1.Review of chemical constituents, pharmacological effects, and quality control status of Eucommiae Cortex and prediction of its Q-markers.
Meng-Fan PENG ; Bao-Song LIU ; Pei-Pei YAN ; Cai-Xia LI ; Xiao-Fang ZHANG ; Yi ZHENG ; Ya-Gang SONG ; Tong LIU ; Lei YANG ; Ming-San MIAO
China Journal of Chinese Materia Medica 2025;50(4):946-958
Eucommiae Cortex, the dried bark of Eucommia ulmoides( Eucommiaceae), has both medicinal and edible values.Modern research has shown that Eucommiae Cortex contains various components such as flavonoids, lignans, iridoids, phenolic acids,terpenoids, and steroids, which have anti-osteoporosis, antioxidant, anti-inflammatory, blood glucose-lowering, and gastrointestinal tract-protecting effects. Eucommiae Cortex has applications in multiple fields such as healthcare, industry, and animal husbandry,demonstrating broad development prospects. This article reviews the chemical constituents, pharmacological effects, and quality control status of Eucommiae Cortex. Furthermore, according to the concept of quality marker(Q-marker), this article predicts the Q-markers of Eucommiae Cortex from traditional medicinal properties, traditional medicinal effects, new medicinal effects, measurability of chemical components, compatibility, harvesting periods, and geographical origins. The components such as pinoresinol diglucoside,chlorogenic acid, caffeic acid, quercetin, baicalein, baicalin, olivil, coniferyl ferulate, and kaempferol can be used as Q-markers for Eucommiae Cortex, which provide reference for establishing a systematic quality control system for Eucommiae Cortex.
Eucommiaceae/chemistry*
;
Drugs, Chinese Herbal/pharmacology*
;
Quality Control
;
Humans
;
Animals
2.Association of higher serum follicle-stimulating hormone levels with successful microdissection testicular sperm extraction outcomes in nonobstructive azoospermic men with reduced testicular volumes.
Ming-Zhe SONG ; Li-Jun YE ; Wei-Qiang XIAO ; Wen-Si HUANG ; Wu-Biao WEN ; Shun DAI ; Li-Yun LAI ; Yue-Qin PENG ; Tong-Hua WU ; Qing SUN ; Yong ZENG ; Jing CAI
Asian Journal of Andrology 2025;27(3):440-446
To investigate the impact of preoperative serum follicle-stimulating hormone (FSH) levels on the probability of testicular sperm retrieval, we conducted a study of nonobstructive azoospermic (NOA) men with different testicular volumes (TVs) who underwent microdissection testicular sperm extraction (micro-TESE). A total of 177 NOA patients undergoing micro-TESE for the first time from April 2019 to November 2022 in Shenzhen Zhongshan Obstetrics and Gynecology Hospital (formerly Shenzhen Zhongshan Urology Hospital, Shenzhen, China) were retrospectively reviewed. The subjects were divided into four groups based on average TV quartiles. Serum hormone levels in each TV group were compared between positive and negative sperm retrieval subgroups. Overall sperm retrieval rate was 57.6%. FSH levels (median [interquartile range]) were higher in the positive sperm retrieval subgroup compared with the negative outcome subgroup when average TV was <5 ml (first quartile [Q1: TV <3 ml]: 43.32 [17.92] IU l -1 vs 32.95 [18.56] IU l -1 , P = 0.048; second quartile [Q2: 3 ml ≤ TV <5 ml]: 31.31 [15.37] IU l -1 vs 25.59 [18.40] IU l -1 , P = 0.042). Elevated serum FSH levels were associated with successful micro-TESE sperm retrieval in NOA men whose average TVs were <5 ml (adjusted odds ratio [OR]: 1.06 per unit increase; 95% confidence interval [CI]: 1.01-1.11; P = 0.011). In men with TVs ≥5 ml, larger TVs were associated with lower odds of sperm retrieval (adjusted OR: 0.84 per 1 ml increase; 95% CI: 0.71-0.98; P = 0.029). In conclusion, elevated serum FSH levels were associated with positive sperm retrieval in micro-TESE in NOA men with TVs <5 ml. In men with TV ≥5 ml, increases in average TVs were associated with lower odds of sperm retrieval.
