Objective To investigate the distribution and antibiotic resistance profile of clinical isolates in the First Hospital of Qiqihar during 2015.Methods Antimicrobial susceptibility test was carried out according to a unified protocol using automated system from January 1,2015 to December 31,2015.The results were analyzed with WHONET 5.6 software according to the 2014 breakpoints of Clinical and Laboratory Standards Institute.Results A total of 5 162 clinical isolates were collected,of which 28.1％ (1 450/5 162) were gram-positive cocci and 71.9％ (3 712/5 162) were gram-negative bacilli.About 36.5％ (255/698) ofS.aureus isolates and 81.4％ (180/221) of coagulase negative Staphylococcus isolates were resistant to methicillin.No S.aureus and coagulase negative Staphylococcus isolate were found resistant to vancomycin or linezolid.Enterococcus isolates showed low resistance to vancomycin and linezolid.One strain of E.faecium was found resistant to vancomycin.ESBLs were produced in 39.9％ (298/747) ofE.coli,26.1％ (294/1 127) ofKlebsiella spp.,and 15.6％ (12/77) ofP mirabilis strains.The Enterobacteriaceae strains were less resistant to imipenem,beta-lactam/beta-lactamase inhibitor combination and amikacin.About 36.6％ (163 / 445) of A.baumannii isolates and 1.8％ (13/715) of P.aeruginosa isolates were extensively drug-resistant strains.Conclusions Antibiotic resistance poses a serious threat to clinical practice,to which more attention should be paid.Clinical microbiology lab should make more efforts to provide better support to clinical therapy.

OBJECTIVETo explore the inhibitory effect of He-Ne laser irradiation on fibroblast growth of hypertrophic scars in culture.

METHODSHe-Ne laser with wavelength of 632.8 nm, power density of 50 mW/cm(2) and doses of 3 J/cm(2), 30 J/cm(2), 90 J/cm(2) and 180 J/cm(2) was used to irradiate human scar fibroblasts in culture 1, 3 and 5 times respectively, and then the cell count and cell cycle analysis were done.

RESULTSRepeated irradiation with He-Ne laser at dose of 180 J/cm(2) three and five times led to an evident decrease in total cell number compared with that of the control group and there was a significant difference (P<0.05). The cell cycle analysis showed after three and five times of irradiation with 180 J/cm(2) He-Ne laser the cell number in S-phase decreased from 51% to 20% and 14% respectively, the cell number in G(0)/G(1) phase increased from 28% to 55% and 60% respectively, and the cell percentage in Sub-G1 phase was 6.7% and 9.8% respectively.

CONCLUSIONSRepeated irradiation with 180 J/cm(2) He-Ne laser can inhibit scar fibroblasts growth in culture. It may be that He-Ne laser irradiation causes cell stagnation in G(0)/G(1) phase and apoptosis.

Cell Division ; radiation effects ; Cells, Cultured ; Cicatrix ; pathology ; Dose-Response Relationship, Radiation ; Female ; Fibroblasts ; cytology ; radiation effects ; Helium ; Humans ; Lasers ; Male ; Neon

OBJECTIVE: To establish an algorithm based on 3D convolution neural network to segment the organs at risk (OARs) in the head and neck on CT images. METHODS: We propose an automatic segmentation algorithm of head and neck OARs based on V-Net. To enhance the feature expression ability of the 3D neural network, we combined the squeeze and exception (SE) module with the residual convolution module in V-Net to increase the weight of the features that has greater contributions to the segmentation task. Using a multi-scale strategy, we completed organ segmentation using two cascade models for location and fine segmentation, and the input image was resampled to different resolutions during preprocessing to allow the two models to focus on the extraction of global location information and local detail features respectively. RESULTS: Our experiments on segmentation of 22 OARs in the head and neck indicated that compared with the existing methods, the proposed method achieved better segmentation accuracy and efficiency, and the average segmentation accuracy was improved by 9%. At the same time, the average test time was reduced from 33.82 s to 2.79 s. CONCLUSIONS The 3D convolution neural network based on multi-scale strategy can effectively and efficiently improve the accuracy of organ segmentation and can be potentially used in clinical setting for segmentation of other organs to improve the efficiency of clinical treatment.
Head ; Humans ; Image Processing, Computer-Assisted ; Neck ; Neural Networks, Computer ; Organs at Risk ; Tomography, X-Ray Computed