ObjectiveTo observe the clinical efficacy of Sanren Runchang formula in treating constipation-predominant irritable bowel syndrome （IBS-C） by regulating the brain-gut axis and the effects of the formula on serum levels of 5-hydroxytryptamine （5-HT）， vasoactive intestinal peptide （VIP）， and substance P （SP）. MethodsA randomized controlled design was adopted， and 72 IBS-C patients meeting Rome Ⅳ criteria were randomized into observation and control groups （36 cases）.The observation group received Sanren Runchang formula granules twice daily， and the control group received lactulose oral solution daily for 4 weeks. IBS Symptom Severity Scale （IBS-SSS）， IBS Quality of Life Scale （IBS-QOL）， and Bristol Stool Form Scale （BSFS） were used to assess clinical symptoms， and bowel movement frequency was recorded. The Self-Rating Anxiety Scale （SAS） and Self-Rating Depression Scale （SDS） were employed to evaluate psychological status. ELISA was employed to measure the serum levels of 5-HT， VIP， and SP. ResultsThe total response rate in the observation group was 91.67% （33/36）， which was higher than that （77.78%， 28/36） in the control group （χ²=4.50， P<0.05）. After treatment， both groups showed increased defecation frequency and BSFS scores， decreased IBS-SSS total score， abdominal pain and bloating scores， IBS-QOL health anxiety， anxiety， food avoidance， and behavioral disorders scores， SAS and SDS scores， serum 5-HT and VIP levels， and increased SP levels （P<0.05， P<0.01）. Moreover， the observation group showed more significant changes in the indicators above than the control group （P<0.05， P<0.01）. The SP level showed no significant difference between the two groups. During the 4-week follow-up， the recurrence rate was 5.88% in the observation group and 31.25% in the control group. No adverse events occurred in observation group， and 2 cases of mild diarrhea occurred in the control group. ConclusionSanren Runchang formula demonstrated definitive efficacy in alleviating gastrointestinal symptoms and improving the psychological status and quality of life in IBS-C patients， with a low recurrence rate. The formula can regulate serum levels of neurotransmitters such as 5-HT and VIP， suggesting its potential regulatory effect on the brain-gut axis through modulating neurotransmitters and neuropeptides. However， its complete mechanism of action requires further investigation through detection of additional brain-gut axis-related biomarkers.

BACKGROUND:Exosomes derived from mesenchymal stem cells play pivotal roles in cell communication and epigenetic regulation due to their low immunogenicity and targeted delivery effects,and have been clinically applied in the treatment of various diseases.OBJECTIVE:To review the isolation,purification,identification methods,and application progress of mesenchymal stem cell-derived exosomes,and to facilitate the development of large-scale preparation techniques and clinical translation of mesenchymal stem cell-derived exosomes.METHODS:The Chinese search terms"exosome,mesenchymal stem cells,isolation,purification,characterization,clinical application"and the English search terms"exosome,extracellular vesicles,mesenchymal stem cells,isolation,characterization,application"were used to search the literature published before September 2024 in CNKI,PubMed,and Web of Science databases.Articles with poor relevance to the topic,outdated,or duplicated content were excluded,and finally,109 articles were included for review.RESULTS AND CONCLUSION:(1)This paper reviews recent methods for isolating and purifying exosomes,comparing the characteristics of ultracentrifugation,ultrafiltration,size-exclusion chromatography,polymer precipitation,immunoaffinity,microfluidic methods,and other novel approaches based on their underlying principles.(2)Methods for identifying exosomes can be categorized into physical and biochemical analyses,characterizing exosomes based on their shape,size,and characteristic proteins.(3)Mesenchymal stem cell-derived exosomes have broad applications in multiple fields such as medical aesthetics,wound repair,and cancer treatment,due to their immune-regulatory properties and ability to cross biological barriers.(4)The clinical translation of exosomes faces challenges due to their complex structure,lack of universal isolation techniques,and poor stability,making it difficult to achieve in a short period of time.

BACKGROUND:Exosomes derived from mesenchymal stem cells play pivotal roles in cell communication and epigenetic regulation due to their low immunogenicity and targeted delivery effects,and have been clinically applied in the treatment of various diseases.OBJECTIVE:To review the isolation,purification,identification methods,and application progress of mesenchymal stem cell-derived exosomes,and to facilitate the development of large-scale preparation techniques and clinical translation of mesenchymal stem cell-derived exosomes.METHODS:The Chinese search terms"exosome,mesenchymal stem cells,isolation,purification,characterization,clinical application"and the English search terms"exosome,extracellular vesicles,mesenchymal stem cells,isolation,characterization,application"were used to search the literature published before September 2024 in CNKI,PubMed,and Web of Science databases.Articles with poor relevance to the topic,outdated,or duplicated content were excluded,and finally,109 articles were included for review.RESULTS AND CONCLUSION:(1)This paper reviews recent methods for isolating and purifying exosomes,comparing the characteristics of ultracentrifugation,ultrafiltration,size-exclusion chromatography,polymer precipitation,immunoaffinity,microfluidic methods,and other novel approaches based on their underlying principles.(2)Methods for identifying exosomes can be categorized into physical and biochemical analyses,characterizing exosomes based on their shape,size,and characteristic proteins.(3)Mesenchymal stem cell-derived exosomes have broad applications in multiple fields such as medical aesthetics,wound repair,and cancer treatment,due to their immune-regulatory properties and ability to cross biological barriers.(4)The clinical translation of exosomes faces challenges due to their complex structure,lack of universal isolation techniques,and poor stability,making it difficult to achieve in a short period of time.

