ObjectiveTo investigate the associations of multiple glycolipid metabolic indicators and their cumulative abnormality burden with incident colorectal cancer risk in a general population-based prospective cohort, and to examine the mediating role of glycolipid metabolic abnormalities in the relationships between smoking, alcohol consumption, physical activity, and colorectal cancer incidence. MethodsA total of 17 897 eligible participants recruited from the Taizhou Cohort between 2011 and 2014 were included. Cox proportional hazards regression models were used to assess the associations of conventional and derived glycolipid indicators, as well as a glycolipid abnormality index constructed from total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, fasting plasma glucose, and insulin, with incident colorectal cancer risk. Restricted cubic spline models were applied to evaluate dose-response relationships for major indicators. Receiver operating characteristic curves were generated to compare predictive performance across indicators. Mediation analyses were conducted to assess the mediating effects of the glycolipid abnormality index on the associations of smoking, alcohol consumption, and physical activity with colorectal cancer incidence. ResultsDuring a median follow-up of 11.2 years, 102 incident colorectal cancer cases were identified, with an incidence density of 51.2 per 100 000 person-years. After adjustment for potential confounders, Cox proportional hazards regression analyses showed that decreased high-density lipoprotein cholesterol was associated with a 1.74-fold higher risk of colorectal cancer (HR=1.74, 95%CI: 1.03‒2.95), elevated low-density lipoprotein cholesterol was associated with a 1.78-fold higher risk (HR=1.78, 95%CI: 1.05‒3.02), and abnormal fasting plasma glucose was associated with a 1.86-fold higher risk (HR=1.86, 95%CI: 1.15‒3.02). Triglycerides and fasting plasma glucose showed an approximately linear increasing association with colorectal cancer risk in multivariable restricted cubic spline models. The glycolipid abnormality index showed a clear gradient association with colorectal cancer risk; participants with three or more abnormal indicators had a 3.08-fold higher risk than those without abnormalities (HR=3.08, 95%CI: 1.60‒5.92). The area under the curve was 0.795, higher than that of individual glycolipid indicators and other combined indices, and gender-stratified analyses showed generally consistent patterns. Glycolipid metabolic abnormalities partially mediated the associations of smoking, alcohol consumption, and physical activity with colorectal cancer incidence, with mediation proportions of 8.33%, 9.45%, and 9.04%, respectively. ConclusionGlycolipid metabolic abnormalities are associated with an increased risk of incident colorectal cancer. The glycolipid abnormality index shows an increasing relationship with colorectal cancer risk and demonstrates better discrimination, and it partially mediates the associations of smoking, alcohol consumption, and physical activity with colorectal cancer incidence in the overall population.

Objective To analyze the distribution characteristics and application value of liver,renal func-tion indexes and autoantibody-related indexes of neuromyelitis optica spectrum disorder(NMOSD).Methods The liver,renal function and autoantibody-related indexes data of patients diagnosed with NMOSD and multiple sclerosis(MS)in Beijing Tiantan Hospita,Capital Medical University from June 2015 to June 2023,as well as gender and age-matched controls underwent routine physical examination were retrospectively collected.A total of 95 patients with NMOSD(NMOSD group),230 patients with MS(MS group),and 244 healthy controls(routine physical examination group)were selected to evaluate the diagnostic value of each index for NMOSD.Results Compared with MS group,the levels of alanine aminotransferase,as well as the positive rates of α-hydroxybutyrate dehydrogenase,y-glutamyltransferase,anti-SS-A antibody,anti-SS-B anti-body,anti-ribosomal P protein antibody and Ro-52 antibody were significantly increased in NMOSD group,while the levels of albumin,indirect bilirubin and total bilirubin were significantly decreased,and the differ-ences were statistically significant(P＜0.05).The difference index between NMOSD and conventional physi-cal examination group was similar to that of MS group.The seven indexes,a-hydroxybutyrate dehydrogenase,albumin,globulin,direct bilirubin,indirect bilirubin,total bile acid and uric acid alkalinity could be used for the diagnosis of NMOSD.The area under the curve of combined diagnosis of NMOSD was 0.969,and the sensitiv-ity and specificity were 92.6％and 92.9％.Conclusion Multiple indexes of liver and kidney function in NMOSD patients are different from those in MS patients and healthy subjects underwent routine physical ex-amination,and the positive rate of some autoantibody indexes in NMOSD patients is higher than that in MS patients.Liver,renal function and autoantibody-related indexes can be used clinically to assist diagnosis,and the combined application of multiple indexes can further enhance its diagnostic value.

