Objective To construct risk prediction models of death or readmission in patients with acute heart failure(AHF)during the vulnerable phase based on machine learning algorithms and screen the optimal model.Methods A total of 651 AHF patients with admitted to Department of Cardiology of the Second Affiliated Hospital of Army Medical University from October 2019 to July 2021 were included.The clinical data consisting of admission vital signs,comorbidities and laboratory results were collected from electronic medical records.The composite endpoint was defined as all-cause death or readmission for worsening heart failure within 3 months after discharge.The patients were divided into a training set(521 patients)and a test set(130 patients)in a ratio of 8:2 through the simple random sampling.Six machine learning models were developed,including logistic regression(LR),random forest(RF),decision tree(DT),light gradient boosting machine(LGBM),extreme gradient boosting(XGBoost)and neural networks(NN).Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the predictive performance and clinical benefit of the models.Shapley additive explanation(SHAP)was used to explain and evaluate the effect of different clinical characteristics on the models.Results A total of 651 AHF patients were included,of whom 203 patients(31.2%)died or were readmitted during the vulnerable phase.ROC curve analysis showed that the AUC values of the LR,RF,DT,LGBM,XGBoost and NN model were 0.707,0.756,0.616,0.677,0.768 and 0.681,respectively.The XGBoost model had the highest AUC value.DCA showed that the XGBoost model exhibited greater clinical net benefit compared with other models,with the best predictive performance.SHAP algorithm analysis showed that the clinical features that had the greatest impact on the output of the model were serum uric acid,D-dimer,mean arterial pressure,B-type natriuretic peptide,left atrial diameter,body mass index,and New York Heart Association(NYHA)classification.Conclusion The XGBoost model has the best predictive performance in predicting the risk of death or readmission of AHF patients during the vulnerable phase.

Objective:To study the effects of reactive oxygen species (ROS)-responsive antibacterial microneedles (MNs) on the full-thickness skin defect wounds with bacterial colonization in diabetic mice.Methods:Experimental research methods were adopted. The ROS-responsive crosslinker N1-(4-boronobenzyl)-N3-(4-boronophenyl)-N1, N1, N3, N3-tetramethylpropane-1,3-diaminium (TSPBA) was first synthesized, and then the polyvinyl alcohol (PVA)-TSPBA MNs, PVA-ε-polylysine (ε-PL)-TSPBA MNs, PVA-TSPBA-sodium hyaluronate (SH) MNs, and PVA-ε-PL-TSPBA-SH MNs were prepared by mixing corresponding ingredients, respectively. The PVA-TSPBA MNs were placed in pure phosphate buffer solution (PBS) and PBS containing hydrogen peroxide, respectively. The degradation of MNs immersed for 0 (immediately), 3, 7, and 10 days was observed to indicate their ROS responsiveness. The standard strains of Staphylococcus aureus ( S. aureus) and Escherichia coli (E. coli) cultured in Luria-Bertani medium containing hydrogen peroxide were divided according to the random number table (the same grouping method below) into blank control group (without any treatment, the same below) and 0 g/L ε-PL group, 1.0 g/L ε-PL group, 5.0 g/L ε-PL group, and 10.0 g/L ε-PL group with which PVA-ε-PL-TSPBA MNs containing the corresponding concentration of ε-PL were co-cultured, respectively. Bacterial growth was observed after 24 h of culture, and the relative survival rate of bacteria was calculated ( n=3). The mouse fibroblast cell line 3T3 cells at logarithmic growth stage (the same growth stage below) were divided into blank control group and 0 g/L ε-PL group, 1.0 g /L ε-PL group, 5.0 g /L ε-PL group, and 10.0 g /L ε-PL group in which cells were cultured in medium with the extract from PVA-ε-PL-TSPBA MNs containing the corresponding concentration of ε-PL, respectively. Cell growth was observed after 24 h of culture by optical microscopy, and the relative survival rate of cells was detected and calculated by cell counting kit 8 (CCK-8) assay to indicate the cytotoxicity ( n=6). Both PVA-TSPBA MNs and PVA-TSPBA-SH MNs were taken, the morphology of the two kinds of MNs was observed by optical