Objective: To explore the intervention effects of different exercise modalities on executive function in school aged children, providing references for formulating exercise prescriptions to promote school aged children executive function. Methods: A systematic literature search was conducted using PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP and CBM to identify studies on the effects of exercises on executive function in school aged children. The search period spanned from the database inception to August 2025. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias of the included studies. Network Meta analysis was performed using Stata 16.0. Results: A total of 51 studies involving 5 710 school aged children and seven modalities of exercises(control group,small ball sports,large ball sports,aerobic exercise,combined exercise,sport game,gymnastic and dance sports) were finally included. Network Meta analysis showed that, in terms of inhibitory control development of school aged children, small ball sports ( SMD =-0.98,95% CI =-1.32 to -0.64 ), large ball sports ( SMD =-0.64,95% CI =-0.91 to -0.36), and mixed sports ( SMD =-0.26,95% CI =-0.50 to -0.02]) were more effective than the control group; in terms of working memory, largeball sports ( SMD =-1.26,95% CI =-1.88 to -0.65) and small ball sports ( SMD =-0.91,95% CI =-1.64 to -0.19) were superior to the control group; in terms of improving cognitive flexibility, large ball sports ( SMD =-1.02,95% CI =-1.28 to -0.76), gymnastics and dance sports ( SMD =-0.80,95% CI =-1.21 to -0.40), and small ball sports ( SMD =-0.75,95% CI =-1.15 to -0.36) were more effective than the control group (all P <0.05). Surface under cumulative ranking curve(SUCRA) showed that small ball sports had the highest value (SUCRA=98.9%) in improving inhibitory control, while large ball sports achieved the highest score(SUCRA=92.6%) in enhancing working memory, and large ball sports also had the highest value(SUCRA=94.7%) in promoting cognitive flexibility. Conclusions For developing inhibitory control in school aged children, small ball sports are recommended as a priority. For enhancing working memory and cognitive flexibility, large ball sports are recommended.

Allergic conjunctivitis is a common ocular inflammatory disease, with intense itching being the most typical and distressing symptom for patients. In recent years, with the in-depth study of the interaction between the nervous and immune systems, significant progress has been made in understanding the mechanism of itching in allergic conjunctivitis. This review elaborates on the neurobiological basis of itching in allergic conjunctivitis, with a focus on the complex dialogue between immune cells and sensory neurons, particularly the core role of the IL-33-ST2-CGRP signaling axis in mediating itching. Additionally, this article introduces new findings in genetic susceptibility research, including the identification of susceptibility genes for allergic conjunctivitis through transcriptome-wide association studies. The sensory nervous system not only transmits itch signals but also actively participates in the formation of antigen channels related to conjunctival goblet cells, thereby regulating the local uptake of allergens and the initiation of the immune response. Moreover, targeted novel therapeutic strategies offer hope for patients with refractory allergic conjunctivitis. Exploring the molecular and cellular mechanisms of itching in allergic conjunctivitis will provide a theoretical basis for the development of more effective treatment methods.

Juvenile idiopathic arthritis (JIA) is the most common condition of chronic rheumatic disease in children. JIA is an autoimmune or autoinflammatory disease, with unclear mechanism and limited treatment efficacy. Recent studies have found a number of alterations in gut microbiota and its metabolites in children with JIA, which are related to the development and progression of JIA. This review focuses on the influence of the gut microbiota and its metabolites on immune function and the intestinal mucosal barrier and discuss the key role of the gut-joint axis in the pathogenesis of JIA and emerging treatment methods based on gut microbiota and its metabolites. This review could help elucidate the pathogenesis of JIA and identify the potential therapeutic targets for the prevention and treatment of JIA.
Humans ; Arthritis, Juvenile/physiopathology* ; Gastrointestinal Microbiome/physiology* ; Child ; Intestinal Mucosa

Maidong products are categorized into "Hang Maidong" and "Chuan Maidong". Since the Ming and Qing Dynasties, "Hang Maidong" has been regarded as having superior quality, but currently, it remains in name only in the market. This article reviewed historical materia medica and local chronicles from the Ming and Qing Dynasties and analyzed the historical evolution of Maidong production areas. The history of Maidong production in Zhejiang can be traced back to the Song Dynasty, and cultivation had already developed by at least the Ming Dynasty. During the Ming and Qing Dynasties, it was consistently used as a tribute. Ming Dynasty chronicles record "Chuan Maidong", which had already been cultivated on a large scale by the Qing Dynasty. "Hang Maidong" and "Chuan Maidong" share the same origin, with the former identifiable by the "gourd waist" shape of its tuberous root. Based on this, it can be inferred that the "Maimendong" herb illustrated in the Origins of Materia Medica(Ben Cao Yuan Shi) and the Maidong stored in the Qing Palace Imperial Pharmacy were both "Hang Maidong". The protection and development of the authentic "Hang Maidong" medicinal herb are urgently needed.
China ; Drugs, Chinese Herbal/history* ; History, 17th Century ; History, Ancient ; Medicine, Chinese Traditional/history* ; History, Medieval ; History, 16th Century ; History, 18th Century ; History, 15th Century ; Plants, Medicinal/chemistry* ; History, 19th Century ; History, 20th Century ; Humans ; Materia Medica/history* ; History, 21st Century

With the rapid development of social economy and the continuous improvement of human living standard, the incidence, fatality and recurrence rates of cardiovascular disease (CVD) are increasing year by year, which seriously affects people's life and health. Conventional therapeutic drugs have limited improvement on the disability rate, so the search for new therapeutic drugs and action targets has become one of the hotspots of current research. In recent years, the therapeutic role of the natural compound rosmarinic acid (RA) in CVD has attracted much attention, which is capable of preventing CVD by modulating multiple signalling pathways and exerting physiological activities such as antioxidant, anti-apoptotic, anti-inflammatory, anti-platelet aggregation, as well as anti-coagulation and endothelial function protection. In this paper, the role of RA in the prevention of CVD is systematically sorted out, and its mechanism of action is summarised and analysed, with a view to providing a scientific basis and important support for the in-depth exploration of the prevention value of RA in CVD and its further development as a prevention drug.

