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.

ObjectiveTo investigate the protective effect of Xielitang on dextran sulfate sodium （DSS）-induced ulcerative colitis （UC） mice and its possible mechanism. MethodsDSS was used to establish UC model. Sixty mice were randomly divided into a normal group， a model group， a sulfasalazine group （0.6 g·kg^-1）， and low-， medium-， and high-dose Xielitang groups （1.67， 3.34， 6.68 g·kg^-1）. After treatment for 42 d， the colon length was recorded， and the disease activity index （DAI） score was calculated. Enzyme-linked immunosorbent assay （ELISA） was used to detect the serum levels of tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-10 （IL-10）. Hematoxylin-eosin （HE） staining was used to observe the pathomorphological changes of colon. Western blot was used to detect the protein expression of farnesoid X receptor （FXR）， small heterodimer partner （SHP）， liver receptor homolog-1 （LRH-1）， cholesterol 7α-hydroxylase （CYP7A1）， and fibroblast growth factor receptor 4 （FGFR4） in liver and FXR， sodium-dependent bile acid transporter （ASBT）， and fibroblast growth factor 15 （FGF15） in ileum. 16S rRNA sequencing was used to analyze the intestinal flora. Moreover， ultra-high performance liquid chromatography–tandem mass spectrometry was used to detect the bile acid content. ResultsCompared with the normal group， the model group showed significantly decreased colon length， IL-10 content， α-diversity index， abundance of Firmicutes and Lactobacillus， and content of deoxycholic acid （DCA） and lithocholic acid （LCA） （P<0.01）， significantly increased DAI score， IL-6 and TNF-α content， abundance of Bacteroidetes， and the content of cholic acid （CA）， chenodeoxycholic acid （CDCA）， and taurocholic acid （TCA） （P<0.05， P<0.01）， significantly down-regulated protein expression of FXR， SHP， and FGFR4 in liver and FXR， ASBT， and FGF15 in ileum （P<0.01）， and significantly up-regulated protein expression of LRH-1 and CYP7A1 in liver （P<0.01）. In addition， the structure of colonic mucosa was destroyed， and inflammatory cells infiltrated in the model group. Compared with the model group， Xielitang could significantly increase the colon length， IL-10 content， α-diversity index， the abundance of Firmicutes and Lactobacillus， and DCA and LCA content （P<0.05， P<0.01）， decrease DAI score， abundance of Bacteroidetes， and the content of IL-6， TNF-α， CA， CDCA， and TCA （P<0.01）， up-regulate the protein expression of FXR， SHP， and FGFR4 in liver and FXR， ASBT， and FGF15 in ileum （P<0.01）， and down-regulate the protein expression of LRH-1 and CYP7A1 in liver （P<0.01）. The pathological damage of colonic mucosa was obviously alleviated. ConclusionXielitang protects against UC probably by regulating the "intestinal microbiota-bile acid" axis， regulating intestinal flora imbalance， and maintaining bile acid homeostasis.

Objective To construct a risk prediction model of mild cognitive impairment(MCI)in the Chinese elderly population based on ensemble learning methods and verify it,to intervene in time and delay the progression of MCI.Methods A total of 8691 elderly people in the Chinese longitudinal health longevity study(CLHLS)from 2008 to 2018 were selected as the research objects,and the data from 2008 to 2014 were used as the training set.Data from 2014 to 2018 as a validation set.The Chinese version of the mini-mental state examination(CMMSE)was used to assess the cognitive status of the participants.Recursive feature elimination-random forest(RFE-RF),Boruta,mutual information(MI),and extra trees classifier(ETC)identified the predictors and screened out the common predictors.Use logistic regression(LR),random forest(RF),linear discriminant analysis(LDA),K-nearest neighbors(KNN),and na?ve bayes(NB)as the five single basic models,and a stacking ensemble model that integrates these basic models to predict the risk of mild cognitive impairment in elderly Chinese.Accuracy,precision,recall,and F1-score,as well as the area under the receiver operating characteristic(AUROC)and the area under the precision-recall curve(AUPRC),were used to evaluate the performance of the models.Results The performance of the stacking ensemble model under different feature selection algorithms is superior to any single base model,with AUROC greater than 0.9 in all cases.The feature selection algorithm ETC+stacking ensemble model performs best,and the AUROC and AUPRC in the test set are 0.912 and 0.872,respectively.Conclusion The stacking model shows superior performance in predicting MCI.This provides strong support for the strategy of healthy aging in China by timely identifying the high-risk groups of MCI,reducing the heavy burden of MCI brought by the elderly.

