ObjectiveTo investigate the triglyceride-glucose (TyG) index and the level of serum homocysteine (Hcy) in association with the incidence of stroke in type 2 diabetes mellitus (T2DM) patients. MethodsBased on the chronic disease risk factor surveillance cohort in Pudong New Area, Shanghai, excluding those with stroke in baseline survey, T2DM patients who joined the cohort from January 2016 to October 2020 were selected as the research subjects. During the follow-up period, a total of 318 new-onset ischemic stroke patients were selected as the case group, and a total of 318 individuals matched by gender without stroke were selected as the control group. The Cox proportional hazards regression model was used to adjust for confounding factors and explore the serum TyG index and the Hcy biochemical indicator in association with the risk of stroke. ResultsThe Cox proportional hazards regression results showed that after adjusting for confounding factors, the risk of stroke in T2DM patients with 10 μmol·L⁻¹-¹ and Hcy>15 μmol·L⁻¹ was 1.532 times (95%CI: 1.017‒2.309 times, P=0.041) and 1.738 times (95%CI: 1.119‒2.699 times, P=0.014) higher respectively, compared to T2DM patients with Hcy≤10 μmol·L⁻¹. T2DM patients with TyG>9.074 had 1.396 times higher risk of stroke (95%CI: 1.091‒1.787, P=0.008) compared to those with TyG≤9.074. The study found that urea and α1-antitrypsin (α1-AT) were independent risk factors for the incidence of stroke in T2DM patients. For every unit increase in urea andα1-AT, the risk of stroke in T2DM patients increased by 233.6% (HR=3.336, 95%CI: 1.588‒7.009, P=0.001) and 11.3% (HR=1.113, 95%CI: 1.028‒1.205, P=0.008), respectively. Cumulative risk curves showed that Hcy>10 μmol·L⁻¹ and TyG>9.074 accelerated the time to stroke occurrence in T2DM patients. ConclusionElevated levels of Hcy>10 μmol·L⁻¹ and a higher TyG index are risk factors for stroke in T2DM patients. Effective interventions for Hcy and TyG should be conducted for diabetic patients to reduce the incidence of stroke.

ObjectiveTo evaluate the intervention effect of meteorological risk forecasting service on acute onset and medical expenses of chronic obstructive pulmonary disease（COPD） patients， and to provide scientific basis for the establishment of health management model for chronic obstructive pulmonary disease（COPD） patients. MethodsStudy subjects were recruited from chronic obstructive pulmonary patients aged ≥40 in Pudong New Area. Propensity score matching method was used to determine the intervention group and the control group. The control group received regular health education and follow-up management， and the intervention group was provided with meteorological and environmental risk forecasting services through WeChat， mobile phone short message service（SMS）and telephone. Finally， a total of2 589 subjects were included in the analysis， including 1 300 in the intervention group and 1 289 in the control group. General demographic data， past medical history and family history of COPD， COPD related knowledge and practice survey， COPD related symptom assessment， acute onset， health service utilization and medical expenses before and after intervention were collected through questionnaire survey. The differences of acute attack， health service utilization and related medical expenses between the two groups before and after intervention were compared to evaluate the intervention effect. ResultsIn terms of acute attacks， after intervention， the incidence of acute attacks in the intervention group was lower than that before intervention（χ²=52.901， P<0.001）， and the incidence of acute attacks in the groups with different intervention methods was lower than that before intervention （P<0.001）. WeChat had the best effect， decreasing the incidence by 14.4%， followed by mobile phone SMS SMS decreasing by 12.3%. In terms of utilization of health services， the outpatient rate due to acute attack was lower in the intervention group after intervention than that before intervention （χ²=7.129， P=0.008）， and the outpatient rate due to acute attack was lower in the subjects who received the forecast service through mobile phone SMS than that before intervention （χ²=4.675， P<0.001）. In terms of medical expenses， there was no significant difference between control group and intervention group with different intervention methods before intervention （P>0.05）. After intervention， the difference between the control group and the intervention group with different intervention methods was statistically significant （H=11.864， P<0.05）. The results of multiple comparisons showed that compared with the control group， the average annual medical expenses of patients receiving mobile phone SMS and telephone forecasting services after intervention were lower than those of the control group， and the difference was statistically significant （P<0.05）. ConclusionMeteorological risk forecasting service can reduce the acute onset of COPD， reduce the rate of consultation and medical expenses due to acute onset， and provide scientific basis for the basic COPD health management model.