microscopy, and the mechanical properties of the two kinds of MNs were tested by microcomputer controlled electronic universal testing machine (denoted as critical force, n=6). Six male BALB/c mice aged 6-8 weeks (the same gender and age below) were divided into PVA-TSPBA group and PVA-TSPBA-SH group, with 3 mice in each group. After pressing the skin on the back of mice vertically with the corresponding MNs for 1 minute, the skin condition was observed at 0, 10, and 20 min after pressing. Another batch of 3T3 cells were divided into blank control group, 0 g/L ε-PL group and simple 5.0 g/L ε-PL group which were cultured with the extract of PVA-ε-PL-TSPBA MNs containing the corresponding concentration of ε-PL, and 5.0 g/L ε-PL+SH group which were cultured with the extract of PVA-ε-PL-TSPBA-SH MNs with 5.0 g/L ε-PL. The CCK-8 assay was performed to detect and calculate the relative survival rate of cells cultured for 24, 48, and 72 h to indicate the cell proliferation activity ( n=6). Eighteen BALB/c mice were induced into diabetic mice model by high-sugar and high-fat diet combined with streptozotocin injection and then divided into sterile dressing group, 0 g/L ε-PL+SH group, and 5.0 g/L ε-PL+SH group, with 6 mice in each group. A full-thickness skin defect wound was made on the back of each mouse, and S. aureus solution was added to make a full-thickness skin defect wound with bacterial colonization model for diabetic mouse. The wounds of mice in 0 g/L ε-PL+SH group and 5.0 g/L ε-PL+SH group were covered with PVA-ε-PL-TSPBA-SH MNs with the corresponding concentration of ε-PL, and the wounds of mice in the 3 groups were all covered with sterile surgical dressings. The wound healing was observed on post injury day (PID) 0, 3, 7, and 12, and the wound healing rate on PID 3, 7, and 12 was calculated. On PID 12, the skin tissue of the wound and the wound margin were stained with hematoxylin and eosin to observe the growth of new epithelium and the infiltration of inflammatory cells. Data were statistically analyzed with one-way analysis of variance, analysis of variance for repeated measurement, Mann-Whitney U test, and Bonferroni test. Results:With the extension of the immersion time, the PVA-TSPBA MNs in PBS containing hydrogen peroxide gradually dissolved and completely degraded after 10 days of immersion. The PVA-TSPBA MNs in pure PBS only swelled but did not dissolve. After 24 h of culture, there was no growth of S. aureus in 5.0 g/L ε-PL group or 10.0 g/L ε-PL group, and there was no growth of E. coli in 10.0 g/L ε-PL group. The relative survival rate of S. aureus was significantly lower in 1.0 g/L ε-PL group, 5.0 g/L ε-PL group, and 10.0 g/L ε-PL group than in blank control group ( P<0.05 or P<0.01). The relative survival rate of E. coli was significantly lower in 5.0 g/L ε-PL group and 10.0 g/L ε-PL group than in blank control group ( P<0.01). After 24 h of culture, the cells in blank control group, 0 g/L ε-PL group, 1.0 g/L ε-PL group, 5.0 g/L ε-PL group, and 10.0 g/L ε-PL group all grew well, and the relative survival rate of cells was similar among the groups ( P>0.05). The needle bodies of PVA-TSPBA MNs and PVA-TSPBA-SH MNs were both quadrangular pyramid-shaped and neatly arranged, and the needle bodies of PVA-TSPBA-SH MNs was more three-dimensional and more angular. The critical force of PVA-TSPBA-SH MNs was significantly higher than that of PVA-TSPBA MNs ( Z=3.317, P<0.01). The MNs in PVA-TSPBA+SH group penetrated the skin of mice at 0 min after pressing, and the pinholes partially disappeared after 10 min and completely disappeared after 20 min, while the MNs in PVA-TSPBA group failed to penetrate the skin of mice. After 24, 48, and 72 h of culture, the proliferation activity of the cells in 5.0 g/L ε-PL+SH group was significantly higher than that of blank control group ( P<0.05 or P<0.01). In sterile dressing group, the wounds of mice healed slowly and exuded more. The wound healing speed of mice in 0 g/L ε-PL+SH group was similar to that of sterile dressing group in the early stage but was faster than that of sterile dressing group in the later stage, with moderate exudation. The wound healing of mice in 5.0 g/L ε-PL+SH group was faster than that in the other two groups, with less exudation. The wound healing rates of mice in 5.0 g/L