1.Herbal Textual Research on Quisqualis Fructus in Famous Classical Formulas
Xiuping WEN ; Shiying CHEN ; Ying TAN ; Guanwen ZHENG ; Huilong XU ; Wen XU ; Chengzi YANG ; Zehao HUANG ; Yu LIN ; Zhilai ZHAN
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):225-237
This article systematically analyzed the historical evolution of the origin, scientific name, producing area, quality evaluation, harvesting and processing, and other aspects of Quisqualis Fructus by consulting the ancient materia medica, medical books, prescription books, local literature and combining with the modern literature and standards, summarized and explored the development rules of its medicinal properties and efficacy along with their underlying causes, in order to provide support for the development and utilization of famous classical formulas containing this herb. According to the textual research, Shijunzi was first recorded as Liuqiuzi in Nanfang Caomuzhuang of the Jin dynasty, and the name of Shijunzi was first used in Kaibao Bencao of the Song dynasty, which has been consistently used throughout subsequent dynasties, and there were also aliases such as Junziren, Sijunzi, and Dujilizi. The mainstream source of Quisqualis Fructus used in the past dynasties has been the dried mature fruits of Quisqualis indica, a plant belonging to the family Combretaceae. In modern times, its variety Q. indica var. villosa has also been recorded as the medicinal material of Quisqualis Fructus. In 2007, the Flora of China(English edition) designated Q. indica var. villosa as a synonym of Q. indica. Today, the accepted name of Shijunzi is updated to Combretum indicum. According to ancient herbal records, the producing areas of Quisqualis Fructus were Guangdong, Hong Kong, Macao, Guangxi, Hainan, Sichuan and Fujian, and then gradually expanded to Yunnan, Taiwan, Jiangxi and Guizhou. Since the Song dynasty, two major production regions have gradually emerged in Sichuan, Chongqing and Fujian. Currently, it is primarily cultivated in Chongqing, Guangxi and other areas, with Chongqing yielding the highest output. Since modern times, superior quality has been defined by large size, a purple-black surface, plump grains, and a yellowish-white kernel. According to ancient herbal records, the harvesting period of Quisqualis Fructus was the July and August of the lunar calendar, mostly used raw after shelling or with the shell intact, it underwent processing methods such as cleaning, slicing, mixing, steaming, roasting, stewing, and frying. Currently, the harvesting period is autumn, followed by sun-drying or low-heat drying, with processing methods including cleaning, stir-frying, and stewing. In ancient and modern literature, the records of the properties, functions and indications of Quisqualis Fructus are basically the same, that is, sweet in taste, warm in nature, predominantly non-toxic, belonging to the spleen and stomach meridians. It possesses effects of insecticide, decontamination and invigorating spleen for ascariasis, enterobiasis, abdominal pain due to worm accumulation and infantile malnutrition.The contraindications for use primarily include avoiding consumption by individuals without parasitic infestations, limiting use for those with spleen-stomach deficiency-cold, refraining from drinking hot tea during medication, and avoiding excessive intake. Based on the textual research, it is suggested that the dried mature fruits of Q. indica should be used as the medicinal material for the development of famous classical formulas containing Quisqualis Fructus. Processing methods may be chosen according to prescription requirements, and the raw products is recommended for medicinal use if not specified.
2.Reflections on Status Quo and Development Pathways of Traditional Chinese Medicine Technology Transfer in Context of Digital-intelligent Transformation
Jie ZHANG ; Jing XU ; Guangwei ZHENG ; Huayu ZHANG ; Chang LIU ; Xiaoxiao WEN ; Xishui PAN ; Bin WANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(4):235-240
As a distinctive resource of Chinese civilization, traditional Chinese medicine (TCM) technology transfer faces significant opportunities under the background of digital and intelligent transformation, while also being constrained by unique challenges such as the complexity of its theoretical system, lengthy industrial chains, and multidimensional policy restrictions, resulting in a "high-value-high-threshold" paradox. At present, TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma, i.e., unwillingness to transfer, inability to transfer, and lack of capacity to transfer. Specifically, the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements, unclear ownership and compliance risks suppress innovation incentives, and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems, blockchain-based traceability, and AI diagnostic models, the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization, promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example, a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements, while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization, reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead, through the construction of national-level databases, the cultivation of interdisciplinary talent, and the mutual recognition of international standards, a new paradigm of "scientific intelligent manufacturing" can be formed, providing systematic solutions for the modernization of TCM and global health governance.