Objective:To evaluate the safety and efficacy of radiofrequency ablation（RFA）in the treatment of papillary thyroid microcarcinoma（PTMC）near and remote from the thyroid capsule.Methods:The clinical data，ultrasound images，ablation parameters and postoperative follow-up metrics were prospectively collected from 130 patients with pathologically confirmed PTMC in the Second Affiliated Hospital of Xi'an Jiaotong University who underwent RFA treatment between January 2023 and December 2024. According to whether the nodule margin was ≤ 2 mm from the thyroid capsule，the patients were divided into the subcapsular group（60 cases）and the remote from the capsule group（70 cases）. The clinical data，ablation parameters，complication rate，absorption of ablation lesions，tumor recurrence and metastasis were compared between the two groups.Results:The success rates of RFA in both groups were 100%. There was a statistically significant difference between the two groups at baseline in the location of nodules（ χ2=13.266， P=0.001）. After 12 months of routine follow-up，the incidence of complications was 5.00%（3/60）in the subcapsular group and 1.43%（1/70）in the remote from the capsule group，all complications recovered within 1 month，with no statistically significant difference（ P=0.407）. There were no significant changes in thyroid function［including free triiodothyronine（FT3），free thyroxine（FT4）and thyroid-stimulating hormone（TSH）］before and one month after RFA in the two groups（all P>0.05）. A statistically significant difference in the volume reduction rate（VRR）between the two groups was observed only when maximum diameter ≤ 5?mm at the 1st and 3rd months（all P<0.05）. For the remaining postoperative follow-up periods，there were no statistically significant differences in ablation zone volume or VRR between the two groups（all P>0.05）. At the final follow-up，for lesions with maximum diameter ≤ 5?mm，the tumor disappearance rate was 100% in both the subcapsular and remote from the capsule groups. For lesions with maximum diameter >5 mm，the rates were 78.4%（29/37）and 89.7%（26/29）in the respective groups，with no statistically significant difference between the two groups（ χ2 = 1.489， P =0.222）.There was no local tumor progression，lymph node metastasis or distant metastasis in either group. Conclusions:RFA is a safe and effective treatment for subcapsular PTMC，demonstrating comparable efficacy to that for PTMC located remote from the thyroid capsule.

