1.Research on Magnetic Stimulation Intervention Technology for Alzheimer’s Disease Guided by Heart Rate Variability
Shu-Ting CHEN ; Du-Yan GENG ; Chun-Meng FAN ; Wei-Ran ZHENG ; Gui-Zhi XU
Progress in Biochemistry and Biophysics 2025;52(5):1264-1278
ObjectiveNon-invasive magnetic stimulation technology has been widely used in the treatment of Alzheimer’s disease (AD), but there is a lack of convenient and timely methods for evaluating and providing feedback on the effectiveness of the stimulation, which can be used to guide the adjustment of the stimulation protocol. This study aims to explore the possibility of heart rate variability (HRV) in diagnosing AD and guiding AD magnetic stimulation intervention techniques. MethodsIn this study, we used a 40 Hz, 10 mT pulsed magnetic field to expose AD mouse models to whole-body exposure for 18 d, and detected the behavioral and electroencephalographic signals before and after exposure, as well as the instant electrocardiographic signals after exposure every day. ResultsUsing one-way ANOVA and Pearson correlation coefficient analysis, we found that some HRV indicators could identify AD mouse models as accurately as behavioral and electroencephalogram(EEG) changes (P<0.05) and significantly distinguish the severity of the disease (P<0.05), including rMSSD, pNN6, LF/HF, SD1/SD2, and entropy arrangement. These HRV indicators showed good correlation and statistical significance with behavioral and EEG changes (r>0.3, P<0.05); HRV indicators were significantly modulated by the magnetic field exposure before and after the exposure, both of which were observed in the continuous changes of electrocardiogram (ECG) (P<0.05), and the trend of the stimulation effect was more accurately observed in the continuous changes of ECG. ConclusionHRV can accurately reflect the pathophysiological changes and disease degree, quickly evaluate the effect of magnetic stimulation, and has the potential to guide the pattern of magnetic exposure, providing a new idea for the study of personalized electromagnetic neuroregulation technology for brain diseases.
2.Bioequivalence study of compound lidocaine cream in healthy Chinese subjects
Meng-Qi CHANG ; Yu-Qi SUN ; Qiu-Jin XU ; Xi-Xi QIAN ; Ying-Chun ZHAO ; Yan CAO ; Liu WANG ; Cheng ZHANG ; Dong-Liang YU
The Chinese Journal of Clinical Pharmacology 2024;40(9):1321-1326
Objective To study the pharmacokinetic characteristics of the test formulation of compound lidocaine cream and reference formulation of lidocaine and prilocaine cream in Chinese healthy subjects and to evaluate whether there is bioequivalence between the two formulations.Methods A single-center,single-dose,randomized,open-label,two-period,two-sequence,crossover design was used.This study included 40 healthy subjects,and in each period,test formulation or reference formulation 60 g was applied to the skin in front of both thighs(200 cm2 each side,a total of 400 cm2)under fasting conditions,and the drug was left on for at least 5 h after application.The concentrations of lidocaine and prilocaine in plasma were determined using liquid chromatography-tandem mass spectrometry(LC-MS/MS)method.Pharmacokinetic parameters were calculated using WinNonlin 8.0 software to evaluate the bioequivalence of the two formulations.Results After the application of the test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream on both thighs of the subjects,the pharmacokinetic parameters of lidocaine in plasma were as follows:Cmax were(167.27±91.33)and(156.13±66.86)ng·mL-1,AUC0-t were(1 651.78±685.09)and(1 636.69±617.23)ng·mL-1·h,AUC0-∞ were(1 669.85±684.65)and(1 654.37±618.30)ng·mL-1·h,the adjusted geometric mean ratios were 104.49%,101.88%and 101.89%,respectively,with 90%confidence intervals of 98.18%-111.20%,97.80%-106.13%and 97.87%-106.07%,all within the range of 80.00%-125.00%.The pharmacokinetic parameters of prilocaine in plasma were as follows:Cmax were(95.66±48.84)and(87.52±39.16)ng·mL-1,AUC0-t were(790.86±263.99)and(774.14±256.42)ng·mL-1·h,AUC0_m were(807.27±264.67)and(792.84±254.06)ng·mL-1 h,the adjusted geometric mean ratios were 107.34%,103.55%and 102.98%,respectively with 90%confidence intervals of 101.69%-113.31%,99.94%-107.30%and 99.65%-106.43%,all within the range of 80.00%-125.00%.Conclusion The test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream are bioequivalent.
