BACKGROUND:Stem cells can promote nerve regeneration,repair damaged nerves,inhibit inflammation and apoptosis of nerve cells,and provide a new way for the treatment of Alzheimer's disease. OBJECTIVE:To make a bibliometrical analysis of the articles on stem cell therapy for Alzheimer's disease published internationally from 2004 to 2023,in order to reveal the research hotspot and trend of stem cell therapy for Alzheimer's disease. METHODS:From the Web of Science Core Collection database,by using Excel,VOSviewer,and Citespace software,the annual number of publications,countries,institutions,journals/co-cited journals,authors,and keywords of articles related to stem cells and Alzheimer's disease published from January 1,2004 to October 31,2023 were visually analyzed. RESULTS AND CONCLUSION:A total of 3 521 core papers were included,and the number of published papers increased year by year.The United States is the country with the most papers.Harvard Medical School is the most prolific institution.Maiese kenneth is the author with the most papers.International Journal of Molecular Sciences has the most papers in this field.The journal PLoS One published the most citations.At present,the field of stem cell therapy for Alzheimer's disease focuses on pathophysiological mechanism and animal experimental research,and"neurogenesis","oxidative stress","extracellular vesicles",and"mesenchymal stem cells"are the research trends in this field.Stem cell therapy for Alzheimer's disease has broad prospects.In the future,exchanges and cooperation between institutions and authors should be strengthened to further explore the main mechanism of stem cell therapy for Alzheimer's disease,solve possible clinical problems such as immune rejection,effectiveness,and safety,and further tap the potential of stem cells in the treatment of Alzheimer's disease.

Objective:To establish a machine learning-based risk prediction model for perimenopausal depressive symptoms and to identify associated risk factors.Methods:A total of 1 105 women aged 45 to 55 years were selected from the 2020 China Health and Retirement Longitudinal Study (CHARLS) dataset.Three machine learning algorithms, including Random Forest, XGBoost and Adaptive Boosting (AdaBoost), were employed to construct prediction models for perimenopausal depressive symptoms. Descriptive statistics and between-group comparisons were performed using SPSS 24.0.And Python 3.10 software was used to build the risk prediction model. Model performance was assessed using receiver operating characteristic (ROC) curves and calibration plots, and the optimal model was identified accordingly. The Shapley additive explanation (SHAP) algorithm was then used to analyze feature importance and the influence of each predictor on the outcome.Results:Among the 1 105 perimenopausal women, 671(60.7%)were categorized in the non-depressive group and 434 (39.3%) in the depressive group. The Random Forest model demonstrated the best overall predictive performance among the three machine learning models, achieving an area under the ROC curve (AUC) of 0.793 and a calibration error of 0.181. SHAP analysis revealed that annual household income was the strongest risk factor in the Random Forest model, with a relative importance of 0.048, followed by cognitive function(0.047), self-rated health status(0.046), life satisfaction(0.043), sleep duration(0.041).Conclusions:The Random Forest based model effectively predicts the risk of perimenopausal depressive symptoms. Annual household income, cognitive function, self-rated health, and life satisfaction are risk factors for depressive symptoms in perimenopausal women.

To verify whether the two B-cell epitopes Pep1 and Pep4 in the FAdV-4 WZ fiber can be used as candidate epitopes for multivalent epitope vaccines,epitopes Pep1 and Pep4 were tandemly linked with the chicken infectious bronchitis virus strain M41 S1 protein gene in different patterns,and a recombinant fusion plasmid was constructed and expressed in E.coli BL21(DE3).It was confirmed by Western blot and ELISA tests that all four expressed fusion proteins reacted specific-ally with anti-M41 whole virus serum and WZ strain anti-Fiber 2-knob protein serum.After purifi-cation and immunization of BALB/c mice,specific antibodies against the peptide epitopes were de-tected in mouse sera.The results showed that the Pep4 epitope induced a stronger immune re-sponse than the Pep1 epitope.When Pep1 was connected with the amino and carboxyl termini of the fusion protein,respectively,both resulted in the production of the same level of anti-Pep1 anti-bodies in the immunized animals,whereas when Pep4 was connected with the carboxyl terminus of the fusion protein,the immunized animals produced a higher level of anti-Pep4-specific antibodies.This research indicates that the B cell epitopes Pep1 and Pep4 of the reactive WZ strain Fiber 2,when conjugated with proteins to form fusion proteins,can enhance the immunogenicity of Pep1 and Pep4 without affecting the antigenicity of the carrier protein.This study provides technical support and serves as a reference for the design and development of a multivalent epitope vaccine for FAdV-4.

