Objective To research the distribution and the characteristics of the plasmid mediated quinolone resistant genes in Shewanella algae. Methods The qnr, qepA, aac(6')-Ib-cr genes were amplified by PCR, then the positive PCR products were sequenced to determine the gene type. The transferability of plasmid mediated quinolone resistance was ensured by conjugation experiment. MICs were measured by E-test. qnrA gene was mapped to plasmids to locate it. Results The qnrA gene were detected in the Shewanella algae, this is a newfound subgroup qnrA7, the GenBank accession no. was GQ463707, qnrB, qnrS,qnrC, qnrD, qepA and aac(6')-Ib-cr genes were not detected. qnrA7 reside in a plasmid about 33 kb, conjugation experiment was unsuccessful. The strain was susceptible to quinolones. Conclusion It deserves paying close attention to the report of an original qnrA subgroup in an isolate of water-borne species of Shewanella algae.

Objective:To systematically evaluate the influencing factors on unplanned shutdown of continuous blood purification, and to provide reference basis for the prevention of unplanned shutdown.Methods:The literatures related to the influencing factors of unplanned shutdown of continuous blood purification in CNKI, Wanfang Database, Chinese Biomedical Literature Database, Chinese Science and Technology Periodical Full-text Database, PubMed and Web of Science were searched.The retrieval time of Chinese database was from the establishment of the database to March 2021.English databases were searched from March 2016 to March 2021.Literature selection, quality evaluation and data extraction were independently conducted by two researchers, and Meta-analysis was performed by Stata 14.0 software.Results:A total of 11 studies were included, including 3 031 cases of continuous blood purification treatment and 1 412 cases of unplanned discontinuation.The combined OR value and 95% CI of all influencing factors were as follows: treatment mode 2.22 (1.06-4.62), blood flow velocity 0.91 (0.776-1.09), agitation 4.54 (2.33-8.86), ventilator 2.67 (1.63-4.38), transfusing blood products and fat milk 1.07 (0.34-3.36), one-time catheter success 0.26 (0.05-1.42), catheterization site (femoral vein vs.jugular vein) 2.24 (0.83-6.02). Conclusion:Unplanned deplaning is influenced by many factors.Treatment mode, agitation and ventilator use are the risk factors for unplanned deplaning.There is no correlation between blood flow velocity, transfusing blood products and fat milk, one-time catheterization success, catheterization site and unplanned deplaning.

Objective To construct and investigate the multi-leaf collimator (MLC) fault prediction model of Varian NovalisTx medical linear accelerator based on BP neural network.Methods The MLC fault data applied in clinical trial for 18 months were collected and analyzed.The total use time of accelerator,the quantity of patients per month,average daily working hours of accelerator,volume of RapidArc plans and time interval between accelerator maintenance were used as the input factors and the prediction of MLC fault frequency was considered as the output result.The BP neural network model of MLC fault prediction was realized by AMORE package of R language and the simulation results were validated.Results The model contained 3 layers of network to realize the input-output switch.There were 5 nodes in the input layer,13 nodes in the hide layer and 1 node in the output layer,respectively.The transfer function from the input layer to the hide layer selected the tansig function and purelin function was used from the hide layer to the output layer.The maximum time of training was pre-set as 150 in the designed model.Actually,111 times of training were performed.The pre-set error was 3％ and the actual error was 2.7％,which indicated good convergence.The simulation results of MLC fault applied in clinical trial for 18 months were similar to the actual data.Conclusions The BP neural network model realized by R language of MLC fault prediction can describe the mapping relationship between fault factors and fault frequency,which provides references for the understanding of accelerator fault and management of spare parts inventory.