ObjectiveTo classify subtypes among middle-aged and elderly type 2 diabetes mellitus (T2DM) patients aged between 35‒74 years in Shanghai suburbs, to compare their characteristics and analyze incidence risk for cerebrovascular disease among these subtypes, so as to promote personalized and precise treatment of T2DM. MethodsA total of 7 792 patients with T2DM who completed a baseline survey from 2016 and 2019 were selected as the research subjects, based on the data from a natural population cohort and biobank in Shanghai suburbs. Patients were stratified by gender and clustered into subtypes using k-means method based on baseline parameters including the age at T2DM diagnosis, body mass index (BMI), fasting blood glucose, and triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C). Patients were followed up until March 31, 2023. Multivariate Cox regression models were used to analyze the association between subtypes and incidence risk for cerebrovascular disease, and those with cerebrovascular disease within 1 year of follow-up survey were excluded from sensitivity analysis. ResultsAmong the 7 792 patients with T2DM, 3 615 were males and 4 177 were females. Stratified by gender, 4 subgroups were identified through k-means clustering analysis, namely poor blood glucose control subgroup, severe insulin-resistant subgroup, younger onset subgroup, and older onset subgroup. The median follow-up time was 4.30 years, during which 1 960 cerebrovascular disease events were observed (844 in males, 1 116 in females). After adjusting for smoking, alcohol consumption, weekly exercise, family history of diabetes mellitus, and duration of diabetes mellitus, among male patients, the incidence risk for cerebrovascular disease was lower in the younger onset subgroup (HR=0.59, 95%CI: 0.48‒0.73, P<0.001), poor blood glucose control subgroup (HR=0.81, 95%CI: 0.65‒1.00, P=0.046), and severe insulin-resistant subgroup (HR=0.61, 95%CI: 0.50‒0.75, P<0.001), compared to the older onset subgroup. While among female patients, the incidence risk for cerebrovascular disease was also lower in the younger onset subgroup (HR=0.68, 95%CI: 0.57‒0.80, P<0.001), poor blood glucose control subgroup (HR=0.73, 95%CI: 0.60‒0.89, P=0.002), and severe insulin-resistant subgroup (HR=0.72, 95%CI: 0.61‒0.85, P<0.001), compared to the older onset subgroup. Results of the sensitivity analysis were consistent with the main findings. ConclusionAmong middle-aged and elderly T2DM patients in suburban Shanghai, both male and female patients have the highest incidence risk for cerebrovascular disease in the older onset subgroup. Subtyping of T2DM patients can help to identify the high-risk populations of cerebrovascular disease.

Propensity score can improve the efficiency and accuracy of clinical trials， and has been widely used in many fields such as comparison of efficacy evaluation， exploration of disease occurrence factors， and monitoring of adverse drug reactions. At present， the propensity scoe has application prospects in traditional Chinese medicine （TCM） monotherapy intervention， complex intervention and integrated Chinese and Western medicine intervention research， and it is a good auxiliary tool for real-world study. By analysing the cha-racteristics of clinical research in TCM， the authors believed that， firstly， the application of propensity score can acce-lerate the progress of clinical efficacy evaluation research in TCM， contribute to the collection of high-level clinical evidence， and promote the development and promotion of TCM therapies； Secondly， under the background of big data resources， propensity score has good application prospects in assisting TCM prescription analysis， drug safety and adverse reaction monitoring， and large-scale cohort studies in TCM； thirdly， in the process of clinical practice， propensity scoring method may face problems such as inappropriate method selection， incorrect judgement or measurement of confounding factors， and unreasonable interpretation or extrapolation of results.

Objective:To establish and verify a diagnostic model for distinguishing multiple sclerosis (MS) from other neurological diseases with similar symptoms by usingcerebrospinal fluid oligoclonal band (CSF-OCB)combined with IgG intrathecal synthesis indicators and biochemical markers.Methods:Multiple sclerosis (MS) patients admitted to the Neurology Department of Beijing Tiantan Hospital affiliated with Capital Medical University from January 2014 to December 2022 were selected as the case group, while patients with similar neurological symptoms were selected as the control group. Using the case-control study design, a retrospective analysis was conducted on the detection of age, gender, oligoclonal bands in cerebrospinal fluid, IgG intrathecal synthesis indicators and biochemical indicators for all study subjects. The differential diagnosis model was determined by the multiple logistic regression analysis, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficiency of the differential diagnosis model for neurological diseases with similar symptoms to MS and other conditions.Results:This study included 167 patients in the case group and 335 patients in the control group, of which 128 patients in the case group and 265 patients in the control group were used to construct the model, and 39 patients in the case group and 70 patients in the control group were used for model validation. The differential diagnostic model constructed by a multivariate logistic regression model was Y=0.871×CSF-OCB-0.051×CSFprotein-0.231×CSFchloride+1.183×gender-0.036×LDH+35.770. The model showed that the area under the curve, sensitivity and specificity were respectively 0.916, 87.3% and 87.6%. The Delong test results showed that the diagnostic efficacy of the model was significantly different from OCB, IgG intrathecal synthesis indicators, and OCB combined with IgG intrathecal synthesis indicators ( P<0.05). The new model validation showed that the actual diagnostic consistency rate for the MS group was 84.6%, while the actual diagnostic consistency rate for the control group was 90.0%. Conclusion:This study combines OCB, IgG intrathecal synthesis indicators, and biochemical indicators to establish a diagnostic prediction model for neurological diseases with similar clinical symptoms in MS. This model may have good differential diagnostic value and can better assist clinical diagnosis in the early stages of disease progression in MS patients.