Objective:To investigate the current situation and correlation between mental health and stressors of new professional master's degree graduates in clinical medicine, and to provide empirical support for improving student mental health.Methods:An online questionnaire survey was conducted among 3 587 fresh graduate students with master's degree in clinical medicine from 65 training institutions in China. SPSS 26.0 was used to compare and analyze the measurement data. Descriptive statistics were used to analyze the mental health using Symptom Checklist-90 (SCL-90) and the current status of stressors. The influence factors and correlation between mental health and stressors were analyzed by means of differentiation analysis and correlation analysis.Results:The SCL-90 overall mean score as well as the scores of obsessive-compulsive symptoms, interpersonal sensitivity, depression, terror, anxious, psychoticism, and hostility of new professional master's degree graduates in clinical medicine were all higher than the national norm ( P<0.05). Among the participants, 58.21% (2 088/3 587) exhibited varying degrees of symptoms listed in the SCL-90. Students from families with low per capita income and low parental education level have more prominent psychological problems. The top three stressors perceived were job seeking, research tasks, and self-ability. Students with positive SCL-90 symptoms reported significantly higher perceived stress in all three stressor dimensions compared to their symptom-negative counterparts ( P<0.001), indicating a significant correlation between mental health status and stressors. Conclusions:The mental health status of new professional master's degree graduates in clinical medicine is concerning and warrants focused attention from educational authorities, academic institutions, and families.

Objective:To understand the graduation destination of newly graduated medical master's students in China and analyze their employment status.Methods:A questionnaire survey was conducted on 15 942 medical master's students who graduated in 2023. Descriptive analysis, χ2 test, and Kruskal-Wallis rank-sum test were used to understand the current situation and differences in the graduation destinations, employment units, job positions, and starting salaries of different types of medical master's graduates. Results:The employment rate of medical master's graduates was 58.21% (9 280/15 942). In terms of graduation destinations, male graduates, professional degree holders, graduates from non-"Double First-Class" universities, and nursing majors had a high proportion of confirmed employment units. Male graduates, academic degree holders, graduates from "Double First-Class" universities, and basic medical science majors had a high proportion pursuing further studies domestically. In terms of employment, the highest proportion of medical master's graduates worked in hospitals (84.92%, 6 495/7 648) and the lowest proportion worked in primary-level medical and healthcare institutions (1.02%, 78/7 648). The majority (78.07%, 5 971/7 648) held professional technical positions. Starting salaries were relatively low and ranged between 3 001 and 5 000 yuan/month, accounting for 30.99% (2 370/7 648).Conclusions:The employment rate of medical master's graduates is low, with concentrated employment units and job positions, and there is a lack of talents in primary medical institutions. Colleges and universities and education management departments should adopt policy-driven approaches to support key demographic groups and encourage employment in primary healthcare. Training programs should be timely adjusted in response to market demands and focus on cultivating the comprehensive quality and job competence of medical master's graduates. Additionally, student-centered approaches should be used to strengthen the employment guidance and career planning services.

Objective:To investigate the effect of a blended teaching mode based on medical knowledge graph and artificial intelligence (AI) teaching assistant on students' learning effectiveness and systematic thinking ability in teaching of pathogens and immunology.Methods:A controlled experimental design was employed, involving 114 clinical medical students ("5+3" integrated) enrolled in 2023 at Tianjin Medical University. They were divided into experimental group ( n=57) and control group ( n=57) based on their classes. A blended online-offline teaching mode based on medical knowledge graph and AI teaching assistant was used in the experimental group, and a blended online-offline teaching mode based on the online resources of this course was used in control group. Teaching effectiveness was assessed by comparing the scores of four chapter quizzes and the final exam between the two groups, as well as by analyzing student questionnaire responses. Data were analyzed using t test and χ2 test. Results:The experimental group achieved significantly higher scores in all four chapter quizzes and the final exam compared to the control group [(78.77±19.65) vs. (69.47±22.95), (84.56±14.02) vs. (76.49±16.20), (81.89±13.60) vs. (73.13±16.52), (81.56±21.28) vs. (73.16±16.27), (69.75±13.30) vs. (64.10±14.93), all P<0.05]. The questionnaire survey showed that 74.07% students ( n=40) believed that this blended teaching model stimulated their learning interest, 74.07% ( n=40) students believed that this blended teaching model enhanced their learning initiative, 81.48% ( n=44) students believed that this blended teaching model could help them construct the relationship between the old and new knowledge and thus improved memory retention, and 81.48% students b( n=44) elieved that this blended teaching model helped them integrate and summarize knowledge and construct systematic knowledge framework to improve their learning effectiveness. Conclusions:The blended teaching mode based on medical knowledge graph and AI teaching assistant is beneficial for cultivating students' systematic thinking ability and is helpful to improve their learning efficiency and effectiveness.

