamo to 300 adults(Sample 1,for item analysis,exploratory factor analysis and item selection of brief version of SAD-D)and 528 adults(Sample 2,for confirmatory factor analysis,criterion validity test,measurement invariance analysis and internal consistency reliabil-ity analysis for both SAD-D and its brief version).Criterion validity was tested with the Social Phobia Scale(SPIN)and Personal Report of Confidence as a Speaker(PRCS).A brief version of the scale was developed by u-sing the Ant Colony Optimization(ACO).A retest was conducted with 152 participants from Sample 2 after three weeks.Results:Exploratory factor analysis indicated that the SAD-D was a unidimensional scale with factor load-ings ranging from 0.49 to 0.82,and the results of the confirmatory factor analysis also supported the unidimension-al structure(x2/df=3.49,RMSEA=0.069,CFI=0.971,TLI=0.962,SRMR=0.028).The scores of Chinese version of the SAD-D were positively correlated with the SPIN scores(ICC=0.70,P＜0.001)and PRCS scores(ICC=0.73,P＜0.001).The Cronbach'α of the scale was 0.92,and the retest reliability was 0.85.The scale dem-onstrated cross-gender measurement invariance(△CFI＜0.01,△RMSEA＜0.01).The brief version of the SAD-D was selected as items 2,5,and 6,and its Cronbach'α coefficient was 0.86.Conclusion:The Chinese version of the SAD-D has satisfactoryvalidity andreliability,making it suitable for the assessment of social anxiety symptoms with Chinese adults.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

Objective:To examine the validity and reliability of the DSM-5 Social Anxiety Disorder Severity Scale(SAD-D)in a Chinese adult population.Methods:The Chinese version of the DSM-5 Social Anxiety Disor-der Severity Scale was administered via online data collection platform Credamo to 300 adults(Sample 1,for item analysis,exploratory factor analysis and item selection of brief version of SAD-D)and 528 adults(Sample 2,for confirmatory factor analysis,criterion validity test,measurement invariance analysis and internal consistency reliabil-ity analysis for both SAD-D and its brief version).Criterion validity was tested with the Social Phobia Scale(SPIN)and Personal Report of Confidence as a Speaker(PRCS).A brief version of the scale was developed by u-sing the Ant Colony Optimization(ACO).A retest was conducted with 152 participants from Sample 2 after three weeks.Results:Exploratory factor analysis indicated that the SAD-D was a unidimensional scale with factor load-ings ranging from 0.49 to 0.82,and the results of the confirmatory factor analysis also supported the unidimension-al structure(x2/df=3.49,RMSEA=0.069,CFI=0.971,TLI=0.962,SRMR=0.028).The scores of Chinese version of the SAD-D were positively correlated with the SPIN scores(ICC=0.70,P＜0.001)and PRCS scores(ICC=0.73,P＜0.001).The Cronbach'α of the scale was 0.92,and the retest reliability was 0.85.The scale dem-onstrated cross-gender measurement invariance(△CFI＜0.01,△RMSEA＜0.01).The brief version of the SAD-D was selected as items 2,5,and 6,and its Cronbach'α coefficient was 0.86.Conclusion:The Chinese version of the SAD-D has satisfactoryvalidity andreliability,making it suitable for the assessment of social anxiety symptoms with Chinese adults.

Objective:To evaluate the safety and complications of external cephalic version(ECV)for term breech presentation and to explore factors influencing the occurrence of ECV-related complications.Methods:Pregnant women with term breech presentation who underwent ECV(ECV group,n=751)and those who under-went direct cesarean section(CS)without ECV(CS group,n=706)at Guangzhou Women and Children's Medi-cal Center of Guangzhou Medical University,from January 1,2018,to July 31,2024,were enrolled.Differences in maternal clinical characteristics and neonatal outcomes were compared between the two groups.The ECV group was further divided into a successful ECV subgroup(n=537)and a failed ECV subgroup(n=214)to compare complication rates.Based on the presence or absence of complications,the ECV group was divided into a compli-cation subgroup(n=86)and a no-complication subgroup(n=665).Univariate analysis was performed on the clinical data of these subgroups.Statistically significant factors identified in the univariate analysis were subse-quently included in a multivariate Logistic regression analysis to identify high-risk factors for ECV complications.Results:①Among the 751 women undergoing ECV,the success rate was 71.50％(537/751).The vaginal deliv-ery rate following successful ECV was 57.26％(430/751).The overall complication rate was 11.45％(86/751),with a perinatal mortality rate of 0.13％(1/751).②There were no significant differences with regard to severe neonatal asphyxia and neonatal intensive care admission rate between ECV group and CS group(P＞0.05).③The total complication rate,incidence of cesarean delivery(CS)within 24 h,and incidence of uterine contrac-tions were significantly higher in the failed ECV group compared to the successful ECV group(P＜0.05).Howev-er,there was no statistically significant difference in the incidence of severe complications(fetal demise,placental abruption,emergency CS)between the two groups(P＞0.05).④Univariate and multivariate Logistic regression analyses revealed that three factors were associated with a reduced risk of ECV complications(P＜0.05):a high-er amniotic fluid index(AFI),non-engagement of the presenting part,and a palpable fetal head.Conversely,the use of anesthesia and the use of nifedipine as the tocolytic were associated with an increased risk of ECV compli-cations(P＜0.05).Conclusions:ECV does not increase the adverse outcomes of full-term neonates with breech presentation.But failed ECV can increase complications.Higher amniotic fluid index,not engaged of fetal presen-tation,touchable of fetal head and appropriate tocolytic agent application can reduce the complications while anes-thesia during ECV procedure can increase the complications of ECV.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