3.Full-length transcriptome sequencing and bioinformatics analysis of Polygonatum kingianum
Qi MI ; Yan-li ZHAO ; Ping XU ; Meng-wen YU ; Xuan ZHANG ; Zhen-hua TU ; Chun-hua LI ; Guo-wei ZHENG ; Jia CHEN
Acta Pharmaceutica Sinica 2024;59(6):1864-1872
The purpose of this study was to enrich the genomic information and provide a basis for further development and utilization of
4.Analysis of the biosynthesis pathways of phenols in the leaves of Tetrastigma hemsleyanum regulated by supplemental blue light based on transcriptome sequencing
Hui-long XU ; Nan YANG ; Yu-yan HONG ; Meng-ting PAN ; Yu-chun GUO ; Shi-ming FAN ; Wen XU
Acta Pharmaceutica Sinica 2024;59(10):2864-2870
Analyze the changes in phenolic components and gene expression profiles of
5.Development of an in vitro screening method for idiosyncratic hepatotoxic components in traditional Chinese medicine: a case study with Epimedii Folium and Psoraleae Fructus
Ying-ying LI ; Meng-meng LIN ; Bo CAO ; Ying LI ; Jing XU ; Xiao-he XIAO ; Guo-hui LI ; Chun-yu LI
Acta Pharmaceutica Sinica 2024;59(3):621-632
Idiosyncratic drug-induced liver injury (IDILI) has long posed a challenging and pivotal concern in pharmaceutical research. The complex composition of traditional Chinese medicine (TCM) has introduced a bottleneck in current research, hindering the elucidation of the component basis associated with IDILI in TCM. Using
6.Distribution Patterns of Traditional Chinese Medicine Constitution in 959 Patients with Endometriosis
Xin-Chun YANG ; Wei-Wei SUN ; Ying WU ; Qing-Wei MENG ; Cai XU ; Zeng-Ping HAO ; Yu-Huan LIU ; Rui-Jie HOU ; Rui-Hua ZHAO
Journal of Guangzhou University of Traditional Chinese Medicine 2024;41(6):1387-1392
Objective To investigate the distribution patterns of traditional Chinese medicine(TCM)constitution in 959 patients with endometriosis(EMs).Methods From January 2019 to November 2019,959 EMs patients were selected from Guang'anmen Hospital of China Academy of Chinese Medical Sciences,Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University,Beijing Hospital,Dongfang Hospital of Beijing University of Chinese Medicine,Beijing Friendship Hospital Affiliated to Capital Medical University,and Fuxing Hospital Affiliated to Capital Medical University.The general clinical information of the patients was recorded and then the TCM constitution was identified.After that,the correlation of TCM constitution distribution with concurrent constitution and the relationship of TCM constitution distribution with age and the complication of dysmenorrhea were analyzed.Results(1)The constitution types of EMs patients listed in descending order of the proportion were yang deficiency constitution(65.1%,624/959),qi stagnation constitution(58.4%,560/959),qi deficiency constitution(52.8%,506/959),blood stasis constitution(44.2%,424/959),phlegm-damp constitution(42.5%,408/959),damp-heat constitution(41.9%,402/959),yin deficiency constitution(39.6%,380/959),balanced constitution(26.8%,257/959),and inherited special constitution(16.6%,159/959).Among the patients,there were fewer patients with single constitution,accounting for 20.2%(194/959),and most of them had concurrent constitution types,accounting for 79.8%(765/959).(2)The association rule mining based on Apriori algorithm obtained 33 related rules.The concurrent constitution types of qi deficiency-yang deficiency,blood stasis-yang deficiency,and blood stasis-qi stagnation were the association rules with high confidence.(3)Compared with patients aged 35 years and below,the patients over 35 years old were predominated by high proportion of blood stasis constitution(P<0.05).Compared with patients without dysmenorrhea,the patients with dysmenorrhea had the increased proportion of biased constitutions and the decreased proportion of balanced constitution(P<0.05 or P<0.01).Conclusion Yang deficiency constitution,qi stagnation constitution,qi deficiency constitution and blood stasis constitution are the high-risk constitution types of EMs patients.The concurrent constitution types are commonly seen in EMs patients,which are more common than single biased constitution.Management of EMs patients with the methods of warming yang,relieving stagnation,benefiting qi and activating blood will be helpful for correcting the biased constitutions in time and preventing disease progression,which will achieve the preventive treatment efficacy through TCM constitution correction.
7.Analysis of causes of bleeding after endoscopic duodenal papillary adenoma resection and establishment of prediction model
Chun-Yan JIN ; Hua YANG ; Lei WANG ; Qin YIN ; Meng-Yun HU ; Xu FANG ; Mu-Han NI
Modern Interventional Diagnosis and Treatment in Gastroenterology 2024;29(4):398-402,406
Objective The causes of bleeding after endoscopic duodenal papilloma resection were analyzed and discussed,and the prediction model of nomogram was established.Methods A total of 233 patients who underwent endoscopic duodenal papilloma resection in our hospital from January 2018 to December 2023 were retrospectively analyzed,and they were divided into bleeding group(n=31 cases)and non-bleeding group(n=202 cases)according to whether postoperative bleeding occurred.The clinical data of the two groups were compared,the independent risk factors for postoperative bleeding were analyzed by multi-factor logistic regression,the risk nomogram prediction model was constructed,and the Bootstrap method was used for 1000 repeated samples to carry out internal verification.Results Anticoagulant drugs(OR=9.063,95%CI:2.132-38.525),lesion diameter ≥2 cm(OR=2.802,95%CI:1.073-7.321),intraoperative fragment resection(OR=27.653,95%CI:3.055~619.174)and pancreatic complications(OR=6.859,95%CI:1.930~24.377)were independent risk factors for postoperative bleeding after endoscopic duodenal papilloma resection(P<0.05).A risk prediction nomogram model was constructed according to the Logistic regression analysis results.The samples were repeatedly sampled 1000 times through Bootstrap method for internal verification.The area under the ROC curve was 0.850,and the 95%CI was 0.780-0.913,indicating good differentiation ability of the model.Calibration curve analysis indicated that the prediction probability of postoperative bleeding predicted by the nomogram prediction model was in good agreement with the actual probability of postoperative bleeding,and Hosmer-Lemeshow showed good goodness of fit(x2=3.304 9,P=0.913 8).Conclusion Taking anticoagulant drugs,lesion diameter ≥2 cm,intraoperative segmentary resection,and postoperative combination of pancreas were independent risk factors for bleeding after endoscopic duodenal papilloma resection.A nomogram prediction model was established to help clinical assessment of postoperative bleeding risk in patients and improve decision-making basis for early prevention.
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

Result Analysis
Print
Save
E-mail