1.Quality Analysis and Suggestion of Zukamu Preparation Based on National Drug Sampling and Testing
Shengyun DAI ; Dongxue WU ; Rui WU ; Meng XIAO ; Jie LIU ; Chaojie LIAN ; Xiaoru HU ; Feng WEI ; Jian ZHENG ; Jialiang ZHU
Herald of Medicine 2025;44(10):1600-1605
Objective To examine the quality of Zukamu preparations through the national drug sampling and testing,and further understand their current quality status and existing problems.This work is benefit for improving the quality standard of Zukamu preparations and providing technical support for the drug regulatory authorities.Methods Samples of Zukamu preparations were collected from a total of 29 provinces in China,and were tested for description,identification,other requirements(weight variation,particle size,determination of water,disprsion,and microbial limit items),and assay in accordance with the national pharmaceutical standards.The test data were analyzed to evaluate the quality status of the Zukamu preparations,and exploratory research was carried out to address the problems found in the test.Results A total of 97 batches of Zukamu preparations were sampled,and the passing rate was 100.0%according to the current quality standard.Exploratory study,revealed that Zukamu preparation were subject to 4 testing standards,with uneven test items,missing items,poor operability,and lack of exclusivity in some items.The test based on the existing standards can't comprehensively evaluate the quality of the preparation.Conclusions Based on the national drug sampling and testing,combined with exploratory research on drug safety,authenticity and effectiveness,it is recommended to unify the quality standards of Zukamu preparations by combining with the work of standard improving,revising the identification method of thin-layer chromatography,increasing the content determination,and establishing the quick test method,thereby effectively evaluating and controling the quality of the samples of Zukamu preparations.
2.Identifying High-Risk Areas for Type 2 Diabetes Mellitus Mortality in Guangdong, China: Spatiotemporal Clustering and Socioenvironmental Determinants.
Hai Ming LUO ; Wen Biao HU ; Yan Jun XU ; Xue Yan ZHENG ; Qun HE ; Lu LYU ; Rui Lin MENG ; Xiao Jun XU ; Fei ZOU
Biomedical and Environmental Sciences 2025;38(5):585-597
OBJECTIVE:
This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies.
METHODS:
Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model.
RESULTS:
A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide.
CONCLUSION
High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology*
;
China/epidemiology*
;
Humans
;
Risk Factors
;
Spatio-Temporal Analysis
;
Air Pollutants/analysis*
;
Socioeconomic Factors
;
Bayes Theorem
;
Female
;
Male
;
Middle Aged
3.NFKBIE: Novel Biomarkers for Diagnosis, Prognosis, and Immunity in Colorectal Cancer: Insights from Pan-cancer Analysis.
Chen Yang HOU ; Peng WANG ; Feng Xu YAN ; Yan Yan BO ; Zhen Peng ZHU ; Xi Ran WANG ; Shan LIU ; Dan Dan XU ; Jia Jia XIAO ; Jun XUE ; Fei GUO ; Qing Xue MENG ; Ren Sen RAN ; Wei Zheng LIANG
Biomedical and Environmental Sciences 2025;38(10):1320-1325
4.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
5.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
6.Construction and Optimization of Alzheimer's Disease Classification Model Based on Brain Mixed Function Network Topology Parameters and Machine Learning
Xiao-yu HAN ; Xiu-zhu JIA ; Yang LI ; Meng-ying LOU ; Yong-qi NIE ; Xin-ping GUO ; Lu YU ; Zhi-yuan LI ; Lian-zheng SU
Progress in Modern Biomedicine 2025;25(11):1770-1778
Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P<0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7%,and the AUC values were up to 100%,99.5%,99.1%and 99.5%,respectively.The accuracy(98.5%),precision(98.5%),recall(98.5%),and AUC(99.1%)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0%,while Bagging has the lowest AUC value(99.1%)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13%),AUC(99.42%),recall rate(99.46%)and specificity(99.42%)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.