With an aging population, the incidence of osteoporotic vertebral fractures (OVFs) is on the rise, posing new challenges for developing personalized treatment strategies. For patients who do not respond to conservative treatment, percutaneous vertebroplasty or percutaneous kyphoplasty (PVP/PKP) remains the preferred surgical option due to its minimal invasiveness and rapid recovery time. However, progressive local kyphosis (PLK) is one of the most severe complications following PVP/PKP, with an incidence rate of 1.5%-25.8%. PLK often presents with recurring thoracic and lower back pain, and in severe cases, spinal stenosis, causing symptoms like numbness and pain in the lower limbs. The severity of PLK varies, and treatments can range from conservative management and bone cement reinforcement to internal fixation or osteotomy. Current studies suggest that re-fracture of the affected vertebra, intervertebral disc degeneration, and osteonecrosis may be underlying mechanisms. These conditions shift the axial load forward, promoting postoperative PLK, which tends to progress over time. Postoperative PLK is closely associated with patient characteristics, fracture details, surgical factors, and post-surgery osteoporosis management. 1) The severity of osteoporosis, as indicated by the T-score from bone mineral density testing, can help predict postoperative PLK. While factors like age and gender influence osteoporosis severity, no direct relationship has been established between these factors and PLK. 2) Thoracolumbar fractures, old nonunion fractures, endplate fractures, or severe preoperative compression changes with kyphosis can increase PLK risk. Surgical factors, including the use of balloons or implants and the distribution of bone cement, also play a role. Personalized treatment plans should be developed based on the patient's general condition and imaging results to ensure adequate bone cement diffusion, as enhanced integration can reduce PLK risk. 3) Postoperative anti-osteoporosis therapy is also crucial; long-term therapy, particularly with teriparatide, can prevent PLK. Recognizing the related risk factors and establishing predictive models can help clinicians tailor treatments. Machine learning models, utilizing big data, are particularly adept at handling complex interrelated risk factors and may provide a powerful tool for personalized treatment in the future.

Objective:To discuss the effect of sialic acid-binding immunoglobulin-like lectin-15(Siglec15)derived from M2 tumor-associated macrophages(M2-TAMs)on promoting the malignant biological behavior of the esophageal squamous cell carcinoma(ESCC)through bioinformatics analysis,and to validate the findings through cell experiment.Methods:The Tumor Immune Estimation Resource(TIMER)online Database was used to analyze the expression differences and immune infiltration of Siglec15 in pan-cancer and adjacent normal tissues.Real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the expression levels of Siglec15 mRNA in M2-TAMs and ESCC EC109 and KYSE150 cells.Based on the non-contact co-culture of M2-TAMs and ESCC cells,the following groups were set up,such as EC109/KYSE150 group,EC109/KYSE150+si-NC group(transfected with si-NC sequence),and EC109/KYSE150+si-Siglec15 group(transfected with si-Siglec15#1 and si-Siglec15#2 sequences).CCK-8 method was used to detect the proliferation activities of the cells in various groups;wound healing assay was used to detect the wound healing rates of the cells in various groups;Transwell chamber assay was used to detect the numbers of migration and invasion cells in various groups;flow cytometry was used to detect the apoptotic rates of the cells in various groups.Results:The bioinformatics analysis results showed that compared with adjacent normal tissue,the expression levels of Siglec15 mRNA in pan-cancer tissues such as esophageal cancer,colon cancer,and head and neck squamous cell carcinoma tissues were increased(P＜0.05 or P＜0.01),and the expression level of Siglec15 mRNA in esophageal cancer tissue was significantly positively correlated with the infiltration of the macrophages(P＜0.05).Compared with the EC109 cells and KYSE150 cells,the expression level of Siglec15 mRNA in M2-TAMs was significantly increased(P＜0.01).There was no significant difference in the proliferation rate of the cells among EC109/KYSE150 group,EC109/KYSE150+si-NC group,and EC109/KYSE150+si-Siglec15 group(P＞0.05).Compared with EC109/KYSE150 group,after treated for 24 and 48 h,the wound healing rate of the cells in EC109/KYSE150+si-NC group was increased(P＜0.01),the numbers of migration and invasion cells were increased(P＜0.05),and the apoptotic rate was decreased(P＜0.01).Compared with EC109/KYSE150+si-NC group,the wound healing rates of the cells in EC109/KYSE150+si-Siglec15#1 group and EC109/KYSE150+si-Siglec15#2 group were decreased(P＜0.05),the numbers of migration and invasion cells were decreased(P＜0.05),and the apoptotic rates of the cells had no significant difference(P＞0.05).Conclusion:Siglec15 derived from M2-TAMs may be a key factor in promoting the migration and invasion of the ESCC cells.