Objective:To explore the predictive value of peripheral blood neutrophil to lymphocyte ratio (NLR) and serum trimethylamine oxide (TMAO) on in-hospital mortality events in patients with acute myocardial infarction complicated by cardiogenic shock (AMICS) upon admission.Methods:A retrospective collection of medical records of 103 AMICS patients admitted to the Shanxi Yingkang Life General Hospital from January 2018 to June 2023 was conducted. The patients were divided into a survival group ( n=78) and a death group ( n=25) based on whether they experienced in-hospital mortality events. Two groups of peripheral blood NLR, serum TMAO, baseline data, and other laboratory indicators were compared. A logistic regression model was used to analyze the risk factors for in-hospital mortality in AMICS patients and a prediction model was constructed. We established receiver operating characteristic (ROC) curves to evaluate the predictive efficacy of peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and predictive model indicators for in-hospital mortality events in AMICS patients. Results:The peripheral blood NLR and serum TMAO levels in the death group were significantly higher than those in the survival group (all P<0.05). The age of the death group was higher than that of the survival group, and the proportion of hypertension, alanine aminotransferase, creatinine, random blood glucose, proportion of patients who did not receive emergency percutaneous coronary intervention (PCI) treatment, peak cardiac troponin I, B-type natriuretic peptide, Gensini score of coronary artery disease, and C-reactive protein were all higher than those of the survival group. Systolic blood pressure and platelet count were lower than those of the survival group, heart rate and erythrocyte sedimentation rate were faster than those of the survival group, and the pre hospital time was longer than that of the survival group. The differences were statistically significant (all P<0.05). The results of binary logistic regression analysis showed that after adjusting for confounding factors such as age, male proportion, body mass index, proportion of old myocardial infarction, proportion of hypertension, and proportion of PCI history, advanced age, long pre hospital time, failure to receive emergency PCI, elevated peripheral blood NLR, and elevated serum TMAO were independent risk factors for in-hospital mortality in AMICS patients ( P<0.05). The predictive model was obtained as 0.734×age+ 0.277×pre hospital time+ 2.263×failure to receive emergency PCI+ 0.549×peripheral blood NLR+ 0.608×serum TMAO-26.923. The ROC curve results showed that the area under the curve (AUC) values of peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and predictive model indicators for predicting in-hospital mortality events in AMICS patients were 0.744, 0.781, 0.825, and 0.921, respectively. When the optimal cutoff value was taken, the sensitivities were 0.880, 0.520, 0.680, and 0.880, and the specificities were 0.526, 0.923, 0.872, and 0.821, respectively. Conclusions:Advanced age, long pre hospital duration, failure to undergo emergency PCI, elevated peripheral blood NLR, and elevated serum TMAO are independent risk factors for in-hospital mortality in AMICS patients. Peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and prediction models all have certain predictive value for in-hospital mortality events in AMICS patients. Among them, the sensitivity and specificity of the prediction models are high, and the efficacy is good.

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.

AIM To simultaneously determine the contents of 3,6'-disinapoyl sucrose,sibiricose A5,sibiricose A6,ferulic acid,sinapic acid,caffeic acid,luteolin,progoitrin,apigenin,isorhamnetin and 3,4-dihydroxybenzaldehyde in Sanzi Yangqin Decoction,and to investigate their inhibitory effects on pancreatic lipase.METHODS The high-performance liquid chromatography-triple quadrupole tandem mass spectrometry(HPLC-QQQ-MS/MS)analysis was performed on a 25 ℃ thermostatic Halo-C18column(2.1 mmx100 mm,2.7 μm),with the mobile phase comprising of water(containing 0.05％formic acid)-acetonitrile(containing 0.05％formic acid)flowing at 0.3 mL/min in a gradient elution manner,and electron spray ionization source was adopted in negative ion scanning with multiple reaction monitoring mode.The simulation was performed by molecular docking,after which 4-nitrophenyl butyrate method was adopted in the evaluation of inhibitory effects.RESULTS Eleven constituents showed good linear relationships within their own ranges(R2＞0.992 0),whose average recoveries were 85.79％-117.52％with the RSDs of 0.78％-3.73％.3,6'-Disinapoyl sucrose,caffeic acid,sinapic acid and 3,4-dihydroxybenzaldehyde demonstrated good affinities with pancreatic lipase,the IC50 values of Sanzi Yangqin Decoction,caffeic acid,sinapic acid and 3,4-dihydroxybenzaldehyde were 41.16 mg/mL,4.006 mmol/L,6.798 mmol/L and 10.48 mmol/L,respectively.CONCLUSION This stable and reliabe method can provide theoretical basis for the quality control of Sanzi Yangqin Decoction with inhibitory effects on pancreatic lipase.

Objective: The docking and superantigen activity sites of staphylococcal enterotoxin-like W (SElW) and T cell receptor (TCR) were predicted, and its SElW was cloned, expressed and purified. Methods: AlphaFold was used to predict the 3D structure of SElW protein monomers, and the protein models were evaluated with the help of the SAVES online server from ERRAT, Ramachandran plot, and Verify_3D. The ZDOCK server simulates the docking conformation of SElW and TCR, and the amino acid sequences of SElW and other serotype enterotoxins were aligned. The primers were designed to amplify selw, and the fragment was recombined into the pMD18-T vector and sequenced. Then recombinant plasmid pMD18-T was digested with BamHⅠand Hind Ⅲ. The target fragment was recombined into the expression plasmid pET-28a(+). After identification of the recombinant plasmid, the protein expression was induced by isopropyl-beta-D- thiogalactopyranoside. The SElW expressed in the supernatant was purified by affinity chromatography and quantified by the BCA method. Results: The predicted three-dimensional structure showed that the SElW protein was composed of two domains, the amino-terminal and the carboxy-terminal. The amino-terminal domain was composed of 3 α-helices and 6 β-sheets, and the carboxy-terminal domain included 2 α-helices and 7 antiparallel β-sheets composition. The overall quality factor score of the SElW protein model was 98.08, with 93.24% of the amino acids having a Verify_3D score ≥0.2 and no amino acids located in disallowed regions. The docking conformation with the highest score (1 521.328) was selected as the analysis object, and the 19 hydrogen bonds between the corresponding amino acid residues of SElW and TCR were analyzed by PyMOL. Combined with sequence alignment and the published data, this study predicted and found five important superantigen active sites, namely Y18, N19, W55, C88, and C98. The highly purified soluble recombinant protein SElW was obtained with cloning, expression, and protein purification. Conclusions: The study found five superantigen active sites in SElW protein that need special attention and successfully constructed and expressed the SElW protein, which laid the foundation for further exploration of the immune recognition mechanism of SElW.
Humans ; Enterotoxins/genetics* ; Superantigens/genetics* ; Catalytic Domain ; Selenoprotein W/metabolism* ; Receptors, Antigen, T-Cell

Humans ; Infant, Newborn ; Intensive Care Units, Neonatal ; Logistic Models ; Phenotype ; Risk Factors