1.Dynamic Monitoring and Correlation Analysis of General Body Indicators, Blood Glucose, and Blood Lipid in Obese Cynomolgus Monkeys
Yanye WEI ; Guo SHEN ; Pengfei ZHANG ; Songping SHI ; Jiahao HU ; Xuzhe ZHANG ; Huiyuan HUA ; Guanyang HUA ; Hongzheng LU ; Yong ZENG ; Feng JI ; Zhumei WEI
Laboratory Animal and Comparative Medicine 2025;45(1):30-36
ObjectiveThis study aims to investigate the dynamic changes in general body parameters, blood glucose, and blood lipid profiles in obese cynomolgus monkeys, exploring the correlations among these parameters and providing a reference for research on the obese cynomolgus monkey model. Methods30 normal male cynomolgus monkeys aged 5 - 17 years old (with body mass index < 35 kg/m² and glycated hemoglobin content < 4.50%) and 99 spontaneously obese male cynomolgus monkeys (with body mass index ≥35 kg/m² and glycated hemoglobin content < 4.50%) were selected. Over a period of three years, their abdominal circumference, skinfold thickness, body weight, body mass index, fasting blood glucose, glycated hemoglobin, and four blood lipid indicators were monitored. The correlations between each indicator were analyzed using repeated measurement ANOVA, simple linear regression, and multiple linear regression correlation analysis method. Results Compared to the control group, the obese group exhibited significantly higher levels of abdominal circumference, skinfold thickness, body weight, body mass index, and triglyceride (P<0.05). In the control group, skinfold thickness increased annually, while other indicators remained stable. Compared with the first year, the obese group showed significantly increased abdominal circumference, skinfold thickness, body weight, body mass index, triglyceride, and fasting blood glucose in the second year(P<0.05), with this increasing trend persisting in the third year (P<0.05). In the control group, the obesity incidence rates in the second and third years were 16.67% and 23.33%, respectively, while the prevalence of diabetes remained at 16.67%. In the obese group, the diabetes incidence rates were 29.29% and 44.44% in years 2 and 3, respectively. Among the 11-13 year age group, the incidence rates were 36.36% and 44.68%, while for the group older than 13 years, the rates were 28.13% and 51.35%. Correlation analysis revealed significant associations (P<0.05) between fasting blood glucose and age, abdominal circumference, skinfold thickness, body weight, and triglyceride in the diabetic monkeys. Conclusion Long-term obesity can lead to the increases in general physical indicators and fasting blood glucose levels in cynomolgus monkeys, and an increase in the incidence of diabetes. In diabetic cynomolgus monkeys caused by obesity, there is a high correlation between their fasting blood glucose and age, weight, abdominal circumference, skinfold thickness, and triglyceride levels, which is of some significance for predicting the occurrence of spontaneous diabetes.
2.Expert consensus on prognostic evaluation of cochlear implantation in hereditary hearing loss.
Xinyu SHI ; Xianbao CAO ; Renjie CHAI ; Suijun CHEN ; Juan FENG ; Ningyu FENG ; Xia GAO ; Lulu GUO ; Yuhe LIU ; Ling LU ; Lingyun MEI ; Xiaoyun QIAN ; Dongdong REN ; Haibo SHI ; Duoduo TAO ; Qin WANG ; Zhaoyan WANG ; Shuo WANG ; Wei WANG ; Ming XIA ; Hao XIONG ; Baicheng XU ; Kai XU ; Lei XU ; Hua YANG ; Jun YANG ; Pingli YANG ; Wei YUAN ; Dingjun ZHA ; Chunming ZHANG ; Hongzheng ZHANG ; Juan ZHANG ; Tianhong ZHANG ; Wenqi ZUO ; Wenyan LI ; Yongyi YUAN ; Jie ZHANG ; Yu ZHAO ; Fang ZHENG ; Yu SUN
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(9):798-808
Hearing loss is the most prevalent disabling disease. Cochlear implantation(CI) serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system(Favorable, Marginal, Poor). The consensus focuses on common hereditary non-syndromic hearing loss(such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1) and syndromic hereditary hearing loss(such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome), which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans
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Cochlear Implantation
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Prognosis
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Hearing Loss/surgery*
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Consensus
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Connexin 26
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Mutation
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Sulfate Transporters
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Connexins/genetics*
3.Clinical characteristics and risk factors of delayed viral clearance in 562 Chikungunya fever patients in Shunde region, Guangdong Province, 2025
Zuning REN ; Guotao LYU ; Qun LIN ; Zhifeng HONG ; Shuichun WAN ; Feng KANG ; Yanling OUYANG ; Chunhua TU ; Guo RAO ; Hua LIANG ; Yawei LIU ; Yan ZHU ; Jie PENG ; Jie SHEN ; Hong LI
Chinese Journal of Infectious Diseases 2025;43(8):449-456