ε-PL+SH group were (40.6±4.2)%, (64.3±4.1)%, and (95.8±2.4)% on PID 3, 7, and 12, which were significantly higher than (20.4±2.7)%, (38.9±2.2)%, and (59.1±6.2)% in sterile dressing group and (21.6±2.6)%, (44.0±1.7)%, and (82.2±5.3)% in 0 g/L ε-PL+SH group ( P<0.01). The wound healing rates of mice in 0 g/L ε-PL+SH group on PID 7 and 12 were significantly higher than those in sterile dressing group ( P<0.05 or P<0.01). On PID 12, the wounds of mice in 5.0 g/L ε-PL+SH group were almost completely epithelialized with less inflammatory cell infiltration, the wounds of mice in 0 g/L ε-PL+SH group were partially epithelialized with a large number of inflammatory cell infiltration, and no obvious epithelialization but a large number of inflammatory cell infiltration was found in the wounds of mice in sterile dressing group. Conclusions:The composite MNs prepared by TSPBA, PVA, ε-PL, and SH can successfully penetrate mouse skin and slowly respond to ROS in the wound to resolve and release antibacterial substances, inhibit bacterial colonization, and promote the repair of full-thickness skin defect wounds with bacterial colonization in diabetic mice.

Objective: To analyze the distribution and drug resistance of pathogens isolated from patients with catheter-related bloodstream infection (CRBSI) in burn intensive care unit (BICU). Methods: From January 2011 to December 2018, among 2 264 patients who were peripherally inserted central venous catheter at the BICU of the First Affiliated Hospital of Army Medical University (the third Military Medical University), hereinafter referred to as the author′s unit, 159 patients were diagnosed CRBSI, including 131 males and 28 females, aged 43 (1, 79) years. The pathogens primarily isolated from peripheral venous blood and central venous catheter blood/anterior central venous catheter specimen of patients with CRBSI were retrospectively analyzed. API bacteria identification kits and automatic microorganism identification instrument were used to identify pathogens. Broth micro-dilution method or Kirby-Bauer paper disk diffusion method was used to detect the drug resistance of the pathogens to 5 antifungal drugs including fluconazole and itraconazole, etc., and 37 antibacterial drugs including tigecycline and imipenem, etc. Modified Hodge test was used to further identify imipenem- and meropenem-resistant Klebsiella pneumonia. D test was used to detect erythromycin-induced clindamycin resistant Staphylococcus aureus. The WHONET 5.6 software was applied to analyze the annual incidence of CRBSI, mortality of patients with CRBSI, incidence of CRBSI cases, distribution of infection site, and duration of catheterization, detection of Gram-negative and Gram-positive bacteria, fungi, methicillin-resistant Staphylococcus aureus (MRSA), and methicillin-sensitive Staphylococcus aureus (MSSA), and drug resistance of fungi and major Gram-negative and Gram-positive bacteria to the commonly used antibiotics in clinic. Results: (1) The incidence of CRBSI was 7.0% (159/2 264) during the eight years, which was slightly higher in 2014 and 2017 with 13.6% (30/221) and 11.1% (24/217) respectively. The mortality rate of patients with CRBSI was 7.5% (12/159). (2) The incidence of CRBSI cases was 14.9% (338/2 264); the main infection site was femoral vein, totally 271 cases (80.2%), and the duration of catheterization of this site was 9 (2, 25) d. (3) During the eight years, totally 543 strains of pathogens were isolated, including 353 (65.0%) strains of Gram-negative bacteria, 140 (25.8%) strains of Gram-positive bacteria, and 50 (9.2%) strains of fungi. The top three isolated pathogens with isolation rate from high to low were Acinetobacter baumannii, Staphylococcus aureus, and Pseudomonas aeruginosa, accounting for 23.2% (126/543), 17.1% (93/543), and 15.7% (85/543), respectively. Fungi were mainly Candida parapsilosis. Among the Staphylococcus aureus, the detection rate of MRSA was 98.9% (92/93), and that of MSSA was 1.1% (1/93). (4) Except for the low drug resistance rates to polymyxin B, minocycline, and tigecycline, the drug resistance rates of Acinetobacter baumannii to the other antibiotics were considerably high (80.1%-100.0%). Pseudomonas aeruginosa was not resistant to polymyxin B but highly resistant to netilmicin (88.7%) and