1.Establishment of detection method for Chlamydophila abortus by using SYBR green real-time PCR and determination of bacterial load in mice
Zhi-Jun ZHANG ; Zhao-Cai LI ; Zhong-Zi LOU ; Ji-Zhang ZHOU
Chinese Journal of Zoonoses 2018;34(3):224-229
We established a fluorescent quantitative PCR (qPCR)method for the detection of Chlamydophila abortus (C. abortus),and replaced the method of smear staining which has subjective influence on the detection of C.abortus inactivated vaccine titer.According to the conserved sequence of the large cysteine-rich periplasmic protein(envB)of C.abortus,a specific primer was designed and the EnvB-PMD19T positive plasmid was used as the reference standard,optimization condition,sensi-tivity assay,specificity assay,repeatability assay and the bacteria loads of organs from mouse have been done.The results showed that the standard curve established with positive plasmid had a liner response from 1×102copies/μL to 1×106copies/μL with the correlation coefficient of 97%,sensitive for detecting C.abortus with the detection limit of 10 copies/μL,and re-peatable and stable with the coefficients of variation less than 2%.According to the result,the established method can detect the bacteria loads in organ of mouse,which provide a reliable method for evaluation of inactivated C.abortus vaccine.
2.Epidemiologic characteristics of influenza in China, from 2001 to 2003.
Jing ZHANG ; Wei-Zhong YANG ; Yuan-Ji GUO ; Hong XU ; Ye ZHANG ; Zi LI ; Jun-Feng GUO ; Min WANG ; Wen-Jie WANG ; Zheng-Mao LI ; Xin-Hua SUN ; Dong-Lou XIAO
Chinese Journal of Epidemiology 2004;25(6):461-465
OBJECTIVETo understand the epidemiologic characters of influenza in China from 2001 to 2003.
METHODSData of outpatient visits for influenza-like illness (ILI) each week and outbreaks of influenza were collected through National Influenza Surveillance Network, which includes 11 northern and 12 southern provinces of China. Samples were collected in the outpatients of ILI from 2001 to 2003 and influenza viruses were isolated and identified.
RESULTSEpidemiological and laboratory surveillance data showed that the annual seasonality of influenza epidemic was clear. The peak of epidemic of influenza in northern areas was in winter season, during December to January. However, there were three peaks distributed to Spring (Apr.-May.), Summer (Jun.-Aug.) and Winter (Dec.-Jan.) seasons in the southern areas. In the peak months, the number of ILI visits per day and per surveillance hospital had increased two-fold in northern and by 37% in southern China. The baseline of percentages for ILI visits, which calculated with 75th percentiles (P75), was 13.68% in the north and 13.08% in southern China. The age distribution of ILI was related to seasonal types of influenza. When the predominated strain of the season was influenza B virus, the ratio of the ILI visits younger than 15 year-old, increased obviously. When the predominated stains became influenza A virus, the ratio of patient visits for ILI aged over 25 year-old increased. Of 63 outbreaks of influenza, 92% of them occurred at primary and middle schools and usually occurred in May (32%). The type of strains usually changed around June.
CONCLUSIONThe quality of national influenza surveillance system is reliable since it was matched between percentages of ILI visits and rates of influenza virus isolation. The different epidemiologic characteristics in north and south of China was noticed. Peak in spring was shown in southern area and which called for more analysis. The change of the types of strains in the outbreaks during April to June in the southern China could provide data for better understanding on the trend of epidemics in the next season.
Adolescent ; Adult ; Aged ; Aged, 80 and over ; Child ; Child, Preschool ; China ; epidemiology ; Female ; Humans ; Infant ; Influenza A virus ; Influenza B virus ; Influenza Vaccines ; administration & dosage ; Influenza, Human ; epidemiology ; prevention & control ; virology ; Male ; Middle Aged ; Population Surveillance ; Seasons ; Vaccination
3.Genetic variation of the 8-kDa glycoprotein family from Echinococcus granulosus, Taenia multiceps and Taenia hydatigena.
Wan-Zhong JIA ; Hong-Bin YAN ; Zhong-Zi LOU ; Xing-Wei NI ; Hong-Xia LIU ; Hong-Min LI ; Ai-Jiang GUO ; Bao-Quan FU
Chinese Medical Journal 2011;124(18):2849-2856
BACKGROUNDEchinococcosis, coenurosis and cysticercosis are debilitating diseases which prevail in China. Immunological diagnosis of metacestodosis is important in disease control. The 8-kDa glycoproteins from taeniid cestodes have successfully been used for diagnosis of human cysticercosis in immunological assays. The aim of the present study was to investigate genetic variations and phylogenetic relationships of the 8-kDa proteins for evaluating the possibility of utilizing these proteins as diagnostic antigens for other metacestode infections.