ObjectiveTo investigate the association of SH2B1 rs7359397 （C>T） polymorphism with the progression to hepatic fibrosis in the elderly patients with metabolic dysfunction-associated steatotic liver disease （MASLD） in Beijing， China， and to provide an important genetic basis for the precise subtyping， prognostic evaluation， and individualized treatment of elderly MASLD patients in China. MethodsA total of 505 elderly patients （aged ≥65 years） who participated in regular physical examination in Mentougou Kuangshan Hospital of Beijing Jingmei Group General Hospital from November 2020 to September 2021 and were diagnosed with MASLD by abdominal ultrasound were enrolled as MASLD group， and 381 elderly population who underwent physical examination in the same community hospital during the same period of time and were not found to have MASLD by abdominal ultrasound were enrolled as control group. FibroScan was used to measure liver fat content and determine fibrosis stage. The 96-well microfluidic chip technique was used to identify SH2B1 rs7359397 polymorphism. The independent-samples t test was used for comparison of normally distributed continuous data between the two groups， and the chi-square test or the adjusted chi-square test was used for comparison of categorical data between the two groups. Univariate and multivariate Logistic regression analyses were used to identify the independent predictive factors for MASLD and its comorbidities. ResultsCompared with the control group， the MASLD group had a significantly younger age and significantly higher levels of waist circumference， hip circumference， waist-hip ratio， body mass index （BMI）， alanine aminotransferase， aspartate aminotransferase， triglyceride， platelet count， and fibrosis-4 （FIB-4） index， as well as a significantly lower level of high-density lipoprotein cholesterol （all P<0.05）. Among the 381 patients in the control group， 264 （69.29%） had genotype CC and 117 （30.71%） had genotype CT+TT， while among the 505 patients in the MASLD group， 317 （62.77%） had genotype CC and 188 （37.23%） had genotype CT+TT， suggesting that the MASLD group had a significantly higher proportion of patients with genotype CT+TT compared with the control group （χ²=4.09， P=0.043）. In the MASLD group， compared with the genotype CC group， the genotype CT+TT group had a significantly lower proportion of patients with FIB-4 ≥2 or atherosclerotic cardiovascular diseases （P<0.05）. The multivariate Logistic regression analysis showed that after adjustment for age， sex， and BMI， carrying T allele was a protective factor against progressive hepatic fibrosis （odds ratio ［OR］=0.481， 95% confidence interval ［CI］： 0.249 — 0.929， P=0.029）. In the subgroups of comorbidities with hypertension， metabolic syndrome， and obesity， genotype CT+TT was associated with a significant reduction in the risk of progressive hepatic fibrosis （hypertension： OR=0.27， 95%CI：0.09 — 0.77， P=0.014； metabolic syndrome： OR=0.30， 95%CI： 0.11 — 0.79， P=0.015； obesity： OR=0.11， 95%CI： 0.03 — 0.48， P=0.003）. After adjustment for age， sex， and BMI， in the patients with MASLD， the patients with genotype CT+TT had a significant reduction in the prevalence rate of atherosclerotic cardiovascular diseases compared with those with genotype CC （OR=0.506， 95%CI：0.336 — 0.761， P=0.001）. ConclusionSH2B1 rs7359397 （C>T） polymorphism is associated with the reduction in the risk of hepatic fibrosis and atherosclerotic cardiovascular diseases in MASLD patients.

Objective:To analyze the trend of infertility disease burden from 1990 to 2019 and predict the age-standardized prevalence rate (ASPR) and age-standardized disability-adjusted life-year (DALY) rate of male and female infertility for 2020—2029, providing a certain reference for the prevention and treatment of infertility diseases.Methods:Based on the Global Burden of Disease 2019, prevalence, ASPR, DALY rate, and age-standardized DALY rate were used to evaluate the global burden of infertility comprehensively. The estimated annual percentage change was used to describe trends in the disease burden of infertility in 21 regions worldwide. The Bayesian age period cohort model was used to predict the ASPR and age-standardized DALY rate for male and female infertility in 204 countries and regions from 2020 to 2029. Sensitivity analysis was performed using the autoregressive integrated moving average model.Results:The prevalence, DALY rate, ASPR and age-standardized DALY rate of global male infertility increased from 319.52 per 100 000,1.82 per 100 000, 2 856.53 per 100 000, and 16.19 per 100 000 in 1990 to 565.30 per 100 000, 3.22 per 100 000, 3 398.53 per 100 000, and 19.36 per 100 000 in 2019, respectively. The prevalence, DALY rate, ASPR, and age-standardized DALY rate of global female infertility increased from 656.67 per 100 000, 3.53 per 100 000, 6 036.36 per 100 000, and 32.27 per 100 000 in 1990 to 1 223.78 per 100 000, 6.59 per 10 000, 7 483.12 per 100 000, and 40.33 per 100 000 in 2019, respectively. The burden of infertility disease was the highest in men and women aged 30-34 years, and the ASPR and age-standardized DALY rates were 4 407.47 per 100 000, 25.08 per 100 000, 10 270.55 per 100 000 and 55.65 per 100 000, respectively. Only in 45-49 years of age, the prevalence of infertility (11.31 per 100 000) and DALY rate (0.06 per 100 000) in women were lower than those in men (15.68 per 100 000 and 0.08 per 100 000). In addition, the burden of infertility was the lowest in high socio-demographic index regions. Cameroon had the highest ASPR (7 652.40 per 100 000) and age-standardized DALY rate (43.94 per 100 000) for male infertility. Chinese women had the highest ASPR (20 402.30 per 100 000) and age-standardized DALY rate (106.16 per 100 000) of infertility. The forecast results show that the burden of male and female infertility diseases will increase in 204 countries and regions from 2020 to 2029.Conclusion:The burden of infertility diseases in men and women increased in 204 countries and regions from 1990 to 2019, and it is predicted that the global burden of infertility diseases will continue to rise in 2020—2029. Preliminary screening of infertility should be carried out as soon as possible, health education should be strengthened and effective prevention and treatment strategies should be formulated.