7.Research Progress on the Wuwei Qingzhuo Preparation of Mongolian Medicine and Shiliu Jianwei Preparation of Zang Medicine
Shengyun DAI ; Dongxue WU ; Rui HUANG ; Jie LIU ; Xiaoru HU ; Meng XIAO ; Chaojie LIAN ; Feng WEI ; Jian ZHENG ; Jialiang ZHU
Herald of Medicine 2025;44(1):61-67
Based on the results of the National Drug Sampling and Inspection Programme,we summarized the history,the standard collection,the production enterprises and the dosage form specifications,the quality standard study,the pharmacological and pharmacodynamic study,and the clinical application study of Wuwei Qingzhuo preparation of Mongolian medicine and Shiliu Jianwei preparation of Zang medicine,to provide the basis for improved quality standards for both preparations.The development of these two preparations was searched and analyzed through literature.The available information shows that there is very little research on the two preparations and insufficient pharmacological experimental and clinical experimental data.The two preparations are basically the same in prescription and efficacy.However,the quality standards are very different,which are not conducive to the quality control of the two and their related dosage forms.And it is suggested that the Chinese Pharmacopoeia should take the situation of this category into comprehensive consideration,and unify the quality standards of the two preparations.
8.Quality Analysis and Suggestion of Zukamu Preparation Based on National Drug Sampling and Testing
Shengyun DAI ; Dongxue WU ; Rui WU ; Meng XIAO ; Jie LIU ; Chaojie LIAN ; Xiaoru HU ; Feng WEI ; Jian ZHENG ; Jialiang ZHU
Herald of Medicine 2025;44(10):1600-1605
Objective To examine the quality of Zukamu preparations through the national drug sampling and testing,and further understand their current quality status and existing problems.This work is benefit for improving the quality standard of Zukamu preparations and providing technical support for the drug regulatory authorities.Methods Samples of Zukamu preparations were collected from a total of 29 provinces in China,and were tested for description,identification,other requirements(weight variation,particle size,determination of water,disprsion,and microbial limit items),and assay in accordance with the national pharmaceutical standards.The test data were analyzed to evaluate the quality status of the Zukamu preparations,and exploratory research was carried out to address the problems found in the test.Results A total of 97 batches of Zukamu preparations were sampled,and the passing rate was 100.0%according to the current quality standard.Exploratory study,revealed that Zukamu preparation were subject to 4 testing standards,with uneven test items,missing items,poor operability,and lack of exclusivity in some items.The test based on the existing standards can't comprehensively evaluate the quality of the preparation.Conclusions Based on the national drug sampling and testing,combined with exploratory research on drug safety,authenticity and effectiveness,it is recommended to unify the quality standards of Zukamu preparations by combining with the work of standard improving,revising the identification method of thin-layer chromatography,increasing the content determination,and establishing the quick test method,thereby effectively evaluating and controling the quality of the samples of Zukamu preparations.
