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.

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.

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.

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.

Objective To investigate the distribution and antimicrobial resistance profiles of the clinical isolates from wound pus in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods All the bacterial strains were isolated from wound pus samples from 2015 to 2021.The isolates were identified according to conventional methods.Antimicrobial susceptibility test was conducted by disk diffusion method or commercial automated susceptibility testing systems according to CHINET-specified uniform protocol.The results are interpreted according to the Clinical and Laboratory Standards Institute (CLSI) breakpoints (2021 Edition).Results A total of 90856 bacterial strains were isolated from wound pus samples from 2015 to 2021,of which gram positive bacteria accounted for 36.0％ (32729/90856) and gram negative bacteria accounted for 64.0％ (58127/90856).The most common bacterial species were Escherichia coli,Staphylococcus aureus,Klebsiella pneumoniae,Pseudomonas aeruginosa,and Enterococcus.About 88.9％ of these strains were isolated from inpatients and 11.1％ from outpatients.The strains collected from surgery department and internal medicine accounted for (53.4±3.6)％ (49191/90856) and (9.6±1.0)％ (8960/90856) on average over the 7-year period.E.coli showed low level resistance to carbapenems (1.1％).The prevalence of ESBLs-producing E.coli was 51.1％.More than 35％ of the E.coli isolates were resistant to cefotaxime,ciprofloxacin,and trimethoprim-sulfamethoxazole.The prevalence of ESBLs-producing K.pneumoniae was 29.7％.The prevalence of imipenem-resistant and meropenem-resistant K.pneumoniae varied from 2015 to 2021,but reached the peak level (12.5％ and 12.7％) in 2020.However,other Enterobacterales species showed low resistance rates to carbapenems.The prevalence of ESBLs-producing Klebsiella oxytoca and Proteus was 18.3％ and 32.5％,respectively.About 13.1％ and 10.6％ of P.aeruginosa isolates were resistant to imipenem and meropenem,respectively.However,71.1％ and 72.4％ of A.baumannii isolates were resistant to imipenem and meropenem,respectively.The overall prevalence of MRSA was 22.7％ in wound pus samples over the 7-year period.Three vancomycin-resistant strains and 122 linezolid-resistant isolates were identified in Enterococcus faecalis.Thirty-one vancomycin-resistant strains and 11 linezolid-resistant strains were detected in Enterococcus faecium.Conclusions The overall prevalence of MRSA,vancomycin-resistant Enterococcus (VRE),linezolid-resistant Enterococcus (LRE),ESBLs-producing Enterobacterales,and carbapenem-resistant organisms (CRO) in the isolates from wound pus samples was relatively lower than the corresponding prevalence in the total clinical isolates collected in the CHINET program.This finding suggests that the antimicrobial resistance profile of bacterial isolates may vary with the source of clinical samples.Therefore,we should strengthen the antimicrobial resistance surveillance for the isolates from different sites of infection.

