Abstract To improve adolescent health behavior, the study summarizes and analyzes the performance, pathways of transmission, and influencing factors of the intergenerational transmission of adolescent health behaviors from the perspective of intergenerational transmission. The study emphasizes the need to deepen research on the intergenerational transmission of adolescent health behaviors, promote multidisciplinary and cross team collaboration, and shift adolescent health care from individual focused care to a holistic approach that prioritizes family and community culture. Simultaneously, an action framework should be established to block the intergenerational transmission of health risk behaviors, with a focus on childhood and adolescence. Additionally, parent-child participatory health education and health promotion activities should be carried out under a tripartite coordinated intervention model involving the community, school, and family, collectively fostering the development of healthy behaviors among adolescents.

With the integration of 5G communication technology and robotic surgical systems, remote robot-assisted thoracic surgery is overcoming geographical barriers, offering an innovative approach to addressing the uneven distribution of medical resources. This study conducted a systematic literature review—using databases such as PubMed and CNKI, with the search period extending up to 2025—incorporating clinical studies, case reports, and review articles to comprehensively evaluate the clinical efficacy and safety of 5G-enabled remote robot-assisted thoracic surgery (5G-RRATS). The analysis also examined current technological limitations and potential future development trajectories. Existing evidence indicates that, given adequate technical support, 5G-RRATS can achieve perioperative outcomes comparable to those of conventional local robotic surgeries across procedures including pulmonary wedge resection, lobectomy, and esophagectomy. Furthermore, it demonstrates potential advantages in minimizing surgical incisions and reducing intraoperative blood loss. Nevertheless, challenges related to network stability, latency control, interdisciplinary collaboration between medical and engineering teams, and legal, regulatory, and ethical considerations continue to hinder widespread clinical adoption. Looking ahead, the emergence of a "one-to-many" remote surgical model, combined with the integration of artificial intelligence and augmented reality technologies, as well as advancements in low-orbit satellite communications, may enable 5G-RRATS to further advance precision and efficiency in thoracic surgery, thereby facilitating equitable access to high-quality care for a broader patient population.

ObjectiveTo construct an actor-network for integrating physical activity into rehabilitation services based on the World Health Organization Rehabilitation in Health Service System framework and actor-network theory (ANT). MethodsContent analysis was employed using the six building blocks of health service systems as the theoretical framework. Actors related to rehabilitation services were extracted and categorized into a rehabilitation actor pool, while a physical activity actor pool was formed based on four major physical activity scenarios. Actors from both pools were integrated, deduplicated and classified to form a final list of integrated actors. Using ANT, the construction process of the actor network integrating physical activity into rehabilitation was analyzed through the four stages of translation: problematization, interessment, enrollment and mobilization. ResultsA dynamic integration network was constructed, comprising human actors (patients, rehabilitation professionals, researchers, sports coaches, government departments, medical institutions, community organizations and industry media, etc.) and non-human actors (assistive devices, sports infrastructure, smart equipment, information systems, online exercise guidance systems, laws and regulations, strategic documents, and exercise prescriptions, etc.). The study identified maximizing rehabilitation outcomes as the mandatory passage point and elaborated on the critical role of government departments as focal actors in coordinating various stakeholders. ConclusionThe integration of physical activity into rehabilitation services is a dynamic network constructed by diverse actors through a process of translation. ANT provides an operational theoretical framework for cross-departmental governance of rehabilitation policies in China, promotes the spatial expansion of the rehabilitation field, and drives its transformation toward a networked and ecological system. The government needs to play a leading role in facilitating role reconstruction and synergy among heterogeneous actors in both the sports and rehabilitation sectors through mechanism design, to create a bidirectional empowerment mechanism that fosters mutual progress and ensures the sustainable development of integrated services.

