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AIM: To determine the contents of protocatechuic acid,peoniflorin,coumarin,cinnamic acid,cinnamaldehyde and glycyrrhizic acid in categorized formulas about Guizhi Decoction (Ramulus cinnamoni,Radix paeoniae alba,Rhizoma zingiberis recens,Radix et Rhizoma glycyrrhizae and Fructus jujubae) by HPLC.METHODS: The gradient elution mode was applied in chromatographic separation.The C18 column was used with the mobile phase of 0.05% phosphoric acid-acetonitrile,flow rate was at 1.0 mL/min,detection wavelength at 230 nm and 254 nm,and the column temperature was at 30 ℃.The contents of the above-mentioned six constituents were determined in Guizhi Decoction,Guizhi Decoction plus Ramulus cinnamoni and Guizhi Decoction plus Radix paeoniae alba,respectively.The differences among all combinations were tested by one-way analysis of variance using SPSS software.RESULTS: The concentrations of the above-mentioned six constituents in different decoctions were simultaneously determined by HPLC and the linear equations of six constituents were established.Compared with Ramulus Cinnamomi alone,cinnamic acid content decreased and protocatechuic acid content increased in categorized formulas about Guizhi Decoctions significantly,but then coumarin content increased in Guizhi Decoction and Guizhi Decoction plus Radix paeoniae alba.Compared with Radix Paeoniae Alba alone,peoniflorin content decreased in categorized formulas about Guizhi Decoctions significantly.Compared with Radix et Rhizoma Glycyrrhiza alone,glycyrrhizic acid content increased in categorized formulas about Guizhi Decoctions significantly.CONCLUSION:The methods are accurate,reproducible and suitable for determineation of the contents of six constituents in categorized formulas about Guizhi Decoctions,Results show that the contents change with different decoctions.

OBJECTIVE To examine the prevalence and trends of drug resistance of nontuberculous mycobacteria(NTM)in Shanghai.METHODS All NTM strains isolated between 1998 and 2004 in Shanghai were identified with conventional biochemical tests.Antimicrobial susceptibility test for all NTM was performed by standard absolute concentration method.RESULTS The prevalence rate was determined as 1.49%,1.17%,1.98%,2.46%,2.66%,2.72% and 3.0% among mycobacteria culture positive patients per year in 1998,1999,2000,2001,2002,2003,and in 2004,respectively.These data indicated the prevalence rate has continuously increased.Distribution of NTM isolates was Group Ⅰ18.7%,Group Ⅱ 5.1%,Group Ⅲ 25.1%,and Group Ⅳ 51.1% accordingly.Group Ⅳ rapidly growing NTM accounted for majority of them.Most of NTM showed high drug resistance to general antituberculotic drug.In particular Group Ⅳ Mycobacterium chelonae and M.fortuitum appeared multi-drug resistance.CONCLUSIONS The prevalence rate of NTM in Shanghai shows increased tendency.Most of NTM isolates are Group Ⅳ rapidly growing NTM.NTM shows high drug resistance to first line antituberculotic substance.

Objective To determine the serum IgM and IgG antibody levels post-COVID-19 vaccination， and provide scientific evidence for COVID-19 antibody response after vaccination. Methods A total of 980 healthy persons were included in Kunming Third People’s Hospital from July through August， 2021， which had been vaccinated with COVID-19 vaccines and then tested for anti-SARS-CoV-2 IgM and IgG antibodies. Results After the COVID-19 vaccination， 469 persons （positive rate， 47.86%） were positive for anti-IgG antibody. Of them， 75 were males with （positive rate， 39.06%）， and the average IgG level was 0.618 （0.180， 2.526） AU·mL^-1［M（Q₁，Q₃）］； 394 were females （50.00%）， and the IgG level was 0.999 （0.305， 3.334） AU·mL^-1. In addition， 53 persons （5.41%） were anti-IgM antibody positive. Of them， 14 were males （positive rate， 7.29%）， and the average IgM level was 0.057 （0.026， 0.195） AU·mL^-1； 39 were females （4.95%）， and the IgM level was 0.047 （0.027， 0.110） AU·mL^-1. The positive rate of anti-IgG antibody was highest in those aged ≤30 years， which was 51.02% in male （n=25） and 55.88% in female （n=133）. The anti-IgG response differed significantly by gender （χ²=7.401， D=0.135 1， P<0.05）， whereas the anti-IgM response was not significantly different （χ²=1.656， P>0.05）. Among the age groups， anti-IgG antibody level was higher in those aged ≤30 and 51-70 years， with 158 （55.05%） and 122 （52.36%） persons， respectively； the average antibody level was 1.209 （0.426， 4.386） AU·mL^-1 and 1.074 （0.191， 7.670） AU·mL^-1， respectively. The differences in the positive rates of IgG and IgM antibodies and the levels of IgG antibodies among different age groups were statistically significant （P<0.05）. Using Kruskal-Wallis test and Spearman correlation analysis， it showed a high correlation between the IgG and IgM antibodies （r=0.836 4， H=64.82， 20.09， P<0.05）. Conclusion The Anti-SARS-CoV-2 IgG antibody remains high six months post-COVID-19 vaccination， while anti-IgM antibody is low. The IgM and IgG response are higher in the young and elderly. The response differs by gender and age， demonstrating a correlation.