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 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.

Objective To explore the correlation between smoking,light to moderate alcohol consumption and cognitive function in elderly men in the community.Methods One thousand two hundred one elderly men(excluding heavy drinkers)from the Chinese longitudinal aging cohort database were selected and divided into smoking and drinking group(n=332),non-smoking but drinking group(n=126),smoking but non-drinking group(n=308),and non-smoking and non-drinking group(n=435)based on self-provided smoking and drinking information.Cognitive function was evaluated using the Beijing version of the Montreal cognitive assessment(MoCA).A two factor ANOVA and a multiple factor linear regression model were used to analyze differences in cognitive function,and risk factors for cognitive decline,respectively.Results The main effect analysis indicated that light to moderate alcohol consumption had a statistically significant impact on MoCA total score(F=6.076,P=0.014),MoCA naming(F=1.179,P=0.001),and MoCA abstraction(F=7.718,P=0.006).Light to moderate drinkers had lower MoCA total score(22.50±5.27 vs.23.30±5.28),MoCA naming(2.41±0.85 vs.2.58±0.76),and MoCA abstraction(0.93±0.84 vs.1.10±0.82)compared to non-drinkers.The main effects of smoking on MoCA total score(F=0.234,P=0.628),MoCA naming(F=0.110,P=0.741),and MoCA abstraction(F=1.335,P=0.248)were not significant.There was no interaction between smoking and light to moderate alcohol consumption on MoCA score(P>0.05).The results of multiple factor linear regression analysis showed a positive correlation(B=0.125,P=0.008)between no history of light to moderate alcohol consumption and MoCA naming.A stratified analysis of non-dementia individuals showed a positive correlation between a history of light to moderate alcohol consumption and MoCA total score(B=0.550,P=0.011)and MoCA naming(B=0.134,P=0.002).Conclusion Smoking and light to moderate alcohol consumption have no significant mutual effect on cognitive function in elderly men in the community,while light to moderate alcohol consumption may be associated with the impairments in global cognitive and naming functions.

Objective:To investigate the plasma differential protein expressions between patients with Alzheimer's disease (AD) and normal controls, and to search plasma protein markers or protein combinations with screening or diagnostic significance.Methods:Plasma samples from 98 patients with dementia of Alzheimer type (DAT), 102 patients with mild cognitive impairment (MCI) and 101 normal controls (NC) were collected from Wuxi Mental Health Center and Shanghai Mental Health Center from 2016 to 2018.The expression levels of 50 kinds of plasma proteins in all plasma samples were detected by Milliplex MAP assays(xMAP).Analysis of variance, regression analysis, discriminant analysis, and ROC analysis on the data were performed using SPSS 20.0 software.Results:(1)Compared with the NC group, 26 plasma proteins were up-regulated and 4 proteins were down-regulated in DAT group, while 6 proteins were up-regulated and 4 proteins were down-regulated in MCI group(all P<0.05).Compared with the NC group, 6 proteins were upregulated in both MIC group and DAT group, which were clusterin(Clust) (613.41(278.89), 761.76(358.60), 473.01(321.73)), cystatin C(Cys C) (691.88(441.34), 852.28(551.75), 548.64(545.28)), transthyretin(TTR) (207.10(168.60), 220.95(151.20), 152.89(162.70)), complement factor H(Com FH) (331.67(218.37), 361.69(124.64), 225.79(236.82)), soluble intercellular adhesion molecule-1(sICAM1) (109.30(49.47), 137.21(50.36), 87.06(57.59), and apolipoprotein E(APOE) (79.33(78.13), 79.31(68.85), 54.88(67.34)).The serum amyloid P component(SAP) was downregulated in both DAT and MCI groups(121.23(311.31), 92.39(156.62), 125.00(242.82)) compared with NC group.(2)Three sets of protein combination were screened by differential analysis, regression analysis, and discriminant analysis, including 8 proteins, 9 proteins and 7 proteins, respectively.And SAP, angiotensin (AGT), osteopontin (OPN), and complement C4 (Com C4) were the compared with NC group most frequently selected protein.The screening correct rate of three protein combinations were respectively 67.4%-71.4% for AD, 82.4%-88.4% for DAT, and 60.6%-63.5% for MCI. Conclusions:A variety of plasma proteins such as Clust, Cys C, TTR, Com FH, sICAM1, APOE are upregulated, while SAP is downregulated in AD patients.These differential protein combinations can help with early diagnosis of dementia with Alzheimer type.SAP, AGT, OPN and Com C4 may be potential markers for early screening or diagnosis of AD.