Objective To explore the relationship between baseline urinary protein levels and the onset of chronic obstructive pulmonary disease (COPD). Methods A questionnaire survey, blood and urine sample collection, physical examination, and pulmonary function test were conducted among permanent residents over 40 years old in Pudong New Area, Shanghai. The subjects were divided into four groups based on the baseline urine albumin-to-creatinine ratio (ACR) quartiles (0~1.65 mg/g, 1.65~4.89 mg/g, 4.89~10.78 mg/g, and ≥10.78 mg/g). Cox regression analysis was used to explore the relationship between ACR levels and the incidence of COPD in middle-aged and elderly people. Results Among the 3 105 subjects, the median follow-up time was 3.212 years (P25~P75：3.102~3.473). 116 new cases of COPD were observed, with an incidence density of 10.423 per 1000 person-years. The incidence densities for COPD at four ACR levels were 7.922 per 1 000 person-years, 8.300 per 1 000 person-years , 11.419 per 1 000 person-years, and 13.843 per 1 000 person-years, respectively. Cox regression analysis revealed that as the ACR level increased, there was a rising trend in the incidence rate of COPD (χ²=4.396, P=0.036). After adjusting for gender, age, education level, occupational exposure to dust, history of childhood pneumonia, smoking, family history of COPD, central obesity, and hypertension, the risk of developing COPD was 2.499 times higher (95% CI: 1.460~4.276) for ACR levels ≥10.78 mg/g compared to the reference group with a baseline ACR level of 0~1.65 mg/g. Conclusion Elevated ACR levels in middle-aged and elderly population may increase the risk of COPD, and early monitoring of urine protein levels is beneficial for COPD prevention.

Objective:To investigate the changing trend of mortality rate and death cause spectrum among household-registered residents aged 60 and above in Beijing from 2007 to 2020.Methods:The mortality data was collected from the Beijing Death Information Registration and Management System. We calculated the mortality rates and constituent ratios by gender, age groups, and death causes and estimated the changing trend of mortality rate and average annual percent change (AAPC) by Joinpoint 4.3.1.Results:The crude mortality rate decreased from 27.62‰ in 2007 to 23.55‰ in 2020 (AAPC=-1.18%, P<0.001), and the standard rate also decreased from 25.39‰ in 2007 to 19.85‰ in 2020 (AAPC=-1.68%, P<0.001) among registered residents aged 60 and above in Beijing. The top 5 causes of death were heart diseases, malignant tumors, cerebrovascular diseases, respiratory diseases, and endocrine and nutritional metabolic diseases, accounting for 87.1% of the total deaths. The mortality rates of heart diseases (AAPC=-1.08%, P=0.024), cerebrovascular diseases (AAPC=-3.79%, P<0.001), malignant tumors (AAPC=-0.31%, P=0.006) and respiratory diseases (AAPC=-5.56%, P=0.007) showed a decreasing trend. The rate of injury and poisoning showed an increasing trend (AAPC=1.54%, P=0.001), while no statistically significant change was found in endocrine and nutritional metabolic diseases mortality rates (AAPC=-1.46%, P=0.054). Conclusions:The mortality rate of registered residents aged 60 years and over in Beijing showed a downward trend from 2007 to 2020. Heart diseases, cerebrovascular diseases, malignant tumors, and respiratory diseases should be treated as the key diseases for prevention and control, and targeted measures should be taken to improve the health level of the elderly population.

Objective To construct a traditional Chinese medicine(TCM)knowledge base using knowl-edge graph based on deep learning methods,and to explore the application of joint models in intelligent question answering systems for TCM. Methods Textbooks Prescriptions of Chinese Materia Medica and Chinese Materia Medicawere applied to construct a comprehensive knowledge graph serving as the founda-tion for the intelligent question answering system.In the study,a BERT+Slot-Gated(BSG)deep learning model was applied for the identification of TCM entities and question inten-tions presented by users in their questions.Answers retrieved from the knowledge graph based on the identified entities and intentions were then returned to the user.The Flask framework and BSG model were utilized to develop the intelligent question answering sys-tem of TCM. Results A TCM knowledge map encompassing 3 149 entities and 6 891 relational triples based on the prescriptions and Chinese materia medica was drawn.In the question answer-ing test assisted by a question corpus,the F1 value for recognizing entities when answering 20 types of TCM questions was 0.996 9,and the accuracy rate for identifying intentions was 99.75%.This indicates that the system is both feasible and practical.Users can interact with the system through the WeChat Official Account platform. Conclusion The BSG model proposed in this paper achieved good results in experiments by increasing the vector dimension,indicating the effectiveness of the joint model method and providing new research ideas for the implementation of intelligent question answering sys-tems in TCM.