9.Study on the association between heatwaves and road traffic injury mortality in five provinces of China
Siwen YU ; Min YU ; Aga ZHENG ; Chunliang ZHOU ; Ruilin MENG ; Biao HUANG ; Yize XIAO ; Wei WU ; Guanhao HE ; Jianxiong HU ; Wenjun MA ; Tao LIU
Chinese Journal of Epidemiology 2025;46(4):573-580
Objective:To evaluate the impact of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality and calculate the attributable mortality burden.Methods:This study collected road traffic mortality data from the Disease Surveillance System in Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces from 2013 to 2018. A time-stratified case-crossover design was used in this study, with the death date for each case serving as the case day. Control days were selected from the same year, month, and day of the week as the case day. A conditional logistic regression model was employed to estimate the cumulative associations of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality (lag 0-1 day) and to calculate the attributable fractions (AF).Results:Compared to non-heatwave days, the excess risk ( ER) of road traffic mortality on daytime heatwave days, nighttime heatwave days, and compound heatwave days was 5.3% (95% CI: 0.5%-10.2%), 4.9% (95% CI: 0.5%-9.4%) and 7.5% (95% CI: 2.3%- 12.9%), with corresponding AF of 5.0% (95% CI: 0.5%-9.3%), 4.7% (95% CI: 0.5%-8.6%), and 6.9% (95% CI: 2.3%-11.4%), respectively. Stratified analysis showed that the risk of traffic mortalities caused by daytime heatwaves was higher in females ( ER=15.7%, 95% CI: 5.8%-26.5%) than in males ( ER=1.8%, 95% CI: -3.6%-7.4%). Elderly individuals over 64 years old ( ER=10.9%, 95% CI: 0.3%- 22.6%) had a higher risk of road traffic mortalities from compound heatwaves than those under 45 years old ( ER=2.6%, 95% CI: -5.4%-11.2%). The risk of road traffic injury mortality from motor vehicle accidents caused by compound heatwaves ( ER=16.6%, 95% CI:2.4%-32.7%) was higher than that from non-motor vehicle accidents ( ER=5.7%, 95% CI:0.1%-11.5%). Conclusions:Short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves was associated with an increased risk of road traffic mortality, with the strongest association observed for compound heatwaves. The mortality burden attributable to compound heatwaves was higher than that for daytime and nighttime heatwaves. Heatwaves were more significantly associated with road traffic mortality risk among females, elderly individuals over 64 years old, and motor vehicle accidents.
10.MiR-543/SNTB1 axis modulates immune microenvironment in colorectal cancer
Min ZHANG ; Min LI ; Meng XIAO ; Cai CHEN ; Xiaoju ZHENG ; Yuguang LEI
Journal of Army Medical University 2025;47(13):1484-1493
Objective To investigate the clinical significance of the miR-543/syntrophin beta 1(SNTB1)axis in colorectal cancer(CRC)and its influence on the tumor immune microenvironment.Methods The expression of SNTB1 in CRC tissues was analyzed using public data,such as,The Cancer Genome Atlas(TCGA),Genotype-Tissue Expression(GTEx),and Human Protein Atlas(HPA).Then Kaplan-Meier survival analysis,univariate Cox regression analysis and correlation analysis were performed to evaluate the prognostic value of SNTB1 and its relationship with immune microenvironment in CRC.The targeting relationship between miR-543 and SNTB1 was confirmed through online databases and fluorescence assays in HT-29 cells.For in vitro experiments,after transfecting si-SNTB1,miR-543 mimics and/or SNTB1 overexpression plasmids,HT-29 cells were co-cultured with CD8+T cells,the expression of miR543 and SNTB1 and the viability and cytotoxicity of CD8+T cells were assessed with qRT-PCR,Western blotting,flow cytometry,ELISA,and lactate dehydrogenase(LDH)release assay.Results Analysis of public databases revealed significantly higher expression of SNTB1 in CRC tissues than normal tissues(P<0.001).The CRC patients with high SNTB1 expression exhibited poorer prognosis when compared with those with low expression level(P<0.05).Moreover,high SNTB1 expression was negatively correlated with immune scores in the tumor microenvironment and immune cell infiltration,especially CD8+T cells(P<0.05).Furthermore,Knockdown of SNTB1 in HT-29 cells enhanced the cytotoxic activity of CD8+T cells(P<0.01).Online database and in vitro experiments confirmed that miR-543 targets SNTB1,while the expression of miR-543 was decreased in colorectal cancer(P<0.001).Transfection with the miR-543 mimic inhibited the expression of SNTB1 in HT-29 cells(P<0.001),while overexpressing SNTB1 counteracted the promotion effect of miR-543 mimics on CD8+T cell-mediated cytotoxicity(P<0.05).Conclusion MiR-543 activates CD8+T cells and enhances their cytotoxicity against HT-29 cells by directly targeting SNTB1.

Result Analysis
Print
Save
E-mail