piperacillin (92.6%), with resistance rates to the other antibiotics from 34.5% to 62.7%. Klebsiella pneumoniae was not resistant to tigecycline and lowly resistant to imipenem and meropenem (28.9%, 9 imipenem- and meropenem-resistant strains were further confirmed by modified Hodge test), with resistance rates to the other antibiotics from 40.9% to 95.2%. The resistance rates of MRSA to most antibiotics were higher than those of MSSA. MRSA was not resistant to linezolid, vancomycin, teicoplanin, sulfamethoxazole, or tigecycline. The resistance rates of MRSA to clindamycin and erythromycin were 7.9% and 62.0%, respectively, and those to the other antibiotics were higher than 91.5%. Except for the complete resistance to penicillin G and tetracycline, MSSA was not resistant to the other antibiotics. Thirty-three strains of Staphylococcus aureus showed resistance to erythromycin-induced clindamycin. Fungi was not resistant to amphotericin B, with drug resistance rates to voriconazole, itraconazole, ketoconazole, and fluconazole from 4.2% to 6.2%. Conclusions The incidence of CRBSI and mortality of patients with CRBSI are high in BICU of the author′s unit, and the main infection site is femoral vein. There are various types of pathogens in patients with CRBSI, and most of them are Gram-negative. The top three isolated pathogens are Acinetobacter baumannii, Staphylococcus aureus, and Pseudomonas aeruginosa, accompanying with grim drug resistance phenomenon.

Objective: To retrospectively analyze the diagnosis time, pathogen distribution, and drug resistance of fungal bloodstream infection in severe burn patients. Methods: Blood samples were collected from 55 severe burn patients with fungal bloodstream infection (including 46 males and 9 females, aged 42 (1, 78) years) admitted to the intensive care unit of the Institute of Burn Research of the First Affiliated Hospital of Army Medical University (the Third Military Medical University) from July 2011 to May 2019 for retrospective analysis. Microbial monitoring system was used to cultivate pathogens, API yeast identification kit and Candida chromogenic medium were used to identify pathogens, and Kirby-Bauer paper disk diffusion method was used to detect drug resistance of fungi to fluconazole, amphotericin B, itraconazole, ketoconazole, and voriconazole. The positive rate of blood fungal culture, mortality rate, distribution of local fungal proliferation sites, the diagnosis time distribution of fungal bloodstream infection, the distribution of fungal species, resistance to commonly-used antifungal drugs, and the use of antibiotics were assessed. The WHONET 5.6 software was applied to analyze the distribution and drug resistance of fungi. Results: (1) Totally 4 839 blood samples were collected during the 9 years, and 122 strains of fungi were isolated, with positive rate of 2.52%. The mortality rate was 14.55% (8 patients) in 55 patients. Catheter fungal proliferation ranked the first among 30 cases of local fungal proliferation. (2) The diagnosis time of fungal bloodstream infection mainly distributed in ≤1 week of hospitalization [32.73% (18/55)]. (3) Among the 55 strains of fungi detected, the detection rate of Candida parapsilosis ranked the first (21.82%, 12 strains), Candida glabrata was the second (18.18%, 10 strains), and Candida tropicalis was tied with Candida albicans in the third place (14.55%, 8 strains). All the detected fungi were sensitive to amphotericin B, and the resistance rates to voriconazole, fluconazole, itraconazole, and ketoconazole were between 4.5% and 9.1%. (4) Droad-spectrum antibiotics were used in all the 55 patients, ≥3 kinds of antibiotics were used in 44 patients, and 37 patients used antibacterial drugs ≥7 days. Conclusions The diagnosis time of fungal bloodstream infection in the 55 severe burn patients was mainly within 1 week of hospitalization. Candida parapsilosis is the most commonly detected fungal species. Catheter fungal proliferation occurs most commonly among the 30 patients with local fungal proliferation. All the detected fungi were sensitive to amphotericin B, with low drug resistance to voriconazole, fluconazole, itraconazole, and ketoconazole. Broad-spectrum antibiotics were overused in the severe burn patients with fungal bloodstream infection.