Objective: To explore the related factors of college students social network addiction based on problem behavior theory, so as to provide a basis for improving social networking addiction in this population. Methods: From May to June 2023, a method combining convenient sampling and cluster random sampling was used to select 1 768 college students from five universities in Shanghai for a questionnaire survey on social networking addiction, self esteem, loneliness, depressive symptoms, social support, interpersonal needs, sense of distress and frustration; at the same time, the physical exercise, smoking and drinking of college students were investigated. Multivariate Logistic regression analysis was applied to explore the association between the three systems of the problem behavior theory (personality, behavior, and social environment) and social networking addiction among college students. Results: The score on the Social Network Addiction Tendency Scale was (21.08±6.29) among college students, and the detection rate of social networking addiction was 66.29%. After adjusting for gender, family economic status, parental divorce status, and whether being an only child, multivariate Logistic regression analysis showed that in the personality system, higher loneliness ( OR =1.66) and higher depressive symptoms ( OR =2.18) were associated with increased risk of social networking addiction among college students; in the behavior system, alcohol consumption ( OR =1.42) was associated with higher risk of soical networking addiction compared to non drinkers; and in the social environment system, low social support ( OR =1.43) was associated with increased risk of social networking addiction (all P <0.05). Conclusions The rate of social networking addiction among college students is relatively high, and the systems of personality, behavior, and social environment are all related to social network addiction. Providing social support, cultivating healthy lifestyle habits, and increasing interpersonal interactions may help reduce excessive dependence on social networking among college students.

AIM:To analyze the association between mobile phone addiction and high myopia among college students.METHODS:We conducted a cross-sectional questionnaire survey in December 2022 on all students of a university in Shaanxi Province, and the questionnaire included socio-demographic characteristics, mobile phone addiction, high myopia, and lifestyle. Binary Logistic regression model was used to analyze the association between mobile phone addiction and high myopia among college students.RESULTS:A total of 19 952 college students were included. The prevalence of high myopia was 7.31%. The rate of mobile phone addiction was 25.68%, and the mobile phone addiction score was 37.59±13.38. The incidence of high myopia among college students with mobile phone addiction was higher than non-mobile phone addiction(P<0.001). After adjusting for socio-demographic characteristics and lifestyle, the risk of high myopia among college students with mobile phone addiction was 1.274 times(95%CI:1.131-1.434)higher than non-mobile phone addiction. For each point increase of total mobile phone addiction score, withdrawal symptoms score, salience score, social comfort score, and mood changes score, the risk of high myopia among college students increased by 0.9%(95%CI:1.005-1.013), 2.0%(95%CI:1.010-1.030), 2.6%(95%CI:1.010-1.043), 4.8%(95%CI:1.030-1.066), and 3.3%(95%CI:1.014-1.052), respectively.CONCLUSION:Mobile phone addiction is significantly associated with the increased risk of high myopia among college students, and early intervention of mobile phone use may reduce the risk of high myopia among college students.

Electroencephalogram (EEG) serves as an effective indicator of detecting fatigue driving. Utilizing the open accessible Shanghai Jiao Tong University Emotion Electroencephalography Dataset (SEED-VIG), driving states are divided into three categories including awake, tired and drowsy for investigation. Given the characteristics of mutual influence and interdependence among EEG channels, as well as the consistency of the graph convolutional neural network (GCNN) structure, we designed an adjacency matrix based on the Pearson correlation coefficients of EEG signals among channels and their positional relationships. Subsequently, we developed a GCNN for recognition. The experimental results show that the average classification accuracy of driving state categories for 20 subjects, from the SEED-VIG dataset under the smooth feature of differential entropy (DE) linear dynamic system is 91.66%. Moreover, the highest classification accuracy can reach 98.87%, and the average Kappa coefficient is 0.83. This work demonstrates the reliability of this method and provides a guideline for the research field of safe driving brain computer interface.
Humans ; Electroencephalography/methods* ; Neural Networks, Computer ; Fatigue/physiopathology* ; Automobile Driving ; Brain-Computer Interfaces ; Signal Processing, Computer-Assisted ; Convolutional Neural Networks

