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Objective To discuss the application value of modified Hodge test(MHT) for screening carbapenemase-producing Enterobacteriaceae.Methods The 24 Enterobacteriaceae reduced susceptibility to carbapenems were detected by MHT.At the same time,polymerase chain reaction(PCR) was used to detect carbapenemase genes of KPC,NDM,IMP,SIM and VIM.PCR products were sequenced and the results were compared with the sequences of Gen Bank database.Comprehensive analysis the application value of MHT and PCR to detect carbapenemase.Results Among these 24 strains,13 stains appeared to produce carbapenemase by MHT,5 positive strains were found to carry carbapenemase genes by PCR.By comparing with the sequences of Gen Bank database 1 strain were confirmed to KPC-2 and 4 strains were confirmed to IMP-4.We found that 4 strains of Enterobacteriaceae,detected carbapenemase by MHT and PCR at the same time.9 strains of MHT were positive,but we couldn′t detect the carbapenemase genes.1 strain of MHT was negative,but carbapenemase gene was found in the strain.Conclusion The value of MHT to screen carbapenemase-producing Enterobacteriaceae is necessary to further study.
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Objective To know the contents and changes situation of trace elements among children aged 0-6 years old in Chengdu are‐a .Methods The BH5100T atomic absorption spectrometry was adopted to detect the levels of trace elements Cu ,Zn ,Ca ,Mg ,Fe in 786 children aged 0-6 years old undergoing the physical examination in our hospital from April 2015 to November 2015 .The detection results were statistically analyzed .Results The deficiency rates of Cu ,Zn ,Ca ,Mg and Fe in Chengdu area were 0 .4% ,5 .0% ,18 .1% ,9 .5% and 8 .3% respectively ,in which the deficiency rates of Ca in children aged <1 ,1 ,2 ,3 ,≥ 4 years old were 47 .4% ,27 .5% ,12 .6% ,9 .9% and 11 .9% respectively ,indicating that the Ca deficiency rate in children < 1 years old was higher .The Ca deficiency rate had statistical differ‐ence among different age groups(P<0 .05) ,and there were no statistically significant differences in the deficiency rates of several trace ele‐ments among different age groups of male and female children .Conclusion The abnormality rate of trace elements among children aged 0-6 years old in Chengdu area is higher ,in which the Ca deficiency rate is highest ,meanwhile the Mg and Fe were lack too .The trace element content in children is closely related with the feeding habit .The 0-6 years old children in this area should pay attention to the supplement of trace elements ,especially supplement of Ca ,meanw hile breastfeeding is advocated .
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Objective To investigate the mechanism of one carbapenems resistant Raoultella planticola( R.planticola) isolate.Methods This is an experimental study.R.planticola was isolated from a patient′s drainage fluid from orthopedic department in November 2010 in Sichuan Provincial People′s Hospital.Minimum inhibitory concentration of R.planticola to 13 antibiotics was determined by using the agar dilution method.Modified Hodge test was used to detect carbapenemase .EDTA synergistic test was performed to research metallo-beta-lactamase.The genes coded the β-lactamase were amplified by polymerase chain reaction ( PCR ) , including class A carbapenemase ( KPC ) , class B carbapenemases (NDM, IMP, VIM, SIM), extended spectrum beta-lactamases[ESBL(CTX, TEM, SHV)], and AmpCβ-lactamases ( FOX, EBC, ACC, DHA, CIT, MOX).Results The susceptibility test showed that R.planticola was resistant to 9 antibiotics.MIC value of meropenem for R.planticola was up to 32 mg/L.R.planticola kept intermediary to imipenem , whereas it was susceptible to cefepime , amikacin and polymyxin B.Modified Hodge test and EDTA synergistic test were positive in R.planticola.Class B carbapenemase (IMP) gene and two extended spectrum β-lactamases(CTX, SHV) genes were positive by PCR.The genes were conformed as IMP-4, CTX-M3 and SHV-12 by sequencing and compared with GenBank.Other resistant genes were negative.Conclusion IMP-4 was identified in R.planticola, the combined produce IMP-4 and ESBLs might be the main mechanism of R.planticola resistant to carbapenems.
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Objective To establish protein fingerprints of common bacteria in clinics and to lay a foundation for rapid identification of bacteria.Methods Strains of Escherichia coli,Klebsiella pneumoniae,Pseudomonas aeruginosa and Staphylococcus aureus were detected by surface enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS).Stable expression protein peaks were screened and the data was input into the self-constructed Fingerwave software for identification of target bacteria by protein fingerprint comparison.Two hundred and fifty-six clinical isolates,including E.coli,K.pneumoniae,P.aeruginosa and S.aureus were detected and the data was compared with constructed database to evaluate its diagnostic value.Results The protein fingerprints including four common bacteia was used to identify the target bacteria with identification rate of 93.1％ (54/58) for E.coli,87.2％ (75/86) for K.pneumoniae,96.2％ (60/63) for P.aeruginosa and 96.2％ (51/53) for S.aureus,respectively.Conclusion Common bacteria can be rapidly identified by using the protein fingerprint comparison,which provides a powerful tool for bacterial identification.
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Objective To establish protein fingerprinting identification model of Pseudomonas aeruginosa (P. aeruginosa) and to lay a foundation for rapid identification of P. aeruginosa by proteinchip golden array. Methods Sixty-four P. aeruginosa and one hundred and ninety-nine control bacteria identified in our laboratory were collected and divided into training and testing group. Surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) and proteinchip golden array were used to detect the protein profiling of the bacteria. Data were automatically collected by Ciphergen Proteinchip Software and protein markers of P. aeruginosa were screened by BioMarker Wizard Software. Classification tree model was developed and validated by BioMarker Patterns Software. The model was blindly tested with twenty-nine P. aeruginosa and sixty-four control bacteria. Results Eighty protein peaks were detected between 3000 and 20 000, among which fifty-eight ones showed significantly difference between P. aeruginosa and the control bacteria (P＜0.01). By BioMarker Patterns Software, one protein peak ( M/Z at 14 045.2) was chosen to develop a classification tree model. The results exhibited with sensitivity of 96. 55% and specificity of 100%. Conclusion Proteinchip golden array has the potential for rapid identification of P. aeruginosa.