Résumé
@#Abstract： Objective To analyze the characteristics and corresponding drug resistance of pathogenic bacterial spectrum in eight major infection sites of hospitalized patients, and to provide epidemiological data for the rational selection of antibiotics in clinical practice. Methods A total of 396 bacterial strains isolated from clinical specimens of hospitalized patients in member institutions of the Hainan Provincial Bacterial Resistance Monitoring Network from September 1, 2020, to September 30, 2022, were included in this study. Data were screened and filtered from the database of MH120 Microbial Identification and Drug Sensitivity Analysis System based on the technical scheme of the National Bacterial Drug Resistance Surveillance Network and Science and Technology Basic Resources Investigation Project research plan in 2020. The testing data were integrated, summarized, and analyzed using EXCEL and WHONET 5.6 software, and statistical analysis was conducted using SPSS 26.0 software. Results Among of 396 strains of bacteria, 78 (19.7%) were isolated from respiratory tract specimens, 74 (18.7%) from urinary tract specimens, 72 (18.2%) from blood specimens, 54 (13.6%) from abdominal cavity specimens, 48 (12.1%) from skin and soft tissue specimens 48 strains (12.1%), 30 (7.6%) from reproductive tract specimens, 22 (5.6%) from central nervous system specimens, 18 (4.5%) from digestive tract specimens. Gram-negative bacteria accounted for 69.4% of the isolates, while gram-positive bacteria accounted for 30.6%. The top five gram-negative bacteria isolated were Klebsiella pneumoniae (14.9%), Escherichia coli (14.4%), Pseudomonas aeruginosa (10.4%), Acinetobacter baumannii (5.3%), and Salmonella species (4.5%). The top five gram-positive bacteria were Staphylococcus aureus (11.1%), Streptococcus agalactis (7.8%), Enterococcus faecalis (3.0%), Enterococcus faecium (2.8%), and Streptococcus suis (1.8%). Respiratory failure and bloodstream infection were independent influencing factors of treatment response (P<0.01). The resistance rate of Escherichia coli to ampicillin was 81.4%, and the resistance rate of Staphylococcus aureus to gentamicin and levofloxacin were both below 7%. Conclusions The pathogen spectra vary with different infection sites of patients, and rational selection of antibiotics based on drug susceptibility testing is crucial to shorten the treatment time of patients and avoid the unnecessary emergence of drug-resistant strains caused by drug abuse.
Résumé
@#Abstract: Objective To explore the spatial epidemiological characteristics of severe cases hand, foot and mouth disease (HFMD) in Guangxi, China, from 2014 to 2018, and to provide a basis for identifying the high-risk regions as well as the prevention and control of severe cases of HFMD in Guangxi. Methods Spatial-temporal scanning analysis, global and local spatial autocorrelation analysis were used to analyze the spatial clustering of HFMD. The trend surface analysis was used to evaluate the spatial distribution trend of HFMD. Results From 2014 to 2018, the incidence and severe case fatality rates of HFMD were 3.89/100 000 and 4.23%, respectively. Monte Carlo scanning analysis showed that the first cluster region was Cenxi City, the second cluster was mainly concentrated in northwest of Guangxi, and the aggregation time was mainly concentrated in April to May and August to October. The global spatial autocorrelation analysis showed that the severe HFMD was significant clustering distribution, and the Moran's I coefficients of the sever cases, severe morbidity and severe case fatality rate were 0.088, 0.118, 0.197, respectively (P<0.05). Local spatial autocorrelation analysis showed that hotspots of severe HFMD cases were concentrated in the southern Guangxi, mainly in Lingshan County. Anselin local Moran's I clustering and outlier analysis indicated that 5 high-high (H-H) clustering regions for fatality were Lingshan, Pubei, Zhongshan, Zhaoping and Pinggui County. There were 6 high-high (H-H) clustering regions for severe incidence rate, namely Lingshan, Qinnan, Lingyun, Youjiang, Bama Yao Autonomous and Pinggui County, and 1 high-low (H-L) clustering region, Cenxi County. The trend surface analysis showed that the overall number of severe cases of death decreased from east or west to the middle, and increased from north to middle, and then decreased to south. Conclusions Severe HFMD cases in Guangxi have obvious spatial-temporal clustering, and the hop spots are mainly concentrated in southern Guangxi. The prevention and control of HFMD in areas with high incidence of severe cases should be strengthened to reduce the burden of HFMD cases.
Résumé
The aim of the present study is to explore whether membrane targeting of K+ channel-interacting protein 1 (KChIP1) is associated with its EF-hand motifs and varies with specifi c phospholipids. Truncated KChIP1, in which the EFhands 3 and 4 were deleted, retained the α-helix structure, indicating that the N-terminal half of KChIP1 could fold appropriately. Compared with wild-type KChIP1, truncated KChIP1 exhibited lower lipid-binding capability. Compared with wild-type KChIP1, increasing membrane permeability by the use of digitonin caused a marked loss of truncated KChIP1, suggesting that intact EF-hands 3 and 4 were crucial for the anchorage of KChIP1 on membrane. KChIP1 showed a higher binding capability with phosphatidylserine (PS) than truncated KChIP1. Unlike that of truncated KChIP1, the binding of wild-type KChIP1 with membrane was enhanced by increasing the PS content. Moreover, the binding of KChIP1 with phospholipid vesicles induced a change in the structure of KChIP1 in the presence of PS. Taken together, our data suggest that EF-hands 3 and 4 of KChIP1 are functionally involved in a specifi c association with PS on the membrane.