ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To analyze the predictive role of WT1 expression levels pre-and early post-transplantation on relapse and overall survival(OS)in patients with acute myeloid leukemia(AML)undergoing allogeneic hematopoietic stem cell transplantation(allo-HSCT)during their first complete remission(CR1).Methods:A retrospective analysis was conducted on the clinical data of 107 adult AML patients who underwent allo-HSCT during their CR1 at our center between May 2012 and December 2021.The predictive role of bone marrow WT1 expression levels before transplantation and at 3 and 6 months post-transplantation on relapse and OS was explored in combination with relevant clinical factors.Results:The median follow-up time for the 107 patients was 70(range:11-117)months.Among the patients,15 cases died.Kaplan-Meier survial analysis showed that the 3-year overall survival(OS)rate was 85.0％.20 patients experienced relapse,with a median time to relapse of 8(range:0.5-44)months and a l-year cumulative relapse rate of 13.1％.The overall median value of WT1 before transplantation,3 months after transplantation,and 6 months after transplantation was 0.26％(range:0％-23.64％),with an upper quartile value of 0.74％.No statistically significant differences in WT1 expression levels were observed among the pre-transplantation,3-month post-transplantation,and 6-month post-transplantation time points(P=0.227).Univariate analysis showed that patients with WT1 levels＞0.74％at 3 months post-transplantation had a higher 1-year relapse rate(P=0.029)and lower 3-year OS rate(P＜0.001)compared to patients with WT1 levels ≤0.74％.Other significant factors affecting 1-year relapse included stem cell source(P=0.041)and chronic graft-versus-host disease(cGVHD)(P=0.013).For 3-year OS,additional influencing factors were genetic high risk(P=0.048)and stem cell source(P=0.016).Multivariate analysis revealed that WT1 level＞0.74％at 3 months post-transplantation had a trend to affect 1-year relapse rate(HR=3.309,95％CI:0.958-11.431,P=0.058),while the absence of cGVHD was an independent risk factor for 1-year relapse(HR=3.473,95％CI:0.749-16.100,P=0.037).Only WT1 level＞0.74％at 3 months post-transplantation was an independent risk factor for 3-year OS(HR=6.886,95％CI:2.402-19.738,P＜0.001).Conclusion:High WT1 expression level at 3 months post-transplantation in AML patients undergoing allo-HSCT during CR1 affects the 1-year relapse rate and 3-year OS,and is an independent risk factor affecting 3-year OS.These findings suggest that dynamic monitoring of WT1 expression levels has certain value in prognostic assessment of AML patients who received allo-HSCT during CR1.

Objective To design a high altitude adaptive oxygen generator for the crews to alleviate their high altitude reaction in high altitude environment and meet their requirements for oxygen supply.Methods A high altitude adaptive oxygen generator based on the mature pressure swing adsorption oxygen production method was designed with the key technologies of discharge capacity compensation of air compression pump and airway fusion of molecular sieve tower,which had the components of molecular sieve tower,air compression pump,controller,cooling fan,cooler,solenoid valve,regulator,flow meter and etc.Trials were carried out at the simulated altitude and field plateau environment so as to verify the high altitude adaptive performance of the oxygen generator developed.Results The trial results showed the oxygen generator met the desired objectives and the requirements for oxygen volume fraction in GJB 2799-1996 General specification for medical oxygen generator using molecular sieve method.Conclusion The oxygen generartor provides oxygen supply effectively for vehicle operators in plateau environments or the ones rushing into the plateau.[Chinese Medical Equipment Journal,2025,46(4):29-34]

Objective To explore the relationship between community health follow-up management and the mental health of the long-term care insurance residents,and to provide a basis for the construction of an integrated community home care service mode for disabled elders.Methods The residents were selected through cluster sampling who participated in LTCI home care from Jan 1 to Dec 31,2021.After a year of participation,the subjects'mental health was assessed face-to-face by trained community doctors using the Self-Rating Anxiety Scale and the Self-Rating Depression Scale.By referring to residents'electronic health records combined with on-site questionnaire survey,community doctors collected the demographic information and health follow-up management provided by primary medical and health institutions.The multivariate logistic regression were conducted to evaluate the association between follow-up care and mental health outcomes.Results The study consisted of 399 LTCI-enrolled individuals,57.64%(n=230)received follow-up care by family physicians.The prevalence of anxiety and depression among participants was 19.80%(n=79)and 67.67%(n=270),respectively.Univariate analysis found that community health follow-up management could underscore the potential impact of follow-up care in mitigating anxiety(χ2=38.926,P<0.001)and depression(χ2=14.598,P<0.001)among LTCI enrollees.Multivariate analysis revealed that follow-up care was an independent protective factor against anxiety(adjusted OR=0.351,95%CI:0.176-0.701,P=0.003).However,follow-up care did not significantly impact depression prevalence.Additionally,LTCI grade and education level were also identified factors influencing the mental health of participants(P<0.05).Conclusion Community health service centers provide health follow-up management that plays a positive role in alleviating the anxiety symptoms of disabled residents under long-term care insurance home care.It is an effective way to improve the quality of LTCI home care services.