Objective:To construct a prognosis associated micro RNA(miRNA) prediction model based on bioinformatics analysis and evaluate its application value in pancreatic cancer patients.Methods:The retrospective cohort study was conducted. The clinicopathological data of 171 pancreatic cancer patients from the Cancer Genome Atlas (TCGA) (https: //cancergenome.nih.gov/) between establishment of database and September 2017 were collected. There were 93 males and 78 females, aged from 35 to 88 years, with a median age of 65 years. Of the 171 patients, 64 had complete clinicopathological data. Patients were allocated into training dataset consisting of 123 patients and validation dataset consisting of 48 patients using the random sampling method, with a ratio of 7∶3. The training dataset was used to construct a prediction model, and the validation dataset was used to evaluate performance of the prediction model. Nine pairs of miRNA sequencing data (GSE41372) of pancreatic cancer and adjacent tissues were downloaded from Gene Expression Omnibus database. The candidate miRNAs were selected from differentially expressed miRNAs in pancreatic cancer and adjacent tissues for LASSO-COX regression analysis based on the patients of training dataset. A prognosis associated miRNA prediction model was constructed upon survival associated miRNAs which were selected from candidate differentially expressed miRNAs. The performance of prognosis associated miRNA prediction model was validated in training dataset and validation dataset, the accuracy of model was evaluated using the area under curve (AUC) of the receiver operating characteristic curves and the efficiency was evaluated using the consistency index (C-index). Observation indicarors: (1) survival of patients; (2) screening results of differentially expressed miRNAs; (3) construction of prognosis associated miRNA model; (4) validation of prognosis associated miRNA model; (5) comparison of clinicopathological factors in pancreatic cancer patients; (6) analysis of factors for prognosis of pancreatic cancer patients; (7) comparison of prediction performance between prognosis associated miRNA model and the eighth edition TNM staging. Measurement data with normal distribution were represented as Mean± SD, comparison between groups was analyzed by the student- t test, and comparison between multiple groups was analyzed by the AVONA. Measurement data with skewed data were represented as M (range), and comparison between groups was analyzed using the Mann-Whitney U test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. Ordinal data were analyzed using the rank sum test. Correlation analysis was conducted based on count data to mine the correlation between prognosis associated miRNA model and clinicopathological factors. COX univariate analysis and multivariate analysis were applied to evaluate correlation with the results described as hazard ratio ( HR) and 95% confidence interval ( CI). HR<1 indicated the factor as a protective factor, HR>1 indicated the factor as a risk factor, and HR equal to 1 indicated no influence on survival. The Kaplan-Meier method was used to draw survival curve and calculate survival rates, and the Log-rank test was used for survival analysis. Results:(1) Survival of patients: 123 patients in the training dataset were followed up for 31-2 141 days, with a median follow-up time of 449 days. The 3- and 5-year survival rates were 16.67% and 8.06%. Forty-eight patients in the validation dataset were followed up for 41-2 182 days, with a median follow-up time of 457 days. The 3- and 5-year survival rates were 15.63% and 9.68%. There was no significant difference in the 3- or 5-year survival rates between the two groups ( χ2=0.017, 0.068, P>0.05). (2) Screening results of differentially expressed miRNAs. Results of bioinformatics analysis showed that 102 candidate differentially expressed miRNAs were selected, of which 63 were up-regulated