Object To study the efficacy and potential mechanism of Tongbianling capsule in constipation. Methods The effects of Tongbianling capsule on intestinal motility in normal mice and carbon powder propulsion rate in small intestine of constipation model mice after were observed administration. The potential targets and key pathways of Tongbianling capsule in treating constipation were identified through network pharmacology. To verify the mechanism, the expression of p-PI3K/PI3K, p-AKT/AKT and CASP3 proteins in mouse colon tissue was detected by the western blot. Results The time for mice to excrete the first black stool was shortened and the number of fecal particles was increased in Tongbianling capsule administration group, and the carbon powder propulsion rate of mice in each Tongbianling capsule administration group was increased. The results of network pharmacology showed that treatment of constipation by Tongbianling capsule may be related to signaling pathways such as PI3K-Akt signaling pathway and 5-HT. The protein expression of p-PI3K/PI3K, p-AKT/AKT, and CASP3 in mouse colon tissue could be significantly downregulated in administration group. Conclusion Tongbianling capsule could effectively promote intestinal peristalsis in mice, increase the frequency of defecation, and effectively treat constipation. The mechanism of its action may be related to the direct or indirect regulation of intestinal motility by the PI3K-Akt signaling pathway.

Objective:To investigate the relationship between triglyceride glucose (TyG) index and major adverse cardiovascular events (maces) within 30 days after discharge in patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI) and its predictive value.Methods:A single center retrospective study was conducted to select AMI patients with PCI in the chest pain center of the Fourth Hospital of Changsha from January 2023 to January 2024 by a convenience sampling method. The clinical data and follow-up information of the patients were collected. The relationship between TyG index and Maces and its predictive value were tested by correlation analysis and logistic regression model.Results:A total of 110 patients met the inclusion and exclusion criteria, including 88 males and 22 females, aged (61.46 ± 12.42) years old. Spearman correlation analysis showed that TyG index was positively correlated with maces 30 days after discharge ( r = 0.421, P<0.001). Logistic regression analysis showed that TyG index was a risk factor for maces in AMI patients 30 days after discharge ( OR = 9.033, 95% CI 2.835-8.788, P<0.001). Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) was 0.854 (95% CI 0.765-0.943, P<0.001). Conclusions:TyG index has a significant positive correlation with maces within 30 days after discharge, which is an independent risk factor for maces within 30 days after discharge. Risk stratification by TyG index is more conducive to the management of clinical postoperative nursing and nursing education after discharge.

Objective:To investigate the relationship between triglyceride glucose (TyG) index and major adverse cardiovascular events (maces) within 30 days after discharge in patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI) and its predictive value.Methods:A single center retrospective study was conducted to select AMI patients with PCI in the chest pain center of the Fourth Hospital of Changsha from January 2023 to January 2024 by a convenience sampling method. The clinical data and follow-up information of the patients were collected. The relationship between TyG index and Maces and its predictive value were tested by correlation analysis and logistic regression model.Results:A total of 110 patients met the inclusion and exclusion criteria, including 88 males and 22 females, aged (61.46 ± 12.42) years old. Spearman correlation analysis showed that TyG index was positively correlated with maces 30 days after discharge ( r = 0.421, P<0.001). Logistic regression analysis showed that TyG index was a risk factor for maces in AMI patients 30 days after discharge ( OR = 9.033, 95% CI 2.835-8.788, P<0.001). Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) was 0.854 (95% CI 0.765-0.943, P<0.001). Conclusions:TyG index has a significant positive correlation with maces within 30 days after discharge, which is an independent risk factor for maces within 30 days after discharge. Risk stratification by TyG index is more conducive to the management of clinical postoperative nursing and nursing education after discharge.