BACKGROUND: Early control of low-density lipoprotein cholesterol (LDL-C) is crucial for reducing the progress of cardiovascular disease. However, its additional role to the risk of primary osteoporosis in men with coronary heart disease was inconclusive. Our study aims to determine the association of LDL-C and its trajectories for osteoporosis risk in the middle-aged and aged men of China. METHODS: The retrospective cohort study of 1546 men aged 69.74 ± 11.30 years conducted in Beijing, China from 2015 to 2022. And the incidence of primary osteoporosis was annually recorded. LDL-C trajectories were further identified by latent class growth model using repeated measurements of LDL-C. The association of baseline LDL-C for osteoporosis was estimated using hazard ratio (HR) with 95% CI in Cox proportional hazard model, while mean level and trajectories of LDL-C for osteoporosis were evaluated using odds ratio (OR) with 95% CI in logistic regression model. RESULTS: During the median 6.2-year follow-up period, 70 men developed primary osteoporosis. The higher level of baseline LDL-C (HR = 1.539, 95% CI: 1.012-2.342) and mean LDL-C (OR = 2.190, 95% CI: 1.443-3.324) were associated with higher risk of osteoporosis in men with coronary heart disease after adjusted for covariates. Compared with those in the LDL-C trajectory of low-stable decrease, participants with medium-fluctuant trajectory, whose longitudinal LDL-C started with a medium LDL-C level and appeared an increase and then decrease, were negatively associated with osteoporosis risk (OR = 2.451, 95% CI: 1.152-5.216). And participants with initially high LDL-C level and then a rapid decrease demonstrated a tendency towards reduced risk (OR = 0.718, 95% CI: 0.212-2.437). CONCLUSIONS Elevated LDL-C level and its long-term fluctuation may increase the risk of primary osteoporosis in men. Early controlling a stable level of LDL-C is also essential for bone health.

Objective: To explore the association between CDKAL1 rs35261542, FAIM2 rs 3205718, and VGLL4 rs 2574704 polymorphisms with childhood obesity and related metabolic phenotypes to provide evidence for personalized prevention and management strategies. Methods: Based on the 2023 Long term Nutritional Health Effects of Early Childhood Nutrition Package Intervention project, the study enrolled 1 078 children aged 5-7 years from four counties in Henan (Songxian and Ruyang countries) and Guizhou (Guiding and Fuquan countries) provinces. Using BMI Z scores, 87 overweight and obese(OVOB) children were selected and matched by sex, age, and BMI Z score with 117 normal weight controls. Participants were further stratified into four metabolic phenotype groups: metabolically healthy normal weight (MHNW, n =51), metabolically unhealthy normal weight (MUNW, n =66), metabolically healthy obesity (MHO, n =31) and metabolically unhealthy obesity (MUO, n =56) based on four conventional cardiometabolic risk factor (CR) criteria. Data were collected through questionnaires, anthropometric measurements, serum biochemical tests, and KASP genotyping. The distribution of three genetic polymorphisms ( CDKAL1 rs35261542, FAIM2 rs3205718, VGLL4 rs 2574704) across metabolic subgroups was analyzed. Multivariate Logistic regression models assessed associations between these polymorphisms and obesity/metabolic phenotypes. Results: Multivariate Logistic regression analysis showed that Homozygous mutant AA genotype of CDKAL1 rs 35261542 was positively associated with OVOB( OR =3.63), MHO ( OR =11.04), MUO ( OR = 4.88 ) ( P <0.05). Homozygous TT genotype of FAIM2 rs 3205718 increased OVOB risk ( OR =4.44, P <0.05) but showed no association with metabolic phenotypes ( P >0.05). Homozygous mutant TT of VGLL4 rs 2574704 reduced the risks of MHO and MUO ( OR = 0.30, 0.24， P <0.05). Cumulative genetic effects analysis demonstrated carriers of 1 or 2 risk genotypes of rs 35261542 and rs 3205718 had progressively higher OVOB risk ( OR =2.53, 20.79), and the combination of rs 35261542 and rs 2574704 increased risks for both MHO ( OR =8.50) and MUO ( OR =5.00) ( P <0.05). Conclusions The AA genotype of rs 35261542 ( CDKAL1 ) positively correlates with childhood obesity and metabolic abnormalities. The TT genotype of rs 3205718 ( FAIM 2) increases obesity risk but not metabolic phenotypes. The TT genotype of rs 2574704 ( VGLL 4) shows protective effects against metabolic dysfunction. Risk genotypes exhibit dosedependent cumulative effects on obesity and metabolic outcomes.

Implementation Science is an interdisciplinary field dedicated to systematically studying how to effectively translate evidence-based research findings into practical application and implementation. In the health-related context, it focuses on enhancing the efficiency and quality of healthcare services, thereby facilitating the transition from scientific evidence to real-world practice. This article elaborates on Theories, Models, and Frameworks (TMF) within health-related Implementation Science, clarifying their basic concepts and classifications, and discussing their roles in guiding implementation processes. Furthermore, it reviews and prospects current research from three aspects: the constituent elements of TMF, their practical applications, and future directions. Five representative frameworks are emphasized, including the Consolidated Framework for Implementation Research (CFIR), the Practical Robust Implementation and Sustainability Model (PRISM), the Exploration, Preparation, Implementation, Sustainment (EPIS)framework, the Behavior Change Wheel (BCW), and the Normalization Process Theory (NPT). Additionally, resources such as the Dissemination & Implementation Models Webtool and the T-CaST tool are introduced to assist researchers in selecting appropriate TMFs based on project-specific needs.