Humans
;
Male
;
Azoospermia/surgery*
;
Sperm Retrieval/statistics & numerical data*
;
Adult
;
Follicle Stimulating Hormone/blood*
;
Retrospective Studies
;
Testis/pathology*
;
Microdissection
;
Organ Size
3.Deep learning model based on fundus images for detection of coronary artery disease with mild cognitive impairment
Yi YE ; Wei FENG ; Yao-dong DING ; Qing CHEN ; Yang ZHANG ; Li LIN ; Tong MA ; Bin WANG ; Xian-gang CHANG ; Zong-yuan GE ; Xiao-yi WANG ; Long-jun CAI ; Yong ZENG
Chinese Journal of Interventional Cardiology 2025;33(6):303-311
Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50% stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE<27 or MoCA<26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95%CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95%CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95%CI 0.714-0.802),corresponding to a validated AUC of 0.710(95%CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95%CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95%CI 0.719-0.778)and the specificity was 0.561(95%CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95%CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.
4.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
5.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
6.Deep learning model based on fundus images for detection of coronary artery disease with mild cognitive impairment
Yi YE ; Wei FENG ; Yao-dong DING ; Qing CHEN ; Yang ZHANG ; Li LIN ; Tong MA ; Bin WANG ; Xian-gang CHANG ; Zong-yuan GE ; Xiao-yi WANG ; Long-jun CAI ; Yong ZENG
Chinese Journal of Interventional Cardiology 2025;33(6):303-311
Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50% stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE<27 or MoCA<26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95%CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95%CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95%CI 0.714-0.802),corresponding to a validated AUC of 0.710(95%CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95%CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95%CI 0.719-0.778)and the specificity was 0.561(95%CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95%CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.
7.Study on the trajectories change of visiting community health service centers and blood glucose control level of type 2 diabetes patients in Minhang District,Shanghai
Dan-Dan HE ; Yi-Bin ZHOU ; Hui-Lin XU ; Tong-Tong LIANG ; Yi-Zhou CAI ; Dan-Dan YU ; Xiao-Li XU ; Lin-Juan DONG ; Nian LIU ; Xiao-Hua LIU
Fudan University Journal of Medical Sciences 2024;51(6):981-989
Objective To construct trajectory models of care-seeking patterns for type 2 diabetes mellitus(T2DM)patients,analyze the influencing factors of different trajectories,and explore the fasting blood glucose control levels of T2DM patients with different trajectories.Methods A retrospective cohort study was carried out on 18088 T2DM patients who had health records and been involved in the diabetic management in Community Health Service Center of Minhang District,Shanghai from 2006 to 2009.Starting from Jan 1,2010,participants were followed up until Dec 31,2019,with complete follow-up information.Group-based trajectory modelling(GBTM)was employed to identify and construct the fluctuation trajectory of fasting blood glucose in the patients.Bayesian information criterion(BIC),average posterior probability(AvePP)and other evaluation indicators were used to select the optimum subgroup number model.Then the differences in demographic characteristics,health status,family history,fasting blood glucose,BMI,etc were compared among different categories.Multinational logistic regression model was constructed to explore the influencing factors of different fluctuation trajectories.Cox regression analysis was used to examine the relationship between the long-term trajectories of care-seeking patterns and fasting blood glucose control level.Results Using GBTM analysis,we constructed the optimal Model 4 to categorize 18088 T2DM patients with community health records into five distinct trajectory subgroups:continuous non-attendance group(22.29%),low-level increasing group(15.09%),high-level slowly decreasing group(14.18%),high-level rapidly decreasing group(14.90%),and continuous regular attendance group(33.54%).With the continuous regular attendance group serving as the reference,gender,age,place of residence,baseline comorbidity of hypertension,baseline fasting plasma glucose level,and BMI were found to influence the community attendance trajectories of T2DM patients(P<0.05).After adjusting for confounding factors,Cox regression analysis revealed that compared to the continuous non-attendance group,the low-level increasing group,high-level slowly decreasing group,and continuous regular attendance group had better glycemic control,with HRs of 0.37(95%CI:0.34-0.39),0.72(95%CI:0.67-0.78),and 0.78(95%CI:0.73-0.84),respectively.The glycemic control level in the high-level rapidly decreasing group was comparable,with an HR of 1.06(95%CI:0.99-1.12).Conclusion Based on the optimal model,the community medical treatment trajectories of T2DM patients showed different dynamic characteristics.Factors such as gender,residence,hypertension,and weight loss may influence these varying trajectories.Regular community visits and follow-up may help control blood glucose levels.