in tumor tissues while 39 were down-regulated. (3) Construction of prognosis associated miRNA model: of the 102 candidate differentially expressed miRNAs, 5 survival associated miRNAs were selected, including miR-21, miR-125a-5p, miR-744, miR-374b, miR-664. The differential expression patterns of pancreatic cancer to adjacent tissues were up-regulation, up-regulation, down-regulation, up-regulation, and down-regulation, respectively, with the fold change of 4.00, 3.43, 3.85, 2.62, and 2.35. A prognostic expression equation constructed based on 5 survival associated miRNAs = 0.454×miR-21 expression level-0.492×miR-125a-5p expression level-0.49×miR-744 expression level-0.419×miR-374b expression level-0.036×miR-664 expression level. (4) Validation of prognosis associated miRNA model: The C-index of prognosis associated miRNA model was 0.643 and 0.642 for the training dataset and validation dataset, respectively. (5) Comparison of clinicopathological factors in pancreatic cancer patients: results of COX analysis showed that the prognosis associated miRNA model was highly related with pathological T stage and location of pancreatic cancer ( Z=45.481, χ2=10.176, P<0.05). (6) Analysis of factors for prognosis of pancreatic cancer patients: results of univariate analysis showed that pathological N stage, radiotherapy, molecular targeted therapy, score of prognosis associated miRNA model were related factors for prognosis pf pancreatic cancer patients ( HR=2.471, 0.290, 0.172, 2.001, 95% CI: 1.012-6.032, 0.101-0.833, 0.082-0.364, 1.371-2.922, P<0.05). Results of multivariate analysis showed that molecular targeted therapy was an independent protective factor for prognosis of pancreatic cancer patients ( HR=0.261, 95% CI: 0.116-0.588, P<0.05) and score of prognosis associated miRNA model≥1.16 was an independent risk factor for prognosis of pancreatic cancer patients ( HR=1.608, 95% CI: 1.091-2.369, P<0.05). (7) Comparison of prediction performance between prognosis associated miRNA model and the eighth edition TNM staging: in the training dataset, there was a significant difference in the prediction probability for 3- and 5-year survival of pancreatic cancer patients between prognosis associated miRNA model and the eighth edition TNM staging ( Z=-1.671, -1.867, P<0.05). The AUC of the prognosis associated miRNA model and the eight edition TNM staging for 3- and 5-year survival prediction was 0.797, 0.935 and 0.737 , 0.703, with the 95% CI of 0.622-0.972, 0.828-1.042 and 0.571-0.904 , 0.456-0.951. The C-index was 0.643 and 0.534. In the validation dataset, there was a significant difference in the prediction probability for 3- and 5-year survival of pancreatic cancer patients between prognosis associated miRNA model and the eighth edition TNM staging ( Z=-1.729, -1.923, P<0.05). The AUC of the prognosis associated miRNA model and the eight edition TNM staging was 0.750, 0.873 and 0.721 , 0.703, with the 95% CI of 0.553-0.948, 0.720-1.025 and 0.553-0.889, 0.456-0.950, respectively. The C-index was 0.642 and 0.544. Conclusions:A prognosis associated miRNA prediction model can be constructed based on 5 survival associated miRNAs in pancreatic cancer patients, as a complementation to current TNM staging and other clinicopathological parameters, which provides individual and accurate prediction of survival for reference in the clinical treatment.

The burn microbiology laboratory of the author′s unit is a level Ⅱ biosafety laboratory, which is mainly responsible for handling clinical microbial samples from our department and other departments in the hospital. Since the outbreak of the coronavirus disease 2019, in order to ensure the normal operation of routine work and the safety of medical staff, the microbiology laboratory has actively adjusted the daily work flow. The detailed work flow is summarized as follows to provide references for the safety protection of peer in clinical microbiology laboratory.