Objectives:This study aims to explore the causal relationships between immune cells and serum metabolites in the development of coronary heart disease(CHD)using Mendelian randomization(MR)methods.Methods:We conducted a two-sample MR analysis utilizing data from the FinnGen Project's genome-wide association study(GWAS)on CHD,alongside data on metabolites and immune cells from the GWAS catalog.For the identified associated metabolites,we further employed mediation MR methods to evaluate their mediating roles in the influence of immune cells on CHD.Results:The MR analysis indicated that three immune cells(IgD-CD24-%B cell,CD11b on CD14+monocyte,HLA DR on DC)had stable causal relationship with CHD(under the premise of inverse variance weighted[IVW]method P<0.05,both MR-Egger and weighted median methods also showed P<0.05).Furthermore,these immune cells were associated with CHD through four metabolites(N-acetylneuraminic acid levels,the ratio of desmethyltaurine to taurine,X-24801 and X-18779).Conclusions:This study reveals the causal relationships between immune cells and serum metabolites in the pathogenesis of CHD,providing new biomarkers for early prediction and risk assessment of CHD.

Objective To explore the relationship between community health follow-up management and the mental health of the long-term care insurance residents,and to provide a basis for the construction of an integrated community home care service mode for disabled elders.Methods The residents were selected through cluster sampling who participated in LTCI home care from Jan 1 to Dec 31,2021.After a year of participation,the subjects'mental health was assessed face-to-face by trained community doctors using the Self-Rating Anxiety Scale and the Self-Rating Depression Scale.By referring to residents'electronic health records combined with on-site questionnaire survey,community doctors collected the demographic information and health follow-up management provided by primary medical and health institutions.The multivariate logistic regression were conducted to evaluate the association between follow-up care and mental health outcomes.Results The study consisted of 399 LTCI-enrolled individuals,57.64%(n=230)received follow-up care by family physicians.The prevalence of anxiety and depression among participants was 19.80%(n=79)and 67.67%(n=270),respectively.Univariate analysis found that community health follow-up management could underscore the potential impact of follow-up care in mitigating anxiety(χ2=38.926,P<0.001)and depression(χ2=14.598,P<0.001)among LTCI enrollees.Multivariate analysis revealed that follow-up care was an independent protective factor against anxiety(adjusted OR=0.351,95%CI:0.176-0.701,P=0.003).However,follow-up care did not significantly impact depression prevalence.Additionally,LTCI grade and education level were also identified factors influencing the mental health of participants(P<0.05).Conclusion Community health service centers provide health follow-up management that plays a positive role in alleviating the anxiety symptoms of disabled residents under long-term care insurance home care.It is an effective way to improve the quality of LTCI home care services.

Objectives:This study aims to explore the causal relationships between immune cells and serum metabolites in the development of coronary heart disease(CHD)using Mendelian randomization(MR)methods.Methods:We conducted a two-sample MR analysis utilizing data from the FinnGen Project's genome-wide association study(GWAS)on CHD,alongside data on metabolites and immune cells from the GWAS catalog.For the identified associated metabolites,we further employed mediation MR methods to evaluate their mediating roles in the influence of immune cells on CHD.Results:The MR analysis indicated that three immune cells(IgD-CD24-%B cell,CD11b on CD14+monocyte,HLA DR on DC)had stable causal relationship with CHD(under the premise of inverse variance weighted[IVW]method P<0.05,both MR-Egger and weighted median methods also showed P<0.05).Furthermore,these immune cells were associated with CHD through four metabolites(N-acetylneuraminic acid levels,the ratio of desmethyltaurine to taurine,X-24801 and X-18779).Conclusions:This study reveals the causal relationships between immune cells and serum metabolites in the pathogenesis of CHD,providing new biomarkers for early prediction and risk assessment of CHD.

