OBJECTIVE To investigate the production of AmpC enzyme and ESBLs in Gram-negative bacilli and their drug-resistance to provide basis for reasonable use of antibiotics in clinical practice.METHODS All bacteria were identified by VITEK-32 system and disk test.RESULTS The main five strains of all 184 Gram-negative bacilli were Pseudomonas aeruginosa(24.4%),Acinetobacter baumannii(19.3%),Enterobacter cloacae(14.8%),Escherichia coli(10.2%) and Klebsiella pneumoniae(9.7%).The AmpC enzyme-producing rate was 53.8% and 14.7% in E.cloacae and A.baumannii the ESBLs-producing rate was 35.3%(12/34) and 15.4%(4/26) in A.baumannii and E.cloacae.P.aeruginosa was sensitive to imipenem and the drug-resistance rate of K.pneumoniae was 0%.CONCLUSIONS ESBLs and AmpC enzymes are important mechanisms of the drug-resistance of Gram-negative bacilli.

OBJECTIVE To explore the clinical distribution and drug resistance of extended-spectrum ?-lactamases(ESBLs) producing Enterobacter cloacae.METHODS The clinical distribution and drug resistance of 73 strains of E.cloacae and ESBLs producing E.cloacae identified in our hospital from Jan 2002 to Jan 2004 were analyzed.RESULTS Among them,the highest detectable rate was in respiratory department and from phlegm specimen.No ESBLs producing E.cloacae and non-(ESBLs) were resistant to imipenem;no non-ESBLs were resistant to cefepime,but some ESBLs producing E.cloacae was resistant to it;all ESBLs producing E.cloacae and non-(ESBLs) were resistant to ceftriaxone and amoxicillin/clavulanic acid.CONCLUSIONS E.cloacae is one of the(commonest) pathogens in nosocomial infection,and ESBLs producing E.cloacae has a high detectable rate,its drug resistance has increased;the clinic should choose antimicrobial agents rationally according to drug sensitive tests in vitro.

Objective:To evaluate the values of 18F-PI-2620 PET/CT brain imaging with SUV ratio (SUVR) in the assessment of tau protein deposition in the brain of patients with different cognitive disorders and its correlation with cognition. Methods:This was a cross-sectional study. From December 2019 to November 2022, a total of 67 subjects including 54 patients with Alzheimer′s disease (AD; 21 males, 33 females, age (68.6±7.8) years), 7 patients with mild cognitive impairment (MCI; 1 male, 6 females, age (63.1±11.2) years) and 6 healthy controls (HC; 4 males, 2 females, age (69.0±5.8) years) were enrolled retrospectively in Renji Hospital. All participants were examined by 18F-PI-2620 PET/CT. SUVRs of brain regions were obtained, including frontal lobe, temporal lobe, occipital lobe, parietal lobe, insular lobe, whole brain, as well as 10 independent brain ROIs (amygdala, orbitofrontal cortex, cingulate gyrus, superior occipital gyrus, superior parietal gyrus, inferior angular gyrus, precuneus, inferior temporal gyrus, entorhinal cortex and parahippocampal gyrus), with inferior cerebellum cortex as the reference region. All participants were estimated by cognitive scales(mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA)). One-way analysis of variance and the least significant difference t test were used to compare the differences of SUVR in each brain region among HC, MCI and AD groups. ROC curve analysis was used to determine the optimal cut-off values of SUVR in each brain region for the differential diagnosis of AD-MCI and AD-HC. Pearson correlation analysis was employed to examine the correlations of SUVR with cognitive scale scores. Results:The SUVR of whole brain was 1.40±0.31 in AD group, 1.08±0.19 in MCI group, and 1.01±0.12 in HC group. SUVR analysis in the whole brain and each brain region could distinguish AD from HC, AD from MCI ( F values: 1.76-10.09, t values: 2.98-7.47, all P<0.05), but could not distinguish HC from MCI ( t values: 0.17-1.53, all P>0.05). ROC curve analysis showed that the best cut-off value of SUVR was 1.18 for whole brain (AUC=0.89), 1.13 for amygdala (AUC=0.94) and 1.26 for parahippocampal gyrus (AUC=0.94) for differential diagnosis of AD and HC, which was 1.06 for whole brain (AUC=0.82), 1.18 for amygdala (AUC=0.88) and 1.28 (AUC=0.88) for infratemporal gyrus to differential diagnosis of AD and MCI. SUVRs of the whole brain, frontal, occipital, parietal, temporal and insula were significantly negatively correlated with MMSE and MoCA cognitive scale scores ( r values: from -0.64 to -0.40, all P<0.05). Conclusions:SUVR quantitative analysis in 18F-PI-2620 PET imaging can assist the differential diagnosis of AD and HC, AD and MCI. The SUVRs of whole brain and five lobes show negative correlations with MMSE and MoCA scores.

Objective:To assess the diagnostic efficiency of 18F-FDG PET for Alzheimer′s disease (AD) in patients with memory impairment. Methods:A retrospective analysis was conducted on 96 patients (40 males, 56 females, age: 69.0(62.8, 74.0) years) initially diagnosed with memory impairment in Renji Hospital, School of Medicine, Shanghai Jiao Tong University between August 2019 and September 2023. The amyloid-tau-neurodegeneration (ATN) criteria, based on 18F-AV45+ 18F-PI-2620 PET/CT+ MRI imaging results, were used as the diagnostic standard for AD. Visual analysis (temporoparietal or posterior cingulate cortex (PCC) hypometabolism) and semi-quantitative analysis methods (PET-SCORE and NeuroQ software analysis (SUV ratio, SUVR)) were applied to evaluate the diagnostic efficiency of 18F-FDG PET imaging for AD. Diagnostic efficiencies of visual assessment and semi-quantitative parameters were compared by χ2 test. Additionally, Pearson correlation analysis was performed to examine the relationship between results of PET-SCORE and cognitive scales. Results:Of the 96 patients initially diagnosed with memory impairment, 61 were clinically diagnosed with AD, while 35 were non-AD patients. Visual assessment of temporoparietal hypometabolism showed the highest sensitivity (91.80%, 56/61), which was significantly different from the sensitivities of PET-SCORE (40.98%(25/61); χ2=29.03, P<0.001) and visual assessment of PCC hypometabolism (77.05%(47/61); χ2=5.82, P=0.016). While semi-quantitative assessment using PET-SCORE demonstrated the highest specificity (100%, 35/35), which was significantly different from the specificities of visual assessment methods (temporoparietal hypometabolism: 17.14%(6/35), χ2=27.03, P<0.001; PCC hypometabolism: 54.29%(19/35), χ2=14.06, P<0.001). PET-SCORE exhibited statistically significant correlations with Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Activities of Daily Living (ADL) scores ( r values: -0.38, -0.36, 0.31, all P<0.01). Conclusions:Among patients initially diagnosed with memory impairment, visual assessment in 18F-FDG PET imaging analysis demonstrates higher sensitivity, while semi-quantitative analysis using PET-SCORE exhibits higher specificity. PET-SCORE shows statistically significant correlation with the severity of cognitive decline.