Objective To investigate the effects of simvastatin mediated adenylate activated protein kinase/peroxisome proliferator-activated receptor-γ-coactivator 1 α(AMPK/PGC-1α)pathway on neural function in rats with Parkinson's disease.Methods Parkinson's disease model was established in SD rats.After successful modeling,they were divided into model group,positive group(1.67 mg·kg-1 metoba),experimental-L group(10 mg·kg-1 simvastatin),experimental-H group(20 mg·kg-1 simvastatin),BML-275 group(20 mg·kg-1 simvastatin+0.25 mg·kg-1 AMPK inhibitor BML-275)and 10 normal rats were selected as control group.Enzyme-linked immunosorbent assay(ELISA)was used to detect dopamine(DA),3,4 dihydroxyphenylacetic acid(DOPAC),homovanillic acid(HVA),5-hydroxyindoleacetic acid(5-HIAA),5-hydroxytryptamine(5-HT);Western blot was used to detect the expression of tyrosine hydroxylase(TH)and AMPK/PGC-1α pathway-related proteins;TH expression was detected by immunohistochemistry,malondialdehyde(MDA),superoxide dismutase(SOD)and glutathione peroxidase(GSH-Px)were detected by kit.Results The DA of control group,model group,experimental-H group and BML-275 group were(495.63±34.30),(207.53±24.10),(429.39±44.89)and(285.55±20.79)pg·mL-1,respectively;DOPAC were(33.38±2.48),(17.70±1.31),(29.12±1.72)and(20.67±1.45)ng·mL-1,respectively;HVA were(58.75±6.25),(25.27±2.00),(46.16±2.83)and(30.58±1.91)ng·mL-1,respectively;5-HT were(5.62±0.45),(2.37±0.13),(4.42±0.26)and(3.23±0.29)ng·mL-1,respectively;5-HIAA were(11.11±1.08),(3.88±0.30),(7.99±0.63)and(6.04±0.51)ng·mL-1,respectively;p-AMPK protein expression were 0.98±0.06,0.35±0.04,0.80±0.05 and 0.21±0.02,respectively;PGC-1α protein expression were 1.12±0.11,0.40±0.04,0.90±0.08 and 0.58±0.05,respectively.There were statistically significant differences in the above indexes between control group and model group,and between model group and experimental-H group and inhibitor group(all P＜0.05).Conclusion Simvastatin can improve the neural function of Parkinson's disease rats by regulating AMPK/PGC-1α pathway.

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 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.

OBJECTIVE: To predict the trends for fine-scale spread of Oncomelania hupensis based on supervised machine learning models in Shanghai Municipality, so as to provide insights into precision O. hupensis snail control. METHODS: Based on 2016 O. hupensis snail survey data in Shanghai Municipality and climatic, geographical, vegetation and socioeconomic data relating to O. hupensis snail distribution, seven supervised machine learning models were created to predict the risk of snail spread in Shanghai, including decision tree, random forest, generalized boosted model, support vector machine, naive Bayes, k-nearest neighbor and C5.0. The performance of seven models for predicting snail spread was evaluated with the area under the receiver operating characteristic curve (AUC), F1-score and accuracy, and optimal models were selected to identify the environmental variables affecting snail spread and predict the areas at risk of snail spread in Shanghai Municipality. RESULTS: Seven supervised machine learning models were successfully created to predict the risk of snail spread in Shanghai Municipality, and random forest (AUC = 0.901, F1-score = 0.840, ACC = 0.797) and generalized boosted model (AUC= 0.889, F1-score = 0.869, ACC = 0.835) showed higher predictive performance than other models. Random forest analysis showed that the three most important climatic variables contributing to snail spread in Shanghai included aridity (11.87%), ≥ 0 °C annual accumulated temperature (10.19%), moisture index (10.18%) and average annual precipitation (9.86%), the two most important vegetation variables included the vegetation index of the first quarter (8.30%) and vegetation index of the second quarter (7.69%). Snails were more likely to spread at aridity of < 0.87, ≥ 0 °C annual accumulated temperature of 5 550 to 5 675 °C, moisture index of > 39% and average annual precipitation of > 1 180 mm, and with the vegetation index of the first quarter of > 0.4 and the vegetation index of the first quarter of > 0.6. According to the water resource developments and township administrative maps, the areas at risk of snail spread were mainly predicted in 10 townships/subdistricts, covering the Xipian, Dongpian and Tainan sections of southern Shanghai. CONCLUSIONS Supervised machine learning models are effective to predict the risk of fine-scale O. hupensis snail spread and identify the environmental determinants relating to snail spread. The areas at risk of O. hupensis snail spread are mainly located in southwestern Songjiang District, northwestern Jinshan District and southeastern Qingpu District of Shanghai Municipality.
Animals ; Bayes Theorem ; China/epidemiology* ; Ecosystem ; Gastropoda ; Supervised Machine Learning