Objective:To analyze the trend of infertility disease burden from 1990 to 2019 and predict the age-standardized prevalence rate (ASPR) and age-standardized disability-adjusted life-year (DALY) rate of male and female infertility for 2020—2029, providing a certain reference for the prevention and treatment of infertility diseases.Methods:Based on the Global Burden of Disease 2019, prevalence, ASPR, DALY rate, and age-standardized DALY rate were used to evaluate the global burden of infertility comprehensively. The estimated annual percentage change was used to describe trends in the disease burden of infertility in 21 regions worldwide. The Bayesian age period cohort model was used to predict the ASPR and age-standardized DALY rate for male and female infertility in 204 countries and regions from 2020 to 2029. Sensitivity analysis was performed using the autoregressive integrated moving average model.Results:The prevalence, DALY rate, ASPR and age-standardized DALY rate of global male infertility increased from 319.52 per 100 000,1.82 per 100 000, 2 856.53 per 100 000, and 16.19 per 100 000 in 1990 to 565.30 per 100 000, 3.22 per 100 000, 3 398.53 per 100 000, and 19.36 per 100 000 in 2019, respectively. The prevalence, DALY rate, ASPR, and age-standardized DALY rate of global female infertility increased from 656.67 per 100 000, 3.53 per 100 000, 6 036.36 per 100 000, and 32.27 per 100 000 in 1990 to 1 223.78 per 100 000, 6.59 per 10 000, 7 483.12 per 100 000, and 40.33 per 100 000 in 2019, respectively. The burden of infertility disease was the highest in men and women aged 30-34 years, and the ASPR and age-standardized DALY rates were 4 407.47 per 100 000, 25.08 per 100 000, 10 270.55 per 100 000 and 55.65 per 100 000, respectively. Only in 45-49 years of age, the prevalence of infertility (11.31 per 100 000) and DALY rate (0.06 per 100 000) in women were lower than those in men (15.68 per 100 000 and 0.08 per 100 000). In addition, the burden of infertility was the lowest in high socio-demographic index regions. Cameroon had the highest ASPR (7 652.40 per 100 000) and age-standardized DALY rate (43.94 per 100 000) for male infertility. Chinese women had the highest ASPR (20 402.30 per 100 000) and age-standardized DALY rate (106.16 per 100 000) of infertility. The forecast results show that the burden of male and female infertility diseases will increase in 204 countries and regions from 2020 to 2029.Conclusion:The burden of infertility diseases in men and women increased in 204 countries and regions from 1990 to 2019, and it is predicted that the global burden of infertility diseases will continue to rise in 2020—2029. Preliminary screening of infertility should be carried out as soon as possible, health education should be strengthened and effective prevention and treatment strategies should be formulated.

Objective To construct a risk prediction model of mild cognitive impairment(MCI)in the Chinese elderly population based on ensemble learning methods and verify it,to intervene in time and delay the progression of MCI.Methods A total of 8691 elderly people in the Chinese longitudinal health longevity study(CLHLS)from 2008 to 2018 were selected as the research objects,and the data from 2008 to 2014 were used as the training set.Data from 2014 to 2018 as a validation set.The Chinese version of the mini-mental state examination(CMMSE)was used to assess the cognitive status of the participants.Recursive feature elimination-random forest(RFE-RF),Boruta,mutual information(MI),and extra trees classifier(ETC)identified the predictors and screened out the common predictors.Use logistic regression(LR),random forest(RF),linear discriminant analysis(LDA),K-nearest neighbors(KNN),and na?ve bayes(NB)as the five single basic models,and a stacking ensemble model that integrates these basic models to predict the risk of mild cognitive impairment in elderly Chinese.Accuracy,precision,recall,and F1-score,as well as the area under the receiver operating characteristic(AUROC)and the area under the precision-recall curve(AUPRC),were used to evaluate the performance of the models.Results The performance of the stacking ensemble model under different feature selection algorithms is superior to any single base model,with AUROC greater than 0.9 in all cases.The feature selection algorithm ETC+stacking ensemble model performs best,and the AUROC and AUPRC in the test set are 0.912 and 0.872,respectively.Conclusion The stacking model shows superior performance in predicting MCI.This provides strong support for the strategy of healthy aging in China by timely identifying the high-risk groups of MCI,reducing the heavy burden of MCI brought by the elderly.

