Objective To investigate the distribution and drug resistance of pathogens in intensive care unit (ICU) so as to provide scientific basis for antibiotic adoption and the prevention and control of nosocomial infections. Methods The various specimens collected from the patients admitted into ICU in the First People's Hospital of Shunde Affiliated to the South Medical University from January 2007 to December 2014 were used to isolate the pathogens that might cause nosocomial infections and retrospectively analyze their clinical distribution and drug resistance. Kirby-Bauer paper diffusion and minimal inhibitory concentration (MIC) methods were applied to test the drug sensitivity, and according to National Committee for Clinical Laboratory Standards/Clinical and Laboratory Standards Institute (NCCLS/CLSI) standard, the results were identified.Results The sputum was the major specimen source in ICU, accounting for 68.8%, followed by urine (12.4%) and blood (6.8%). All together 557 pathogens in ICU causing nosocomial infections were isolated of which there were 377 gram-negative (G-) bacilli (67.7%), 103 gram-positive (G+) cocci (18.5%), and 77 fungi (13.8%). Among G- bacilli, the top three wereAcinetobacter baumannii (34.5%), Klebsiella pneumonia (17.8%), andPseudomonas aeruginosa (13.0%). Beside carbapenem, the drug resistance rates of Acinetobacterbaumannii to other antibiotics were more than 40%. The main G+ coccus causing nosocomial infection wasSaphylococcus aureus (36.9%) in ICU. The drug resistance rates ofSaphylococcus aureus to penicillin, gentamicin and erythromycin were higher than 50%. In 77 fungus strains,Candida albicans was ranked the first, accounting for 41.6%.Conclusion The main infection site in ICU is primarily respiratory tract, the G- bacilli are the predominate pathogens, and the drug resistance to antibiotics found in this report is serious, so clinically, the antibiotics should be properly used to avoid the occurrence of pathogenic strain with drug tolerance.

Objective:To investigate the clinical effect of Banxia Baizhu Tianma decoction combined with bean embedding in ear points on patients with cervical vertigo.Methods:From May 2018 to October 2020, 160 cases of cervical vertigo patients with phlegm turbidity and moderate resistance in Jinhua Central Hospital were selected as the research objects. According to the random number table method, the research objects were divided into ear acupoint buried beans group (A group, n=53), Banxia Baizhu Tianma decoction group (B group, n=54), Banxia Baizhu Tianma decoction combined with ear-buried beans group (C group, n=53). The three groups were treated with ear point burying bean, Banxia Baizhu Tianma decoction and Banxia Baizhu Tianma decoction combined with ear point burying bean for 10 consecutive days. The clinical effect, traditional Chinese medicine (TCM) syndrome score, cerebral blood flow velocity and hemorheology of the three groups were compared. Results:There was no significant difference in the total clinical effective rate between group B and group C ( P>0.05). The total clinical effective rate of group C was significantly higher than that of group A, the difference was statistically significant ( P<0.05). After treatment, scores of vertigo, neck and shoulder pain, headache and symptoms of daily life and work in 3 groups were significantly higher than before treatment, the differences were statistically significant (all P<0.05); The scores of TCM syndrome in group C were significantly higher than those in group A and group B, with statistical significance (all P<0.05). After treatment, the cerebral blood flow velocity of left vertebral artery (LVA), right vertebral artery (PVA), and basilar artery (BA) in the three groups were significantly increased compared with that before treatment, and the cerebral blood flow velocity of LVA, PVA, and BA in group C was significantly faster than that in A, B group, with statistical significance ( P<0.05). After treatment, the plasma viscosity, whole blood high shear viscosity and hematocrit of the patients in the three groups were significantly lower than those before treatment, and the cerebral blood flow velocity of group C was significantly lower than that of group A and group B ( P<0.05). Conclusions:Banxia Baizhu Tianma decoction combined with ear acupoint buried beans in the treatment of cervical vertigo with middle resistance of phlegm and turbidity can improve the symptoms of cervical vertigo, cerebral blood flow velocity and reduce blood viscosity, which is worthy of clinical promotion.

Expressed Sequence Tag (EST) analysis has pioneered genome-wide gene discovery and expression profiling. In order to establish a gene expression index in the rice cultivar indica, we sequenced and analyzed 86,136 ESTs from nine rice cDNA libraries from the super hybrid cultivar LYP9 and its parental cultivars. We assembled these ESTs into 13,232 contigs and leave 8,976 singletons. Overall, 7,497 sequences were found similar to existing sequences in GenBank and 14,711 are novel. These sequences are classified by molecular function, biological process and pathways according to the Gene Ontology. We compared our sequenced ESTs with the publicly available 95,000 ESTs from japonica, and found little sequence variation, despite the large difference between genome sequences. We then assembled the combined 173,000 rice ESTs for further analysis. Using the pooled ESTs, we compared gene expression in metabolism pathway between rice and Arabidopsis according to KEGG. We further profiled gene expression patterns in different tissues, developmental stages, and in a conditional sterile mutant, after checking the libraries are comparable by means of sequence coverage. We also identified some possible library specific genes and a number of enzymes and transcription factors that contribute to rice development.
Arabidopsis ; genetics ; DNA, Complementary ; metabolism ; Databases as Topic ; Expressed Sequence Tags ; Gene Library ; Genome, Plant ; Genomics ; methods ; Multigene Family ; Open Reading Frames ; Oryza ; genetics ; Quality Control ; Software

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.