BACKGROUND:Rapid developments in the field of bioinformatics have provided new methods for the diagnosis of osteoarthritis.Artificial neural networks have powerful data computing and classification capabilities,which have shown better performance in disease diagnosis. OBJECTIVE:To establish a new diagnostic predictive model of osteoarthritis based on artificial neural network and to verify the diagnostic value of the model in osteoarthritis with an external dataset. METHODS:The eligible osteoarthritis-related data sets were downloaded through GEO database search and divided into Train group and Test group.The gene expression matrix of the Train group was analyzed to screen the differentially expressed genes.GO and KEGG enrichment analyses were performed on the differentially expressed genes.Through Lasso regression model,support vector machine model and random forest tree model,the key genes of osteoarthritis were further identified from the differentially expressed genes.The R software"Neuralnet"package was then used to construct the osteoarthritis diagnosis model based on artificial neural network,and the model performance was evaluated by the five-fold cross-validation.Two independent data sets in the Test group were used to verify their diagnostic results. RESULTS AND CONCLUSION:A total of 90 differentially expressed genes related to osteoarthritis were obtained by differential analysis,of which 33 were down-regulated and 57 were up-regulated.GO enrichment analysis showed that the differentially expressed genes were mainly involved in the following biological processes,including leukocyte-mediated immunity,leukocyte migration in bone marrow and chemokine production.KEGG enrichment analysis showed that these genes were mainly enriched in rheumatoid arthritis,interleukin-17 signaling pathway and osteoclast differentiation pathway.Five key genes for the diagnosis of osteoarthritis,HMGB2,GADD45A,SLC19A2,TPPP3 and FOLR2,were identified by three machine learning methods.The artificial neural network model of five key genes in the Train group showed that the accuracy was 96.36%and the area under the curve was 0.997.The five-fold cross validation of the neural network model showed that the average area under the curve was greater than 0.9 and the model was of robustness.Two independent data sets in the Test group showed its area under the curve was 0.814 and 0.788 respectively.Therefore,the establishment of an artificial neural network model for the diagnosis of osteoarthritis has a certain diagnostic value.

Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2018 to December 2019. Antibiotic susceptibility tests were conducted with agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 14 778 bacterial strains were collected from 50 hospitals, of which 4 117 (27.9%) were Gram-positive bacteria and 10 661(72.1%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.2%), Klebsiella pneumoniae (17.0%), Staphylococcus aureus (9.7%), coagulase-negative Staphylococci (8.7%), Pseudomonas aeruginosa (3.7%), Enterococcus faecium (3.4%), Acinetobacter baumannii(3.4%), Enterobacter cloacae (2.9%), Streptococci(2.8%) and Enterococcus faecalis (2.3%). The the prevalence of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus were 27.4% (394/1 438) and 70.4% (905/1 285), respectively. No glycopeptide-resistant Staphylococcus was detected. More than 95% of S. aureus were sensitive to amikacin, rifampicin and SMZco. The resistance rate of E. faecium to vancomycin was 0.4% (2/504), and no vancomycin-resistant E. faecalis was detected. The ESBLs-producing rates in no carbapenem-resistance E. coli, carbapenem sensitive K. pneumoniae and Proteus were 50.4% (2 731/5 415), 24.6% (493/2001) and 35.2% (31/88), respectively. The prevalence of carbapenem-resistance in E. coli and K. pneumoniae were 1.5% (85/5 500), 20.6% (518/2 519), respectively. 8.3% (27/325) of carbapenem-resistance K. pneumoniae was resistant to ceftazidime/avibactam combination. The resistance rates of A. baumannii to polymyxin and tigecycline were 2.8% (14/501) and 3.4% (17/501) respectively, and that of P. aeruginosa to carbapenem were 18.9% (103/546). Conclusions:The surveillance results from 2018 to 2019 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while E. coli was the most common pathogen, and ESBLs-producing strains were in majority; the MRSA incidence is getting lower in China; carbapenem-resistant E. coli keeps at a low level, while carbapenem-resistant K. pneumoniae is on the rise obviously.

Objective:To investigate the bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China.Methods:The clinical bacterial strains isolated from blood culture were collected during January 2020 to December 2020 in member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS). Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical Laboratory Standards Institute(CLSI, USA). WHONET 5.6 was used to analyze data.Results:During the study period, 10 043 bacterial strains were collected from 54 hospitals, of which 2 664 (26.5%) were Gram-positive bacteria and 7 379 (73.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (38.6%), Klebsiella pneumoniae (18.4%), Staphylococcus aureus (9.9%), coagulase-negative Staphylococci (7.5%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.3%), Enterobacter cloacae (2.8%), Enterococcus faecalis (2.6%), Acinetobacter baumannii (2.4%) and Klebsiella spp (1.8%). The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus aureus were 27.6% and 74.4%, respectively. No glycopeptide- and daptomycin-resistant Staphylococci were detected. More than 95% of Staphylococcus aureus were sensitive to rifampicin and SMZco. No vancomycin-resistant Enterococci strains were detected. Extended spectrum β-lactamase (ESBL) producing Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis were 48.4%, 23.6% and 36.1%, respectively. The prevalence rates of carbapenem-resistance in Escherichia coli and Klebsiella pneumoniae were 2.3% and 16.1%, respectively; 9.6% of carbapenem-resistant Klebsiella pneumoniae strains were resistant to ceftazidime/avibactam combination. The prevalence rate of carbapenem-resistance in Acinetobacter baumannii was 60.0%, while polymyxin and tigecycline showed good activity against Acinetobacter baumannii. The prevalence rate of carbapenem-resistance of Pseudomonas aeruginosa was 23.2%. Conclusions:The surveillance results in 2020 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen, and ESBL-producing strains declined while carbapenem-resistant Klebsiella pneumoniae kept on high level. The proportion and the prevalence of carbapenem-resistant Pseudomonas aeruginosa were on the rise slowly. On the other side, the MRSA incidence got lower in China, while the overall prevalence of vancomycin-resistant Enterococci was low.