Objective To investigate the distribution and antimicrobial resistance profiles of the clinical isolates from wound pus in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods All the bacterial strains were isolated from wound pus samples from 2015 to 2021.The isolates were identified according to conventional methods.Antimicrobial susceptibility test was conducted by disk diffusion method or commercial automated susceptibility testing systems according to CHINET-specified uniform protocol.The results are interpreted according to the Clinical and Laboratory Standards Institute (CLSI) breakpoints (2021 Edition).Results A total of 90856 bacterial strains were isolated from wound pus samples from 2015 to 2021,of which gram positive bacteria accounted for 36.0％ (32729/90856) and gram negative bacteria accounted for 64.0％ (58127/90856).The most common bacterial species were Escherichia coli,Staphylococcus aureus,Klebsiella pneumoniae,Pseudomonas aeruginosa,and Enterococcus.About 88.9％ of these strains were isolated from inpatients and 11.1％ from outpatients.The strains collected from surgery department and internal medicine accounted for (53.4±3.6)％ (49191/90856) and (9.6±1.0)％ (8960/90856) on average over the 7-year period.E.coli showed low level resistance to carbapenems (1.1％).The prevalence of ESBLs-producing E.coli was 51.1％.More than 35％ of the E.coli isolates were resistant to cefotaxime,ciprofloxacin,and trimethoprim-sulfamethoxazole.The prevalence of ESBLs-producing K.pneumoniae was 29.7％.The prevalence of imipenem-resistant and meropenem-resistant K.pneumoniae varied from 2015 to 2021,but reached the peak level (12.5％ and 12.7％) in 2020.However,other Enterobacterales species showed low resistance rates to carbapenems.The prevalence of ESBLs-producing Klebsiella oxytoca and Proteus was 18.3％ and 32.5％,respectively.About 13.1％ and 10.6％ of P.aeruginosa isolates were resistant to imipenem and meropenem,respectively.However,71.1％ and 72.4％ of A.baumannii isolates were resistant to imipenem and meropenem,respectively.The overall prevalence of MRSA was 22.7％ in wound pus samples over the 7-year period.Three vancomycin-resistant strains and 122 linezolid-resistant isolates were identified in Enterococcus faecalis.Thirty-one vancomycin-resistant strains and 11 linezolid-resistant strains were detected in Enterococcus faecium.Conclusions The overall prevalence of MRSA,vancomycin-resistant Enterococcus (VRE),linezolid-resistant Enterococcus (LRE),ESBLs-producing Enterobacterales,and carbapenem-resistant organisms (CRO) in the isolates from wound pus samples was relatively lower than the corresponding prevalence in the total clinical isolates collected in the CHINET program.This finding suggests that the antimicrobial resistance profile of bacterial isolates may vary with the source of clinical samples.Therefore,we should strengthen the antimicrobial resistance surveillance for the isolates from different sites of infection.

OBJECTIVE To identify an d analyze chemical cons tituents of Pleione yunnanensis with origin of Pleione yunnanensis. METHODS UPLC-Q-Exactive-Plus-Orbitrap-MS was adopted. The determination was performed on Hyperdil GOLD column with mobile phase consisted of 0.1％ formic acid solution-0.1％ formic acid acetonitrile solution （gradient elution ）at the flow rate of 0.3 mL/min. The column temperature was set at 40 ℃，and sample size was 2 µL. The electrospray ion source was adopted，and the scanning range was m/z 100-1 500，and the scanning mode was positive and negative ion exchange mode of full scan+ddMS2. The structure of chemical constituents were determined by using Compound Discoverer 3.1 software，comparing with mzCloud，PubChem network database and OTCML ，on the basis of reference substance and published literatures. RESULTS & CONCLUSIONS A total of 42 chemical constituents were identified （positive ion mode has 24，negative ion mode has 27）， including 13 benzyl succinate glycosides （such as dactylorhin C ，coelovirin A ，militarine），4 phenol glycosides （such as adenosine ， guanosine，gastrodin），3 alkaloids（choline，betaine，berberine），and one flavonoid （nobiletin），7 aromatics（such as DL-lysine ， DL-arginine，DL-glutamine），one sugar （sucrose），3 benzenes（shancigusin H ，shancigusin H isomer ，batatasin Ⅲ）and 10 others （such as p-methoxybenzoic acid ，monomethyl dodecanedioate ，diphenylamine）. Glucose oxybenzyl and some small mole cules are easy to be lost in the cleavage of benzyl succinate glycosides；glycosyl is easy to be lost in the cleavage of phenol glycosides；the cleavage of alkaloids mainly manifest as the cleavage and loss of small molecular substituents ；demethyla- tion reaction is occurred in most flavonoids.