Objective:To evaluate the safety and efficacy of radiofrequency ablation（RFA）in the treatment of papillary thyroid microcarcinoma（PTMC）near and remote from the thyroid capsule.Methods:The clinical data，ultrasound images，ablation parameters and postoperative follow-up metrics were prospectively collected from 130 patients with pathologically confirmed PTMC in the Second Affiliated Hospital of Xi'an Jiaotong University who underwent RFA treatment between January 2023 and December 2024. According to whether the nodule margin was ≤ 2 mm from the thyroid capsule，the patients were divided into the subcapsular group（60 cases）and the remote from the capsule group（70 cases）. The clinical data，ablation parameters，complication rate，absorption of ablation lesions，tumor recurrence and metastasis were compared between the two groups.Results:The success rates of RFA in both groups were 100%. There was a statistically significant difference between the two groups at baseline in the location of nodules（ χ2=13.266， P=0.001）. After 12 months of routine follow-up，the incidence of complications was 5.00%（3/60）in the subcapsular group and 1.43%（1/70）in the remote from the capsule group，all complications recovered within 1 month，with no statistically significant difference（ P=0.407）. There were no significant changes in thyroid function［including free triiodothyronine（FT3），free thyroxine（FT4）and thyroid-stimulating hormone（TSH）］before and one month after RFA in the two groups（all P>0.05）. A statistically significant difference in the volume reduction rate（VRR）between the two groups was observed only when maximum diameter ≤ 5?mm at the 1st and 3rd months（all P<0.05）. For the remaining postoperative follow-up periods，there were no statistically significant differences in ablation zone volume or VRR between the two groups（all P>0.05）. At the final follow-up，for lesions with maximum diameter ≤ 5?mm，the tumor disappearance rate was 100% in both the subcapsular and remote from the capsule groups. For lesions with maximum diameter >5 mm，the rates were 78.4%（29/37）and 89.7%（26/29）in the respective groups，with no statistically significant difference between the two groups（ χ2 = 1.489， P =0.222）.There was no local tumor progression，lymph node metastasis or distant metastasis in either group. Conclusions:RFA is a safe and effective treatment for subcapsular PTMC，demonstrating comparable efficacy to that for PTMC located remote from the thyroid capsule.

Objective To construct the theoretical framework of rehabilitation big data based on International Classification of Func-tioning,Disability and Health(ICF). Methods Drawing upon international rehabilitation policy documents,such as the World Health Organization's Rehabili-tation in health systems;Rehabilitation in health systems:guide for action;Rehabilitation indicator menu:a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation(FRAME);Template for Rehabilita-tion Information Collection(TRIC):a tool accompanying the Systematic Assessment of Rehabilitation Situation(STARS);and Framework and Standards for Country Health Information Systems;this study examined the com-position and function of rehabilitation big data.The content structure of the rehabilitation big data domain was an-alyzed using the World Health Organization Family of International Classifications(WHO-FICs).Furthermore,the generation patterns of rehabilitation big data was constructed drawing on the Health Metrics Network and big data hierarchical classification. Results Within the six primary elements of the health service system,the information system element was particularly significant,encompassing a substantial branch known as rehabilitation big data.There were three components of rehabilitation big data:health condition,health-related factors and health services.The content framework for this data was derived from the WHO-FICs framework,which covered three dimensions:health and function,dis-ease and function,and disease,function and intervention.A comprehensive model for generating and applying re-habilitation big data in rehabilitation services was developed in line with the requirements for constructing big da-ta architectures.The sources of this data included population censuses,social registration information,population surveys,resources,services and personal records.The result chain of rehabilitation big data encompassed five major processes:input,process,output,outcome and impact.The processing and utilization of this data involved collection,storage,management,analysis and application. Conclusion A theoretical framework for rehabilitation big data has been constructed based on the ICF theory.