AIM To explore the clinical effects of Jiawei Yanghe Decoction combined with Budesonide and Formoterol Fumarate Powder for Inhalation on patients with mild to moderate bronchial asthma in chronic and persistent period.METHODS One hundred and eighteen patients were randomly assigned into control group(59 cases)for 4-week administration of Budesonide and Formoterol Fumarate Powder for Inhalation,and observation group(59 cases)for 4-week administration of both Jiawei Yanghe Decoction and Budesonide and Formoterol Fumarate Powder for Inhalation.The changes in clinical effects,ACT score,bronchial asthma control rate,pulmonary function indices(FEV1,PEF,FEV1％,PEF％),inflammatory indices(EOS,EOS％,FeNO),TCM syndrome score and incidence of adverse reactions were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed increased bronchial asthma control rate,ACT score,PEF(P＜0.05),and decreased TCM syndrome score(P＜0.05),especially for the observation group(P＜0.05);the observation group exhibited increased FEV1,FEV1％,PEF％(P＜0.05),among which FEV1,PEF％were higher than those in the control group(P＜0.05);the observation group showed decreased inflammatory indices(P＜0.05),among which FeNO was lower than that in the control group(P＜0.05).No significant difference in incidence of adverse reactions was found between the two groups(P＞0.05).CONCLUSION For the patients with mild to moderate bronchial asthma in chronic and persistent period,Jiawei Yanghe Decoction combined with Budesonide and Formoterol Fumarate Powder for Inhalation can safely and effectively alleviate clinical symptoms,improve pulmonary functions,airway inflammatory reactions,and enhance bronchial asthma control rate.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

AIM To establish the near-infrared spectroscopy quantitative models for moisture,23-acetylalismol B and 23-acetylalismol C in Alismatis Rhizoma decoction pieces.METHODS The near-infrared spectroscopy(NIRS)data were collected in 95 batches of decoction pieces,after which drying method was adopted in the content determination of moisture,HPLC was applied to determining the contents of 23-acetylalismol B and 23-acetylalismol C,the quantitative models were established by partial least squares method combined with feature extraction algorithms.RESULTS The model training determination coefficients were 0.952 6,0.958 1 and 0.920 8,along with the prediction determination coefficients of 0.930 0,0.905 2 and 0.906 4,the residual prediction deviations(PRD)of 4.00,3.58 and 3.46,and the root mean square error ratios of prediction values to calibration values(RMSEP/RMSEC)of 1.15,1.11 and 1.06,respectively.CONCLUSION The quantitative models based on NIRS exhibit good prediction effects,which can be used for the rapid quality detection of Alismatis Rhizoma decoction pieces.

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.

Objective To investigate the expression of microRNA-508-3p(miR-508-3p)in epithelial ovarian cancer(EOC)tissue,its impact on the migration and invasion of ovarian cancer cells,and its regulatory relationship with zinc-finger E-box-binding homeobox 1(ZEB1).Methods The surgical resection of EOC cancer tissues and paired adjacent normal tissues were collected.SKOV3 cells were divided into the NC mimic group(transfected with NC mimic),miR-508-3p mimic group(transfected with miR-508-3p mimic),si-NC group(transfected with si-NC),si-ZEB1 group(transfected with si-ZEB1)and co-transfection group(co-transfected with si-ZEB1 and miR-508-3p mimic).The mRNA expression levels of miR-508-3p and ZEB1 in EOC cancer tissues,adjacent normal tissues and five groups of cells were measured by real-time quantitative polymerase chain reaction.The Transwell assay was used to detect the cell migration and invasion abilities.Results The relative expression levels of miR-508-3p in EOC tissues and adjacent normal tissues were 0.77±0.36 and 1.07±0.40,the relative expression levels of ZEB1 mRNA in EOC tissues and adjacent normal tissues were 2.10±1.21 and 1.29±0.95,and the differences were statistically significant(all P＜0.01).The migration cell number of the NC mimic,miR-508-3p mimic,si-NC,si-ZEB1 and co-transfection groups was 633.00±32.49,319.20±19.89,650.40±25.85,375.00±17.25 and 129.40±17.10;the invasion cell number was 527.20±25.01,288.60±16.68,520.00±25.83,293.40±18.37 and 76.60±8.76;the relative expression levels of miR-508-3p were 1.05±0.37,3.94±1.21,1.01±0.21,1.26±0.34 and 3.40±0.41;the relative expression levels of ZEB1 mRNA were 1.00±0.04,0.58±0.05,1.00±0.08,0.54±0.07 and 0.29±0.03,respectively.The above indicators showed statistically significant differences between the miR-508-3p mimic group and the NC mimic group,between the si-NC group and the co-transfection group(P＜0.01,P＜0.05).Conclusion MiR-508-3p is lowly expressed in EOC cancer tissue,and it may inhibit the migration and invasion of ovarian cancer cells by targeting ZEB1 expression.

Objective:Exploring the role and mechanism of CHMP4C in regulating necroptosis during gastric can-cer development and progression.Method:The expression of CHMP4C in pan-cancer was analyzed by bioinformatics methods,and the expression of CHMP4C was detected in human normal gastric epithelial cells and GC cell lines by RT-qPCR and Western blot.Overexpression or knockdown of CHMP4C was performed in GC cell lines,and the effects of CHMP4C on the growth and proliferation of GC cells were detected using CCK-8 and clone formation assays.The CCK-8 experiment and Hoechst/PI double staining experiment were used to detect the changes in GC cell mortality and PI positive cell ratio after treatment with the necroptsis inducer TSZ or inhibitor necrostatin-1(Nec-1).Western blot assay was used to detect the protein and phosphorylation levels of RIPK1,RIPK3,and MLKL in GC cells.Result:CHMP4C was upregulated in GC tissues and cells.The CCK-8 and clone formation experiments showed that overex-pression of CHMP4C significantly improved the proliferation ability and colony formation efficiency of GC cells,while knockdown of CHMP4C significantly weakened GC cells.Moreover,the results of CCK-8 and Hoechst 33342/PI double staining experiments showed that upregulated CHMP4C could inhibit TSZ induced GC cell death;Nec-1 can reverse the decrease in GC cell viability caused by CHMP4C knockdown.Western blot experiment showed that the levels of p-RIPK1,p-RIPK3,and p-MLKL were significantly decreased in overexpressing cells,while they were increased in knockdown cells.After treatment with Nec-1,the expression levels of these three proteins decreased in knockdown cells.Conclusion:CHMP4C may promote GC progression by negatively regulating necroptosis through inhibiting the phosphorylation of the RIPK1/RIPK3/MLKL signaling pathway,suggesting that it is expected to be a potential target for GC therapy.