Objective To investigate the role of Glycoprotein non-metastatic melanoma protein B(GPNMB)in hypoxia-induced epithelial-mesenchymal transition(EMT)in human chorionic trophoblast HTR-8/SVneo cells.Methods HTR-8/SVneo cells were cultured in vitro to investigate the effect of hypoxia on GPNMB expression.The cells were transfected with either a GPNMB overexpression plasmid(pcDNA3.1-GPNMB),small interfering RNA targeting GPNMB(si-GPNMB-1/2),or their respective negative controls(pcDNA3.1-NC or si-NC),and were also treated with the autophagy agonist rapamycin(Rap).The experimental groups were categorized as follows:Normoxia,Hypoxia,Normoxia/Hypoxia+si-NC or si-GPNMB,Normoxia/Hypoxia+pcDNA3.1-NC or pcDNA3.1-GPNMB,Normoxia/Hypoxia+Rap,and Hypoxia+Rap+pcDNA3.1-NC or pcDNA3.1-GPNMB.GPNMB expression levels were evaluated using qRT-PCR,Western blotting,and immunofluorescence staining.The expression of autophagy-related proteins(LC3B Ⅱ/Ⅰ,p62)and epithelial-mesenchymal transition(EMT)markers(E-cadherin,N-cadherin)was analyzed by Western blotting.Cell migration and invasion capacities were assessed using wound healing and Transwell assays.Results Compared with the Normoxia group,the mRNA and protein levels of GPNMB were downregulated in the Hypoxia group.Additionally,the protein levels of p62 and N-cadherin were reduced,while LC3B Ⅱ/Ⅰ and E-cadherin expression levels were increased(P<0.05).Compared with the Hypoxia+si-NC group,the Hypoxia+si-GPNMB-2 group showed significantly decreased protein levels of p62 and N-cadherin,along with elevated levels of LC3B Ⅱ/Ⅰ and E-cadherin(P<0.05).Compared with the Hypoxia+pcDNA3.1-NC group,the Hypoxia+pcDNA3.1-GPNMB group exhibited opposite trends.Notably,compared with the Hypoxia group,the Hypoxia+Rap group showed increased LC3B Ⅱ/Ⅰ and E-cadherin levels,accompanied by reduced p62 and N-cadherin levels(P<0.05).However,compared with the Hypoxia+pcDNA3.1-GPNMB group,the Hypoxia+Rap+pcDNA3.1-GPNMB group attenuated the promoting effect of GPNMB overexpression on EMT in HTR-8/SVneo cells,as evidenced by decreased p62 and N-cadherin protein expression levels and increased LC3BⅡ/Ⅰ and E-cadherin protein expression levels(P<0.05).Conclusion In hypoxia-induced HTR-8/SVneo cells,GPNMB inhibits autophagy,promotes the epithelial-mesenchymal transition,and enhances cell migration and invasion.

Objective To investigate the expression of T cell subsets in the spleen of BTBR T+Itpr3tf autistic mouse at 4,8,and 12 weeks of age,and to determine the optimal age for studying the relationship between immune abnormalities and autism in BTBR autistic mice.Methods It randomly selected 5～6 male BTBR mouse at 4 weeks,8 weeks,and 12 weeks of age and C57BL/6J mouse of the same gender at corresponding ages for the three-box social interaction test,the self-grooming test,and the marble-burying test;Single cell suspensions were prepared from the spleens of mouse at 8 and 12 weeks of age,and flow cytometry was used to detect 8 subsets of T cells(TH 1,TH2,TH17,TC1,TC2,TC17,TFH,and Treg).Results Compared with C57BL/6J mouse of the same age,BTBR mouse at 4 weeks,8 weeks,and 12 weeks of age showed a decrease in social time(P＜0.001),an increase in grooming time(P＜0.01,P＜0.001),and an increase in the number of marbles buried(P＜0.01,P＜0.001)in BTBR mouse at 8 weeks and 12 weeks of age.As well,the expression of TH 1(P＜0.001),TH2(P＜0.01),TC 1(P＜0.05),TC2(P＜0.001),and TFH(P＜0.01)cells in 8-week-old BTBR mouse were significantly increased,while the expression of Treg(P＜0.001)cells were significantly decreased;The expression of TH 1(P＜0.01),TH2(P＜0.01),TH 17(P＜0.05),TC1(P＜0.01),TC2(P＜0.001),TC 17(P＜0.01),and TFH(P＜0.001)increased in 12-week-old BTBR mouse,while the expression of Treg(P＜0.05)cells decreased.At different age stages(P＜0.050)the ratio of TH 1/Treg and TC 1/Treg in 8-week-old BTBR mouse were significantly higher than those in 12 week old mouse,while the TC 17/Treg ratio decreased.Conclusions BTBR mouse at different developmental stages exhibit varying degrees of abnormal increase in Teff/Treg ratio.Based on result of behavioral test,it is recommended to use 8-week-old BTBR mice for research on autism and immune abnormalities.