Since 2015 when the transmission of schistosomiasis was controlled in China, the country has been moving towards elimination of schistosomiasis, with the surveillance-response as the main interventions for schistosomiasis control. During the period of the 13th Five-Year Plan, the transmission of schistosomiasis had been interrupted in four provinces of Sichuan, Jiangsu, Yunnan and Hubei and the prevalence of schistosomiasis has been at the historically lowest level in China. As a consequence, the goal set in The 13th Five-Year National Schistosomiasis Control Program in China is almost achieved. However, there are multiple challenges during the stage moving towards elimination of schistosomiasis in China, including the widespread distribution of intermediate host snails and complicated snail habitats, many types of sources of Schistosoma japonicum infections and difficulty in management of bovines and sheep, unmet requirements for the current schistosomiasis control program with the currently available tools, and vulnerable control achievements. During the 14th Five-Year period, it is crucial to consolidate the schistosomiasis control achievements and gradually solve the above difficulties, and critical to provide the basis for achieving the ultimate goal of elimination of schistosomiasis in China. Based on the past experiences from the national schistosomiasis control program and the challenges for schistosomiasis elimination in China, an expert consensus has been reached pertaining to the objectives, control strategy and measures for The 14th Five-Year National Schistosomiasis Control Program in China, so as to provide insights in to the development of The 14th Five-Year National Schistosomiasis Control Program in China.

Studies have found that metformin is not only the preferred drug for lowering blood sugar, but also shows lipid-lowering and weight-loss effects. The purpose of this study was to use a hyperlipidemia hamster model to investigate the lipid-lowering effect of metformin and its effect on important metabolic pathways in lipid metabolism disorders. Fifty golden hamsters were divided into a control group, a model group, metformin high- and low-dose groups, and a simvastatin group. A high-fat diet was fed for 1 week to create the model, and then drug was administered for 11 weeks with the high-fat diet. Serum was taken for measurement of blood lipid and blood glucose at 2, 6, and 9 weeks after administration, and at weeks 3, 5, and 9 feces and urine were collected for ¹H NMR metabolomics tests. After 11 weeks of intravenous injection of [U-¹³C₆] glucose, serum was collected for a ¹³C NMR metabolic flux test. The results showed that the administration of metformin can significantly reduce blood lipids and glucose levels and can significantly affect metabolic pathways such as sugar metabolism, lipid metabolism, ketone metabolism, amino acid metabolism, and intestinal flora metabolism. The results of the metabolic flux analysis showed that the high-fat diet reduced the metabolism of tricarboxylic acids by 37.48%. After administration of low and high doses of metformin the metabolism of tricarboxylic acid increased by 98.14% and 143.10%, respectively. After administration of simvastatin tricarboxylic acid metabolism increased by 33.18%. The results indicate that metformin has a significant effect on promoting energy metabolism. This study used a combination of metabolomics and metabolic flow to explore the effect of metformin on lipid metabolism disorders and quantifies changes in the key pathway of energy metabolism-the tricarboxylic acid cycle. This study provides useful information for the study of the efficacy and mechanism of metformin, as well as a practical technical method for the screening of lipid-lowering drugs based on a hamster model.

Heart failure is the end stage of many cardiovascular diseases. It seriously affects the safety and quality of life of nearly 40 million people worldwide. At present, the clinical and pathophysiological characteristics of some types of heart failure are unknown, and there is no effective diagnosis and treatment. In recent years, genomics, transcriptomics, epigenomics, proteomics, metabolomics and other omics technologies have been widely used in disease research, providing new opportunities for the prevention, diagnosis and treatment of diseases. These strategies have also brought hope for the reduction in heart failure mortality. Based on the current status of clinical treatment of heart failure, this article reviews the roles and potential applications of these various omics technologies and their opportunities in the study of the pathogenesis of heart failure, clinical diagnosis and treatment, and related drug pharmacodynamics and mechanism of action.