METHODSThe genes and complementary DNAs (cDNAs) encoding the 8-kDa proteins from Echinococcus (E.) granulosus, Taenia (T.) multiceps and T. hydatigena were amplified using PCR method. Their amplicons were cloned into the vector pMD18 and the positive clones were sequenced. Sequence data were analyzed with the SeqMan program, and sequence homology searches were performed using the BLAST program. Alignments were conducted using the ClustalX program, and the phylogenetic analyses were performed with the Protein Sequences Program and the Puzzle Program using the Neighbor-joining method.
RESULTSFifteen, 18 and 22 different genomic DNA sequences were identified as members of the 8-kDa protein gene family from E. granulosus, T. multiceps and T. hydatigena, respectively. Eight, four and six different cDNA clones respectively from E. granulosus, T. multiceps and T. hydatigena were characterized. Analysis of these sequences revealed 54 unique 8-kDa protein sequences. Phylogenetic trees demonstrated that the taeniid 8-kDa proteins are clustered into eight clades at least: Ts18, Ts14, TsRS1, TsRS2, T8kDa-1, T8kDa-2, T8kDa-3 and T8kDa-4.
CONCLUSIONWe found that the gene family encoding for the taeniid 8-kDa antigens is comprised of many members with high diversity, which will provide molecular evidence for cross-reaction or specific reaction among metacestode infections and may contribute to the development of promising immunological methods for diagnosis of metacestodosis.
Amino Acid Sequence ; Animals ; DNA, Helminth ; genetics ; Echinococcus granulosus ; genetics ; metabolism ; Genetic Variation ; genetics ; Glycoproteins ; chemistry ; classification ; genetics ; Helminth Proteins ; chemistry ; classification ; genetics ; Molecular Sequence Data ; Phylogeny ; Sequence Homology, Amino Acid ; Taenia ; genetics ; metabolism
4.Gingival thickness assessment of gingival recession teeth.
Zi Yuan CHEN ; Jin Sheng ZHONG ; Xiang Ying OUYANG ; Shuang Ying ZHOU ; Ying XIE ; Xin Zhe LOU
Journal of Peking University(Health Sciences) 2020;52(2):339-345
OBJECTIVE:
To evaluate the gingival thickness and gingival biotype of gingival recession teeth of Chinese population.
METHODS:
A total of 112 non-molar teeth with gingival recession in 34 patients were included. Direct measurement, cone-beam computerized tomography (CBCT) measurement and periodontal probe method were used to evaluate gingival thickness and biotype. Gingival thickness was measured at 2 mm apical to the gingival margin. Direct measurement was performed with a caliper of 0.01 mm resolution and anesthesia needles attached to silicone disk stops. Gingival biotype was assessed by sulcus probing, if the periodontal probe was visible through the gingival tissue, the gingival biotype was thin; If not visible, the gingival biotype was thick. The differences of gingival thickness among different gingival biotype, tooth site and gingival recession type were analyzed respectively. Besides, the results of CBCT measurement was analyzed compared with the direct measurement.
RESULTS:
The average gingival thickness of non-molar recession teeth was (1.17±0.41) mm. The average gingival thickness of thick and thin biotype group were (1.38±0.4) mm and (0.97±0.30) mm, respectively, with statistically significant difference (P<0.001). The median of gingival thickness was 1.1 mm. Using 1.1 mm as the cut-off value of thick and thin gingival thickness group, the results matched well with the gingival biotype classification results by periodontal probe method (P=1.000). The average gingival thickness of maxillary teeth was significantly thicker than that of the mandibular teeth. They were (1.39±3.44) mm and (1.01±0.31) mm, respectively (P<0.001). The mean gingival thickness of MillerI, II and III degree gingival recession teeth were (1.15±0.34) mm, (0.83±0.17) mm and (1.26±0.56) mm, respectively, without statistically significant difference (P=0.205). The gingival thickness measurement results between CBCT method and direct measurement were without statistically significant difference (P=0.206).
CONCLUSION
In the non-molar gingival recession teeth, the cut-off value of gingival thickness to classify thick and thin biotype of Chinese population was 1.1 mm. The average gingival thickness of the maxillary teeth was significantly thicker than that of the mandibular teeth. Besides, CBCT measurement was an accuracy method for evaluating facial gingival thickness.
Cone-Beam Computed Tomography
;
Gingiva
;
Gingival Recession
;
Humans
;
Incisor
;
Maxilla