Objective This study was to understand the structure characteristics of prophages in the genome of Enterococcus hirae R17,and also to analyze their interaction relationships with the host bacterium.Methods The gene distribution and gene encoding characteristics of prophages in the genome of Enterococcus hirae R17 were identified using the PHAST software.The virulence gene,antimicrobial resistance genes,and environmental resistance genes in the prophages were also analyzed.Results Three prophages were found on the chromosome of Enterococcus hirae,including two incomplete prophage elements (Prophage-1 and Prophage-2) and one complete prophage (Prophage-3).Some function genes of bacteria were found in the sequence of three prophages,including nucleotide transportation and metabolism related genes.One incomplete prophage carrying erythromycin-and bacitracin-resistance genes was identified in the plasmid,which suggested that prophage induced gene horizontal transfer caused erythromycin-and bacitracin-resistance of Enterococcus hirae R17.Conclusion This study laid a solid foundation for the diversity analysis of prophages of Enterococcus hirae.Prophages played an important role in promotion of antimicrobial resistance of enterococci.Scientists should pay more attention to the spread of antimicrobial resistance and pathogenicity induced by prophages.

BACKGROUND: Nasal mucosa fibroblasts are reported to involve in inflammation and wound repair of various nasal diseases by secreting a variety of cytokines and chemokines. Guinea pig is a most suitable experimental animal for the study of allergic diseases. OBJECTIVE: To investigate the effective methods of isolation, culture, purification and identification of guinea pig nasal mucosa fibroblasts. METHODS: Guinea pig nasal mucosa fibroblasts were isolated by collagenase digestion, and purified by differential velocity adherence. The morphology of fibroblasts was observed by inverted phase contrast microscope, fibroblasts were identified by vimentin immunocytochemical staining, and the cell growth was detected by MTT assay to draw the growth curve. RESULTS AND CONCLUSION: (1) Under inverted phase contrast microscope, there were cells with different shapes in the primary nasal mucosa fibroblasts, most of which showed spindle-like and applanate shape, and cells were scattered distribution in cluster. The purified fibroblasts were homogeneous, mainly were long spindle-shaped, and distributed in fish shoal-like and radial-like. (2) Immunocytochemical staining indicated that fibroblasts were positive for vimentin. (3) The cell growth curve appeared to be typical S-shaped. (4) To conclude, the isolated and cultured cells exhibit typical biological characteristics of fibroblasts.

BackgroundMental illness during pregnancy has become a major public health problem in China over the recent years， and depression is the most common psychological symptom during pregnancy. Current research efforts are directed towards the therapy on prenatal depression， whereas the construction of prediction model for prenatal depression risk has been little studied. ObjectiveTo construct a simple model for predicting the risk of prenatal depression， thus providing a valuable reference for the prevention of maternal depression during pregnancy. MethodsA total of 803 pregnant women attending three hospitals in Nanchong city were consecutively recruited from May 2021 to February 2022. A self-administered questionnaire was developed for the assessment of social demographic variables， obstetrical and general medical indexes and psychological status of all participants， and Self-rating Depression Scale （SDS） was utilized to screen for the presence of maternal depression. Subjects were randomly assigned into modelling group （n=635） and validation group （n=168） at the ratio of 8∶2 under simple random sampling with replacement. The candidate risk factors of maternal depression during pregnancy were screened using binary Logistic regression analysis， and the predictive model was constructed. Then the performance of the predictive model was validated using receiver operating characteristics （ROC） curve. Results① Lack of companionship （β=-0.692， OR=0.501， 95% CI： 0.289~0.868）， low mood during the last menstrual period （β=-1.510， OR=0.221， 95% CI： 0.074~0.656）， emotional stress during the last menstrual period （β=-1.082， OR=0.339， 95% CI： 0.135~0.853）， unsatisfactory relationship between mother-in-law and daughter-in-law （β=-1.228， OR=0.293， 95% CI： 0.141~0.609）， and indifferent generally relationship between mother-in-law and daughter-in-law （β=-0.831， OR=0.436， 95% CI： 0.260~0.730） were risk factors for prenatal depression in pregnant women （P<0.05 or 0.01）. ② Model for predicting the prenatal depression risk yielded an area under curve （AUC） of 0.698 （95% CI： 0.646~0.749）， the maximum Youden index was 0.357 in modelling group with the sensitivity and specificity was 0.606 and 0.751， and an AUC of 0.672 （95% CI： 0.576~0.767） and maximum Youden index of 0.263 in validation group with the sensitivity and specificity of 0.556 and 0.707. ConclusionThe simple model constructed in this study has good discriminant validity in predicting of the risk of prenatal depression. ［Funded by Nanchong Social Science Research Project of the 14th Five-Year Plan （number， NC21B165）］