Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

Objective To explore the characteristics,potential challenges,and optimization paths of high-quality development policies for public hospitals in China,and to provide reference for policy formulation and implementation.Methods The 31 policy documents on high-quality development of public hospitals issued at the central and provincial levels between 2021 and 2024 were coded using Nvivo 11 software,and a three-dimensional analytical framework was constructed on the basis of the policy tools,stakeholders,and system dimensions,combining both quantitative and qualitative methods for content analysis.Results It found that the distribution of policy content in the three dimensions was characterized by stage imbalance:policy tools were mainly environmental,followed by supply,and demand;stakeholder attention was focused on public hospitals and healthcare administrations,and patient attention was low;The system dimension focused mainly on the macro level,with less distribution at the meso and micro levels.Although the unbalanced distribution of policy instruments is relevant at certain stages,the long-term structural imbalance may lead to insufficient systemic policies and weakened stakeholder synergies,and there is an urgent need to optimize the structure of instruments.Conclusions It is recommended to increase the proportion of demand-based policy instruments in policy design and dynamically adjust the synergistic application of the three types of instruments;to strengthen the attention to vulnerable stakeholders,such as patients;and to optimize the design of policies at the meso-levels and micro-levels in order to enhance the systemicity and sustainability of policy implementation.

Objective To analyze the efficacy of different nucleoside(acid)analogs(NAs)used as monotherapy and in combination with pegylated interferon α-2b(Peg-IFN-α-2b)in the treatment of chronic hepatitis B(CHB).Methods A retrospective analysis was conducted on 229 CHB patients who visited the Hepatology Department of the Third People's Hospital of Kunming from September 2022 to August 2023.Patients were divided into six groups based on their antiviral regimen:entecavir(ETV)group(A,n=47),ETV combined with Peg-IFN-α-2b group(B,n=19),Tenofovir Alafenamide(TMF)group(C,n=64),TMF combined with Peg-IFN-α-2b group(D,n=35),Tenofovir Disoproxil Fumarate(TDF)group(E,n=29),and TDF combined with Peg-IFN-α-2b group(F,n=35).The blood routine,liver function,kidney function,HBV serological markers,and HBV-DNA levels were compared before and after 24 weeks of treatment.Results After 24 weeks of treatment,there were no statistically significant differences in efficacy rates and HBV-DNA positivity rates between the monotherapy with NAs and the combination with Peg-IFN-α-2b(P>0.05).Comparing before and after treatment,the ETV group had the highest effective rate,while TDF combined with Peg-IFN-α-2b group had the lowest effective rate.TDF group had the highest efficiency,while ETV combined with Peg-IFN-α-2b group had the lowest efficiency.Except for ETV+Peg-IFN-α-2b and TDF+Peg-IFN-α-2b groups,the HBV-DNA positivity rates in the other four groups were significantly lower after treatment compared to before(P<0.05).There was a significant difference in HBsAg levels among the different treatment regimens of monotherapy with NAs and combination with Peg-IFN-α-2b(P=0.0483).Additionally,except for the ETV and TDF groups,the serum HBsAg levels in the other four groups were significantly lower after treatment compared to before(P<0.05).There were no significant difference in LSM and GFR before and after treatment(P>0.05).In the monotherapy groups,ALT and GGT levels were significantly lower after treatment compared to before(P<0.05),while in the combination Peg-IFN-α-2b group,WBC,NEUT,and PLT levels were significantly lower after treatment compared to before(P<0.05).Conclusion Combination therapy with Peg-IFN-α-2b can reduce HBsAg levels and may be more effective in controlling the virus;however,it may cause adverse reactions such as bone marrow suppression,increasing risks.Physicians and patients need to weigh the benefits against the risks and develop personalized treatment plans based on individual circumstances.

Cardiovascular disease(CVD)is currently one of the most severe diseases endangering human health,encompassing myocardial ischemia syndrome,myocardial fibrosis,atrial fibrillation,and other conditions.MicroRNAs(miRNAs/miR)are a class of small non-coding RNAs that can bind to specific se-quences and subsequently regulate post-transcriptional processing,translation,or epigenetic modifications,thereby modulating gene expression.Studies have found that miR-223 is associated with the occurrence and de-velopment of CVD and represents a potential specific therapeutic target.This article summarizes the relevant re-search on miR-223 in CVD,focusing on myocardial ischemia syndrome,myocardial fibrosis,and atrial fibrilla-tion,and discusses its application prospects and challenges as a specific therapeutic target,providing new ideas for the diagnosis and treatment of CVD.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

Objective To explore the characteristics,potential challenges,and optimization paths of high-quality development policies for public hospitals in China,and to provide reference for policy formulation and implementation.Methods The 31 policy documents on high-quality development of public hospitals issued at the central and provincial levels between 2021 and 2024 were coded using Nvivo 11 software,and a three-dimensional analytical framework was constructed on the basis of the policy tools,stakeholders,and system dimensions,combining both quantitative and qualitative methods for content analysis.Results It found that the distribution of policy content in the three dimensions was characterized by stage imbalance:policy tools were mainly environmental,followed by supply,and demand;stakeholder attention was focused on public hospitals and healthcare administrations,and patient attention was low;The system dimension focused mainly on the macro level,with less distribution at the meso and micro levels.Although the unbalanced distribution of policy instruments is relevant at certain stages,the long-term structural imbalance may lead to insufficient systemic policies and weakened stakeholder synergies,and there is an urgent need to optimize the structure of instruments.Conclusions It is recommended to increase the proportion of demand-based policy instruments in policy design and dynamically adjust the synergistic application of the three types of instruments;to strengthen the attention to vulnerable stakeholders,such as patients;and to optimize the design of policies at the meso-levels and micro-levels in order to enhance the systemicity and sustainability of policy implementation.