Alzheimer's disease (AD) is a degenerative disease of the central nervous system characterized by progressive cognitive and behavioral disorders.Clinical manifestations include memory impairment, aphasia, apraxia, impaired visual spatial function, executive power, decreased computing power, personality and behavior changes and so on.At present, the incidence of dementia is increasing year by year, causing a huge social burden, and there is still no effective treatment.Therefore, many scholars try to prevent and delay the occurrence of cognitive impairment through the identification and control of risk factors.Combining with previous studies, nap is helpful for the maintenance and consolidation of memory.This article discusses the effect of nap on cognitive function and its related mechanisms.First, nap can improve cognitive function, but it depends on the length, the frequency of the nap, and the difficulty of the task.Second, the effect of nap on cognition may be through inflammatory response, neuroendocrine, Aβ and gene polymorphism.In addition, this paper also proposes future research prospects in terms of standardized research methods, deepening research on relevant mechanisms, and lifestyle interventions in view of the lack of previous research.

Objective:To evaluate the value of visual analysis and standardized uptake value ratio (SUVR) during 18F-florbetapir (AV45) PET/CT brain imaging in diagnosis of β-amyloid (Aβ) deposition in patients with mild cognitive impairment (MCI) and Alzheimer′s disease (AD), and to explore the clinical ancillary value of the two indexes. Methods:From December 2018 to July 2019, a total of 47 subjects, including 5 (3 males, 2 females, age (58±13) years) normal controls (NC), 8 (2 males, 6 females, age (66±10) years) patients with AD and 34 (16 males, 18 females, age (70±7) years) patients with MCI were enrolled. All subjects underwent 18F-AV45 PET/CT scan. All images were evaluated by visual analysis and SUVR were calculated. The diagnostic efficiencies of visual analysis and SUVR were compared by McNemar test and Kappa test. One-way analysis of variance and Welch test were used to compare data differences. The best threshold value of SUVR was obtained by receiver operating characteristic (ROC) curve analysis. Results:The positive rate of Aβ deposition for all subjects was 46.81%(22/47) by SUVR analysis, and 38.30%(18/47) by visual analysis. There was no significant difference between the two methods ( χ2=33.15, P>0.05), and the consistency was good ( Kappa=0.83). Considering the clinical diagnosis as the"gold standard", the Aβ deposition obtained by visual analysis and SUVR analysis can effectively distinguish AD from NC, and the sensitivities were 7/8 vs 8/8, respectively, both specificities were 5/5( χ2=9.48, P>0.05), with good consistency ( Kappa=0.84). SUVR quantitative analysis could distinguish AD from NC, AD from MCI ( F values: 3.99-8.79, all P<0.01), but could not distinguish NC from MCI (all P>0.05). ROC curve analysis showed that the best threshold value of precuneus′ SUVR was 1.08 for the differential diagnosis of AD and NC; for the differential diagnosis of AD and MCI, the best threshold value of lateral temporal′s SUVR was 1.06. Conclusion:Visual analysis was consistent with SUVR′s qualitative determination during 18F-AV45 PET/CT imaging for brain Aβ deposition, while SUVR quantitative analysis could assist in the differential diagnosis of AD and NC, AD and MCI.

ObjectiveTo study the metastructure volumes of medial temporal lobe in diagnosis the patients with Alzheimer's disease (AD) using 3 dimensional MRI.Methods23 AD patients according to DSM-Ⅳ criteria and 23 normal controls (NC) were examined with 3D-MRI.Hippocampus formation,amygdala,entorhinal cortex ( EC ),perirhinal cortex ( PC),and comu temporale were measured with 3D-MRI.ResultsSensitivity and specificity of diagnosis AD were 73.9％,97％ ( Hippocampus formation) ;39.1％,95.7％ (amygdala) ;73.9％,95.7％ (EC) ;95.7％,87.0％ (PC) and 34.8％,39.1％ ( cornu temporale).Overall discriminate function =cornu temporal × 3.887 + PC × 5.960 - EC × 0.074 + amygdale × 3.489 + hippocampus formation × 6.656- 22.449.Over-all-accuracy was 91.3％.ConclusionThe total volume of PC can better diagnosis the mild to moderate AD than other structure of medial temporal lobe.The changes of the medial temporal lobe volume could be used in diagnosis the patients with Alzheimer's disease.