Objective:To establish and verify a diagnostic model for distinguishing multiple sclerosis (MS) from other neurological diseases with similar symptoms by usingcerebrospinal fluid oligoclonal band (CSF-OCB)combined with IgG intrathecal synthesis indicators and biochemical markers.Methods:Multiple sclerosis (MS) patients admitted to the Neurology Department of Beijing Tiantan Hospital affiliated with Capital Medical University from January 2014 to December 2022 were selected as the case group, while patients with similar neurological symptoms were selected as the control group. Using the case-control study design, a retrospective analysis was conducted on the detection of age, gender, oligoclonal bands in cerebrospinal fluid, IgG intrathecal synthesis indicators and biochemical indicators for all study subjects. The differential diagnosis model was determined by the multiple logistic regression analysis, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficiency of the differential diagnosis model for neurological diseases with similar symptoms to MS and other conditions.Results:This study included 167 patients in the case group and 335 patients in the control group, of which 128 patients in the case group and 265 patients in the control group were used to construct the model, and 39 patients in the case group and 70 patients in the control group were used for model validation. The differential diagnostic model constructed by a multivariate logistic regression model was Y=0.871×CSF-OCB-0.051×CSFprotein-0.231×CSFchloride+1.183×gender-0.036×LDH+35.770. The model showed that the area under the curve, sensitivity and specificity were respectively 0.916, 87.3% and 87.6%. The Delong test results showed that the diagnostic efficacy of the model was significantly different from OCB, IgG intrathecal synthesis indicators, and OCB combined with IgG intrathecal synthesis indicators ( P<0.05). The new model validation showed that the actual diagnostic consistency rate for the MS group was 84.6%, while the actual diagnostic consistency rate for the control group was 90.0%. Conclusion:This study combines OCB, IgG intrathecal synthesis indicators, and biochemical indicators to establish a diagnostic prediction model for neurological diseases with similar clinical symptoms in MS. This model may have good differential diagnostic value and can better assist clinical diagnosis in the early stages of disease progression in MS patients.

Objective To study the value of CYP2C19 gene polymorphism combined with biochemical indi-cators in predicting clopidogrel resistance(CR)in patients with cerebral infarction.Methods A total of 387 patients with cerebral infarction admitted to Beijing Tiantan Hospital,Capital Medical University from Januar-y 2021 to December 2023 were selected as the research subjects.According to the test results of platelet aggre-gation test-adenosine diphosphate(PAgT-ADP)after admission,the patients with cerebral infarction were di-vided into clopidogrel effective group(PAgT-ADP≤43％)and CR group(PAgT-ADP＞43％).The distribu-tion of CYP2C19 genotype in patients with cerebral infarction were observed.The age,gender and biochemical indicators,including urea,creatinine(Cr),uric acid(UA),alanine aminotransferase(ALT),aspartate amin-otransferase(AST),total bilirubin(TBIL),direct bilirubin(DBIL),indirect bilirubin(IBIL),lactate dehydro-genase(LDH),triglycerides(TG),total cholesterol(CHO),high-density lipoprotein cholesterol(HDL),low-density lipoprotein cholesterol(LDL),homocysteine(Hcy),of the two groups were retrospectively analyzed.Single factor analysis was conducted on statistical indicators,and a combined prediction model was constructed through multivariate Logistic regression analysis.Receiver operating characteristic(ROC)curve was plotted to analyze the efficacy of CYP2C19 gene metabolic types alone and in combination with biochemical indicators for predicting CR in patients with cerebral infarction.Results The gender,Cr,TBIL,DBIL,IBIL,Hcy and CYP2C19 gene metabolic types showed statistically significant differences between the CR group and the clo-pidogrel effective group(P＜0.05).Multivariate Logistic regression analysis showed that Cr,ALT,AST,TBIL,DBIL,IBIL,CHO,LDL and CYP2C19 gene metabolic types were independent predictors of CR(P＜0.05).ROC curve analysis results showed that the area under the curve of the combined prediction model for predicting CR in patients with cerebral infarction was 0.720,and the sensitivity and the specificity were 71.1％and 65.5％,respectively.The area under the curve of the CYP2C19 gene metabolic types for predicting CR in patients with cerebral infarction alone was 0.641,and the sensitivity and the specificity were 67.3％and 56.9％,respectively.There was a statistically significant difference in the area under the curve between the combined prediction model and the CYP2C19 gene metabolic type alone(P＜0.05).Conclusion The combi-nation of CYP2C19 gene polymorphism and biochemical indicators is helpful in predicting the occurrence of CR in patients with cerebral infarction,and has good predictive value especially for patients with CR and CYP2C19 gene metabolism showing normal metabolism.