Objective To understand the proficiency level and sources of Traditional Chinese Medicine(TCM)health education among hemodialysis patients,in order to provide the basis for promoting the application of TCM nursing in hemodialysis patients.Methods Utilizing a convenience sampling approach,we conducted a survey from April to May 2023 involving hemodialysis patients from 7 tertiary TCM hospitals across Beijing,Hebei Province,Sichuan Province,and other regions.Custom-made questionnaires were utilized,gathering general information,respons-es conceming the level of mastery on TCM health education,and their primary sources of such knowledge.Results A total of 413 questionnaires were disseminated,and 392 proved valid,yielding a valid response rate of 94.92％.The score of patient's knowledge on TCM health education averaged(8.25±3.73),and an average score rate of 48.53％was obtained.In the patients undergoing hemodialysis,a relatively larger number of people possess knowl-edge of TCM health knowledge about relieving symptoms(50.8％～55.9％)and traditional Chinese daily life routines(56.4％～90.1％).However,fewer people are aware of how to use the five-tone therapy method for emotional inter-vention(40.8％)and principle of taking restorative Traditional Chinese Medicine(24.5％～36.7％),the dietary prin-ciples of"nurturing yang in spring and summer,and nurturing yin in autumn and winter"(14.3％),and theories of TCM kidney functions(9.9％).Approximately 23.0％of the patients sourced their TCM health education knowledge from new media platforms.Compared with new media method alone,patients who utilized only traditional education-al platforms(P=0.020),and those who combined both new media and traditional methods(P=0.018)demonstrated higher proficiency in TCM health education.Conclusion Hemodialysis caregivers are urged to develop a TCM health education framework that emphasizes emotional well-being and traditional wellness concepts,thereby fostering patient-centric TCM health ideologies.Hemodialysis education personnel are encouraged to leverage new media whilst ensuring education quality and effective outcomes.

Objective To retrieve relevant literature on risk prediction model for methicillin-resistant Staphylococcus aureus (MRSA) infection among hospitalized patients from databases and evaluate the predictive model. Methods The literature on risk prediction models for MRSA infection among hospitalized patients was retrieved from PubMed, Embase, Scopus, Cochrane library, China National Knowledge Infrastructure (CNKI), WanFang data, and VIP database, with a time range from the inception of the database to January 1, 2024. Two researchers independently screened the literature, extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was applied to evaluate the risk of bias and applicability of the prediction model in the literature, and descriptive analysis was conducted. Results A total of 12 articles (15 prediction models) were included in this study, with significant differences in the total sample size, the number of MRSA infection events, sample size of modeling, and sample size of validation among the studies. Common predictors in the prediction models were admission to the intensive care unit, antibiotic use, history of residence in nursing facilities, age, chronic kidney disease, and previous hospitalization history. Nine articles conducted internal validation, and three articles conducted both internal and external validation. Nine articles reported the area under the receiver operating characteristic curve, and only three articles reported the calibration of the model based on the Hosmer-Lemeshow test. PROBAST analysis showed that 10 articles were assessed as high risk bias, mainly stemming from statistical analysis. Conclusion Most of the MRSA infection risk prediction models in the current literature have good predictive efficacy for MRSA infection, but they all have higher overall risk of bias, and only a few models have undergone external validation. Researchers should follow PROBAST standards to construct and externally validate models in the future so as to develop models suitable for clinical practice.

