Objective To explore the microbiological characteristics of Staphylococcus aureus(S.aureus)with no-vel incomplete hemolytic phenotype(SIHP).Methods Hemolytic phenotypes were detected and categorized by u-sing the three-point inoculation method.A total of 11 novel SIHP and 33 randomly matched S.aureus with com-plete hemolytic phenotype(SCHP)were included.Antibiotic susceptibility test was performed using broth microdi-lution method.Coagulase test was performed with freeze-dried rabbit plasma.Catalase activity was detected by slide catalase test.Expression of hemolysin genes was detected by qRT-PCR.Toxicity to human red blood cells was as-sessed by microplate method.Microplate biofilm formation was measured using crystal violet staining method.Growth kinetic determination was performed through microcultivation assay.Results Compared with SCHP,the expression profiles of the four hemolysin genes(hla,hlb,hlc,and hld)in the new SIHP were different.The new SIHP had higher resistance rates to penicillin,oxacillin,gentamicin,quinolones,clindamycin,and trimethoprim-sulfamethoxazole.Furthermore,the new SIHP had stronger hemolytic toxicity,plasma coagulase activity,and bio-film formation ability.Additionally,the new SIHP grown faster in the logarithmic phase.Conclusion Taken to-gether,the microbiological characteristics of the new SIHP are different from those of SCHP,including stronger an-tibiotic resistance and pathogenicity,which should be paid more attention by clinicians.

Objective:To construct a risk prediction model for the inter-hospital transfer of critically ill children using machine learning methods, identify key medical features affecting transfer outcomes, and improve the success rate of transfers.Methods:A prospective study was conducted on critically ill children admitted to the pediatric transfer center of Hunan Children's Hospital from January 2020 to January 2021. Medical data on critical care features and relevant data from the Pediatric Risk of Mortality (PRISMⅢ) scoring system were collected and processed. Three machine learning models, including logistic regression, decision tree, and Relief algorithm, were used to construct the risk prediction model. A back propagation neural network was employed to build a referral outcome prediction model to verify and analyze the selected medical features from the risk prediction model, exploring the key medical features influencing inter-hospital transfer risk.Results:Among the 549 transferred children included in the study, 222 were neonates (40.44%) and 327 were non-neonates (59.56%). There were 50 children in-hospital deaths, resulting in a mortality rate of 9.11%. After processing 151 critical care medical feature data points, each model selected the top 15 important features influencing transfer outcomes, with a total of 34 selected features. The decision tree model had an overlap of 72.7% with PRISMⅢ indicators, higher than logistic regression (36.4%) and Relief algorithm (27.3%). The training prediction accuracy of the decision tree model was 0.94, higher than the accuracy of 0.90 when including all features, indicating its clinical utility. Among the top 15 important features selected by the decision tree model, the impact on transfer outcomes was ranked as follows based on quantitative feature violin plots: base excess, total bilirubin, ionized calcium, total time, arterial oxygen pressure, blood parameters (including white blood cells, platelets, prothrombin time/activated partial thromboplastin time), carbon dioxide pressure, blood glucose, systolic blood pressure, heart rate, organ failure, lactate, capillary refill time, temperature, and cyanosis. Eight of these important features overlapped with PRISMⅢ indicators, including systolic blood pressure, heart rate, temperature, pupillary reflex, consciousness, acidosis, arterial oxygen pressure, carbon dioxide pressure, blood parameters, and blood glucose. The decision tree was used to select the top 15 medical features with high impact on the neonatal and non-neonatal datasets, respectively. A total of 19 features were selected, among which there were 8 differences and 11 overlap terms between the important features of the neonatal and non-neonatal.Conclusions:Machine learning models could serve as reliable tools for predicting the risk of inter-hospital transfer of critically ill children. The decision tree model exhibits superior performance and helps identify key medical features affecting inter-hospital transfer risk, thereby improving the success rate of inter-hospital transfers for critically ill children.

Objective The aim of this study was to investigate whether there are differences in the expression spectrums of RSK4 in different tumor cells and to predict the possible protein subtypes and their biological characteris-tics.Methods RNA was extracted from glioma cells GL261,ovarian cancer cells ID8,breast cancer cells 4T1 and 168FARN,colon cancer cells mc38 and CT26,gastric cancer cells MFC and lung cancer cells LLC1.The expres-sions and splicing isomers of RSK4 were detected by RT-PCR.The biological characteristics and functions of RSK4 were analyzed by bioinformatics.Results RT-PCR results showed that RSK4 was expressed in GL261,4T1,mc38,CT26,MFC and LLC1;and multiple splicing isomers were expressed in different tumor cells.Open reading frame analysis revealed RSK4 may encode at least 11 protein subtypes.Secondary structure analysis showed that these protein subtypes encoded by the splicing isomers were composed of α-helix,extended strand,β-turn and random coil,and had the same conserved domain.The results of protein interaction network enrichment analysis showed that RSK4 exerted kinase activity in the nucleus and cytoplasm mainly through the mTOR signaling pathway and long-term potentiation.Conclusions RSK4 has different expression spectrums in different tumor cells,and may produces a variety of protein isoforms with different nitrogen terminals,which can be involved in different biological processes through multiple signaling pathways.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.

Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5％in all clinical isolates amd 5.7％in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7％(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)％,followed by secretions/pus(16.4±2.3)％and urine(16.0±0.9)％.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9％),and only(7.1±0.8)％of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)％compared to the inpatients in any other departement.Overall,≤ 7.9％of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6％of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7％vs 3.9％).Overall,≤8.1％of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5％of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0％over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10％of the Proteus and Morganella strains were resistant,while less than 20％of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4％in Proteus isolates,1.9％in Morganella isolates,and 15.6％in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.

Objective To understand the changing distribution and antimicrobial resistance profiles of Klebsiella strains in 52 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Antimicrobial susceptibility testing was carried out according to the unified CHINET protocol.The susceptibility results were interpreted according to the breakpoints in the Clinical & Laboratory Standards Institute(CLSI)M100 document.Results A total of 241,549 nonduplicate Klebsiella strains were isolated from 2015 to 2021,including Klebsiella pneumoniae(88.0％),Klebsiella aerogenes(5.8％),Klebsiella oxytoca(5.7％),and other Klebsiella species(0.6％).Klebsiella strains were mainly isolated from respiratory tract(48.49±5.32)％.Internal medicine(22.79±3.28)％,surgery(17.98±3.10)％,and ICU(14.03±1.39)％were the top 3 departments where Klebsiella strains were most frequently isolated.K.pneumoniae isolates showed higher resistance rate to most antimicrobial agents compared to other Klebsiella species.Klebsiella isolates maintained low resistance rates to tigecycline and polymyxin B.ESBLs-producing K.pneumoniae and K.oxytoca strains showed higher resistance rates to all the antimicrobial agents tested compared to the corresponding ESBLs-nonproducing strains.The K.pneumoniae and carbapenem-resistant K.pneumoniae(CRKP)strains isolated from ICU patients demonstrated higher resistance rates to majority of the antimicrobial agents tested than the strains isolated from non-ICU patients.The CRKP strains isolated from adult patients had higher resistance rates to most of the antimicrobial agents tested than the corresponding CRKP strains isolated from paediatric patients.Conclusions The prevalence of carbapenem-resistant strains in Klebsiella isolates increased greatly from 2015 to 2021.However,the Klebsiella isolates remained highly susceptible to tigecycline and polymyxin B.Antimicrobial resistance surveillance should still be strengthened for Klebsiella strains.

Objective To investigate the changing distribution and antibiotic resistance profiles of clinical isolates of Staphylococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Staphylococcus according to the unified protocol of CHINET(China Antimicrobial Surveillance Network)using disk diffusion method and commercial automated systems.The CHINET antimicrobial resistance surveillance data from 2015 to 2021 were interpreted according to the 2021 CLSI breakpoints and analyzed using WHONET 5.6.Results During the period from 2015 to 2021,a total of 204,771 nonduplicate strains of Staphylococcus were isolated,including 136,731(66.8％)strains of Staphylococcus aureus and 68,040(33.2％)strains of coagulase-negative Staphylococcus(CNS).The proportions of S.aureus isolates and CNS isolates did not show significant change.S.aureus strains were mainly isolated from respiratory specimens(38.9±5.1)％,wound,pus and secretions(33.6±4.2)％,and blood(11.9±1.5)％.The CNS strains were predominantly isolated from blood(73.6±4.2)％,cerebrospinal fluid(12.1±2.5)％,and pleural effusion and ascites(8.4±2.1)％.S.aureus strains were mainly isolated from the patients in ICU(17.0±7.3)％,outpatient and emergency(11.6±1.7)％,and department of surgery(11.2±0.9)％,whereas CNS strains were primarily isolated from the patients in ICU(32.2±9.7)％,outpatient and emergency(12.8±4.7)％,and department of internal medicine(11.2±1.9)％.The prevalence of methicillin-resistant strains was 32.9％in S.aureus(MRSA)and 74.1％in CNS(MRCNS).Over the 7-year period,the prevalence of MRSA decreased from 42.1％to 29.2％,and the prevalence of MRCNS decreased from 82.1％to 68.2％.MRSA showed higher resistance rates to all the antimicrobial agents tested except trimethoprim-sulfamethoxazole than methicillin-susceptible S.aureus(MSSA).Over the 7-year period,MRSA strains showed decreasing resistance rates to gentamicin,rifampicin,and levofloxacin,MRCNS showed decreasing resistance rates to gentamicin,erythromycin,rifampicin,and trimethoprim-sulfamethoxazole,but increasing resistance rate to levofloxacin.No vancomycin-resistant strains were detected.The prevalence of linezolid-resistant MRCNS increased from 0.2％to 2.3％over the 7-year period.Conclusions Staphylococcus remains the major pathogen among gram-positive bacteria.MRSA and MRCNS were still the principal antibiotic-resistant gram-positive bacteria.No S.aureus isolates were found resistant to vancomycin or linezolid,but linezolid-resistant strains have been detected in MRCNS isolates,which is an issue of concern.