1.Establishment and application of the method for plasma concentration determination of lamotrigine,levetiracetam and perampanel in children with epilepsy
Wenlin SONG ; Ying ZHOU ; Haoran CHEN ; Ziyue LIN ; Yan LI ; Jie LIU ; Taiwei JIN ; Xuqiang ZHOU
China Pharmacy 2026;37(10):1313-1317
OBJECTIVE To establish a method for simultaneous determination of plasma concentration of lamotrigine(LTG), levetiracetam(LEV) and perampanel(PER) in children with epilepsy and apply this method in clinical practice. METHODS Plasma proteins were precipitated with acetonitrile. Using PER-D 5 as internal standard, ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was adopted. The determination was performed on ACQUITY UPLC HSS T3 C 18 column with mobile phase consisted of 0.1% formic acid with 5 mmol/L ammonium acetate-acetonitrile (gradient elution) at the flow rate of 0.3 mL/min. The column temperature was 40 ℃, and sample size was 5 μL. The analysis time was 5 min. The electrospray ionization source and multiple reaction monitoring mode were used for positive ion scanning. The ion pairs used for quantitative analysis of LTG, LEV, PER and internal standard were m / z 255.9→144.9, m / z 171.1→126.1, m / z 350.1→219.0 and m / z 354.9→220.2, respectively. The steady-state trough concentrations of the aforementioned drugs in the plasma of 14 pediatric epilepsy patients receiving combination therapy were determined using the same UPLC-MS/MS method as above. RESULTS The linear ranges of LTG, LEV and PER were 0.15-24 μg/mL ( R 2 >0.993), 0.312 5-50 μg/mL ( R 2 >0.997) and 6.25-1 000 ng/mL ( R 2 >0.997), respectively. The lower limits of quantification were 0.15 μg/mL, 0.312 5 μg/mL and 6.25 ng/mL, respectively. RSDs of intraday and interday precision tests of the three drugs were no more than 9.83%, and the accuracies (relative errors) were between -9.33% and 13.72%( n =6 or n =18); the average extraction recovery rates were 86.4%-97.9%, and the average matrix effects were 86.9%-110.0% ( n =6). The absolute values of the relative errors in the stability tests were all below 15%. The steady-state trough concentrations of LTG, LEV and PER were (5.64±4.03)μg/mL, (10.67±8.78)μg/mL and(450.20±251.27)ng/mL, respectively; the rates of achieving target trough concentrations were 71.4%, 37.5% and 84.6%, respectively. CONCLUSIONS The established UPLC-MS/MS method is specific, rapid and suitable for the plasma concentration monitoring in epileptic children receiving combination therapy.
2.Analysis of risk factors for cardiovascular events and construction of a nomogram prediction model in patients undergoing long-term peritoneal dialysis
Xinyuan ZHOU ; Yuxin JIANG ; Xiaoxia WANG ; Xiangjie YANG ; Runzhe ZHOU ; Yuqing MENG ; Dingxin ZHANG ; Jin ZHANG ; Ying WANG
Acta Universitatis Medicinalis Anhui 2026;61(4):748-757
ObjectiveTo analyze the risk factors for long-term cardiovascular events in patients undergoing long-term peritoneal dialysis (PD), and to construct and validate a visual nomogram prediction model based on multiple parameters. MethodsA prospective cohort study was conducted, consecutively enrolling 248 maintenance PD patients (dialysis duration ≥ 3 months). Demographic characteristics, clinical indicators, laboratory parameters, and echocardiographic indices (including left ventricular ejection fraction [LVEF], ratio of early diastolic mitral inflow velocity to early diastolic mitral annular velocity (E/e’), etc.) were collected. The composite endpoint was defined as the occurrence of cardiovascular events or cardiovascular death, with non-cardiovascular death as the competing risk and loss to follow-up or the end of follow-up as censoring events. Fine-Gray competing risks model was used to screen independent predictors, based on which a nomogram model was constructed. Internal validation was performed using the Bootstrap method (1 000 resamplings), and the concordance index (C-index) and time-dependent receiver operating characteristic (time-dependent ROC) curve were calculated to evaluate the model performance. ResultsWith a median follow-up of 29 months (interquartile range: 24–35 months), 88 patients (35.48%) reached the composite endpoint, including 80 cases of cardiovascular events and 8 cases of cardiovascular death, and 4 patients died of non-cardiovascular causes. Multivariate Fine-Gray analysis revealed that age, diabetes mellitus, hemoglobin (HGB) level and E/e' ratio were independent influencing factors of the composite endpoint. Specifically, each 1-year increase in age was associated with a 3.0% increase in the risk of the composite endpoint (HR=1.030, P=0.006); patients with diabetes mellitus had a 167.9% higher risk compared with non-diabetic patients (HR=2.679, P=0.007); each 1g/L increase in HGB level contributed to a 1.5% reduction in the risk (HR=0.985, P=0.003); and each 0.1 increase in E/e' ratio led to a 7.2% increase in the risk (HR=1.072, P=0.045). The nomogram model had a C-index of 0.76 (95% CI: 0.698–0.820), and the AUC of the time-dependent ROC curve reached 0.849 at 23 months of follow-up. ConclusionIncreased age, complicated with diabetes mellitus, decreased HGB, and elevated E/e' ratio are independent risk factors of long-term occurrence of cardiovascular events and cardiovascular death in patients undergoing long-term PD. The nomogram model constructed based on the above variables has good predictive value and clinical applicability, which can provide a reference for cardiovascular risk stratification and individualized intervention in long-term PD patients.