Objective:To establish a machine learning-based risk prediction model for perimenopausal depressive symptoms and to identify associated risk factors.Methods:A total of 1 105 women aged 45 to 55 years were selected from the 2020 China Health and Retirement Longitudinal Study (CHARLS) dataset.Three machine learning algorithms, including Random Forest, XGBoost and Adaptive Boosting (AdaBoost), were employed to construct prediction models for perimenopausal depressive symptoms. Descriptive statistics and between-group comparisons were performed using SPSS 24.0.And Python 3.10 software was used to build the risk prediction model. Model performance was assessed using receiver operating characteristic (ROC) curves and calibration plots, and the optimal model was identified accordingly. The Shapley additive explanation (SHAP) algorithm was then used to analyze feature importance and the influence of each predictor on the outcome.Results:Among the 1 105 perimenopausal women, 671(60.7%)were categorized in the non-depressive group and 434 (39.3%) in the depressive group. The Random Forest model demonstrated the best overall predictive performance among the three machine learning models, achieving an area under the ROC curve (AUC) of 0.793 and a calibration error of 0.181. SHAP analysis revealed that annual household income was the strongest risk factor in the Random Forest model, with a relative importance of 0.048, followed by cognitive function(0.047), self-rated health status(0.046), life satisfaction(0.043), sleep duration(0.041).Conclusions:The Random Forest based model effectively predicts the risk of perimenopausal depressive symptoms. Annual household income, cognitive function, self-rated health, and life satisfaction are risk factors for depressive symptoms in perimenopausal women.

Objective:To compare arthroscopic versus open Brostr?m-Gould repair of the anterior talofibular ligament (ATFL) in the treatment of chronic ankle instability (CAI) in young men undergoing high intensity exercise.Methods:A retrospective study was conducted to analyze the 61 young male patients with CAI undergoing high-intensity exercise who had been treated at Department of Trauma and Orthopedics, 947th Army Hospital of Chinese People’s Liberation Army from January 2016 to July 2020. Their age was (25.9±2.7) years and their disease duration (13.9±2.8) months. According to their different treatment methods, they were divided into an arthroscopic group ( n=26) in which their ATFL was repaired by arthroscopic Brostr?m-Gould surgery and a Brostr?m-Gould group ( n=35) in which their ATFL was repaired by open Brostr?m-Gould surgery. The 2 groups were compared in terms of operation time and intraoperative bleeding, as well as the ankle-hindfoot scores of American Orthopaedic Foot & Ankle Society (AOFAS), Karlsson ankle functional (KAF) scores and visual analogue scale (VAS) pain scores at postoperative 3, 6, 12, and 24 months. Results:There were no significant differences in the preoperative general data between the 2 groups, indicating comparability ( P > 0.05). The operation time [(35.8±3.9) min] and intraoperative bleeding [(6.6±2.6) mL] in the arthroscopic group were significantly less than those in the Brostr?m-Gould group [(52.1±4.6) min and (16.1±4.0) mL] ( P < 0.05). The AOFAS ankle-hindfoot scores and KAF scores in the arthroscopic group were significantly higher than those in the Brostr?m-Gould group at postoperative 3 and 6 months, but the AOFAS ankle-hindfoot score and KAF score at postoperative 24 months were significantly lower than those in the Brostr?m-Gould group ( P < 0.05). There was no statistically significant difference in AOFAS ankle-hindfoot score or KAF score between the 2 groups at postoperative 12 months, as well as in VAS pain scores at postoperative 3, 6, 12, and 24 months between the 2 groups ( P > 0.05). Conclusions:In young men undergoing high intensity exercise, compared with open Brostr?m-Gould surgery, arthroscopic Brostr?m-Gould surgery may lead to better clinical outcomes in a short-term (3 months after surgery). However, open Brostr?m-Gould surgery may result in better long-term efficacy than arthroscopic Brostr?m-Gould surgery (24 months after surgery).