Objective: To explore the resistance mechanism and gene type of carbapenems-resistant Klebsiella pneumoniae (CRKP) in burn care unit. Methods: A total of 27 CRKP strains were primarily isolated from 22 patients [20 males, 2 females, aged (42±16) years] admitted to burn care unit of Institute of Burn Research of the First Affiliated Hospital of Army Medical University (the Third Military Medical University, hereinafter referred to as our department) from January to December 2017. After identification of bacteria, the months of detection and distribution of sample source were analyzed. Drug resistance tests of 15 antibiotics were conducted. Polymerase chain reaction was used to detect the drug resistant genes. Pulsed-field gel electrophoresis (PFGE) and multi-locus sequence typing (MLST) were used to analyze the gene type of strains. Results: (1) During the whole year of 2017, CRKP strains were mostly detected in August (8 strains), September (6 strains), and October (5 strains), with no CRKP in January, March, June, November, and December. Five strains from bed units were detected in August (2 strains), September (1 strain), and October (2 strains). (2) Twenty-seven CRKP strains were derived from blood samples (40.7%, 11/27), wound exudate samples (18.5%, 5/27), deep vein catheter samples (11.1%, 3/27), sputum samples (7.4%, 2/27), urine samples (3.7%, 1/27), and bed unit samples (18.5%, 5/27). (3) The 27 CRKP strains were detected with drug-resistance rates of 100.0% to 7 antibiotics including cefoperazone/sulbactam, piperacillin/tazobactam, cefazolin, ceftriaxone, cefepime, ertapenem, and compound sulfamethoxazole, no drug-resistance to tigecycline, with drug-resistance rates higher than 81.0% to the rest 7 antibiotics. (4) Detection rates for resistance gene bla_CTX-M-10, bla_SHV, bla_TEM, bla_CTX-M-14, bla_ACT, and bla_KPC were all above 92.5%. (5) According to PFGE, the 27 CRKP strains had 6 types (A, A₁, A₂, B, C, and D). Strains of type A were mainly detected in February, May, and September, with detection rate of 37.0% (10/27). Strains of type C were mainly detected in July, August, and October, with detection rate of 48.1% (13/27). Strains of types A₁, A₂, B, and D were scatteredly detected, with detection rate of 3.7% (1/27) respectively. According to MLST, the 27 CRKP strains had 6 STs. ST11 was the most frequent type, accounting for 74.1% (20/27), which was detected in August to October. The detection rate of ST395, ST2230, ST215, ST260, and STnew ranged from 3.7%(1/27) to 7.4%(2/27), and the strains were scatteredly detected. Conclusions The main source of CRKP from burn care unit of our department was bloodstream. All the CRKP strains showed high drug-resistance rate and complicated resistance mechanism. There were small scale outbreaks caused by CRKP of type A, type C, and ST11, which should be paid more attention to in clinical treatment and infection control.

To screen the pathogenic mutation location in a genetic family with the neurofibromatosis (NF1) by the next generation sequencing and analyze the clinical phenotype,Illumina Miseq sequencing was applied to capture and analyze the target regions of NF1 family's probands,and furtherly find out the suspicious mutations,as well as to verify the family members by Sanger sequencing.Two rare variants were identified in proband,including the heterozygous missense mutation c.C3649T (p.P1217S) in KIF1B gene and the missense mutation c.T6311C (p.L2104P) on exon 41 of NF1 gene (NM_000267.3).The amino acid at position 2104 was found to be changed from leucine to proline in NF1.The protein prediction SIFT and Polyphen-2 values were 0,0.997,which predicted a conformational change in the encoded protein and eventually affected its function.The mutation c.T6311C in NF1 gene was detected in all patients in this family,which showed genetic co-segregation.The clinical phenotype was neurofibroma in the spinal canal.There were no café au lait spots,iris Lisch nodules,scoliosis,tinnitus,heating loss,or elevated intracranial pressure.The missense mutation c.T6311C (p.L2104P) in NF1 gene might be the genetic cause of this hereditary disease of neurofibromatosis.