Purpose: Invasive ductal carcinoma (IDC) accounts for 90% of triple-negative breast cancer (TNBC). IDC is mainly derived from the breast ductal epithelium which is innervated by the 4th to 6th thoracic sympathetic nerves. However, little is known about the contribution of the interactions between sympathetic nerves and breast cancer cells to the malignant progression of TNBC. Methods: The expression levels of the β2 -adrenergic receptor (β2 -AR, encoded by ADRB2 gene), nerve growth factor (NGF), and tropomyosin receptor kinase A (TrkA) were determined using immunohistochemistry (IHC). NGF expression levels in the serum were compared by enzyme-linked immunosorbent assay (ELISA). Cell proliferation was assessed using the Cell Counting Kit-8 assay. The β2 -AR, NGF, p-ERK, and p-CERB expression levels were determined using western blotting. TNBC cells and neuronal cells of the dorsal root ganglion (DRG) in 2-day-old Sprague Dawley rats were co-cultured. Using norepinephrine (NE), NGF, and β2 -AR, NGF/TrkA blocker pretreatments, the axon growth of each group of DRG neuron cells was detected by immunofluorescence analysis. Results: The sympathetic adrenergic neurotransmitter NE activated the ERK signaling pathway in TNBC cells. NE/β2 -AR signaling promotes NGF secretion. NGF further facilitates the malignant progression of TNBC by increasing sympathetic neurogenesis. In the coculture assay, the sympathetic adrenergic NE/β2 -AR signal pathway also enhanced NGF secretion. NGF binds TrkA in DRG neurons and promotes axonal growth. Conclusion These results suggest that NE/β2 -AR pathway promotes cell proliferation and NGF production in triple-negative breast cancer.

Objective:To explore the immune and angiogenesis-related genes in aortic valve stenosis(AS)and potential therapeutic targets, based on bioinformatics and machine learning analysis.Methods:AS data sets from the Gene Expression Omnibus(GEO), immune-related genes from the ImmPort database, and angiogenesis-related genes from the Genecards database and MsigDB were downloaded and combined to determine differentially expressed immune and angiogenesis-related genes(DEGs).Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)functional enrichment analyses were performed.Protein-protein interaction(PPI)was analyzed by using STRING database.The key biomarkers were identified by two machine learning methods including Least Absolute Shrinkage Selection Operator(LASSO)and Support Vector Machine Recursive Feature Elimination(SVM-RFE), validated in training data set and verification data set by receiver operating characteristic curve(ROC), and analyzed by Gene Set Enrichment Analysis(GSEA).The subtypes of immune infiltrating cells were analyzed by CIBERSORT.Based on starBase, miRDB, miRWalk and hTFtarget databases, the mRNA-miRNA-TF was constructed.Finally, Potential therapeutic targets and drugs were analyzed through the CTD database.Results:A total of 90 DEGs related to AS, immune, and angiogenesis were obtained.Enrichment analysis found that DEIRGs were mainly related to immune regulation and cell cycle regulation, such as "leukocyte migration" , "cell chemotaxis" and "cytokine-cytokine receptor interaction" .84 related proteins and 548 interactions were obtained by PPI analysis.Two key biomarkers SecretograninⅡ(SCG2)and Tenascin-C(TNC)were identified by machine learning, which showed high diagnostic value for AS by ROC.SCG2 and TNC are mainly involved in the immune regulation by Enrichment analysis.The infiltration level of macrophage M0 in AS group was significantly higher than that in control group by CIBERSORT analysis.The correlation between macrophage M0 and macrophage M2 and SCG2 was the highest.879 mRNA-miRNA-TF, 253 potential therapeutic agents and 299 relationships were obtained.Conclusions:The key biomarkers, immune characteristics and potential therapeutic targets obtained from the research play a vital role in exploring the pathophysiological progress and new therapeutic strategies of AS.

Hepatic ischemia/reperfusion injury (HIRI) is a serious complication that occurs following shock and/or liver surgery. Gut microbiota and their metabolites are key upstream modulators of development of liver injury. Herein, we investigated the potential contribution of gut microbes to HIRI. Ischemia/reperfusion surgery was performed to establish a murine model of HIRI. 16S rRNA gene sequencing and metabolomics were used for microbial analysis. Transcriptomics and proteomics analysis were employed to study the host cell responses. Our results establish HIRI was significantly increased when surgery occurred in the evening (ZT12, 20:00) when compared with the morning (ZT0, 08:00); however, antibiotic pretreatment reduced this diurnal variation. The abundance of a microbial metabolite 3,4-dihydroxyphenylpropionic acid was significantly higher in ZT0 when compared with ZT12 in the gut and this compound significantly protected mice against HIRI. Furthermore, 3,4-dihydroxyphenylpropionic acid suppressed the macrophage pro-inflammatory response in vivo and in vitro. This metabolite inhibits histone deacetylase activity by reducing its phosphorylation. Histone deacetylase inhibition suppressed macrophage pro-inflammatory activation and diminished the diurnal variation of HIRI. Our findings revealed a novel protective microbial metabolite against HIRI in mice. The potential underlying mechanism was at least in part, via 3,4-dihydroxyphenylpropionic acid-dependent immune regulation and histone deacetylase (HDAC) inhibition in macrophages.