OBJECTIVE To analyze the traditional Chinese medicine （TCM） emergency management policy texts in China， reveal the characteristics， problems and improvement directions of Chinese medicine emergency management policies in China， and provide references and lessons for improving the level of Chinese medicine emergency management. METHODS Twenty-four TCM emergency management policy texts issued at the central level from 2016 to 2023 were coded and analyzed using Nvivo11 software to construct a three-dimensional analysis framework based on policy tools， stakeholders and policy strength. RESULTS In the policy tools dimension， the environmental type was the most （46.74%）， the supply type was the second （31.80%）， and the demand type was the least （21.46%）； in the stakeholder dimension， there were more healthcare institutions （40.63%） and government departments （31.25%）， and fewer healthcare workers （14.84%） and residents （13.28%）； in the policy strength dimension， the overall policy strength was poor， and the differences in effectiveness across policy instruments and stakeholders were more significant. The cross-cutting results showed that there was a certain degree of mismatch in policy instruments， stakeholders and policy strength. CONCLUSIONS The use of supply-oriented policy tools is slightly lacking， and the use of policy tools should be optimized in a coordinated manner； the distribution of stakeholders is relatively unbalanced， and synergies among stakeholders should be enhanced； the overall strength of policies is poor， and the top-level design of relevant policies should be improved.

Objective To evaluate the methylation levels of DNA at six specific CpG sites located in the mRNA region of histone cluster 4 subfamily F member 6(HIST1H4F)gene and determine their diagnostic signifi-cance about lung cancer.Methods The DNA methylation levels of 15 cases of lung cancer and adjacent paired nor-mal lung tissue were detected using pyrophosphate sequencing.Based on preliminary evaluation,a methylation-sensitive restriction enzyme-fluorescence quantitative PCR(MSRE-qPCR)method was developed to detect DNA methylation levels in the test group(60 cases of lung adenocarcinoma,38 cases of squamous cell carcinoma,30 cases of benign diseases,and 26 cases of normal lung tissue)and the validation group(36 cases of lung adenocarci-noma,16 cases of squamous cell carcinoma,21 cases of benign diseases,and 23 cases of normal lung tissue).The diagnostic value was evaluated using ROC curves.Results The results of pyrophosphate sequencing showed that the methylation levels of lung cancer were significantly higher than that of paired normal lung tissue(P<0.005).The detection results of MSRE-qPCR showed that the areas under the ROC curve for diagnosing lung cancer in the test group and validation group were 0.894 and 0.888,with sensitivity of 76.5%and 73.1%,and specificity of 92.9%and 97.7%,respectively.The methylation levels were significantly positively correlated with smoking in lung cancer patients(r=0.273,P<0.01).Conclusion The six CpG sites in the mRNA region of the HIST1H4F gene can serve as biomarkers for diagnosing lung cancer,providinga new molecular target for clinical lung cancer diagnosis.

Chronic fatigue syndrome(CFS)is a chronic comprehensive disease with a slow course and often accompanied by a variety of physical and psychiatric symptoms.At present,the incidence rate is on the rise.Based on the theory of"qi-pulse smooth and unobstructed",the pathogenesis of CFS is considered to be the loss of spleen and kidney and the deficiency of qi-pulse as the root;liver and lung disorders,qi-pulse stagnation as the pivot;wind fire invasion,phlegm blood stasis as the superficiality.Treatment should focus on tonifying the spleen and tonifying the kidneys to treat its root cause.According to the degree of deficiency of spleen and kidney and the emphasis of deficiency of qi-blood yin-yang,Buzhong Yiqi Decoction,Guipi Decoction,Shengyang Yiwei Decoction,Linggui Zhugan Decoction and Shenqi Pills should be selected flexibly.The methods of soothing the liver and regulating the lungs to regulate their pivot,harmonizing the liver and lungs,and using both ascending and descending functions should be used.Chaihu Shugan Powder,Xiaoyao Powder,Sini Powder,Guizhi Decoction,Shengmai Powder,etc.could be selected flexibly according to the disease location and disease focus.Clearing wind and clearing heat,eliminating phlegm and promoting blood circulation should be used to treat its superficiality,emphasizing tonifying deficiency and resolving depression.According to the different pathogenesis of patients,the corresponding treatment method should be flexibly chosen to supplement with medication.One medical case was attached in this article as the evidence,in order to provide reference for the TCM treatment of CFS.