Objective:To analyze the clinical characteristics of the Chikungunya fever outbreak in Shunde District, Foshan City, Guangdong Province in July 2025 and the risk factors associated with delayed viral RNA clearance.Methods:A total of 562 patients with Chikungunya fever admitted to three designated hospitals in Shunde District from July 10 to 30, 2025 were enrolled. Demographic data, clinical manifestations, and laboratory findings were collected. Patients were categorized into four age groups including minors (<18 years), young adults (18 to 39 years), middle-aged adults (40 to 64 years) and elderly adults (≥65 years). The differences of clinical characteristics among these age groups were analyzed. Intergroup comparisons were performed using chi-square test, one-way analysis of variance, or Kruskal-Wallis H test. Pairwise comparisons between groups were conducted using the Bonferroni or Games-Howell or Dunn method. Binary logistic regression was employed to analyze risk factors associated with delayed viral RNA clearance (>7 days). Results:The mean age of the 562 enrolled Chikungunya fever patients was (44.8±21.3) years. Fever, arthralgia and rash were the three core symptoms, with incidence rates of 87.5% (492/562), 88.4%(497/562) and 69.6%(391/562), respectively. At discharge, only 54.1%(304/562) of patients achieved complete symptom resolution, while 26.5%(149/562) still had arthralgia and 36.1%(203/562) had residual rash. Significant differences were observed among age groups in the incidence of fever ( χ2=9.43, P=0.024), peak body temperature ( F=6.54, P<0.001), incidence of arthralgia ( χ2=26.89, P<0.001), duration of arthralgia ( F=12.68, P=0.001), incidence of rash ( χ2=68.99, P<0.001), rate of residual rash at discharge ( χ2=32.37, P<0.001), lymphocyte count ( F=12.94, P<0.001), platelet count ( F=14.95, P<0.001), and C-reactive protein levels (CRP) ( H=94.18, P<0.001). Further pairwise comparisons revealed that compared to the middle-aged and elderly groups, the minor group had a higher incidence of fever and a lower incidence of arthralgia, and the duration of arthralgia was shorter than the elderly group (all P<0.008 3). Compared with the other three groups, the elderly group had lower incidence and residual rate of rash, and lower platelet counts (all P<0.008 3), and higher levels of CRP (all P<0.05). The elderly group had lower lymphocyte counts compared to the minor and young adult groups (both P<0.05). Significant differences were found among age groups in the time to viral RNA clearance ( F=5.77, P=0.003) and length of hospital stay ( F=11.64, P<0.001), with the elderly group having significantly longer duration for both compared to the other three groups (all P<0.05). Multivariate analysis showed that advanced age (odds ratio ( OR)=1.049, 95% confidence interval ( CI) 1.015 to 1.083), longer duration of fever ( OR=1.529, 95% CI 1.086 to 2.155) and longer duration of arthralgia ( OR=1.927, 95% CI 1.318 to 2.817) were independent risk factors for delayed viral RNA clearance (all P<0.05). Conclusions:Patients with Chikungunya fever in Shunde District primarily present with fever, arthralgia and rash. The incidence and characteristics of these three core symptoms show age-related variations. Elderly patients and those with longer durations of fever or arthralgia are more likely to experience delayed viral clearance.
4.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
5.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
6.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
7.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
8.A method for quality control of Angelicae Dahuricae Radix derived from different plants based on UPLC characteristic fingerprints, chemometrics, and QAMS.
Tian-Hua DUAN ; Rong-Rong XU ; Rui LI ; Chu-Han ZHANG ; Xin-Guo WANG ; Wei FENG
China Journal of Chinese Materia Medica 2025;50(4):1051-1062
The ultra-high performance liquid chromatography( UPLC) characteristic fingerprints of Angelica dahurica and A. dahurica var. formosana were established. The compounds corresponding to common peaks were identified by ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry( UPLC-Q-TOF-MS/MS). The results were combined with chemometrics and quantitative analysis of multi-components with a single-marker method(QAMS) to study the quality control of A. dahurica and A. dahurica var. formosana. The separation was performed on a Titank C_(18) column(2. 1 mm × 150 mm, 1. 8 μm)with a mobile phase of acetonitrile-0. 2% formic acid at a flow rate of 0. 3 m L·min~(-1). The column temperature was 35 ℃ and the injection volume was 1. 2 μL. Seven batches of A. dahurica and 11 batches of A. dahurica var. formosana were injected and analyzed. The UPLC characteristic fingerprints of A. dahurica and A. dahurica var. formosana were established according to the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine( version 2012), and 19 and 20 characteristic peaks were matched respectively. The common peaks were identified by reference substance comparison and UPLC-Q-TOF-MS/MS. Cluster analysis(CA), principal component analysis(PCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA)were performed to analyze the chemical pattern recognition of A. dahurica and A. dahurica var. formosana. The results of CA and PCA could distinguish Angelicae Dahuricae Radix from different producing areas, and the differential quality markers of A. dahurica and A. dahurica var. formosana were obtained by OPLS-DA. With imperatorin as the internal reference, the relative correction factors of oxypeucedanin hydrate, byakangelicin, bergapten, isopimpinellin, oxypeucedanin, and isoimperatorin were 1. 310, 1. 069, 0. 729, 0. 633, 0. 753, and 1. 010, respectively. There was no significant difference between the QAMS and external standard method(ESM)results of each component, indicating that the QAMS established with imperatorin as the internal reference was accurate and reliable. The characteristic fingerprints, chemometrics, and QAMS established in this study can quickly and efficiently control the quality of A. dahurica and A. dahurica var. formosana.