Objective To explore the efficacy of the self-formulated Zhuzhang Formula in trea-ting the spleen deficiency with dysfunction of transportation syndrome of idiopathic short stature(ISS)and its effects on the growth rate,disease-related indicators,and bone metabolism indicators in affect-ed children.Methods A total of 80 children with ISS were enrolled as study subjects.They were randomly assigned to control group and observation group using random number table method,with 40 cases in each group.The control group received conventional western medicine treatment,while the observation group was administered self-formulated Zhuzhang Formula in addition to the treatment of the control group.Comparisons were made between the two groups in terms of clinical efficacy,TCM syndrome scores,growth parameters(monthly average height increment,annual growth rate),levels of disease-related indicators[serum insulin-like growth factor-1(IGF-1),bone morphogenetic pro-tein-2(BMP-2),insulin-like growth factor binding protein-3(IGFBP-3)],levels of bone metabo-lism indicators[bone alkaline phosphatase(BAP),type Ⅰ procollagen N-terminal propeptide(PⅠNP),type Ⅰ collagen cross-linked C-terminal telopeptide(β-CTX)],and the incidence of adverse reac-tions.Results The overall effective rate in the observation group was 97.50％,which was significantly higher than the 80.00％ in the control group(P＜0.05).After 3 and 6 months of intervention,the scores for symptoms such as short stature,sallow complexion,loss of appetite,weak voice and shortness of breath,limb weakness,and loose stools,as well as the total TCM syndrome scores,were lower in the observation group than those in the control group,with statistically significant differences(P＜0.05).After 6 months of intervention,the monthly average height increment and annual growth rate were higher in the observation group than those in the control group,and the differences were statistically significant(P＜0.05).After 3 and 6 months of intervention,the levels of IGF-1,BMP-2,IGFBP-3,BAP,and PⅠNP were higher in the observation group than those in the control group,while the level of β-CTX was lower,and the differences were statistically significant(P＜0.05).There was no statistically significant difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion The self-formulated Zhuchang Formula demon-strates remarkable efficacy in treating the spleen deficiency with dysfunction of transportation syndrome of ISS.It can alleviate clinical symptoms by regulating the levels of IGF-1,BMP-2,IGFBP-3,and bone metabolism indicators,thereby promoting the growth and development of affected children,and exhibits high safety.

Objective To observe hierarchical differences in brain functional networks in unilateral mesial temporal lobe epilepsy(mTLE)patients with different outcomes after surgery.Methods A total of 69 unilateral mTLE patients who underwent resection of epileptogenic lesion on the affected side were retrospectively enrolled.Based on Engel classification 1 year after surgery,the patients were divided into seizure free(SF)group and non-seizure free(NSF)group.Functional connectivity gradient analysis was employed to extract principal gradient explaining the highest variance on preoperative resting-state functional MRI(rs-fMRI),then the whole-brain gradient characteristics and principal gradient values within specific functional networks were compared between groups.Results Principal gradient connected default mode network(DMN)with sensorimotor network(SMN)along a continuous axis.Compared to SF group,NSF group showed a contracted gradient range at both ends(DMN and SMN)of the functional network and weakened hierarchical differentiation,and principal gradient value of DMN was higher,while that of SMN was lower than those in SF group(both P＜0.05).Conclusion Hierarchical differences in brain functional networks in unilateral mTLE patients with different outcomes after surgery mainly present as enhanced DMN and weakened SMN in NSF ones,and the latter two might serve as important neuroimaging markers for evaluating postoperative seizure recurrence.

Objective To observe the value of machine learning(ML)models based on brain functional network features combining clinical indicators for predicting postoperative outcomes of patients with drug-resistant mesial temporal lobe epilepsy(DR-mTLE).Methods Totally 84 patients with unilateral DR-mTLE who underwent surgery were retrospectively enrolled and classified into seizure free(SF)group(n=55)and non-seizure free(NSF)group(n=29)according to one-year postoperative follow-up.Clinical data were analyzed to screen independent predictors of postoperative outcomes.Based on brain preoperative resting-state functional MRI,brain functional networks were constructed using graph theory analysis,and 587 features were extracted.Five-fold cross validation was used to divide the data into training set and test set,then the optimal brain functional network features related to postoperative outcomes of DR-mTLE patients were selected.Combining with clinically relevant independent predictors,ML models were constructed using classifiers including Gaussian process(GP),logistic regression(LR),support vector machine(SVM)and quadratic discriminant analysis(QDA),respectively,and the prediction efficacy,calibration and clinical value of each ML model were evaluated.Results Both course of disease and lesion location were clinically relevant independent predictors of postoperative outcome of DR-mTLE patients(OR=0.928,5.710,P=0.010,0.016).Four optimal brain function network features were selected,including betweenness centrality of the third zone of cerebellar vermis,degree centrality of right globus pallidus,nodal efficiency of temporal left inferior temporal gyrus and nodal clustering coefficient of left inferior parietal lobule.The average area under the curve(AUC)of GP,LR,SVM and QDA models in test set was 0.868,0.864,0.875 and 0.870,respectively.Calibration curves and decision curve analysis indicated that each ML model had good calibration and high clinical net benefit.Conclusion ML models based on brain functional network features combining with clinical indicators could be used to effectively predict postoperative outcomes in DR-mTLE patients.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.