OBJECTIVE:To establish a method for the determination of related substances in Thioctic acid injection. METH-ODS:HPLC was performed on the column of Agilent Eclipse Plus C18 with mobile phase A of 0.005 mol/L potassium dehydroge-nate phosphate solution(adjusted with phosphoric acid to pH 3.0 to 3.1)and B of methanol:aoetonitrile(1∶1,V/V)(gradient elu-tion) at a flow rate of 1.2 ml/min;detection wavelength was 215 nm,column temperature was 35 ℃,and the injection volume was 20 μl. RESULTS:Under the established chromatographic conditions,thioctic acid with impurities and its degradation products were well separated;the linear range of thioctic acid was 0.828-52.992 μg/ml(r=0.999 9);RSDs of precision and stability tests were lower than 3%;recovery of impurity A was 98.45%-105.73%(RSD=2.41%,n=9);the largest single impurity content in mass fraction was 0.152%-0.189%,the total impurity content in mass fraction was 0.487%-0.516%. CONCLUSIONS:The meth-od is simple,accurate,specific and sensitivity,and can be used to determine the related substances of the Thioctic acid injection.

Objective To fabricate an anti?tuberculosis controlled drug release coating with Ti?PDA?PEG?PLGA?INH and to investigate its surface characteristics, in vivo and in vitro drug release behavior, and tissue biocompatibility. Methods 4?arm?polyethylene glycol (PEG) was synthesized first. Then cover the surface of titanium (Ti) with a layer of poly dopamine (PDA) by Michael addition reaction. Use porous starch and 4?arm?PEG as a carrier, load with isoniazid (INH), then attach to the surface of titanium by casting or sol?gel dip coating methods, and then cover with a layer of poly lactic?co?glycolic acid (PLGA) by the same method, to fabricate the Ti?PDA?PEG?PLGA?INH composite coating finally. The functional group of 4?arm?PEG was charac?terized by proton nuclear resonance spectroscopy (HNMR). The surface characteristics of Ti?PDA?PEG?PLGA?INH were evaluated by scanning electron microscope (SEM), while drug release behaviors were detected by high performance liquid chromatography (HPLC) and the cumulative release rate was calculated, and carry out the antibacterial performance in vitro. The animal model of femoral condyle bone defect was established in 25 New Zealand white rabbits. Titanium rods covered with PDA?PEG?PLGA?INH coating were implanted into defect area. INH concentrations were detected by HPLC in venous blood, muscle and bone tissue at each time point postoperatively. Another 12 rabbits were randomly divided into experimental group and control group, the experi?mental group was implanted with titanium tablets and titanium rods coated with PDA?PEG?PLGA?INH in the paraspinous muscle and left femoral condyles respectively, while the control group was implanted with a blank sheet of titanium tablets and titanium rods in the same place. Hematoxylin and Eosin Staining were used to observe the biocompatibility of the composite system in vivo at 28 and 56 days postoperatively. Results Ti?PDA?PEG?PLGA?INH controlled drug release coating uniformly distributed on the surface of plates and rods, with translucent form and smooth surface. In vitro INH release kinetics exhibited a short?burst release during the first 8h, and the cumulative release of the INH was about 65%. On the 9th day, the cumulative release of the INH was about 90%, and then the release tended to be flat, and the drug release behavior in vitro continued more than 20d. In vivo release test showed that the concentration of INH in vein blood, muscle and bone tissue around the composite system was increased steadi?ly postoperatively. On about the 28th day, the concentration reached the max. However, the INH concentrations in muscle and bone tissue around the composite system were still higher than the minimum inhibitory concentration (MIC) on the 56th day. The antibacterial test in vitro showed that the titanium tablets coated with PDA?PEG?PLGA?INH formed obvious bacterial inhibition zones. The pathological results indicated that mild inflammatory reaction was seen in the 4th week postoperatively, and the reac?tive capsule formed with loose connective tissue. In the 8th week postoperatively, there's no obvious inflammation occurred, and the reactive capsule became more dense and thicker. Conclusion The study successfully fabricated the Ti?PDA?PEG?PLGA?INH anti?tuberculosis controlled drug release coating, with reasonable release behavior both in vivo and in vitro, effective antibac?terial effect of Mycobacterium tuberculosis in vitro and good tissue biocompatibility, which is a potentially effective drug delivery system for spinal tuberculosis.