Objective To explore the predictive value of intratumor and peritumoral edema radiomics combined with the autoencoder algorithm for human epidermal growth factor receptor(HER-2)status in breast cancer to provide a new idea for preoperative noninvasive prediction of HER-2 status.Methods Totally 145 breast cancer patients from Yancheng Hospital Affiliated to Nanjing University Medical College(Center 1)and 52 ones from Jianhu Hospital Affiliated to Nantong University(Center 2)had their clinical and imaging data collected retrospectively,who were divided into a HER-2 positive group including 87 ones from Center 1 and 30 ones from Center 2 and a HER-2 negative group including 58 ones from Center 1 and 22 ones from Center 2.From December 2018 to October 2024 there were 78 patients with peritumoral edema from Center 1 randomly enrolled into a training set(55 patients)and a validation set(23 patients)in a ratio of 7∶3,and from November 2024 to March 2025 another 26 ones placed into a time validation set.The 52 patients with peritumoral edema from Center 2 were included into an external test set.Firstly,the Mazda software was used to delineate the regions of interest for the largest tumor layer and the peritumoral edema area.Secondly,multivariate analysis of variance(ANOVA),Kruskal-Wallis test,recursive feature elimination(RFE)and Relief algorithm were respectively employed to screen the radiomics features;finally,combined with ten-fold cross validation,the receiver operating characteristic curve was drawn,and the diagnostic efficacy of the models respectively constructed with radiomics parameters and ten types of machine learning algorithms,including auto encoder,support vector machine,linear discriminant analysis,random forest,Logistic regression,Logistic regression via Lasso,adaptive boosting,Gaussian process,native Bayes and decision tree,was evaluated for the HER-2 status in breast cancer.Results The model established by the auto encoder algorithm combined with three feature parameters including intratumor MaxNorm and Variance and peritumoral edema SumAverg behaved the best.The average AUC values of the training and validation sets were 0.808 and 0.735 resepctively,and the AUC values of the time validation and external test sets were 0.746 and 0.732 respectively.Conclusion The model developed with intratumor and peritumoral edema radiomics combined with the auto encoder algorithm can be used for preoperative noninvasive prediction of HER-2 status of breast cancer,which provides references for the preparation of individualized treatment scheme of breast cancer patients.[Chinese Medical Equipment Journal,2025,46(9):9-15]

Objective To explore the predictive value of intratumor and peritumoral edema radiomics combined with the autoencoder algorithm for human epidermal growth factor receptor(HER-2)status in breast cancer to provide a new idea for preoperative noninvasive prediction of HER-2 status.Methods Totally 145 breast cancer patients from Yancheng Hospital Affiliated to Nanjing University Medical College(Center 1)and 52 ones from Jianhu Hospital Affiliated to Nantong University(Center 2)had their clinical and imaging data collected retrospectively,who were divided into a HER-2 positive group including 87 ones from Center 1 and 30 ones from Center 2 and a HER-2 negative group including 58 ones from Center 1 and 22 ones from Center 2.From December 2018 to October 2024 there were 78 patients with peritumoral edema from Center 1 randomly enrolled into a training set(55 patients)and a validation set(23 patients)in a ratio of 7∶3,and from November 2024 to March 2025 another 26 ones placed into a time validation set.The 52 patients with peritumoral edema from Center 2 were included into an external test set.Firstly,the Mazda software was used to delineate the regions of interest for the largest tumor layer and the peritumoral edema area.Secondly,multivariate analysis of variance(ANOVA),Kruskal-Wallis test,recursive feature elimination(RFE)and Relief algorithm were respectively employed to screen the radiomics features;finally,combined with ten-fold cross validation,the receiver operating characteristic curve was drawn,and the diagnostic efficacy of the models respectively constructed with radiomics parameters and ten types of machine learning algorithms,including auto encoder,support vector machine,linear discriminant analysis,random forest,Logistic regression,Logistic regression via Lasso,adaptive boosting,Gaussian process,native Bayes and decision tree,was evaluated for the HER-2 status in breast cancer.Results The model established by the auto encoder algorithm combined with three feature parameters including intratumor MaxNorm and Variance and peritumoral edema SumAverg behaved the best.The average AUC values of the training and validation sets were 0.808 and 0.735 resepctively,and the AUC values of the time validation and external test sets were 0.746 and 0.732 respectively.Conclusion The model developed with intratumor and peritumoral edema radiomics combined with the auto encoder algorithm can be used for preoperative noninvasive prediction of HER-2 status of breast cancer,which provides references for the preparation of individualized treatment scheme of breast cancer patients.[Chinese Medical Equipment Journal,2025,46(9):9-15]