BACKGROUND:At present,the pathogenesis of osteoarthritis is still unclear,and there is a lack of effective means to control the disease.Research on osteoarthritis is mostly concentrated in the field of immunity,and there are few studies in the field of oxidative stress. OBJECTIVE:To explore the roles of oxidative stress and immune infiltration in osteoarthritis and to predict related miRNAs and therapeutic agents. METHODS:The GSE55235 dataset(10 samples of osteoarthritis and 10 healthy control samples)and the GSE55457 dataset(10 samples of osteoarthritis and 10 healthy control samples)were obtained from the GEO database for merging to obtain their differentially expressed genes that were combined with oxidative stress genes to get the differentially expressed genes of oxidative stress.The differentially expressed genes of oxidative stress were analyzed for KEGG and GO enrichment,and the osteoarthritis pathways and biological processes were evaluated using GSEA enrichment analysis.The protein-protein interaction network was constructed using the STRING online website and Cytoscape software,and the Degree algorithm was run to get the key genes.The GSE1919 dataset was obtained from the GEO database as a validation dataset,and the key genes were analyzed by variance analysis and receiver operating characteristic curve analysis to get the core genes.In addition,immune infiltration was evaluated by CIBERSORT and the correlation between core genes and immune cells was explored.miRNA prediction of core genes was performed using TargetScan and target drugs were predicted using the DSigDB database. RESULTS AND CONCLUSION:Sixty-five differentially expressed genes and five core genes(IL1B,CXCL8,MYC,NFKBIA,JUN)associated with oxidative stress were identified.Enrichment analysis showed that differentially expressed genes associated with oxidative stress were concentrated in the pathways of oxidative stress,interleukin-17,osteoclast differentiation,fluid shear stress and atherosclerosis.The area under the receiver operating characteristic curve for the five core genes exceeded 0.85,indicating their excellent specificity and sensitivity in diagnosing bone and joint conditions,as well as their close association with immune cells.The predicted miRNA was has-miR-3937,and the therapeutic small-molecule drugs were metformin,ionomycin and celecoxib.To conclude,oxidative stress and immune infiltration exist in osteoarthritis,and immune infiltration is involved in activating oxidative stress.The core genes and predicted miRNAs can be used as novel markers for the diagnosis of osteoarthritis,and small molecule drugs are predicted to treat osteoarthritis.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective To explore the relationship between axillary artery and axillary vein by combining computed tomography angiography computed tomography angiography(CTA)and computed tomography venography(CTV),and to provide imaging data for establishing an effective blood circulation pathway for vascular injury in clinical transaxillary surgery.Methods The image data of 30 patients who underwent left upper limb and axillary CTA and CTV at the same time were collected.After three-dimensional reconstruction of the images by GE AW4.6 workstation,the course,branch type and variation of axillary artery,the course of axillary vein,the reflux of subordinate branches and the relationship between axillary artery and axillary vein were observed.The length of the whole segment,the length of segment and the inner diameter of the starting point of each segment were measured and statistically analyzed.Results According to the number of branches from the main trunk,the axillary artery was divided into 7 types.According to the variation of the number of blood vessels,the axillary vein was divided into 5 types;The unknown vein branches converge into 32 branches,of which the first segment accounted for 37.5％,the second segment accounted for 46.9％,and the third segment accounted for 15.6％.According to the absence of arterial branches,the relationship between axillary artery and axillary vein was divided into 2 types.Conclusion There are many types of branches of axillary arteries and branches of axillary veins,and the variation types are complex.The changes of branches of axillary arteries affect the distribution of branches of axillary veins.Combined with CTA and CTV images,the relationship between axillary vessels can be reflected clearly and intuitively,which can provide imaging reference for the establishment of new ways of blood supply and reflux in clinical axillary treatment.

Lung cancer exhibits the highest incidence and mortality rates among cancers globally, with a five-year overall survival rate alarmingly below 20%. Targeting autophagy, though a controversial therapeutic strategy, is extensively employed in clinical practice. Current research is actively pursuing various therapeutic strategies using small molecules to exploit the dual function of autophagy. Nevertheless, the pivotal question of enhancing or inhibiting autophagy in cancer therapy merits further attention. This review aims to provide a comprehensive overview of the mechanisms of autophagy in lung cancer. It also explores recent advances in targeting cytotoxic autophagy and inhibiting protective autophagy with small molecules to induce cell death in lung cancer cells. Notably, most autophagy-targeting drugs, primarily natural small molecules, have demonstrated that activating cytotoxic autophagy effectively induces cell death in lung cancer, as opposed to inhibiting protective autophagy. These insights contribute to identifying druggable targets and drug candidates for potential autophagy-related lung cancer therapies, offering promising approaches to combat this disease.