OBJECTIVE：To explore the metabolic charact eristics of Miao medicine Laportea bulbifera extract in isolated human intestinal flora. METHODS ：L. bulbifera was extracted with 70％ ethanol reflux extraction. After concentration，extraction with n-butanol and drying ，L. bulbifera extract was obtained. Taking 0.05 g/mL L. bulbifera extract 1 mL mixed with isolated human intestinal flora fluid 10 mL and cultured for 36 h in anaerobic environment （setting up blank control without drugs or human intestinal bacterial solution ），so as to simulate the metabolic process of the extract in human intestine. The metabolites were detected by UPLC-Q-TOF/MS. The determination was performed on Agilent Eclipse Plus C 18 RRHD column with mobile phase consisted of 0.01％ formic acid water solution- 0.01％ formic acid acetonitrile solution （gradient eluetion ）at the flow rate of 0.25 mL/min. The column temperature was set at 40 ℃，and the sample size was 1 µL. ESI detection was adopted and scanned by negative ion mode （ESI－）；the capillary voltage was 4.5 kV，the ion source temperature was 120 ℃，the collision energy was 15-32 V，and the scanning range was m/z 50-1 000. The “Strip”module of MassLynx V 4.1 software was used to analyze the differential chromatograms between the reaction solution and the blank control of L. bulbifera extract. Mass spectrum data and UNIFI so ftware were used to predict relative molecular weight and formula ；based on the information of substance control and related literature reports ， the structure and biotransformation pathway of L. bulbifera metabolites in isolated human intestinal flora were predicted and analyzed. RESULTS & CONCLUSIONS ： A total of 3 prototype ： products（rutin，quercetin，kaempferol-3-O-rutinoside）and 22metabolites （mainly the metabolites of quercetin ，mono- caffeoylquinic acid ，isoquercitrin，etc.） were detected after metabolized in isolated human intestinal flora. Itsbiotransformation pathway is phase Ⅰ reaction，which mainly consisted of reduction ，oxidation and hydrolysis.

OBJECTIVE：To estab lish a method that can comprehensively and rapidly analyze the chemical compositions of Miao medicine Caesalpinia decapetala，and to providing reference for quality control and pharmacodynamic material basis study of C. decapetala . METHODS ：UPLC-Q-TOF-MS/MS was adopted . The determination was performed on Agilent SB-C 18 column with mobile phase consisted of 0.1％ formic acid solution- 0.1％ formic acid acetonitrile （gradient elution ）at the flow rate of 0.25 mL/min. The column temperature was 30 ℃，and sample size was 2 µL. ESI source was applied in negative and positive scanning ion mode and data collection range of m/z 50-1 500. The capillary voltage was 4.5 kV，the atomizing gas （nitrogen）pressure was 1.2 Bar， the solvent removal gas was nitrogen ，the flow rate of solvent removal gas was 8 L/min and the solvent removal gas temperature was 200 ℃. Data Analysis 4.2 software was adopted to analyze fragment ion information of each peak ，and identify chemica l compositions on the basis of relevant literature and mass spectograms of reference substance. RESULTS ：Under positive ion mode ， 9 chemical compounds were identified ；peak 1，2，3，4，5，6，7，8，9 were catechin ，protohematoxylin B ，epicatechin，ethyl gallate，quercetin，luteolin，3-deoxy-hematoxylin chalcone ， isoliquiritigenin and linoleic acid. Under negative ion mode ， U1812403）， totally 21 peaks were confirmed and 13 compounds were identified；peak 3，4，5，6，7，8，9，10，11，12，13，15， 21 were catechins ， brevifolin carboxylic acid ， proto- hematoxylin B ，epicatechin，ethyl gallate ，epicatechin gallate ， quercetin，resveratrol，hematoxylin，luteolin，3-deoxy-hema- toxylin， isoliquiritigenin， linoleic acid. CONCLUSIONS UPLC-Q-TOF-MS/MS method is established successfully for analysis of chemical compositions in C. decapetala .