Digestive system malignant tumor is one of the common malignant tumors in humans,and its high morbidity and low survival rate at advanced stages bring heavy disease burden to patients,families and society.However,current tumor screening technologies are not suitable for screening in large-scale populations and long-term follow-up because of the invasiveness or complexity.Thus,liquid biopsy,which based on biomarkers such as circulating tumor DNA,circulating tumor cells,exosomes and other new biomarkers,has broad prospects for development in tumor screening.Exosome,secreted by living cells,is a type of extracellular vesicle with the lipid bilayer.Compared to other biomarkers,exosome has the advantages of high stability,wide distribution,and high quantity.The various proteins carried by exosome can reflect the characteristics of the origin cells,and exosome has important research value for the early diagnosis of tumors.This article reviews the studies of exosomal proteins as biomarkers for early diagnosis of digestive system malignant tumors in the past five years,and summarizes the characteristics and limitations of the above studies,so as to provide reference for promoting the clinical transformation of exosomal proteins.

Objective: To propose reasonable suggestions to promote the standardization of clinical studies by reviewing the systematic reviews and meta-analyses of acupuncture-moxibustion treatment of essential hypertension (EH). Methods: Computer retrieval was conducted through Excerpta Medica Database (EMBASE), PubMed, China National Knowledge Infrastructure (CNKI), Chongqing VIP Database (CQVIP), China Biology Medicine Disc (CBM), and Wanfang Academic Journal Full-text Database (Wanfang) to collect systematic reviews and meta-analyses relevant to treating EH with acupuncture-moxibustion therapy. The time range was from the database's inception till July, 2020. The studies were screened based on the inclusion and exclusion criteria and then data-extracted. The study's quality and evidence ratings were performed by referring to the preferred reporting items for systematic review and meta-analysis (PRISMA), a measurement tool to assess systematic reviews 2 (AMSTAR 2), and the grading of recommendations, assessment, development, and evaluation (GRADE). Results: A total of 14 studies, 10 in Chinese and 4 in English, published between 2012 and 2019, were included, involving 70 outcome measures. The methodological quality was rated as critically low, the reporting was relatively complete or had certain flaws, and the evidence strength was rated as low or very low. Conclusion: Regarding the acupuncture-moxibustion treatment of EH, the methodological quality and outcome measure evidence of existing systematic reviews and meta-analyses are relatively low, and the reporting quality also expects further improvements.

Objective: To understand influencing factors on workers' personal protective equipment (PPE) usage, and provide a basis for standardizing the PPE use in the city. Methods: The basic information of workers exposed to occupational hazards in a municipal area was imported into SPSS 18.0 and numbered sequentially in May 2018. A simple random sampling method was used to select 1 678 workers as the research object, and then a questionnaire survey was conducted from June to July 2018. In the valid questionnaires collected, workers who self-rated as "full-time correct use of PPE" and were approved by occupational health managers of employing units were included in the "correct use group" and others in the "incorrect use group". χ² test was used to analyze the PPE use of different factors, and binary unconditional logistic regression analysis was used to analyze the influencing factors. Results: 1547 valid questionnaires were collected in this study, including 803 workers correctly used PPE at full time (51.9%) , and other workers never used or occasionally used PPE. There were statistical difference of PPE usage rate among workers of different sex, industry and wage type (P<0.05) . Occupational health supervisors setting example in PPE usage (β=0.368) , workmates using PPE correctly and reminding PPE usage (β=0.891) , posting warning specifications of occupational hazards (β=0.361) , setting up "safe man" at the entrance of workshop (β=0.585) , WeChat and other new media on occupational health knowledge propaganda (β=0.536) , punishing incorrect usage of PPE (β=0.252) 、sex (β=-0.512) and wage type (β=-0.203) are influencing factors affecting the usage of PPE. Conclusion PPE usage rate of the occupational population in the city is still fairly low, and the PPE usage is influenced by a variety of factors. Comprehensive measures should be taken by employers to ensure using PPE to protect workers' occupational health.