Quality Control
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Chromatography, High Pressure Liquid/methods*
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Drugs, Chinese Herbal/chemistry*
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Angelica/chemistry*
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Chemometrics/methods*
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Tandem Mass Spectrometry/methods*
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Principal Component Analysis
9.Digital identification of Cervi Cornu Pantotrichum based on HPLC-QTOF-MS~E and Adaboost.
Xiao-Han GUO ; Xian-Rui WANG ; Yu ZHANG ; Ming-Hua LI ; Wen-Guang JING ; Xian-Long CHENG ; Feng WEI
China Journal of Chinese Materia Medica 2025;50(5):1172-1178
Cervi Cornu Pantotrichum is a precious animal-derived Chinese medicinal material, while there are often adulterants derived from animals not specified in the Chinese Pharmacopeia in the market, which disturbs the safety of medication. This study was conducted with the aim of strengthening the quality control of Cervi Cornu Pantotrichum and standardizing the medication. To achieve digital identification of Cervi Cornu Pantotrichum from different sources, a digital identification model was constructed based on ultra-high performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry(UHPLC-QTOF-MS~E) combined with an adaptive boosting algorithm(Adaboost). The young furred antlers of sika deer, red deer, elk, and reindeer were processed and then subjected to polypeptide analysis by UHPLC-QTOF-MS~E. Then, the mass spectral data reflecting the polypeptide information were obtained by digital quantification. Next, the key data were obtained by feature screening based on Gini index, and the digital identification model was constructed by Adaboost. The model was evaluated based on the recall rate, F_1 composite score, and accuracy. Finally, the results of identification based on the constructed digital identification model were validated. The results showed that when the Gini index was used to screen the data of top 100 characteristic polypeptides, the digital identification model based on Adaboost had the best performance, with the recall rate, F_1 composite score, and accuracy not less than 0.953. The validation analysis showed that the accuracy of the identification of the 10 batches of samples was as high as 100.0%. Therefore, based on UHPLC-QTOF-MS~E and Adaboost algorithm, the digital identification of Cervi Cornu Pantotrichum can be realized efficiently and accurately, which can provide reference for the quality control and original animal identification of Cervi Cornu Pantotrichum.
Animals
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Algorithms
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Antlers/chemistry*
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Boosting Machine Learning Algorithms
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Chromatography, High Pressure Liquid/methods*
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Deer
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Drugs, Chinese Herbal/chemistry*
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Mass Spectrometry/methods*
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Quality Control
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Reindeer
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Tandem Mass Spectrometry/methods*
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Tissue Extracts/analysis*
10.Research progress in pharmacological effects of puerarin.
Xiao-Wei MENG ; Feng-Mei GUO ; Qian-Qian WANG ; Jia-Rong LI ; Ni ZHANG ; Fei QU ; Rong-Hua LIU ; Wei-Feng ZHU
China Journal of Chinese Materia Medica 2025;50(11):2954-2968
Traditional Chinese medicine(TCM), a treasure of the Chinese nation, contains abundant chemical components and demonstrates unique pharmacological activities, showing important values in clinical applications. With profound connotations and broad application prospects, TCM urgently needs us to further explore and conduct systematic research. Puerarin is a small-molecule natural isoflavonoid carbon glycoside extracted from plants of Pueraria. It is also the main active ingredient of Puerariae Lobata Radix, a Chinese herbal medicine with both medicinal and edible values. Puerarin has a variety of pharmacological effects such as blood pressure-lowering, anti-atherosclerosis, anti-ischemia-reperfusion injury, antithrombotic, anti-tumor, anti-inflammatory, liver-protecting, nerve cell-protecting, and intestinal microbiota-regulating effects. It is also an active ingredient that has been widely studied. This article comprehensively reviews the research progress in the pharmacological effects and molecular mechanisms of puerarin over the years, aiming to provide references and theoretical support for the in-depth research and development as well as clinical application of puerarin.
Isoflavones/chemistry*
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Humans
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Animals
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Drugs, Chinese Herbal/chemistry*
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Pueraria/chemistry*

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