8.Analysis of risk factors for clinical use of artificial intelligence-aided medical detection devices
Xiao-Yan ZHANG ; Yu-Tian LIU ; Tong-Cai WANG ; Dan-Dan ZHU ; Yue-Fei LI
Chinese Medical Equipment Journal 2024;45(11):77-82
The common risks of artificial intelligence-aided medical detection devices during the clinical application were analyzed.Some measures were put forward such as improving the design of the devices,ensuring data security and enhancing social and legal supervision,and references were provided for efficiently integrating clinical and data resources and achieving safety during the clinical application of medical devices.[Chinese Medical Equipment Journal,2024,45(11):77-82]
9.Study on detection of bacterial endotoxin by micro kinetic chromogenic method
Chen-Xue ZHANG ; Tong CAI ; Chen CHEN ; Xiao-Yan ZHAO ; Yu-Sheng PEI
Chinese Pharmacological Bulletin 2024;40(7):1392-1398
Aim To determine whether the micro kinetic chro-mogenic method can meet the requirements of Chinese Pharma-copoeia,as a supplement to the existing bacterial endotoxin test method.Methods Using micro kinetic chromogenic horseshoe crab reagent,the sample volume per well was 25 μL,the detec-tion wavelength was 405 nm,the preset OD value was 0.05,and the detection was carried out by half-well enzyme plate.In accordance with the provisions of"9101 Guiding Principles for Validation of Drug Quality Analysis Methods"in the fourth part of the 2020 edition of the People's Republic of China Pharmaco-poeia,the methodological verification of 7 items of specificity,accuracy,precision,limit of quantification,linearity,range and durability was carried out according to the specific requirements of the"quantitative"item in the"Determination of Impurities".The variety suitability study was conducted on 74 batches of samples from 48 drug varieties,and 143 batches of samples from 76 drug varieties(including 133 batches of negative samples and 10 batches of positive samples)were tested daily,and the re-sults were compared with the results of traditional color rendering method.Results The method of microdynamic color develop-ment met the requirements of the Pharmacopoeia of the People's Republic of China for quantitative methods.The results of varie-tal applicability and consistency comparison showed that the mi-crodynamic color development method had better equivalence compared with the traditional color development method.Con-clusion The micro kinetic chromogenic method can be promo-ted as a supplementary alternative to the existing bacterial endo-toxin methods.
10.Dynamic characterization of neuronal injury in cortex and hippocampus of mice after acute cerebral ischemia/reperfusion
Tong LI ; Jia-Ming BAI ; Yi-Jun SHI ; Cai-Ming WEN ; Lin CUI ; Jing-Xian YANG ; Hong-He XIAO
Chinese Pharmacological Bulletin 2024;40(9):1708-1718
Aim To dynamically characterize neuronal damage in the cortex and hippocampus of mice follow-ing acute cerebral ischemia/reperfusion(I/R).Meth-ods Male C57BL/6J mice weighing 25-28 g under-went middle cerebral artery occlusion using the fila-ment method,followed by 1 hour of reperfusion to es-tablish the acute cerebral I/R injury mouse model.The experiment comprised a sham surgery group,I/R-6 h group,I/R-24 h group,and I/R-72 h group.Longa neurological function score was used to assess the neu-rological function.Triphenyltetrazolium chloride(TTC)staining was conducted to detect cerebral in-farct volume.Hematoxylin and eosin(HE)staining was utilized to observe brain tissue pathological dam-age.Nissl staining was performed to evaluate neuronal damage.Immunofluorescence histochemistry staining was employed to assess the activation of astrocytes and microglia,as well as neuronal loss.Transmission elec-tron microscopy was used to examine mitochondrial damage in hippocampal neurons.Western blot analysis was conducted to detect the expression levels of mito-chondrial fission-fusion-related proteins p-Drp1/Drp1,Mff,Fis1,and OPA1.Results With prolonged cere-bral I/R time,neurological functional impairment,cerebral infarct volume,neuronal damage in the cortex and hippocampus,glial cell activation,neuronal loss,and mitochondrial damage gradually worsened in mice.The expression of mitochondrial fission-related proteins increased gradually,while the expression of mitochon-drial fusion-related proteins decreased gradually.Con-clusions Neuronal pathological damage,such as glial cell activation,neuronal loss,and mitochondrial dam-age,is gradually aggravated with prolonged cerebral I/R time,which may be associated with mitochondrial dynamics imbalance.

Result Analysis
Print
Save
E-mail