3.Circulating immunological transcriptomic profile identifies DDX3Y and USP9Y on the Y chromosome as promising biomarkers for predicting response to programmed death 1/programmed death ligand 1 blockade.
Liting YOU ; Zhaodan XIN ; Feifei NA ; Min CHEN ; Yang WEN ; Jin LI ; Jiajia SONG ; Ling BAI ; Jianzhao ZHAI ; Xiaohan ZHOU ; Binwu YING ; Juan ZHOU
Chinese Medical Journal 2025;138(3):364-366
5.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.
6.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.
7.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.
8.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.
9.Identification of terpenoid synthases family in Perilla frutescens and functional analysis of germacrene D synthase.
Pei-Na ZHOU ; Zai-Biao ZHU ; Lei XIONG ; Ying ZHANG ; Peng CHEN ; Huang-Jin TONG ; Cheng-Hao FEI
China Journal of Chinese Materia Medica 2025;50(10):2658-2673
Based on whole-genome identification of the TPS gene family in Perilla frutescens and screening, cloning, bioinformatics, and expression analysis of the synthetic enzyme for the insect-resistant component germacrene D, this study lays the foundation for understanding the biological function of the TPS gene family and the insect resistance mechanism in P. frutescens. This study used bioinformatics tools to identify the TPS gene family of P. frutescens based on its whole genome and predicted the physicochemical properties, systematic classification, and promoter cis-elements of the proteins. The relative content of germacrene D was detected in both normal and insect-infested leaves of P. frutescens, and the germacrene D synthase was screened and isolated. Gene cloning, bioinformatics analysis, and expression profiling were then performed. The results showed that a total of 99 TPS genes were identified in the genome, which were classified into the TPS-a, TPS-b, TPS-c, TPS-e/f, and TPS-g subfamilies. Conserved motif analysis showed that the TPS in P. frutescens has conserved structural characteristics within the same subfamily. Promoter cis-element analysis predicted the presence of light-responsive elements, multiple hormone-responsive elements, and stress-responsive elements in the TPS family of P. frutescens. Transcriptome data revealed that most of the TPS genes in P. frutescens were highly expressed in the leaves. GC-MS analysis showed that the relative content of germacrene D significantly increased in insect-damaged leaves, suggesting that it may act as an insect-resistant component. The germacrene D synthase gene was screened through homologous protein binding gene expression and was found to belong to the TPS-a subfamily, encoding a 64.89 kDa protein. This protein was hydrophilic, lacked a transmembrane structure and signal peptide, and was predominantly expressed in leaves, with significantly higher expression in insect-damaged leaves compared to normal leaves. In vitro expression results showed that germacrene D synthase tended to form inclusion bodies. Molecular docking showed that farnesyl pyrophosphate(FPP) fell into the active pocket of the protein and interacted strongly with six active sites. This study provides a foundation for further research on the biological functions of the TPS gene family in P. frutescens and the molecular mechanisms underlying its insect resistance.
Perilla frutescens/chemistry*
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Plant Proteins/chemistry*
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Multigene Family
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Sesquiterpenes, Germacrane/metabolism*
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Alkyl and Aryl Transferases/chemistry*
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Phylogeny
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Gene Expression Regulation, Plant
10.Polarized light microscopic mineral phase authentication and health risk assessment of raw and calcined fossil mineral Chinese medicinal material Draconis Os.
Yan-Qiong PAN ; Zheng LIU ; Li-Wen ZHENG ; Ying ZHANG ; Liu ZHOU ; Xi-Long QIAN ; Fang FANG ; Xiao WU ; Sheng-Jin LIU
China Journal of Chinese Materia Medica 2025;50(15):4238-4247
This study aims to investigate the polarized microscopic mineral phase characteristics, inorganic element content, and potential health risks associated with the intake of raw and calcined fossil mineral Chinese medicinal material Draconis Os. Microscopy was employed to observe the mineralogical characteristics of Draconis Os and compare the microscopic features and phase composition of raw and calcined Draconis Os under monochromatic and orthogonal polarized light. Inductively coupled plasma mass spectrometry(ICP-MS) was employed to determine the content of 30 inorganic elements. Health risk assessment was conducted by calculating the single pollution index(P_i), average daily intake of elements for adults(ADI), target hazard quotient(THQ), non-carcinogenic assessment method-hazard quotient(HQ), and the carcinogenic risk of elements(CR). The results indicated that under monochromatic polarized light, the Draconis Os powder sections exhibited light gray-brown to gray-brown irregular fragments, some with undulating textures that were slightly curved. Under crossed polarized light, they appeared dark gray, grayish-white, and yellowish-white. Clear apatite was visible in the ground sections of Draconis Os under crossed polarized light. P_i results indicated that Draconis Os samples were free from contamination and were of good quality. According to the maximum allowable limits of heavy metals stipulated in ISO Traditional Chinese Medicine: Determination of heavy metals in herbal medicines used in Traditional Chinese Medicine, ADI, THQ, HQ, and CR were taken as assessment indicators. Only the THQ value for As(arsenic) in raw Draconis Os was greater than 1, while the THQ values for other heavy metal elements in the Draconis Os samples were all less than 1. The study demonstrates that the primary mineral phase of raw and calcined Draconis Os is apatite, with some samples co-existing with calcite, which can serve as one of the means for quality control of Draconis Os. The elemental analysis results from ICP-MS provide scientific evidence for the safety assessment of Draconis Os, indicating that Draconis Os is safe in clinical application.
Drugs, Chinese Herbal/analysis*
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Risk Assessment
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Minerals/chemistry*
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Fossils
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Humans
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Drug Contamination
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Mass Spectrometry

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