Bacterial biofilms(BF)are complex microbial communities formed by bacteria on living or abiotic surfaces.Their formation significantly enhances bacterial virulence and drug resistance and is associated with a high proportion of chronic bacterial infections,posing a serious threat to human health.The ability of traditional antibiotics and commonly used disinfectants to clear biofilms is limited,and an effective new strategy to treat BF is urgently needed.Bacteriophage,as a kind of virus that can infect and lyse bacteria,has high safety and specificity,and is considered as a promising alternative method for the treatment of BF.In this paper,the mechanism of bacteriophage anti-bacterial biofilm and the application strategies based on bacteriophage and its derivatives in the prevention and control of bacteriophage biofilm formation were reviewed,which provided new ideas for the development of efficient bacteriophage anti-bacterial biofilm methods.

Objective To establish a Nomogram model for assessing the risk of intestinal colonization by Carbapenem-Resistant Klebsiella pneumoniae(CRKP)to determine the specific probability of colonization and adopt individualized prevention strategies for the purpose of reducing the occurrence of colonization and secondary infection of neonatal CRKP.Methods A total of 187 neonates hospitalized between January 2021 and October 2022 and diagnosed with CRKP colonization by rectal swab/fecal culture as well drug sensitivity identification 48 h after admission were assigned to the CRKP group.Another 187 neonates without non-CRKP colonization during the same period were set as the non-CRKP group.All the data of the two groups were used for a retrospective analysis.The caret package in R 4.2.1 was used to randomly divide the 374 cases into the model group and validation group at a ratio of 3∶1.Then the glmnet package in R 4.2.1 was used to conduct a LASSO regression analysis over the data from the model group to determine the predictive factors for modeling and the rms software package was used to build a Nomogram model.The pROC and rms packages in R 4.2.1 were used to examine the data,analyzing the consistency indexes(Cindex),receiver operating characteristic curves(ROC),and area under the curves(AUC)and performing the internal and external validation of the efficacy of the Nomogram model via the calibration curves.Results LASSO regression analysis determined eight predictors from the 35 factors probably affecting neonatal CRKP colonization:gender,cesarean section,breastfeeding,nasogastric tube,enema,carbapenems,probiotics,and hospital stay.The Nomogram model constructed using these eight predictors as variables could predict CRKP colonization to a moderate extent,with the area under the ROC curve of 0.835 and 0.800 in the model and validation group,respectively.The Hos-mer-Lemeshow test showed that the predicted probability was highly consistent with the actual probability(the modeling group:P = 0.678>0.05;the validation group:P = 0.208>0.05),presenting a higher degree of fitting.Conclusion The Nomogram model containing such variables as gender,cesarean section,breastfeeding,nasogastric tube,enema,carbapenems,probiotics,and hospital stay is more effective in predicting the risk of neonatal CRKP colonization.Therefore,preventive measures should be individualized based on the colonization probability predicted by the Nomogram model in order to keep neonates from CRKP colonization and reduce the incidence of secondary CRKP infections among them.

Objective:To investigate the diagnostic value of immunoglobulin M (IgM) and immunoglobulin G(IgG) antibodies to 2019 Novel Coronavirus (2019-nCoV) in 2019-nCoV infection.Methods:This is a retrospective study. Serum samples were collected from 284 patients including outpatients and inpatients in the Renmin Hospital of Wuhan University from January 20 to February 17 in 2020. Among them 205 cases were 2019-nCoV infected patients, including 186 cases confirmed with nucleic acid test and 19 cases diagnosed by clinical symptoms and CT characteristics according to "the New Coronavirus Pneumonia Control Protocol (5th edition)" . A total of 79 subjects with other diseases but negative to 2019-nCoV infection were recruited as control group. Serum IgM and IgG antibodies to 2019-nCoV were measured with fully automated immunoassay technology for all subjects. Statistical significance between 2019-nCoV antibodies test and 2019-nCoV nucleic acid test was determined using the χ 2 tests. Results:The sensitivity of serum IgM and IgG antibodies to 2019-nCoV were 70.24%(144/205) and 96.10%(197/205) respectively and the specificity were 96.20%(76/79) and 92.41%(73/79) respectively. The positive and negative predictive values of 2019-nCoV antibodies were 95.63%(197/206) and 91.03% (71/78) respectively, and the positive and negative predictive values of 2019-nCoV nucleic acid test were 100%(186/186) and 80.61%(79/98) respectively. The total coincidence rate of diagnosing 2019-nCoV infection between antibody tests and nucleic acid test for 2019-nCoV were 88.03%(250/284).Conclusion:Joint detection of serum IgM and IgG antibodies to 2019-nCoV is an effective screening and diagnostic indicators for 2019-nCoV infection, and an effective complement to the false negative results to nucleic acid test.

In December, the outbreak of a novel coronavirus (2019-nCoV) in Wuhan, China, has attracted extensive global attention. On January 20, 2020, the Chinese health authorities upgraded the coronavirus to a Class B infectious disease in the Law of the People′s Republic of China on the Prevention and Treatment of Infectious Diseases, and considered it as Class A infectious diseases in disease control and prevention. On January 18, 2020, the 2019-nCoV nucleic acid detection test was listed as the diagnostic criteria in the "guidelines for diagnosis and treatment of pneumonia due to 2019-nCoV (Trial Version 2)" . Therefore, standardizing the operation process of the 2019-nCoV nucleic acid detection in clinical laboratories has become a top priority. It is of paramount importance to establish standard protocols for detection of the 2019-nCoV nucleic acids in clinical laboratories to improve the reliability of the results and ensure the biosafety of laboratory personnel.