3.Effectiveness Evaluation of Pre-Service Training for Laboratory Animal Practitioners Based on the "Three-Separation" Model
Fuli WEN ; Yongjun XU ; Yunfeng FU ; Laien XUE ; Linlin CUI ; Junzhu WANG ; Jun LU ; Heping ZHENG
Laboratory Animal and Comparative Medicine 2026;46(5):771-778
ObjectiveTo summarize the application experience of the "Three-Separation" model in the pre-service training of laboratory animal practitioners and scientifically evaluate its training effectiveness. MethodsA retrospective analysis was conducted on 8 009 practitioners who participated in pre-service training at the Fujian Provincial Laboratory Animal Training Base from January 2010 to December 2025. Among them, 1 250 trainees from January 2010 to December 2017 were included in the control group (traditional training model), and 6 759 trainees from January 2018 to December 2025 were included in the evaluation group ("Three-Separation" model, based on separating job requirements, differentiating exam content, and categorizing exam methods). Meanwhile, a questionnaire survey was conducted to evaluate training effectiveness, yielding 1 624 valid questionnaires (585 from the control group and 1 039 from the evaluation group). The "Three-Separation" model simultaneously optimized fee structures to improve affordability and inclusiveness. The comprehensive competencies and training satisfaction of the two groups after training were compared and analyzed using the independent sample t-test, χ² test, and Wilcoxon rank-sum test. ResultsThe overall satisfaction rate of the evaluation group was 92.49% (961/1 039), significantly higher than that of the control group (77.78%, 455/585), with a highly significant difference (χ²=72.50, P<0.001). The evaluation group showed a more favorable distribution of positive, neutral, and negative ratings in dimensions such as course pertinence, time flexibility, assessment rationality, and reasonableness of fees, and the positive rating rates were highly significantly higher than those in the control group (P<0.001). The comprehensive pass rate of the evaluation group (95.53%) was significantly higher than that of the control group (86.24%), with a highly significant difference (P<0.001). ConclusionThe scientific application of the "Three-Separation" model can accurately match the competency requirements of different positions, optimize the training and assessment system, reduce participation barriers by making training fees more affordable and accessible, effectively improve the comprehensive quality and training satisfaction of laboratory animal practitioners, achieve better teaching outcomes, and provide replicable and promotable practical references for the standardized upgrading of the training system in the laboratory animal industry and other industries.
4.Predictive value of dual-modality ultrasound combined with S-Detect for cervical lymph node metastasis in papillary thyroid carcinoma
Zelin XU ; Zhenhao ZHENG ; Yaqian DENG ; Guanming ZENG ; Tingting DU ; Peishan ZHU ; Wen LIU ; Jun LI
The Journal of Practical Medicine 2025;41(16):2581-2589
Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835~0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.
5.Identifying High-Risk Areas for Type 2 Diabetes Mellitus Mortality in Guangdong, China: Spatiotemporal Clustering and Socioenvironmental Determinants.
Hai Ming LUO ; Wen Biao HU ; Yan Jun XU ; Xue Yan ZHENG ; Qun HE ; Lu LYU ; Rui Lin MENG ; Xiao Jun XU ; Fei ZOU
Biomedical and Environmental Sciences 2025;38(5):585-597
OBJECTIVE:
This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies.
METHODS:
Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model.
RESULTS:
A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide.
CONCLUSION
High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology*
;
China/epidemiology*
;
Humans
;
Risk Factors
;
Spatio-Temporal Analysis
;
Air Pollutants/analysis*
;
Socioeconomic Factors
;
Bayes Theorem
;
Female
;
Male
;
Middle Aged
6.Spatial-temporal Dynamics of Tuberculosis and Its Association with Meteorological Factors and Air Pollution in Shaanxi Province, China.
Heng Liang LYU ; Xi Hao LIU ; Hui CHEN ; Xue Li ZHANG ; Feng LIU ; Zi Tong ZHENG ; Hong Wei ZHANG ; Yuan Yong XU ; Wen Yi ZHANG
Biomedical and Environmental Sciences 2025;38(7):867-872
7.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
8.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
9.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
10.Model establishment for quantitative analysis of saponins of Paris polyphylla by near-infrared spectroscopy
Ping XU ; Qi MI ; Wen-xiu LUO ; You LU ; Meng-wen YU ; Xuan ZHANG ; Guo-wei ZHENG ; Chang-gui QIU ; Jia CHEN
Chinese Traditional Patent Medicine 2025;47(4):1069-1076
AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.

Result Analysis
Print
Save
E-mail