OBJECTIVE：To compar e the absorpt ion characteristics of gastrodin ，parishin A ，parishin B and parishin C of Gastrodia elata powder，and to explore the effect of particle size on intestinal absorption of above components. METHODS ：Based on everted intestinal sac model ，using accumulative absorption amount （Q）and absorption rate constant （Ka）as indexes ，UPLC-MS/MS method was used to determine the absorption of gastrodin ，parishin A ，parishin B and parishin C from different doses （2.5，5，10 g/L） of G. elata powder with different particle sizes （fine powder 146 μm，superfine powder 52 μm，ultrafine powder 37 μm）in different segments（duodenum，jejunum，ileum and colon ）. RESULTS ：Q and Ka of gastrodin and parishin B （intestinal segment ），Q（colon） and Ka（ileum and colon ）of parishin C in 2.5 g/L G. elata superfine powder ；Q and Ka of gastrodin （intestinal segment ），Q and Ka of parishin B （duodenum，jejunum，ileum）and Ka of parishin C （colon）in 2.5 g/L G. elata ultrafine powder ；Q of gastrodin （duodenum），Q of parishin A and parishin B （intestinal segment ）and Q of parishin C （duodenum，jejunum）in 5 g/L G. elata superfine powder ；Q（duodenum jejunum ，colon）and Ka（intestinal segment ）of gastrodin ，Q of parishin B （duodenum，ileum and colon）and Q of parishin C （duodenum，ileum）in 5 g/L G. elata ultrafine powder ；Q and Ka of parishin B （jejunum，ileum），Q of parishin C （jejunum，ileum）in 10 g/L G. elata superfine powder as well as Q（colon）and Ka（duodenum）of gastrodin ，Q （duodenum，ileum，colon）and Ka（duodenum，colon）of parishin B ，Q（duodenum，ileum）and Ka（duodenum）of parishin C in 10 g/L G. elata ultrafine powder were all increased significantly ，compared with the same dose of G. elata fine powder （P＜0.05 or P＜0.01）. Ka of parishin A （jejunum）and Q of parishin C （duodenum）in 2.5 g/L G. elata superfine powder ；Ka of parishin A （jejunum，ileum）， Q and Ka of parishin C （duodenum，jejunum）in 2.5 g/L G. elata ultrafine powder ；Ka of gastrodin （jejunum，ileum and colon ），Ka of parishin A （colon），Ka of parishin B （ileum）and Ka of parishin C （jejunum，ileum）in 5 g/L G. elata superfine powder ；Ka of gastrodin and parishin C （jejunum，ileum and colon ），Q（jejunum，colon）and Ka（colon）of parishin A ，Ka of parishin B （jejunum，ileum）in 5 g/L G. elata ultrafine powder ；Q and Ka of parishin A （ileum）in 10 g/L G. elata superfine powder ；Q（duodenum）and Ka（jejunum） of parishin A ，Ka of parishin C （jejunum）in 10 g/L G. elata ultrafine powder were decreased significantly ，compared with the same dose of G. elata fine powder （P＜0.05 or P＜0.01）. Q of gastrodin （colon），Q（colon）and Ka（ileum，colon）of parishin A ，Q and Ka of parishin B （jejunum，colon），Q and Ka of parishin C （ileum，colon）in 2.5 g/L G. elata fine powder ；Q and Ka of gastrodin （colon），Q（ileum，colon）and Ka（jejunum，ileum，colon）of parishin A ，Ka of parishin C （colon）in 2.5 g/L G. elata superfine powder；Q（colon）and Ka（jejunum，ileum，colon）of parishin A and C ，Q and Ka（ileum，colon）of parishin B in 2.5 g/L G. elata ultrafine powder ；Q and Ka of gastrodin ，parishin A and C （colon），Ka of parishin B （colon）in 5 g/L G. elata fine powder ；Q and Ka of gastrodin and parishin A （colon），Q and Ka of parishin C （jejunum，ileum，colon）in 5 g/L G. elata superfine powder ；Q and Ka of gastrodin（ileum，colon），Q of parishin A （jejunum，ileum，colon），Q and Ka of parishin B （jejunum，colon），Q（jejunum，colon） and Ka（jejunum，ileum，colon）of parishin C in 5 g/L G. elata ultrafine powder ；Q of gastrodin （colon），Q and Ka of parishin A ，B and C （jejunum，ileum，colon）in 10 g/L G. el ata fine powder ；Q of gastrodin （colon），Q and Ka of parishin A and C （jejunum， ileum，colon），Q and Ka of parishin B （colon）in 10 g/L G. elata superfine powder ；Q（colon）and Ka（jejunum，ileum，colon）of gastrodin，Q and Ka of parishin A and C （jejunum，ileum，colon），Q（jejunum，ileum，colon）and Ka（ileum，colon）of parishin B in 10 g/L G. elata ultrafine powder were decreased significantly ，compared with duodeum of the same group （P＜0.05）. Q and Ka of gastrodin（jejunum）in 2.5 g/L G. elata superfine pow